Investigating the Impact of Compound Extremes on Crop Yield Response of Cotton Using DSSAT-CROPGRO-Cotton Crop Simulation Model

Agricultural productivity is highly vulnerable to weather and climate extremes, including droughts and heatwaves, which can significantly impact crop yields. Despite previous studies addressing the effects of individual and compound extremes on crop productivity, a comprehensive understanding of the critical duration thresholds beyond which a crop yield declines substantially remains limited. This study aims to investigate the duration thresholds of compound and individual extremes for cotton under various scenarios. We utilize the decision support system for agrotechnology transfer-cropping system growth model (DSSAT-CROPGRO)-Cotton crop simulation model, combined with bias-corrected projections from eight climate models, to simulate future cotton yields for rainfed and fully irrigated conditions with varying CO2 concentrations. Our findings indicate an overall decline in cotton yields across all scenarios toward the end of the century, with the highest emissions scenario (SSP585) showing the most significant reduction. The occurrence of coincidental heatwaves and droughts in SSP585 leads to yield declines of approximately 33%, 23%, and 15% in S1, S2, and S3 scenarios, respectively. While rainfed scenarios with increased CO2 show some mitigation of extreme events’ impact, fully irrigated scenarios exhibit only marginal improvements. These results underscore the urgency of developing sustainable practices to mitigate the adverse effects of extreme events on cotton yields amid a changing climate.

Authors

Institutions

Publication Details

Journal
Journal of Irrigation and Drainage Engineering
Published
2024-11-26
DOI
https://doi.org/10.1061/jidedh.ireng-10242
Citations
3
Primary Topic
Rice Cultivation and Yield Improvement
Type
article
Field-Weighted Citation Impact
1.80
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Investigating the Impact of Compound Extremes on Crop Yield Response of Cotton Using DSSAT-CROPGRO-Cotton Crop Simulation Model

N. V. Umamahesh, Velpuri Manikanta, K. Srikanth
3 citations
Journal of Irrigation and Drainage Engineering
Rice Cultivation and Yield Improvement
1.80
article

Investigating the Impact of Compound Extremes on Crop Yield Response of Cotton Using DSSAT-CROPGRO-Cotton Crop Simulation Model

N. V. Umamahesh, Velpuri Manikanta, K. Srikanth
article en
3 citations

Abstract

Agricultural productivity is highly vulnerable to weather and climate extremes, including droughts and heatwaves, which can significantly impact crop yields. Despite previous studies addressing the effects of individual and compound extremes on crop productivity, a comprehensive understanding of the critical duration thresholds beyond which a crop yield declines substantially remains limited. This study aims to investigate the duration thresholds of compound and individual extremes for cotton under various scenarios. We utilize the decision support system for agrotechnology transfer-cropping system growth model (DSSAT-CROPGRO)-Cotton crop simulation model, combined with bias-corrected projections from eight climate models, to simulate future cotton yields for rainfed and fully irrigated conditions with varying CO2 concentrations. Our findings indicate an overall decline in cotton yields across all scenarios toward the end of the century, with the highest emissions scenario (SSP585) showing the most significant reduction. The occurrence of coincidental heatwaves and droughts in SSP585 leads to yield declines of approximately 33%, 23%, and 15% in S1, S2, and S3 scenarios, respectively. While rainfed scenarios with increased CO2 show some mitigation of extreme events’ impact, fully irrigated scenarios exhibit only marginal improvements. These results underscore the urgency of developing sustainable practices to mitigate the adverse effects of extreme events on cotton yields amid a changing climate.

Journal of Irrigation and Drainage EngineeringVol. 151(1)
National Institute of Technology Warangal (IN)
Zero hunger
Openalex Percentile: Top 13%
Rice Cultivation and Yield Improvement
1.80
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.