Relative sea level rise at tide gauge Galveston Pier 21, Texas, is the combination of absolute sea level rise and land subsidence. We estimate subsidence rates of 3.53 mm/a during 1909–1937, 6.08 mm/a during 1937–1983, and 3.51 mm/a since 1983. Subsidence attributed to aquifer-system compaction accompanying groundwater extraction contributed as much as 85% of the 0.7 m relative sea level rise since 1909, and an additional 1.9 m is projected by 2100, with contributions from land subsidence declining from 30 to 10% over the projection interval. We estimate a uniform absolute sea level rise rate of 1.10 mm ± 0.19/a in the Gulf of Mexico during 1909–1992 and its acceleration of 0.270 mm/a² at Galveston Pier 21 since 1992. This acceleration is 87% of the value for the highest scenario of global mean sea level rise. Results indicate that evaluating this extreme scenario would be valid for resource-management and flood-hazard-mitigation strategies for coastal communities in the Gulf of Mexico, especially those affected by subsidence.

As much as 3.05 m of land subsidence was observed in 1979 in the Houston-Galveston region as a result primarily of inelastic compaction of aquitards in the Chicot and Evangeline aquifers between 1937 and 1979. The preconsolidation pressure heads for aquitards within these two aquifers were continuously updated in response to lowering groundwater levels, which in turn was caused by continuously increasing groundwater withdrawal rates from 0.57 to 4.28 million m³/day. This land subsidence occurred without any management of changes in groundwater levels. However, the management of recovering groundwater levels from 1979 to 2000 successfully decreased inelastic compaction from about 40 mm/yr in the early 1980s to zero around 2000 through decreasing groundwater withdrawal rates from 4.3 to 3.0 million m³/day. The inelastic consolidation that had existed for about 63 years roughly from 1937 to 2000 caused a land subsidence hazard in this region. Some rebounding of the land surface was achieved from groundwater level recovering management. It is found in this paper that subsidence of 0.08 to 8.49 mm/yr owing to a pseudo-constant secondary consolidation rate emerged or tended to emerge at 13 borehole extensometer station locations while the groundwater levels in the two aquifers were being managed. It is considered to remain stable in trend since 2000. The subsidence due to the secondary consolidation is beyond the control of any groundwater level change management schemes because it is caused by geo-historical overburden pressure on the two aquifers. The compaction measurements collected from the 13 extensometers since 1971 not only successfully corroborate the need for groundwater level change management in controlling land subsidence but also yield the first empirical findings of the occurrence of secondary consolidation subsidence in the Quaternary and Tertiary aquifer systems in the Houston-Galveston region.

The compaction measurements of Quaternary and Tertiary Gulf Coast aquifer system sediments in the Houston-Galveston region (TX) show spatially variable compression of 0.08 to 8.49 mm/yr because of geohistorical overburden pressure when groundwater levels in the aquifer system were stable after about the year 2000. An aquifer-system creep equation is developed for evaluating this variable compression, with a thickness-weighted average creep coefficient based on Taylor's (1942) secondary consolidation theory. The temporal variation of aquifer system creep can be neglected in a short-term observation period (such as a decade) after a long-term creep period (such as over 1,000 years) in geohistory. The creep coefficient of the Gulf Coast aquifer system is found to be in a range of 8.74 × 10⁻⁵ to 3.94 × 10⁻³ (dimensionless), with an average of 1.38 × 10⁻³. Moreover, for silty clay or clay-dominant aquitards in the Gulf Coast aquifer system the creep coefficient value varies in the range of 2.21 × 10⁻⁴ to 3.94 × 10⁻³, which is consistent with values found by Mesri (1973) for most soils, which vary in the range of creep coefficient, 1 × 10⁻⁴ to 5 × 10⁻³. Land subsidence due to secondary consolidation of the Gulf Coast aquifer system is estimated to be 0.04 to 4.33 m in the 20th century and is projected to be 0.01 to 0.64 m in the 21st century at the 13 borehole extensometer locations in the Houston-Galveston region. The significant creep should be considered in the relative sea level rise, in addition to tectonic subsidence and primary consolidation.

In this study, a stress-dependent groundwater model, MODFLOW-SD, has been developed and coupled with the nonlinear subsidence model, NDIS, to predict vertical deformation occurring in basins with highly compressible deposits. The MODFLOW-SD is a modified version of MODFLOW (the USGS Modular Three-Dimensional Groundwater Flow Model) with two new packages, NONK and NONS, to update hydraulic conductivity and skeletal specific storage due to change in effective stress. The NDIS package was developed based on Darcy–Gersevanov Law and bulk flux to model land subsidence. Results of sample simulations run for a conceptual model showed that hydraulic heads calculated by MODFLOW significantly overestimated for confining units and slightly underestimated for aquifer ones. Moreover, it showed that applied stress due to pumping changed initially homogeneous layers to be heterogeneous ones. Comparison of vertical deformations calculated by NDIS and MODFLOW-SUB showed that neglecting horizontal strain and stress-dependency of aquifer parameters can overestimate future subsidence. Furthermore, compared to the SUB (Subsidence and Aquifer-System Compaction) package, NDIS is more likely to provide a more accurate compaction model for a complex aquifer system with vertically variable compression ( $C_c$ ), recompression $\left(C_r\right)$ , and hydraulic conductivity change ( $C_k$ ) indices.

MODFLOW is the U.S. Geological Survey modular finite-difference flow model, which is a computer code that solves the groundwater flow equation. The program is used by hydrogeologists over the world to simulate the flow of groundwater through aquifer systems.Compressible low permeable sediments in aquifer systems may occur as discontinuous interbeds or aquitards within aquifers or as extensive confining units adjacent to aquifers. Flow in the extensive confining units can be simulated by MODFLOW through taking the units as no-delay flow model layers. Flow delay was found by Terzaghi in 1925 through his 1D analytical consolidation solution. For a double-drainage confining unit adjacent to aquifers, consolidation degree reaches 99.4% while time factor value reaches 2. A 99.4% consolidation degree during one time step is employed in this paper to denote a no-delay flow model layer in MODFLOW simulation. An additional delay coefficient compared to Terzaghi’s flow delay in a low permeable confining unit was found in this paper to be in a range of 87.5 to 29 which depend on model layer number of the confining unit in MODFLOW simulation. No-delay option requires that the minimum time step used in MODFLOW is larger than a delay time length determined by a production of time factor of 2, time constant and additional delay coefficient of a confining unit. It is not appropriate to apply no-delay option to simulating flow in a confining unit if the minimum time step is less than a determined delay time length with a selected sub model layer number and drainage length of the unit.No-delay option can be only applied to very thin confining units in aquifer systems.

Soil moisture plays a crucial role in hydrological processes and serves as a key driver of rainfall-induced landslides, especially in regions with steep terrain and intense precipitation. Traditional landslide risk models often oversimplify soil moisture and infiltration dynamics, which limits their predictive accuracy. This study presents a deep learning-based framework for generating high-resolution, spatiotemporal Surface Soil Moisture (SSM) maps for Prince George’s County, Maryland—a region highly susceptible to rainfall-triggered landslides—aimed at improving infiltration modeling and landslide prediction. A Convolutional Long Short-Term Memory (ConvLSTM) network integrates static spatial features (elevation, slope, soil type) with multi-temporal meteorological variables (precipitation, temperature, humidity, wind speed, evapotranspiration) and vegetation indices. The model is trained using dense SSM maps derived from Sentinel-1 SAR data processed through a change detection algorithm, providing a physically meaningful alternative to sparse in-situ observations. To address data imbalance, a two-pass patch extraction strategy was implemented to enhance representation of high-SSM conditions. The framework leverages high-performance computing resources to process large-scale, multi-temporal raster datasets efficiently. Evaluation results show strong predictive performance, with the two-day model achieving ${\mathrm{R}}^2$ = 0.72, correlation = 0.85, RMSE = 0.154, and MAE = 0.103. The results demonstrate the model’s capability to produce fine-resolution, wall-to-wall SSM maps that capture the spatial and temporal dynamics of surface soil moisture, supporting the development of early warning systems and landslide hazard mitigation strategies.