Modeling the Effects of Low Impact Development Practices on Streams at the Watershed Scale

Urban growth contributes to increasing storm water runoff which in turn causes an increase in the frequency and severity of flooding. Moreover, increased storm water runoff contributes to changing the character and volume of energy inputs to the stream. Traditionally, storm water management controls such as detention pond had been extensively studied and evaluated with respect to reducing and controlling peak flows. Nonpoint source pollutants due to urbanization and expanding of agricultural fields have become a big burden on municipalities and states. Low Impact Development practices were developed to negate the negative impacts of urbanization on water resources by reducing the runoff volume and peak flows as well as improving outflow water quality. Though these practices have the capability of reducing runoff volumes and enhancing outflow water quality, they can be costly. Therefore, understanding the impact of installing LID practices on a watershed scale is becoming increasingly important. In this study, field experiment and model study were applied to evaluate the effectiveness of LID practices on a watershed scale in the Blunn Creek Watershed located in Austin, Texas. The three LID practices which were evaluated in this study are permeable pavements, a bioretention area, and a detention pond. The main objective of this study was to investigate the influences of these practices at a watershed scale on: potential reduction on channel bank erosion, potential reduction on flood, and potential impact on aquatic life. This study was one of very few studies that take place in the Blackland clay soil in Texas. A combination of different levels of LID practices such as permeable pavement and bioretention area resulted with achieving the main goal of this study of reducing stream bank erosion, bankfull exceedance, and maintaining acceptable flows for the integrity of aquatic life habitat. All LID practices have shown significant difference with respect to a control treatment at 95% confidence ratio. Performance of the modeled LID practices was validated by showing acceptable agreement in the percentage of reductions in total runoff between field experiments and model data

Investigating Rainwater Harvesting as a Stormwater Best Management Practice and as a Function of Irrigation Water Use

Stormwater runoff has negative impacts on water resources, human health and environment. In this research the effectiveness of Rain Water Harvesting (RWH) systems is examined as a stormwater Best Management Practice (BMP). Time-based, evapotranspiration-based, and soil moisture-based irrigation scheduling methods in conjunction with RWH and a control site without RWH were simulated to determine the effect of RWH as a BMP on a single-family residence scale. The effects of each irrigation scheduling method on minimizing water runoff leaving the plots and potable water input for irrigation were compared. The scenario that reflects urban development was simulated and compared to other RWH-irrigation scheduling systems by a control treatment without a RWH component. Four soil types (sand, sandy loam, loamy sand, silty clay) and four cistern sizes (208L, 416L, 624L, 833L) were evaluated in the urban development scenario. To achieve the purpose of this study; a model was developed to simulate daily water balance for the three treatments. Irrigation volumes and water runoff were compared for four soil types and four cistern sizes. Comparisons between total volumes of water runoff were estimated by utilizing different soil types, while comparisons between total potable water used for irrigation were estimated by utilizing different irrigation scheduling methods. This research showed that both Curve Number method and Mass-Balance method resulted in the greatest volumes of water runoff predicted for Silty Clay soil and the least volumes of water runoff predicted for Sand soil. Moreover, increasing cistern sizes resulted in reducing total water runoff and potable water used for irrigation, although not at a statistically significant level. Control treatment that does not utilize a cistern had the greatest volumes of predicted supplemental water among all soil types utilized, while Soil Moisture-based treatment on average had the least volume of predicted supplemental water

Moving from theory to practice in the water–energy–food nexus: An evaluation of existing models and frameworks

The recognition of the interlinked nature of water, energy and food (WEF) resources has resulted in growing momentum to change the approaches for managing these interlinked resources. Initially, models were developed as a mean of integrated methodology for watershed management. Several frameworks and models have been proposed to help policymakers understand the complexity of the nexus and to assist with planning and regulating these resources. Most countries and governments manage these natural resources with different institutions that have their own mission and objectives, and with their own staff, data, measures and tools. This has mostly led to huge variations in terms of methodological approach to design these models, type of data used and eventually results interpretations and policies design.We conducted a review of current literature on the water–energy–food nexus to understand what’s known and what’s missing and identify key opportunities and challenges facing WEF design and modeling. Our analysis also identified the followings: • Our review reveals that there are a limited number of models and frameworks that address all WEF together and there are even fewer models and frameworks that has diverse methods and transdisciplinary approaches in analyzing the nexus. It’s essential as we design out modeling tools to analyze the nexus to incorporate several dimensions beyond the WEF sectors such as political, social and economic in order to reach nexus thinking and therefore address complexity of the multi-sectoral resources. • Agricultural sectors require significant amounts of energy as an input to production, yet few water–energy–food resource planning approaches have incorporated spatial cropping patterns and land use by combining energy and water requirements. • Policymakers are provided with an effective way to analyze the nexus on an aggregate level using macro-drivers, but these often omit the complexity of managing the resources at a smaller scale where other factors such as climate and geography have tremendous influence on supply and demand. • There are knowledge gaps pertaining the incorporation of spatial–temporal drivers as well as the spatial–temporal dynamics of resource availability or accessibility. This is a significant component in the WEF framework design as natural resources are subject to dramatic changes over space and time. • There are a considerable number of WEF framework and models that demonstrate promising tools to analyze the nexus but some of these models fall short of capturing interactions among nexus components due to lack of data sharing and availability.The increased regional and global variation in natural resources distribution over time and space creates a need to develop more sophisticated models that incorporate these drivers to support the planning and regulatory policy process. These models should also be flexible enough to be applied at varying geographic levels to support resource management at the national, regional, watershed and project levels. Integrating spatial–temporal drivers would result in more comprehensive models that can deliver better policies for sustainable development, increase synergies between institutions and improve social welfare. Keywords: Water, Energy, Food, Policy, Framewor