The studies in this dissertation address the issue of variability in runoff generation and pollutant concentration in urban areas, and specifically in the catchments of stormwater control measures. There is an imperfect correlation between runoff volumes and the capture area and land uses of urban catchments. Variable capture areas and uncertainty in urban runoff sources complicate stormwater control measure design and urban stream assessment. Four stormwater control measures in upstream suburban Philadelphia, ranging in capture area from 0.11 ha to 32 ha, were monitored, sampled, and modeled. Sampling was conducted in the watersheds of Wissahickon Creek, Tookany Creek, and Pennypack Creek. The approaches discussed below have the goal of better understanding runoff and the movement of associated contaminants into stormwater retention basins and streams. Rather than viewing runoff generation and contaminant transport as a static process, this work proposes that the amount of runoff contributed from different areas of a catchment changes during and between storm events, and that the origin and concentration of contaminants change as a result. Linking source areas to runoff volumes through natural and modeled tracers could improve predictions of water quality and quantity in stormwater control measures in urban streams. Nitrate (NO3–) isotope ratios were used as tracer of flow from different urban land uses. Time series samples of stormwater runoff entering two stormwater control measures (a constructed wetland and a small bioretention basin) were collected and analyzed to distinguish sources of NO3– by samples’ δ15N and δ18O ratios. A Bayesian mixing model was used to determine that NO3– sources were a mix of soil nitrogen (N) and atmospheric deposition across six storm events. Furthermore, atmospheric versus soil N sources varied throughout the storms. The large catchment of the constructed wetland had more NO3– source variability between samples compared to the small catchment of the bioretention basin. Thus, the NO3– isotopes suggest more distinct flow paths in the large catchment and more mixing of flow across land uses in the small catchment. Quantifying flow path variability from storm to storm and between different catchments can improve design and placement of urban stormwater control measures. A distributed hydrologic model, GSSHA, was used to simulate overland runoff from impervious and semi-pervious land covers in the catchment of a stormwater control measure. The positions of low vegetation and impervious land uses over the catchment were rearranged to create hypothetical catchments during four storm events. Fluctuating source proportions over time suggested that grab samples might not be adequate for capturing average overland runoff chemistry. It was also found that the portion of total runoff volume from impervious areas varied from 50 to 75% while the relative proportion of impervious cover remained constant at 54%. Land use percentages averaged over capture areas are frequently used to estimate runoff amounts and pollutant concentrations, but this model disrupts the assumption that urban hydrologic responses can be predicted from imperviousness alone. Overland runoff was measured and modeled before and after the installation of two stormwater control measures, a berm and a bioswale. Discharge in the stream was modeled for 9 storms ranging in size from 14 to 54 mm. We found that during 4 of the modeled storms there was no decrease in stream discharge and decreases in discharge were generally only observed for low intensity storms. Furthermore, only 5% of the stream catchment was captured by SCMs. Modeled tracers, used to track runoff contributions from areas upslope of the SCMs found that the size of upslope contributing areas did not predict the proportion of runoff generated in each area. Field data to support the models included water level loggers and samples of overland runoff collected in subsurface stormwater casing. After the SCMs were installed, less water was captured in downslope sampling bottles, but new flow paths developed. Furthermore, significant variation was observed in upslope concentrations of dissolved nutrients and total suspended solids, casting doubt on whether point samples of urban overland runoff geochemistry can be representative given variable runoff generation and heterogeneous land uses. This study points out the challenges in evaluating stormwater control measures and reveals that source areas’ contribution to stream flow varies independently of their size. Therefore, modeling before stormwater control measure installation is recommended to determine the factors that influence a capture area’s contribution to urban streamflow. / Geoscience

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Doctor of Philosophy / Department of Agronomy / P.V. Vara Prasad / Agriculture is the largest (90%) consumer of all fresh water in the world. The consumptive use of water by vegetation represented by the process evapotranspiration (ET) has a vital role in the dynamics of water, carbon and energy fluxes of the biosphere. Consequently, mapping ET is essential for making water a sustainable resource and also for monitoring ecosystem response to water stress and changing climate. Over the past three decades, numerous thermal remote sensing based ET mapping algorithms were developed and these have brought a significant theoretical and technical advancement in the spatial modeling of ET. Though these algorithms provided a robust, economical, and efficient tool for ET estimations at field and regional scales, yet the uncertainties in flux estimations were large, making evaluation a difficult task. The main objective of this study was to evaluate and improve the performance of widely used remote sensing based energy balance models, namely: the Surface Energy Balance Algorithm for Land (SEBAL), Mapping Evapotranspiration at high Resolution and with Internalized Calibration (METRIC), and Surface Energy Balance System (SEBS). Data used in this study was collected as part of a multi-disciplinary and multi-institutional field campaign BEAREX (Bushland Evapotranspiration and Agricultural Remote Sensing Experiment) that was conducted during 2007 and 2008 summer cropping seasons at the USDA-ARS Conservation and Production Research Laboratory (CPRL) in Bushland, Texas. Seventeen high resolution remote sensing images taken from multispectral sensors onboard aircraft and field measurements of the agro-meteorological variables from the campaign were used for model evaluation and improvement. Overall relative error measured in terms of mean absolute percent difference (MAPD) for instantaneous ET (mm h[superscript]-[superscript]1) were 22.7%, 23.2%, and 12.6% for SEBAL, METRIC, and SEBS, respectively. SEBAL and METRIC performances for irrigated fields representing higher ET with limited or no water stress and complete ground cover surfaces were markedly better than that for dryland fields representing lesser ET and greater soil water deficits with sparser vegetation cover. SEBS algorithm performed equally well for both irrigated and dryland conditions but required accurate air temperature data. Overall, this study provides new insights into the performance of three widely used thermal remote sensing based algorithms for estimating ET and proposed modifications to improve the accuracy of estimated ET for efficient management of water resources.

<p>Accurate modeling of land-atmosphere interaction would help us understand the persistent weather conditions and further contribute to the skill of seasonal climate prediction. In this study, seasonal variations in radiation and precipitation forcing are included in a stochastic soil water balance model to explore the seasonal evolution of soil moisture probabilistic structure. The theoretical results show soil moisture tends to exhibit bimodal behavior only in summer when there are strong positive feedback from soil moisture to subsequent rainfall. Besides the statistical analysis of soil moisture – rainfall feedback, simplified mixed-layer models, coupled with soil-plant-atmosphere continuum, are also used to study heat flux partitioning, cloud initiation, and strength of moist convection. Approximate analytical solutions to the mixed-layer model are derived by applying Penman-Monteith approach, which help explain the roles of equilibrium evaporation and vapor pressure deficit in controlling the diurnal evolution of boundary layer. Results from mixed-layer model also define four regimes for possible convection in terms of cloud/no-cloud formation and low/high convection intensity. Finally, cloud-topped mixed-layer model is developed to simulate the boundary-layer dynamics after the cloud formation, when the evaporative and radiative cooling other than surface heat flux may significantly contribute to the growth of the boundary layer.</p> / Dissertation

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