Agronomic management and climate change scenario simulations on productivity of rice, maize and wheat in central Nepal using DSSAT ver 4.5 crop model

Abstract

Average productivity of 3.50 t/ha of rice, 2.50 t/ha of maize and 2.45 t/ha of wheat in Nepal have been very less than their potential productivity for which précised agronomic management and changing climatic scenarios have been reported the most challenging factors at present. Cropping system Model (CSM)-Crop Estimation through Resource and Environment Synthesis (CERES)- Rice, Maize and Wheat, embedded under Decision Support System for Agro-technology Transfer (DSSAT) ver. 4.5 was evaluated from a datasets of farmers’ field experimentations of the central Nepal (Terai-Nawalpur and mid-hill-Kaski districts), and showed high sensitivity of model over change in different agronomic management and climate change scenarios. Model calibration was done by using maximum attainable yield treatments for all tested cultivars while validation was accomplished by using the remaining treatments for predicting growth, phenology and yield of all crop cultivars and results were found perfectly matched with the observed results. Further, the different agronomic management options and climate change scenarios as advocated by IPCC for 2020, 2050 and 2080 from base line of 1995 was studied to simulate the growth and yield performance of diverse crop cultivars. The hybrids and short duration cultivars of all three cereals were found more affected due to climate change than the local and long duration crop cultivars. The model simulation results obtained on rice, maize and wheat using DSSAT ver 4.5 model highlighted that there is utmost importance to develop new climate ready crop cultivars to feed the future generation over different climate change scenarios as suggested by IPCC, 2007 and the simulation results should be extrapolated to the major domains of similar agro-ecozones in Nepal. It is suggested that CSM- CERES- model would be reliable and valid approach for getting strategic decision support system especially with regards to the climate change adaptation measures in Nepal.

Multi-year Prediction of Wheat Yield under the Changing Climatic Scenarios in Central-west Terai using DSSAT Crop Model

“…For the evaluation of CSM-CERES-Wheat, DSSAT ver 4.7 crop model was used in Kapilvastu condition. A properly calibrated and fairly validated model with the genetic co-efficient of wheat cultivar Gautam (Marasini 2016;Amgain et al 2019) was used for the further study the sensitivity of the model.…”

“…We used already calibrated and validated CSM-CERES-Wheat model, DSSAT ver. 4.7 to study the model simulation (Amgain et al, 2019). The determined genetic coefficients for wheat cultivar WK-1204 was 3 (P1V), 39 (P1D), 315 (P5), 40 (G1), 71 (G2), 0.9 (G3) and 64 (PHINT).…”

“…Amgain et al (2006) reported that increase in minimum and maximum temperature by 4˚C over the base scenario decreased the wheat yield by 4%. Reduction of minimum and maximum temperature by 4˚C and increase in CO 2 by 20 ppm showed increase in yield (Amgain et al 2006(Amgain et al , 2019. Increased CO 2 concentration and increased temperature increased growth duration and yield, while increased temperature shortened growth duration and reduced leaf area, biomass and yield (Qureshi et al 2016;Qureshi, Quersi and Iglesias 1994;Timsina et al 1997).…”

“…Increased temperature may decrease wheat potential yield more than the rice and posing a challenging threat in food security. It is also reported that the changing rainfall pattern and its distribution affect negatively on wheat yield because wheat cultivation is mostly rainfed, but more vulnerable to drought stress than other crops in Nepal (Amgain et al 2019, Amgain and Timsina 2004, 2005Timsina and Humphreys 2006). It is also reported that research on farmers' field would be more vulnerable to climate change and, hence urge for innovative climate change research (Amgain et al 2018;Amgain 2015).…”

“…A range of technologies have been identified in recent years, which have the potential to increase resource use efficiency, reduce adverse environmental impacts, and increase crop productivity (Acharya et al 2021;Timsina et al 2021;Amgain 2015). The use of correlation coefficient and regression equations, trend analysis and various crop models are used to know the impact of agro-climatic indices on the yield of rice, maize, wheat and chickpea in Nepal (Amgain and Dhakal 2019;Amgain et al 2019). It is assumed that evaluation and site-specific adaptation of these technologies can be assisted through crop simulation models.…”