Can models help to forecast rainwater dynamics for rainfed ecosystem?

Abstract

Simulation models are important tools to explore and illustrate dynamics of climatic variables in crop based ecosystem. In the rainfed ecosystem (RE), wheat production is impinged on certain climatic events per se high variability in rainfall and increased temperature. These climatic events turn out due to climatic drivers like Sea Surface Temperatures (SSTs) and pressure. Current study is aimed to analyze long term rainfall data (1961–2011) of Pakistan׳s rainfed ecosystem zone (Islamabad, Chakwal and Talagang) by using Agricultural Production Systems Simulator (APSIM) and R model. The principal objective of this analysis was to study the link between SOI phases and SSTs; and thereby understanding the pattern of climate change due to these climatic drivers under rainfed conditions in Pakistan. The results revealed a positive link between July SOI phases and the rainfall variability during October–November (the sowing time of wheat in Pakistan). Long term rainfall data analysis (1961–2011) of Islamabad, Chakwal and Talagang revealed 44%, 40%, 35% possibility of exceeding median rainfall near zero whereas probability of consistently negative SOI phases were 35%, 34% and 33% respectively during July. Similarly, the forecasting results estimated by R using covariates like dry spell, NINO1.2, NINO3, NINO4, NINO3.4 and IOD of different months revealed that prediction of monsoon, wheat early growth, wheat grain filling period and total wheat growing season rainfall, have significant signals with climatic drivers. The study justified the importance of models in the decision making processes and rainfall forecasting as a beneficial and necessary tool for rainfed ecosystem conservation.

Keywords

• Simulation
• Rainfed ecosystem
• APSIM
• Climatic drivers