IMPACTS OF CLIMATE VARIABILITY ON THE OPERATIONAL FORECAST AND MANAGEMENT OF THE UPPER DES-MOINES RIVER BASIN

Data from the regulated 14,000 km(2) upper Des Moines River basin and a coupled forecast-control model are used to study the sensitivity of flow forecasts and reservoir management to climatic variability over s cales ranging from daily to interdecadal. Robust coupled forecast-cont rol methodologies are employed to minimize reservoir system sensitivit y to climate variability and change. Large-scale hydrologic-hydraulic prediction models, models for forecast uncertainty, and models for res ervoir control are the building blocks of the methodology. The case st udy concerns the 833.8 x 10(6) m(3) Saylorville reservoir on the upper Des Moines River. The reservoir is operated by the U.S. Corps of Engi neers for flood control, low-flow augmentation, and water supply. The total record of 64 years of daily data is divided into three periods, each with distinct characteristics of atmospheric forcing. For each cl imatic period the coupled forecast-control methodology is simulated wi th a maximum forecast lead time of 4 months and daily resolution. For comparison, the results of operation using current reservoir control p ractices were obtained for the historical periods of study. Large diff erences are found to exist between the probabilistic long-term predict ions of the forecast component when using warm or cool and wet or dry initial conditions in the spring and late summer. Using ensemble input corresponding to warm or cool and wet or dry years increases these di fferences. Current reservoir management practices cannot accommodate h istorical climate variability. Substantial gain in resilience to clima te variability is shown to result when the reservoir is operated by a control scheme which uses reliable forecasts and accounts for their un certainty. This study shows that such coupled forecast-control decisio n systems can mitigate adverse effects of climatic forcing on regional water resources.