Small Scale Hydropower as a Resources of 1 Renewable Energy in Mozambique : Case of 2 Chua River in Manica

8 All hydropower project type requires an ample availability of stream flow data. Unfortunately most 9 of the hydropower projects especially small hydropower projects are conducted on ungauged river 10 and consequently hydrologists have for a longtime used stream flow estimation methods using the 11 mean annual flows to gauge rivers. Unfortunately flow estimation methods which include the 12 runoff data method, area ratio method and the correlation flow methods employ a lot of 13 assumptions which affect their uncertainty. Although hydropower energy is one of most promising 14 clean energy technologies available, it has potential drawbacks as compared with various other 15 forms of renewable energy, such as biomass, solar and wind energy, due in particular to it high 16 capital investment costs. For most of the rural population in Mozambique, access to conversional 17 energy in the form of electricity is limited. The aim of the present investigation was to analyze the 18 functions of the Chua micro-hydropower plant in the Manica district in Mozambique and to 19 examine the possibility of increasing energy production there. The total power generation capacity 20 currently installed in Mozambique is about 939 MW. Hydropower accounts for 561 MW or 61% 21 of this, oil and natural gas in turn, for 27% and 12% of it, respectively. 22 23


Introductions
In the current energy crisis, energy is considered to play as a key role in the achievement of good health, adequate social development and improved quality of life for people in developing countries in the world generally [1].Both produced and consumed energy resources, especially renewable ones, in hydropower is particular have led to an increase in the demand for energy in many countries of the wourld [2].Some areas of high population concentration may not yet be supplied with electricity or may have simply have old-generation (Diesel-plant) distribution systems that no longer function adequately, only about 21% of the populations there having access to electricity [3].In Mozambique, use of small hydropower plants (SHP) can be one of the solutions to the need of increasing electrification and of combating poverty in rural areas [4].
Hydropower is the most effective source of energy and electricity available.It has played a major role in the development of modern civilization and represents one type of renewable energy, a type converting the movement of water into electricity [5].Hydropower technology has various benefits that fossil fuel lack.It is a renewable source of energy, it produces no carbon dioxide emissions, and hydropower projects can also serve a wide variety of purposes, such as those of irrigation, fishery, flood control, water supply, and milling agricultural products [6].The latter is carried out especially much in the Manica sections of Mozambique.Gaining access to modern energy services is instrumental to fulfilling basic social needs and to driving economic growth, and it has positive effects on productivity, health, education, safe water and communication services [7] Hydropower energy has a high degree of potential, for catalyzing social change providing opportunities for a whole new range of activities that can improve the quality of life for rural populations, in particular.According to [4] hydropower accounted for 15.3% at the power generation in 2011, fossil fuels and nuclear reactor having the largest share in the global power generation scenario through their accounting for 77.9% of global power production altogether followed by other forms of renewable energy with 5% of the total power productions.The total hydropower energy-generation capacity in the world has been increasing steadily over the past 50 years, the rate of increase having accelerated during the past few years.Table 1 shows regional hydropower characteristics in terms of hydropower in operation.In this paper we use hydrological modeling for hydropower in Manica area in Mozambique.The study it was observed that applying the appropriate assumptions for each method correctly, would likely yield very good results in terms of bias, accuracy and uncertainty.Therefore, it was recommended that assumptions regarding each method should be carefully and appropriately applied for good stream flow estimation.

Current Hydropower Potential in Mozambique
The hydropower potential of Mozambique is highly attractive, its being estimated to be at a 18,000 MW level only roughly 2200 MW of it having been developed in a manner providing it if access to the national grid.To meet the needs that exist, the government of Mozambique has made rural electrification a major component of its development programs [8].In addition, it has liberalized its energy sector and there has been an influx of direct foreign investments in hydro-projects within the country as a whole.The Mozambique government has set a number of broad policy objectives relating to the development and governance of the energy sector.It has also supported rural electrification through creating an enabling environment for the stakeholders involved [9].The development of renewable energy in Mozambique dates back to the colonial period, when hydropower plants were developed to supply power to large urban cities such as Maputo, Beira and Nampula and for selling energy to South Africa [10].The total energy mixture available in Mozambique was very large 408.9PJ, its consisting to about 13% of Hydropower, 78% of biomass, 7% of oil products and 2% of other energy-related resources [9] Its has been found that the greatest hydropower potential in Mozambique lies in the Zambezi River basin, at such sites as Cahora Bassa and Manica ( Mavuzi and Chicamba) in the Rivue River, as shown in Table 3, that together have a generating capacity of about 2200MW.The total hydropower currently exploited is presented in Table 2.The most important hydropower plant is Cahora Bassa, with provides 95% of the total hydropower produced in Mozambique [3].In recent years, the government of Mozambique has been faced with having to meet the needs of a populations of increasing population, one that presently consist of some 28 million people.
Increasing investment have been made to meet the energy demands that have developed, and some 80 potential sites mostly in central parts of Mozambique (Manica and Tete, in particular), see

The Study Area of Chua in Manica and present hydropower activity there
The history of hydropower development activities in Manica dates back to the colonial period, when small scale hydropower plants were developed to supply both water and electricity to various of the communities in Chua Manica.Ealier, there hydropower plants were used to grind food (rice and corn), as shown in the in Annex.In the late 1990s, when peace came to Mozambique, a decade of marked development began in the Manica district, and the German organization (GIZ) modernized the system employed for milling corn, a hybrid system also being develop for producing electricity for approximately 50 families there, as well as for a school, and a hospital.Manica is located near the center of Mozambique

3.1.FLOW ESTIMATION METHODS
Generally there are three main flow estimation methods used in small hydropower which basically use mean annual flows to estimate flow.These three flow estimation used in small hydropower include the runoff data method, the area ratio method and the correlation flow method [13].Unlike the flow correlation method, when using the runoff data method and the area ratio method the first thing is to compute the Mean Annual flow (MAF) of the ungauged river.The MAF is computed using equation [14]: The method does not require a gauged site to be located near an ungauged site proposed for the hydropower plant .However, basically the method uses the runoff data which is usually available on runoff maps.Runoff maps can be downloaded online.The mean annual flow of the ungauged catchment was calculated from the Equation 5 below [15]: Then in order to estimate the flow of the ungauged river, the vertical ordinates (xn) representing the flow duration curve of the gauged stream are multiplied by the ratio of the MAF of the ungauged site/stream to that of the gauged stream/site.[16] explains that where the runoff map for the proposed site is not available, the area method becomes useful however, he further advices that a gauged site should exist in the vicinity.On the other hand, he says this method is used upon the assumption that both the ungauged site and the gauged site in the vicinity have similar hydrological characteristics which include: topography, land use, lithography and geomorphology as well as similar precipitation.Having those similar hydrological characteristics it therefore means that both the gauged and ungauged site have the same runoff values since they have similar parameters that generate the runoff values for rivers and catchments [16].Subsequently, the mean annual flow will be approximately proportional to the drainage area [13] The mean annual flow for the ungauged site was estimated using Equation 7below: Again the flow of the ungauged site was estimated using Equation 6 above.
There exist circumstances when the area of the ungauged site is unknown.[16]explains that in this case the correlation flow method is best handy.He says this method strictly requires that the gauged site must not be located too far from the ungauged site.Besides, this method demands constant site visits to make occasional stream flow measurement.The method requires and assumes that both the gauged and the ungauged sites display similar precipitation patterns and that their areas, vegetation cover, and geomorphology do not significantly different [16].

UNCERTAINTY ANALYSIS
The study was done on a well gauged catchment for the analysis of flow estimation methods.An overall of three sites/gauging stations qualified for uncertainty analysis and bias, accuracy and uncertainty measures for each flow estimation method was computed for all the respective sites/gauging stations and the means for bias, accuracy and uncertainty for the candidate stations were considered as final measures of uncertainty analysis for each respective estimation method.The study was done on a well gauged river in order to validate the uncertainty results by comparing the estimated flows with the original stream flows which have been termed as "true stream flows" in this study.Therefore, the variation pattern between the original flows (true flows) and the estimated flows will be revealed for further inferences and decision making for practitioners' use.Due to the assumptions for each flow estimation method explained earlier, it is unlikely that all the three gauging stations/sites can qualify for the uncertainty analysis for each and every method apart from the fact that they fall under a homogeneous region.Consequently not all stations qualified among these three stations.
The true stream flows were the true values in the uncertainty analysis of the flow estimations.
Bias (Mean Error), accuracy (RMSE) and standard error (uncertainty) were computed accordingly for each the flow estimation method.The bias was computed from the formula below: Where As one of the important elements in measurement process, just like the bias, accuracy was computed using the formula below: And finally the uncertainty also called the impression expressed as the standard error (Se) which is simply an expectation of the spread of errors was computed using equation as follows (Atkinson and Foody, 2008): ( )

Turbine Dimension
The choice of what type of water turbine is most appropriate depends upon the conditions at the site in questions, the water head level and the water flow rate being indispensable parameters.Charts have been developed for selection of a turbine as a starting point to determining what turbine may be most appropriate for particular locations [6].The specific speed is a dimensionless parameter that characterizes the hydraulic properties of a turbine in terms of the diameter the speed () runner, the jet velocit, the width of the jet, the radius of the blade and the specific speed (), as expressed as below the Table 4: This turbine chart depends upon the size of power plant, pico, small, medium or large which is combined with other parameters such as head and water flow rate as presented in the Figure 2. is the velocity in m/s.For this design, Ns = 30 was selected.

Parameter
Hydropower schemes use the kinetic energy of moving water to produce electricity.The amount of electricity produced by a turbine is determined by rate of flow of the water and the vertical fall of the water from the upstream to the downstream level, termed the Head see equations [17].The turbine, both the old one and projected one are shown in Figure 2, Figure 2 The chart of result of turbine selections adapted from [16] Since the net head of the mini hydropower system at Chua is 48 m in length and the as discharge designed is 0.15 m 3 /s, the appropriate turbine for this scheme, as can be seen from the turbine chart in

Conclusions
The present study was carried out with the aim of being able to optimize operations in the Chua mini-hydropower plant on the Chua River in Manica in Mozambique, where a hydropower plant was built for the milling of corn and other cereals.The results obtained in the study show it to be possible to increase the power achieved in the Chua hydropower plant to approximately 34.0 kW as the power needed in the village increases.Success in refurbishing or upgrading the small-scale hydropower setups there would create job opportunities during successful operation of the system, as well as providing energy for households and promoting various economic activities such as trade and irrigation.
Analysis of the present flow in the Chua River showed that the flow rate for producing energy would presumably be sufficient for a long period of time, since the stream flow stems from a waterfall in the mountainous terrain there.The measured flow rate was 0.15m 3 /s and associated as it is with the high head there, one of nearly 50 meters, it enable the Pelton turbine that is shown in figure 3 to be used.
Two of the advantages that the energy thus provided would bring to the village of Chua will be to increase development of the village and to eliminate poverty for the local populations there.With the electricity that is made available, life expectancy there should increase since the local hospital already benefits from this energy and will continues doing son, such as though being able to sterilize various hospital supplies and materials.The educational system there will also benefits through students being able to readily do homework in the evening when it is dark, for example.
Beginning of the study it was hypothetically thought that the runoff data method would present the best/least measures of bias, accuracy and uncertainty since the methods directly uses the mean annual runoff or runoff coefficient data to estimate the mean annual flow of an ungauged river.
The mean annual runoff and runoff coefficient are one of the powerful and most-used parameter used to estimate both surface and underground water dynamics and/or flows since they reflect the behavior of a catchment after integrating the most important properties of a catchment that are related to topography and surface cover.

Figure 1 .
It covers approximately 7500 km 2 and had a population in 2017 of about 2,4 million persons [12].The climate a seasonal wet-dry one with about 1090 mm rain per year.

Figure 1 .
Figure 1.Manica study area in Central of Mozambique

Q
are the estimated stream flow and true stream flow respectively.
the diameter of the runner, H is the net head, N is the speed of the runner in revolution per minutes, Ns is the specific speed, Q is the volume flow rate (m 3 /s), Cd is the coefficient of discharge and V

Figure 2 ,FLOW
is Pelton, with has an efficiency of 80-90% and a rated power capacity of 34.220kW.N=1649.5rpm,n=15blades,Ns=30;Aj=0,0049m2,V=30m/s The analysis carried out for estimating the flow rate of made use of historical flow data records from a nearby gauging station on the Chua River.A set of historical flow data recorded over a period 39 years from 1956 to 2004, were used in conjunction with a Wavelet neural network model.In addition, in assessing, the performance of model we found the training and the validation.The correlations Coefficients is (R 2 ) to be 0.9031 and 0.89, respectively, the root mean square error (RMSE) to be 258 and 176.4 and NSE is 0.771 and 0.72 respectively.Establishing the optimal flow in line with both model WNN and ARIMA values and the flow durations curve in the model showed that the flow rate of to be 0.15m 3 /s

Table 2 .
The hydropower sources in Mozambique that are currently exploited[11]

Table 3 .
The estimated capacity of different hydropower site in Mozambique[11]