Comparing Rainfall Erosivity Estimation Methods Using Weather Radar Data for the State of Hesse (Germany)

Jennifer Kreklow,Björn Tetzlaff,Klaus Friedrich,Bastian Steinhoff-Knopp

doi:10.3390/w12051424

Abstract

Rainfall erosivity exhibits a high spatiotemporal variability. Rain gauges are not capable of detecting small-scale erosive rainfall events comprehensively. Nonetheless, many operational instruments for assessing soil erosion risk, such as the erosion atlas used in the state of Hesse in Germany, are still based on spatially interpolated rain gauge data and regression equations derived in the 1980s to estimate rainfall erosivity. Radar-based quantitative precipitation estimates with high spatiotemporal resolution are capable of mapping erosive rainfall comprehensively. In this study, radar climatology data with a spatiotemporal resolution of 1 km2 and 5 min are used alongside rain gauge data to compare erosivity estimation methods used in erosion control practice. The aim is to assess the impacts of methodology, climate change and input data resolution, quality and spatial extent on the R-factor of the Universal Soil Loss Equation (USLE). Our results clearly show that R-factors have increased significantly due to climate change and that current R-factor maps need to be updated by using more recent and spatially distributed rainfall data. Radar climatology data show a high potential to improve rainfall erosivity estimations, but uncertainties regarding data quality and a need for further research on data correction approaches are becoming evident.

Highlights

The R-factor is a measure of rainfall erosivity and an important input variable for estimating soil losses by water using the Universal Soil Loss Equation (USLE) and its many variations [1]
For the 72 stations operated by DWD, which were used for radar data adjustments, the average difference between RYWG,DIN and RG,DIN amounts to 19.1 kJ/m2 mm/h, whereas the average difference at the 38 stations operated by HLNUG is slightly higher with 23.1 kJ/m2 mm/h
Two correction factors proposed in other studies were tested and updated regression equations were derived for the German federal state of Hesse

Summary

Introduction

The R-factor is a measure of rainfall erosivity and an important input variable for estimating soil losses by water using the Universal Soil Loss Equation (USLE) and its many variations [1]. Measurement data from rain gauges or, more recently, from automated rain gauges were used for estimating rainfall erosivity. The R-factors calculated from these point-scale data for every station are spatially interpolated to derive maps of rainfall erosivity. This approach has been recently applied to generate a European erosivity map [4].

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