Soil erosion assessment in the Blue Nile Basin driven by a novel RUSLE-GEE framework

Abdelrazek Elnashar; Hongwei Zeng; Bingfang Wu; Ayele Almaw Fenta; Mohsen Nabil; Robert Duerler

doi:10.1016/j.scitotenv.2021.148466

Soil erosion assessment in the Blue Nile Basin driven by a novel RUSLE-GEE framework

Sci Total Environ. 2021 Nov 1:793:148466. doi: 10.1016/j.scitotenv.2021.148466. Epub 2021 Jun 12.

Authors

Abdelrazek Elnashar¹, Hongwei Zeng², Bingfang Wu³, Ayele Almaw Fenta⁴, Mohsen Nabil⁵, Robert Duerler⁶

Affiliations

¹ State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China; Department of Natural Resources, Faculty of African Postgraduate Studies, Cairo University, Giza 12613, Egypt. Electronic address: abdelrazek@aircas.ac.cn.
² State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address: zenghw@aircas.ac.cn.
³ State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address: wubf@aircas.ac.cn.
⁴ Arid Land Research Center, Tottori University, 1390 Hamasaka, Tottori 680-0001, Japan; Department of Land Resources Management and Environmental Protection, Mekelle University, Mekelle 231, Ethiopia. Electronic address: ayelealmaw@tottori-u.ac.jp.
⁵ State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China; Division of Agriculture Applications, Soils, and Marine (AASMD), National Authority for Remote Sensing & Space Sciences, Egypt. Electronic address: mohsen2017@radi.ac.cn.
⁶ State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address: duerler2@mails.ucas.ac.cn.

PMID: 34175609
DOI: 10.1016/j.scitotenv.2021.148466

Abstract

Assessment of soil loss and understanding its major drivers are essential to implement targeted management interventions. We have proposed and developed a Revised Universal Soil Loss Equation framework fully implemented in the Google Earth Engine cloud platform (RUSLE-GEE) for high spatial resolution (90 m) soil erosion assessment. Using RUSLE-GEE, we analyzed the soil loss rate for different erosion levels, land cover types, and slopes in the Blue Nile Basin. The results showed that the mean soil loss rate is 39.73, 57.98, and 6.40 t ha^-1 yr^-1 for the entire Blue Nile, Upper Blue Nile, and Lower Blue Nile Basins, respectively. Our results also indicated that soil protection measures should be implemented in approximately 27% of the Blue Nile Basin, as these areas face a moderate to high risk of erosion (>10 t ha^-1 yr^-1). In addition, downscaling the Tropical Rainfall Measuring Mission (TRMM) precipitation data from 25 km to 1 km spatial resolution significantly impacts rainfall erosivity and soil loss rate. In terms of soil erosion assessment, the study showed the rapid characterization of soil loss rates that could be used to prioritize erosion mitigation plans to support sustainable land resources and tackle land degradation in the Blue Nile Basin.

Keywords: Cloud computing; Google Earth Engine; Revised Universal Soil Loss Equation; Soil loss severity analysis; TRMM spatial downscaling.

MeSH terms

Conservation of Natural Resources*
Environmental Monitoring
Geographic Information Systems
Soil
Soil Erosion*

Substances

Soil