Toward Understanding the Value of Climate Information for Multiobjective Reservoir Management under Present and Future Climate and Demand Scenarios

Abstract

Numerical simulation techniques and idealized reservoir management models are used to assess the utility of climate information for the effective management of a single multiobjective reservoir. Reservoir management considers meeting release and reservoir volume targets and minimizing wasteful spillage. The influence of reservoir size and inflow variability parameters on the management benefits is examined. The effects of climate and demand (release target) change on the management policies and performance are also quantified for various change scenarios. Inflow forecasts emulate ensembles of dynamical forecasts for a hypothetical climate system with somewhat predictable low-frequency variability. The analysis considers the impacts of forecast skill. The mathematical problem is cast in a dimensionless time and volume framework to allow generalization. The present work complements existing research results for specific applications and expands earlier analytical results for simpler management situations in an effort to draw general conclusions for the present-day reservoir management problem under uncertainty. The findings support the following conclusions: (i) reliable inflow forecasts are beneficial for reservoir management under most situations if adaptive management is employed; (ii) tolerance to forecasts of lower reliability tends to be higher for larger reservoirs; (iii) reliable inflow forecasts are most useful for a midrange of reservoir capacities; (iv) demand changes are more detrimental to reservoir management performance than inflow change effects of similar magnitude; (v) adaptive management is effective for mitigating climatic change effects and may even help to mitigate demand change effects.