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March 10, 2026Hydrological Processes3 citations

Dynamic Water Budget Modeling to Fill Knowledge Gaps and Improve Water Management in Arid and Semi‐Arid Regions

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AMAhmed F. MashalyAHAustin HansonKPKevin Pérez

Key Points

  • The main aim is to develop and assess a dynamic modeling tool for understanding water budgets in arid regions, particularly New Mexico.
  • Developed the Dynamic Statewide Water Budget model for water balance estimation
  • Evaluated model performance using statistical indicators such as correlation coefficient and Nash-Sutcliffe efficiency
  • Analyzed hydrological variables in relation to climate change and drought conditions
  • Reviewed an interactive online tool for data characterization across spatial scales.
  • Model performance indicators showed high accuracy with a correlation coefficient of 0.95
  • Findings indicated a decline in snowmelt runoff and variability in surface water inflow due to climate change
  • Drought conditions were linked to decreased surface water and increased groundwater pumping for irrigation
  • Groundwater storage exhibited steady decline, especially in regions with limited recharge.

Abstract

ABSTRACT There is a gap in hydrological and water data in New Mexico, a state known for its arid to semi‐arid climate. The lack of access to these data presents a challenge to effective water management. The Dynamic Statewide Water Budget (DSWB) model represents an effort to apply water balance and system dynamics methodologies to estimate and quantify water budget components and to provide an accessible online tool for hydrological and water data in New Mexico. This paper highlights the model and presents the analysis and evaluation of the dynamic behaviour of selected hydrological variables in relation to climate change and drought, using data obtained from the model. The online DSWB interactive tool was also reviewed and evaluated for its role in providing hydrological data characterisation and demonstrating modelled results that compare multiple variables and scenarios across different spatial scales. The model performance was evaluated against measured and published data using several statistical indicators, including the correlation coefficient (0.95), root mean square error (8.24 kAF/year), Nash–Sutcliffe efficiency (0.84), performance index (0.96), coefficient of residual mass (0.04), index of agreement (0.92), mean absolute error (6.82 kAF/year), and mean absolute relative error (14.39%). All these metrics indicate satisfactory model performance. The findings indicate a decline in runoff from snowmelt and significant variability in surface water inflow due to climate change. They also demonstrate an interrelated relationship between drought conditions, surface water inflow, and groundwater storage, highlighting the interconnected dynamics among them. Drought further affects evaporation rates from reservoirs, while declining surface water availability leads to increased groundwater pumping to meet irrigation demand, emphasising the reliance on groundwater during drought periods. Groundwater storage has also been steadily decreasing, especially in regions that depend on fossil aquifers receiving little to no recharge. Overall, the model results indicate acceptable levels of accuracy and reliability, making it a useful tool for water management by providing hydrological estimates and predictions, as well as identifying key trends in water conditions. The DSWB model reflects a serious effort and promising attempt to fill existing knowledge gaps related to the water budget and provides a practical framework that can be utilised to improve water resource management in New Mexico. This model may also pave the way for developing additional water budget models based on the same methodology in other arid and semi‐arid regions around the world with hydrological data limitations.

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Cite This Study

Mashaly et al. (2026) studied this question.

synapsesocial.com/papers/69af950a70916d39fea4c420https://doi.org/10.1002/hyp.70443
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