{"title":"基于修正通用水土流失方程和GIS的土壤侵蚀风险及产沙量评价——以埃塞俄比亚西南部Nesha流域为例","authors":"Tesfahun Endalew , Dereje Biru","doi":"10.1016/j.ringps.2022.100049","DOIUrl":null,"url":null,"abstract":"<div><p>This research was administered to spatially predict the soil loss rate of the kaffa zone using a model estimate and GIS. Revised Universal Soil Loss Equation (RUSLE) adapted to Ethiopian conditions was accustomed estimate potential soil losses by utilizing information on rainfall erosivity (R) using interpolation of rainfall data, soil erodibility (K) using DSMW soil map, vegetation cover (C) using spot6 images, topography (LS) using Digital Elevation Model (DEM) and conservation practices (P) using DEM and satellite images. supported the analysis, the mean and total annual soil loss potential of the study area was 30 tons ha-1 year-1 and 36,264.5tons ha-1 year-1, respectively. The results also showed that about 2.89, 8.02, 15.31 and 73.78% of the study area were classified as slight, moderate, high, and very high with values ranging from 0 to 15,15 to50,50 to 200, and >200 tons ha-1 year-1, respectively. The study demonstrates that the RUSLE using GIS and RS provides a great advantage to spatially analyzing multi-layer of knowledge. The expected amount of soil loss and its spatial distribution could facilitate sustainable land use and management.</p></div>","PeriodicalId":101086,"journal":{"name":"Results in Geophysical Sciences","volume":"12 ","pages":"Article 100049"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666828922000098/pdfft?md5=a6f6440a0184070fbfcbe4a15ded8d62&pid=1-s2.0-S2666828922000098-main.pdf","citationCount":"5","resultStr":"{\"title\":\"Soil erosion risk and sediment yield assessment with Revised Universal Soil Loss Equation and GIS: The case of Nesha watershed, Southwestern Ethiopia\",\"authors\":\"Tesfahun Endalew , Dereje Biru\",\"doi\":\"10.1016/j.ringps.2022.100049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This research was administered to spatially predict the soil loss rate of the kaffa zone using a model estimate and GIS. Revised Universal Soil Loss Equation (RUSLE) adapted to Ethiopian conditions was accustomed estimate potential soil losses by utilizing information on rainfall erosivity (R) using interpolation of rainfall data, soil erodibility (K) using DSMW soil map, vegetation cover (C) using spot6 images, topography (LS) using Digital Elevation Model (DEM) and conservation practices (P) using DEM and satellite images. supported the analysis, the mean and total annual soil loss potential of the study area was 30 tons ha-1 year-1 and 36,264.5tons ha-1 year-1, respectively. The results also showed that about 2.89, 8.02, 15.31 and 73.78% of the study area were classified as slight, moderate, high, and very high with values ranging from 0 to 15,15 to50,50 to 200, and >200 tons ha-1 year-1, respectively. The study demonstrates that the RUSLE using GIS and RS provides a great advantage to spatially analyzing multi-layer of knowledge. The expected amount of soil loss and its spatial distribution could facilitate sustainable land use and management.</p></div>\",\"PeriodicalId\":101086,\"journal\":{\"name\":\"Results in Geophysical Sciences\",\"volume\":\"12 \",\"pages\":\"Article 100049\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2666828922000098/pdfft?md5=a6f6440a0184070fbfcbe4a15ded8d62&pid=1-s2.0-S2666828922000098-main.pdf\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Results in Geophysical Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666828922000098\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Results in Geophysical Sciences","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666828922000098","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
摘要
本研究采用模型估算和GIS技术对咖法区土壤流失率进行了空间预测。修订后的通用土壤流失方程(RUSLE)适用于埃塞俄比亚的条件,利用降雨侵蚀力(R)(使用降雨数据插值)、土壤可蚀性(K)(使用DSMW土壤图)、植被覆盖(C)(使用spot6图像)、地形(LS)(使用数字高程模型(DEM))和保护措施(P)(使用DEM和卫星图像)来估计潜在的土壤损失。研究区年平均土壤流失潜力为30 t ha-1 -1,年总土壤流失潜力为36264.5 t ha-1 -1。研究区轻度、中度、高、甚高的比例分别为2.89%、8.02、15.31%和73.78%,分别为0 ~ 15、15 ~ 50、50 ~ 200和200吨/年。研究表明,基于GIS和RS的RUSLE对多层次知识的空间分析具有很大的优势。预测的土壤流失量及其空间分布可以促进土地的可持续利用和管理。
Soil erosion risk and sediment yield assessment with Revised Universal Soil Loss Equation and GIS: The case of Nesha watershed, Southwestern Ethiopia
This research was administered to spatially predict the soil loss rate of the kaffa zone using a model estimate and GIS. Revised Universal Soil Loss Equation (RUSLE) adapted to Ethiopian conditions was accustomed estimate potential soil losses by utilizing information on rainfall erosivity (R) using interpolation of rainfall data, soil erodibility (K) using DSMW soil map, vegetation cover (C) using spot6 images, topography (LS) using Digital Elevation Model (DEM) and conservation practices (P) using DEM and satellite images. supported the analysis, the mean and total annual soil loss potential of the study area was 30 tons ha-1 year-1 and 36,264.5tons ha-1 year-1, respectively. The results also showed that about 2.89, 8.02, 15.31 and 73.78% of the study area were classified as slight, moderate, high, and very high with values ranging from 0 to 15,15 to50,50 to 200, and >200 tons ha-1 year-1, respectively. The study demonstrates that the RUSLE using GIS and RS provides a great advantage to spatially analyzing multi-layer of knowledge. The expected amount of soil loss and its spatial distribution could facilitate sustainable land use and management.