Panjala, P and Gumma, M K and Mesapam, S (2024) Geospatial assessment of cropping pattern shifts and their impact on water demand in the Kaleshwaram lift irrigation project command area, Telangana. Frontiers in Remote Sensing, 5. 01-14. ISSN 2673-6187
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Abstract
Efficient monitoring of crop water requirements is crucial for assessing the impacts of major irrigation projects, such as the Kaleshwaram lift irrigation project, both before and after their implementation. These projects can significantly change agricultural practices and water usage patterns, necessitating thorough evaluations to ensure sustainable water management and agricultural resilience. The main aim of this study is to evaluate and compare crop water needs during the winter (rabi) seasons of 2018–2019 and 2022–2023 across the command area of the project. This is achieved by mapping major crops and their respective length of growing periods across the study area using sentinel-2 satellite data and ground data, and quantifying crop water requirements using reference evapotranspiration and FAO crop coefficients. Results reveal a significant shift towards rice cultivation, with an over 80% increase in the winter season of 2022–2023 compared to 2018–2019, indicating substantial escalations in crop water requirements. These findings provide valuable insights into agricultural transformations induced by large-scale irrigation interventions, emphasizing the need for sustainable water management practices to ensure agricultural resilience and resource conservation in similar contexts.
| Item Type: | Article |
|---|---|
| Divisions: | Global Research Program - Resilient Farm and Food Systems |
| CRP: | UNSPECIFIED |
| Uncontrolled Keywords: | lift irrigation, crop water, crop types, remote sensing, change detection |
| Subjects: | Others > GIS Techniques/Remote Sensing Others > Telangana Others > Cropping and Farming Systems Others > Water Resources |
| Depositing User: | Mr Nagaraju T |
| Date Deposited: | 25 Aug 2025 04:56 |
| Last Modified: | 25 Aug 2025 04:56 |
| URI: | http://oar.icrisat.org/id/eprint/13301 |
| Official URL: | https://www.frontiersin.org/journals/remote-sensin... |
| Projects: | UNSPECIFIED |
| Funders: | UNSPECIFIED |
| Acknowledgement: | This work was conducted in collaboration with the Geospatial and Big Data Sciences cluster of ICRISAT, Hyderabad and RS and GIS of NIT Warangal. We would like express our gratitude for providing the facilities to do the research. |
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