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.

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.