Application of the CSM-CERES-Rice Model for Evaluation of Plant Density and Irrigation Management of Transplanted Rice for An Irrigated Semiarid Environment.

Application of the CSM-CERES-Rice model for evaluation of plant density and irrigation management of transplanted rice for an irrigated semiarid environment

Shakeel Ahmad^a*, Ashfaq Ahmad^b, Hakoomat Ali^a, Abid Hussain^b, Axel Garcia y Garcia^c, Gerrit Hoogenboom^d

^{a *}Department of Agronomy, Bahauddin Zakariya University, Multan-60800, Pakistan

^bAgro-climatology Lab, University of Agriculture, Faisalabad-38040, Pakistan

^cDepartment of Plant Sciences, University of Wyoming, Powell, WY 82435-9135, USA ^dBiological Systems Engineering, Washington State University, Prosser, WA 99350-8694, USA *Corresponding author Tel.: +92 61 9210071-4 Ext. 4011; fax: +92 61 9210098

E-mail address: shakeelahmad@bzu.edu.pk

Abstract

Food security in Asia is at risk due to the scarcity of irrigation water for conventionally flooded rice. Supplemental irrigation is generally necessary for successful crop production in many different environments. High productivity can be obtained through optimization of crop management practices such as plant density, and irrigation management. The interaction of plant density and irrigation levels can be analyzed through field experiments in concert with crop simulation models and decision support systems. The objectives of this study were to evaluate the performance of the Cropping System Model (CSM)-CERES-Rice for simulating growth and yield of rice under irrigated conditions for a semiarid environment in Pakistan and to determine the impact of plant density and irrigation regime on grain yield and economic return. The Cropping System Model (CSM)-CERES-Rice model was evaluated with experimental data collected in 2000 and 2001 in Faisalabad, Punjab, Pakistan. The experiment utilized a randomized complete block design with three replications and included three plant densities (one seedling hill^-1, PD₁; two seedlings hill^-1, PD₂; and three seedlings hill^-1, PD₃) and with five irrigation regimes (62.5 cm, I₁; 77.5 cm, I₂; 92.5 cm, I₃; 107.5 cm, I₄; and 122.5 cm, I₅). To determine the most appropriate combination of plant densities and irrigation regimes, four plant densities from one seedling hill^-1 to four seedlings hill^-1 and 17 irrigation regimes ranging from zero to 1600 mm, for a total of 68 different scenarios were simulated for 35 years of historical daily weather data for Faisalabad. The model was able to accurately simulate growth and yield of rice with an average error of 11% between simulated and observed grain yield. The results of the biophysical analysis showed that the combination of PD₂ and the 1300 mm irrigation regime produced the highest yield compared to all other scenarios. Furthermore, the economic analysis through the Mean Gini Dominance (MGD) also showed the superiority of this treatment compared to the other treatments. The mean monetary return ranged from -47 $ ha^-1 to 1265 $ ha^-1 among all 68 scenarios. To fulfill the demand of rice grain for local consumption and to increase export, there is a need expand this technology among the rice growers of other rice producing areas in Pakistan through extension workers.

Keywords: Crop modeling; Crop management; Grain yield; Biomass; Decision Support System for Agro-technology Transfer; Food security