Surface runoff estimation of Wadi Ba Al-Arid watershed NE Libya using SCS-CN, GIS and RS data

كوكب المنى يناير 12, 2023 يناير 12, 2023
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 Surface runoff estimation of Wadi Ba Al-Arid watershed NE Libya using SCS-CN, GIS and RS data

تقدير الجريان السطحي لمسقط مياه وادي بالعريض شمال شرق ليبيا ، باستخدام طريقة SCS-CN وبيانات GIS و RS

Salah Hamad*
Faculty of natural resources and environmental science Omar Al Mukhtar University, Al Baydah, Libya

IJES Iranian Journal of Earth SciencesVol. 12, No. 3, 2020, 168-175

The aim of this study is to estimate runoff in Wadi Ba Al Arid watershed for a period of ten years 2009-2018 by Soil Conservation Service Curve Number (SCS-CN) method in combination with the GIS techniques using remote sensing data. The used data are the daily rainfall data from NASA Prediction of Worldwide Energy Resource (POWER), digital elevation data (DEM) from ALOS PALSAR RTC , satellite imagery from the European Space Agency (ESA) Sentinel, and soil data represented in soil maps of a scale 1: 50,000 and some local studies carried out by several Libyan institutions. The overall area of the watershed is about 136.4 km2 and perimeter107.3 Km. The watershed upstream and downstream is well recognized due to the topographical difference as a result of the tectonic geology. Soil maps were processed and classified into hydrologic soil groups (HSG), where the dominant HSG in the study area are C and D. The Landcover/Land use (LULC) was classified into five classes (forest, shrubs, agriculture, barren land) and built up. The HSG and LULC layers were intersected and the CN values and the weighted curve number for each Antecedent Moisture (AMC) condition were assigned. Furthermore, the runoff depth was estimated and the average runoff volume for ten years during 2009–2018 in the study area was estimated by 1.67 Mm3 which represents 4.6 % of the observed average annual rainfall as 264.3 mm during 2009-2018. The rainfall-runoff relationship has shown a strong correlation with the value of 0.75.
Keywords: Al-Jabal Al-Akhdar, Watershed, Hydrology, GIS, Remote sensing

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