The Science and Practice of River Forecasting Systems in the United States and Australia

Operational river forecasts have been long produced to support water resources management in the United States and Australia. These forecasts cover a range of timescales from flash flooding (e.g. minutes to hours ahead) to seasonal (e.g. months ahead) and are generated by a range of statistical (e.g. regression-based) and dynamical (e.g. rainfall-runoff) model based techniques. The extent of human control over the forecasts, such as by adjusting model inputs and outputs, varies from nearly completely automated systems to those where forecasts are generated after discussion among a group of experts. Historical and realtime data availability, the complexity of hydrologic processes, forecast user needs, and forecasting institution support/resource availability (e.g. computing power, money for model maintenance) influence the character and effectiveness of operational forecasting systems. Although it is an active research topic, nearly all operational forecasting systems struggle to make quantitative use of Numerical Weather Prediction model-based precipitation forecasts. Similarly, global-scale and spatially distributed hydrologic information, informed by remotely sensed measurements (e.g. radar and satellite) are available experimentally but suffer from biases and other limitations. Forecast uncertainty is commonly estimated operationally by using an ensemble of future precipitation scenarios and/or a measure of historical model error. However, probabilistic forecast communication and use remains a stumbling block for many. The flexibility of the water manager’s operating procedures and the size of the reservoir relative to incoming streamflow determine the relevance of forecasts to hydropower operations; moderately-sized reservoirs that can draw down in anticipation of high flows or slow releases in anticipation of drought stand to benefit the most.

کلیدواژه ها:

Forecasting ، Prediction ، Rivers ، Modeling ، Rainfall-runoff