Incorporating Antecedent Soil Moisture into Streamflow Forecasting

Abdoul Oubeidillah,Thomas Piechota,Glenn Tootle

doi:10.3390/hydrology6020050

Abstract

This study incorporates antecedent (preceding) soil moisture into forecasting streamflow volumes within the North Platte River Basin, Colorado/Wyoming (USA). The incorporation of antecedent soil moisture accounts for infiltration and can improve streamflow predictions. Current Natural Resource Conservation Service (NRCS) forecasting methods are replicated, and a comparison is drawn between current NRCS forecasts and proposed forecasting methods using antecedent soil moisture. Current predictors used by the NRCS in regression-based streamflow forecasting include precipitation, streamflow persistence (previous season streamflow volume) and snow water equivalent (SWE) from SNOTEL (snow telemetry) sites. Proposed methods utilize antecedent soil moisture as a predictor variable in addition to the predictors noted above. A decision system was used to segregate data based on antecedent soil moisture conditions (e.g., dry, wet or normal). Principal Components Analysis and Stepwise Linear Regression were applied to generate streamflow forecasts, and numerous statistics were determined to measure forecast skill. The results show that when incorporating antecedent soil moisture, the “poor” forecasts (i.e., years in which the NRCS forecast differed greatly from the observed value) were improved, while the overall forecast skill remains unchanged. The research presented shows the need to increase the monitoring and collection of soil moisture data in mountainous western U.S. watersheds, as this parameter results in improved forecast skill.

Highlights

Streamflow forecasting is the estimation of seasonal volumes of water at a specific site at a specific time
The Natural Resource Conservation Service (NRCS) has developed a Visual Interactive Prediction and Estimation Routine (VIPER) to forecast streamflow. This forecast application gathers all data on a monthly to seasonal time scale in real-time directly from the source. Linked with both historical and real-time data, the hydrologist specifies a list of predictor sites for a specified streamflow gage, the type of analysis desired, and equations are automatically developed and the forecast produced in real-time
The first of these SNOTEL sites in the North Platte River Basin was established in the early 1970s, which limits the digital data that can be used in producing forecasts

Summary

Introduction

Streamflow forecasting is the estimation of seasonal volumes of water at a specific site (gauge) at a specific time. The Natural Resource Conservation Service (NRCS), in cooperation with the National Weather Service (NWS), issue water supply (or streamflow) forecasts for over 750 points in the western U.S, near the first of the month between January and June each year. These forecasts assist water managers/users for future planning according to the forecasted amount of water available. While these forecasts are produced monthly, this study focuses on forecasting the cumulative April-May-June-July streamflow volume. The primary objective of these forecasts is to minimize any risk and uncertainty for water managers and to create a more efficient use of a scarce resource

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Conclusion