Precipitation Forecasting and Monitoring in Degraded Land: A Study Case in Zaghouan

Okba Weslati (), Moncef Bouaziz and Mohamed-Moncef Serbaji
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Okba Weslati: Laboratory of Water, Energy, Environment, National Engineering School of Sfax, Road of Sokra 3 km, Sfax 3038, Tunisia
Moncef Bouaziz: Institute for Mine Surveying and Geodesy, Freiberg University of Technology, 0959 Freiberg, Germany
Mohamed-Moncef Serbaji: Laboratory of Water, Energy, Environment, National Engineering School of Sfax, Road of Sokra 3 km, Sfax 3038, Tunisia

Land, 2023, vol. 12, issue 4, 1-18

Abstract: The study aimed to forecast and monitor drought over degraded land based on monthly precipitation using the Seasonal Autoregressive Integrated Moving Average (SARIMA) approach. Several statistical parameters to select the most appropriate model were applied. The results indicate that the SARIMA (1,1,1) (0,1,1)12 is the most suitable for 1981 to 2019 CHIRPS time-series data. The combination of precipitation data and this approved model will subsequently be applied to compute, assess, and predict the severity of drought in the study area. The forecasting performance of the generated SARIMA model was evaluated according to the mean absolute percentage error (15%), which indicated that the proposed model showed high performance in forecasting drought. The forecasting trends showed adequate results, fitting well with the historical tendencies of drought events.

Keywords: drought; forecasting; monitoring; SARIMA; precipitation (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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