{"title":"比较各种预测建模方法,以估算空间异质性实地条件下的土壤侵蚀情况","authors":"","doi":"10.1016/j.envsoft.2024.106145","DOIUrl":null,"url":null,"abstract":"<div><p>The accuracy of soil erosion models in agroecosystems with heterogeneous field conditions is challenging due to uncertainties from soil water fluxes and crop growth. In this study, we coupled two modeling methods (Freebairn and Rose) to represent soil erosion with a process-based crop and runoff models within the SIMPLACE framework. Their accuracy was compared to a statistical model developed using 16 erosion plots (each of 625 cm<sup>2</sup>) within the same field. Uncertainty analysis showed that runoff and slope angle were the most critical components for predicting sediment yield in both models, followed by soil erodibility in the Freebairn model and entrainment efficiency in the Rose model. However, due to plot size constraints, slope-length effects were not examined. The Freebairn model had a slightly higher accuracy (RMSE = 0.69 t ha<sup>−1</sup> d<sup>−1</sup>) of sediment yield predictions than the Rose model (RMSE = 0.83 t ha<sup>−1</sup> d<sup>−1</sup>). Both models are effective for predicting soil loss with appropriate parameter values.</p></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":null,"pages":null},"PeriodicalIF":4.8000,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1364815224002068/pdfft?md5=77146a646c3da8c94e0226897e3564b3&pid=1-s2.0-S1364815224002068-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Comparison of predictive modeling approaches to estimate soil erosion under spatially heterogeneous field conditions\",\"authors\":\"\",\"doi\":\"10.1016/j.envsoft.2024.106145\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The accuracy of soil erosion models in agroecosystems with heterogeneous field conditions is challenging due to uncertainties from soil water fluxes and crop growth. In this study, we coupled two modeling methods (Freebairn and Rose) to represent soil erosion with a process-based crop and runoff models within the SIMPLACE framework. Their accuracy was compared to a statistical model developed using 16 erosion plots (each of 625 cm<sup>2</sup>) within the same field. Uncertainty analysis showed that runoff and slope angle were the most critical components for predicting sediment yield in both models, followed by soil erodibility in the Freebairn model and entrainment efficiency in the Rose model. However, due to plot size constraints, slope-length effects were not examined. The Freebairn model had a slightly higher accuracy (RMSE = 0.69 t ha<sup>−1</sup> d<sup>−1</sup>) of sediment yield predictions than the Rose model (RMSE = 0.83 t ha<sup>−1</sup> d<sup>−1</sup>). Both models are effective for predicting soil loss with appropriate parameter values.</p></div>\",\"PeriodicalId\":310,\"journal\":{\"name\":\"Environmental Modelling & Software\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2024-07-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1364815224002068/pdfft?md5=77146a646c3da8c94e0226897e3564b3&pid=1-s2.0-S1364815224002068-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Modelling & Software\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1364815224002068\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Modelling & Software","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1364815224002068","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Comparison of predictive modeling approaches to estimate soil erosion under spatially heterogeneous field conditions
The accuracy of soil erosion models in agroecosystems with heterogeneous field conditions is challenging due to uncertainties from soil water fluxes and crop growth. In this study, we coupled two modeling methods (Freebairn and Rose) to represent soil erosion with a process-based crop and runoff models within the SIMPLACE framework. Their accuracy was compared to a statistical model developed using 16 erosion plots (each of 625 cm2) within the same field. Uncertainty analysis showed that runoff and slope angle were the most critical components for predicting sediment yield in both models, followed by soil erodibility in the Freebairn model and entrainment efficiency in the Rose model. However, due to plot size constraints, slope-length effects were not examined. The Freebairn model had a slightly higher accuracy (RMSE = 0.69 t ha−1 d−1) of sediment yield predictions than the Rose model (RMSE = 0.83 t ha−1 d−1). Both models are effective for predicting soil loss with appropriate parameter values.
期刊介绍:
Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.