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Abstract Drought poses a major threat to agricultural production and food security. This study evaluates the changes in drought-induced crop yield loss risk for six crops (alfalfa, barley, corn, soybean, spring wheat, and winter wheat) between 1971–2000 and 1991–2020 across the contiguous US. Using a copula-based probabilistic framework, our results reveal a spatially heterogeneous change in yield risk to meteorological droughts, which varies with crop types. Regional analyses identify the largest temporal decline in yield risk in the Southeast and Upper Midwest, while the Northwest and South show an increase in risk. Among the considered anthropogenic and climatic drivers of crop productivity, changes in climatic variables such as high temperatures (e.g., killing degree days), vapor pressure deficit and precipitation show significantly stronger associations with changes in yield risk than irrigated area and nitrogen fertilizer application. Among the counties that observe drier drought events, only 55% exhibit an increase in crop yield loss risk due to drier droughts. The rest 45% show a decrease in yield loss risk due to mediation of favorable climatic and anthropogenic factors. Alarmingly, more than half (for barley and spring wheat), and one-third (for alfalfa, corn, soybean and winter wheat) of that the risk increasing regions have outsized influence on destabilizing national crop production. The findings provide valuable insights for policymakers, agricultural stakeholders, and decision-makers in terms of the potential ways and locations to be prioritized for enhancing local and national agricultural resilience and ensuring food security. 

Abstract Accurate assessment of changes in water availability with changing climate is vital for effective mitigation and adaptation. In this research, we employ a parsimonious Budyko curve method to evaluate changes in water availability under low‐ (SSP126) and high‐emission (SSP585) scenarios for 331 river basins in the contiguous United States. We also assess the relative role of changes in precipitation (∆P) and potential evapotranspiration (∆PET) with changing climate on the increase in water availability vulnerability. Results highlight that around 43% (28%) of basins are projected to experience increased vulnerability to changing climate in high‐emission (low‐emission) scenarios. Sub‐humid basins are most often impacted, while arid and semi‐arid basins exhibit lower sensitivity to changes. Intriguingly, ∆PET emerges as the dominant control on vulnerability, surpassing ∆P, particularly under SSP585 scenario. The analysis prompts water managers to focus on long‐term mitigation planning and scientists to further constraint climate and water budget forecasts in affected basins. 

Abstract Evapotranspiration (ET) plays a critical role in water and energy budgets at regional to global scales. ET is composed of direct evaporation (E) and plant transpiration (T) where the latter is regulated via stomatal conductance (g_sc), which depends on a multitude of plant physiological processes and hydrometeorological forcings. In recent years, significant advances have been made toward estimatingg_scusing a variety of models, ranging from relatively simple empirical models to more complex and data‐intensive plant hydraulic models. Using machine learning (ML) and eddy covariance flux tower data of 642 site years across 84 sites distributed across 10 land covers globally, here we show that structural constraints inherent in current empirical and plant hydraulic models ofg_sclimit their effectiveness for predicting ET. These constraints also prevent the models from fully utilizing the available hydrometeorological data at eddy covariance sites. Even if theseg_scmodels are calibrated locally, structural simplifications inherent in them limit their capability to accurately captureg_scdynamics. In contrast, a ML approach, wherein the model structure is learned from the data, outperforms traditional models, thus highlighting that there still is significant room for improvement in the structure of traditional models for predicting ET. These results underscore the need to prioritize improvements ing_scmodels for more accurate ET estimation. This, in turn, will help reduce uncertainties in the assessments of plants' role in regulating the Earth's climate. 

Abstract Irrigation expansion is often posed as a promising option to enhance food security. Here, we assess the influence of expansion of irrigation, primarily in rural areas of the contiguous United States (CONUS), on the intensification and spatial proliferation of freshwater scarcity. Results show rain-fed to irrigation-fed (RFtoIF) transition will result in an additional 169.6 million hectares or 22% of the total CONUS land area facing moderate or severe water scarcity. Analysis of just the 53 large urban clusters with 146 million residents shows that the transition will result in 97 million urban population facing water scarcity for at least one month per year on average versus 82 million before the irrigation expansion. Notably, none of the six large urban regions facing an increase in scarcity with RFtoIF transition are located in arid regions in part because the magnitude of impact is dependent on multiple factors including local water demand, abstractions in the river upstream, and the buffering capacity of ancillary water sources to cities. For these reasons, areas with higher population and industrialization also generally experience a relatively smaller change in scarcity than regions with lower water demand. While the exact magnitude of impacts are subject to simulation uncertainties despite efforts to exercise due diligence, the study unambiguously underscores the need for strategies aimed at boosting crop productivity to incorporate the effects on water availability throughout the entire extent of the flow networks, instead of solely focusing on the local level. The results further highlight that if irrigation expansion is poorly managed, it may increase urban water scarcity, thus also possibly increasing the likelihood of water conflict between urban and rural areas. 

Abstract In recent decades, irrigated agriculture has expanded dramatically over the Southeastern United States (SEUS). The trend is more likely to continue in future given the need to further improve crop productivity and its resilience against droughts, however, the impact of these SEUS land cover changes remains unknown. This study investigates how and to what extent rain-fed to irrigation-fed (RFtoIF) transition in the SEUS region modulates precipitation spatially and temporally under a severe drought meteorological condition. In this study, we perform three Weather Research Forecasting model simulations with varying degrees of irrigated crop areas with meteorological boundary conditions of a record-breaking 2007 drought in the SEUS region. Results show that the SEUS irrigation expansion reduces both the convective triggering potential and low-level humidity index through land-atmospheric interaction. This is accompanied by reduction in the height of atmospheric boundary layer (ABL)-lifting condensation level crossing and increase in the convective available potential energy. These modulations within the ABL provide a favorable condition for strong deep convection during the drought period. However, the impact on precipitation is heterogeneous, with crop areas undergoing RFtoIF transition experiencing an overall reduction in precipitation while other landcovers experiencing an increase. The reduction in precipitation over RFtoIF transitioned croplands is in part due to moisture redistribution aided by generation of an anomalous high-pressure system. The results highlight the complexity of response of precipitation to irrigation expansion in the SEUS, and underscore the need to perform spatially-explicit analysis for mitigating risks to water resources and food security. 

Abstract Wetlands protect downstream waters by filtering excess nitrogen (N) generated from agricultural and urban activities. Many small ephemeral wetlands, also known as geographically isolated wetlands (GIWs), are hotspots of N retention but have received fewer legal protections due to their apparent isolation from jurisdictional waters. Here, we hypothesize that the isolation of the GIWs make them more efficient N filters, especially when considering transient hydrologic dynamics. We use a reduced complexity model with 30 years of remotely sensed monthly wetland inundation levels in 3700 GIWs across eight wetlandscapes in the US to show how consideration of transient hydrologic dynamics can increase N retention estimates by up to 130%, with greater retention magnification for the smaller wetlands. This effect is more pronounced in semi-arid systems such as the prairies in North Dakota, where transient assumptions lead to 1.8 times more retention, compared to humid landscapes like the North Carolina Pocosins where transient assumptions only lead to 1.4 times more retention. Our results highlight how GIWs have an outsized role in retaining nutrients, and this service is enhanced due to their hydrologic disconnectivity which must be protected to maintain the integrity of downstream waters. 

Abstract Groundwater recharge moves downward from the land surface and reaches the groundwater to replenish aquifers. Despite its importance, methods to directly measure recharge remain cost and time‐intensive. Recharge is usually estimated using indirect methods, such as the widely used water‐table fluctuation (WTF) method, which is based on the premise that rises in groundwater levels are due to recharge. In the WTF method, recharge is calculated as the difference between the observed groundwater hydrograph and the hydrograph obtained in the absence of water input. The hydrograph in the absence of rise‐producing input is estimated based on a characteristic master recession curve (MRC), which describes an average behavior for a declining water‐table. Previous studies derive MRC using recession data from all seasons. We hypothesize that for sites where groundwater table is shallow, using recession data from periods with high groundwater‐influenced evapotranspiration (ET) rates versus all periods will yield significantly different MRC, and consequently different estimates of recharge. We test this hypothesis and show that groundwater recession rates are significantly greater in warm months when the groundwater‐influenced ET rates are higher. Since obtaining seasonal recession rates is challenging for locations with a limited amount of data and is prohibitive if it is to be obtained for any given season of a particular year, we propose two novel parsimonious methods to obtain recession time constants for distinct seasons. The proposed methods show the potential to significantly improve the estimates of seasonal recession time constants and provide a better understanding of seasonal variations in recharge estimates. 

The US corn area footprint has changed significantly since the 20th century, declining in the southeastern states while exhibiting an increase or stable variations in the Midwest. As harvested acreage directly impacts the total corn production, understanding the influencing factors is crucial. This study assesses the role of potential drivers on the contrasting trajectories of harvested corn acreage between midwestern and southeastern US. Profit acreage analysis reveals that antecedent profits/losses have a statistically significant influence on corn acreage changes, with southeastern US, which experienced more loss-making years, also experiencing more frequent reductions in corn acreage. The high number of loss-making years in the Southeast is primarily attributed to the region’s low corn yield, influenced by climate and other agro-environmental factors. Using a panel regression model, we find that the loss-making years in the Southeast could have reduced to fewer than 26 out of the considered 45 years, or almost similar to the average in the Midwest, by just increasing the irrigated corn area to 50 %, a realistic irrigated corn area fraction already achieved in several Georgia counties. This underscores the potential for early policy interventions like irrigation facilitation to sustain and expand cropped acreage. However, we also find that this would only be economically feasible with incentives for both the installation and sustained operation of irrigation infrastructure. 

Evaporative Stress Index (ESI), also sometimes referred as Evaporative Stress Ratio (ESR), has been widely used as an indicator of vegetation evaporative stress, and is often used to track forest and agriculture droughts. Lower the stress, higher is the value of ESI or ESR. The goal of this study is to assess the suitability of these indices for tracking vegetation evaporative stress. As the dynamics of water loss from vegetation through transpiration (T) can be different than that of evapotranspiration (ET) from the ecosystem, it is hypothesized that ESI or ESR may not be sufficiently representative of the vegetation evaporative stress. Using eddy covariance flux tower data of 518 site years, distributed across 49-sites and 9 land covers globally, our findings reveal underestimation of vegetation evaporative stress by ESI during periods of high vapor pressure deficit (VPD) and overestimation during dry, low-VPD periods. The results highlight the need to improve representativeness of ESI for monitoring vegetation evaporative stress. Notably, this may entail accurate estimation of ecosystem T in systems lacking in-situ data, a challenge that warrants further attention.