Abstract: Ningbo (NGB), one of the world's most important port cities located on the East Coast of China, contains more than 100 rivers and streams across three major catchments, the Yong, Yuyao and Fenghua Rivers. During the 1970s – 2000s, extensive river engineering, including channelisation, conversion of natural rivers into artificial canals, and construction of sluice gates and embankments were undertaken to cope with rapid urbanisation and development. Since the 2010s, the Ningbo Government and Water Bureau have initiated smart river and fluvial flood management strategies to enhance digital twins and smart flood management technologies, such as 3D flood mapping and real-time water level and discharge monitoring, significantly improving precision. In this study, we demonstrate that smart technology has performed effectively in Ningbo, with applications in the recent climate extreme events such as Typhoon In-Fa and Muihua in 2021 and 2022, during which the Municipal Bureau has safeguarded public safety and welfare. This further strengthening both municipal and national commitment to enhance climate resilience. Nevertheless, further advancement of the DT platform remains necessary. Key areas for improvement include faster computational capacity, enhanced coordination across departments and open data sharing mechanisms, and integration of artificial intelligence (AI) to support more effective decision-making processes in response to the climate extremes and adverse water hazards conditions.

Abstract: The toxic effects of fluorides on aquatic organisms have raised widespread concerns on their pollution in water bodies. This study derived water quality criteria for fluorides by collecting acute and chronic toxicity data globally and conducted an ecological risk assessment of fluoride concentrations in China's surface water: the acute toxicity data covered 34 species across 14 families and 4 phyla, while the chronic toxicity data covered 7 species across 5 families and 3 phyla; Using the species sensitivity distribution (SSD), the water quality criteria SWQC and LWQC were determined to be 17.47 mg/L and 3.334 mg/L, respectively; An ecological risk assessment of fluoride concentrations in China's surface water was conducted using the risk quotient (RQ), identifying the Shahe River, Xihe River, Ebinur Lake, and Chagan Lake as high risk areas among 32 river and lake basins. Among 21 provincial-level administrative regions, the Guangxi Zhuang Autonomous Region was assessed as no risk, while the remaining river and lake basins and administrative regions were classified as moderate risk or low risk. The findings of this study can serve as a reference for subsequent research and detailed optimization in related fields.

Abstract: Rapid urbanization has intensified challenges in urban water management, highlighting the growing importance of sponge city development. However, at present, the unique role of groundwater aquifers in regulating the water cycle process has been ignored, and overly simplistic construction methods are relied on. To address these limitations, this study introduces an integrated spatial optimization framework for urban-scale sponge ecosystems by coupling hydrodynamic modeling, ArcGIS-based spatial analysis, and Monte Carlo simulation. The framework systematically incorporates surface water depth, formation lithology, and groundwater depth to construct a comprehensive evaluation system for sponge ecological suitability. Shenzhen serves as the empirical case to demonstrate the framework’s applicability. Surface water depth is quantified using the Finite-Volume Community Ocean Model (FVCOM), while groundwater conditions are assessed through a calibrated groundwater model, thereby improving the scientific precision of ecological suitability evaluation. Leveraging GIS and Monte Carlo simulation, the study develops a streamlined yet robust methodology for optimizing the spatial configuration of sponge ecological infrastructure. Building on ecological redlines and protected areas, a landscape ecology–oriented matrix–corridor–patch analysis is applied to delineate ecologically suitable zones. Tailored planning and management strategies are subsequently formulated for each zone based on its ecological attributes. The findings offer methodological advances for sponge ecosystem construction and contribute to enhancing urban climate resilience and adaptive capacity under accelerating environmental change.

Abstract:

Driving rain or ‘wind-driven rain’ (WDR) arrives at the ground on an oblique trajectory, and drops may strike at a speed greater than their still-air terminal velocity. Oblique rain can affect a range of geomorphic processes including the splash dislodgment and transport of soil particles, and hydrological processes including overland flow, canopy interception and the generation of stemflow. The mean rain inclination angle at which WDR strikes the ground has been estimated from the catch of paired gauges, one with a conventional horizontal orifice, and one with a vertical orifice. Such data allow the resolution of rain vectors to find the rain inclination. This can only be carried out over periods sufficiently long for a measurable rain depth to be measured, and does not permit the real-time recording of rain inclination. Here, a new acoustic method for measuring rain inclination is introduced that provides an inexpensive tool for the continuous, real-time monitoring of WDR. Furthermore, the method also permits the simultaneous recording of rainfall duration and intermittency at high temporal resolution, with no additional apparatus. Data on rain inclinations collected during showers on a tropical coast exposed to strong trade-winds are presented to illustrate the operation of the acoustic measurement system. However, the focus of this paper is the presentation of the new method itself, and not on the climatology of WDR.

Abstract: Leachate in landfills becomes difficult to treat due to its complex and widely variable composition, containing a large amount of organic, inorganic substances and heavy metals. When it seeps into the ground, leachate pollutes groundwater, and if discharged into surface water, it will harm the aquatic environment in the corresponding area. Therefore, it is extremely necessary to treat leachate before discharging it into the environment to prevent this negative impact. In this study, a lab-scale A2O (Anaerobic–Anoxic–Oxic) system integrated with a Moving Bed Biological Reactor (MBBR) was established. We evaluated key water quality indicators of wastewater pretreated by internal electrolysis, the effluent from the A2O–MBBR system, and the combined treatment process. The wastewater was taken from Nam Son landfill, Soc Son, Hanoi, in Viet Nam. COD, BOD5, NH4+-N, and pH of the input leachate wastewater were 2140 mg/L, 250 mg/L, 895 mg/L, and 8 ± 0.5, respectively. The conditions of internal electrolysis were as follows: 120 minutes of reaction time, pH =4, 4.0 g/L Fe/Cu dosage and 100 mg/L PAM dosage. Following the internal electrolysis pretreatment, the removal efficiencies of COD, BOD₅, and NH₄⁺–N reached 49.0%, 4.8%, and 11.2%, respectively. After 24 hours of operation, the integrated treatment process exhibited markedly enhanced performance, achieving removal rates of 85.0% for COD, 85.2% for BOD₅, 94.1% for total nitrogen, 98.0% for total phosphorus, and 96.7% for NH₄⁺–N. These results demonstrate the high synergistic efficiency of the combined internal electrolysis–A₂O–MBBR system. Furthermore, all post-treatment parameters complied with the Vietnamese standard QCVN 40:2011/BTNMT (Column B2) for leachate wastewater, confirming its effectiveness and environmental suitability.

Abstract: Flood susceptibility mapping is crucial for understanding flood-prone areas and mitigating the associated risks, particularly in vulnerable regions like the Sebeya Catchment. This study has adopted a GIS-AHP approach integrated with local community knowledge over flood susceptibility factors such as Topographic Wetness Index (WTI), Digital Elevation Model (DEM), Precipitation, Slope, Land Use/ Land Cover (LULC), Normalized Vegetative Index (NDVI), Distance to Roads, Distance to River, and Drainage Density. The pairwise comparison matrix was used to determine each factor's weight according to its influence in inducing flood. The findings revealed that 33.1% of the total area has a very and high susceptibility to floods, whereas the rest part of the catchment is moderately susceptible to floods. Most social economic activities in this study are located in high-risk zones, which significantly to appearance of flooding impacts. Current study indicates that, damage to infrastructure, loss of livelihoods, displacement of communities, and increased costs of disaster response are key consequences observed in affected regions. A confusion matrix approach was employed to validate the flood susceptibility map, and the results indicate an overall accuracy of 0.92, confirming strong model performance and reliability. The study further proposes adaptive strategies and provides recommendations for enhancing flood resilience, including improvement in land-use planning, use of early warning systems, and sustainable catchment management. Further studies should develop an economic-loss prediction model based on flood-susceptibility mapping.

Abstract: Minerals extraction from brine solutions is a vital issue for resource recovery in many fields of industry, especially in desalination processes. Usually, the solubility limit is viewed as a key factor that plays a determinant role in the efficiency of a prescribed process. This paper suggests the investigation of the influence of ionic strength, which is a measure of the total concentration of all dissolved ions, on the solubility limits in brines that are extracted from desalination facilities in Kuwait before discharging them into the Arabian Gulf. This information may contribute to the optimisation of the extraction process, especially when treating complex brines with high salinity, and in the case of interest, the mineral extraction from the brine stream may result in the reduction of environmental risk. For this purpose, the solubility of two main minerals (CaSO4 and Mg(OH)2) was measured for several values of ionic strength achieved by adjusting the concentration of the brine solutions. Results show a non-linear relationship between ionic strength and the solubility limit of the target minerals, with behavior similar to that that could be found in the literature. In the case of CaSO4, it was found that the behavior of the solubility in the case of a diluted solution or low ionic strength is not the same as in the case of a brine solution; the latter has a reverse pattern. On the other hand, the solubility of Mg(OH)2 in Kuwait brine water was shown to decrease as the ionic strength of the brine solution decreased. Other minerals obtained by the extraction process are under analysis. The findings of this work provide crucial insights for process design, enabling more precise control over precipitation steps and enhancing the overall yield and economic viability of mineral extraction from complex brine resources.

Abstract: Contaminated water detoxification remains difficult due to the presence of persistent halo-organic contaminants, such as perfluorooctanoic acid (PFOA) and chlorophenols, which are chemically stable and resist conventional purification methods. Functionalized membrane-based separation and decontamination have garnered immense attention in recent years. Commercially available microfiltration membrane (PVDF) and polymeric non-woven fiber filters (glass and composite) are functionalized with Poly (methacrylic acid) (PMAA) that shows outstanding pH responsive performance and tunable water permeability under ambient conditions perfect for environmental applications. Polymer loading based on weight gain measurements on PMAA-Microglass composite fibers (137%) and Microglass fibers (116%) confirmed their extent of functionalization, which was significantly greater than that of PVDF membrane (25%) due to its wide effective pore diameter. Presence of chemically active hydrogel within PVDF matrix was validated by FTIR (hydroxyl/carbonyl) stretch peak, substantial decrease in contact angle (68.8° ± 0.5° to 30.8°± 1.9°), and decrease in pure water flux from 509 to 148 LMH/bar. Nanoparticles are generated both in solution and within PVDF membranes using simple redox reactions. This strategy is extended to PVDF-PMAA membranes, which are loaded with Fe/Pd nanoparticles for catalytic conversion of 4-chlorophenol and PFOA, forming Fe/Pd-PVDF-PMAA systems. 0.25 mg/L Fe/Pd nanoparticles synthesized in solution displayed alloy-type structures and demonstrated a strong catalytic performance, achieving complete hydrogenation of 4-chlorophenol to phenol and 67% hydrogenation of PFOA to its reduced form at 22-23 °C with ultrapure hydrogen gas supply at pH 5.7. These results underscore the potential of hybrid polymer–nanoparticle systems as a novel remediation strategy, integrating tunable separation with catalytic degradation to overcome the limitations of conventional water treatment methods.

Abstract: Japan has largely completed the “first half” of SDG 6—universal access to safe drinking water and sanitation—through decades of investment in water supply and sewerage systems, total pollutant load control and stringent regulation of industrial effluents. National indicators show that coverage of safely managed drinking water and sanitation services is close to 99%, and domestic statistics report high achievement rates of BOD/COD-based environmental standards in rivers, lakes and coastal waters [6–11]. At the same time, SDG 6.3.2 (good ambient water quality) remains at 57% and SDG 6.6.1 (extent of water-related ecosystems) shows a −2.8% change in permanent surface water area compared with the 2000–2019 baseline [9,12,13]. The present review synthesizes how far Japan has progressed towards SDG 6, why gaps remain in the “second half” of the goal and which policy pathways are most promising for a nature-positive water future. Using national statistics from the Ministry of the Environment and the Ministry of Land, Infrastructure, Transport and Tourism (1970–2023), UN-Water SDG 6 indicators and recent literature, we map domestic indicators onto the SDG 6 framework, analyse long-term trends in BOD/COD achievement rates and organise remaining challenges using the DPSIR (Drivers–Pressures–State–Impacts–Responses) perspective [2–4,8,9,17,29]. A simple structural break analysis confirms that improvement in BOD/COD achievement essentially stalled around 2002, reinforcing policy concerns that point-source measures alone can no longer deliver additional gains [8,22]. A comparison of SDG 6.3.2 with domestic environmental standard metrics explains why the former is systematically lower: multi-parameter assessment, stricter aggregation rules and greater sensitivity to nutrients and ecological conditions mean that water bodies passing BOD/COD standards may still fail under SDG 6.3.2 [8,9,13]. Building on this diagnosis, the review proposes six strategic directions—climate-resilient water systems, infrastructure renewal and smart asset management, advanced treatment and pollution prevention, integrated water resources management and governance, citizen participation and nature-based solutions (NbS) and green–gray hybrids—and summarises their expected contributions and constraints in a concise overview table [12–14,16,17,24,26]. Finally, we outline how integrated indicator dashboards and, in the longer term, basin-scale simulation platforms (“digital twins”) could help link SDG 6 indicators, domestic statistics and scenario analysis in a transparent, reproducible way [8,9,25,26]. The paper concludes with research and policy priorities for closing the remaining gaps in SDG 6.3 and 6.6 and for advancing towards a nature-positive water future.

Abstract: Despite the closure of the Semipalatinsk nuclear test site (STS) more than 30 years ago, the removal of radioactive contamination beyond the “Degelen” test site by water continues. Therefore, assessing the water resources formation at this test site is highly relevant, including for predicting the development of the radiation situation at the STS. In this case, isotope hydrology is the most promising method for understanding these processes. The aquatic environment at the “Degelen” test site consists of radioactively contaminated tunnel water, streams, and groundwater. The article presents the research results of the aquatic environment of the “Degelen” test site using the method of isotope hydrology with determination of stable isotopes of hydrogen and oxygen. The determination of the 3H concentration and the chemical composition of water were also determined. The analysis of the isotopic composition (δ2H, δ18O) of water showed that the tunnel and stream water are formed by precipitation (snow and rain). In summer, when precipitation is low, the condensation water significantly contributes to the recharge of “Degelen” test site water. The high radionuclide content of tunnel water leads to contamination to a greater extent of stream water, and, to the lesser extent, and groundwater. The 3H content in tunnel water can reach 260 kBq/L, in stream water – 58 kBq/L, which exceeds the standards established in the Republic of Kazakhstan.

Abstract: Groundwater resources management is a critical issue for populations in regions with significant growth. In arid and semiarid regions, where rainfall is scarce, groundwater is often the only source of water for all their needs. Nevertheless, groundwater characterization is virtually unknown in countries with limited infrastructure and resources. A short-term solution is to study groundwater through numerical simulation using the limited available data. We developed a GIS-integrated groundwater flow scheme based on the finite-difference method to numerically simulate a heterogeneous medium using surface geological information. We validate our implementation by comparing it with MODFLOW. We performed groundwater simulations of the Administrative Aquifer in Calera, Zacatecas, Mexico, using homogeneous and heterogeneous media to evaluate flow changes resulting from heterogeneities. We found that numerical simulations show flow barriers in low hydraulic-conductivity zones that coincide with the administrative boundaries of the aquifer; however, in high hydraulic-conductivity zones, the administrative aquifer boundaries do not match the geological limits of the aquifer. This finding gives insight into reconsidering the administrative boundaries of some aquifers in the region for their sustainability, with an integral understanding of groundwater.

Abstract: In this study, we investigated the impact of varying iron (Fe) and aluminum (Al) contents on the adsorption of phosphonates to activated sludge. Phosphonates originating from household applications account for up to 40% of the non-reactive dissolved phosphorus in domestic sewage treatment plants and thus can contribute to the eutrophication of water bodies. Although these substances are not readily degradable, substantial quantities, ranging from 40% to more than 90%, are removed by sludge adsorption.The results demonstrate a strong correlation between the adsorption of aminophosphonates and the Fe3+ content of the sludge. The maximum phosphonate loadings were 5.94 mmol g-1 Fe3+ for ATMP, 4.94 mmol g-1 Fe3+ for EDTMP and 4.74 mmol g-1 Fe3+ for DTPMP, and 2.25 mmol g-1 Fe3+ for Glyphosate. In contrast to pure ferric hydride flocs, the adsorption of phosphonates was approximately threefold higher when the hydroxides were located within activated sludge flocs. It is concluded that native sludge flocs provide larger iron surfaces than ferric hydroxide alone. Based on the weight of the adsorbents, aluminum salts were four times less efficient than ferric salts. In sludge without ferric or aluminum hydroxides, phosphonate adsorption was negligible.

Abstract: Heavy precipitation clustering is an important factor for flood risk and hydrological forecasting, but its simulation in climate models is still uncertain. This study examines European climate simulations by comparing global climate models with long-term observations. Consecutive wet days (CWD) and very wet days (R95p) were used as indicators, and clustering behavior was assessed across major regions in Europe. The results show that models capture large-scale extremes with moderate accuracy but underestimate clustering by 20–30% in Mediterranean and Alpine areas. Sensitivity tests also show that clustering depends on temporal resolution, with daily indices showing stronger underestimation than multi-day metrics. These outcomes suggest that current models reproduce intensity more reliably than persistence, which lowers confidence in hydrological forecasts and flood risk analysis. The study concludes that improvements in physical schemes and the use of convection-permitting models are needed to better simulate precipitation clustering in Europe.

Abstract: Understanding the temporal clustering of heavy precipitation is important for flood risk assessment in Europe, but current climate models show limited skill in reproducing these events. This study evaluates ten CMIP6 models against the E-OBS dataset for the period 1981–2020, focusing on consecutive days of extreme rainfall defined above the 95th percentile. Cluster features were measured using mean cluster length and maximum consecutive wet days, and model skill was assessed with correlation, mean absolute error, and Nash–Sutcliffe Efficiency. The results show that models capture large-scale spatial patterns but underestimate persistence by 15–30% in Mediterranean and Alpine regions. In contrast, performance is better in maritime climates, where correlations reach 0.55–0.65 and mean absolute error is close to one day. Sensitivity tests indicate that thresholds and linking rules strongly affect cluster metrics. Spatial analysis further highlights systematic underestimation of persistence in southern Europe. These results point to the need for better representation of persistence, convective rainfall, and orographic effects in climate models. Although the analysis is limited by the coarse resolution of observations and the small set of models, it provides useful evidence for improving model evaluation and supports more reliable flood risk management under climate change.

Abstract: Spatial heterogeneity in economic benefits of water use provides crucial evidence for the evaluation of water diversion projects and the spatial equilibrium of water resource allocation. However, research focusing on the economic benefits of water use in major industries within Chinese cities remains insufficient. We collected water use and value added data of agriculture, industry, and service sectors of 334 Chinese cities in 2017, and used the benefit allocation coefficient method to calculated the economic benefit of water use in the three sectors. Then we analyzed spatial heterogeneity in the economic benefits of water use: for agricultural sector, the high economic benefit of water use regions are primarily concentrated on both sides surrounding of the “Hu Huanyong Line”; regions with high economic benefit of industrial water use are mainly found in the North China Plain, the middle and lower Huanghe River basin, the Yangtze River Delta, the Pearl River Delta, Chongqing and Chengdu; and the economic benefit of service water use is higher in the north than in the south. Based on the fundamental distribution of water resources and the spatial heterogeneity in the economic benefits of water use, potential water diversion areas can be preliminarily identified: the Haihe River Basin in the North China Plain and some areas in the southeast coastal region are potential receiving areas, and the eastern regions of Southwest China with abundant water resources and lower elevations, along with the middle and lower reaches of the Yangtze River are potential source areas. Further research about marginal benefits and water use costs, along with dynamic updates, is required for water resource allocation of China.

Abstract: Based on multi-batch filtration and cleaning experiments, this study systematically evaluated the fouling potential of pre-treated textile dyeing wastewater by membrane bioreactor on reverse osmosis (RO) membranes and the recovery performance of fouled RO membranes after different cleaning methods. After a permeate production of 625 L/m², continuous foulants accumulation resulted in a significant decline in RO membrane permeability. Protein-like substances and sol-uble microbial products were identified as the primary organic foulants via three-dimensional fluorescence excitation-emission matrix spectrometry (3D-FEEM). The single forward flushing with pure water, acid solution (pH 3.5), alkaline solution (pH 10.5), and sodium hypochlorite with low effective chlorine concentration (1-2 mg/L) showed very limited recovery of fouled RO membrane permeability. The combined forward flushing with acid solution (pH 2) followed by alkaline solution (pH 11.5) restored fouled membrane permeability up to 87% of new RO mem-brane. The addition of pure water backwashing at transmembrane pressure of 0.5 MPa after both acid and alkaline combined forward flushing restored fouled membrane permeability up to 97% of new RO membrane but deteriorated the rejection capacity of RO membrane. The backwashing parameters were further optimized as transmembrane pressure of 0.5 MPa and crossflow veloci-ty of 0.5 m/s, achieving fouled membrane permeability up to 96% of new RO membrane and no negative effects on the rejection capacity of RO membrane. Therefore, the combined cleaning of acid forward flushing → pure water backwashing → alkaline forward flushing → pure water backwashing was proposed for RO membrane cleaning from textile dyeing wastewater reuse application.

Abstract: Accurate streamflow forecasting is vital for sustainable water resource management but remains challenging due to pronounced spatiotemporal variability. This study evaluates two process-based models SWAT (comprehensive) and GWLF (parsimonious)—and a data-driven Random Forest (RF) model for monthly streamflow simulation in two contrasting Chinese basins: the humid southern basin (SSB) and the semi-arid northern basin (SRB). Using four statistical metrics (NSE, R2, MAE, RMSE), we assess model accuracy, robustness in capturing extremes, and sensitivity to hydrological characteristics and data availability. Results reveal consistently superior performance in the SSB across all models, with SWAT demonstrating the highest overall accuracy—especially for peak flows—due to its physically based structure. GWLF provides acceptable simulations with minimal data requirements, offering a practical alternative in data-limited regions like the SRB. RF performs well in the SSB under zero-lag conditions but requires hydrologically informed lag structures in the SRB. However, it consistently underestimates high flows due to its lack of physical constraints. The findings underscore that model selection must therefore be guided not only by predictive performance, but by the underlying hydrological context, data availability, and the need for physical realism in decision-making.

Abstract: Heavy precipitation clustering is important for flood risk in Europe, but its description in reanalysis datasets is still uncertain. This study examined how well ERA5, ERA5-Land, and JRA-55 reproduce the size and timing of extreme precipitation from 1981 to 2022. Observations from the E-OBS dataset were used as reference, with heavy events defined as daily totals above the 95th percentile. Consecutive wet days were grouped into clusters, and measures such as mean cluster length (MCL) and mean gap between clusters (MGC) were used. Correlations between reanalysis and observed MCL were 0.58–0.63 across seasons, with mean absolute errors of 0.9–1.2 days. The largest bias was found in convective areas, where MGC was underestimated by up to 0.6 days. Sensitivity tests showed that thresholds and linking rules had stronger influence on clustering than the dataset used. The results show that reanalyses reproduce large-scale patterns but tend to underestimate storm duration and event order, which affects flood modeling. Better use of data, improved physical methods, and denser observation networks are needed to reduce these limits and support climate adaptation.

Abstract: Sustainable urban water governance in rapidly transforming cities requires integrative decision-making frameworks capable of balancing social equity, economic efficiency, and environmental resilience. This study develops a multi-criteria decision-making (MCDM) model designed to support policy optimization for sustainable water management in Yerevan City, Armenia. Building upon prior AI- and GIS-based diagnostics, the proposed framework integrates quantitative indicators of social participation, economic cost-efficiency, and ecological performance into a unified analytical structure. Using AHP–TOPSIS weighting and scenario analysis, the study evaluates alternative policy strategies such as leakage reduction, demand management, and decentralized reuse systems. Results reveal the trade-offs and synergies among sustainability dimensions, highlighting that equity-prioritized weighting schemes enhance social outcomes without significantly compromising economic performance. The Yerevan case demonstrates how adaptive, data-informed governance models can strengthen resilience, improve resource allocation, and guide policy under uncertainty. The framework contributes to advancing decision science in urban water management and offers transferable insights for mid-income cities facing institutional and environmental constraints.

Abstract: This study presents an analysis of the Infrastructure Leakage Index (ILI) variability for two District Metered Areas (DMAs) in the Silesian Region (Poland), based on 2024 data. The objective was to assess the suitability of the ILI for short-term leakage evaluation and its potential to support operational decision-making. ILI values were calculated for daily, weekly, and monthly intervals using synchronized hourly data from an Advanced Me-tering Infrastructure (AMI) system and water network monitoring platforms. A key ad-vantage of the dataset was the temporal alignment of inflow, outflow, and consumption data at the DMA level. The study applied statistical measures of variability (standard deviation, variance, coeffi-cient of variation) and graphical methods (histograms, boxplots) to evaluate ILI behavior across time resolutions. The two DMAs were compared to explore the differences in ILI dynamics, range, and identify operational factors influencing leakage levels. The results confirm that ILI interpretation is highly dependent on temporal resolution. Daily data is more responsive to anomalies and operational events, while monthly data provides more stable values suitable for benchmarking. Despite the aggregation smooth-ing the variability, notable differences in system performance between zones persist. High-frequency AMI data enhances the precision and operational value of ILI analyses.