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There is overwhelming evidence that climate change can alter the precipitation patterns, which in turn will affect the quantity and timing of freshwater availability and also the reservoir operations. Moreover, the exisiting approaches for reservoir operation correspond to historical conditions, and do not account for future climate non-stationarity. In this thesis, we explored strategies to combat the effects of climate variablility and extremes on reservoir operation and freshwater supply. First, we examine an approach to mitigate the effects of reservoir supply uncertainty due to climate variability. We develop a joint water supply model by combining the operation of a reservoir with wastewater recycling plants and seawater desalination plants. In comparison to stand-alone reservoir operation, the proposed joint system is less vulnerable to climate uncertainties, and is also cost effective. The joint model is operated on a daily time step following a cost-based priority based rule to govern the water release or production from the facilities. The joint system is modeled as a multi-objective optimization problem with the double objectives of minimizing risk and vulnerability, subject to a minimum limit on resilience and water quality, capacity and budget constraints. The system is optimized using a genetic algorithm. The joint model is applied to two hypothetical but realistic cases based on India and California, considering various scenarios of costs and budget. The results show the joint operation to improve water supply security. Even though the joint operation requires an additional cost over that of stand-alone reservoir operation, this cost is significantly smaller than the case when the three sources are operated separately in a non-integrated fashion. This study contributes to a greater quantitative understanding of desalination as a redundancy measure for adapting water supply infrastructures for a future of greater scarcity and uncertainty. Next, we exam

There is overwhelming evidence that climate change can alter the precipitation patterns, which in turn will affect the quantity and timing of freshwater availability and also the reservoir operations. Moreover, the exisiting approaches for reservoir operation correspond to historical conditions, and do not account for future climate non-stationarity. In this thesis, we explored strategies to combat the effects of climate variablility and extremes on reservoir operation and freshwater supply. First, we examine an approach to mitigate the effects of reservoir supply uncertainty due to climate variability. We develop a joint water supply model by combining the operation of a reservoir with wastewater recycling plants and seawater desalination plants. In comparison to stand-alone reservoir operation, the proposed joint system is less vulnerable to climate uncertainties, and is also cost effective. The joint model is operated on a daily time step following a cost-based priority based rule to govern the water release or production from the facilities. The joint system is modeled as a multi-objective optimization problem with the double objectives of minimizing risk and vulnerability, subject to a minimum limit on resilience and water quality, capacity and budget constraints. The system is optimized using a genetic algorithm. The joint model is applied to two hypothetical but realistic cases based on India and California, considering various scenarios of costs and budget. The results show the joint operation to improve water supply security. Even though the joint operation requires an additional cost over that of stand-alone reservoir operation, this cost is significantly smaller than the case when the three sources are operated separately in a non-integrated fashion. This study contributes to a greater quantitative understanding of desalination as a redundancy measure for adapting water supply infrastructures for a future of greater scarcity and uncertainty. Next, we exam

There is overwhelming evidence that climate change can alter the precipitation patterns, which in turn will affect the quantity and timing of freshwater availability and also the reservoir operations. Moreover, the exisiting approaches for reservoir operation correspond to historical conditions, and do not account for future climate non-stationarity. In this thesis, we explored strategies to combat the effects of climate variablility and extremes on reservoir operation and freshwater supply. First, we examine an approach to mitigate the effects of reservoir supply uncertainty due to climate variability. We develop a joint water supply model by combining the operation of a reservoir with wastewater recycling plants and seawater desalination plants. In comparison to stand-alone reservoir operation, the proposed joint system is less vulnerable to climate uncertainties, and is also cost effective. The joint model is operated on a daily time step following a cost-based priority based rule to govern the water release or production from the facilities. The joint system is modeled as a multi-objective optimization problem with the double objectives of minimizing risk and vulnerability, subject to a minimum limit on resilience and water quality, capacity and budget constraints. The system is optimized using a genetic algorithm. The joint model is applied to two hypothetical but realistic cases based on India and California, considering various scenarios of costs and budget. The results show the joint operation to improve water supply security. Even though the joint operation requires an additional cost over that of stand-alone reservoir operation, this cost is significantly smaller than the case when the three sources are operated separately in a non-integrated fashion. This study contributes to a greater quantitative understanding of desalination as a redundancy measure for adapting water supply infrastructures for a future of greater scarcity and uncertainty. Next, we exam

We investigate the potential of integrating desalination to existing reservoir systems to mitigate supply uncertainty. Desalinated seawater and wastewater are relatively reliable but expensive. Water from natural resources like reservoirs is generally cheaper but climate sensitive. We propose combining the operation of a reservoir and seawater and wastewater desalination plants for an overall system that is less vulnerable to scarcity and uncertainty, while constraining total cost. The joint system is modeled as a multiobjective optimization problem with the double objectives of minimizing risk and vulnerability, subject to a minimum limit on resilience. The joint model is applied to two cases, one based on the climate and demands of a location in India and the other of a location in California. The results for the Indian case indicate that it is possible for the joint system to reduce risk and vulnerability to zero given a budget increase of 20–120% under current climate conditions and 30–150% under projected future conditions. For the Californian case, this would require budget increases of 20–80% and 30–140% under current and future conditions, respectively. Further, our analysis shows a two-way interaction between the reservoir and desalination plants where the optimal operation of the former is just as much affected by the latter as the latter by the former. This highlights the importance of an integrated management approach. This study contributes to a greater quantitative understanding of desalination as a redundancy measure for adapting water supply infrastructures for a future of greater scarcity and uncertainty. © 2016. American Geophysical Union. All Rights Reserved.

Accurate stream flow forecasts are critical for reservoir operations for water supply planning. As the world urban population increases, the demand for water in cities is also increasing, making accurate forecasts even more important. However, accurate forecasting of stream flows is difficult owing to short- and long-term weather variations. We propose to reduce this need for accurate stream flow forecasts by augmenting reservoir operations with seawater desalination and wastewater recycling. We develop a robust operating policy for the joint operation of the three sources. With the joint model, we tap into the unlimited reserve of seawater through desalination, and make use of local supplies of wastewater through recycling. However, both seawater desalination and recycling are energy intensive and relatively expensive. Reservoir water on the other hand, is generally cheaper but is limited and variable in its availability, increasing the risk of water shortage during extreme climate events. We operate the joint system by optimizing it using a genetic algorithm to maximize water supply reliability and resilience while minimizing vulnerability subject to a budget constraint and for a given stream flow forecast. To compute the total cost of the system, we take into account the pumping cost of transporting reservoir water to its final destination, and the capital and operating costs of desalinating seawater and recycling wastewater. We produce results for different hydro climatic regions based on artificial stream flows we generate using a simple hydrological model and an autoregressive time series model. The artificial flows are generated from precipitation and temperature data from the Canadian Regional Climate model for present and future scenarios. We observe that the joint operation is able to effectively minimize the negative effects of stream flow forecast uncertainty on system performance at an overall cost that is not significantly greater than the cost of a st

Accurate stream flow forecasts are critical for reservoir operations for water supply planning. As the world urban population increases, the demand for water in cities is also increasing, making accurate forecasts even more important. However, accurate forecasting of stream flows is difficult owing to short- and long-term weather variations. We propose to reduce this need for accurate stream flow forecasts by augmenting reservoir operations with seawater desalination and wastewater recycling. We develop a robust operating policy for the joint operation of the three sources. With the joint model, we tap into the unlimited reserve of seawater through desalination, and make use of local supplies of wastewater through recycling. However, both seawater desalination and recycling are energy intensive and relatively expensive. Reservoir water on the other hand, is generally cheaper but is limited and variable in its availability, increasing the risk of water shortage during extreme climate events. We operate the joint system by optimizing it using a genetic algorithm to maximize water supply reliability and resilience while minimizing vulnerability subject to a budget constraint and for a given stream flow forecast. To compute the total cost of the system, we take into account the pumping cost of transporting reservoir water to its final destination, and the capital and operating costs of desalinating seawater and recycling wastewater. We produce results for different hydro climatic regions based on artificial stream flows we generate using a simple hydrological model and an autoregressive time series model. The artificial flows are generated from precipitation and temperature data from the Canadian Regional Climate model for present and future scenarios. We observe that the joint operation is able to effectively minimize the negative effects of stream flow forecast uncertainty on system performance at an overall cost that is not significantly greater than the cost of a st