When construction of the Grand Ethiopian Renaissance Dam (GERD) is completed, the Nile will have two of the world’s largest dams—the High Aswan Dam (HAD) and the GERD—in two different countries (Egypt and Ethiopia). There is not yet agreement on how these dams will operate to manage scarce water resources. We elucidate the potential risks and opportunities to Egypt, Sudan and Ethiopia by simulating the filling period of the reservoir; a new normal period after the reservoir fills; and a severe multi-year drought after the filling. Our analysis illustrates how during filling the HAD reservoir could fall to levels not seen in recent decades, although the risk of water shortage in Egypt is relatively low. The new normal will benefit Ethiopia and Sudan without significantly affecting water users in Egypt. Management of multi-year droughts will require careful coordination if risks of harmful impacts are to be minimized.

A water resource modeling process is demonstrated to support multistakeholder negotiations over transboundary management of the Nile River. This process addresses the challenge of identifying management options of new hydraulic infrastructure that potentially affects downstream coriparian nations and how the management of existing infrastructure can be adapted. The method includes an exploration of potential management decisions using a multiobjective evolutionary algorithm, intertwined with an iterative process of formulating cooperative strategies to overcome technical and political barriers faced in a transboundary negotiation. The case study is the addition of the Grand Ethiopian Renaissance Dam (GERD) and considers how its operation may be coordinated with adaptations to the operations of Egypt's High Aswan Dam. The results demonstrate that a lack of coordination is likely to be harmful to downstream riparians and suggest that adaptations to infrastructure in Sudan and Egypt can reduce risks to water supplies and energy generation. Although risks can be substantially reduced by agreed releases from the GERD and basic adaptations to the High Aswan Dam, these measures are still insufficient to assure that no additional risk is assumed by Egypt. The method then demonstrates how improvements to water security for both downstream riparians can be achieved through dynamic adaptation of the operation of the GERD during drought conditions. Finally, the paper demonstrates how the robustness of potential management arrangements can be evaluated considering potential effects of climate change, including increased interannual variability and highly uncertain changes such as increases in the future persistence of droughts.

We propose a time series modeling approach based on nonlinear dynamical systems to recover the underlying dynamics and predictability of streamflow and to produce projections with identifiable skill. First, a wavelet spectral analysis is performed on the time series to identify the dominant quasiperiodic bands. The time series is then reconstructed across these bands and summed to obtain a signal time series. This signal is embedded in a D‐dimensional space with an appropriate lag τ to reconstruct the phase space in which the dynamics unfolds. Time‐varying predictability is assessed by quantifying the divergence of trajectories in the phase space with time, using Local Lyapunov Exponents. Ensembles of projections from a current time are generated by block resampling trajectories of desired projection length, from the K‐nearest neighbors of the current vector in the phase space. This modeling approach was applied to the naturalized historical and paleoreconstructed streamflow at Lees Ferry gauge on the Colorado River, which offered three interesting insights. (i) The flows exhibited significant epochal variations in predictability. (ii) The predictability of the flow quantified by Local Lyapunov Exponent is related to the variance of the flow signal and selected climate indices. (iii) Blind projections of flow during epochs identified as highly predictable showed good skill in capturing the distributional and threshold exceedance statistics and poor performance during low predictability epochs. The ability to assess the potential skill of these long lead projections opens opportunities to perceive hydrologic predictability and consequently water management in a new paradigm.

Water managers in the western United States and throughout the world are facing the increasing challenge of supplying a variety of water demands under the growing stresses of climate variability and of population and economic growth. Accurate streamflow forecasts are key to the water resources planning and decision-making process. There is growing evidence that variability in western streamflow is modulated by large-scale ocean-atmospheric features. Traditional forecasting techniques, however, do not systematically utilize large-scale climate information. In this study we present a framework for incorporating climate information into water resources decision-making and demonstrate the method on the semiarid Truckee-Carson Basin in Nevada where environmental, agricultural, and municipal demands compete for a limited supply of water. In this basin, water managers must plan carefully to meet the demands of timing and required flowrates. The framework presented in this paper consists of a streamflow forecast ...

This study contributes a many-objective analysis of water supply in the Tarrant Regional Water District (TRWD) in Texas in the United States, in order to demonstrate how multiobjective evolutionary algorithm (MOEA) decision support can be used with sophisticated water infrastructure models in a highly constrained water-planning environment. A detailed representation of TRWD’s network in the river system modeling tool RiverWare (a model actually used by the utility) is coupled with the Borg MOEA to solve a seven-objective problem formulation. Objectives within the formulation include systemwide performance objectives, as well as reliability objectives to balance multiple reservoirs, calculated using two stochastic hydrology scenarios. The results provide valuable information to TRWD that may inform the utility’s approach to optimization and decision making in the future, as well as illuminate the benefits of optimizing systemwide and component-specific objectives to reveal hidden system dynamics.