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A properly functioning local stormwater drainage system is essential for mitigating flood risks. This study evaluates the quality of roadside drainage channels in three underserved communities in Texas: the Sunnyside neighborhood in Houston (Harris County), a neighborhood in the City of Rockport (Aransas County), and the Hoehn colonia (Hidalgo County). These communities have a history of flooding, are highly socially vulnerable, and rely on roadside ditches as their principal stormwater drainage system for runoff control. Mobile lidar (Light Detection and Ranging) measurements were collected for 6.09 miles of roadside channels in these communities. The raw lidar measurements were processed to evaluate drainage conditions based on the channel's geometric properties, hydraulic capacity, and level of service. The assessment results are linked to a Geographic Information System (GIS) tool for enhanced visualization. Finally, the paper provides insights regarding the quality of stormwater infrastructure in the study communities and discusses their practical implications. [ABSTRACT FROM AUTHOR]

Lowland rivers regularly flood and create complex inundation patterns where energy and matter are exchanged between landscape patches over a dynamic network of surface‐water connections. Scale‐freeness of networks for phenomena in many disciplines have been studied with mixed results. Here we present the first documented example of a (roughly) scale‐free network of surface‐water connections within a river‐floodplain landscape. We accomplish this by simulating 23 inundation maps across the historical range of flows for the Mission River in Texas. We then analyze the topology of the surface‐water connections between the river and two habitat patch types. Results show that surface‐water connectivity is scale‐free for ≥64% of simulated flows (≥70% for flows with floodplain inundation). Moreover, the dynamic surface‐water connections meet five of the six conceptual criteria of scale‐free networks. Our findings indicate that river‐floodplain landscapes are self‐organizing toward scale‐free surface‐water connections among patches that optimizes energy and matter exchange. Plain Language Summary: Rivers that flow over relatively flat landscapes that are formed by their own sediment deposits flood in a manner where river water escapes the confines of the river channel and spills onto the adjacent floodplain. This flooding connects the river to a variety of habitats on the floodplain with the number of connections changing with the size of the river flow. The scale‐free network conceptual model has been used to represent connections and interactions among phenomena within numerous disciplines that include the geophysical, physical, biological, mathematical, engineering, and social sciences. Here we present the first documented example of a pattern of connections between a river and surrounding habitats induced by flooding that resembles the scale‐free network model. We accomplish this by modeling various river flows for Mission River in Texas using specialized computer programs. We then analyze the pattern of connections induced by flooding using specialized statistical methods and computer codes. Our results indicate that most of our modeled river flows create connections that meet five of the six conceptual criteria for scale‐free networks. This indicates that the parts of the river landscape are organizing themselves in a manner that attempts to optimize exchange of energy and matter. Key Points: Backwater inundation is a major component in the structure and function of river‐floodplain interactionsSurface‐water connectivity creates a dynamic network with a size, configuration, and function indicative of a scale‐free networkChannel and channel‐like features in the river landscape act as hubs that hold together the structure of surface‐water connectivity [ABSTRACT FROM AUTHOR]

Abstract: Freshwater inflows, among the most important factors in the overall health of estuarine environments, can be altered both by regional climatic influences as well as changes in land use and land cover. We conduct a scenario analysis to study the individual and combined impacts of changes in land use and land cover and in precipitation patterns in a coastal Texas watershed. The watershed is one of the major sources of freshwater for the estuarine area within the Mission-Aransas National Estuarine Research Reserve (NERR). Our scenario analysis suggests that climatic changes are more influential than land changes at the watershed level. However, localized impacts of land change may still be significant on habitats within the NERR site. Results from our watershed-level analysis poorly agree with the recommended freshwater flows established for the region, which deserve further scrutiny. Our findings suggest that geomorphic characteristics of the streams in the watershed need to be taken into consideration in hydrological modeling. Further research on the interactions between land change and hydrological dynamics should also aim for tighter temporal integration of the two sets of processes. [Copyright &y& Elsevier]

Abstract: We assessed short-term impacts of changes in military training load on vegetative cover at Fort Hood, TX. From 1989 to 1995, permanent field transects were monitored for vegetative cover and land use disturbance using standard army monitoring methods [Land Condition Trend Analysis (LCTA)]. Land use intensity (training load) was quantified and used to develop a model to predict future vegetation cover values. We found that standard Army monitoring methods detected changes in installation resources associated with changes in training load. Increased training loads were associated with increased measures of disturbance, decreased ground cover, and decreased aerial vegetative cover. We found that the spatial pattern of disturbance and vegetation cover remained relatively constant over the study period despite large variations in overall training load. Our model used the consistency in spatial cover patterns over time and the strong relationship between training load and vegetation cover to predict the impact of future training loads on vegetation. [Copyright &y& Elsevier]