Frequency analysis of storm-scale soil erosion and characterization of extreme erosive events by linking the DWEPP model and a stochastic rainfall generator

Authors: SHMILOVITZ, Y. - Hebrew University; MARRA, F. - National Research Council - Italy; WEI, H. - University Of Arizona; ARGAMAN, E., - Ministry Of Agriculture - Israel; NEARING, M. - Retired ARS Employee; Goodrich, David - Dave; ASWSOULINE, S. - Volcani Center (ARO)

Submitted to: Science of the Total Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/3/2021
Publication Date: 5/8/2021
Citation: Shmilovitz, Y., Marra, F., Wei, H., Argaman, E., Nearing, M., Goodrich, D.C., Aswsouline, S. 2021. Frequency analysis of storm-scale soil erosion and characterization of extreme erosive events by linking the DWEPP model and a stochastic rainfall generator. Science of the Total Environment. 787(15). https://doi.org/10.1016/j.scitotenv.2021.147609.
DOI: https://doi.org/10.1016/j.scitotenv.2021.147609

Interpretive Summary: Soil erosion affects agricultural landscapes worldwide, threatening food security and ecosystem viability. Including extreme storm events in long-term simulations for risk assessment of extreme erosion is typically missing. This study is intended to overcome the typical exclusion of extreme events by quantifying the discrete and cumulative impacts of rainstorms on plot-scale soil erosion and providing storm-scale erosion risks for a cropland region in northern Israel. Central to our analyses is the coupling of (1) A rainfall simulator that is able to reproduce extremes down to 5-minute intervals of intensity; (2) A processes-based event-scale cropland erosion model; and, (3) A new method to analyze when, in a long-term simulation, rainstorms occur and the properties of the rainstorm (e.g. size and the time varying intensity pattern of the rainfall). The erosion model used in this study is DWEPP which stands for Dynamic Water Erosion and Prediction Project. To our knowledge, this is the first study in which DWEPP runoff and soil loss are predicted well at the plot-scale on cropland. We simulated a 300-year time series of precipitation and the associated record of event runoff and sediment yield. Based on this data, the mean annual soil erosion in the study site is quite small. However, an extreme storm that would occur on average every 50 years with a 30-minute maximum intensity of roughly 2.4 inches per hour and roughly 7.9 inches of total storm depth can trigger soil losses that are one order of magnitude higher than the annual mean. The results demonstrate the importance of incorporating extreme events into soil conservation and management tools. We expect our methodology to be valuable for investigating future changes in soil erosion with changing climate.

Technical Abstract: Soil erosion affects agricultural worldwide, threatening food security and ecosystem viability. The complexity of erosive events challenges modeling efforts and explicit inclusion of extreme events in long-term risk assessment is missing. This study is intended to bridge this gap by quantifying the discrete and cumulative impacts of rainstorms on plot-scale soil erosion and providing storm-scale erosion risk analyses for a cropland region in northern Israel. Central to our analyses is the coupling of (1) a stochastic rainfall generator able to reproduce extremes down to 5-minute temporal resolutions; (2) a processes-based event-scale cropland erosion model (Dynamic WEPP, DWEPP); and, (3) a state-of-the-art frequency analysis method that explicitly accounts for rainstorms occurrence and properties. To our knowledge, this is the first study in which DWEPP runoff and soil loss are calibrated at the plot-scale on cropland (NSE is 0.82 and 0.79 for event runoff and sediment, respectively). We generated 300-year stochastic simulations of event runoff and sediment yield based on synthetic precipitation time series. Based on this data, the mean annual soil erosion in the study site is 0.1 kgm-2 [1.1 t ha-1]. Results of the risk analysis indicate that individual extreme rainstorms (>50 return period), characterized by high rainfall intensities (30-minute maximal intensity>~60mmh-1) and high rainfall depth (>~200 mm), can trigger soil losses even one order of magnitude higher than the annual mean. The results demonstrate the importance of incorporating the impact of extreme events into soil conservation and management tools. We expect our methodology to be valuable for investigating future changes in soil erosion with changing climate.