Rainfed wheat (Triticum aestivum L.) yield prediction using economical, meteorological, and drought indicators through pooled panel data and statistical downscaling

• Published in: Ecological indicators 2020-04, Vol.111, p.105991, Article 105991
• Main Authors: Salehnia, Nasrin, Salehnia, Narges, Saradari Torshizi, Ahmad, Kolsoumi, Sohrab
• Format: Article
• Language: English
• Subjects: Chow test; Diurnal temperature; Durbin Watson test; Precipitation; SPEI; SPI
• ISSN: 1470-160X; 1872-7034
• DOI: 10.1016/j.ecolind.2019.105991

•From 21 variables only six variables showed significant correlation with wheat yield.•The pooled panel data model was implemented for prediction wheat yield.•Our results revealed that MIROC5 under RCP45 was selected as the best model.•Increased 1% in Nhour and SPIoct respectively reduce 1.19% and 0.44% in wheat yield.•The mean total wheat yields possibly would increase during future period. Agriculture productions play significant roles in economic development. Extreme weather events, especially drought under climate change conditions, can affect future crop production. Nowadays, researchers are trying to apply modeling approaches for estimating future changes on amounts of crop yields. This study employed pooled panel data to simulate the most effective meteorological drought indices, economic and meteorological variables on rainfed wheat yield. The observation period was 1990–2016 for several meteorological data, besides SPI (Standardized Precipitation Index) and SPEI (Standardized Precipitation Evapotranspiration Index) drought indices in monthly and yearly scales. The available economic variables during the study period were yearly guaranteed wheat prices (Rial/kg) and area under cultivation (ha). In this research, first, the most effective variables were selected according to the efficiency criteria and stepwise regression. Then by using pooled panel data, a relation was estimated between yield and the independent variables. Finally, with future downscaled variables, the amount of wheat yield was determined for the next 20 years (2019–2038). The GFDL- ESM2M and MIROC5 models under RCP45 and RCP85 were run, and MIROC5 under RCP45 was selected as the best model, for the evaluation period. The results revealed that guaranteed wheat prices, yearly precipitation and sunshine hours, the area under cultivation, and SPI of October were identified as the most effective variables on wheat yield through the Panel model. By using the projection weather variables and the pooled panel model, we achieved that the amount of rainfed wheat yield would be increased over two next decades at Mashhad, Sabzevar, and Torbat H. locations.