Hydropower Reservoirs Research Articles

A Review of Greenhouse Gas Emissions by Hydropower Reservoirs

A Review of Greenhouse Gas Emissions by Hydropower Reservoirs

Estimation of dependable flow in river baspa at kuppa barrage using flow duration curve

Estimation of dependable flow at different levels is considered one of the important parameters for planning, designing, and managing water-related projects, including hydropower generation, irrigation systems, water use, and river and reservoir sedimentation. For this purpose, the Flow Duration Curve (FDC) is developed by analyzing the available stream flow data at the site when adequate length of observed data are not available. The FDC is a valuable tool for determining the flow patterns of a river and estimating dependable flow. The FDC provides the percentage of time duration during which a stream flow (monthly, seasonal, or annual) is exceeded over a recorded period for a particular river or stream, which can be constructed by adopting the empirical method. By analyzing the FDC, the flow patterns of the Baspa river at the Kuppa barrage were determined, and the dependable flow was estimated. This paper presents a study on the assessment of monthly, seasonal, and annual dependable flow through the FDC by adopting an empirical method for the river Baspa at Kuppa barrage. The study suggests the dependable flow at different percentage levels like 75%, 90%, and 100% obtained from FDCs could be used for planning irrigation, hydropower, and drinking water projects in the study area.

Learning from past coevolutionary processes to envision sustainable futures: Extending an action situations approach to the Water-Energy-Food nexus

Despite near-global consensus on the Sustainable Development Goals and the Paris Climate Agreement, unresolved and politically contentious trade-offs have undermined implementation. One exemplary case facing difficult trade-offs are Water-Energy-Food (WEF) nexus cases. Here, we extend the nascent ‘Social-Ecological Action Situations’ framework to analyse past coevolution of WEF nexus cases (or other social-ecological systems) to envision possible futures where trade-offs are equally considered and minimized. We illustrate the value of the approach for a WEF nexus case in Switzerland with upstream hydropower reservoirs, water-bound biodiversity, and emerging downstream agricultural irrigation needs. The proposed solution-oriented, transformative approach goes beyond existing frameworks by analysing past coevolution of the intertwined system to build system understanding and to envision a future with concrete policies that would result in a higher adaptive capacity of the system and a compromise within the WEF nexus. We argue that this perspective helps to devise policies to address trade-offs in WEF nexus cases and thereby to tackle global crises.

Assessment of Technical Potential of Floating Solar Photovoltaic System for Electricity Generation in Zambia

Sustainable hydropower development provides a basis for a reliable and stable power source that is economical and environmentally friendly. Zambia is heavily dependent on hydropower whose hydrological pattern is facing serious threats from frequent droughts and severe weather conditions affecting power generation. However, Zambia’s hydropower is characterized by larger water reservoirs (Mulungushi, Itezhi Tezhi, Kafue Gorge and Kariba North) receiving high solar energy exceeding 2000 kWh/m2 per year. Hence, integration of floating solar PV systems with hydropower could help boost hydropower production during dry periods and save loss of water through vapor. The paper aims at assessing the technical potential of integrating floating solar PV systems for electricity generation on the existing larger hydropower water reservoirs. The findings indicate that larger hydropower reservoirs have a total surface area of 11,146 km2 equivalent to an annual theoretical solar energy potential of 25,610TWh.At 10% of the total coverage of all the surface areas, the technical potential is estimated at 172.76 GWP (Monocrystalline), 141.44 GWP (CIS) and 116.10 GWP (CdTe) equivalent to an annual solar electricity generation potential of 304 TWh, 244 TWh and 211TWh respectively. In short, Zambia has huge potential for integration of floating solar with hydropower using the existing power grid infrastructure to increase on the electricity generation for the nation. Additionally, the solar energy profile fits well with the electricity demand profile for Zambia which makes it a better alternative for the energy mix of the country. These findings are vital to providing a guide to decision-makers for the inclusion of floating solar energy in the future national energy mix and conservation of land.

Effects of atmospheric low-level jets on the mixing process of a large tropical reservoir.

Changes in the physical and biogeochemical properties of water columns are frequently associated with cold fronts and mesoscale convective systems due to increased cloud cover. The effects of low-level jet (LLJ) events on thermal stratification and water quality, however, remain undescribed, particularly for tropical reservoirs. Here, water temperature time series are combined with meteorological data, LIDAR observations, ERA5 reanalysis data, and hydrodynamical modeling to investigate the impact of an event of LLJ over the Furnas hydropower reservoir in Brazil. The LLJ event was characterized by dry, intense, and persistent winds (~10 m s-1) blowing for more than 12 hours over the main fetch of the reservoir. In the downwind side of the lake, the surface mixed layer depth increased by 50% during the LLJ event. The changes to the water column were produced by a combination of wind-induced upwelling, shear-driven mixing, and nocturnal convective overturning, different from the heat balance expected during passing cold fronts and mesoscale convective systems. The results suggest that both momentum and heat fluxes during LLJ events need to be accounted for in lake modelings to reproduce the vertical mixing process.

Sustainable planning of multipurpose hydropower reservoirs with environmental impacts in a simulation–optimization framework

Abstract Hydropower projects involve enormous investments that require an efficient cost–benefit framework and optimization model for proper development. Dams and hydropower plants have many impacts on the environment. These environmental impacts are often not included in the economic calculations and planning of the projects, which leads to the loss of natural resources. The primary purpose of this research is to incorporate environmental impacts into optimization and decision-making. A comprehensive simulation–optimization model is developed to optimize hydropower decisions. The positive and negative values of environmental impacts are incorporated into an economic objective function under different scenarios, and optimal design was done for each scenario. The results show that considering environmental economics affects the multipurpose hydropower project's NPV and decision outcomes. Considering environmental impacts compared to not considering them has reduced NPV of the project by 13.9%. The results emphasize the importance of including these impacts to achieve sustainable development and management.

A Monthly Hydropower Scheduling Model of Cascaded Reservoirs with the Zoutendijk Method

A monthly hydropower scheduling determines the monthly flows, storage, and power generation of each reservoir/hydropower plant over a planning horizon to maximize the total revenue or minimize the total operational cost. The problem is typically a complex and nonlinear optimization that involves equality and inequality constraints including the water balance, hydraulic coupling between cascaded hydropower plants, bounds on the reservoir storage, etc. This work applied the Zoutendijk algorithm for the first time to a medium/long-term hydropower scheduling of cascaded reservoirs, where the generating discharge capacity is handled with an iterative procedure, while the other head-related nonlinear constraints are represented with exponential functions fitting to discrete points. The procedure starts at an initial feasible solution, from which it finds a feasible improving direction, along which a better feasible solution is sought with a one-dimensional search. The results demonstrate that the Zoutendijk algorithm, when applied to six cascaded hydropower reservoirs on the Lancang River, worked very well in maximizing the hydropower production while ensuring the highest firm power output to be secured.

Blending high-resolution satellite rainfall estimates over urban catchment using Bayesian Model Averaging approach

Study regionAkaki is a headwater catchment of Awash River Basin that hosts the capital city of Ethiopia, Addis Ababa. The area encompasses several agglomerated towns, water supply, and hydropower reservoirs and is characterized by a chain of mountains and floodplains. Due to basin rainfall, and the expansion of urbanized areas, the catchment is frequently affected by flooding. Study focusThis study evaluates dynamic Bayesian Model Averaging (BMA) approach to improve rainfall estimation over the catchment by blending four high-resolution satellite rainfall estimate (SRE) products. Using daily data (2003–2019) observed at thirteen stations as a reference, seven statistical metrics served to assess the point and spatial scale accuracy of the rainfall estimates. New hydrological insightsMain findings from this study are: (i) the blended product outperformed the individual SRE products by notably improving correlation with in-situ observed rainfall, and reducing the error of the estimated rainfall, (ii) the blended and individual SRE products performed better in the highlands than the lowlands of the catchment, and (iii) the amount of daily rainfall during the main-rainy season was mostly overestimated by the individual SRE products but was fairly estimated by the blended product. This study showed the nonexistence of surpassing individual SRE products and emphasized the blending of several products for gaining optimal results from each product.

Variability in modelled reservoir greenhouse gas emissions: comparison of select US hydropower reservoirs against global estimates

Greenhouse gas (GHG) emissions from reservoirs have most often been evaluated on a global extent through areal scaling or linear-regression models. These models typically rely on a limited number of characteristics such as age, size, and average temperature to estimate per reservoir or areal flux. Such approaches may not be sufficient for describing conditions at all types of reservoirs. Emissions from hydropower reservoirs have received increasing attention as industry and policy makers seek to better understand the role of hydropower in sustainable energy solutions. In the United States (US), hydropower reservoirs span a wide range of climate regions and have diverse design and operational characteristics compared to those most heavily represented in model literature (i.e., large, tropical reservoirs). It is not clear whether estimates based on measurements and modeling of other subsets of reservoirs describe the diverse types of hydropower reservoirs in the US. We applied the Greenhouse Gas from Reservoirs (G‐res) emissions model to 28 hydropower reservoirs located in a variety of ecological, hydrological, and climate settings that represent the range of sizes and types of facilities within the US hydropower fleet. The dominant pathways for resulting GHG emissions estimates in the case-study reservoirs were diffusion of carbon dioxide, followed by methane ebullition. Among these case-study reservoirs, total post-impoundment areal flux of carbon ranges from 84 to 767 mgCm−2d−1, which is less variable than what has been reported through measurements at other US and global reservoirs. The net GHG reservoir footprint was less variable and towards the lower end of the range observed from modeling larger global reservoirs, with a range of 138 to 1,052 g CO2 eq m−2 y−1, while the global study reported a range of 115 to 145,472 g CO2 eq m−2 y−1. High variation in emissions normalized with respect to area and generation highlights the need to be cautious when using area or generation in predicting or communicating emissions footprints for reservoirs relative to those of other energy sources, especially given that many of the hydropower reservoirs in the US serve multiple purposes beyond power generation.

Knowledge domain of greenhouse gas emissions from hydropower reservoirs: Hotspots, frontiers and future perspectives

Research on greenhouse gas (GHG; CO2, CH4, N2O) emissions from hydropower reservoirs has attracted widespread attention due to the potential effect on global climate change. However, few attempts have been made to conduct the research progress in this field from a global perspective. In this study, knowledge mapping research was conducted by applying scientometric analysis to explore research hotspots, frontiers and emerging trends of this field from 1993 to 2021, and five research priorities were recommended for the further study. The results showed that the research on GHG emissions from hydropower reservoirs was interdisciplinary, and there was an exponential increase in yearly publication outputs. Additionally, China, Brazil, Canada, America, and France were the leading contributors with high publication outputs, and the Chinese Academy of Science was the most productive and influential institution. Furthermore, the research hotspots in the field mainly focused on CO2, CH4, and N2O emissions and their spatiotemporal characteristics due to great contributions to greenhouse effect and heterogeneities of the GHG emissions from hydropower reservoirs. Research frontiers mainly concentrated on the Three Gorges Reservoir, bubble-mediated gas exchange, GHG emissions across different interfaces and gas transfer velocity. Meanwhile, the first three research frontiers were regarded as emerging trends in recent years. Although great progress has been made in the field, there were still some research challenges. Future research priorities were recommended to strengthen: 1) Application of remote sensing in the research on GHG emissions from hydropower reservoirs, 2) improvement of life cycle assessment research, 3) standardization research on the measurement methods, 4) anthropogenic impacts on carbon dynamics, and 5) international cooperation and database construction. Finally, several mitigation measures were suggested to provide useful insights into the management and control of GHG emissions. In contrast to previous reviews, this paper provides an insight for the visual study of the research on GHG emissions from hydropower reservoirs, helping researchers understand the current research status and future perspectives from a global perspective.

Benefits of pairing floating solar photovoltaics with hydropower reservoirs in Europe

Achieving carbon-neutrality is increasing the demand of renewable electricity which is raising the competition for land and associated acquisition costs. Installation of floating photovoltaic (FPV) on existing hydropower reservoirs offers one solution to limited land availability while providing solar electricity, leveraging water bodies, and reducing water evaporation losses. This work assesses the potential electricity output of FPVs at regional and national levels on 337 hydropower reservoirs in the EU27 considering four scenarios and two types of floaters. Evaporation, water losses and water savings due to FPVs installation are also estimated using climatic parameters for the year 2018. The reservoirs' total water losses are estimated at 9380 mcm. The installation of FPVs of equal installed capacity as the hydropower plants, has the potential to generate 42.31 TWh covering 2.3% of the total reservoir area. In this case, up to 557 mcm could be saved by installing FPV. The FPVs' multiple benefits and the potential offered by existing hydropower reservoirs are compatible with the EU's goals for net zero emissions and more autonomy from imported fossil fuels and energy transformation.

Investigating dam reservoir operation optimization using metaheuristic algorithms

The optimization of dam reservoir operations is of the utmost importance, as operators strive to maximize revenue while minimizing expenses, risks, and deficiencies. Metaheuristics have recently been investigated extensively by researchers in the management of dam reservoirs. But the animal-concept-based metaheuristic algorithm with Lévy flight integration approach has not been used at Karun-4. This paper investigates the optimization of dam reservoir operation using three unexplored metaheuristics: the whale optimization algorithm (WOA), the Levy-flight WOA (LFWOA), and the Harris hawks optimization algorithm (HHO). Utilizing a time series data set on the hydrological and climatic characteristics of the Karun-4 hydroelectric reservoir in Iran, an analysis was conducted. The objective functions and constraints of the Karun-4 hydropower reservoir were examined throughout the optimization procedure. HHO produces the best optimal value, the least-worst optimal value, the best average optimal value, and the best standard deviation (SD) with scores of 0.000026, 0.001735, 0.000520, and 0.000614, respectively, resulting in the best overall ranking mean (RM) with a score of 1.5 at Karun-4. Throughout the duration of the test, the optimized trends of water release and water storage indicate that HHO is superior to the other investigated metaheuristics. WOA has the best correlation of variation (CV) with a score of 0.090195, while LFWOA has the best convergence rate (3.208 s) and best CPU time. Overall, it can be concluded that HHO has the most desirable performance in terms of optimization. Yet, current studies indicate that both WOA and LFWOA generate positive and comparable outcomes.

Extract nonlinear operating rules of multi-reservoir systems using an efficient optimization method

Hydropower plants are known as major renewable energy sources, usually used to meet energy demand during peak periods. The performance of hydropower reservoir systems is mainly affected by their operating rules, thus, optimizing these rules results in higher and/or more reliable energy production. Due to the complex nonlinear, nonconvex, and multivariable characteristics of the hydropower system equations, deriving the operating rules of these systems remains a challenging issue in multi-reservoir systems optimization. This study develops a self-adaptive teaching learning-based algorithm with differential evolution (SATLDE) to derive reliable and precise operating rules for multi-reservoir hydropower systems. The main novelty of SATLDE is its enhanced teaching and learning mechanism with three significant improvements: (i) a ranking probability mechanism is introduced to select the learner or teacher stage adaptively; (ii) at the teacher stage, the teaching mechanism is redefined based on learners’ performance/level; and (iii) at the learner stage, an effective mutation operator with adaptive control parameters is proposed to boost exploration ability. The proposed SATLDE algorithm is applied to the ten-reservoir benchmark systems and a real-world hydropower system in Iran. The results illustrate that the SATLDE achieves superior precision and reliability to other methods. Moreover, results show that SATLDE can increase the total power generation by up to 23.70% compared to other advanced optimization methods. Therefore, this study develops an efficient tool to extract optimal operating rules for the mentioned systems.

Prioritization of Renewable Energy for Sustainable Electricity Generation and an Assessment of Floating Photovoltaic Potential in Lao PDR

Lao PDR faces seasonal power supply problems due to its heavy reliance on hydropower. Thus, the aim of this paper was to prioritize renewable energy (RE) resources for sustainable electricity generation in Lao PDR using the analytic hierarchy process (AHP) method, and to further estimate the energy available for the prioritized RE to enhance the seasonal power supply. Four RE alternatives were assessed considering technological, economic, environmental, and social criteria with twelve overall sub-criteria. The results indicated that hydropower was the most highly prioritized alternative, followed by solar. The resulting weights of the RE prioritization were in agreement with the Lao energy policy and plan. In order to address the seasonal power supply problem, setting-up floating photovoltaic (FPV) units in the existing hydropower reservoirs was proposed. The FPV potential was estimated, and the results revealed that the predicted power demand by 2030, as calculated in the latest Lao national power development strategy, could be fully covered by integrating the FPV output from 10% coverage of the water surface in four existing hydropower reservoirs with the existing power supply in 2020. The proposed FPV technology would provide a solution to enhance the seasonal power supply and reduce the power import.

Vulnerability of water resource management to climate change: Application to a Pyrenean valley

Study region:The Aure Valley in the French Pyrenees. Study focus:This study applies a bottom-up framework for assessing water management vulnerability in terms of hydropower production, environmental regulations, and reservoir storage management by integrating the sensitivity, the management metrics with the participation of stakeholders, and the exposure of the water system. The hydrological model GR6J-CEMANEIGE is implemented to simulate the management metrics in the study region. The sensitivity of management metrics to climate change is investigated by comparing simulation results under current climate conditions and under perturbed climate series. Results are demonstrated with response surfaces, which are overlaid with the predefined thresholds of management metrics. The thresholds help identifying climate conditions that are critical for water management. Plausible climate change pathways are displayed on the response surfaces to assess the probability of critical conditions. New hydrological insights for the region:Results show that annual hydropower production is mostly vulnerable to future drier conditions. Environmental metrics are sensitive to both precipitation and temperature changes while the current policy render the low-flow management less susceptible to risks. Reservoir storage management is found to be extremely sensitive to temperature increase that induces an earlier snowmelt. Although downstream water use is less vulnerable to climate change even under a high greenhouse gases emissions scenario, more intense water competition among stakeholders could be foreseen. Corresponding adaptation actions are proposed to reduce the vulnerability.

Hybrid multi-criteria framework to determine the hierarchy of hydropower reservoirs in India for floatovoltaic installation

• Estimated the floating solar potential of major hydropower reservoirs in India. • Proposed hybrid multi-criteria framework to determine the hierarchy. • Potential hydropower plant in each state for installing FSP plant is identified. • Floatovoltaic potential of Madhya Pradesh is the highest among all the states. Increasing the share of renewable energy power generation is imperative for the attainment of Sustainable Development Goal 7 (SDG-7). Though photovoltaic technology is a reliable renewable alternative in many countries, the land required to expand the installed capacity remained as a prime barrier. In this context, Floating Solar Panels (FSP), also popular as floatovoltaics, are identified as a viable alternative. Installation of floatovoltaics is in the nascent stages in many countries, especially in India, where photovoltaics are popular for harnessing solar energy. Research works addressing the FSP potential of hydropower reservoirs in India and determining their hierarchy to plan developmental works in phase wise manner are limited. This study analyses the FSP potential of all major hydropower reservoirs in India. National inventory data to facilitate floatovoltaic power estimates is created, and an active dashboard is hosted for better transparency and monitoring. Using the created geospatial database, the hierarchy of hydropower reservoirs is evaluated with the help of the proposed hybrid multi-criteria framework developed by integrating Shannon entropy and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) techniques. A wide range of governing parameters, such as (i) available area for installation, (ii) harnessable power, (iii) capacity factor, (iv) elevation, and (v) wind speed, are considered to evaluate the hydropower reservoirs. Overall dominance of each hydropower reservoir evaluated using the proposed multi-criteria approach helps to understand the hierarchy. The findings of this study help stakeholders prioritize the reservoirs for setting up FSP systems.

Evaluation of Nominal Energy Storage at Existing Hydropower Reservoirs in the US

AbstractLong‐term planning and operation of hydropower reservoirs require an understanding of both water and energy storage. As energy storage needs of the evolving grid increase, we must account for the water and energy storage potential of these reservoirs. Given the limitations of current data on existing hydropower, we compile statistics related to storage volume and hydraulic head from publicly available data sets and examine differences in descriptions of US hydropower storage. Assembled characteristics are used to calculate nominal energy storage capacity, a simple measure of potential to generate power from a given volume of water, not factoring in detailed constraints. Inventory‐based estimates of energy storage are calculated at 2,075 dams, which helps put the potential for US hydropower to support energy storage in context with similar evaluations in other regions and with other energy storage technologies. The national energy storage capacity ranges between 34.5 and 45.1 TWh depending on the information used, with 52% of energy storage located at the 10 largest reservoirs in the US. Energy storage capacities are also calculated at 236 dams with historical volume and elevation data. Finally, reservoir inflows provide context for the storage volumes and sensitivities to hydrologic variability. Larger reservoirs with greater storage volume to inflow ratios are concentrated in the Western US, but the majority of hydropower reservoirs store less than the annual inflow. We address several infrastructure and water resource informatics challenges and highlight remaining issues, including representing seasonal or shorter variability in water volumes and representing connected hydropower facilities.

Co-evaluation of climate services. A case study for hydropower generation

Climate services are attracting growing attention and interest as instruments to promote climate change adaptation. The transparent assessment of the potential value brought by the services can play a major role. It can foster the commitment of the user towards a co-generation process increasingly central to climate services creation, can provide developers important information to better tailor the service to the user needs, and can finally increase recognition of the value of the service boosting confidence and trust in the tool.This study presents and then demonstrates the applicability of an evaluation methodology based on the Bayesian framework derived from the information value theory. The specific case study is the Smart Climate Hydropower Tool (SCHT), a climate service designed to support management decisions in hydropower generation. The service uses freely available seasonal forecasts and machine learning algorithms to predict incoming discharge to hydropower reservoirs. The user is ENEL Green Power Italy, and the testing environments are two water basins in Colombia.The study defines the expected value of perfect information, the expected value of the information currently used by the hydropower producer and the expected value of the service information. It then discusses pros and cons of the applicability of the method.

Impact of hydropower reservoirs on floods: evidence from large river basins in Austria

ABSTRACT In this study the impact of hydropower reservoirs on floods is systematically assessed for eight heavily modified river basins in Austria. Since little discharge data from prior to the construction is available, unaffected annual peak discharges downstream of the reservoirs were estimated by transposing the peak runoff of an unaffected catchment, considering the spatial proximity, the catchment area and the temporarily corresponding precipitation conditions. Comparing the observed and estimated discharge, results show significant reductions not only at gauges directly affected by the reservoir but also farther downstream at receiving rivers. The propagation of the flood peak reduction downstream is also related to catchment area and reservoir characteristics. Extreme events with return periods greater than 30 years show a noteworthy flood peak reduction of over 33% on average. These findings show that reservoirs primarily constructed for hydropower generation also contribute significantly to flood control and flood mitigation.

The impacts of hydropower dam construction on the adjacent rural households’ food insecurity in Northwestern Ethiopia

This study examines the impact of two hydropower dam reservoirs, Amerti and Neshe, on the adjacent rural household food insecurity in the Abay Chome district, northwestern Ethiopia. A cross-sectional method was employed to collect data from 485 households (268 affected and 217 non-affected households) following a probability proportional to the size sampling procedure. Households’ food insecurity access scale (HFIAS) and households’ dietary diversity score (HDDS) were used to examine households’ food insecurity status in the study area. The Endogenous Switching Regression model was employed to identify the impact of the dam construction on household food insecurity. The results revealed that the average HDDS and HFIAS in the study area were 5.1 and 10.29, respectively. The study also demonstrated that the affected household’s average HDDS and HFIAS were 4.48 and 10.98, respectively. The study results further revealed that the construction of dams has significantly increased the HFIAS of displaced households by 14.6% while reducing HDDS by 24%. This study found a negative relationship between dam construction and food security, although dam construction is supposed to increase food security by increasing access to water. Thus, we recommend that hydropower reservoirs be effectively designed to reduce the impacts on adjacent communities.