Simulating Water and Nitrogen Requirements for Maize Under Semi-Arid Conditions Using the CSM-CERES-Maize Model.

Simulating water and nitrogen requirements for maize under semi-arid conditions using the CSM-CERES-Maize model

Hafiz Mohkum Hammad^1,2a, Ashfaq Ahmad³, Farhat Abbas⁴, Shafqat Saeed¹, Wajid Farhad⁴, Jakarat Anothai² and Gerrit Hoogenboom²

¹College of Agriculture Layyah, Sub Campus Bahauddin Zakariya University, Pakistan

²Agro-Climatology Lab., University of Agriculture Faisalabad-38040, Pakistan

²AgWeatherNet, Washington State University, Prosser, Washington 99350, USA

³Department of Environmental Sciences, Government College University Faisalabad-38000, Pakistan

⁴Sindh Agriculture University, Department of Agronomy, Tandojam-Pakistan

^aCorresponding author’s E-mail: hafizmohkum@gmail.com Tel.: + 92333617 7013

Abstract

Crop modeling facilitates the calculation of plant water and nutrient requirements for a range of conditions and management scenarios. The goal of this study was the evaluation of the Cropping System Model (CSM) CERES-Maize for simulating growth, development and yield of maize (Zea mays L.) under semi-arid environments of Pakistan. Two experiments were conducted in 2009 and 2010 with three irrigation levels (full irrigation, water deficit at vegetative and at reproductive stages) and five N application rates (100, 150, 200, 250 and 300 kg ha^-1) using a split plot arrangement. The results showed that for maize crop I₁ and N₄ are optimum level of irrigation and N, respectively. The model was calibrated with an optimum treatment and model successfully predicted soil moisture content (with d statistic 0.96) throughout growing season. The mean percentage differences (MPD) in days to anthesis, days to maturity and met yield was 0. However, the MPD for number of grain per cob, leaf area index (LAI) and total dry matter (TDM) was 11.36%, 5.98% and 4.85%, respectively. The model prediction for LAI and TDM was good with d statistic 0.60 to 99 and 0.97 to 0.99, respectively. The model predicted crop phenology and grain yield with satisfactory root mean square error.  The model can be used to evaluate and simulate maize production under semi-arid environment.