Hydrogeology and simulation of ground-water flow and land-surface subsidence in the northern part of the Gulf Coast aquifer system, Texas

Mark C. Kasmarek; James L. Robinson

doi:10.3133/sir20045102

Home/Archive/USGS

USGS · sir20045102

Hydrogeology and simulation of ground-water flow and land-surface subsidence in the northern part of the Gulf Coast aquifer system, Texas

Mark C. Kasmarek·James L. Robinson

View original source ↗Read source document ↗Export metadata ↓

Abstract

As a part of the Texas Water Development Board Ground- Water Availability Modeling program, the U.S. Geological Survey developed and tested a numerical finite-difference (MODFLOW) model to simulate ground-water flow and land-surface subsidence in the northern part of the Gulf Coast aquifer system in Texas from predevelopment (before 1891) through 2000. The model is intended to be a tool that water-resource managers can use to address future ground-water-availability issues. From land surface downward, the Chicot aquifer, the Evangeline aquifer, the Burkeville confining unit, the Jasper aquifer, and the Catahoula confining unit are the hydrogeologic units of the Gulf Coast aquifer system. Withdrawals of large quantities of ground water have resulted in potentiometric surface (head) declines in the Chicot, Evangeline, and Jasper aquifers and land-surface subsidence (primarily in the Houston area) from depressurization and compaction of clay layers interbedded in the aquifer sediments. In a generalized conceptual model of the aquifer system, water enters the ground-waterflow system in topographically high outcrops of the hydrogeologic units in the northwestern part of the approximately 25,000-square-mile model area. Water that does not discharge to streams flows to intermediate and deep zones of the system southeastward of the outcrop areas where it is discharged by wells and by upward leakage in topographically low areas near the coast. The uppermost parts of the aquifer system, which include outcrop areas, are under water-table conditions. As depth increases in the aquifer system and as interbedded sand and clay accumulate, water-table conditions evolve into confined conditions. The model comprises four layers, one for each of the hydrogeologic units of the aquifer system except the Catahoula confining unit, the assumed no-flow base of the system. Each layer consists of 137 rows and 245 columns of uniformly spaced grid blocks, each block representing 1 square mile. Lateral no-flow boundaries were located on the basis of outcrop extent (northwestern), major streams (southwestern, northeastern), and downdip limit of freshwater (southeastern). The MODFLOW general-head boundary package was used to simulate recharge and discharge in the outcrops of the hydrogeologic units. Simulation of land-surface subsidence (actually, compaction of clays) and release of water from storage in the clays of the Chicot and Evangeline aquifers was accomplished using the Interbed-Storage Package designed for use with the MODFLOW model. The model was calibrated by trial-anderror adjustment of selected model input data in a series of transient simulations until the model output (potentiometric surfaces, land-surface subsidence, and selected water-budget components) reasonably reproduced field measured (or estimated) aquifer responses. Model calibration comprised four elements: The first was qualitative comparison of simulated and measured heads in the aquifers for 1977 and 2000; and quantitative comparison by computation and areal distribution of the root-mean-square error between simulated and measured heads. The second calibration element was comparison of simulated and measured hydrographs from wells in the aquifers in a number of counties throughout the modeled area. The third calibration element was comparison of simulated water-budget componentsprimarily recharge and dischargeto estimates of physically reasonable ranges of actual water-budget components. The fourth calibration element was comparison of simulated land-surface subsidence from predevelopment to 2000 to measured land surface subsidence from 1906 through 1995.

Explore related subjects

Scientific Investigations Report Report

Source-reported bounding extent: 28.36240173523821° to 31.998759371947294° latitude; -97.41577148437499° to -93.526611328125° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Mark C. Kasmarek, James L. Robinson. 2004. Hydrogeology and simulation of ground-water flow and land-surface subsidence in the northern part of the Gulf Coast aquifer system, Texas. https://doi.org/10.3133/sir20045102

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2026

Evaluating the number of realizations (train-test splits) necessary to ensure robust estimates of conventional hydrothermal resource favorability using Monte Carlo cross-validation, the Great Basin, Western USA

Supervised machine learning approaches used to produce favorability maps in resource assessments commonly partition an input dataset into training and testing subsets (that is, through train-test splits). However, if a single split is not representative of underlying resource conditions, the resulting favorability map may be biased, particularly with sparse or heterogeneous datasets. To mitigate the potential for unrepresentative favorability maps, recent works by U.S. Geological Survey researchers have used Monte Carlo cross-validation to implement a large number ( n) of randomized train-test splits to produce n realizations. The realizations are then aggregated using cell-wise median predictions to produce the resulting final favorability map, recognizing that the median will remove extreme values that might have been estimated from a comparatively few unrepresentative realizations. Theoretically, the median prediction at every cell converges to a single estimate as n approaches infinity, and the question addressed herein is: How many realizations are necessary to get a robust estimate (that is, an estimate unaffected by additional realizations)? Therefore, convergence metrics are described to identify the number of train-test splits and realizations needed to make a reliable map using the data and supervised machine learning workflow for conventional hydrothermal resource assessment of the Great Basin of the Western United States. For this study, robust prediction occurs with n approximately equal to 600 realizations, and smaller ensembles (for example, n is approximately equal to 200 or even 100) may be suitable during preliminary or exploratory analyses. Although the resulting threshold numbers will vary depending on the data and modeling approach used, the convergence metrics proposed and applied herein are applicable to other supervised machine learning studies that use Monte Carlo cross-validation.

Scientific Investigations Report↗

USGS2026

Groundwater budget for the Portneuf River Basin, southeastern Idaho

The U.S. Geological Survey, in cooperation with the Idaho Department of Water Resources, developed the first groundwater budget for the upper Portneuf River Basin in southeastern Idaho, a tributary of the Snake River. A groundwater budget for the Portneuf River Basin supports water resource and administrative management decisions within the basin and for downstream users of the eastern Snake River Plain aquifer. The analysis quantifies inflows, outflows, and residuals for an aquifer system defined by the Idaho Department of Water Resources under three recent precipitation conditions: an average year (2016), a dry year (2021), and a wet year (2023). The budget was calculated for the basin and for two subbasins delineated by the U.S. Geological Survey streamgage Portneuf River at Topaz, Idaho (13073000): the above Topaz subbasin, which includes the Portneuf-Gem valley, and the below Topaz subbasin, which includes Marsh Valley. Aquifer inflows include mountain-front recharge; areal recharge; recharge from applied water, including recharge from irrigation, canal seepage, and effluent returns; groundwater flow into the basin; and reservoir seepage. Outflows include groundwater pumping for agricultural, municipal, and domestic uses; subsurface outflow through the Portneuf gap; and discharge to streams as base flow. Estimated annual inflows for the full basin ranged from 116,880 acre-feet in 2021 to 154,880 acre-feet in 2023, and outflows ranged from 132,190 acre-feet in 2016 to 158,490 acre-feet in 2023. Basinwide residuals, the change in storage plus uncertainty, were −2,410 acre-feet in 2016, −18,410 acre-feet in 2021, and −3,610 acre-feet in 2023, and each subbasin had a mixture of negative and positive residuals. These basinwide results, interpreted as change in storage plus water-budget uncertainty, indicate minor net losses that increase with dry conditions, consistent with well depth-to-water measurements indicating gradual multi-decadal declines. Patterns in subbasin residuals are driven by irrigation practices and surface-water management; for example, the above Topaz subbasin relies more on groundwater for irrigation, resulting in more negative residuals during dry years. In contrast, the below Topaz subbasin depends more on surface water, producing positive residuals during dry years because of irrigation losses and canal seepage. The analyses for both subbasins indicate decades-long groundwater declines, which agree with the overall negative residuals calculated. The largest sources of uncertainty include climate inputs (precipitation and evapotranspiration) and poorly constrained components such as groundwater inflow and tributary stream infiltration. These findings provide insight into how climatic variables and irrigation practices affect groundwater inflows and outflows within the Portneuf River Basin.

Idaho↗

USGS2026

World minerals outlook—Antimony, copper, graphite, niobium, potash, silicon, silver, and tungsten through 2030

Demand for mineral commodities continues to increase owing to rapid technological advancements and global economic growth. To support this increase in demand, information about current and near-term supplies of these mineral commodities is essential. Such data help evaluate the health and stability of global supply chains and protect against potential supply risks. Current production and production capacity data coupled with information regarding near-term expected changes (such as facility closures, planned expansions, or the completion of new mineral production projects) can provide insight into expected future market developments and expected available supply of mineral commodities. This report within the “World Minerals Outlook” series analyzes data for antimony, copper, natural graphite, niobium, potash, silicon metal, silver, and tungsten—eight mineral commodities listed in the 2025 List of Critical Minerals. World production data from 2019 through 2025, as well as estimated world capacity data from 2023 through 2025 were analyzed. Using these data, near-term (2026–2030) expected world capacities were estimated. For antimony, copper, niobium, silicon metal, silver, and tungsten, modest increases in production capacity of 4 to 10 percent were expected between 2025 and 2030, whereas capacities for natural graphite and potash were expected to increase by about 18 to 20 percent.

Scientific Investigations Report↗