Percentage of basin-fill aquifer model grid cells in the Southwest Principal Aquifers study area that are predicted to exceed the relative background nitrate concentration, by percentage of agricultural and urban land use in the model grid cell ........... 48 12. Standardized importance scores for the prediction and confirmatory random forest classifiers of arsenic concentrations in basin-fill aquifers of the Southwest

[1] As populations grow in arid climates and desert bedrock aquifers are increasingly targeted for future development, understanding and quantifying the spatial variability of net infiltration becomes critically important for accurately inventorying water resources and mapping contamination vulnerability. This paper presents a conceptual model of net infiltration to desert sandstone and then develops an empirical equation for its spatial quantification at the watershed scale using linear least squares inversion methods for evaluating controlling parameters (independent variables) based on estimated net infiltration rates (dependent variables). Net infiltration rates used for this regression analysis were calculated from environmental tracers in boreholes and more than 3000 linear meters of vadose zone excavations in an upland basin in southwestern Utah underlain by Navajo sandstone. Soil coarseness, distance to upgradient outcrop, and topographic slope were shown to be the primary physical parameters controlling the spatial variability of net infiltration. Although the method should be transferable to other desert sandstone settings for determining the relative spatial distribution of net infiltration, further study is needed to evaluate the effects of other potential parameters such as slope aspect, outcrop parameters, and climate on absolute net infiltration rates.

The southwestern United States has substantially changed since 1900, with warming temperatures, diminishing precipitation and streamflows, worsening drought, and growth in population, irrigated agricultural land, and water withdrawals (MacDonald, 2010). The region is currently experiencing its worst drought in recorded history, with the period from 2000 to 2018 being the driest 19-year period since the late 1500s and the second driest since 800 Common Era (Williams et al., 2020). Despite little change in precipitation in the Upper Colorado River Basin (UCRB) between 1896 and 2019, temperatures have risen (Tillman et al., 2020) and water supplies in the basin have suffered (Udall & Overpeck, 2017). This recent drought has strained water resources and led to Congress passing the Colorado River Basin Drought Contingency Plan (DCP) Authorization Act in 2019. The DCP outlines agreements for Colorado River Basin (CRB) stakeholders to collaborate to reduce the risk that large Colorado River reservoirs (Lake Powell and Lake Mead) decline to critically low elevations. Despite these efforts, both reservoirs reached historic low elevations in 2021 (Bureau of Reclamation, 2021a, 2021b).

For more information on the USGS-the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment, visit http: //www.usgs.gov or call 1-888-ASK-USGS.For an overview of USGS information products, including maps, imagery, and publications, visit http://www.usgs.gov/pubprod. To order this and other USGS information products, visit http://store.usgs.gov.Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.Although this report is in the public domain, permission must be secured from the individual copyright owners to reproduce any copyrighted materials contained within this report. AbstractHuman-health concerns and economic considerations associated with meeting drinking-water standards motivated a study of the vulnerability of basin-fill aquifers to nitrate contamination and arsenic enrichment in the southwestern United States. Statistical models were developed by using the random forest classifier algorithm to predict concentrations of nitrate and arsenic across a model grid representing about 190,600 square miles of basin-fill aquifers in parts of Arizona, California, Colorado, Nevada, New Mexico, and Utah. The statistical models, referred to as classifiers, reflect natural and human-related factors that affect aquifer vulnerability to contamination and relate nitrate and arsenic concentrations to explanatory variables representing local-and basin-scale measures of source and aquifer susceptibility conditions. Geochemical variables were not used in concentration predictions because they were not available for the entire study area. The models were calibrated to assess model accuracy on the basis of measured values.

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