<p>Lakes and wetlands cover a large portion of the earth’s surface and play a crucial role in hydrology. They provide permanent and temporary storage for water within the landscape allowing for greater infiltration and evaporation along with a reduction in peak flooding events. Lakes and wetlands also provide many other non-hydrological benefits such as their ability to improve water quality and provide wildlife and fisheries habitat. Despite their known benefits, wetland destruction has been a prominent issue for many years. This study quantifies the hydrologic effects of lakes and wetlands by introducing a parametrization method for hydrologic model simulations in the North American Land Data Assimilation System (NLDAS) domain. Lake profiles were created based on the geospatial lake depth-area relationship through interpolation of known lake depths and areas throughout the domain. Wetlands were parametrized based on topographic wetness index (TWI) calculated using high-resolution DEM imagery. Wetland profiles were created using a binning technique along with the DEM and land use classifications. The Variable Infiltration Capacity (VIC) macroscale hydrologic grid-based model and its associated lake and wetland algorithm were used to quantify the effects of lakes and wetlands on streamflow. Profiles were generated for every corresponding VIC grid cell in the NLDAS domain, but for this study two watersheds, the Buttahatchee River in Mississippi and the Black River in North Carolina, were selected to test the parametrization and quantify the impact of lakes and wetlands on watershed hydrology. The Buttahatchee River watershed contains 6.6% lakes and wetlands, which were predominantly clustered near the stream channel, and the Black River watershed contained 19.2% lakes and wetlands which were spread out across the entirety of the watershed. Simulated daily streamflow with and without the lake and wetland algorithm activated was used to evaluate impacts on flood frequency as well as components of the water balance. Flood magnitude decreased due to the presence of lakes and wetlands. This decrease was 5.8% and 29.6% for a 10-year return period flood for the Buttahatchee River and the Black River sites, respectively. Mean annual flowrate decreased significantly as a result of lakes and wetlands indicating storage of water in the lakes and wetlands allowed for a greater degree of evapotranspiration. There were 1.6% and 10.9% decreases in average streamflow rates as well as corresponding 0.3% and 4.1% increases in annual evapotranspiration in the Buttahatchee River and Black River watersheds, respectively. While lakes and wetlands reduce peak flood events and decrease average streamflow rates through increased storage and evapotranspiration, the magnitude of these impacts varies based on the quantity and distribution of lakes and wetlands in the watershed as well as the climate and vegetation present. </p>

This thesis presents the development of a hydrologic model in the vector environment. Establishing spatial relationship between flow elements is the key for flow routing techniques. Such a relationship is called hydrologic topology, making each flow element know which other elements are upstream and which are downstream. Based on the hydrologic topology established for the flow elements, tools were developed for flow network navigation, drainage area estimation, flow length calculation and drainage divide determination. To apply the tools, data required might be obtained from different sources, which may lead to certain problems that have to do with wrong flow direction of stream lines and, mismatches in location of stream lines with respect to the corresponding drainage area polygons. Procedures to detect such inconsistencies and to correct them have been developed and are presented here. Data inconsistencies correction and parameter computation methods form the basis for the development of a routing model, which would be referred as hydrologic model. The hydrologic model consists of an overland flow routing module, two options for channel routing and a reservoir routing module. Two case studies have been presented to show the application of the tools developed.

This thesis presents a method for calibrating regional scale hydrologic models using the upper South Saskatchewan River watershed as a case study. Regional scale hydrologic models can be very difficult to calibrate due to the spatial diversity of their land types. To deal with this diversity, both a manual calibration method and a multi-basin automated calibration method were applied to a WATFLOOD hydrologic model of the watershed. Manual calibration was used to determine the effect of each model parameter on modeling results. A parameter set that heavily influenced modeling results was selected. Each influential parameter was also assigned an initial value and a parameter range to be used during automated calibration. This manual calibration approach was found to be very effective for improving modeling results over the entire watershed. Automated calibration was performed using a weighted multi-basin objective function based on the average streamflow from six sub-basins. The initial parameter set and ranges found during manual calibration were subjected to the optimization search algorithm DDS to automatically calibrate the model. Sub-basin results not involved in the objective function were considered for validation purposes. Automatic calibration was deemed successful in providing watershed-wide modeling improvements. The calibrated model was then used as a basis for determining the effect of altering rain gauge density on model outputs for both a local (sub-basin) and global (watershed) scale. Four de-clustered precipitation data sets were used as input to the model and automated calibration was performed using the multi-basin objective function. It was found that more accurate results were obtained from models with higher rain gauge density. Adding a rain gauge did not necessarily improve modeled results over the entire watershed, but typically improved predictions in the sub-basin in which the gauge was located.

This thesis presents a method for calibrating regional scale hydrologic models using the upper South Saskatchewan River watershed as a case study. Regional scale hydrologic models can be very difficult to calibrate due to the spatial diversity of their land types. To deal with this diversity, both a manual calibration method and a multi-basin automated calibration method were applied to a WATFLOOD hydrologic model of the watershed. Manual calibration was used to determine the effect of each model parameter on modeling results. A parameter set that heavily influenced modeling results was selected. Each influential parameter was also assigned an initial value and a parameter range to be used during automated calibration. This manual calibration approach was found to be very effective for improving modeling results over the entire watershed. Automated calibration was performed using a weighted multi-basin objective function based on the average streamflow from six sub-basins. The initial parameter set and ranges found during manual calibration were subjected to the optimization search algorithm DDS to automatically calibrate the model. Sub-basin results not involved in the objective function were considered for validation purposes. Automatic calibration was deemed successful in providing watershed-wide modeling improvements. The calibrated model was then used as a basis for determining the effect of altering rain gauge density on model outputs for both a local (sub-basin) and global (watershed) scale. Four de-clustered precipitation data sets were used as input to the model and automated calibration was performed using the multi-basin objective function. It was found that more accurate results were obtained from models with higher rain gauge density. Adding a rain gauge did not necessarily improve modeled results over the entire watershed, but typically improved predictions in the sub-basin in which the gauge was located.

This thesis presents the development of a hydrologic model in the vector environment. Establishing spatial relationship between flow elements is the key for flow routing techniques. Such a relationship is called hydrologic topology, making each flow element know which other elements are upstream and which are downstream. Based on the hydrologic topology established for the flow elements, tools were developed for flow network navigation, drainage area estimation, flow length calculation and drainage divide determination. To apply the tools, data required might be obtained from different sources, which may lead to certain problems that have to do with wrong flow direction of stream lines and, mismatches in location of stream lines with respect to the corresponding drainage area polygons. Procedures to detect such inconsistencies and to correct them have been developed and are presented here. Data inconsistencies correction and parameter computation methods form the basis for the development of a routing model, which would be referred as hydrologic model. The hydrologic model consists of an overland flow routing module, two options for channel routing and a reservoir routing module. Two case studies have been presented to show the application of the tools developed.

Synthetic unit hydrographs, which assume uniform rainfall excess distribution and static watershed conditions, are frequently used to estimate hydrograph characteristics when observed data are unavailable. The objective of this research was to develop a spatially distributed unit hydrograph (SDUH) model that directly reflects spatial variation in the watershed in generating runoff hydrographs. The SDUH model is a time-area unit hydrograph technique that uses a geographic information system (GIS) to develop a cumulative travel time map of the watershed based on cell by cell estimates of overland and channel flow velocities. The model considers slope, land use, watershed position, channel characteristics, and rainfall excess intensity in determining flow velocities. The cumulative travel time map is divided into isochrones which are used to generate a time-area curve and the resulting unit hydrograph. Predictions of the SDUH model along with the Snyder, SCS, and Clark synthetic unit hydrographs were compared with forty observed storm events from an 1153-ha Virginia Piedmont watershed. The SDUH model predictions were comparable or slightly better than those from the other models, with the lowest relative error in the peak flow rate prediction for 12 of the 40 storms, and a model efficiency of at least 0.90 for 21 of the storms. Despite the good predictions of the hydrograph peak flow rate and shape, the time to peak was underpredicted for 34 of the 40 storms. Runoff from the 40 storms was also generated for two subwatersheds (C: 462 ha; D: 328 ha) in Owl Run to assess the effect of scale on the SDUH model. Peak flow rate predictions were more accurate for the entire watershed than for either subwatershed. The time to peak prediction and model efficiency statistics were comparable for the entire watershed and subwatershed D. Subwatershed C had poorer predictions, which were attributed to a large pond in the main channel, rather than to scale effects. The SDUH model provides a framework for predicting runoff hydrographs for ungauged watersheds that can reflect the spatially distributed nature of the rainfall-runoff process. Predictions were comparable to the other synthetic unit hydrograph techniques. Because the time to peak and model efficiency statistics were similar for the 1153-ha watershed and a 328-ha subwatershed, scale does not have a major impact on the accuracy of the SDUH model. / Master of Science

Effective prediction of localized flash flood regions for an approaching rainfall event requires an in-depth knowledge of the land surface and stream characteristics of the forecast area. Flash Flood Guidance (FFG) is currently formulated once or twice a day at the county level by River Forecast Centers (RFC) in the U.S. using modeling systems that contain coarse, generalized land and stream characteristics and hydrologic runoff techniques that often are not calibrated for the forecast region of a given National Weather Service (NWS) office. This research investigates the application of embedded geographic information systems (GIS) modeling techniques to generate a localized flash flood model for individual small watersheds at a five minute scale and tests the model using historical case storms to determine its accuracy in the FFG process. This model applies the Soil Conservation Service (SCS) curve number (CN) method and synthetic dimensionless unit hydrograph (UH), and Muskingum stream routing modeling technique to formulate flood characteristics and rapid update FFG for the study area of interest. The end result of this study is a GIS-based Flash Flood Forecasting system for ungaged small watersheds within a study area of the Blacksburg NWS forecast region. This system can then be used by forecasters to assess which watersheds are at higher risk for flooding, how much additional rainfall would be needed to initiate flooding, and when the streams of that region will overflow their banks. Results show that embedding these procedures into GIS is possible and utilizing the GIS interface can be helpful in FFG analysis, but uncertainty in CN and soil moisture can be problematic in effectively simulating the rainfall-runoff process at this greatly enhanced spatial and temporal scale. / Master of Science

Precipitation and surface runoff producing mechanisms are inherently spatially variable. Many hydrologic runoff models do not account for this spatial variability and instead use "lumped" or spatially averaged parameters. Lumped model parameters often must be developed empirically or through optimization rather than be calculated from field measurements or existing data. Recent advances in geographic information systems (GIS) remote sensing (RS), radar measurement of precipitation, and desktop computing have made it easier for the hydrologist to account for the spatial variability of the hydrologic cycle using distributed models, theoretically improving hydrologic model accuracy. Grid based distributed models assume homogeneity of model parameters within each grid cell, raising the question of optimum grid scale to adequately and efficiently model the process in question. For a grid or raster based hydrologic model, as grid cell size decreases, modeling accuracy typically increases, but data and computational requirements increase as well. There is great interest in determining the optimal grid resolution for hydrologic models as well as the sensitivity of hydrologic model outputs to grid resolution. This research involves the application of a grid based hydrologic runoff model to the Upper Roanoke River watershed (1480km2) to investigate the effects of precipitation resolution and grid cell size on modeled peak flow, time to peak and runoff volume. The gridded NRCS curve number (CN) rainfall excess determination and ModClark runoff transformation of HEC-HMS is used in this modeling study. Model results are evaluated against observed streamflow at seven USGS stream gage locations throughout the watershed. Runoff model inputs and parameters are developed from public domain digital datasets using commonly available GIS tools and public domain modeling software. Watersheds and stream networks are delineated from a USGS DEM using GIS tools. Topographic parameters describing these watersheds and stream channel networks are also derived from the GIS. A gridded representation of the NRCS CN is calculated from the soil survey geographic database of the NRCS and national land cover dataset of the USGS. Spatially distributed precipitation depths derived from WSR-88D next generation radar (NEXRAD) products are used as precipitation inputs. Archives of NEXRAD Stage III data are decoded, spatially and temporally registered, and verified against archived IFLOWS rain gage data. Stage III data are systematically degraded to coarser resolutions to examine model sensitivity to gridded rainfall resolution. The effects of precipitation resolution and grid cell size on model outputs are examined. The performance of the grid based distributed model is compared to a similarly specified and parameterized lumped watershed model. The applicability of public domain digital datasets to hydrologic modeling is also investigated. The HEC-HMS gridded SCS CN rainfall excess calculation and ModClark runoff transformation, as applied to the Upper Roanoke watershed and for the storm events chosen in this study, does not exhibit significant sensitivity to precipitation resolution, grid scale, or spatial distribution of parameters and inputs. Expected trends in peak flow, time to peak and overall runoff volume are observed with changes in precipitation resolution, however the changes in these outputs are small compared with their magnitudes and compared to the discrepancies between modeled and observed values. Significant sensitivity of runoff volume and consequently peak flow, to CN choices and antecedent moisture condition (AMC) was observed. The changes in model outputs between the distributed and lumped versions of the model were also small compared to the magnitudes of model outputs. / Master of Science

Master of Science / Department of Biological and Agricultural Engineering / Stacy Hutchinson / Military land management is vital to the future health and usability of maneuver training areas. As land disturbance increases, runoff from the area also increases and may create significant erosion potential. Determining the relationship between what is safe training versus what is harmful to the environment can be done by determining runoff potential at different disturbance percentages given different training intensities. Various studies have shown that soil density, soil structure, plant biodiversity, animal biodiversity, and many other essential ecosystem factors are greatly damaged by continuous training. These ecosystem factors influence runoff amounts and likewise erosion potential in that area. The primary factor examined in this study was the Curve Number (CN). Since military procedures do not have predefined CNs, representative CNs were created based off of CNs for agricultural use and supplemental research about training impacts on the land. Training intensity was broken into four classes: undisturbed, light use, moderate use, and heavy use. Five sample watersheds on Fort Riley were used as replications for the study. Disturbance intensity indexes were broken into 10% increments, and changes in runoff amount and peak rate modeled with TR-55. Statistical analysis was done comparing watersheds, training intensities and disturbance percentages for different storm magnitudes to assess statistically significance of changes in runoff amount and peak rate. This analysis showed that runoff amount and rate were both significantly impacted at every 10% increase on disturbance percentage. Results also showed that at the lower disturbance percentage (less than 30%), runoff amount and rate were not significantly impacted by training use classes. From this it can be seen that even with very little training done to the land increased erosion can be expected.

abstract: Soil moisture (θ) is a fundamental variable controlling the exchange of water and energy at the land surface. As a result, the characterization of the statistical properties of θ across multiple scales is essential for many applications including flood prediction, drought monitoring, and weather forecasting. Empirical evidences have demonstrated the existence of emergent relationships and scale invariance properties in θ fields collected from the ground and airborne sensors during intensive field campaigns, mostly in natural landscapes. This dissertation advances the characterization of these relations and statistical properties of θ by (1) analyzing the role of irrigation, and (2) investigating how these properties change in time and across different landscape conditions through θ outputs of a distributed hydrologic model. First, θ observations from two field campaigns in Australia are used to explore how the presence of irrigated fields modifies the spatial distribution of θ and the associated scale invariance properties. Results reveal that the impact of irrigation is larger in drier regions or conditions, where irrigation creates a drastic contrast with the surrounding areas. Second, a physically-based distributed hydrologic model is applied in a regional basin in northern Mexico to generate hyperresolution θ fields, which are useful to conduct analyses in regions and times where θ has not been monitored. For this aim, strategies are proposed to address data, model validation, and computational challenges associated with hyperresolution hydrologic simulations. Third, analyses are carried out to investigate whether the hyperresolution simulated θ fields reproduce the statistical and scaling properties observed from the ground or remote sensors. Results confirm that (i) the relations between spatial mean and standard deviation of θ derived from the model outputs are very similar to those observed in other areas, and (ii) simulated θ fields exhibit the scale invariance properties that are consistent with those analyzed from aircraft-derived estimates. The simulated θ fields are then used to explore the influence of physical controls on the statistical properties, finding that soil properties significantly affect spatial variability and multifractality. The knowledge acquired through this dissertation provides insights on θ statistical properties in regions and landscape conditions that were never investigated before; supports the refinement of the calibration of multifractal downscaling models; and contributes to the improvement of hyperresolution hydrologic modeling. / Dissertation/Thesis / Doctoral Dissertation Civil, Environmental and Sustainable Engineering 2018