A dynamical statistical framework for seasonal streamflow forecasting in an agricultural watershed

@article{Slater2017ADS,
  title={A dynamical statistical framework for seasonal streamflow forecasting in an agricultural watershed},
  author={Louise J. Slater and Gabriele Villarini and A. Allen Bradley and Gabriel A. Vecchi},
  journal={Climate Dynamics},
  year={2017},
  pages={1-17}
}
The state of Iowa in the US Midwest is regularly affected by major floods and has seen a notable increase in agricultural land cover over the twentieth century. We present a novel statistical-dynamical approach for probabilistic seasonal streamflow forecasting using land cover and General Circulation Model (GCM) precipitation forecasts. Low to high flows are modelled and forecast for the Raccoon River at Van Meter, a 8900 km2 catchment located in central-western Iowa. Statistical model fits for… CONTINUE READING

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