Daily Streamflow Data Research Articles

Copula Theory as a Generalized Framework for Flow‐Duration Curve Based Streamflow Estimates in Ungaged and Partially Gaged Catchments

AbstractFlow‐duration curve (FDC) based streamflow estimation methods involve estimating an FDC at an ungaged or partially gaged location and using the time series of nonexceedance probabilities estimated from donor streamgage sites to generate estimates of streamflow. We develop a mathematical framework to illustrate the connection between copulas and prior FDC‐based approaches. The performance of copula methods is compared to several other streamflow estimation methods using a decade of daily streamflow data from 74 sites located within two river basins in the southeast United States with different climate characteristics and physiographic properties. We show that copula approaches: (1) outperform other methods in the limiting case of perfect information with regard to the rank‐based correlation structure and FDCs across the gaging network; (2) provide a hedge against poor performance when donor information becomes sparser and less informative; (3) outperform other methods when used for partially gaged sites with several years of available data; and (4) remain a competitive albeit nondominating method for ungaged sites and partially gaged sites with limited data when realistic error is introduced in the estimation of FDCs and correlations across the gaging network.

Challenges to Implementing an Environmental Flow Regime in the Luvuvhu River Catchment, South Africa.

Rivers are now facing increasing pressure and demand to provide water directly for drinking, farming and supporting industries as a result of rapidly growing global human population. Globally, the most common practice for catchment managers is to limit water abstraction and changes to stream flow by setting environmental flow standards that guard and maintain the natural ecosystem characteristics. Since the development of the environmental flow concept and methods in South Africa, very few studies have assessed the institutional constraints towards environmental flow implementation. This study determined stream flow trends over time by fitting simple linear regression model to mean daily stream flow data at three selected stations in the Luvuvhu River Catchment (LRC). We also conducted a literature search to review, firstly the response of aquatic organisms (fish and macroinvertebrate) to changes in habitat conditions and secondly on local challenges affecting the sustainable implementation of environmental flow regime and related water resources management strategies. All the three stream flow stations show decreasing stream flow volume of 1 and 2 orders of magnitude faster in some stations with the possibility that flow will cease in the near future. Qualitative analyses from both local and international literature search found that the main challenges facing the implementation of sustainable flow strategies and management are absence of catchment management agency, lack of understanding of environmental flow benefits, limited financial budget, lack of capacity and conflict of interest. Rivers with changing stream flows tend to lose sensitive species. The development of scientifically credible catchment-wide environmental flow and abstraction thresholds for rivers within the LRC would make a major contribution in minimizing the declining stream flow volumes. Monitoring and reporting should be prioritized to give regular accounts of the state of our rivers.

Development of Flow Duration Curves and Eco-Flow Metrics for the Tawi River Basin - (Jammu, India)

A Flow duration Curve (FDC) and eco-metrics are one of the principal techniques employed to study the changes in flow regimes and flow discharge in any river basin. Stream flows vary widely over a year and this variability can be assessed by using FDC’s which is a curve plotting stream flows (Q) on the vertical axis and the percent of time the flow is equalled or exceeds (P) a critical discharge threshold on the horizontal axis for a particular river basin. Flow Duration curves (FDCs) are imperative instruments which are fundamental for water asset distribution and administration, which can further be analysed to get a great deal of hydrological data to understand the impact of climate changes on water asset frameworks. Results got from the flow duration curves are required by hydrologists and specialists associated with various water asset ventures such as assessing the hydropower capabilities of a waterway, stream health, surge control examines such as recurrence outlines, runoff estimations, figuring the dregs stack and broken down solids of a stream, and contrasting the adjacent catchments. Apart from these classical uses, the FDCs can also be used to survey the health status of the streams in terms of its ecological status. The present study has been undertaken with an objective to identify the ecological health status of the Tawi River, based on ecoflow metrics. Eco-surplus and eco-deficit are known as the indicators of Hydrologic Alteration (IHA) and are used to study intra and inter annual variations in river flows. The daily stream flow data at Gulab Singh Bridge, Jammu from the Hydrological Data Centre of the Central Water Commission (CWC), Jammu has been used to develop the Flow Duration Curve (FDCs) for the different periods like daily, monthly, annual etc. Finally, 10- daily time series have been used to identify the ecosurplus and the ecodeficit years and their respective magnitudes. Further, an eco-flow metric for the Tawi River was prepared for the 30 years daily discharge data from the period 1977 to 2007. The results of the study conclude that Tawi River is an ecosurplus river, in most of the years of the study period. The ecology of Tawi River is at par for the study period except for the years 1999 and 2000. Although the ecology is under sustaining conditions, but the metric has been falling in course of time, which can be a signal of ecological deterioration in the future.

Shifts of sediment transport regime caused by ecological restoration in the Middle Yellow River Basin

Sediment in rivers is the dominant material source for ecosystems in lower reaches and estuaries, and it is undergoing large variations globally in recent decades. Though we have knowledge that human activities are greatly affecting land surface ecosystem processes and functions, the relationships between sediment transport regime and the intensifying human activities, are still poorly understood. This study was to investigate the changes of sediment transport regime due to the large-scale ecological restoration in the Middle Yellow River Basin (MYRB). In this study, we examined the change of the sediment rating curves using daily sediment load and streamflow data from 30 stations during time periods including pre- and post-ecological restoration in this region. We found the pair-relationship of the rating parameters (coefficient and exponent), denoted as coefficient-exponent pair-line, is a critical indicator that can detect the shift of sediment transport regime due to disturbed land surface conditions, though the changed hydrometeorological condition may just influence the absolute values of the rating parameters. Our analysis indicates there was a significant and interesting change of the sediment transport regime in the MYRB characterized by the consistent shift of the coefficient-exponent pair-line, together with an increasing exponent and a decreasing coefficient. This changed sediment transport regime can tell that sediment delivery would become lower for normal discharge conditions but potentially higher for extreme discharge conditions, and this phenomenon seems more distinct in relatively smaller watersheds, suggesting a higher risk of the potential high sediment delivery for extreme rainfall conditions especially for small watersheds. Our study would be informative and valuable to decision makers for sustainable watershed management in the MYRB when considering the changed sediment delivery.

Using sediment rating parameters to evaluate the changes in sediment transport regimes in the middle Yellow River basin, China

AbstractThis study analyses the changes in sediment transport regimes in the middle Yellow River basin (MYRB) using sediment rating parameters. Daily streamflow and suspended sediment concentration data were collected at 35 hydrological stations from the 1950s to 2016, which can be divided into three periods based on the type and intensity of human activities: the base stage before 1970, the restraining stage from 1971 to 1989, and the restoration stage after 2002. Data within each period were fitted by log‐linear sediment rating curves and the sediment rating parameters were utilized to analyse the spatial and temporal variations in sediment transport regimes. The results show that sediment rating parameters are indicative of sediment transport regimes. In the base stage and the restraining stage, the hydrological stations can be categorized into four groups based on their locations on the rating parameter plot. The stations with small drainage basins were characterized by the highest sediment transport regime, followed by those located in the coarse‐particle zone, the loess zone, and the mountainous/forest zone. In the restoration stage, the difference in sediment transport regimes between different geomorphic zones became less distinguishable than in previous stages. During the transition from the base stage to the restraining stage, sediment rating parameters showed no significant changes in sediment transport regimes in all four geomorphic groups. During the transition from the restraining stage to the restoration stage, significant changes were observed in the coarse‐particle zone and the mountain/forest zone, indicating that the revegetation programme and large reservoirs imposed a stronger influence on sediment transport regimes in these two zones than in the rest of the MYRB. This study provides theoretical support for evaluating sediment transport regimes with sediment rating parameters.

Capacity Sizing of a Small Hydropower Plant using Assured Energy Analysis

For a Small Hydropower Plant (SHP), the installation capacity is one of the most important issues in planning step. This paper presents a methodology for the capacity sizing of SHP based on assured energy. The analyzes were substantiated on historical series with daily streamflow data, operating limits of the turbines, forced unavailability due to the minimum streamflow of the turbine, Turbine efficiency variation in function of the streamflow variation and a project with two turbines operating in parallel of different type and size. The methodology was developed at the Tijuco River Basin in Brazil, with the data of Ituiutaba fluviometric station. It was used the time series from 1975 to 2017 (43 years). The results show that the analysis can be executed already in the initial phases of a hydroelectric project of the SHP. Key words Small Hydropower Plant, Assured Energy, Renewable Energy, Turbine Efficiency, Hydroelectric Potential Estimate.

Streamflow permanence curve of the river Timbó, Santa Catarina, Brazil

The permanence curve is used as a source of information on water availability. It is adopted as a reference in the processes of management of water resources. In the present study, the streamflow permanence curve of the Timbó River, located in the Northern Plateau of Santa Catarina, was evaluated and modeled. Daily streamflow data of the fluvial station Santa Cruz do Timbó (Code 65295000) were used for the period from 1975 to 2005. Thus, permanence curves can be established for monthly streamflows and daily streamflows. The values were rendered dimensionless by the average long-term streamflow, and adjusted to the Rational model. The daily streamflow permanence curves were also determined for each month, and the models for these non-dimensioned streamflows were adjusted by the average monthly streamflows. The results show that the use of the monthly permanence curve overestimates the streamflow values by frequencies higher than 20%. The adjusted models allow estimating the streamflow with a small estimation standard error. The coefficient of determination is higher than 0.99.

Bivariate Design of Hydrological Droughts and Their Alterations under a Changing Environment

AbstractFew studies have focused on the multivariate joint design of drought properties. Using daily streamflow data, this paper analyzes the impacts of pooling and exclusion of drought events in d...

Evaluation of basin storage–discharge sensitivity in Taiwan using low‐flow recession analysis

AbstractSensitivity analysis of the hydrological behaviour of basins has mainly focused on the correlation between streamflow and climate, ignoring the uncertainty of future climate and not utilizing complex hydrological models. However, groundwater storage is affected by climatic change and human activities. The streamflow of many basins is primarily sourced from the natural discharge of aquifers in upstream regions. The correlation between streamflow and groundwater storage has not been thoroughly discussed. In this study, the storage–discharge sensitivity of 22 basins in Taiwan was investigated by means of daily streamflow and rainfall data obtained over more than 30 years. The relationship between storage and discharge variance was evaluated using low‐flow recession analysis and a water balance equation that ignores the influence of rainfall and evapotranspiration. Based on the obtained storage–discharge sensitivity, this study explored whether the water storage and discharge behaviour of the studied basins is susceptible to climate change or human activities and discusses the regional differences in storage–discharge sensitivity. The results showed that the average storage–discharge sensitivities were 0.056 and 0.162 mm−1 in the northern and southern regions of Taiwan, respectively. In the central and eastern regions, the values were both 0.020 mm−1. The storage–discharge sensitivity was very high in the southern region. The regional differences in storage–discharge sensitivity with similar climate conditions are primarily due to differences in aquifer properties. Based on the recession curve, other factors responsible for these differences include land utilization, land coverage, and rainfall patterns during dry and wet seasons. These factors lead to differences in groundwater recharge and thus to regional differences in storage–discharge sensitivity.

Future Hydrological Drought Risk Assessment Based on Nonstationary Joint Drought Management Index

As the environment changes, the stationarity assumption in hydrological analysis has become questionable. If nonstationarity of an observed time series is not fully considered when handling climate change scenarios, the outcomes of statistical analyses would be invalid in practice. This study established bivariate time-varying copula models for risk analysis based on the generalized additive models in location, scale, and shape (GAMLSS) theory to develop the nonstationary joint drought management index (JDMI). Two kinds of daily streamflow data from the Soyang River basin were used; one is that observed during 1976–2005, and the other is that simulated for the period 2011–2099 from 26 climate change scenarios. The JDMI quantified the multi-index of reliability and vulnerability of hydrological drought, both of which cause damage to the hydrosystem. Hydrological drought was defined as the low-flow events that occur when streamflow is equal to or less than Q80 calculated from observed data, allowing future drought risk to be assessed and compared with the past. Then, reliability and vulnerability were estimated based on the duration and magnitude of the events, respectively. As a result, the JDMI provided the expected duration and magnitude quantities of drought or water deficit.

Investigation of runoff response to land use/land cover change on the case of Aynalem catchment, North of Ethiopia

The impact of land use/land cover and climate change on the hydrology are global issues affecting the whole catchment of the river basin. The main objective of this study was to investigate runoff response to land use/land cover change in Aynalem catchment, located in Tigray regional state, northern Ethiopia. The study analyzed the historical land cover changes from 1995 to 2015 that have taken place in the catchment and its effect on the runoff of the catchment. The land cover changes within the catchment were examined through classification of satellite images with integrated use of ERDAS Imagine (Version 9.2) and ArcGIS software. Land cover change analysis between the periods of 1995 and 2015 has shown that the urban area has increased from 1.39% to 7.50%, Cropland from 54.03% to 65.69% and Water bodies from 0.14% to 0.42%, while Planted Forest area has decreased from 3.61% to 2.92%, Grassland 2.22%–1.90% and Open Shrub lands from 38.61% to 21.53%. Further, Water and Energy Transfer between Soil, Plants, and Atmosphere (WetSpa) model was used to investigate the runoff response to a land cover change on the study area. The model was calibrated (1994–1998) and validated (1999–2001) against the observed daily stream flow data. WetSpa model parameters sensitivity analysis result shown that the groundwater recession coefficient (Kg), Initial active groundwater storage (Go) and Surface runoff exponent (K_run) are the most sensitive parameters affecting the hydrology of the catchment. The WetSpa model application in Aynalem catchment performances very good in reproducing the hydrological process of the catchment with coefficient of determination (R2), Nash and Sutcliff efficiency (NSE) values of 0.82 and 0.90 for calibration, 0.78 and 0.88 for validation, respectively. The WetSpa model application with land useland cover maps of 1995, 2003 and 2015 shows annual runoff increased by 21.1% from the year of 1995–2003 and 23.5% from 2003 to 2015 and also, 44.6% from 1995 to 2015. The increment in runoff is likely to have been caused by the change of the land use/land cover from shrubs and grass lands to urban and cultivated lands.

Multiple streamflow time series modeling using VAR–MGARCH approach

Multivariate time series modeling approaches are known as valuable methods for simulating and forecasting the temporal evolution of hydroclimatic variables. These approaches are also useful for modeling the temporal dependence and cross-dependence between variables and sites. Although multiple linear time series approaches, such as vector autoregressive (VAR) and multiple generalized autoregressive conditional heteroscedasticity (MGARCH) approaches are ordinarily applied in finance and econometrics, these methods have not been broadly applied in hydrology science. The present research employs the VAR and VAR–MGARCH methods to model the mean and conditional variance (heteroscedasticity) of daily streamflow data in the Zarrineh Rood dam watershed, in northwestern Iran. The bivariate diagonal vectorization heteroscedasticity (DVECH) model, as one of the key MGARCH models, demonstrates how the conditional variance, covariance, and correlation structures change in time between the residual time series from VAR model. In this regards, in the present study, five experiments which present different combinations of twofold streamflows (including both upstream and downstream stations) are conducted. The VAR approach is fitted to the twofold daily time series in each of the experiments with different orders. The Portmanteau test, as a formal test for demonstrating time-varying variance (or so-called ARCH effect), indicates the existence of conditional heteroscedastic behavior in the twofold residual time series obtained from the VAR models fitted to the twofold streamflows. Thus, the VAR–DVECH approach is suggested to capture the inherent heteroscedasticity in daily streamflow series. The bivariate DVECH approach indicates short-term and long-term persistency in the conditional variance–covariance structure of the twofold residuals of streamflows. Results show also that the use of the nonlinear bivariate DVECH model improves streamflow modeling efficiency by capturing the heteroscedasticity in the twofold residuals obtained from the VAR model for all experiments. The assessment criteria indicate also that the VAR–DVECH approach leads to a better performance than the VAR model.

Parameter sensitivity of automated baseflow separation for snowmelt‐dominated watersheds and new filtering procedure for determining end of snowmelt period

AbstractAutomation in baseflow separation procedures allowed fast and convenient baseflow and baseflow index (BF and BFI) estimation for studies including multiple watersheds and covering large spatio‐temporal scales. While most of the existing algorithms are developed and tested extensively for rainfall‐ and baseflow‐dominated systems, little attention is paid on their suitability for snowmelt‐dominated systems. Current publishing practice in regional‐scale studies is to omit BF and BFI uncertainty evaluation or sensitivity analysis. Instead, “standard” and “previously recommended” parameterizations are transferred from rainfall/BF to snowmelt‐dominated systems. We believe that this practice should be abandoned. First, we demonstrate explicitly that the three most popular heuristic automated BF separation methods—Lyne–Hollick and Eckhardt recursive digital filters, and the U.K. Institute of Hydrology smoothed minima method—produce a wide range of annual BF and BFI estimates due to parameter sensitivity during the annual snowmelt period. Then, we propose a solution for cases when BF and BFI calibration is not possible, namely excluding the snowmelt‐dominated period from the analysis. We developed an automated filtering procedure, which divides the hydrograph into pre‐snowbelt, post‐snowmelt, and snowmelt periods. The filter was tested successfully on 218 continuous water years of daily streamflow data for four snowmelt‐dominated headwater watersheds located in Wyoming (60–837 km2). The post‐snowmelt BF and BFI metric can be used for characterizing summer low‐flows for snowmelt‐dominated systems. Our results show that post‐snowmelt BF and BFI sensitivity to filter parameterization is reduced compared with the sensitivity of annual BF and BFI and is similar to the sensitivity levels for rainfall/baseflow systems.

The map-correlation method for ungauged catchments streamflow prediction in the Ufa River, Russian Federation

The paper investigates the problem of streamflow prediction at ungauged catchments by the use of the map-correlation method and focuses on the selection of reference stream gauges to estimate the average daily streamflow for ungauged catchments. Daily streamflow data are indeed crucial for several fields such as water management, sustainable water resource management, hydropower energy production, but the number of ungauged watersheds is still big and reliable large scale regional approaches are indeed needed as a practical response to the ungauged catchment problem. In the following, results of an application to the catchments of the rivers Ufa and main tributaries for a total of 25 catchments, is presented. The map-correlation method has been performed, where differences is made between the 'nearest' stream gauge and the 'best correlated' stream gauge criterion for reference station selection. It was found that, on average, for the case study the best performing method for the selection of reference station is the 'best correlated'.

Multifractality and cross-correlation analysis of streamflow and sediment fluctuation at the apex of the Pearl River Delta

The fluctuation and distribution of hydrological signals are highly related to the fluvial and geophysical regime at estuarine regions. Based on the long daily streamflow and sediment data of Makou (MK) and Sanshui (SS) stations at the apex of the Pearl River Delta, the scaling behavior of the streamflow and sediment is explored by multifractal detrended fluctuation analysis (MF-DFA). The results indicated that there was significant multifractal structure present in the fluctuations of streamflow and sediment. Meanwhile, the multifractal degree and complexity of sediment were much stronger than streamflow. Although the scaling exponents of streamflow were larger than sediment at both MK and SS, no evident differences have been found on the scaling properties of streamflow and sediment for the ratios MK/SS. Moreover, the cross-correlation between streamflow and sediment is further detected by Multifractal Detrended Cross-Correlation Analysis (MF-DXA). The multifractal response between streamflow and sediment at small timescale is characterized by long-range correlations whereas it exhibits random behavior at large timescale. The interaction of the broadness of probability density function and the long-range correlations should be responsible for the multifractal properties of hydrological time series as the multifractal degree of surrogate and shuffled data was significantly undermined.

Hydrometeorological data from Baker Creek Research Watershed, Northwest Territories, Canada

Abstract. It is uncommon to collect long-term coordinated hydrometeorological and hydrological data in northern circumpolar regions. However, such datasets can be very valuable for engineering design, improving environmental prediction tools or detecting change. This dataset documents physiographic, hydrometeorological and hydrological conditions in the Baker Creek Research Watershed from 2003 to 2016. Baker Creek drains water from 155 km2 of subarctic Canadian Shield terrain in Canada's Northwest Territories. half-hourly hydrometeorological data were collected each year, at least from April to October, from representative locations, including exposed Precambrian bedrock ridges, peatlands, open black spruce forest and lakes. Hydrometeorological data include radiation fluxes, rainfall, temperature, humidity, winds, barometric pressure and turbulent energy fluxes. Terrestrial sites were monitored for ground temperature and soil moisture. Spring maximum snowpack water equivalent, depth and density data are included. Daily streamflow data are available for a series of nested watersheds ranging in size from 9 to 128 km2. These data are unique in this remote region and provide scientific and engineering communities with an opportunity to advance understanding of geophysical processes and improve infrastructure resiliency. The data described here are available at: https://doi.org/10.20383/101.026.

Calibration of the Global Flood Awareness System (GloFAS) using daily streamflow data

This paper presents the calibration and evaluation of the Global Flood Awareness System (GloFAS), an operational system that produces ensemble streamflow forecasts and threshold exceedance probabilities for large rivers worldwide. The system generates daily streamflow forecasts using a coupled H-TESSEL land surface scheme and the LISFLOOD model forced by ECMWF IFS meteorological forecasts. The hydrology model currently uses a priori parameter estimates with uniform values globally, which may limit the streamflow forecast skill. Here, the LISFLOOD routing and groundwater model parameters are calibrated with ECMWF reforecasts from 1995 to 2015 as forcing using daily streamflow data from 1287 stations worldwide. The calibration of LISFLOOD parameters is performed using an evolutionary optimization algorithm with the Kling-Gupta Efficiency (KGE) as objective function. The skill improvements are quantified by computing the skill scores as the change in KGE relative to the baseline simulation using a priori parameters. The results show that simulation skill has improved after calibration (KGE skill score > 0.08) for the large majority of stations during the calibration (67% globally and 77% outside of North America) and validation (60% globally and 69% outside of North America) periods compared to the baseline simulation. However, the skill gain was impacted by the bias in the baseline simulation (the lowest skill score was obtained in basins with negative bias) due to the limitation of the model in correcting the negative bias in streamflow. Hence, further skill improvements could be achieved by reducing the bias in the streamflow by improving the precipitation forecasts and the land surface model. The results of this work will have implications on improving the operational GloFAS flood forecasting (www.globalfloods.eu).

A geostatistical data-assimilation technique for enhancing macro-scale rainfall–runoff simulations

Abstract. Our study develops and tests a geostatistical technique for locally enhancing macro-scale rainfall–runoff simulations on the basis of observed streamflow data that were not used in calibration. We consider Tyrol (Austria and Italy) and two different types of daily streamflow data: macro-scale rainfall–runoff simulations at 11 prediction nodes and observations at 46 gauged catchments. The technique consists of three main steps: (1) period-of-record flow–duration curves (FDCs) are geostatistically predicted at target ungauged basins, for which macro-scale model runs are available; (2) residuals between geostatistically predicted FDCs and FDCs constructed from simulated streamflow series are computed; (3) the relationship between duration and residuals is used for enhancing simulated time series at target basins. We apply the technique in cross-validation to 11 gauged catchments, for which simulated and observed streamflow series are available over the period 1980–2010. Our results show that (1) the procedure can significantly enhance macro-scale simulations (regional LNSE increases from nearly zero to ≈0.7) and (2) improvements are significant for low gauging network densities (i.e. 1 gauge per 2000 km2).

Streamflow availability ratings identify surface water sources for groundwater recharge in the Central Valley

In California's semi-arid climate, replenishment of groundwater aquifers relies on precipitation and runoff during the winter season. However, climate projections suggest more frequent droughts and fewer years with above-normal precipitation, which may increase demand on groundwater resources and the need to recharge groundwater basins. Using historical daily streamflow data, we developed a spatial index and rating system of high-magnitude streamflow availability for groundwater recharge, STARR, in the Central Valley. We found that watersheds with excellent and good availability of excess surface water are primarily in the Sacramento River Basin and northern San Joaquin Valley. STARR is available as a web tool and can guide water managers on where and when excess surface water is available and, with other web tools, help sustainable groundwater agencies develop plans to balance water demand and aquifer recharge. However, infrastructure is needed to transport the water, and also changes to the current legal restrictions on use of such water.

Estimation of Sediment Deposition at Nausehri Reservoir by Using Multiple Linear Regression and Assessment of its Effect on Hydropower Generation Capacity

This article presents investigation of the inflow of sediments depending upon the stream flow, density and kinematic viscosity of water. The process involves Multiple Linear Regression (MLR) technique for estimation of sediment load and volume, by using UNISTAT software (Version 5.6). A general equation is developed for a specific flow rate while considering density and kinematic viscosity of water as other parameters. The developed equation can be applied in future for determining the sediment concentration when the flow rate is known. The daily stream flow and suspended sediment data belonging to the station Nausehri operated by the Water and Power Development Authority, Pakistan is used as case study. The results indicate that the dam site experiences a mean annual sediment load of 3.74mst. With this much incoming sediment load the reservoir life comes out to be 45 years when no flushing is done. The impact of this sediment deposition on hydro-electric energy generation is also determined, which shows a decrease of 113MW (12%) in the production capacity of the power plant over the life of the reservoir.