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Spatial Downscaling of Snow Water Equivalent Using Machine Learning Methods Over the Zayandehroud River Basin, Iran

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Abstract

Snow cover is an informative indicator of climate change and surface hydrological cycles. Despite its essential accurate dynamic measurement (i.e., accumulation, erosion, and runoff), it is poorly known, particularly in mountainous regions. Since passive microwave sensors can contribute to obtaining information about snowpack volume, microwave brightness temperatures (BT) have long been used to assess spatiotemporal variations in snow water equivalent (SWE). However, SWE is greatly influenced by geographic location, terrain parameters/covers, and BT differences, and thus, the low spatial resolution of existing SWE products (i.e., the coarse resolution of AMSR-based products) leads to less satisfactory results, especially in regions with complex terrain conditions, strong seasonal transitions and, great spatiotemporal heterogeneity. A novel multifactor SWE downscaling algorithm based on the support vector regression (SVR) technique has been developed in this study for the Zayandehroud River basin. Thereby, passive microwave BT, location (latitude and longitude), terrain parameters (i.e., elevation, slope, and aspect), and vegetation cover serve as model input data. Evaluation of downscaled SWE estimates against ground-based observations demonstrated that when moving into higher spatial resolution, not only was there no significant decrease in accuracy, but a 4% increase was observed. In addition, this study suggests that integrating passive microwave remote sensing data with other auxiliary data can lead to a more efficient and effective algorithm for retrieving SWE with appropriate spatial resolution over various scales.

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Acknowledgements

The study results are the initial steps of the research project of estimating Zayandehroud dam inflow utilizing AMSR-based SWE observations. The authors kindly appreciate for support of the Iran National Science Foundation (INSF) through the research project of 98020001.

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Authors and Affiliations

  1. Department of Geomatics, Faculty of Civil and Transportation Engineering, University of Isfahan, Isfahan, Iran

    Mina Moradizadeh

  2. Department of Civil Engineering, Faculty of Civil and Transportation Engineering, University of Isfahan, Isfahan, Iran

    Mohammadali Alijanian & Ramtin Moeini

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  1. Mina Moradizadeh
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  2. Mohammadali Alijanian
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Correspondence to Mina Moradizadeh.

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Moradizadeh, M., Alijanian, M. & Moeini, R. Spatial Downscaling of Snow Water Equivalent Using Machine Learning Methods Over the Zayandehroud River Basin, Iran. PFG 91, 391–404 (2023). https://doi.org/10.1007/s41064-023-00249-9

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