Comparative Analysis of Climate Change Impacts on Climatic Variables and Reference Evapotranspiration in Tunisian Semi-Arid Region

Basma Latrech, Taoufik Hermassi (), Samir Yacoubi, Adel Slatni, Fathia Jarray, Laurent Pouget and Mohamed Ali Ben Abdallah
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Basma Latrech: National Research Institute for Rural Engineering, Water and Forestry, University of Carthage, BPN 10, Ariana 2080, Tunisia
Taoufik Hermassi: National Research Institute for Rural Engineering, Water and Forestry, University of Carthage, BPN 10, Ariana 2080, Tunisia
Samir Yacoubi: National Research Institute for Rural Engineering, Water and Forestry, University of Carthage, BPN 10, Ariana 2080, Tunisia
Adel Slatni: National Research Institute for Rural Engineering, Water and Forestry, University of Carthage, BPN 10, Ariana 2080, Tunisia
Fathia Jarray: National Research Institute for Rural Engineering, Water and Forestry, University of Carthage, BPN 10, Ariana 2080, Tunisia
Laurent Pouget: Water Technological Center, CETAQUA, Ctra. d’Esplugues, 75, Cornellà de Llobregat, 08940 Barcelona, Spain
Mohamed Ali Ben Abdallah: National Research Institute for Rural Engineering, Water and Forestry, University of Carthage, BPN 10, Ariana 2080, Tunisia

Agriculture, 2024, vol. 14, issue 1, 1-15

Abstract: Systematic biases in general circulation models (GCM) and regional climate models (RCM) impede their direct use in climate change impact research. Hence, the bias correction of GCM-RCMs outputs is a primary step in such studies. This study compares the potential of two bias correction methods (the method from the third phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3) and Detrended Quantile Matching (DQM)) applied to the raw outputs of daily data of minimum and maximum air temperatures and precipitation, in the Cap-Bon region, from eight GCM-RCM combinations. The outputs of GCM/RCM combinations were acquired from the European branch of the coordinated regional climate downscaling experiment (EURO-CORDEX) dataset for historical periods and under two representative concentration pathway (RCP4.5 and RCP8.5) scenarios. Furthermore, the best combination of bias correction/GCM-RCM was used to assess the impact of climate change on reference evapotranspiration (ET 0 ). Numerous statistical indicators were considered to evaluate the performance of the bias correction/historical GCM-RCMs compared to the observed data. Trends of the Hargreaves–Samani_ET 0 model during the historical and projected periods were determined using the TFPMK method. A comparison of the bias correction methods revealed that, for all the studied model combinations, ISIMIP3 performs better in reducing biases in monthly precipitation. However, for Tmax and Tmin, the biases are greatly removed when the DQM bias correction method is applied. In general, better results were obtained when the HadCCLM model was used. Before applying bias correction, the set of used GCM-RCMs projected reductions in precipitation for most of the months compared to the reference period (1982–2006). However, Tmin and Tmax are expected to increase in all months and for the three studied periods. Hargreaves–Samani ET 0 values obtained from the best combination (DQM/ HadCCLM) show that RCP8.5 (2075–2098) will exhibit the highest annual ET 0 increase compared to the RCP4.5 scenario and the other periods, with a change rate equal to 11.85% compared to the historical period. Regarding spring and summer seasons, the change rates of ET 0 are expected to reach 10.44 and 18.07%, respectively, under RCP8.5 (2075–2098). This study shows that the model can be used to determine long-term trends in ET 0 patterns for diverse purposes, such as water resources planning, agricultural crop management and irrigation scheduling in the Cap-Bon region.

Keywords: bias correction; GCM/RCMs combinations; reference evapotranspiration; Cap-Bon (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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