Statewide Water Summary
Summaries of historical and future water balance fluxes across the state
National Water Model Outputs
Historical hydrologic fluxes (1980-2020) have been mapped through the use of the National Oceanic and Atmospheric Administration’s (NOAA) National Water Model (NWM) and Noah land surface model with multiparameterization options (Noah-MP), which provide gridded outputs for precipitation, evapotranspiration, surface runoff, groundwater recharge and other variables statewide. Model outputs are evaluated against on-the-ground data (stream gages, eddy covariance flux towers, snow telemetry stations, etc.) where available. The Hydroclimate team is currently working on future projections of water balance components statewide using downscaled general circulation models of future climate.
The following figures, developed by our Hydroclimate team members, show the long-term mean annual fluxes (1980-2020) for precipitation (P), evapotranspiration (ET), surface runoff (SR), and recharge (Re) according to the water mass balance of P = ET + SR + Re. The outputs from the NWM are provided per 1-km grids, as well as aggregated by USGS HUC-8 basin and groundwater basins. The data are also available for additional variables (max. precipitation, number of wet days, etc.) as well as seasonal averages (Jan.-March, April-June, July-Sept., Oct.-Dec.). As shown in the figures, while little natural recharge occurs across the state overall, the Mogollon Rim is highlighted as a region of critical importance for natural recharge.
The figures below are provided as example outputs and can be tailored to the needs of natural resource managers using the data available in .shp and .geotiff file formats.
Please use the following citation to credit this work:
Moiz, A. (2025). Arizona Hydrologic Fluxes (1981-2020) - National Water Model, HydroShare, http://www.hydroshare.org/resource/197f5389e8844a6f9cce31c239f81f08
1-km Gridded
Aggregated at HUC-8 Level
Aggregated at DWR Groundwater Basin Level
Publications
Regional base-flow index in arid landscapes using machine learning and instrumented records.
Mroczek, C., Springer, A. E., Gupta, N., Sankey, T., & Lucas, B. (2025). Regional base-flow index in arid landscapes using machine learning and instrumented records. Journal of Hydrology: Regional Studies, 62, 102778. https://doi.org/10.1016/j.ejrh.2025.102778
Abstract:
Study region: This study focuses on Arizona, a dryland state in the southwestern United States with marked variability in climate, elevation, and hydrogeology. Arizona spans two major physiographic regions, the Colorado Plateau and the Basin and Range, each exhibiting distinct hydrologic behavior.
Study focus: We quantify long-term base-flow index (BFI) patterns and trends across Arizona and develop a predictive framework for ungauged basins. BFI was calculated at 205 USGS stream gauges using a recursive digital filter applied to multi-decadal streamflow records. Coincident trends in precipitation, temperature, and evapotranspiration were analyzed to assess climate–base-flow relationships. We trained an eXtreme Gradient Boosting (XGBoost) model on hydroclimatic and physiographic variables to estimate long-term BFI from 1991 to 2020 at the 8-digit Hydrologic Unit Code (HUC) scale.
New hydrological insights for the region: Groundwater discharge accounts for approximately 32 % of streamflow in Arizona, with substantial spatial variability linked to topography, land cover, and climate. High BFI values are found in forested headwaters with spring-fed and snowmelt-driven systems, while low values dominate the state’s arid lowlands. Declining BFI trends were most pronounced in monsoon-dominated, warm-dry, and low-slope basins. Precipitation was the strongest climate correlate of BFI trends, underscoring the importance of climate variability for dryland base flow. This integration of observational records and machine learning provides new insights into groundwater–surface water interactions and offers a transferable framework for water resource assessment in data-scarce dryland regions globally.
The strong impact of precipitation intensity on groundwater recharge and terrestrial water storage change in Arizona, a typical dryland.
Qiu, Y., Famiglietti, J. S., Behrangi, A., Farmani, M. A., Yousefi Sohi, H., Gupta, A., Hung, F., Abdelmohsen, K., & Niu, G. (2025). The strong impact of precipitation intensity on groundwater recharge and terrestrial water storage change in Arizona, a typical dryland. Geophysical Research Letters, 52(14). https://doi.org/10.1029/2025gl114747
Abstract: This study demonstrates the critical role of precipitation intensity in groundwater recharge generation and terrestrial water storage (TWS) change. We conducted two experiments driven by precipitation products with close annual totals but distinct intensity in Arizona, using the Noah-MP model with advanced soil hydrology. The experiment with higher precipitation intensity (EXPHI) produces an annual groundwater recharge of 6.91 mm/year in Arizona during 2001–2020, ∼15 times that of the experiment with lower precipitation intensity (EXPLI). Correspondingly, EXPLI produces a declining groundwater storage (GWS) trend of 0.51 mm/month, nearly triple that of EXPHI. GWS change dominates the TWS trend. EXPLI shows a declining TWS trend of 0.57 mm/month, nearly twice that of EXPHI. Higher precipitation intensity reduces evapotranspiration and enhances infiltration and percolation, allowing more precipitation to recharge groundwater. This study underscores the need to ensure the accuracy of precipitation intensity in hydrological modeling for reliable water resources assessment and projection.