Search for: All records

Groundwater depletion threatens global freshwater resources, necessitating urgent water management and policies to meet current and future needs. However, existing data-intensive approaches to assessments do not fully account for the complex human, climate, and water interactions within transboundary groundwater systems. Here, we present the design of and findings from a pilot participatory modeling workshop aiming to advance understanding of the hydrologic–human–climate feedback loops underpinning groundwater systems. Using participatory modeling tools and methods from the system dynamics tradition, we captured the mental models of researchers from water, social, data, and systems sciences. A total of 54 feedback loops were identified, demonstrating the potential of this methodology to adequately capture the complexity of groundwater systems. Based on the workshop outcomes, as an illustrative example, we discuss the value of participatory system modeling as a conceptualization tool, bridging perspectives across disciplinary silos. We further discuss how outcomes may inform future research on existing knowledge gaps around groundwater issues, and in doing so, advance interdisciplinary, use-inspired research for water decision-making more broadly. 

The extensive interest in sustainable water management reflects the extent to which the global water landscape has changed in the past twenty years, which is a natural development of changes in water resources and an increase in the level of imbalance between water supply and demand. In this paper, a simulation model based on system dynamics (SD) methodology was developed to aid sustainable water management efforts in a semi-arid region. Six policy scenarios were used to study, analyze, and assess water management trends in the Southeast region of New Mexico, USA. The modeling process included two phases: calibration (2000–2015) and future prediction (2016–2050). Several statistical criteria were applied to assess the developed model performance. The findings revealed that the simulated outputs were in excellent agreement with the historical data, indicating accurate model simulation. The SD model’s determination coefficients ranged from 0.9288 to 0.9936 and the index of agreement values ranged from 0.9397 to 0.9958. Findings for the business-as-usual scenario indicated that total water withdrawals and total population will continue to rise, whereas groundwater storage, agricultural consumptive water use, and total consumptive water use will decrease over the simulated period. Sensitivity analysis using Monte Carlo simulation indicated that cultivated irrigated land change is the most influential parameter affecting groundwater storage, water supply storage change (total withdrawals), agricultural consumptive water use, and total consumptive water use. The changes occurring in the agricultural cultivated area had a great influence on controlling the groundwater system. Overall, the results showed that our SD model has been successful in capturing the system’s dynamic behavior, and confirmed its capability in modeling water management issues for policy and decision makers under semi-arid conditions. 

The conventional approach of policy interventions in water management that focus on the portions of the system that directly relate to water often lead to unintended consequences that potentially exacerbate water scarcity issues and present challenges to the future viability of many rural agricultural communities. This paper deploys a system dynamics model to illustrate how expanding the policy space of hydrology models to include socioeconomic feedbacks could address these challenges. In this regard, policies that can potentially mitigate general water scarcity in a region of the American Southwest in southern New Mexico are examined. We selected and tested policies with the potential to diminish water scarcity without compromising the system’s economic performance. These policies included supporting choices that reduce or limit the expansion of water-intensive crops, promoting workforce participation, encouraging investment in capital, and regulating land use change processes. The simulation results, after the proposed boundary expansion, unveiled intervention options not commonly exercised by water decision-makers, bolstering the argument that integrated approaches to water research that include socioeconomic feedbacks are crucial for the study of agricultural community resilience. 

Agriculture is the most important sector with regard to water resources management due to its social, economic, hydrological, and environmental aspects, and many scholars and researchers have been driven to investigate the dynamic interrelationships among hydrological, environmental, and socioeconomic factors affecting agriculture. The system dynamics (SD) approach has become widely used because of its merits and benefits as a tool to deal with complex, dynamic problems and systems with many aspects and components that are involved and must be understood to ensure sound decisions regarding water and hydrological systems. Although agricultural water management needs to be studied as a main part of water management, socioeconomic management, and environmental management requiring the use of SD, this review shows that SD is currently used to a limited extent in terms of agricultural water management. This paper sheds light on the studies and investigations on the use of SD in the water sector and highlights the strengths of SD in order to encourage researchers to use this promising method to manage such a vital resource. Accordingly, this review seeks to include a comprehensive and up-to-date survey of existing publications and scholarly papers on the use of SD modeling as an effective technique for dealing with different problems associated with planning, management, and analysis of hydrology and water resources systems. Recent trends in the integration of SD with other modeling systems, such as artificial intelligence systems, are discussed along with the limitations and challenges facing application. This article makes a new contribution by giving a foundation of references and studies for scholars, researchers, and academics which encourages future investigation in employing the SD approach to hydrology and water resources management and planning, especially with agricultural water. 

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.