Journal of Applied Science and Engineering

Published by Tamkang University Press

1.30

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2.10

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Environmental Engineering

Kandula Srikanth , N V Umamahesh

Department of Civil Engineering, National Institute of Technology Warangal, India

 

Received: May 2, 2023
Accepted: August 3, 2023
Publication Date: October 14, 2023

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


Download Citation: ||https://doi.org/10.6180/jase.202406_27(6).0003  


Cotton cultivation in India is of vital importance to the national economy. However, the susceptibility of cotton crops to climate change poses significant challenges. Recognizing the spatial heterogeneity of climate change’s influence, comprehending its potential repercussions on cotton productivity is crucial. This research examines the effects of climate change on forthcoming cotton yields by utilizing the AquaCrop crop simulation model alongside eight climate models. A sensitivity analysis using the EFAST method is conducted to identify the key parameters influencing cotton yield, revealing eight influential parameters (Kcb, CGC, CCx, CDC, CCmin, wp, HIo, and Zmax) among the 30 parameters considered. These influential parameters are further employed to calibrate the model, automating, and optimizing the calibration process using a genetic algorithm to reduce the root mean square error (RMSE) between observed and simulated values. The AquaCrop model simulations demonstrate favourable agreement with observed data, exhibiting an RMSE of 0.15 t/ha during the calibration period (2001-2010) and 0.24 t/ha during the validation period (2011-2018). Utilizing the well-calibrated model, future projections are generated under different climate scenarios (SSP126 and SSP245) until the end of the century. The results indicate median yield increases of 4.4% and 1.9% in the SSP126 and SSP245 scenarios, respectively. Conversely, under the SSP370 and SSP585 scenarios, median yields are projected to decline by approximately 1.2% and 2% by the year 2100. It is an innovative study that combines AquaCrop, sensitivity analysis, and optimization to assess climate change impact on Indian cotton yields.


Keywords: Climate change scenarios, AquaCrop, Sensitivity Analysis, EFAST, Genetic Algorithm, Compromise programming.


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