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Impacts of climate change on rice yields in the Nile River Delta of Egypt: A large-scale projection analysis based on CMIP6

均方误差 环境科学 降水 决定系数 气候变化 相关系数 气候学 粮食安全 数学 统计 气象学 地理 农业 地质学 考古 生物 生态学
作者
Elsayed Ahmed Elsadek,Ke Zhang,Yousef Alhaj Hamoud,Ahmed Mousa,Ahmed Awad,Mohammed Abdallah,Hiba Shaghaleh,Amar Ali Adam Hamad,Muhammad Tahir Jamil,Ahmed Elbeltagi
出处
期刊:Agricultural Water Management [Elsevier BV]
卷期号:292: 108673-108673 被引量:10
标识
DOI:10.1016/j.agwat.2024.108673
摘要

Climate change directly affects crop yields, which would cause more future food security crises. Ensemble global climate models (GCMs) combined with crop growth models are an effective method to project such impacts. In the current study, five criteria were used to pick out ten GCMs. Three types of efficiency criteria, namely root-mean-squared error (RMSE), Pearson's correlation coefficient (R), Nash-Sutcliffe efficiency coefficient (NSE), and bias (BISA) between predicted and observed temperature and precipitation, were used to evaluate and select the better-performing of the GCMs for the baseline period (1981–2010). Then, AquaCrop-GIS, driven by the downscaled projected climate data from the selected GCMs, was used to predict rice yields in the Nile River Delta (NRD) region under two Shared Socioeconomic Pathways (SSP) scenarios (SSP2–4.5 and SSP5–8.5) and four prediction periods (2021–2099). Four statistical indicators, namely, prediction error (Pe), normalized RMSE (RMSEn), index of agreement (Dindex), and coefficient of determination (R2), were used to evaluate the performance of AquaCrop-GIS. Our results showed that five GCMs, including the BCC-CSM2-MR, CMCC-ESM2, INM-CM5–0, MRI-ESM2–0, and UKESM1–0-LL, had better performances in simulating temperature and precipitation (0.81 ≤ RMSE ≤ 4.77, 0.30 ≤ NSE ≤ 0.97, and 0.57 ≤ R ≤ 0.99). In addition, AquaCrop-GIS showed excellent accuracy in simulating rice yields and predicted that, without CO2 effects, rice yields would increase by 2.19% and 4.23% under SSP2–4.5 and by 0.72% and 0.30% under SSP5–8.5 during the 2030s and 2050s, respectively. However, in the 2070s and 2090s, rice yields would decline by 7.20% and 9.0% under SSP2–4.5 and by 23.34% and 34.24% under SSP5–8.5 during the 2070s and 2090s, respectively. With CO2 effects, rice yields would rise by 14.49%, 24.97%, 15.96%, and 16.93% under SSP2–4.5 and by 14.33%, 26.22%, 8.06%, and 1.61% under SSP5–8.5 during the 2030s, 2050s, 2070s, and 2090s, respectively. Regardless of uncertainties and limitations, our findings are beneficial for farmers and policymakers to develop appropriate management strategies to improve rice yields in Egypt.
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