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.

Climate change presents serious threats to the sustainability of coupled Water–Agriculture–Community Systems (WACSs) in New Mexico’s Lower Rio Grande (LRG) region. Enhancing the resilience of WACSs is essential for ensuring the system’s long-term adaptability and sustainability. Although the importance of system feedback and dynamic behavior is increasingly acknowledged in resilience studies, many existing assessments fail to account for the complex interconnections and self-organizing nature of these systems. This study utilizes a System Dynamics (SD) simulation modeling and a function-based resilience framework to assess WACSs’ responses to climate change, specifically investigating whether improvements in Water Conveyance Efficiency (WCE) can enhance system resilience in the LRG. The analysis centers on the interaction of socioeconomic and hydrological dynamics, incorporating future climate projections derived from three models: UKMO, GFDL, and NCAR. Findings reveal that under the UKMO scenario, enhanced WCE leads to improved resilience in the groundwater system; however, agricultural-community resilience declines under both the UKMO and GFDL scenarios. While hydrological resilience shows improvement—particularly with increased WCE—the agriculture–community system consistently exhibits limited capacity to adapt or reorganize. The differing outcomes across climate models underscore the sensitivity of WACS resilience to varying climatic conditions.

Water sustainability in the Lower Rio Grande region of southern New Mexico faces mounting challenges, including growing agricultural and municipal demands, uncertain policy directives, and prolonged drought conditions. Fallowing—temporarily taking land out of production—has been proposed as a strategy to conserve water, but its long-term effectiveness for sustaining both water resources and the agricultural economy remains unclear. This study builds on existing, previously published System Dynamics (SD) models, extending it through the integration of newly collected qualitative data to implement fallowing strategy and the development of a stakeholder-oriented decision support interface. The tool integrates SD modeling with social science insights derived from 49 semi-structured ethnographic interviews with local farmers to ensure relevance and usability. The SD model includes seven interconnected modules—hydrology, water use, agricultural and non-agricultural production, population, labor, and wages—along with fallowing-specific variables. The model incorporates hydro-agro-economic data for 205 variables, enabling simulation of feedback loops across water systems, economic activities, and land use decisions. Key DSS features include the ability to evaluate scenarios related to water rights, cover cropping, irrigation efficiency, mixed surface and groundwater use, crop rotation, and fallowing schedules. The DSS allows users to input specific farm-level information and visualize the long-term impacts of fallowing strategy on water availability and agricultural outcomes. Through an interactive interface, the tool aims to support data-driven decision-making among farmers, policymakers, and water managers. By combining scientific modeling with community engagement, this research contributes a practical framework for promoting sustainable water management and resilient agricultural systems in arid regions.