Evaluating future water availability in Texas through the lens of a data-driven approach leveraged with CMIP6 general circulation models.

Climate change is escalating the frequency and intensity of extreme precipitation events, significantly influencing the spatial and temporal distributions of water resources. This is particularly evident in Texas, a rapidly growing state with a pronounced west-east gradient in water supply. This study utilizes Coupled Model Intercomparison Project Phase 6 (CMIP6) data and data-driven methodology to improve projections of Texas's future water resources, focusing on actual evapotranspiration (AET) and water availability through enhanced Multi-Model Ensembles. The results reveal that the data-driven model significantly outperforms the CMIP5 and CMIP6 models across all skill metrics, underscoring the potential of data-driven methodologies in advancing climate science. Furthermore, the study provides an in-depth analysis of the projected changes in net water availability (NWA) and estimated water demand for different regions in Texas over the next six decades from 2015 to 2074, which reveal fluctuating patterns of water stress, with the regions (nine out of sixteen water planning regions in Texas, especially for the most populated regions) poised for heightened challenges in reconciling water demand and availability. While increasing trends are found in precipitation, AET, and NWA for the northern region of Texas based on SSP2-4.5, decreasing trends are found over the southern region for all three parameters based on SSP5-8.5. These findings underscore the importance of factoring both spatial and temporal variations in water availability and demand for effective water management strategies and the need for adaptive water management strategies for the changing water availability scenarios.

Does flooding get worse with subsiding land? Investigating the impacts of land subsidence on flood inundation from Hurricane Harvey.

As one of the most devastating tropical storms, 2017 Hurricane Harvey caused severe flooding and damage in Houston, Texas. Besides enormous rainfall amount, land subsidence might be another contributing factor to the Harvey flood. However, few studies have numerically quantified the evolvement of land subsidence over decades, largely due to the lack of reliable methods to realistically estimate land subsidence both continuously and at high spatial resolution. Therefore, this study aims to investigate retrospective changes of regional topology due to 117 years (1900 to 2017) of land subsidence and the consequent impacts on flood inundation. Based on continuous land subsidence, we conduct a series of simulations on the 2017 Hurricane Harvey in Brays Bayou, Texas using a hydrodynamic/hydraulic model. The results indicate that the overall change of flood depth caused by land subsidence is relatively minor with the flood water deepened by six centimeters per one meter of subsided land at the worst impacted location. The impact from land subsidence on flood depth exhibits strong nonlinearity in time, where effects from previous land subsidence hotspots could be altered by later continuing land subsidence. Spatially, changes in flood depth due to the land subsidence are not only heterogeneous but mixed with coexisting increased and reduced flood depths. The results of this study improve the understanding of the dynamic evolvement of flood inundation due to continuous land subsidence so that better planning can be initiated for sustainable urban development for coastal communities, which is imperative under ongoing climate change and sea level rise.