EO-data and remote sensing integration for water erosion modelling and mapping in North Tunisia: a case study of Medjerda watershed

Abstract

Understanding, mapping and modelling of water erosion process become a serious concern for water and soil conservation practitioners, as well as decision-makers concerned with natural resource management and agricultural policies. The current research aims to map and quantify water erosion rates in the Upper-valley of Medjerda Watershed in Northern Tunisia. A systematic method incorporating three water erosion models (RUSLE: revised soil loss equation, FAO: food and agricultural organization, and EPM: erosion potential model) was adopted. Indeed, multi-sources earth observation data (EO-data), geographic information systems (GIS), and remote sensing (RS) techniques were integrated into the modelling process. Mean annual erosion rates estimated by RUSLE, FAO, and EPM models vary between 18 and 71 t/ha/yr. Examination of three methods reveals that soil loss values estimated with both FAO and EMP models are more consistence than RUSLE estimates. Indeed, about 51% to 78% of the study area is affected by moderate to very high erosive dynamic. Moreover, six methods depending on the drainage area and the morphometric characteristics were adopted to calculate the sediment delivery ratio (SDR). Key results indicate that Maner’s SDR model is the best one for sediment yield estimation. The findings of this work may be helpful for water erosion mitigation purposes.

Keywords

• Water erosion
• modelling
• EO-data
• GIS and RS
• SDR
• Medjerda watershed