Nitrogen losses from artificially drained watersheds degrade water quality at local and regional scales. In this study, we used an end-member mixing analysis (EMMA) together with high temporal resolution water quality and streamflow data collected in the 122 km Otter Creek watershed located in northeast Iowa. We estimated the contribution of three end-members (groundwater, tile drainage, and quick flow) to streamflow and nitrogen loads and tested several combinations of possible nitrate concentrations for the end-members. Results indicated that subsurface tile drainage is responsible for at least 50% of the watershed nitrogen load between April 15 and November 1, 2015. Tiles delivered up to 80% of the stream N load while providing only 15-43% of the streamflow, whereas quick flows only marginally contributed to N loading. Data collected offer guidance about areas of the watershed that should be targeted for nitrogen export mitigation strategies.

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In 2008 flooding occurred over a majority of Iowa, damaging homes, displacing residents, and taking lives. In the wake of this event, the Iowa Flood Center (IFC) was charged with the investigation of distributed flood mitigation strategies to reduce the frequency and magnitude of peak flows in Iowa. This dissertation is part of the several studies developed by the IFC and focused on the application of a coupled physics based modeling platform, to quantify the coupled benefits of distributed flood mitigation strategies on the reduction of peak flows in an agricultural watershed. Additional investigation into tile drainage and terraces, illustrated the hydrologic impact of each commonly applied agricultural practice. The effect of each practice was represented in numerical simulations through a parameter adjustment. Systems were analyzed at the field scale, to estimate representative parameters, and applied at the watershed scale. The impact of distributed flood mitigation wetlands reduced peak flows by 4 % to 17 % at the outlet of a 45 km 2 watershed. Variability in reduction was a product of antecedent soil moisture, 24-hour design storm total depth, and initial structural storage capacity. The highest peak flow reductions occurred in scenarios with dry soil, empty project storage, and low rainfall depths. Peak flow reductions were estimated to dissipate beyond a total drainage area of 200 km 2 , approximately 2 km downstream of the small watershed outlet. A numerical tracer analysis identified the contribution of tile drainage to stream flow (QT/Q) which varied between 6 % and 71 % through an annual cycle. QT/Q responded directly to meteorological forcing. Precipitation driven events produced a strong positive logarithmic correlation between QT/Q and drainage area. The addition of precipitation into the system saturated near surface soils, increased lateral soil water v movement, and reduced the contribution of instream tile flow. A negative logarithmic trend in QT/Q to drainage area persisted in non-event durations. Simulated gradient terraces reduced and delayed peak flows in subcatchments of less than 3 km 2 of drainage area. The Hydrographs were shifted responding to rainfall later than non-terraced scenarios, while retaining the total volumetric outflow over longer time periods. The effects of dense terrace systems quickly dissipated, and found to be inconsequential at a drainage area of 45 km 2. Beyond the analysis of individual agricultural features, this work assembled a framework to analyze the feature at the field scale for implementation at the watershed scale. It showed large scale simulations reproduce field scale results well. The product of this work was, a systematic hydrologic characterization of distributed flood mitigation structures, pattern tile drainage, and terrace systems facilitating the simulation of each practices in a physically-based coupled surface-subsurface model.

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Currently the Iowa Flood Center (IFC) of the University of Iowa is working in conjunction with the Iowa Department of Natural Resources (IDNR) to create statewide floodplain maps. The IFC has set up a four year plan to construct flood inundation maps for 85 of the 99 counties within the state of Iowa, with the final goal of creating maps acceptable by FEMA. High resolution statewide LiDAR information provides a base dataset from which floodplain maps are produced. Stream centerline data is extracted from a DEM produced by the LiDAR dataset. The centerline information is used in both this project and as a replacement for the USGS NHD streamline for the state. Stream flow estimation for a range of annual exceedance discharges are produced through a USGS recommended combination of regional regression analysis weighted by gage influence. Water surface elevations are produced for each of the annual exceedance discharges through the use of a HEC-RAS one dimensional steady flow model. Flood boundaries are the final product created by HEC-GeoRAS though a comparison of a TIN produced from the water surface elevations and the ground surface DEM. Final FEMA acceptable DFIRM's are produce by the IDNR and submitted to FEMA for adoption into the NFIP. iv TABLE OF CONTENTS LIST OF TABLES .

Core Ideas Soil hydraulic properties were inverse modeled to in situ soil water content. The most appropriate soil property depths were identified. Best‐fit soil parameter depths compared well with characterized soil stratigraphy. Site‐specific monitoring and subsurface boundary conditions improved performance. Modeling of spatial and vertical variability in soil hydraulic properties is a pervasive dilemma in computational hydrology. In an effort to provide guidance in inverse modeling of soil hydraulic properties, this study (i) calibrated soil hydraulic properties, for different soil layer depths, to measured soil moisture, (ii) identified the best‐suited soil thickness through validation, and (iii) post‐validated the resulting best‐fit soil properties and layer depth to the observed soil stratigraphic conditions. Soil property depths were varied to identify the most important stratigraphic features in soil water modeling. Statistical and graphic goodness‐of‐fit measures indicated that calibration and validation simulations performed better at shallow depths and generally worsened with depth. A comparison of differences in modeled soil layering at two field sites reflected differences in the observed soil stratigraphic conditions. Comparison with in situ soil stratigraphy indicated the importance of soil horizon changes and human‐induced alterations to the near‐surface soils. These results indicate that soil moisture dynamics can be effectively modeled using basic soil input data and inverse methods. However, to improve model performance, a site‐specific field monitoring campaign is needed to properly account for the effects of soil stratigraphy and boundary conditions.

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