ArcBASINS: a GIS model for the BASINS database

Center for Research in Water Resource

A prototype toolset for the ArcGIS Hydro Data Model

Center for Research in Water Resource

Benefits of GIS Application in Hydrological Modeling: A Brief Summary

During recent years, Geographic Information Systems (GIS) as a powerful tool have had a tremendous impact on research techniques in the realm of geography and spatial analysis. The integrative ability of GIS to capture, store, manipulate, analyze, manage, and finally present all types of geographical spatial data, has drawn many attentions to it. Water Resources Engineering as a interdisciplinary field requires modeling and analyzing data with different spatial resolutions. Therefore, GIS could definitely be utilized as a suitable tool for solving water resources problems from local to global scale. This paper tries to present the larger scheme of the benefits for the applications of GIS in water resources and hydrological modeling in particular. Certainly, within the few pages ahead only the surface is scratched and a more thorough and comprehensive review requires more time and effort. The fundamental reason for the need of integrating GIS and hydrological modeling is briefly discussed and different tools are introduced. Also, various examples of GIS application are presented to create a better understanding. Case studies such as the Wadi Madoneh Basin in Jordan, Kuronagi River in Japan and San Antonio River Basin in Central Texas, USA, are presented. The good agreement between the results from a fairly simple GIS model and observations in cases such as Kuronagi River and Wadi Madoneh is indicating a promising future for GIS application in hydrological modeling. Finally, the benefits of GIS utilization in the field are discussed and summarized

Flow and transport modeling in large river networks

textThe work presented in this dissertation discusses large scale flow and transport in river networks and investigates advantages and disadvantages of grid-based and vector-based river networks. This research uses the Mississippi River basin as a continental-case study and the Guadalupe and San Antonio rivers and Seine basin in France as regional-case studies. The first component of this research presents an extension of regional river flow modeling to the continental scale by using high resolution river data from NHDPlus dataset. This research discovers obstacles of flow computations for river a network with hundreds of thousands river segments in continental scales. An upscaling process is developed based on the vector-based river network to decrease the computational effort, and to reduce input file size. This research identifies drainage area as a key factor in the flow simulation, especially in a wet climate. The second component of this research presents an enhanced GIS framework for a steady-state riverine nitrogen transport modeling in the San Antonio and Guadalupe river network. Results show that the GIS framework can be applied to represent a spatial distribution of flow and total nitrogen in a large river network with thousands of connected river segment. However, time features of the GIS environment limit its applicability to large scale time-varied modeling. The third component shows a modeling regional flow and transport with consideration of stream-aquifer interactions at a regional scale at high resolution. The STICS- Eau-Dyssée combined system is implemented for entire seine basin to compute daily nitrate flux in the Seine grid river network. Results show that river-aquifer exchange has a significant impact on river flow and transport modeling in larger river networks.Civil, Architectural, and Environmental Engineerin

Modelling water discharge and nitrogen loads from drained agricultural land at field and watershed scale

This thesis examines water discharge and NO₃-N loads from drained agricultural land in southern Sweden by modelling at field and watershed scale. In the first stage of the work, the ability of DRAINMOD to simulate outflow in subsurface drains and that of DRAINMOD-N II to simulate NO₃-N loads in these drains was evaluated in field experiments. In addition, the ROSETTA pedotransfer model was used to estimate soil hydraulic properties required by DRAINMOD. In the second stage, DRAINMOD was integrated with Arc Hydro in a GIS framework (Arc Hydro-DRAINMOD) to simulate the hydrological response of an artificially drained watershed. DRAINMOD-N II and a temperature-dependent NO₃-N removal equation were also included in Arc Hydro-DRAINMOD to predict NO₃-N loading. Arc Hydro-DRAINMOD used a distributed modelling approach to aggregate the results of field-scale simulations, where the Arc Hydro data model described the drainage patterns in the watershed and connected the model simulations from fields through the stream network to the watershed outlet. GLUE methodology was applied to estimate uncertainties in the framework inputs. At field scale, monthly values of drain outflows simulated by DRAINMOD and NO₃-N loads simulated by DRAINMOD-N II showed good agreement with observed values. Good agreement was also found between observed and DRAINMOD-simulated drainage rates when ROSETTA-estimated Ks values were used as inputs in DRAINMOD. At watershed scale, temporal trend and magnitude of monthly measured discharge and NO₃-N loads were well predicted by Arc Hydro-DRAINMOD, which included uncertainty estimation using GLUE methodology. Sensitivity analysis showed that NO₃-N loads from the stream baseflow and N removal in the stream network processes had the most sensitive parameters. These results demonstrate the potential of DRAINMOD/DRAINMOD-N II and Arc Hydro-DRAINMOD for simulating hydrological and N processes in drained agricultural land at field and watershed scale. These models can contribute to improve water use efficiency in watersheds and to evaluate best management practices for preventing surface water and groundwater pollution

Modeling within a Digital Watershed Context

2008 S.C. Water Resources Conference - Addressing Water Challenges Facing the State and Regio

PrePro2004: a data model with pre and post-processor for HEC-HMS

This thesis presents the design concepts and development of an interface (Pre- Pro2004) utilizing geodatabases for the Hydrologic Modeling System (HMS) of the Hydrologic Engineering Center (HEC). HMS is a rainfall-runoff model which supports lumped-parameter as well as distributed-parameter based modeling. PrePro2004 uses the spatial-analysis as well as data handling capabilities of ArcGIS. The spatial data are processed to create input files for HMS. These input files and the output from HMS are stored in two geodatabases which were developed using data model concepts. The tools are provided to reproduce an HMS model from the data inside these geodatabases. The interface is developed based on the DataCentric approach which brings different hydrologic and hydraulic models together. This approach aims to attain a long-term goal of utilizing the same data for different hydrologic or hydraulic models with additional model specific requirements. Two case studies are presented to show the applications of the tools developed. The first case study details the creation of HMS input files for Salado Creek watershed with Digital Elevation Model as input. It includes the importation of an existing HMS model for Salado Creek watershed as Appendix C. The second case study details the creation of HMS input files for the Bull Creek watershed, with land use and soil type data as inputs. It describes the capabilities of tools developed in detail

Modelling flash flood using LiDAR and high resolution satellite imagery: a case study of West Creek, Toowoomba

Australia is one of the most heavily exposed countries in the world to different natural hazards, such as floods. In December 2010 and January 2011, large areas of the south and central Queensland were affected by flooding. On Monday 10th January 2011 heavy rains continued from 12:30 pm to 2:00 pm in the City of Toowoomba catchment area. Flash flooding occurred suddenly and unexpectedly making it difficult to prevent or predict before it occurred. This led to a rise in water levels in streets and roads, disrupting traffic and causing loss of life and properties. To reduce the effect of flood disasters and minimize the damages, flood inundation maps can be used to determine the locations of threat. This research used an integration of the HEC-Hydrologic Modelling System (HEC-HMS), HEC-River Analysis System (HEC-RAS) with Geographic Information Systems (GIS) to develop an improved model of the West Creek flood extent and flood event in the city of Toowoomba. The flood extent and depth in the different flow conditions of the West Creek channel was described in this study. The Hydrologic model (HEC-HMS) was used for 15 minutes time series data to create the flow rate at West Creek catchment from 12:00 pm to 4:00 pm. HEC-RAS with HEC-GeoRAS extension in ArcGIS was applied to simulate the flash flood in West Creek from Spring Street to Long Street. Digital Elevation Model (DEM) derived from high density LiDAR data and land cover data extracted from high resolution remote sensing imagery were used to model the flood inundation in the study area. The HEC-GeoRAS extension was used to prepare data sets for the stream centreline, banks, flow paths and cross-sections for import to the HEC-RAS hydraulic model. The downstream boundary conditions were defined in HEC-RAS. The hydrological results from HEC-HMS showed the maximum discharge value of West Creek Catchment at different periods of time. These results were comparable with Toowoomba Regional Council Report (TRCR). The flood inundation maps showed the maximum flood width and depth of West Creek Channel (starting from Spring Street and ending at Long Street) at 1:00 pm to 3:00 pm, which was greater than any previous floods in Toowoomba. The validation between the modelled flood extent at peak time and flood extent in the Nearmap aerial photo showed a high degree of correlation. Therefore, the model can provide a sound basis on which to analyse similar scenarios

Massive Spatiotemporal Watershed Hydrological Storm Event Response Model (MHSERM) with Time-Lapsed NEXRAD Radar Feed

Correctly and efficiently estimating hydrological responses corresponding to a specific storm event at the streams in a watershed is the main goal of any sound water resource management strategy. Methods for calculating a stream flow hydrograph at the selected streams typically require a great deal of spatial and temporal watershed data such as geomorphological data, soil survey, landcover, precipitation data, and stream network information to name a few. However, extracting and preprocessing such data for estimation and analysis is a hugely time-consuming task, especially for a watershed with hundreds of streams and lakes and complicated landcover and soil characteristics. To deal with the complexity, traditional models have to simplify the watershed and the streams network, use average values for each subcatchment, and then indirectly validate the model by adjusting the parameters through calibration and verification. To obviate such difficulties, and to better utilize the new, high precision spatial/temporal data, a new massive spatiotemporal watershed hydrological storm event response model (MHSERM) was developed and implemented on ESRI ArcMap platform. Different from other hydrological modeling systems, the MHSERM calculated the rainfall run off at a resolution of finer grids that reflects high precision spatial/temporal data characteristics of the watershed, not at conventional catchment or subcatchment scales, and that can simulate the variations of terrain, vegetation and soil far more accurately. The MHSERM provides a framework to utilize the USGS DEM and Landcover data, NRCS SSURGO and STATSGO soil data and National Hydrology Dataset (NHD) by handling millions of elements (grids) and thousands of streams in a real watershed and utilizing the Spatiotemporal NEXRAD precipitation data for each grid in pseudo real-time. Specifically, the MHSERM model has the following new functionalities: (1) Grid the watershed on the basis of high precision data like USGS DEM and Landcover data, NRCS SSURGO and STATSGO soil data, e.g., at a 30 meter by 30 meter resolution; (2) Delineate catchments based on the USGS National Digital Elevation Model (DEM) and the stream network data of the National Hydrography Dataset (NHD); (3) Establish the stream network and routing sequence for a watershed with hundreds of streams and lakes extracted from the National Hydrography Dataset (NHD) either in a supervised or unsupervised manner; (4) Utilize the NCDC NEXRAD precipitation data as spatial and temporal input, and extract the precipitation data for each grid; (5) Calculate the overland runoff volume, flow path and slope to the stream for each grid; (6) Dynamically estimates time of concentration to the stream for each interval, and only for the grids with rainfall excess, not for the whole catchment; (7) Deal with different hydrologic conditions (Good, Fair, Poor) for landcover data and different Antecedent Moisture Condition (AMC); (8) Process single or a series of storm events automatically; thus, the MHSERM model is capable of simulating both discrete and continuous storm events; (9) Calculate the temporal flow rate (i.e., hydrograph) for all the streams in the stream network within the watershed, save them to a database for further analysis and evaluation of various what-if scenarios and BMP designs. In MHSERM model, the SCS Curve number method is used for calculating overland flow runoff volume, and the Muskingum-Cunge method is used for flow routing of the stream network