1. Frequency analysis of storm-scale soil erosion and characterization of extreme erosive events by linking the DWEPP model and a stochastic rainfall generator
- Author
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Mark A. Nearing, Haiyan Wei, Yuval Shmilovitz, David C. Goodrich, Efrat Morin, Shmuel Assouline, Francesco Marra, and Eli Argaman
- Subjects
Hydrology ,Return period ,Environmental Engineering ,Stochastic rainfall generator ,010504 meteorology & atmospheric sciences ,Soil erosion ,Erosion risk ,Extreme rainstorms ,DWEPP ,Cropland ,Sediment ,010501 environmental sciences ,01 natural sciences ,Pollution ,Erosion ,Environmental Chemistry ,Environmental science ,Ecosystem ,Precipitation ,WEPP ,Surface runoff ,Soil conservation ,Waste Management and Disposal ,0105 earth and related environmental sciences - Abstract
Soil erosion affects agricultural landscapes worldwide, threatening food security and ecosystem viability. In arable environments, soil loss is primarily caused by short, intense rainstorms, typically characterized by high spatiotemporal variability. 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 kg m-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 > ~60 mm h-1) and high rainfall depth (>~200 mm), can trigger soil losses even one order of magnitude higher than the annual mean. The erosion efficiency of these rainstorms is mainly controlled by the short-duration (≤30 min) maximal intensities. 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.
- Published
- 2021