Volume 58, Issue 10 e2022WR033016
Research Article

Projection of Streamflow Change Using a Time-Varying Budyko Framework in the Contiguous United States

Zhiying Li

Corresponding Author

Zhiying Li

Department of Geography, The Ohio State University, Columbus, OH, USA

Department of Geography, Dartmouth College, Hanover, NH, USA

Correspondence to:

Z. Li,

[email protected]

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Steven M. Quiring

Steven M. Quiring

Department of Geography, The Ohio State University, Columbus, OH, USA

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First published: 19 October 2022
Citations: 5

Abstract

Predicting future streamflow change is essential for water resources management and understanding the impacts of projected climate and land use changes on water availability. The Budyko framework is a useful and computationally efficient tool to model streamflow at larger spatial scales. This study predicts future streamflow changes in 889 watersheds in the contiguous United States based on projected climate and land use changes from 2040 to 2069. The temporal variability of surface water balance controls, represented by the Budyko ω parameter, was modeled using multiple linear regression, random forest (RF), and gradient boosting. Results show that RF is the optimal model and can explain >85% of the variance in most watersheds. Relative cumulative moisture surplus, forest coverage, crop land and urban land are the most important variables of the time-varying ω in most watersheds. There are statistically significant increases in mean annual precipitation, potential evapotranspiration, and ω in 2040–2069, as compared to 1950–2005. This leads to a statistically significant decrease in the runoff ratio (Q/P). Streamflow is projected to decrease in the central, southwestern, and southeastern United States and increase in the northeast. These projections of water availability which are based on future climate and land use change scenarios can inform water resources management and adaptation strategies.

Key Points

  • Random forest outperforms other tested models in predicting the temporal variability of surface water balance controls

  • Climate seasonality and forest coverage are the most important controls of temporal variability of surface water balance in most watersheds

  • Streamflow is expected to decrease in most watersheds, especially in Southwest, Central, and Southeast United States

Data Availability Statement

The TopoWx data set is provided by the Network for Sustainable Climate Risk Management, University Park, PA, USA, from their website at https://www.scrim.psu.edu/resources/topowx/. The GAGES-II data set is available from https://water.usgs.gov/GIS/metadata/usgswrd/XML/gagesII_Sept2011.xml. The PRISM precipitation data set is available from https://prism.oregonstate.edu/. The streamflow data is available from https://waterwatch.usgs.gov/. The MACA data set is available from http://www.climatologylab.org/maca.html. The Modeled Historical LULC for the Conterminous United States data set is available from https://www.sciencebase.gov/catalog/item/59d3c73de4b05fe04cc3d1d1. The Conterminous United States Land Cover Projections data set is available from https://www.sciencebase.gov/catalog/item/5b96c2f9e4b0702d0e826f6d.