20 Hydrogeology and Marine/Coastal Geoscience (Posters)
This session covers aspects related to SGDs & their associated aquifers, including but not limited to: water–rock interaction, coastal aquifer contamination, geochemical transformation, hydrological flows, saline intrusion, coastal estuaries, and environmental, economic, and social SGD-related issues.
Wednesday, 22 April 2026
8:00 AM - 5:30 PM
LMH, 5th Floor Chapel
Do High-Resolution Gridded Precipitation Data Improve Hydrologic Modeling in Monsoon-Dominated Mountain Basins? Insights From SWAT+ Simulations in Northwestern Mexico
Paper number: 20-1
Program: Technical Sessions
Time: 8:15 AM – 8:30 AM
Authors
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Pasquinel de la Fraga ChávezCentro de Investigación Científica y de Educación Superior de Ensenada, Baja California, Ensenada, Baja California
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Enrique VivoniCenter for Hydrologic Innovations, Arizona State University, Tempe, AZ
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Yalina Montecelos ZamoraServicios Profesionales de Geología, Geofísica y Geotecnia, Ensenada, Baja California
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Francisco José Del Toro GuerreroInstituto de Ingeniería, Universidad Autónoma de Baja California , Mexicali, Baja California
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Tereza CavazosCentro de Investigación Científica y de Educación Superior de Ensenada, Baja California, Ensenada, Baja California
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Thomas Kretzschmar Presenting AuthorCentro de Investigación Científica y de Educación Superior de Ensenada, Baja California, Ensenada, Baja California
Abstract
Hydrologic modeling in mountainous regions is often hindered by complex topography, strong precipitation gradients, and limited ground-based observations. These challenges are particularly pronounced in monsoon-dominated basins of northwestern Mexico, where water resources support extensive agricultural and ecological systems. This study evaluates the influence of precipitation forcing on hydrologic simulations using the Soil and Water Assessment Tool Plus (SWAT+) model in the Humaya River basin, a steep, data-scarce watershed located in the Sierra Madre Occidental.
Four precipitation inputs were assessed: rain gauge observations, the Daymet high-resolution gridded dataset, and two bias-corrected versions of Daymet derived using quantile mapping and mean field bias correction (MFBC). Model calibration and validation were conducted independently for each forcing using monthly streamflow data for the period 1983–2001. An ensemble-based approach was applied by retaining the 100 best-performing simulations per configuration, allowing model outputs to be analyzed probabilistically and enabling an assessment of parameter uncertainty and equifinality. Water balance components and the spatial representation of hydrologic processes were also examined.
Results show that SWAT+ can reliably reproduce observed streamflow dynamics in this complex and data-limited environment, achieving good to very good performance across most configurations. The MFBC-corrected Daymet dataset yielded the highest overall performance (NSE = 0.81; PBias = 6.4 %), followed by uncorrected Daymet and gauge-based forcing, whereas quantile mapping resulted in reduced model skill. Evapotranspiration was the dominant water balance component, accounting for 49–55 % of annual precipitation, while streamflow represented 22–28 %. Daymet-based forcings increased simulated surface runoff and reduced groundwater contributions relative to Gauge-based simulations. Gridded precipitation inputs also enhanced the spatial representation of hydrologic processes, producing more realistic patterns of evapotranspiration, surface runoff, and groundwater contributions that reflect topographic and land-cover controls. Ensemble analyses revealed that precipitation forcing strongly influences water balance partitioning and parameter uncertainty, with bias-corrected inputs reducing equifinality relative to uncorrected datasets.
Overall, the findings demonstrate that precipitation forcing plays a critical role in conditioning hydrologic model behavior, water balance partitioning, and process representation in mountainous, data-scarce regions. High-resolution gridded precipitation datasets offer a robust alternative to sparse observations and can improve hydrologic assessments in complex terrain.
Geological Society of America Abstracts with Programs. Vol. 58, No. 3
doi: 10.1130/abs/2026CD-410806
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