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The goal of this study is to investigate the usefulness of the relatively new 30 m spatial and cVI) for estimating field scale crop evapotranspiration (ETc). Increased spatial and temporal resolution ETc estimates are needed for improving irrigation scheduling, monitoring impacts of water conservation programs, and improving crop yield. The crop coefficient (Kc) method is widely used for estimating ETc. Remote sensing vegetation indices (VI) are highly correlated to Kc and allow the creation of a KcVI but the approach is limited by the availability of high temporal and spatial resolutions. We selected and calculated sixteen commonly used VIs using HLS data and regressed them against field-measured ET for alfalfa in the Mesilla Valley, New Mexico to create linear KcVI models. All models showed good agreement with Kc (r2 > 0.67 and RMSE < 0.15). ETc prediction resulted in an MAE ranging between 0.35- and 0.64-mm day−1, an MSE ranging between 0.20- and 0.75-mm day−1 and an MAPD ranging between 10.0 and 16.5%. The largest differences in predicted ETc occurred early in the growing season and during cutting periods when the spectral signal could be influenced by soil background or irrigation events. The results suggest that applying the KcVI approach to the HLS dataset can help fill in the data gap in remote sensing ET tools. Future work should focus on assessing additional crops and integration into other tools such as the emerging OpenET platform.

Prolonged drought exacerbated by climate change in the Mesilla Valley, one of the major agricultural areas of New Mexico, USA, is causing a shortage of surface water from the Rio Grande for irrigation. Farmers in the Valley are using groundwater for irrigation and complementing it with limited surface water from the river (Rio Grande). Managing irrigation water better is vital to sustaining agriculture in the Valley. Remote sensing (RS)-based crop evapotranspiration (ETa) models offer significant advantages over traditional methods. The ET maps generated by these RS models provide valuable information that can be used to manage irrigation water and crops in water-scarce areas. This study used METRIC and SSEBop RS models to map the ET of alfalfa on a private farm that is managed as commonly practiced in the Valley. The integrated ET values of the two models are compared to those of the ETa measured using the eddy covariance method. The comparison showed that 91.55% of the variability in SSEBop ETa estimates can be explained by the variability in the METRIC ETa estimates, and the variability in eddy covariance ETa can explain 93.07% of the variability in METRIC ETa and 86.01% in the SSEBop Eta estimates. Both METRIC and SSEBop reflected the ETa of alfalfa during full growth and harvesting periods. However, the absolute percent mean relative difference (MRD) of ET was higher for two out of three cuttings by SSEBop (>32%) compared to those for METRIC and eddy covariance. The spatiotemporal variabilities in crop ET estimates using METRIC and SSEBop showed a need to improve on-farm irrigation conveyance and on-the-field irrigation efficiency. Overall, RS models can provide spatiotemporal maps of ET that can be used for decision-making to manage irrigation water better and improve crop yield on a field, farm, and regional scale.

Pecan is a major crop in the Mesilla Valley, New Mexico. Due to prolonged droughts, growers face challenges related to water shortages. Therefore, irrigation management is crucial for farmers. Advancements in satellite-derived evapotranspiration (ET) models and accessibility to data from web-based platforms like OpenET provide farmers with new tools to improve crop irrigation management. This study evaluates the evapotranspiration (ET) of a mature pecan orchard using OpenET platform data generated by six satellite-based models and their ensemble. The ET values obtained from the platform were compared with the ET values obtained from the eddy covariance (ETec) method from 2017 to 2021. The six models assessed included Google Earth Engine implementation of the Surface Energy Balance Algorithm for Land (geeSEBAL), Google Earth Engine implemonthsmentation of the Mapping Evapotranspiration at High Resolution with Internalized Calibration (eeMETRIC) model, Operational Simplified Surface Energy Balance (SSEBop), Satellite Irrigation Management Support (SIMS), Priestley–Taylor Jet Propulsion Laboratory (PT-JPL), and Atmosphere–Land Exchange Inverse and associated flux disaggregation technique (ALEXI/DisALEXI). The average growing season ET of mature pecan estimated from April to October of 2017 to 2021 by geeSEBAL, eeMETRIC, SSEBop, SIMS, PT-JPL, ALEXI/DisALEXI, and the ensemble were 1061, 1230, 1232, 1176, 1040, 1016, and 1130 mm, respectively, and 1108 mm by ETec. Overall, the ensemble model-based monthly ET of mature pecan during the growing season was relatively close to the ETec (R2 of 0.9477) with a 2% mean relative difference (MRD) and standard error of estimate (SEE) of 15 mm/month for the five years (N = 60 months). The high agreement of the OpenET ensemble of the six satellite-derived models’ estimates of mature pecan ET with the ETec demonstrates the utility of this promising approach to enhance the reliability of remote sensing-based ET data for agricultural and water resource management.

Enhancing the comprehension of alterations in land use holds paramount importance for water management in semi-arid regions due to its effects on hydrology and agricultural economics. Allowing agricultural land to lie fallow has emerged as a technique to decrease water use. This research employs the methodology of system dynamics modeling to evaluate the hydrologic and agricultural economic ramifications of employing the fallowing strategy, which aims to preserve water resources in interconnected socio-hydrologic systems. This strategy is explored across three different crops, focusing on the Mesilla–Rincon Valley (MRV) in southern New Mexico. The study’s timeline spans from 2022 to 2050 with historical background from 1969 and encompasses various dimensions, including water availability, land utilization, and agricultural economics. Three types of crops were selected for the fallowing strategy, including cotton, alfalfa/hay, and chile. For each crop, 2500 acres of it would be designated for fallowing separately in two subsequent years, allowing the land to be cultivated in the third year and recurring such pattern. Simulation findings across scenarios (GFDL, UKMO, and NCAR) indicate that water withdrawals for all crops decreased significantly, ranging from approximately 2.69% to 4.37%. Similarly, agriculture income experienced reductions, varying from around 1.53% to 2.26%. Also, surface water and groundwater withdrawals are represented as percentages. The data illustrate significant reductions in water withdrawals across all scenarios. For instance, in the GFDL scenario, surface water withdrawal decreased by approximately 1.85% for cotton, 2.56% for alfalfa/hay, and 1.58% for chile. Similarly, groundwater withdrawals saw substantial reductions, such as 14.93% for cotton, 20.44% for alfalfa/hay, and 12.62% for chile. These numbers emphasize the urgent need for sustainable water management practices to address the challenges posed by reduced water availability.

Groundwater is a strategic resource for economic development, social justice, environmental sustainability, and water governance. The lower Casas Grandes River Basin, located in the state of Chihuahua, México, is in a semi-arid region with increasing groundwater demand and regional challenges such as drought and depletion of aquifers. Even though there is official information about the availability of groundwater, a comprehensive aquifer characterization requiring an interdisciplinary investigation using a diverse suite of tools and multiple data sources has yet to be carried out. This study presents a multi-technique framework to evaluate potential sites to drill for groundwater resources and reduce the risk of unsuccessful drilling. The main components of the methodology include wellhead leveling correction with a differential global positioning survey to define piezometric levels, principal component analysis using LANDSAT-8 images, application of geospatial tools, geophysics analysis using time domain electromagnetic surveys (TDES) and vertical electric soundings (VES), and structural geohydrology to define aquifer characteristics. The results showed that using the proposed framework steps improved the possibility of identifying subsurface layers with lower resistivity values that could be related to groundwater. Low resistivity values (35 Ohm-m) were found at depths from 50 to 85 m at sites where the regional static water level reached a depth of 245 m, indicating the potential location of a shallow groundwater resource at a site where the intersection of a fracture trace was identified. This procedure can be used in other regions in the world where limited information is available for groundwater exploration, thus reducing the risk of drilling dry wells in complex hydrogeological environments.

Interconnected food, energy, and water (FEW) nexus systems face many challenges to support human well-being (HWB) and maintain resilience, especially in arid and semiarid regions like New Mexico (NM), United States (US). Insufficient FEW resources, unstable economic growth due to fluctuations in prices of crude oil and natural gas, inequitable education and employment, and climate change are some of these challenges. Enhancing the resilience of such coupled socio-environmental systems depends on the efficient use of resources, improved understanding of the interlinkages across FEW system components, and adopting adaptable alternative management strategies. The goal of this study was to develop a framework that can be used to enhance the resilience of these systems. An integrated food, energy, water, well-being, and resilience (FEW-WISE) framework was developed and introduced in this study. This framework consists mainly of five steps to qualitatively and quantitatively assess FEW system relationships, identify important external drivers, integrate FEW systems using system dynamics models, develop FEW and HWB performance indices, and develop a resilience monitoring criterion using a threshold-based approach that integrates these indices. The FEW-WISE framework can be used to evaluate and predict the dynamic behavior of FEW systems in response to environmental and socioeconomic changes using resilience indicators. In conclusion, the derived resilience index can be used to inform the decision-making processes to guide the development of alternative scenario-based management strategies to enhance the resilience of ecological and socioeconomic well-being of vulnerable regions like NM.

This research addresses a gap in the produced water management (PWM) literature by providing a conceptual framework to describe the connections of PWM to regional water budgets. We use southeastern New Mexico as a case study, because the region is facing looming shortfalls in water availability, and oil and gas production generate high volumes of produced water in the region. The framework was developed through expert interviews, analysis of industry data, and information gained at industry meetings; it is supported by detailed descriptions of material flows, information flows, and PWM decisions. Produced water management decisions may be connected to regional water budgets through dynamic complexities; however, modeling efforts exploring PWM often do not capture this complexity. Instead, PWM is most often based on the least expensive management and disposal alternatives, without considering short and long-term impacts to the regional water budget. On the other hand, regional water budgets do not include treated produced water as a potential resource, thus missing opportunities for exploring the impact of potential beneficial reuse. This is particularly important when there is a need to address water shortages in chronically water-short regions of the United States. At the same time, oil and gas production in the western United States is challenged by the need to dispose of large volumes of produced water. The framework is useful for developing improved models of PWM to identify the impact of alternative management decisions on regional water budgets.

An important tool to identify the origin of a groundwater resource is the use of isotopic signatures. Isotopic signatures give us the age of water and provide information as to the water’s origin, potential transit at geologic structures, source of salinization, and possible recharge points. The purpose of this study was to collect and analyze well samples to evaluate isotopic tracers (δ18O and tritium) in the transboundary Conejos-Médanos/Mesilla aquifer located between the US and Mexico. This new analyzed information was compared with the isotopic information available in the US Mesilla and US-MX Hueco basins generated by previous works, which described the common origin of the Hueco Bolson and Mesilla Basins aquifers. This study used isotopic analysis to validate the theory of the original formation and interconnectivity of both transboundary basins. This research presents new data of δ18O and tritium, and a comparison with previous published data from other workers, versus the known global meteoric water line (GMWL) and the Rio Grande evaporation line (RGEL). Results show that the groundwater at the transboundary aquifer features an evaporated isotopic signal, which is consistent with referenced published data that discusses the geologic history of aquifer formations at the studied area. This study is important because isotopic studies from the area were nonexistent and because isotopic data can explain recharge scenarios that relate to groundwater quality.

The effects of future land use change on arid and semi-arid watersheds in the American Southwest have important management implications. Seamless, national-scale land-use-change scenarios for developed land were acquired from the US Environmental Protection Agency Integrated Climate and Land Use Scenarios (lCLUS) project and extracted to fit the Northern Rio Grande River Basin, New Mexico relative to projections of housing density for the period from 2000 through 2100. Habitat models developed from the Southwest Regional Gap Analysis Project were invoked to examine changes in wildlife habitat and biodiversity metrics using five ICLUS scenarios. The scenarios represent a US Census base-case and four modifications that were consistent with the different assumptions underlying the A1, A2, B1, and B2 Intergovernmental Panel on Climate Change global greenhouse gas emission storylines. Habitat models for terrestrial vertebrate species were used to derive metrics reflecting ecosystem services or biodiversity aspects valued by humans that could be quantified and mapped. Example metrics included total terrestrial vertebrate species richness, bird species richness, threatened and endangered species, and harvestable species (e.g., waterfowl, big game). Overall, the defined scenarios indicated that the housing density and extent of developed lands will increase throughout the century with a resultant decrease in area for all species richness categories. The A2 Scenario, in general, showed greatest effect on area by species richness category. The integration of the land use scenarios with biodiversity metrics derived from deductive habitat models may prove to be an important tool for decision makers involved in impact assessments and adaptive planning processes.