Large water bodies such as the Laurentian Great Lakes have significant influences on local and regional climate through their unique physical features. Due to the coarse spatial resolution of general circulation models (GCMs), the Great Lakes are geometrically ignored in most GCMs. Thus, the dynamical downscaling technique serves as a necessary and feasible solution to bridge the gap. The Weather Research and Forecasting model (WRF) with an updated lake scheme is employed to downscale from a GCM, GFDL-CM3. The WRF-Lake’s performance is evaluated against observations, the GCM, as well as 23 other GCMs. Results show that the coupled air-lake model, with a fine spatial resolution and realistic lake bathymetries, reproduced a more reasonable spatiotemporal climatology than GCMs, as well as the lake-induced characteristics that were missed in GCMs. With lakes present, the seasonal variability of air temperature was reduced in WRF-Lake relative to GFDL-CM3, especially in summer. A reduced air temperature trend, about 4.5 °C/100 year in the 21st century, was projected in WRF-Lake. The seasonal evolutions of lake surface temperature and lake ice coverage were well captured by the lake model. The lake surface temperature was projected to be warming by 3.5-4 °C and the lake ice diminishing by 58.9% - 86%. Those results brought by the WRF-Lake model suggest that a fine resolution of the topography and the incorporation of the lake-atmosphere interactions are crucial to improve the understanding of the climate and climate change in the Great Lakes region.

Lake Rawapening, Semarang Regency, Indonesia, has incorporated a holistic plan in its management practices. However, despite successful target achievements, some limitations remain that a review of its management plan is needed. This paper identifies and analyzes existing lake management strategies as a standard specifically in Lake Rawapening by exploring various literature, both legal frameworks and scholarly articles indexed in Google Scholar and published in Water by MDPI about lake management in many countries. There are two major types of lake management, namely pillar-based and object-based. While the former is the foundation of a conceptual paradigm that does not comprehensively consider the roles of finance and technology in the lake management, the latter indicates the objects to manage so as to create standards or benchmarks for the implementation of various programs. Overall, Lake Rawapening management should include more programs on erosion-sedimentation control and monitoring of operational performance using information systems.

Inland lake variations are considered sensitive indicators of global climate change. However, human activity is playing as a more and more important role in inland lake area variations. Therefore, it is critical to identify whether anthropogenic activity or natural event is playing as the dominant factor in inland lake surface area change. In this study, we proposed a Douglas-Peucker simplification algorithm and bend simplification algorithm combined method to locate major lake surface area disturbances; these disturbances were then characterized to extract the time series change features according to documented records; and the disturbances were finally classified into anthropogenic or natural. We took the nine lakes in Yunnan Province as test sites, a 31 years long (from 1987 to 2017) time series Landsat TM/OLI images and HJ-1A/1B used as data sources, the official records was used as references to aid the feature extraction and disturbance identification accuracy. Results of our method for both disturbance location and the disturbance identification could be concluded as follows: 1) The method can accurately locate the main lake changing events based on the time series lake surface area curve. The accuracy of this model for segmenting the lake area time series curves in our study area was 95.24%. 2) Our proposed method achieved an overall accuracy of 91.67%, with F-score of 94.67 for anthropogenic disturbances and F-score of 85.71 for natural disturbances. 3) According to our results, lakes in Yunnan Provence, China, have undergone extensive disturbances, and the human-induced disturbances occurred almost twice as often as natural disturbances, indicating intensified disturbances caused by human activities. This inland lake area disturbance identification method is expected to uncover whether a disturbance to inland lake area is human activity-induced or natural event.

Plain lakes play a crucial role in the hydrological cycle of a watershed, but their interactions with adjacent rivers and downstream water bodies can create complex river-lake relationships, often leading to frequent flooding disasters. Taking Poyang Lake as an example, this paper delves into its interaction with the Yangtze River, revealing the spatiotemporal patterns of flood propagation within the lake and its impact on surrounding flood control measures. The aim is to provide insights for flood management in similar environments worldwide. This study employs a comprehensive approach combining hydrological statistical analysis and two-dimensional hydrodynamic modeling, based on extensive hydrological, topographic, and socio-economic data. The results indicate that the annual maximum outflow from Poyang Lake is primarily controlled by floods within the watershed, while the highest annual lake water level is predominantly influenced by floods from the Yangtze River. The peak discharge typically reaches the lake outlet within 48 hours, with the peak water level taking slightly longer at 54 hours. However, water storage in the lake can shorten the time for the peak discharge to arrive. When converging with floods from the Yangtze River, the peak water level may be delayed by up to 10 days due to the top-supporting interaction. Furthermore, floods from the "Five Rivers" propagate differently within the lake, affecting various lake regions to differing degrees. Notably, floods from the Fu River cause the most significant rise in lake water level under the same flow rate. The top-supporting effect from the Yangtze River also significantly impacts the water surface slope of Poyang Lake. When the Yangtze River flood discharge far exceeds that of the "Five Rivers" (i.e., when the top-supporting intensity f value exceeds 4), the lake surface becomes as flat as a reservoir. During major floods in the watershed, the water level difference in the lake can increase dramatically, potentially creating a "dynamic storage capacity" of up to 840 million cubic meters.

A typical river-connected lake, Jinshan Lake, was selected as the study area. By the combination of field experiment, laboratory experiment and mathematical model, we plotted the relationship between the concentration of DCu-SCu and FDI, and constructed the mathematical model of the migration and transformation of HMCu in Jinshan Lake. We choose a typical diurnal tide to simulate and revealed the vertical migration characteristics of HMCu in Jinshan Lake during a diurnal tide. The results show that: (1) The release rate of DCu was proportional to FDI and background content, respectively. (2) Due to the nearby industrial enterprises and terrain characteristics, SA loads the most HMCu, the average concentration is 70.07mg/kg. According to the characteristics and geographical location of LC, the concentration of copper in the two states fluctuates greatly (DCu: 43.20~74.77 mg/kg, SCu: 53.63~74.67mg/kg). The fluctuation trend of SCu in ZA is significantly different from that in other areas, which mainly due to the complex hydraulic distribution and the sorption-desorption process of HMs in sediment particles. The hydraulic disturbance of JG is the least and relatively stable, which is the farthest from the inlet of the lake and is the least affected by the Yangtze river. (3) The FDI in a diurnal tide reaches the suspension condition of fine sediment particles in each region. FDI and sediment concentration on the vertical exchange of two - state Cu is significant.

Lake sediment records are of great importance for understanding the evolution of watershed environments. Various studies have been carried out to constrain the depositional ages of lake sediments and examine their physical, chemical, and biological characteristics, aiming to construct historical vegetation, environment and climate patterns in Chinese lake watersheds. In this study, we obtained relevant literature on lake sediment records by searching the key word 'age-depth' from the databases – Web of Science and China National Knowledge Infrastructure (CNKI, the largest Chinese academic database). We analyzed the literature based on its type (published in a Chinese/English journal or as a Master’s/PhD thesis), period of publication, journal (if published in a journal), key authors, study area, dating scale, and main aims. The results suggest that the lakes in the plateau regions are the most popular research topic typically covering 100–200 years (short-term) and 500–30,000 years (long-term). The literature focuses on a wide range of topics, from past environmental evolution in the watershed to lake ecology, and provides a solid foundation for better understanding regional climate change and the preservation of lake environments and ecosystems. In the future, resulting data from environmental reconstruction with lake sediments will be needed to integrate with emerging information processing technologies (e.g., artificial intelligence and meta-analysis), to disentangle the complex interplay between Earth surface processes and global climate change; furthermore, strengthening interdisciplinary collaboration will deepen our comprehension of man-land relationship and promote the sustainable management of lake ecosystems in the context of global climate change.

Lake Urmia in northwestern Iran is the largest lake in Iran and the second largest saltwater lake in the world. The water level in Lake Urmia has decreased dramatically in recent years, due to drought, climate change, and overuse of water resources for irrigation. This shrinking of the lake may affect local climate conditions, assuming that the lake itself affects the local climate. In this study, we quantified the lake’s impact on the local climate by analyzing hourly time series of data on climate variables (temperature, vapor pressure, relative humidity, evaporation, and dewpoint temperature for all seasons, and local lake/land breezes in summer) for the period 1961-2016. For this, we compared high quality, long-term climate data obtained from Urmia and Saqez meteorological stations, located 30 km and 185 km from the lake center, respectively. We then investigated the effect of lake level decrease on the climate variables by dividing the data into 1961-1995 (normal lake level) and 1996-2016 (low lake level). The results showed that at Urmia station (close to the lake), climate parameters displayed fewer fluctuations and were evidently affected by Lake Urmia compared with those at Saqez station. The effects of the lake on the local climate increased with increasing temperature, with the most significant impact in summer and the least in winter. The results also indicated that, despite decreasing lake level, local climate conditions are still influenced by Lake Urmia, but to a lesser extent.

This study assesses the performance of the Weather Research and Forecasting (WRF) model using a high-resolution spatial grid (1 km) with various combinations of physical parameterization packages to simulate a severe event in August 2021 in the southeastern Brazilian coast. After determining the optimal set of physical parameterizations for representing wind patterns during this event, a year-long evaluation was conducted, covering forecast horizons of 24, 48, and 72 hours. The simulation results were compared with observational wind data from four weather stations. The findings highlight variations in the efficacy of different physical parameterization sets, with certain sets encountering challenges in accurately depicting the peak of the severe event. The most favorable results were achieved using a combination of Tiedtke (cumulus), Thompson (microphysics), TKE (boundary layer), Monin-Obukhov (surface layer), Unified-NOAH (land surface), and RRTMG (shortwave and longwave radiation). Over the one-year forecasting period, the WRF model effectively represented the overall wind pattern, including forecasts up to three days in advance (72-hour forecast horizon). Generally, the statistical metrics indicate robust model performance, even for the 72-hour forecast horizon, with correlation coefficients consistently exceeding 0.60 at all analyzed points. While the model proficiently captured wind distribution, it tended to overestimate northeast wind speed and gust intensities. Notably, forecast accuracy decreased as stations approached the ocean, exemplified by the ATPM station.

A 3-month (June-August) regime of the year 2002 summer rainfall (JJA2002) was simulated with 30 physics combinations using the Weather Research and Forecasting (WRF) model at 12-km horizontal grid resolution. The objective is to examine summer rainfall sensitivity to parameterization of microphysical, convective, and boundary layer processes and identify the best possible combination of parameterization options that perform relatively better in simulating the spatial and temporal distribution of summer rains over Ethiopia. The WRF simulated rainfall was evaluated against station data and satellite rainfall products (CHIRPS and ENACTS) using mean absolute error, Pearson and Pattern correlation coefficients (PCC), pattern correlation, and error in a number of rainy days as evaluation metrics. Summer rainfall is found to be most sensitive to the choice of cumulus parameterization and least sensitive to cloud microphysics. All simulations captured the spatial distribution of mean seasonal precipitation with PCC ranging from 0.89-0.94. However, all simulations overestimated precipitation amount and number of rainy days. Out of the 30, the simulations that use a combination of Grell-3D cumulus scheme, ACM2 boundary layer, Lin Microphysics, Dudhai shortwave radiation, and RRTM longwave radiation scheme ranked the top and provided the most realistic simulation in terms of amount and spatio-temporal distribution of summer rainfall.

Dredging is a common technique for managing eutrophication problems in waters, reducing the accumulation of pollutants by removing sediments from the bottom of water bodies. However, dredging can cause complex impacts on lake ecosystems, and it is crucial to understand benefits and mechanisms for environments. In this paper, the dredged and undredged areas in the Caohai portion of Dianchi Lake were studied to analyze the effects of dredging on nitrogen-phosphorus transport and conversion and changes in nitrogen-phosphorus morphology content and its mechanisms by comparing the nitrogen-phosphorus morphology content, percentage; nitro-gen-phosphorus ratio, and release contribution of the two areas. It was found that the ratio of sta-bilized nitrogen (SN) to stabilized phosphorus (SP) in the dredged area was lower than that in the non-dredged area; the BD-P and TOC contents had a large turnaround at the 16-20 cm position of the sediment in the dredged area; and the main conclusions were that the dredging would disrupt the internal equilibrium of the lake system for many years, and in particular, it would have the greatest effect on the balance of the BD-P in the phosphorus forms of the sediment, and that the column cores of the dredged area from 0 to 16 cm might be newly accumulated sediments after the dredging project. However, with time, the distribution of nitrogen and phosphorus forms in the newly accumulated sediments will gradually reach a new equilibrium. In addition, dredging will also cause significant changes in the retention efficiency of nitrogen and phosphorus in the sediment, and the stable nitrogen and phosphorus forms will be released and transformed into unstable ni-trogen and phosphorus forms.

Pit lakes can represent significant liabilities at mine closure. However, pit lakes also present opportunities to provide significant regional benefit and address residual closure risks of both their own and overall project closure, and even offset the environmental costs of mining by creating new end uses. Unfortunately, many pit lakes have continued to be abandoned without repurposing for an end use. We reviewed published pit lake repurposing case studies of abandoned mine pit lakes. We found beneficial end use type and outcome varied dependent upon climate and commodity; but equally important social and political dynamics that manifest as mining company commitments or regulatory requirements. Many end uses have been realized: passive and active recreation, nature conservation, fishery and aquaculture, drinking and industrial water storage, greenhouse carbon fixation, flood protection and waterway remediation, disposal of mine and other waste, mine water treatment and containment, and education and research. Common attributes and reasons that led to successful repurposing of abandoned pit lakes as beneficial end uses are discussed. Recommendations are given for all stages of mine closure planning to prevent pit lake abandonment and to achieve successful pit lake closure with beneficial end uses.

A reliable flood early warning system must take into account the mechanisms that cause heavy precipitation events and accurate surface hydrology modeling. In this project, analysis of atmospheric processes and hydrological modelling of selected flood events over Dire Dawa is conducted using various observational/reanalysis data and uncoupled WRF-Hydro model simulations. To comprehend the processes causing such severe precipitation occurrences, large scale atmospheric fields linked to selected extreme precipitation events are examined using ERA5 reanalysis. The land surface was configured at 1 km resolution while 250 m sub-grid resolution was set to perform the routing process. Model forcing for the uncoupled WRF-Hydo model is obtained from ERA5 reanalysis data. Sensitivity of stream-flow simulation to various parameter values such as hydrolic conductivity and surface infiltration coefficient was carried out for August 2006. The result of the sensitivity experiment reveals that infiltration-runoff, hydrolic soil conductivity and saturated volumetric soil moisture with the parameter value of 0.1, 1.5 and 1.0, respectively are found to produce realistic spatial and temporal distribution of stream-flow. The extreme flood events of March 2005 and April 2007 were studied further to assess the performance of WRF-Hydro model and to understand the underlying atmospheric mechanisms causing these heavy precipitation events. The result of hydrological simulation demonstrated that uncoupled WRF-Hydro simulation reproduced both the temporal evolution and the spatial pattern reasonably well. Our analysis indicated that the amount of precipitation during these two events exceeded the long-term average by several factors, furthermore, the anomalies cover larger areas of eastern Ethiopia. Associated to these extreme events, upper level subtropical westerly jet-streams were anomalously stronger and also extended further southward favouring upper level divergence over the region. At lower level, the notable circulation anomalies include anomalous positive pressure anomaly over Sudan/Egypt leading to northerly flow anomaly over Red Sea, strengthening of southerly influx from southern Indian ocean due to stronger Mascarene High. The encouraging results from WRF-Hydro simulation suggest that this modelling framework can be implemented in operational context within national and regional forecasting centers as a key component to establish a flood monitoring and early warning system.

Storm Ophelia made landfall over Ireland as an extra-tropical storm on the morning of the 16th of October 2017. The storm caused major power outages, lifted roofs, caused coastal flooding in Ireland, and resulted in the loss of three lives. A model’s capability to forecast extreme weather events such as Storm Ophelia is of utmost importance and now with a changing climate, it becomes more important to improve and enhance model forecasting capability. The Weather Research and Forecasting (WRF) model V3.9 has been configured for the Irish domain and this study presents a preliminary evaluation of the Model during Storm Ophelia. Simulated wind speed and direction were compared with hourly remote sensing (lidar) and in-situ (wind speed and wind direction at 10m) observations at the coastal site of Mace Head Atmospheric Research Station on the West coast of Ireland (53.33◦ N, 9.90 49 ◦ W). The model simulation has generally small biases in the simulated wind speed and wind direction during this case study. The model also realistically simulated the magnitude and geographical distribution of the wind speed and wind direction observed during Ophelia.

This manuscript examines from the diurnal convection cycle (CDC) to the interdecadal variability in the region of the Peruvian Altiplano (RAP). Currently, estimating precipitation using satellites is an alternative which can be used to study the spatio-temporal evolution of precipitation systems. Herein CPC data Morphing technique - CMORPH (Joyce et al, 2004) was used between 2002 and 2014 to analyze the CDC in RAP. The CMOPRH data were compared with rainfall data series measured by rain gauges of meteorological stations (EMS) in the RAP. The results indicate that the CDC shows high variability in the Titicaca Basin and is associated with patterns of lake breeze (day), land breeze (night) and mountain - valley circulation. The CDC starts at 1800 HL (local time) in the northern region of Lake Titicaca, lasting between 2 h and 6 h, and most of 2000 HL. The CDC over the dry surface (ST) of Titicaca Basin starts early at around 1200 HL, lasting 4 h to 7 h, and maximum at 1800 HL.

Understanding the evolving hydrological characteristics of landslide-induced barrier lakes is crucial for flood control, forecasting, early warning, and safety measures in the reservoir area. This study examines the changes in hydrological characteristics of the Attabad landslide-dammed lake over the past decade after the occurrence of the landslide, focusing on lake area dynamics and sediment concentration. High-resolution satellite images from QuickBird, Pleiades, and WorldView2 over seven periods were analyzed. The findings indicate that the lake area has gradually decreased, with the center of mass shifting towards the lake dam, indicating a trend towards stability. The suspended sediment in the barrier lake is distributed in a strip running from north to south, then northeast to southwest, with sediment concentration decreasing from the lake entrance to the dam and from the lake bank to the center. Over time, the average sediment concentration has decreased from 2010 to 2020, with higher concentrations in summer than in winter. Notably, during the 2017-2020 period, the lower-middle parts of the lake experienced higher sediment concentration, while the dam area witnessed lower concentrations, thereby reducing the sediment impact on the dam.

This study examines the performance of the Indian Monsoon Data Assimilation and Analy-sis (IMDAA) in predicting five extremely severe cyclonic storms (ESCS) over the Bay of Bengal. The Advanced Research version of the WRF (ARW) model is utilized for this analysis over the last two decades. The initial and lateral boundary conditions are derived from the IMDAA datasets with a horizontal resolution of 0.12° × 0.12°. Five ESCSs from the past two decades are considered: Sidr 2007, Phailin 2013, Hudhud 2014, Fani 2019, and Amphan 2020. The model is integrated up to 96 hours using double nested domains of 12 km and 4 km. Model performance is evaluated using the 4 km results, compared with available observational datasets, including the best-fit data from the India Meteorological Department (IMD), The Tropical Rainfall Measuring Mission (TRMM) satellite, and Doppler Weather Radar (DWR). The results indicate that IMDAA provides accurate forecasts for ESCSs Fani, Hudhud, and Sidr in terms of track, intensity, and mean sea level pressure, aligning well with IMD observational datasets. However, Sidr's track deviates more from the observations. The calculated mean absolute maximum sustained wind speed errors range from 8.4 m/s to 10.6 m/s from day-1 to day-4, while mean track errors range from 114 km to 496 km during the same period. Statistical analysis, including bias, mean error, and standard deviation, underscores the significance of ESCS prediction. The discussion also covers rainfall prediction, maximum reflectivity, and the associated structure of the storms.

Radar observation data with high temporal and spatial resolution are used in the data assimilation experiment to improve precipitation forecast of a numerical model. The numerical model considered in this study is Weather Research and Forecasting (WRF) model with double-moment 6-class microphysics scheme (WDM6). We calculated radar equivalent reflectivity factor using higher resolution WRF and compared with radar observations in South Korea. To compare the precipitation forecast characteristics of three-dimensional variational (3D-Var) assimilation of radar data, four experiments are performed based on different precipitation types. Comparisons of the 24-h accumulated rainfall with Automatic Weather Station (AWS) data, Contoured Frequency by Altitude Diagram (CFAD), Time Height Cross Sections (THCS), and vertical hydrometeor profiles are used to evaluate and compare the accuracy. The model simulations are performed with and with-out 3D-VAR radar reflectivity, radial velocity and AWS assimilation for two mesoscale convective cases and two synoptic scale cases. The radar data assimilation experiment improved the location of precipitation area and rainfall intensity compared to the control run. Especially, for the two convective cases, simulating mesoscale convective system was greatly improved.

Turkana County's fisheries sector, which is entirely dependent on Lake Turkana, is vital to the county's economy. The Fisheries Sector in the County supports 1,500 households directly and 1,100 households indirectly. Despite its economic and social importance, the sector faces numerous challenges such as high post-harvest fish losses, uncoordinated development approaches, over-exploitation of some lake areas and weak links between research, management, and other sector players. Furthermore, since the start of devolution in 2013, the sector has been operating without an overall policy and legal framework. The primary goal of the study was to identify important challenges in the management of the fisheries sector in Turkana County that would lead the successful and coordinated growth of the fisheries industry. To capture their perspectives on the problems and potential in the usage of Lake Turkana's fisheries resources, semi-structured questionnaires and Key Informants interviews were used to collect primary data from the sector's fisheries actors. A total of 60 people were interviewed, and their responses were recorded in the Kobo Collect toolbox for later analysis. Secondary data was also gathered from numerous national policy declarations, guidelines, and legislation that have been used to manage Lake Turkana's fishery resources. The findings indicate that a policy directing the exploitation and development of fisheries is required in order to fully realize the potential of fisheries and aquaculture in the County. The development of the policy will lay a solid foundation for the creation of a legal framework to strengthen the sector in Turkana County, which is a necessary step toward achieving sustainable development and management of fisheries in accordance with national, regional, and international frameworks. By leveraging the role of the County Directorate of Fisheries and Beach Management Units in the sectors' monitoring, management, and development, the policy will also promote effective coordination of stakeholders at all levels.

In unicellular organisms, intracellular inclusions of amorphous calcium carbonate (ACC) have been initially described in cyanobacteria and, later, in unicellular eukaryotes of Lake Geneva (Switzerland/France). Inclusions in unicellular eukaryotes ‒named micropearls‒ consist of hydrated ACCs, frequently enriched in Sr or Ba, displaying internal oscillatory zonations due to variations in the Ba:Ca or Sr:Ca ratios. The analysis of our database consisting of 1597 micropearl analyses from Lake Geneva and 34 from Lake Titicaca (Bolivia/Peru) has shown that a certain number of Sr and Ba-enriched micropearls from these lakes contain As in amounts measurable by EDXS. A Q-mode statistical analysis has confirmed the existence of five geochemically distinct morpho-chemical groups of As-bearing micropearls, among which a new category identified in Lake Geneva, where As is often associated with Mg. This new type of micropearl is possibly produced in a small (7-12 m size) bi-flagellated organism. Micropearls from Lake Titicaca, which contain Sr, are found in an organism very similar to Tetraselmis cordiformis, observed in Lake Geneva. Lake Titicaca micropearls contain higher As concentrations which can be explained by the high As concentration in the water of this lake. The ubiquity of the biomineralization process observed points to the need for better understanding of the role of amorphous or crystalline calcium carbonates in As cycling in surface waters.

As the problem of air pollution becomes more urgent, the precise determination of the characteristics of air pollution and the associated mechanisms of transport of pollutants becomes an increasingly urgent task. The simulation results of the Copernicus Atmospheric Monitoring Service (CAMS) [18] were used as initial data sets. The area of the Crimean Peninsula (within coordinates 44.50 latitude, 33.50 longitude) in 23 - 26 January, 2019 was chosen for the study. That time concentrations of pollutants (aerosol particles with a diameter of 2.5 (PM2.5) and 10 micrometers (PM10)) steadily increased and reached the maximum value. Four kinds of meteorological data sets were used in the work. The first and second data sets were the global NCEP/NCAR and (ERA-5) re-analyses. The third and fourth meteorological data sets were obtained using the Weather tracking and Forecasting model (WRF) as domains on high-resolution grids: 9 km and 2 km. The analysis of meteorological data sets was carried out to analyze the nature of the air masses movement in the studied region. Using the HYSPLIT model simulation was carried out to determine area of the sources of negative impact. The emissions transfer from the supposed sources of negative impact on the Crimea region is analyzed. The sensitivity of simulation the inverse and direct trajectories of air masses transfer was studied based a set of simulation results. On the basis of HYSPLIT model the simulation was carried out separately using meteorological data sets having different spatial and temporal resolutions. In general, the simulation results allowed us to conclude that the HYSPLIT model in combination with high-resolution meteorological input data of the WRF model are good to identify the sources of possible negative effects on atmospheric air located at long distances from the study site.

Biogenic emission can have significant impact on atmospheric chemistry. Isoprene (C5H8) is known as the most predominant volatile organic compound and its emission is highly dependent on temperature and light (solar radiation). This study aims to investigate future changes of isoprene emission under climate change scenario. The Southeast Asia (SEA) region is home to 15% of the world’s tropical forest, and the biogenic emission from this region can have significant effect on the global climate chemistry. Three climate change scenarios (RCP4.5, RCP6.0 and RCP8.5) were used to drive climate change simulation in 2013 (baseline), 2030 (near-future), 2050 (mid-century), 2070 (post-mid) and 2100 (end of century) using the Weather Research Forecasting (WRF v3.9.1) model. The Model Emission of Gases and Aerosol from Nature (MEGAN v2.1) was then used to simulate isoprene fluxes using climate output datasets from the WRF model. This study highlights that the projected mean surface temperature and PAR (photosynthetic active radiation) were higher in July than in January. Towards the end of the century, the overall surface temperature and PAR over the SEA region is expected to increase by 0.9℃ - 2.1℃, and 7.6 W m-2 – 12 W m-2 under all RCPs. The all-time high isoprene emitters are Borneo and Papua Island. Meanwhile, the projected increment of isoprene emission over this region is between 10 – 14%, 15-30% and 29 – 53% for RCP4.5, RCP6.0 and RCP8.5, respectively. Our result concludes that the total isoprene emission was higher during July, consistent with the high surface temperature and PAR. The results also agreed with the hypothesis of high isoprene emission over the region that has oil palm plantation. Thus, challenges in dealing with future emissions of isoprene in SEA are closely tied to future climate policies to limit the warming of the atmosphere over this region and the land-use conversion of palm oil plantations.

Soil moisture modeling is necessary for many hydrometeorological and agricultural applications. One of the ways in which modeling of soil moisture (SM) can be improved is by assimilating SM observations to update the model states. Remotely sensed SM observations are prone to being riddled with data discontinuities, namely in the horizontal and vertical spatial, and temporal dimensions. A set of synthetic experiments were designed in this study to assess how much impact each of these individual components of spatiotemporal gaps can have on the modeling performance of SM as well as streamflow. Results show that not having root-zone SM estimates from satellite derived observations is most impactful in terms of modeling performance. Having temporal gaps and horizontal spatial gaps in the satellite SM data also impacts modeling performance, but to a lesser degree. Real-data experiments with the remotely sensed Soil Moisture Active Passive (SMAP) product generally brought improvements to the SM modeling performance in the upper soil layers, but not so much in the bottom soil layer. The updating of model SM states with observations also resulted in some improvements in the streamflow modeling performance during the synthetic experiments, but not during the real-data experiments.

Severe thunderstorms are often accompanied by strong vertical air currents, temporary wind gusts, and heavy rainfall. The development of this atmospheric phenomenon over tropical shallow water zones, such as bays, can lead to intensification of atmospheric disturbances and produce a small-scale storm surge. Here, the storm surge that occurred on 19 March 2017 in the Persian Gulf coastal area has been investigated. Air temperature, precipitation, mean sea level pressure, wave height, wind direction, wind speed, geopotential height, zonal components, meridional winds, vertical velocity, relative humidity, and specific humidity obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF (and Global Forecast System (FNL) were used to implement the Weather Research and Forecasting (WRF) model. The results showed that the main cause of the storm surge was the occurrence of a supercell thunderstorm over the Persian Gulf. The formation of this destructive phenomenon resulted from a downburst under Cumulonimbus cloud and high-velocity air subsidence, after collision with the sea surface coinciding with the high tide. This caused a severe, yet temporary, gust, which in turn caused the creation of the four waves of 3.1 m height along the coast of Bandar Dayyer.

The Himalayan region is facing frequent cloud burst and flood events during the summer monsoon e.g., Kedarnath flood of 2013. It was one of the most devastating event which claimed thousands of human lives, heavy infrastructure and economic losses. Fast moving monsoon, pre-existing westerlies, and orographic uplifting was reported as the major reason for cloud burst over Kedarnath in previous research. Our study illustrates the vertical distribution of aerosols during this event and its possible role using Weather Research and Forecasting model coupled with chemistry (WRF-Chem) simulations. Model performance evaluation shows that simulations can capture the spatial and temporal pattern of observed precipitation during this event. Model simulation at 25km and 4km horizontal grid resolution without any changes in physical parameterization shows very minimal average difference in precipitation. Whereas simulation at convection permitting scale shows de-tailed information related to parcel motion compared to coarser resolution simulation. This indicates parameterization at different resolution needs to examine for better outcome. The result shows up to 20-50% changes in rain over area near Kedarnath due to the presence of aerosols. The simulation at both resolution shows significant vertical transport of natural (increases by 50%+) and anthropo-genic aerosols (increases by 200%+) during the convective event. Which leads to significant changes in cloud property, rain concentration and ice concentration in presence of aerosols. Due to aero-sol–radiation feedback, the important instability indices like convective available potential energy, convective inhibition energy, vorticity etc. shows changes near Kedarnath.

This paper examines the diurnal cycle of convection (DCC) over Lake Titicaca Basin (LTb) during summertime months based on the high spatial resolution (8 x 8 km2) and hourly temporal resolution, estimates of Climate Prediction Center Morphing technique (CMORPH). Analysis was performed using observed data from rain gauges (Rg-SENAMHI) for the period 2002 to 2013. Graphical comparisons and several statistical metrics such as correlation coefficient, bias, and root mean square error were used to evaluate CMORPH product. Spatial maps and graphic metrics of diurnal cycle were developed to assess CMORPH data, spatial dependency an accuracy over the LTb. Approximately, 43% of the total Rg-SENAMHI variation is explained CMORPH data. The correlation between Rg-SENAMHI and CMORPH is positively over southeast and northern LTb, and negatively in the central and southern LTb. A underestimation bias is observed over most the LTb areas and overestimation bias (e.g., Lagunillas, Isla Suana and Desaguadero stations). In general, spatial patterns of rainfall over the LTb were captured through CMORPH data. Over the surrounding lake area, high mountain, and plateau area, maximum peaks of precipitation occur in the early evening, neverhtheless over low areas such as the lake, surrounding and valleys, maximum precipitation values occur early morning. The results show that DCC its very related by surface exchange processes and local circulation resulting from solar radiation and heterogeneous topography.

The nine plateau lake watersheds in Yunnan are important ecological security barriers for southwest China, and the prevention and control of landslides are important considerations in the management of these watersheds. Taking Dianchi Lake watershed as a typical study area, this paper puts forward an improved comprehensive process of landslide susceptibility evalua-tion, and discusses the model’s sensitivity regarding susceptibility to landslides. The compre-hensive process is based on the weight of evidence method (WoE) and integrates many analyti-cal techniques, such as cross-validation, multi-quantile cumulative Student’s comprehensive weight analysis, independence tests, step-by-step modeling, ROC analysis and ROC-based sus-ceptibility zoning. This paper established fourteen models, with high accuracy and validity AUC, reaching 0.83-0.87 and 0.85-0.88, respectively. Moreover, according to the susceptibility zoning map compiled using the optimal model, 80% of landslides can be predicted in the very high and high susceptibility zones, which only account for 19.58% of the study area. Finally, the strategies for geological disaster prevention and ecological restoration deployment were put forward, providing great guiding significance for deeply understanding the landslide susceptibility of lake watersheds (Dianchi Lake) in Yunnan Plateau and guiding the planning and deployment of landslide prevention and mitigation activities and ecological restoration in the watershed.

To increase rice production, fertilizer plays a crucial role in rice yield. In this research, we applied the coupled atmospheric and crop model, which is based on the WRF and CERES-Rice models, to find the appropriate nitrogen fertilizer level for increasing rice yield production in northern Thailand. The model was conducted from October to December in 2011 to 2015. To evaluate the model capability, the output from the model, including meteorological data, i.e., precipitation and temperature, and rice production, as compared to actual observation data. The modeling system shows an acceptable level of output for statistical examination; for example, the R² values were 0.93, 0.76, and 0.97 for precipitation, temperature, and rice production, respectively. To assess the optimization of the nitrogen fertilizer level, we designed 9 experiments: control cases and other cases that were multiplied by a factor of 2 – 10 times the nitrogen fertilizer levels. The model suggested that we can produce worthwhile rice yield production by approximately 4830 kg/ha if we increase the nitrogen fertilizer levels by 36 kg/ha.

Rainfall is a major climate parameter whose variation in space and time influences activities in different weather sensitive sectors such as agriculture, transport, and energy among others. Therefore, accurately forecasting rainfall is of paramount importance to the development of these sectors. In this regard, this study sought to contribute to quantitative forecasting of rainfall over Eastern Uganda through assessing the Weather Research and Forecasting model’s ability to simulate the intra–seasonal characteristics of the September to December rain season. These were: onset and cessation dates; wet days and lengths of the wet spells. The data used in the study included daily ground rainfall observations and lateral and boundary conditions data from the National Centers for Environmental Prediction (NCEP) final analysis at 1 0 horizontal resolution and at a temporal resolution of 6 hours for the entire study period were used to initialize the Weather Research and Forecasting (WRF) model. The study considered four weather synoptic weather stations namely; Jinja, Serere, Soroti and Tororo. The results show that the WRF model generally simulated fewer wet days at each station except for Tororo. Also, the WRF model simulated earlier onset and cessation dates of the rainfall season and overestimated the length of the wet spells.

Towards the investigation and further understanding of the development and propagation of Medicanes, this study explores the forecasting capability of WRF model in case of cyclone “Cleopatra” which affected with extreme rainfall and strong winds Sardinia and Calabria, Italy, in November 2013. This cyclone was unusual in that it developed a warm core but did not fulfill its transformation into a tropical-like cyclone because its core did not expand high enough in the tropospnere. The ERA5 reanalysis dataset was dynamically downscaled from 31 km spatial horizontal resolution to 9 km using WRF model. The methodology consists of; firstly, an extensive physical parameterization schemes sensitivity test and consequently, a short-range ensemble forecasting implementation based on the highest statistical scored physics configuration. All simulation results were validated against surface observations and remote sensing products. Subsequently, the modeled cyclone trajectories are compared to satellite imagery derived from EUMETSAT-SEVIRI gridded data. The findings of the conducted analysis illustrate that ensemble average displays significant difference in performance compared to any of the deterministic runs individually, suggesting that ensemble forecasts will be beneficial in studies assessing cyclonic events in the Mediterranean region.

Background: Long-range transport of dust aerosol has intense impacts on the atmospheric environment over wide areas. Methods: The annual and seasonal changes in meteorological parameters associated with the occurrence of dust storms were studied. The features of an intense dust storm and its transport characteristics were studied during June 7th to June 9th 2010 in Ahvaz city. Temporal and spatial distribution of Middle Eastern dust storm event was analyzed by models of HYSPLIT and WRF/Chem, and in- situ observations. Results: A disagreement between the occurrences of dust storms, temperature, relative humidity and rainfall, show the major source of dust storms over Ahvaz city are neighboring countries. Using HYSPLIT results, the dust particles are mainly transported from north western region of Iraq and eastern Syria to downward areas including Ahvaz city. The arrived Dust aerosols mixed with local anthropogenic emissions, led to the highest PM10 concentration of 4200 ppm. The model results were found to well reproduce temporal and spatial distribution of mineral dust concentrations according to in-situ measurements. Conclusion: The performance of WRF/Chem was acceptable for simulation of temporal and spatial distributions of dust storm events. Therefore, it can be taken as a reference in daily air quality forecasting.

East Lake in Wuhan, China, harbors a high number of freshwater fish species of great conservation value, concurrently serving as vital resources for local livelihoods. However, the ecosystem is threatened by an array of anthropogenic activities, thus requiring consistent monitoring of the local fish community to enable more efficacious conservation management. In place of conventional surveying methods, we undertook the first analysis of the fish distribution within East Lake via metabarcoding of environmental DNA (eDNA). The accuracy and efficacy of eDNA metabarcoding relies heavily upon selecting an appropriate primer set for PCR amplification. Given the varying environmental conditions and taxonomic diversity across distinct study systems, it remains a challenge to propose an optimal genetic marker for universal use. Thus, it becomes necessary to select PCR primers suitable for the composition of fish in the East Lake. Here, we evaluated the performance of two primer sets, Mifish-U and Metafish, designed to amplify 12S rRNA barcoding genes in fishes. Our results detected a total of 116 taxonomic units and 51 fish species, with beta diversity analysis indicating significant differences in community structure diversity between the 6 sampling locations encompassing East Lake. While it was difficult to accurately compare the species-level discriminatory power and amplification bias of the two primers, Mifish outperformed Metafish in terms of taxonomic specificity for fish taxa and reproducibility. These findings will assist with primer selection for eDNA-based fish monitoring and biodiversity conservation in the East Lake and other freshwater ecosystems.

Lake Rawa Besar is an urban lake surrounded by dense settlements and market area. Currently Lake Rawa Besar is experiencing physical and ecology strain. This research’s objectives are to determine the levels of sediment and nutrient, the distribution, also the relation to land use and human activities producing pollutant. Field surveys with 30 sample points and observations was needed scattered within the lake. Measuring the value of each parameter is carried out in national standardized laboratory. The result shows that sediment load of TDS is still below the standard limit for clean water, while TSS levels in the middle of lake exceed the standard limit. Nutrient loads, spesifically nitrate and phospate levels is below the standard limit. While turbidity and BOD levels have a uniform distribution pattern in the lake, exceed the standard limit for clean water, and have a positive correlation. High levels of turbidity and BOD are caused by household waste and human activities producing organic waste such as tofu factory, fowl manure, and garbage dump. Small sewage goes into the lake mediates pollutants inflow. Attention is needed by nearby people, also for the government, to sustain the ecological condition of the lake.

Forest vegetation plays a key role in the cycling of mercury (Hg) and organic matter (OM) in terrestrial ecosystems. Litterfall has been indicated as the major transport vector of atmospheric Hg to forest soils, which is eventually transported and stored in the sediments of forest lakes. Hence, it is important to understand how changes in forest vegetation affect Hg in soil and its biogeochemical cycling in lake systems. We investigated the pollen records and the geochemical compositions of sediments from two lakes (Schurmsee and Glaswaldsee) in the Black Forest (Germany) to evaluate whether long-term shifts in forest vegetation induced by climate or land use influenced Hg accumulation in the lakes. We were particularly interested to determine whether coniferous forests were associated with a larger export of Hg to aquatic systems than deciduous forests. Principal components analysis followed by principal component regression enabled us to describe the evolution of the weight of the latent processes determining the accumulation of Hg over time. Our results emphasize that the in-lake uptake of Hg during warm climate periods, soil erosion after deforestation and emissions from mining and other human activities triggered changes in Hg accumulation during the Holocene stronger than the changes caused by forest vegetation alone.

Due to urban warming, energy demand for cooling buildings is rising. The current study used CitySim to estimate the cooling energy requirements for 40 buildings in Downtown, Dubai using high-resolution climate data from weather research and forecasting (WRF) coupled with single layer urban canopy model (SLUCM). Simulating the four mitigation scenarios allowed for the examination of the reduction in cooling load caused by the addition of greenery at a rate ranging from 25% to 100%. The insulated building's cooling demand reduced by a maximum of 13.89% under 100% GI (M4). Scenario M4 resulted in a reduction of 4.6 kWh/m2 and 3.1 kWh/m2 for the non-insulated and insulated low-rise residential buildings, respectively, while the high-rise buildings saw a reduction of 3.09-4.91 kWh/m2 for the non-insulated and 2.07-3.09 kWh/m2 for insulated buildings. This study offered a potential remedy to deal with the problem of urban heating in subtropical environments.

: This study investigates the use of various thunderstorm indices in predicting severe thunderstorms events during the monsoon season in four different regions in India. The research evaluates the performance of the prediction model using a model skill score and utilizes the Weather Research and Forecasting (WRF) model with the double moment microphysics scheme to simulate model cases. It also compares fifteen thunderstorm indices derived from the ERA5 dataset to identify the most effective index for predicting severe thunderstorms events. The results of this study show that in-corporating thunderstorm indices with model skill scores improves severe thunderstorms fore-casting in the monsoon season in India. The result revealed that determining the optimal threshold for each index is crucial in achieving accurate predictions. The study also highlights the importance of considering multiple indices rather than relying on a single index to predict severe thunderstorms events. The advance indices such as Energy Helicity Index (EHI), Supercell Composite Parameter (SCP), mainly works well with extreme severe thunderstorms. The simplistic indices can predict the weak or severe thunderstorm easily. The use of multiple thunderstorm indices can also help mete-orologists to make more accurate predictions, which can further enhance public safety. In conclu-sion, this study demonstrates the potential of incorporating thunderstorm indices with model skill scores like HSS and TSS and combinations of different skill scores in severe thunderstorms fore-casting during the monsoon season in India. Future research can build upon the findings of this study to develop more accurate and reliable severe weather forecasting models.

The prediction of an extremely severe cyclonic storm (ESCS) is one of the challenging issues due to increasing intensity and its life period. In this study, an ESCS Fani that developed over Bay of Bengal region during 27 April - 4May, 2019 and made landfall over Odisha coast of India is investigated to forecast the storm track, intensity and structure. Two numerical experiments (changing two air-sea flux parameterization schemes; namely FLUX-1 and FLUX-2) are conducted with the Advanced Research version of the Weather Research and Forecasting (ARW-WRF) model by using a moving nest with fine horizontal resolution about 3 km. The high resolution (25 km) NCEP operational Global Forecast System (GFS) analysis and forecast datasets are used to derive the initial and boundary conditions, the ARW model initialized at 00 UTC 29 April 2019 and forecasted for 108 hours. The forecasted track and intensity of Fani is validated with available India Meteorological Department (IMD) best-fit track datasets. Result shows that the track, landfall (position and time) and intensity in terms of minimum sea level pressure (MSLP) and maximum surface wind (MSW) of the storm is well predicted in the moving nested domain of the WRF model using FLUX-1 experiment. The track forecast errors on day-1 to day-4 are ~ 47 km, 123 km, 96 km, and 27 km in FLUX-1 and ~54 km, 142 km, 152 km and 166 km in Flux-2 respectively. The intensity is better predicted in FLUX-1 during the first 60 h followed by FLUX -2 for the remaining period. The structure in terms of relative humidity, water vapor, maximum reflectivity and temperature anomaly of the storm is also discussed and compared with available satellite and Doppler Weather Radar observations.

The grid nudging technique is often used in regional climate dynamical downscaling to make the simulated large-scale fields consistent with the driving fields. In this study, we focused on two specific questions about grid nudging: (1) which nudged variable had a larger impact on the downscaling results and (2) what was the “optimal” grid nudging strategy for each nudged variable to achieve better downscaling result during summer over the Chinese mainland. To solve this queries, 41 3-month long simulations for the summer of 2009 and 2010 were performed using the Weather Research and Forecasting model (WRF) to downscale National Centers for Environmental Prediction (NCEP) Final Operational Global Analysis (FNL) data to a 30-km horizontal resolution. The results showed that nudging horizontal wind or temperature had significant influence on the simulation of almost all conventional meteorological elements; nudging water vapor mainly affected the precipitation, humidity, and 500 hPa temperature. Moreover, the optimum nudging scheme varied with simulated regions and layers. As a whole, the optimal nudging time was one hour or three hours for nudging wind, three hours for nudging temperature, and one hour for nudging water vapor. The optimal nudged level was above the planetary boundary layer for almost every nudged variable.

Within the town, Abiotic is a built environment that includes buildings, roads, pedestrians, and other elements that interact with biotics, which are living things including plants, animals, and humans. From a landscape ecological perspective, the urban structure consists of (1) a matrix, which is a collection of dominant buildings and homogeneous elements, (2) Patches are grouped as housing, urban forests, parks, lakes, and finally (3) Corridors such as roads, rivers, and pedestrians. The dominance of watertight areas over green open spaces in urban development can lead to increased temperatures and runoff. The condition of the soil structure and the steep slope of the soil can cause landslides, therefore urban development must pay attention to the natural conditions of the area being built. This research was conducted in Kota Baru, Bogor, South Tangerang, and Cikarang (Bekasi Regency). The purpose of this study is to determine the natural environment and the built environment as well as changes in the ecosystem and their consequences for the new town and its surroundings. This research uses quantitative and qualitative approaches. Analysis of land-use change uses spatial and temporal methods, while Nieuwolt's equation is used to measure comfort. This study finds comfortable environmental planning, with green open spaces such as urban forests, city parks, and bodies of water, such as lakes, as a space for interaction between fellow new city residents and people outside the new towns.

Lake Chapala is a natural ecosystem of Mexico, declared Ramsar site, currently, is an area with importance in the agricultural sector, tourism, and important source of drinking water in the Metropolitan area of Guadalajara, considered as a thermo regulatory body. This study used tools such as Rhtest, as well as analyzing extreme climate indices using RClimdex. In addition, the relationship with the change in water surface of Lake Chapala was assessed through the NDWI index, using Landsat images, between 1985 and 2018. According to the obtained results, the signs of climatic variability are detected in the study region, which, directly affects the basin runoff and water levels in the lake, as well as, the factor of water overexploitation in the basin, so it is considered that the lake conditions mostly depend on the type of management that is given to the resource. Finally, the results will help the understanding of climate variability and its water resources influence of the Lerma Chapala basin, which will assist in future research.

Control of nutrients, mainly nitrogen (N) and phosphorus (P), plays a significant role in preventing cyanobacterial blooms (harmful algal blooms (HABs)). This study aimed at evaluating changes in the risk of the occurrence of cyanobacterial blooms and advancing the understanding of how N and P affect the growth of cyanobacteria in a eutrophic lake, Lake Vombsjön, in southern Sweden. Statistical analysis was used to demonstrate the pattern of cyanobacterial blooms, that the highest content present in September and the later that algal blooms occur, the more likely it is a cyanobacterial bloom as cyanobacteria became dominating in October and November (90%). Two hypothesises tested in Lake Vombsjön confirmed namely that a high total phosphorus (TP) level correlates with an abundance of cyanobacteria and that low N:P ratio (total nitrogen/total phosphorus < 20) favours the growth of cyanobacteria. To control the growth of cyanobacteria in Lake Vombsjön, the TP level should be kept below 20 µg/L and the N:P ratio be maintained at a level of over 20. The two species Planktothrix agardhii, and Pseudanabaena spp. should be carefully monitored especially in late autumn. Future work should consider any high degree of leakage from the sediment of the dissolved phosphorus available there.

Since late December, the underwater Hunga Tonga-Hunga Ha'apai volcano has been erupting for weeks and has seen sporadic activities in a series of pretty big eruptions. On Friday 15th January 2022, an explosion shot a massive cloud of ash high into the atmosphere and generated a tsunami that impacted much of the Pacific Rim, which makes it one of the most energetic explosions of the entire 21st century so far. Thus, the need to determine the significant impact of these generated volcanic aerosols on the environment is a prominent task. This study depicts the modeling of the volcanic ash dispersion from the 2022 Hunga Tonga-Hunga Ha'apai volcanic eruption while investigating the effects of incorporating radiative feedback effects within the inline Weather Research and Forecasting model coupled with chemistry (WRF-Chem). Results for 4-day averaged values have proven that the basic run (No Feedback) produced higher ash concentrations than the one with aerosol radiative feedback effects (Feedback). The simulations highlighted also the significant volcanic ash biases concentrated around the ash cloud. Additionally, our data analysis from meteorological stations and Copernicus TROPOspheric Monitoring Instrument Sentinel-5 Precursor (TROPOMI-S5P) mission indicates that total sulfur dioxide () emissions traveled west. We show also that the huge plume of on January 18 reached Australia, more than 7000 km west of the eruption. With the enormous ash cloud produced, its impact on the environment and global climate change would be considered an excellent exercise for atmospheric dispersion modelers, volcanologists, and the environmental scientists' community.

Studies on the detection of layers with elevated black carbon aerosol (BC) concentrations and the formation conditions of these layers help understand the vertical distribution of BC concentrations, which will provide a basis for the assessment of climate effects and early BC pollution warnings. By using the Weather Research and Forecasting with Chemistry (WRF-Chem) numerical model, we performed a numerical simulation analysis on the authenticity of strong elevated BC concentration layers that were detected by an aircraft in the mixing layer over Harbin, China, which is a high-emission area, on a clear sunny afternoon in the early heating period of 2016. We then discuss possible problems and solutions when non-vertical paths are used to detect the vertical distribution of BC concentrations. Finally, we discuss the favorable conditions for the formation of elevated BC concentration layers by weak vertical flow. The results show that the horizontal variability of BC concentration in the mixing layer in the observation area in Harbin was sufficiently large during the measurement. This produced a false elevated layer, as detected by the aircraft during one round of spiral flight in the mixing layer. The root mean square of the horizontal distribution of BC concentration did not change with height in the mixing layer during the daytime, but it decreased with the thickness of the mixing layer and was higher in the mixing layer than in the free atmosphere. Therefore, the thinner the mixing layer, in which the vertical distribution of the BC concentration is detected in an inclined path, the stronger interference of the horizontal variability on the detected results. When a spiral flight detection path is used, the aircraft should fly at least two rounds in the mixing layer. In the daytime, due to strong turbulence in the mixing layer, weak vertical uplift is not favorable for the occurrence of elevated BC concentration layers in the mixing layer. In the nighttime, if weak vertical uplift is well matched with the BC concentration or its vertical gradient, elevated BC concentration layers can be formed in the atmosphere. Compared with upper layers far from the ground, nighttime elevated layers are easier to form in lower layers near the ground because high BC concentrations or large vertical gradients are more likely to occur in the lower layers. Both cases facilitate the occurrence of large vertical upward transport rates of BC.

Dissolved calcium (Ca2+) concentrations in freshwater ecosystems are of growing concern as increasing levels have been implicated in altering the environmental conditions and biodiversity. Elevated Ca2+ levels and sporadic re-emergence and disappearance of invasive zebra mussels in Kentucky Lake in recent years served as a motivation for this study. The objective of this study was to determine Ca2+ spatial and temporal patterns in Kentucky Lake, selected tributary streams, and the Ohio River during and following a zebra mussel invasion. Over 1000 water samples were collected and analysed for dissolved calcium during 2018-2022. Approved analytical methods were followed for sampling and measuring dissolved calcium levels. Results revealed significant spatial and temporal patterns. Kentucky Lake Ca2+ levels varied between 15-25 mg/L depending on the sampling location and month/year. Kentucky Lake channel sites exhibited comparably higher concentrations of Ca 2+ than did most embayment and/or stream sites, indicating that tributary streams did not serve as primary sources of calcium to the lake. Dissolved calcium levels at main lake sites exceeded the threshold for zebra mussel growth and reproduction in 2018 during the time when zebra mussels were present. Calcium in lake water samples collected from 2019 through 2022 was at or just below the threshold. Temporal trend data showed a gradual increase in Ca2+ in Kentucky Lake throughout the study period but remaining at or below the threshold level considered critical for the zebra mussels’ reproduction and development. Calcium levels in the Ohio River site at Paducah were similar to Kentucky Lake reflecting the predominance of Tennessee River water, while levels at the Brookport site were consistent with values known to support zebra mussel populations. The elevated calcium levels in Kentucky Lake waters during the late winter and early spring months may be due to natural sources (mineral weathering) as well as human activities in the Tennessee River basin. This study emphasizes the need for continued calcium monitoring in the watershed to determine the potential for future zebra mussel outbreaks and potential influences on the lake ecosystem and its functions.

The Rb/Sr ratio of lake sediments has been widely adopted as an indicator of weathering intensity in studies of past climate change, but the geochemical significance of this ratio varies with timescale. Here we present Rb/Sr data for the last 300 years for sediments collected from Chaonaqiu Lake in the Liupan Mountains of the western Chinese Loess Plateau as a decadal-scale record of weathering intensity. To validate the application of this weathering proxy, we correlated the record with those of other major elements, rock-forming minerals, and paleoclimatic proxies. We found that Rb/Sr ratios are influenced mainly by Sr activity within the lake catchment (where Sr is likely sourced from albite). In addition, higher (lower) Rb/Sr ratios of bulk sediments from Chaonaqiu Lake are correlated with lower (higher) fractions of terrigenous detritus (SiO2, Ti, K2O, Al2O3, and Na2O). Lake bulk sediment Rb/Sr ratios are dominated by the input of terrigenous detritus over decadal timescales. Our data show that physical and chemical weathering in Chaonaqiu Lake catchment have opposing influences on bulk sediment Rb/Sr ratios, competing to dominate these ratios of lake sediments over different timescales, with ratios reflecting the relative importance of the two types of weathering. We infer that the Rb/Sr ratios of Chaonaqiu Lake sediments reflect climatic signals of precipitation and temperature over long timescales and of precipitation over short timescales.

This paper presents an analysis of future precipitation patterns over the Lake Victoria Basin using bias-corrected CMIP6 model projections. A mean increase of about 5% in mean annual (ANN) and seasonal [March-May (MAM), June-August (JJA), and October-December (OND)] precipitation climatology is expected over the domain by mid-century (2040-2069). The changes intensify towards the end of the century (2070-2099) with an increase in mean precipitation of about 16% (ANN), 10% (MAM), and 18% (OND) expected, relative to the 1985-2014 baseline period. Additionally, the mean daily precipitation intensity (SDII), the maximum 5-day precipitation values (RX5Day), and the heavy precipitation events, represented by the width of the right tail distribution of precipitation (99p-90p) show an increase of 16%, 29%, and 47%, respectively, by the end of the century. The projected changes have a substantial implication for the region - which is already experiencing conflicts over water and water-related resources.

The paper portrays predictive models for dissolved oxygen (DO) levels in an urban lake using common water quality parameters like Temperature, pH, Conductivity and ORP at a time. Data were sampled using three real-time, industry-standard sensors, OPTOD, CTZN, and PHEHT, and then interpolated using the ArcGIS kriging technique. Correlation studies were analyzed through the ML algorithm, the correlation study signified a highly positive correlation between DO and other water parameters and the model was corroborated by R-score in order to create the linear regression model. In addition, an artificial neural network- a machine learning method using the Levenberg-Marquardt algorithm was developed to build a model to predict the do as well. Then, the performance of the models was validated and also the R² accuracy was checked of the predicted data against the actual data. Thus, the appropriateness of the ANN model for the forecasting of investigated attributes is indicated by the fact that the discrepancy between the forecasted and real ANN model is significantly lesser than that of the regression model. However, the model can be used to reveal DO data from unknown urban lake water.

Hot spring is a hot water that is naturally occurring on the surface from the underground and typically heated by subterranean volcanic activity and local underground geothermal gradient. There are four main hot springs in Rwanda such as: Kalisimbi, Bugarama, Kinigi and Nyamyumba former name Gisenyi hot springs. It is often believed that soaking in hot springs is a great way which naturally detox human skin. This research focused on the geochemical analysis of Nyamyumba hot springs located near the fresh water of Lake Kivu for the purpose of understanding its healing capacity and safety. Nyamyumba hot springs are located in the western branch of the East African Rift System and they are located near Virunga volcanic complex, explaining the rising and heating mechanism of water. The concentrations of Sulfate, Iron, Ammonia, Alkalinity, Silica, Phosphate, Salinity, Alkalinity, and Conductivity using standard procedures were measured. The results showed that hot spring water has higher concentrations of chemicals compared to Lake Kivu water and the geochemistry of these hot springs maybe associated with rock dissolution by hot water. The measured parameters were compared with World Health Organization (WHO) standards for recreational waters and it has been identified that Nyamyumba hot springs are safe to use in swimming and therapeutic activities.

In order to better understand the biogeochemical cycle of nitrogen in meromictic lakes, which can serve as a model for past aquatic environments, we measured dissolved concentrations of nitrate, nitrite, ammonium and organic nitrogen in deep (39 m maximal depth) subarctic Lake Svetloe (NW Russia). The lake is a rare type of freshwater meromictic water boy with high concentrations of methane, ferrous iron, manganese and low concentrations of sulfates and sulfides in the monimolimnion. In the oligotrophic mixolimnion, the concentration of mineral forms of nitrogen decreased in summer compared to winter, likely due to phytoplankton bloom. The decomposition of the bulk of organic matter occurs under microaerophilic/anaerobic conditions of the chemocline and accompanied by the accumulation of nitrogen in the form of N-NH4 in the monimonimlion. We revealed a strong relationship between methane and nitrogen cycles in the chemocline and monimolimnion horizons. The nitrate concentrations in Lake Svetloe varied in the range from 9 to 13 μM throughout the water column. This fact is rare for meromictic lakes, where nitrate concentrations up to 13 µM are found in the monimolimnion zone down to the bottom layers. We hypothesize, in accord with available data for other stratified lakes, that under conditions of high concentrations of manganese and ammonium at the boundary of redox conditions and below, anaerobic nitrification with the formation of nitrates occurs. Overall, most of organic matter in Lake Svetloe undergoes biodegradation essentially under microaerophilic/anaerobic conditions of the chemocline and the monimolimnion. Consequently, the manifestation of the biogeochemical nitrogen cycle is expressed in these horizons in the most vivid and complex relationship with other cycles of elements.

Wind is one of the factors that has a great influence on suspended matter in lakes, especially in shallow lagoons. In order to know how wind affects the water in Albufera of Valencia, a shallow coastal lagoon, the measured variables of turbidity and transparency have been correlated with the estimates by processing Sentinel-2 satellite images with the Sen2Cor processor. Data from four years of study show that most of them are light to gentle easterly breezes and moderate to fresh westerly breezes. The results obtained show significant correlations between the measured variables and those obtained from the satellite images for total suspended matter and water transparency and with the average daily wind speed. There is no significant correlation between wind and chlorophyll a. Moderate to fresh breezes resuspend the fine sediment reaching concentration values from 100 to 300 mg L-1 according to satellite data. However, it is necessary to obtain field data for the values of moderate and fresh winds, as for now there are no experimental data to verify the validity of the satellite estimates.

Lake Manzala, the largest of the northern Delta lakes of Egypt, has a great economic importance as a major natural resource of fish and salt. Unfortunately, the lake is suffering from the high inputs of pollutants from industrial, domestic, and agricultural sources. The present study aims to develop the proposed water quality management scenarios to assess and control lake pollution, the pollution sources as well as the pollution spread from the lake to the connected Mediterranean Sea. To apply study methodology, the work tasks divided into two main parts, the first part involved in modelling the lake environments by using Delft3D-WAQ hydrodynamic and water quality model to study the current status and predict the dynamic state of the Lake. This model was calibrated and validated by using various water quality datasets to simulate different scenarios. In the second part, the required lake water quality improvement scenarios were developed to solve the lake water quality problems. The study results showed that the first three developed scenarios that focusing on treatment drain effluent using primary, secondary treatment and surface wetland techniques respectively have a limited efficiency on lake water quality improvement. While the fourth scenario that involved on using biological biofilm techniques can improve lake water quality parameters. Moreover, the fifth scenario that proposed adding a new artificial inlet has a limitation due to the noted increases in lake salinity levels. The sixth scenario that proposed a diversion of some drains can improve lake water quality parameters but it can lead to a decrease in Lake water level. From water quality view point, the last scenario that applying a combination biological biofilm activated technique and also adding a new artificial inlet at northern lake region can represent the optimum scenario. Hopefully, this research will preserve the lake environment and contribute to the benefit of the man health as well. This approach could be extended to the hydrodynamic studies in similar large, shallow lakes anywhere in the world.

This study aims to identify the optimal combination of microphysics (MP) and cumulus (CU) parameterization schemes for accurately simulating heavy to violet rainfall events associated with Tropical Cyclones (TCs) and atmospheric disturbances in Thailand using the coupled Weather Research and Forecasting (WRF) and Regional Oceanic Model (ROMS), hereafter referred to as WRF-ROMS. Three CU schemes, namely Betts–Miller–Janjic (BMJ), Grell 3D Ensemble (G3), and Kain–Fritsch (KF), along with three MP schemes, namely Eta (ETA), Purdue Lin (LIN), and WRF Single-moment 3-class (WSM3), are selected for the sensitivity analysis. Seven instances of heavy to violent rainfall in Thailand, occurring during summer season of 2020 and associated with tropical storms and atmospheric disturbances, are simulated using all possible combinations of the chosen physics schemes. The simulated rain intensities are compared against observations from the National Hydroinformatics Data Center. Performance was assessed using the Probability of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) metrics. The models showed proficiency in predicting light to moderate rainfall, with certain combinations performing better in specific rainfall categories. However, forecasting heavy and violent rainfall proved challenging for all models and lead-time forecasts. Specific combinations, particularly those incorporating the KF scheme, demonstrated superior prediction of heavy to violent rainfall. The FAR values increased with lead-time and rain intensity, and the KF scheme combinations showed improved predictions of intense rainfall with lower FAR values. The CSI values indicated comparable performance between the control model and combination models across light to heavy rain categories, with the KF scheme showing better predictions for longer lead-times. However, accurately predicting intense rainfall remained limited. These findings highlight the need for further improvements, including refining model parameters and exploring advanced techniques to enhance accuracy and skill, particularly for longer-term forecasts. Sub-seasonal to seasonal prediction should be considered to extend forecast capabilities.

In early 2020 from April to early June, the metropolitan area of Sydney as well as the rest of New South Wales (NSW, Australia) experienced a period of lockdown to prevent the spread of Covid-19 virus in the community. The effect of reducing anthropogenic activities including transportation had an impact on the urban environment in term of air quality which is shown to have improved for a number of pollutants, such as nitrogen dioxides (NO2) and carbon monoxide (CO), based on monitoring data on ground and from satellite. Besides primary pollutants CO and NOx emitted from mobile sources, PM2.5 (primary and secondary) and secondary ozone (O3) during the lockdown period will also be analysed using both air quality data and modelling method. The results show that NO2, CO and PM2.5 levels decreased during the lockdown, but O3 instead increased. The change in the concentration levels however are small considering the large reduction in traffic volume of ~30%. By estimate the decrease in traffic volume in Sydney region, the corresponding decrease in emission input to the WRF-CMAQ (Weather Research and Forecasting - Community Multiscale Air Quality Modeling System) air quality model is then used to estimate the effect of lockdown on the air quality especially CO, NO2, O3 and PM2.5 in the Greater Metropolitan Region (GMR) of Sydney. COVID-19 lockdown period is an ideal case to study the effect of motor vehicle and mobile source contribution to air pollutants such as those listed above in the GMR.

Between 11 to 15 February 2019, a dust storm originating from Central Australia with persistent westerly and south westerly winds caused high particles concentration at many sites in the state of New South Wales (NSW), both inland and along the coast. The dust continued on to New Zealand and to Antarctica in the south east. This study uses observed data from air quality monitoring stations in NSW and New Zealand, MODIS 3km AOD (Aerosol Optical Depth) product from Terra/Aqua and lidar aerosol profile from CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite data, and the Weather Research Forecast WRF-Chem model based on GOCART-AFWA (Goddard Chemistry Aerosol Radiation and Transport – Air Force and Weather Agency) dust scheme and GOCART aerosol and gas-phase MOZART (Model for Ozone And Related chemical Tracers) chemistry model to study the long-range transport of aerosols for the period 11 to 15 February 2019 across eastern Australia and onto New Zealand and Antarctica. Wild fires also happened in northern NSW at the same time and their emissions are taken into account in WRF-Chem model by using Fire Inventory from NCAR (FINN) as emission input. Modelling results by the WRF-Chem model show that for the Canterbury region of South Island of New Zealand, peak concentration of PM10 (and PM2.5) as measured on 14 February 2019 at 05:00 UTC at the monitoring stations of Geraldine, Ashburton, Timaru and Woolston (Christchurch), which are more than 100km from each other and at Rangiora, Kaiapoi about 2 hours later, correspond to the prediction of high PM10 due to intrusion of dust to ground level from transported dust layer above. The Aerosol Optical Depth (AOD) observation data from MODIS Terra/Aqua and CALIOP lidar measurements on board CALIPSO satellite also indicate that high altitude of dust, originated from this dust storm event in Australia, was located above Antarctica. This study suggests that at present dust storms in Australia can transport dust from sources in Central Australia to the Tasman sea, New Zealand and Antarctica. This process has been going on for at least the last 170k years as indicated by dust found in ice cores from Antarctica and sediment records in the Tasman Sea.

The prediction of hydrological flows (rainfall-depth or rainfall-discharge) is becoming increasingly important in the management of hydrological risks such as floods. In this study, the Long Short-Term Memory (LSTM) network, a state-of-the-art algorithm dedicated to time series, is applied to predict the daily water level of lake Nokoue in Benin. This paper aims to provide an effective and reliable method enable of reproducing the future daily water level of Lake Nokoue, which is influenced by a combination of two phenomena: rainfall and river flow (runoff from the Ouémé River, the Sô River, the Porto-Novo lagoon, and the Atlantic Ocean). Performance analysis based on the forecasting horizon indicates that LSTM can predict the water level of Nokoué Lake up to a forecast horizon of t+10 days. Performance metrics such as Root Mean Square Error (RMSE), coefficient of correlation (R²), Nash-Sutcliffe Efficiency (NSE), and Mean Absolute Error (MAE) agree on a forecast horizon of up to t+3 days. The values of these metrics remain stable for forecast horizons of t+1 days, t+2 days, and t+3 days. The values of R² and NSE are greater than 0.97 during the training and testing phases in the Nokoué Lake basin. Based on the evaluation indices used to assess the model's performance for the appropriate forecast horizon of water level in the Nokoué lake basin, the forecast horizon of t+3 days is chosen for predicting future daily water levels.

A very detailed water budget was conducted on Lake Trafford in southern Florida. The inflow was dominated by surface-water influx via five canals (61%) with groundwater influx constituting 12% and direct rainfall 27%. Lake discharge was dominated by sheet-flow (69%) and evapotranspiration (30.5%) with groundwater recharge of the hydraulically connected unconfined aquifer accounting for only 0.5%. Removal of 30 M tons (4.4 x 106 m3) of organic sediment impacted groundwater influx, causing enhanced groundwater flows into the deeper parts of the lake and mixed flows along the banks creating a rather unusual pattern. The large number of groundwater seepage meters used during the investigation led to a very reliable set of measurements with occasional failure of only a few meters. A distinctive relationship was found between the wet season lake stage, heavy rainfall events and pulses of exiting sheet-flow from the lake. Estimation of the evapotranspiration loss using data collected from a weather station on the lake allowed the use of three different models which, when averaged, produced results comparable to Lake Okeechobee (southern Florida). A limitation of the investigation was the inability to directly measure sheet-flow discharges, which had to be estimated as a residual within the calculated water budget.

Garlic, as an important economic crop in China, still has room for improvement in terms of identification using remote sensing technology, Among them, high-precision classification of garlic has become an important subject. The Erhai Lake is an important freshwater lake in China. Under the influence of technology and policies, significant changes have occurred in the cultivation of garlic crops. this study constructed multidimensional features for crop classification suitable for Google Earth Engine, and Propose a method for identifying garlic crops using sample and feature datasets under limited conditions. The results indicate that: 1) In the land-use classification of the Erhai Lake Basin, the importance ranking of characteristic bands, from high to low, is as follows: spectral features, vegetation features, texture features, and terrain features. 2) The Random Forest method based on feature selection demonstrates high classification accuracy in land-use classification within the Erhai Lake Basin in Yunnan Province. The overall classification accuracy reaches 95.79%, with a Kappa coefficient of 0.9481. 3) The expansion direction of garlic cultivation in the Erhai Lake Basin initially strengthened and then weakened from 1999 to 2023. The vertical development of garlic cultivation reached saturation, showing a slow trend towards horizontal expansion between 2005 and 2018. The planting distribution in various townships in the Erhai Lake Basin gradually shifted from a relatively uniform distribution to an upstream development in the basin. This study utilizes the Google Earth Engine (GEE) cloud computing platform and machine learning algorithms to compensate for the lack of statistical data on garlic cultivation in the Erhai Lake Basin. Simultaneously, it accurately, rapidly, and efficiently extracts planting information, demonstrating significant potential for practical applications.

A thermal system in very deep Lake Tazawa (maximum depth, 423 m) was investigated by estimating the heat budget. In the heat budget estimate, the net heat input at lake surface and the heat input by river inflow and groundwater inflow were considered. Then, the heat loss by snowfall onto lake surface was taken into account. Meanwhile, lake water temperature was monitored at 0.2 m to the bottom by mooring temperature loggers for more than two years. The heat storage change of the lake from the loggers was calibrated by frequent vertical measurements of water temperature at every 0.1 m pitch by a profiler with high accuracy (± 0.01 °C). The heat storage change (W/m2) obtained by the temperature loggers reasonably accords to that from the heat budget estimate. In the heat budget, the net heat input at lake surface dominates the heat storage change, but the significant heat loss by river inflow sporadically occurred, which is caused by the relatively large discharge from a reservoir in the upper region. How deep the vertical water circulation in the lake occurs in winter was judged by the differences between water temperatures at 0.2 m depth and bottom and between vertical profiles of dissolved oxygen over winter. It is strongly suggested that the whole water circulation does not occur every winter, if any, very weak.

This research investigates the environmental characteristics of the saline lake in the Jiangling depression, southwestern Jianghan Basin from Paleocene to Eocene using bulk-rock geochemistry. The ratios of FeO/MnO, Al2O3/MgO and C-value indicate a semi-humid to semi-arid climate in the early-middle Paleocene. There was a rapid shift to a humid climate during the late Paleocene to early Eocene, following a short-time intense dryness. The Eocene climate was arid, but experienced intermittent humidity. The variation trend of CIA, CIW and PIA is similar to that of FeO/MnO, Al2O3/MgO and C-value, so the chemical weathering was influenced by climate changes. The redox conditions of lake in the Jiangling depression during Paleocene to Eocene were reconstructed using the ratios of U/Th, Ni/Co, and V/Cr. In the humidity and alternations of aridity and humidity, the lake water received external water input, resulting in weak stratification, so the sediments were in oxidation condition. In the aridity, lakes become a still water environments, leading to sediments formed in reduced condition. The salinity of the lake in Jiangling depression from Paleocene to Eocene was determined through the analysis of sedimentary sequences and the change of Sr/Ba ratio. In the early-middle Paleocene, the salinity of lake varied greatly. From the late Paleocene to the early Eocene, the salinity of lake decreased. In the Eocene, the salinity of the lake increased, and the halite precipitated, and finally the salinity of the lake decreased due to humid climate.

The purpose of this study was to elucidate patterns and mechanisms driving seasonal and inter-annual variations of carbon and nitrogen stable isotopes in the zooplankton crustacean commu-nity of Lake Maggiore (Italy), during the period 2009-2020. Different zooplankton taxa and groups revealed different ranges of d13C signatures, giving an insight into food sources and niche partition. In particular, cyclopoids had a restricted range with most negative d13C‰ values and increase in d13C fractionation with the establishment of water thermal vertical stratification, high-lighting the importance of vertical distribution as key factor for taxa coexistence in a vertically heterogenous environment. d13C of the zooplankton community and of Daphnia were positively related to water temperature (R2=0.58 p <0.0001 and R2=0.68 p <0.0001, respectively) and d13C Daphnia signature to chlorophyll-a (R2=0.32, p < 0.0001). Decomposition of time series data for zooplankton carbon and nitrogen signatures and environmental parameters identified increasing trends in water temperature, chlorophyll-a and water conductivity and decrease in nitrate, that matched changes in carbon isotopic signature trend in some zooplankton taxa (Bosmina, Daphnia and diaptomids). Overall, the observed patterns in zooplankton isotopic signatures were interpreted as integrations of climate warming effects in Lake Maggiore, affecting both food sources availability and environmental conditions.

In the Yucatán Peninsula, anthropogenic activities such as urbanization and final dispose of solid and wastewaters critically impact aquatic systems. Here, we evaluated the anthropogenic-related environmental alteration of Lake La Sabana, located in the northern limit of one of the main cities of the Mexican Caribbean. We evaluate lake water quality using physical, chemical, and microbiological indicators, and heavy metals in surficial sediments and fish tissue to evaluate the potential environmental risk. Multivariate analyses reveal that environmental conditions in La Sabana are spatial and temporal heterogeneous. Medium to bad water quality was determined within basins by the NSFWQI, related with the degree of anthropogenic influence. The center-south zones display critical microbiological values largely exceeding national standards. Heavy metals in sediments (Zn&gt;Hg) and fish tissue (Hg) were relatively low, but Hg concentration threat the ecological environment. Incipient wastewater treatment and final dispose in La Sabana is the main responsible of changes in the trophic status and nutrients availability, which in turn may have promoted changes in the biological structure and aquatic plant invasions. Lake La Sabana can be considered a model of the potential sequential effects of the anthropogenic alterations in oligotrophic karts tropical aquatic systems in Yucatán Peninsula.

Tilapia lake virus (TiLV) is the main tilapia-infecting virus worldwide, causing serious economic losses. However, there is no vaccine for this viral disease. Here, TiLV ORF10 (TiLV-ORF10) encoding a protein with abundant epitopes was constructed into the eukaryotic expression vector pcDNA3.1, and used to evaluate the immune protective effects in Nile tilapia (Oreochromis niloticus). RT-PCR and western blot analyses confirmed vaccine plasmid expression in tilapia muscle tissues. Moreover, the transcription levels of immunoglobulin M, toll-like receptor 2, myeloid differentiation factor 88, interleukin 8, tumor necrosis factor alpha, gamma-IFN, and nuclear factor κB immune-related genes were statistically significantly upregulated in the spleen, liver, and kidney of vaccinated tilapias (P < 0.05). TiLV challenge experiments showed that relative percent survival (RPS) was significantly enhanced in fish by this DNA vaccine. Moreover, RPS was enhanced further when using a higher amount of the DNA vaccine (85.72% RPS at a DNA dose of 45 μg pcDNA3.1–ORF10). Vaccination with pcDNA3.1–ORF10 significantly reduced virus replication, as evidenced by the low amount of virus in the spleen, liver, and kidney of vaccinated tilapias after TiLV challenge. Thus, pcDNA3.1–ORF10 could induce protective immunity in tilapia and may be a potential vaccine candidate for controlling diseases caused by TiLV.

Water pollution in Iraq has been extended disaster edge; this pollution is caused by wastes and sewages into soil and rivers, pollutant water sources influence the outbreak and serious epidemic status among the population.. The aim of this study is to determine the bacteriological quality of drinking water sources and characteristics of water-borne diseases especially diarrheal cases in Darbandikhan city. 166 water samples, collected from the different sources and areas, were tested for the presences of coliform bacteria as an indicator for pathogen contamination. Most probable number index was used for coliform enumeration. 161 diarrheal cases were taken as a sample from the patients were admitted to the general hospital in Darbandikhan district.. The questionnaire form was planned to view characteristics of diarrheal cases and patients were interviewed directly, the data was analyzed by STATA software application. 46% of the diarrheal cases used tap water for drinking. On the other hand, the reminder (54%) used other sources for the same purpose. All the risk factor such as type of water source, sufficiency of the water, duration of water storage and chlorination were associated with diarrhea. Almost half of the cases were children and three quarters were single. The data was analyzed by STATA version 13.1.This study indicated that the majority of drinking water sources in Darbandikhan city are not suitable for drinking, although net pipe system supplied chlorine significantly it has been proven that the tap water from the homes is not suitable for consumption.

Keenjhar Lake is the main source of drinking water for the metropolitan city of Karachi. The release of untreated wastewater from Kotri industrial area and other sources have made the lake water polluted. This study was subjected to determine the impacts of such pollutant sources on the water quality of Keenjhar Lake. The study involves the analysis of water quality parameters of Keenjhar Lake and its Feeding source (KB Feeder). The sampling sites were selected based on the sources of contamination. The water samples are tested for physical, chemical and microbiological parameters. The result of water analysis indicates the contamination level of the lake is quite alarming for the sites of Kotri effluent and WAPDA colony where Total Dissolved Solids (TDS), Chloride and other ionic metals were quite higher in concentration than other sites. These sites are also contaminated with Fluoride and Arsenic which are carcinogenic elements. The study reveals that the contamination level of feeding source is causing big non-reversible damage to the lake if continued to be uncontrolled. This contamination is mainly due to the release of toxic metals and ions in the KB feeder caused by human carelessness.

Soil temperature reflects the impact of local factors，such as vegetation，soil and the atmosphere of a region. Therefore, it is important to understand the regional variation of soil temperature. However, lack of observations with adequate spatial and/or temporal coverage, it would be difficult to use the observation data to study the regional variation. Based on the observation data from Nanchang and Ganzhou stations and ERA-Interim/Land reanalysis data, this study analyzed the temporal-spatial distribution characteristics of soil temperature over Poyang Lake Basin. The results showed close correlations between observation data and reanalysis data at different depths. Reanalysis data could mainly reproduce the temporal-spatial distributions of soil temperature over the Poyang Lake Basin, but generally underestimate their magnitudes. Temporally, there is an obvious warming trend in the basin. Seasonally, the temperature raised fastest in spring and slowest in summer, except for the ST4, which rising fastest in spring and slowest in winter. In terms of depths, the temperature of ST1 rises fastest. For the other layers, the warming trend is almost similar. An abrupt change of annual soil temperature at all depths occurred in 1997, and annual soil temperatures at all depths were abnormally low in 1984. Spatially, annual soil temperature decreased with latitude, except for the summer ST1. Because of the high temperature and precipitation in summer, the ST1 are higher around the lake and the river. The climatic trend of soil temperature presents the general increase trend from south to north, opposite to the distribution of soil temperature. The findings provide a basis for understanding and assessing the variation of the soil temperature over the Poyang Lake Basin.

A temperate deep lake, Lake Kuttara, Hokkaido, Japan (148 m deep at maximum) was completely frozen every winter in the 20th century. However, unfrozen conditions of the lake over winter occurred four times in the 21st century, which is probably due to global warming. In order to understand how thermal regime of the lake responds to climate change, its heat storage change was calculated by estimating heat budget of the lake and monitoring water temperature at the deepest point for September 2012–June 2016. As a result, temporal change of the heat storage from the heat budget was very consistent with that from the direct temperature measurement (determination coefficient R² = 0.827). The 1978–2017 data at a meteorological station near Kuttara indicated that there are significant (less than 5% level) long-term trends for air temperature (0.024 °C/yr) and wind speed (−0.010 m/s/yr). A sensitivity analysis for the heat storage from the heat budget estimate and an estimate of return periods for mean air temperature in mid-winter allow us to conclude that the lake could be unfrozen once per about two year in a decade.

The 2019-2020 summer wildfire event on the east coast of Australia was a series of major wildfires occurring from November 2019 to end of January 2020 across the states of Queensland, New South Wales (NSW), Victoria and South Australia. The wildfires were unprecedent in scope and the extensive extend of the wildfires has caused smoke pollutants transported not only to New Zealand but across the Pacific Ocean to South America. At the height of the wildfires, smoke plumes were injected into the stratosphere at height up to 25km and hence transported across the globe. Based on meteorological and air quality simulation using WRF-Chem model, air quality monitoring data collected during the bushfire period and remote sensing data from MODIS and CALIPSO satellites, the extend of the wildfires and the pollutant transport, and their impacts on air quality and health on exposed population in NSW can be analysed. The results showed that WRF-Chem model using Fire Emission Inventory from NCAR (FINN) predicts the dispersion and transport of pollutants and the predicted concentration of PM2.5 and other pollutants from wildfires reasonably well when compared with ground-based and satellite data. The impact on health endpoints such as mortality, respiratory and cardiovascular diseases hospitalisation across the modelling domain is then estimated. The estimated health impact is comparable with previous study based only on observation data, but the results in this study provide much more detailed spatially and temporally with regards to the health impact from the 2019-2020 wildfire.

Dust storms originating from Central Australia and western New South Wales frequently cause high particles concentration at many sites across New South Wales, both inland and along the coast. This study focussed on a dust storm event in February 2019 which affect air quality across the state as detected at many ambient monitoring stations in the Department of Planning, Industry and Environment (DPIE) air quality monitoring network. The WRF-Chem (Weather Research and Forecast Model – Chemistry) model is used to study the formation, dispersion and transport of dust across the state of New South Wales (NSW, Australia). Wildfires also happened in northern NSW at the same time of the dust storm in February 2019, and their emissions are taken into account in WRF-Chem model by using Fire Inventory from NCAR (FINN) as emission input. The model performance is evaluated and is shown to predict fairly accurate the PM2.5 and PM10 concentration as compared to observation. The predicted PM2.5 concentration over New South Wales during 5 days from 11 to 15 February 2019 is then used to estimate the impact of the February 2019 dust storm event on three health endpoints namely mortality, respiratory and cardiac diseases hospitalisation rates. The results show that even though as the daily average of PM2.5 over some parts of the state, especially in western and north western NSW near the centre of the dust storm and wild fires, are very high (over 900 µg/m3), the population exposure is low due to the sparse population. The top five Statistical Area Level 4 regions with the most impact in term of mortality, respiratory diseases hospitalisation and cardiac disease hospitalisation are Far West and Orana, Newcastle and Lake Macquarie, New England and North West, Sydney – Inner South West and either Central Coast (mortality) or Sydney – Parramatta (respiratory diseases hospitalisation) or Sydney – Inner West (cardiac diseases hospitalisation). Generally, the health impact is similar in order of magnitude to that caused by biomass burnings events from wildfires or from hazardous reduction burnings (HRBs) near populous centres such as in Sydney in May 2016. One notable difference is the higher respiratory diseases hospitalisation for this dust event (161) compared to fire event (24).

Typhoon Durian forming over the Western North Pacific Ocean and entering into the South China Sea (SCS), caused extreme and widespread damages in 2006. In this research, sensitivity analyses on different physical parameterization schemes of the Weather Research and Forecasting Atmospheric Model (WRF-ATM) have been utilized to study typhoon Durian. Model accuracy and performance testing were investigated with different initial conditions during the tropical cyclone simulation in the SCS. The initial and boundary conditions (IBCs) for all experiments were derived from the European Centre for Medium Range Weather Forecasts (ECMWF), Re-Analysis Interim (ERAI), and the National Centers for Environmental Prediction (NCEP) with Final (FNL) analysis data compiled through the WRF-ATM model. The sensitivity analysis results indicated a major improvement for the cumulus scheme by using the Grell-Devenyi scheme along with the PBL scheme of Yonsei University, mixed-phase microphysics scheme of the WRF Single Moment 5-class and IBCs for ECMWF-ERAI of TC simulation under the context of Wind-Pressure Relationships. This predicted better track and intensity comparing with these of the Joint Typhoon Warning Center. The results revealed that the TC track and intensity were well simulated by the WSM5-GD combination for the WRF-ATM model with an intensity error of 1.69 hPa for minimum surface level pressure, maximum wind speed of 1.83 knots and average track error of 25 km in 72 hours. The simulations showed that the potential track and intensity error decreased with the delayed IBCs, suggesting that the model simulation is more dependable when the coast is approached by the TC.

Wildland fires are responsible for large socio-economic impacts. Fires affect the environment, damage structures, threaten lives, cause health issues, and involve large suppression costs. These impacts can be mitigated via accurate fire spread forecast to inform the incident management team. We show that a fire forecast system based on a numerical weather prediction (NWP) model coupled with a wildland fire behavior model can provide this forecast. This is illustrated with the Chimney Tops II wildland fire responsible for large socio-economic impacts. The system is run at high horizontal resolution (111 m) over the region affected by the fire to provide a fine representation of the terrain and fuel heterogeneities and explicitly resolve atmospheric turbulence. Our findings suggest that one can use the high spatial resolution winds, fire spread and smoke forecast to minimize the adverse impacts of wildland fires.

Saudi Arabia consists mainly of desert land. However, it has big and small natural wetlands and artificial wetlands. Most of these wetlands are seen along the Red Sea and the Arabian Gulf coastal regions. Al-Asfar Lake, located in the Eastern Region of Saudi Arabia, is one of the historical landmarks of Al-Ahsa province. The primary lake water source is agricultural drainage water, which some refer to as an artificial lake. This paper mainly aims to reflect shade on the wetlands in Saudi Arabia in general and to show in detail the environmental impacts of Al-Asfar Lake on the ecosystem and biodiversity of the study area. The analytical review of the previous studies conducted in Al-Asfar Lake was adopted in this article. Hence, the impact of the lake on the land-use system, water quality and biodiversity was illustrated as the main outputs of the review analysis. However, the sustainable management of Al-Asfar Lake requires the stakeholders to adopt the wetland ecosystem health concept, which might lead to improving the lake's environmental conditions.

Morphological study of lakes defines the sensitivity of their watershed. Moreover, it plays important role in safeguarding the lake’s ecosystem services through proper planning and utilization of the lakes’ resources. In the last few decades, the morphology of lakes in Ethiopian and Kenyan Rift (EKR) valley are experiencing contradicting morphological changes. Being in the same system, some are shrinking and others are expanding beyond their natural boundaries. The objective of this review is to shed light on the trends in spatio-temporal water level fluctuation and their contributing factors for lakes to the academia and decision makers. Peer reviewed article journals, conference proceedings, thesis, and book chapters collected from online sources and supplied by authors on request formed a database of 346 documents where 226 are critically assessed. The review indicated that lakes in Ethiopian rift are shrinking and expanding, while Kenyan lakes are expanding. The en-dorheic lakes suffered the most fluctuations due to anthropogenic factors at the expense of loss of forest and woodlands in their watershed. While the lakes’ water quality related to the morphological changes are given less attention, the predicted 12 m drop of Lake Turkana due to projects in the Omo catchment did not materialize.

Freshwater lakes represent a potential source of methane (CH4) to the atmosphere. However, the CH4 emission contribution to the total emission in the littoral zones of lakes, especially emergent macrophytes (e.g., lotus), are poorly known. Lotus, has been cultivated in almost all provinces in China, is not only an aquatic plant but also a kind of vegetables. Two sampling zones (lotus plant and open water) were established in the lake of the middle reaches of Yangtze River. The CH4 emission was measured using a floating opaque chamber and gas chromatography between April to December of the years 2021 and 2022. The results indicated that the flux of CH4 emissions ranged from 0.10 to 59.75 mg m-2 h-1, with an average value of 5.61 mg m-2 h-1 in the open water, while ranged from 0.19 to 57.32 mg m-2 h-1, with an average value of 17.14 mg m-2 h-1 in the lotus plant zone. The maximal CH4 emissions occurred in July and August for the open water, which was highly related to the air and water temperature; whereas it happened in September for the lotus plant zone, due to the fresh organic matter inputting to sediments, CH4 transportation by lotus plant, high soil organic carbon content, and the lower dissolved oxygen concentration. Considering the carbon emissions (both CH4 and CO2) and plant productivity, although the greater CH4 emission occurring in lotus plant zone, it could still represent a potential carbon sink (213 g m-2 yr-1), compared to the open water.

Despite a growing concern over sustainability in tourism, research on this domain regarding, specifically, lake destinations, is still scarce. Although perceptions on lake destinations have been studied, no study is known that analyses the impact of visitors’ perceptions on satisfaction and behavioral intentions. Thus, this paper aims to develop and test a model to analyse the effect of lake visitors’ perceptions of destination’s sustainability on both satisfaction and loyalty towards lake destinations. A questionnaire survey was conducted in the Shchuchinsk-Burabay resort area, an important lake destination in northern Kazakhstan. The results support the proposed lake destination loyalty model, tested using partial least squares structural equation modelling (PLS-SEM). Sustainability proved to be decisively influential, with water quality being the dimension with the highest impact on satisfaction with the lakes, along with a positive key impact of the absence of congestion. In addition, both water quality and lack of congestion had a significant indirect impact on satisfaction with the lake destination, and on loyalty. Based on the research findings, theoretical conclusions and practical implications are drawn.

The monitoring of lake waterbody area in the Qinghai Tibet Plateau (QTP) is of great significance to deal with global climate change. As the latest generation of Landsat series satellites, Landsat-9 data not only have higher radiometric resolution, but also cooperate with other Landsat satellites to greatly improve the temporal resolution. It has great application potential in lake waterbody area monitoring. In order to explore the performance of different algorithms for extracting waterbody and lake waterbody area in Landsat-9 data under large-scale QTP regions, this study relies on Google Earth Engine (GEE) platform and selects 10 waterbody extraction algorithms as the basis to realize the quantitative evaluation of QTP lake waterbody area extraction results. The results show that the Random Forest (RF) algorithm performs best in all models. The overall accuracy of waterbody extraction is 95.84%, and the average error of lake waterbody area extraction is 1.505%. Among the traditional threshold segmentation waterbody extraction algorithms, the overall accuracy of the NDWI waterbody extraction method is 89.89%, and the average error of lake waterbody area extraction is 3.501%, which is the highest performance model in this kind of algorithms. This study proves that Landsat-9 data can effectively classify QTP waterbodies. With the development of cloud computing technologies such as Gee, more complex models such as RF can be selected to improve the extraction accuracy of water body and Lake area in large-scale research.

This study investigated the influence of land-use and precipitation change and variability on Lake Victoria’s water-level fluctuations. Extreme precipitation events, corresponding to extreme water-levels, over the lake and its catchment area were identified and their return periods estimated by fitting them into a generalized extreme value (GEV) distribution. Using general circulation models from the 6^th phase of the Coupled Model Intercomparison Project (CMIP6)’s Detection & Attribution Model Intercomparison Project (DAMIP), an assessment of the potential contribution of human-induced climate change on the observed precipitation patterns over the study area was done. The greatest precipitation anomalies for the period 1900-2020 were recorded in 1961’s October-December (OND) season and 2019’s June-August (JJA) and OND seasons, corresponding to the period when the highest water-levels were recorded in Lake Victoria. While land-use change in the study domain was observed, extended and unusually heavy June to December 2019 precipitation bore the greatest responsibility for the 2019/2020 high water-levels in Lake Victoria. The OND precipitation event of 2019 was a 1-in-52-year event compared to the 1961’s 1-in-693 years. Differences in return periods at various parts of the lake imply a high spatial climate variability within the lake itself. An analysis of the fraction of attributable risk (FAR) showed natural variability to have a greater influence on the JJA and OND precipitation patterns over Lake Victoria than human-induced climate change. However, variability over the land area of the study domain was mainly driven by human-induced climate change rather than natural variability, implying a unique climate system over Lake Victoria. Findings from the current study enhance the understanding of Lake Victoria’s water budget and motivate for further research to inform effective strategies on the planning and use of Lake Victoria’s water resources in a changing climate.

Lake Malombe fish stocks have been depleted by chronic overfishing. Various management approaches (co-management, command control, and ecosystem-based management to fisheries) have been used to manage the fishery. However, the lack of an accurate predictive model has hampered their success. Therefore, we developed and tested a time series model for Lake Malombe fishery. The seasonal fish biomass and CPUE trends were first observed and both were non-stationary. The second-order differencing was applied to transform the non-stationary data into stationary. Autocorrelation functions (AC), partial autocorrelation function (PAC), and Akaike information criterion (AIC) were estimated, which led to the identification and construction of autoregressive integrated moving average (ARIMA) models, suitable in explaining the time series and forecasting. The results showed that ARIMA (1,2,1) provided a better prediction than its counterparts. The model satisfactorily predicted that by 2032, both fish biomass and CPUE will decrease to 3204.6 tons and 59.672 respectively, signifying the potential threat to Lake Malombe fishery. The model justified the necessity of taking precautionary measures to avoid the total collapse of the fishery.

Environmental isolates, genetically manipulated organisms, plants, animals and their products and economical methods are being expertly explored to biosynthesize poly-3-hydroxybutyrate plastics of comparable properties to petroplastics. This study assessed a hypothesized feasibility of utilizing a proliferative pleustophytic greenery, water hyacinth (Eichhornia crassipes (Mart.) Solms-Laubach) in Lake Victoria, Uganda as a potential carbon source for poly-3-hydroxybutyrate biosynthesis. The poly-3-hydroxybutyrate biosynthesizing bacteria (Bacillus megaterium) was isolated from municipal sewage sludge and harnessed for batch fermentation of acid-catalysed water hyacinth biomass. Poly-3-hydroxybutyrate formed in the cytoplasm of the bacterial cells was extracted by chloroform extraction method, and thereof confirmed and quantified by UV spectroscopy. Batch fermentation was carried out in 100ml of the culture media in a 250ml fermenter for different times (48, 96, 144 and 192 hours) to determine the best incubation time for maximum yield. An all-out net yield of 61.3% was realized after 96 hours of fermentation. Utilization of this ecological plague for poly-3-hydroxybutyrate biosynthesis is a promising strategy for regulating the weed population along the length of Nile River and the Victorian basin.

LULC changes are major environmental challenges in many parts of the world which are adversely affecting ecosystem services. This study was aimed to analyze LULC changes in the ecological landscape of Ethiopia CRV areas from 1985 to 2015. Satellite images were accessed and pre-processing and classification is done. Major LULC types were detected and change analysis was executed. Nine LULC changes were successfully evaluated. The classification result revealed that in 1985, 44.34% of the land was covered with small scale farming followed by mixed cultivated/acacia (21.89%), open woodland (11.96%), and water bodies (9.77%). Whereas for the same study year open grazing land, forest, degraded savannah and settlements accounted the smallest proportion. Though the area varied among land use classes, the trend of share occupied by the LULC types in the study area remained the same in 1995 and 2015. Increase in small and large scale farming, settlements and mixed cultivation/acacia while a decrease in water bodies, forest, and open woodlands is noted. About 86.11% of the land showed major changes in land use/cover. Lastly, DPSIR framework analysis was done and integrated land use and development planning and policy reform are suggested for sustainable land use planning and management.

Volcanic emissions (ash, gas, aerosols) dispersed in the atmosphere during explosive eruptions generate hazards affecting aviation, human health, air quality and the environment. We document for the first time the contamination of airspace by very fine volcanic ash due to sequences of tran-sient ash plumes from Mount Etna. The atmospheric dispersal of sub-10 μm (PM10) ash is mod-elled using the WRF-Chem model coupled online with meteorology and aerosols and offline with Mass Eruption Rates (MER) derived from near-vent Doppler radar measurements and inferred plume altitudes. We analyse two sequences of paroxysms with widely varied volcanological conditions and contrasted meteorological synoptic patterns in October–December 2013 and on 3-5 December 2015. We analyse the PM10 ash dispersal simulation maps in terms of time-averaged columnar ash density, concentration at specified flight levels averaged over the entire sequence interval, and daily average concentration during selected paroxysm days at these flight levels. The very fine ash from such eruption sequences is shown to easily contaminate the airspace around the volcano within a radius of about 1000 km in a matter of a few days. Synoptic patterns with relatively weak tropospheric currents lead to the accumulation of PM10 ash at a re-gional scale all around Etna. In this context, closely interspersed paroxysms tend to accumulate very fine ash more diffusively in the lower troposphere and in stretched ash clouds higher up in the troposphere. Low-pressure, high-winds weather systems tend to stretch ash clouds into ~100 km-wide clouds forming large-scale vortices 800-1600 km in diameter. Daily average PM10 ash concentrations commonly exceed the aviation hazard threshold up to 1000 km downwind from the volcano and up to the upper troposphere for intense paroxysms. Vertical distributions show ash cloud thicknesses in the range 0.7–3 km, and PM10 sometimes stagnating at ground level, represent a potential health hazard.

During the night between 9 and 10 September 2017, multiple flash floods associated to a heavy-precipitation event affected the town of Livorno, located in Tuscany, Italy. Accumulated precipitation exceeding 200 mm in two hours, associated with a return period higher than 200 years, caused all the largest streams of the Livorno municipality to flood several areas of the town. We used the limited-area Weather Research and Forecasting (WRF) model, in a convection-permitting setup, to reconstruct the extreme event leading to the flash floods. We evaluated possible forecasting improvements emerging from the assimilation of local ground stations and X- and S-band radar data into the WRF, using the configuration operational at the meteorological center of Tuscany region (LaMMA) at the time of the event. Simulations were verified against weather station observations, through an innovative method aimed at disentangling the positioning and intensity errors of precipitation forecasts. By providing more accurate descriptions of the low-level flow and a better assessment of the atmospheric water vapour, the results demonstrate that assimilating radar data improved the quantitative precipitation forecasts.

Human disturbances can have severe environmental impacts on freshwater ecosystems. The main aim of this study was to detect the influences of physiochemical variables, land-cover characteristics, and river connectivity on fish assemblages in Lake Chaohu Basin, China. A cluster analysis of the river connectivity variables identified four groups of sites that characterized by significantly different connectivity gradients in local scale. These four groups of sites showed increasing connectivity from the upper reaches to the lower reaches. At the same time, among the four groups, the values of the environmental variables generally increased from the upper reaches with less human activity towards the lower reaches with more human activities. For instance, some main physiochemical variables (e.g., river width, water depth, nitrate, phosphate) significantly increased among the four groups. In contrast, fish taxa richness and diversity indices were not significantly different among the four connectivity groups. However, fish assemblages showed significant variation among the connectivity groups (p=0.026). In addition, the study determined that upper riparian land uses (e.g., woodland and grassland), flow velocity, and elevation were environmental variables regulating the variance in the fish communities, and for the connectivity variables, only river order and number of branches along a path to the left of the main stem affected the variance in the fish communities. Therefore, new practices aimed at maintaining and even increasing the riparian canopy coverage and the flow velocity of rivers should be integrated into local conservation planning for freshwater ecosystems, especially in the upper reaches of the basin.

Tilapia tilapinevirus, or tilapia lake virus (TiLV), is a virus that has caused disease outbreaks in many countries worldwide since 2009. We recently developed two simple but effective TiLV vaccines based on heat-killed virus (HKV) and formalin-killed virus (FKV). In the present study, we evaluated the immunological response and efficacy of MontanideTM ISA 763A VG oil-based vaccines (O-HKV and O-FKV) in Nile tilapia (Oreochromis niloticus) and compared these responses in fish vaccinated with water-based formulations (W-HKV and W-FKV). Juvenile Nile tilapia were given primary and booster vaccinations with the vaccine formulations. The relative fold change in expression of five immunoglobulin genes (IgM, IgT, IgD, CD4 and CD8) was assessed before and after booster vaccination, and a challenge with TiLV was performed to evaluate the efficacy of the vaccines. The results showed that the water-based vaccines induced higher levels of Ig transcripts and conferred significantly higher levels of protection compared to the oil-based formulations, with relative percent survival (RPS) values ranging from 54.6% to 59.7% for W-HKV and W-FKV vaccinated fish, and 32% and 0% for the O-HKV and O-FKV vaccinated fish, respectively. These findings suggest that water-based vaccines are more effective at protecting tilapia against TiLV infection, and MontanideTM ISA 763A VG may not be a suitable adjuvant for formulating whole-inactivated TiLV vaccines.

Ancient lakes are among the most interesting models for evolution studies, because their biodiversity is the result of a complex combination of migration and speciation. Here, we investigate the origin of single celled planktonic eukaryotes from the oldest lake in the world – Lake Baikal. By using 18S rDNA metabarcoding we recovered 1,427 Operational Taxonomic Units (OTUs) belonging to protists populating surface waters (1-50 meters) and belonging to pico- and nano-plankton size fractions. The recovered communities resembled other lacustrine freshwater assemblages found elsewhere, especially the unclassified protists. However, our results suggest that a fraction of Baikal protists originated evolutionary recently from marine/brackish ancestors. Moreover, our results suggest that rapid radiation may have occurred among some protist taxa, partially mirroring what was already shown for multicellular organisms in Lake Baikal. We found potential species flocks in Stramenopiles, Alveolata, Opisthokonta, Archaeplastida, Rhizaria and Hacrobia. Putative flocks predominated in Chrysophytes, which are highly diverse in Lake Baikal. Some of the species, especially those from these flocks, may be endemic from Lake Baikal, because their 18S rDNA differed > 10% from known DNA. Overall, our study points to novel diversity of planktonic protists in Lake Baikal, some of which may have emerged in situ after evolutionary diversification.

ABSTRACT This study focused for socio-economic benefit of Western shoreline of Lake Ziway ecosystem. The data collected from two woredas they are Adami Tulu Jidu Kombolch (ATJK) and Dugda woreda of fishermen and small scale irrigation users. Lake Ziway great importance food and water for both groups of respondents and additionally sources of raw material, energy, cultivation, organic fertilizers, genetic and medicinal plants. Lake Ziway also has a major economic benefit for both groups of respondents. The sampled fishermen cached mean amount of 2,524Kg per year with minimum and maximum amount of fish 504Kg and 16,800Kg per year respectively and with this fish catching they got average income of 51,398 Birr ($2,570) per year with range of 7,200 Birr ($360) and 288,000 Birr ($14,400) per year. As like of fishermen small scale irrigation also got economic benefit with their production of cereal crops, fruits and vegetables. They produce in average 13.47Quintal of cereal crop and 69.56Quintal of fruits and vegetables per year and they got average income of 7,727 Birr ($386) and with range of 13,714 Birr ($686) per year respectively. this incurred that wetland ecosystem has a lot of socio-economic benefit for the people live near by specially for developing countries like Ethiopia they are more dependent on natural ecosystem like of Lake Ziway. Because of its high importance, we have to protect and conserve and use sustainably of Lake Ziway and similar wetland ecosystems. Key Words: Wetland ecosystem service; Lake Ziway; Socioeconomic benefit; Fishermen; Small scale irrigation users

From June 18 to 19, 2013, the Ésera river in the Pyrenees, Northern Spain, caused widespread damage due to flooding as a result of torrential rains and sustained snowmelt. We estimate the contribution of snow melt to total discharge applying a snow energy balance to the catchment. Precipitation is derived from sparse local measurements and the WRF-ARW model over three nested domains, down to a grid cell size of 2 km. Temperature profiles, precipitation and precipitation gradient are well simulated, although with a possible displacement regarding the observations. Snowpack melting was correctly reproduced and verified in three instrumented sites, and according to satellite images. We found that the hydrological simulations agree well with measured discharge. Snowmelt represented 33% of total runoff during the main flood event and 23% at peak flow. The snow energy balance model indicates that most of the energy for snow melt during the day of maximum precipitation came from turbulent fluxes. This approach forecast correctly peak flow and discharge during normal conditions at least 24h in advance and could give an early warning of the extreme event 2.5 days before.

Remote sensing methods have the potential to improve lake water quality monitoring and deci-sion-making in water management. This reviews introduces novel findings in the field of opti-cally active water quality parameters using remote sensing. It summarizes existing retrieval methods (analytical, semi-analytical, empirical, semi-empirical, and artificial intelli-gence/machine learning (AI/ML)), examines measurement methods used to determine concen-tration of specific water quality parameters, summarizes satellite systems that enable temporal data for understanding the state of the lake with focus on water quality parameters, and pro-poses enhancements for future research of lake water quality using remote sensing. As part of this review, eight optically active biological and physical water quality parameters were ana-lyzed, including chlorophyll-α (chl-α), transparency (Secchi disk depth (SDD)), colored dis-solved organic matters (CDOM), turbidity (TUR), electrical conductivity (EC), surface salinity (SS), total suspended matter (TSM), and water temperature (WT). The research proposes a shift from point-based data representation to a more reliable raster representation and encourages optimizing grid selection for in situ measurements by combining hydrodynamic model with re-mote sensing methods. This review presents a comprehensive summary of the bands, band combinations, and band equations per sensor for eight optically active water quality parameters as listed in Tables A1-A8. The review’s findings indicate that use of remotely sensed data is an effective method for estimating water quality parameters in lakes, with a significant increase in global utilization. The review highlights potential solutions and limitations to the challenges of remote sensing water quality determination in lakes.

There is little information about moisture changes in different altitudinal belts in mountainous regions of the Southern Russian Far East. We present ecological-taxonomic composition of the diatom flora, the botanical composition of peat of small mountain lake/mire complexes located in the Central Sikhote-Alin within large landslides on the paleovolcano slopes are identified. Frequent changes in diatom assemblages and peat-forming plants indicate unstable hydroclimatic conditions with varying degrees of watering and dry condition up to complete overgrowth of the lakes. Frequent change of sphagnum mosses with different trophic preferences was established. The chronology is based on 11 radiocarbon dates. Accumulation rates reached up to 1.9 mm/year, the temporal resolution for the reconstructions is up to 30–40 years. The tendencies of lake evolution depended on different-scale hydroclimatic changes for the last 4400 yr. The most detailed data for the last 2600 yr were obtained from the Nizhnee Lake sequence, more sensitive to climatic changes. The main reason for the change in the hydrological regime of the lakes was variations in precipitation during short-term climatic changes. The sediment record moisture fluctuations are relatively well correlated with regional patterns reflecting summer monsoon intensity and cyclogenesis activity.

The article reviews the constituent’s physico-chemical parameters in the water of the Mansagar Lake of the Jaipur City. The water quality is also investigated using evaluated physico-chemical parameters with in-depth study of their distribution as per sample location-wise and season-wise. A detailed discussion on the associationship among parameters (pH, Conductivity, turbidity, dissolved Oxygen, chemical and Biochemical Oxygen demand, etc.) using the Pearson’s analytical method is also presented. The strength of the article is the graphical presentation of evaluated physico-chemical parameters and the water quality indices for sample station-wise and the season-wise. To our best of understanding, first time such details have been clubbed together and discussion in brief for studied lake.

Human-driven biodiversity destruction are responsible for significant and sustained heritage losses in Africa. In Venda, northern South Africa, biodiversity losses are eroding the existence of sacred places. Such places define the essence of indigenous people’s identity and well-being. We highlight how developments in Venda such as mining and agricultural expansion since apartheid times have destroyed biodiversity in the broader landscape, undermining efforts to reduce hunger and poverty. Thathe forest, Lake Fundudzi and Phiphidi waterfalls are central to Venda mythology and legends, origins and identity and are key towards conserving current biodiversity and heritage losses.

Although sources of seston are much more complicated in lakes compared to marines, the influences of different source on the spatiotemporal variations in seston stoichiometry are still underexplored, especially in large eutrophic floodplain lakes. Here, we investigated the seston stoichiometry across a typical large eutrophic floodplain lake (Lake Taihu) over one year. In addition, we used the n-alkanes proxies for source estimation which are more robust than other elemental indicators (e.g. C: N ratios). Throughout the study, the average value of C: N: P ratio of 143: 19: 1 across Lake Taihu was higher than the classical Redfield ratio, but closed to the synthesized data from other lakes. Generally, seston C: N ratios varied the least across all environments, but C: P and N: P ratios varied widely and shown a significant seasonal pattern with lower ratios of N: P and C: P during senescence seasons and higher ratios in the growing seasons. This seasonal change was mainly associated with the shift from terrestrial-derived seston to algal-derived seston as, the significant lower ratios of terrestrial-derived seston from surrounding agricultural watershed. Spatially, the mean ratios of each site were similar, except relative high values of C: P and N: P ratios in the algal dominated area. Statistically, the predictive power of environmental variables was strongly improved by adding n-alkanes proxies. However, apart from sources indicators, particulate phosphorus (PP) contents also partly explained the spatiotemporal variations in stoichiometric ratios. Nevertheless, the mechanisms behind the dynamics of PP could be totally different and source-specific. This study highlights the priority of using n-alkanes proxies as tools to identify the source of seston which is essential to interpret the spatiotemporal variations in seston stoichiometric ratios among eutrophic floodplain lakes.

This study presents an analysis of the spatial and temporal distribution of the two large destructive earthquakes that occurred in Lake Van area on October 23, and November 9, 2011, together with the azimuth-dependent distribution of the seismic activity and microseismicity clusters after the mainshocks, associated with the complex rupture processes of their aftershock sequence. The sequence began with the magnitude Mw 7.1 earthquake of 23 October and a second destructive earthquake of Mw 5.6. The aftershock sequences of the two mainshocks were linked to the local crustal faults beneath Lake Van area, followed successively and produced unusually intense activity and significant damage in the area. The main purposes of this study are to document the spatial and temporal distribution and evolution of the October 23, 2011 aftershock hypocenters and the azimuth-dependent distribution of seismic activity, and to understand the spatial and temporal character of the aftershock sequence using the distributional and evolutional patterns of the aftershock hypocenters. A total of 10,000 aftershocks were obtained from seismic data with a high signal-to-noise ratio over collected over three years from October 23, 2011 to March 2014. These aftershocks were plotted for the time periods from November 2011 through March 2012 to March 2014 and ≈ 5000 aftershocks were retained in the depth versus distance cross-sections to detect the clusters in the first step of study (November 2011–March 2012). The focal depth distribution of the aftershock clusters, the migration of hypocenter activity and microseismicity clusters were analyzed and the distributional patterns of the detected clusters were assessed using the geometric distribution of the aftershock hypocenters. The spatial and temporal distribution of aftershocks reveal interesting key features of the deep rupture complexity of the Van earthquake: (1) most prominent aftershocks have been located in the upper crust at depths shallower than 10 km beneath ruptured area, indicating that the upper crust is brittle and seismogenic; (2) two spatial clusters have been detected at 8-10 km depths and the upward extrapolation of these clusters intersects with faults; the main cluster (60 km wide) bounded by inferred reverse faults (f3 and f4) and the central cluster (25–30 km wide) bounded by faults (f1 and f2); (3) these spatial clusters form the largest volumetric pattern of the conical-shaped cluster at depths of about 25–30 km of the azimuth-dependent rotational projections, suggesting azimuthal distributions of deep rupture characteristics; and (4) the strongest temporal cluster of microseismicity derived from temporal distribution of aftershocks has been detected within an area of about 2.5–3.0 km² and it is spatially observed at 20 km depth within the central cluster, suggesting progressive failure of the adjacent patches of possible fault.

A three-dimensional, unstructured grid, hydrodynamic and suspended-sediment transport model (i.e., SELFE-SED) was developed to simulate temporal and spatial variations of suspended sediment and was applied to the subtropical subalpine Tsuei-Feng Lake (TFL) of Taiwan. The model was validated with measured water level and suspended‑sediment concentration in 2009, 2010, and 2011. The overall model simulation results are in quantitative agreement with the observational data. The validated model was then applied to explore the most important parameter that affects the suspended-sediment concentration and to investigate the effect of wind stress on the mean current and suspended‑sediment distribution in this shallow lake. Modeling results of sensitivity analysis reveal that the settling velocity is a crucial parameter and erosion rate is less important in the suspended-sediment transport model. Remarkable lake circulation was found based on the strength of wind speed and wind direction. Strong wind would result in higher mean current in the top layer and suspended-sediment distribution in the top and bottom layers. This study demonstrated that the wind stress played a significant influence on mean circulation and suspended-sediment transport in a shallow lake.

The Source Region of the Yellow River (SRYR), renowned as the "Water Tower of the Yellow River", serves as an important water conservation domain in the upper reaches of the Yellow River, significantly influencing water resources within the basin. Based on the Weather Research and Forecasting (WRF) Model Hydrological modeling system (WRF-Hydro) model, the key variables of the atmosphere-land-hydrology coupling processes over the SRYR during the 2013 rainy season are analyzed. The investigation involves a comparative analysis between the coupled WRF-Hydro and the standalone WRF simulations, focusing on the hydrological response to the atmosphere. The results reveal that the WRF-Hydro model's proficiency in depicting streamflow variations over the SRYR, yielding a Nash Efficiency Coefficient (NSE) of 0.44 and of  0.61 during the calibration and validation periods, respectively. Compared to the standalone WRF simulations, the coupled WRF-Hydro model demonstrates enhanced performance in soil heat fluxes simulations, reducing the mean Root Mean Square Error (RMSE) of surface soil temperature by 0.96 K and soil moisture by 0.01 m\textsuperscript{\textsuperscript{3}}/m\textsuperscript{\textsuperscript{3}}. Furthermore, the coupled model adeptly captures the streamflow variation characteristics with the NSE of 0.33. This underscores the significant potential of the coupled WRF-Hydro model for delineating coupled atmosphere-land-hydrology processes in regions characterized by cold climates and intricate topography.

Accurately predicting the power of solar power generation can greatly reduce the impact of the randomness and volatility of power generation on the stability of the power grid system, which is beneficial for the balanced operation and optimized dispatch of the power grid system, and reduces operating costs. Solar PV power generation depends on weather conditions, which are prone to large fluctuations under different weather conditions. Its power generation is characterized by randomness, volatility and intermittency. Recently, the demand for further investigation and effective use on the uncertainty of short-term solar PV power generation prediction has been getting increasing attention in many application of renewable energy sources. In order to improve the predictive accuracy of output power of solar PV power generation and develop a precise predictive model, the authors worked predictive algorithms for the output power of a solar PV power generation system. Moreover, since short-term solar PV power forecasting is one of the important aspects for optimizing the operation and control of renewable energy systems and electricity markets, this review focuses on the predictive models of solar PV power generation, which can be verified in the daily planning and operation of a smart grid system. In addition, the predictive methods in the reviewed literature are classified according to the input data source used for accurate predictive models, and the case studies and examples proposed are analyzed in detail. The contributions, advantages and disadvantages of the predictive probabilistic methods are compared. Finally, the future studies of short-term solar PV power forecasting is proposed.

We found out main regularities of surface waters pollution by diesters of о-phthalic acid (PAEs) at the background level of concentrations. Lake Baikal was selected as a model for our studies. The composition of PAEs in Baicalins waters is represented by dimethyl phthalate (DMP), diethyl phthalate (DEP), di-n-butyl phthalate (DnBP), and di-(2-ethylhexyl) phthalate (DEHP). Their concentrations are assessed in statistically valuable average values and ranges: 0.02 (0.01 – 0.02), 0.07 (0.06 – 0.09), 0.55 (0.47 – 0.66), 0.30 (0.26 – 0.34), µg/L, respectively. Main factors determining PAEs concentration are found out: year and season of sampling. The distribution of PAEs in the water body meets their hydrophobicity and is characterized by: i) even distribution of minor hydrophilic congeners DMP and DEP in the whole water area; ii) maximal concentrations of hydrophobic congeners DnBP and DEHP in the upper and near-bottom layers of the water column; iii) decrease of concentration of hydrophobic congeners in the near-shore zone. The contribution of near-shore sources of PAEs into the pelagic site is minimal, the main pollutants source is atmospheric transfer. A valuable contribution of DEHP from biogenic sources into the background level of PAEs is shown. Within RQ coefficients, we assessed the environmental risk for Baicalins biota.

Hydrological connectivity plays a major role in solving water resource and eco-environmental problems. However, this phenomenon has not been afforded the attention it deserves. Detailed analysis of connectivity in river systems could provide considerable insight into structural and functional attributes of riverine landscapes. The current study used graph theory approach and associated connectivity indicators to explore the characteristics and evolution of river systems and hydrological connectivity in a large catchment (Poyang Lake, China). The results revealed that the structure of the river system tended to be complex during 1990-2020, characterized by a dynamic evolution of tributaries in certain northern areas. Both river density and complexity exhibited an increasing trend by up to 15%, with the change rate after 2000 approximately twice as high as that of the preceding period. Overall, human activities across the catchment are more likely to play a key role in leading to significant changes in the quantity, morphometric, and structure characteristics of the river system. Additionally, the functional connectivity analysis indicated that the index of connectivity (IC) in the downstream catchment is stronger than that of the upstream vegetation areas, suggesting a strong contribution to the runoff-sediment transport (r=0.6-0.7). This study highlights the spatial and temporal evolution of both the structural and functional connectivity in the large Poyang Lake catchment. The findings of this work will bene-fit future water resource management and applications by providing a strategy for protecting the surface hydrology and mass transport of large river basins under climate and land-use changes.

In this paper we study solutions and drift homogenization for a class of viscous lake equations by using the method of semigroups of bounded operators. Suppose that the initial value i.e.,for some Hölder continuous function onwith smooth function value satisfying and Then the initial value problem (2) for viscous lake equations has a unique smooth local strong solution. Using this result we study the drift homogenization for three-dimensional stationary Stokes equation in the usual sense

As one of the unique destinations in Iran, Abdanan Black Twin Lake attracts many tourists yearly. Among striking features is the presence of minerals, boiling springs, and its beautiful landscape. Human beings are willing to spend money on such natural resources. An economic valuation can be interfered constructively and positively in improving environmental policies. So, quantifying these benefits is of the utmost importance. The paper mainly estimated the tourists' willingness to pay and their recreational value using the contingent valuation method. Random sampling was conducted on 384 people using the two-dimensional double-choice questionnaire in spring 2019. In the Twin Lake Recreational Value Questionnaire, the main questions were devoted to the visitors' willingness to pay, with three bids of 0.07 $, 0.14 $, and 0.22$. Among 384 respondents, 304 (79%) were willing to pay for recreational use of the lake, and 80 respondents (21%) were not. The likelihood, the model's parameters were estimated. The findings indicated the average tourists' willingness to pay for recreational value was estimated at 0.09$ per visit and the recreational value of this lake for each household was estimated at 0.40$. The findings revealed the effect of education, household income, household size and tourists' willingness to pay was significant.

This study describes the seasonal course of denitrifying and nitrate reducing bacteria in a dimictic mesotrophic lake (Lake Scharmützelsee, Brandenburg, Germany) within a three-year period from 2011 to 2013. The bacterial cell numbers were quantified by fluorescence microscopy, most probable number (MPN) and PCR dependent quantification of the chromosomal 16S rDNA and of the nirS and nirK gene copy number. The highest seasonal differences (up to three orders of magnitudes) has been measured by MPN in the epilimnion. This variation was not reflected by PCR dependent approaches or direct microscopical enumeration. At adverse conditions (low temperature and/or low nitrate concentrations), the differences between MPN and gene copy numbers increased up to five orders of magnitudes and decreased to one magnitude at favorable environmental conditions. These results can be explained best by an increasing ratio of viable but not cultivable (VBNC) cells or dead cells at impairing conditions. In the hypolimnion, the courses of MPN and nir gene copy numbers were similar. This can be explained by higher feeding pressure and therefore smaller amounts of dormant cells. In the pelagial in general, the total cell numbers enumerated by either microscopical or molecular approaches were similar. In the sediment, more than 99 % of the DNA was obviously not related to viable bacteria but was rather “dead DNA” in dead cells or adsorbed to particle surfaces.

Flood records of the Kunmalik River in Chinese Tien Shan mountains have showed that glacier- dammed lake outburst floods (GLOF) had occurred almost every year since 1956 from the glaci-er-dammed Lake Merzbacher. However, GLOF in cold season is seldomly studied. The defense and management of the flood need further observation and study. The maximum peak discharge of 825 m3/s occurred on 5th December 1996 with the maximum flood volume of 2.875×108 m3, which was 18 times larger than that of the mean daily discharge in winter over the past six decades. The drainage of the Merzbacher lake is not a mechanical breaking up of the glacier dam, but the release of pressurized water along a subglacial tunnel triggered by quickly surge of the Northern Glacier, the subglacial tunnels are enlarged by both ice melting and frictional heat in the flooding water and heat under the glaciated dam and the lake in winter. There is no correlation between the GLOF size and air temperature of cold season. The floods in cold season have become bigger since 1996 than that before, and the flood duration has been extended from winter to spring. Once the cold GLOF starts, its discharge can be forecasted day by day to extrapolate the monitoring hydrograph as a linear curve.