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"balance" Keyword-tagged Publications:
| Title: | Agriculture s impact on water-energy balance varies across climates | ||||
| Authors: | Zaerpour M, Hatami S, Ballarin AS, Papalexiou SM, Pietroniro A, Nazemi A | ||||
| Link: | https://pubmed.ncbi.nlm.nih.gov/40096605/ | ||||
| DOI: | 10.1073/pnas.2410521122 | ||||
| Publication: | Proceedings of the National Academy of Sciences of the United States of America | ||||
| Keywords: | Budyko water balance; agriculture; irrigation; water balance; | ||||
| PMID: | 40096605 | Category: | Date Added: | 2025-03-17 | |
| Dept Affiliation: |
ENCS
1 Department of Civil Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada. 2 Department of Hydraulics and Sanitation, São Carlos School of Engineering, University of São Paulo, São Paulo 13566-590, Brazil. 3 Department of Water Resources and Environmental Modeling, Faculty of Environmental Sciences, Czech University of Life Sciences, Prague 165 00, Czech Republic. 4 Department of Building, Civil, and Environmental Engineering, Concordia University, Montreal, QC H3G 2W1, Canada. |
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Description: |
Agriculture is a cornerstone of global food production, accounting for a substantial portion of water withdrawals worldwide. As the world's population grows, so does the demand for water in agriculture, leading to alterations in regional water-energy balances. We present an approach to identify the influence of agriculture on the water-energy balance using empirical data. We explore the departure from the Budyko curve for catchments with agricultural expansion and their associations with changes in the water-energy balance using a causal discovery algorithm. Analyzing data from 1,342 catchments across three Köppen-Geiger climate classes-temperate, snowy, and others-from 1980 to 2014, we show that temperate and snowy catchments, which account for over 90% of stations, exhibit distinct patterns. Cropland percentage (CL%) emerges as the dominant factor, explaining 47 and 37% of the variance in deviations from the Budyko curve in temperate and snowy catchments, respectively. In temperate catchments, CL% shows a strong negative correlation with precipitation-streamflow (P-Q) causal strength (Spearman [Formula: see text]), suggesting that cropland exacerbates precipitation-driven deviations. A moderate negative correlation with aridity-streamflow (AR-Q) causal strength ([Formula: see text]) indicates additional influences of cropland through aridity-driven interactions. In snowy catchments, CL% is similarly influential, with a positive correlation with P-Q causal strength ([Formula: see text]). However, the negative correlation with AR-Q causal strength ([Formula: see text]) underscores the role of aridity as a secondary driver. While vegetation and precipitation seasonality also contribute to the deviations, their impacts are comparatively lower. These findings underscore the need for inclusion of agricultural activities in changing water-energy balance to secure future water supplies. |



