Impact of Using Spatially Distributed Soils Information on Flood Hydrograph Simulation with HEC-HMS

Hydrologic rainfall-runoff models employ numerical equations to simulate the soil absorption of rainfall and resulting runoff. A number of methods have been developed to model these processes, but the parameters used to define these methods can be difficult to directly measure due to the variable nature of soil properties. They often rely on estimation of hydraulic and hydrologic parameters and calibration to produce accurate results. A challenge with runoff method parameterization is the need for oversimplification using a lumped modeling approach. While distributed hydrologic modeling techniques are now available, distributed runoff methods are limited in use due to the tradition of lumped modeling and lack of widely available runoff parameter datasets. This study sought to define modeling parameters for three runoff methods based on physical soil data contained within the Soil Survey Geographic (SSURGO) database for lumped and distributed modeling approaches. These parameters were defined for 1-foot and 3-foot soil depths for estimating controlling influences on infiltration. The methods investigated are the Deficit and Constant method, the Green and Ampt method, and the SCS Curve Number method. The Salt Creek Basin located in southeast Nebraska was the pilot basin for this study. The basin was modeled using the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) software package. The model was adapted to the basin using ArcGIS and the HEC-GeoHMS extension. Three different precipitation events were modeled with the simulated runoff hydrographs at seven locations compared to the observed data to assess the model performance. Several trends in the quality of loss parameters were observed. First, Deficit and Constant and Green and Ampt runoff methods produced runoff hydrographs that closely matched observations. Second, distributed loss parameters for these two methods produced more accurate results than their lumped counterparts. Third, the shallower soil depth parameters produced marginally better hydrographs than their counterparts. Finally, the SCS Curve Number method was able to produce accurate peak flow and runoff volume estimates, but performed poorly with the hydrograph timing. Advisor: Ayse Kili

Incorporation of uncertainties in real-time catchment flood forecasting

Floods have become the most prevalent and costly natural hazards in the U.S. When preparing real-time flood forecasts for a catchment flood warning and preparedness system, consideration must be given to four sources of uncertainty -- natural, data, model parameters, and model structure. A general procedure has been developed for applying reliability analysis to evaluate the effects of the various sources of uncertainty on hydrologic models used for forecasting and prediction of catchment floods. Three reliability analysis methods -- Monte Carlo simulation, mean value and advanced first-order second moment analyses (MVFOSM and AFOSM, respectively) - - were applied to the rainfall -runoff modeling reliability problem. Comparison of these methods indicates that the AFOSM method is probably best suited to the rainfall-runoff modeling reliability problem with the MVFOSM showing some promise. The feasibility and utility of the reliability analysis procedure are shown for a case study employing as an example the HEC-1 and RORB rainfall-runoff watershed models to forecast flood events on the Vermilion River watershed at Pontiac, Illinois. The utility of the reliability analysis approach is demonstrated for four important hydrologic problems: 1) determination of forecast (or prediction) reliability, 2) determination of the flood level exceedance probability due to a current storm and development of "rules of thumb" for flood warning decision making considering this probabilistic information, 3) determination of the key sources of uncertainty influencing model forecast reliability, 4) selection of hydrologic models based on comparison of model forecast reliability. Central to this demonstration is the reliability analysis methods' ability to estimate the exceedance probability for any hydrologic target level of interest and, hence, to produce forecast cumulative density functions and probability distribution functions. For typical hydrologic modeling cases, reduction of the underlying modeling uncertainties is the key to obtaining useful, reliable forecasts. Furthermore, determination of the rainfall excess is the primary source of uncertainty, especially in the estimation of the temporal and areal rainfall distributions.U.S. Department of the InteriorU.S. Geological SurveyOpe

Potential of Spaceborne X & L-Band SAR-Data for Soil Moisture Mapping Using GIS and its Application to Hydrological Modelling: the Example of Gottleuba Catchment, Saxony / Germany

Hydrological modelling is a powerful tool for hydrologists and engineers involved in the planning and development of integrated approach for the management of water resources. With the recent advent of computational power and the growing availability of spatial data, RS and GIS technologies can augment to a great extent the conventional methods used in rainfall runoff studies; it is possible to accurately describe watershed characteristics in particularly when determining runoff response to rainfall input. The main objective of this study is to apply the potential of spaceborne SAR data for soil moisture retrieval in order to improve the spatial input parameters required for hydrological modelling. For the spatial database creation, high resolution 2 m aerial laser scanning Digital Terrain Model (DTM), soil map, and landuse map were used. Rainfall records were transformed into a runoff through hydrological parameterisation of the watershed and the river network using HEC-HMS software for rainfall runoff simulation. The Soil Conservation Services Curve Number (SCS-CN) and Soil Moisture Accounting (SMA) loss methods were selected to calculate the infiltration losses. In microwave remote sensing, the study of how the microwave interacts with the earth terrain has always been interesting in interpreting the satellite SAR images. In this research soil moisture was derived from two different types of Spaceborne SAR data; TerraSAR-X and ALOS PALSAR (L band). The developed integrated hydrological model was applied to the test site of the Gottleuba Catchment area which covers approximately 400 sqkm, located south of Pirna (Saxony, Germany). To validate the model historical precipitation data of the past ten years were performed. The validated model was further optimized using the extracted soil moisture from SAR data. The simulation results showed a reasonable match between the simulated and the observed hydrographs. Quantitatively the study concluded that based on SAR data, the model could be used as an expeditious tool of soil moisture mapping which required for hydrological modelling

Modeling of Soil Erosion and Sediment Transport

The Special Issue entitled “Modeling of Soil Erosion and Sediment Transport” focuses on the mathematical modeling of soil erosion caused by rainfall and runoff at a basin scale, as well as on the sediment transport in the streams of the basin. In concrete terms, the quantification of these phenomena by means of mathematical modeling and field measurements has been studied. The following mathematical models (software) were used, amongst others: AnnAGNPS, SWAT, SWAT-Twn, TUSLE, WRF-Hydro-Sed, CORINE, LCM-MUSLE, EROSION-3D, HEC-RAS, SRC, WA-ANN. The Special Issue contains 14 articles that can be classified into the following five categories: Category A: “Soil erosion and sediment transport modeling in basins”; Category B: “Inclusion of soil erosion control measures in soil erosion models”; Category C: “Soil erosion and sediment transport modeling in view of reservoir sedimentation”; Category D: “Field measurements of gully erosion”; Category E: “Stream sediment transport modeling”. Most studies presented in the Special Issue were applied to different basins in Europe, America, and Asia, and are the result of the cooperation between universities and/or research centers in different countries and continents, which constitutes an optimistic fact for the international scientific communication