E. James Nelson

Comparison of Lumped and Quasi-Distributed Clark Runoff Models Using the SCS Curve Number Equation

The Clark synthetic unit hydrograph and the Soil Conservation Service (SCS) curve number method has been used to simulate the rainfall and runoff behavior of a watershed for many years. Methodologies like Clark generally rely on the use of lumped or average rainfall and runoff parameters defined for the watershed, even though such parameters are spatially variable. In an attempt to leverage spatial parameters derived from geographic information, a modified Clark (ModClark) method or quasi-distributed model was developed for HEC-HMS. The ModClark method was initially developed to use the national network of WSR-88D radar (NEXRAD) rainfall data but few has been published on its application which is likely because of the difficulties in obtaining usable and reliable radar rainfall data and because of a lack of despisal preprocessing tools required to parameterize a ModClark simulation. While the original implementation and testing of the ModClark method required the use of NEXRAD data in specific formats, th...

Spatial averaging of land use and soil properties to develop the physically-based green and ampt parameters for HEC-1

Abstract The computer hydrologic model HEC-1, developed by the Hydrologic Engineering Center (HEC), has been used for many years by hydrologists and engineers to estimate surface water runoff caused by rainfall events. Besides the rainfall data itself, the most sensitive set of input parameters in a runoff model are the rainfall loss parameters. The SCS (NRCS) Curve Number approach is commonly used to compute rainfall losses. Another method available for computing rainfall losses in HEC-1 is the Green and Ampt approach. However, this method is used infrequently because of the difficulty in obtaining the soil data needed to derive the Green and Ampt parameters. The purpose of this study is to present an automated method of computing Green and Ampt parameters using digital soil and land use data. Studies were performed with data that compare this automated method with another non-automated method of computing Green and Ampt parameters. Parameters computed using the automated method were consistent with the parameters computed using the non-automated method. Furthermore, by taking advantage of Geographic Information System (GIS) overlay capabilities, significant time was saved in computing the Green and Ampt parameters.

A High-Resolution National-Scale Hydrologic Forecast System from a Global Ensemble Land Surface Model†

Abstract Warning systems with the ability to predict floods several days in advance have the potential to benefit tens of millions of people. Accordingly, large‐scale streamflow prediction systems such as the Advanced Hydrologic Prediction Service or the Global Flood Awareness System are limited to coarse resolutions. This article presents a method for routing global runoff ensemble forecasts and global historical runoff generated by the European Centre for Medium‐Range Weather Forecasts model using the Routing Application for Parallel computatIon of Discharge to produce high spatial resolution 15‐day stream forecasts, approximate recurrence intervals, and warning points at locations where streamflow is predicted to exceed the recurrence interval thresholds. The processing method involves distributing the computations using computer clusters to facilitate processing of large watersheds with high‐density stream networks. In addition, the Streamflow Prediction Tool web application was developed for visualizing analyzed results at both the regional level and at the reach level of high‐density stream networks. The application formed part of the base hydrologic forecasting service available to the National Flood Interoperability Experiment and can potentially transform the nations forecast ability by incorporating ensemble predictions at the nearly 2.7 million reaches of the National Hydrography Plus Version 2 Dataset into the national forecasting system.

Reducing elevation roundoff errors in digital elevation models

Abstract A smoothing algorithm is presented for the removal of roundoff error, inherent in almost all digital elevation data. Elevation adjustments are kept within the tolerance of roundoff error, so that the resulting terrain model is not over smoothed. After smoothing, the digital elevation model is more suitable for use with algorithms that seek to automatically delineate stream networks and basins of a watershed. The algorithm is specifically intended for use with gridded data, and is particularly effective when used with elevations originating from the 7.5 min quadrangles provided by the United States Geological Survey.

Reservoir water quality monitoring using remote sensing with seasonal models: case study of five central-Utah reservoirs

Abstract Remote sensing models estimate chlorophyll concentrations by correlating spectral reflectance and reservoir chlorophyll. Different algal populations have different spectral signatures and thus different correlation models, an issue typically addressed by developing and applying a model using the same satellite image. Here we exploit these population differences by developing seasonal models that can be applied to other images from that season. We rely on algal succession and assume the phytoplankton population is relatively constant over a season, dividing the growth season into 3 parts as substitutes for population measurements. We present seasonal models developed using data from 2 Utah reservoirs, Deer Creek and Jordanelle, which have comprehensive long-term field datasets large enough to provide adequate near-coincident data for model development. We then apply the chlorophyll-estimation models to 5 reservoirs in north-central Utah and present the trends in the average, maximum, and variance of the chlorophyll concentration for each reservoir over a nearly 40-year period. We present examples of chlorophyll distribution maps that show spatial patterns and discuss implications for field sampling design and analysis. We found that season-specific models perform well for satellite images from the same season but do not perform well against images from other seasons. We suggest that these models can be used with confidence in the season for which they were developed, allowing analysis of historical data and providing current information on reservoir conditions without accompanying field samples.

A GIS Approach to Watershed Modeling in Maricopa County, Arizona

Most conventional rainfall-runoff modeling methods are tedious and time-consuming. The Watershed Modeling System (WMS) is a comprehensive computer software application for watershed characterization and rainfall-runoff modeling in a graphical user interface environment. Through several GIS operations and tight integration with GIS databases, WMS enables hydrologists and water resource engineers to perform rainfall-runoff modeling more efficiently than conventional modeling methods. In this paper, methods of computing hydrologic parameters for the Flood Control District of Maricopa County are discussed, and demonstrated by applying them to the Gavilan Peak Watershed. This watershed is located in the vicinity of the community of New River in northern Maricopa County, Arizona.

Probabilistic Flood Inundation Forecasting Using Rating Curve Libraries

One approach for performing uncertainty assessment in flood inundation modeling is to use an ensemble of models with different conceptualizations, parameters, and initial and boundary conditions that capture the factors contributing to uncertainty. However, the high computational expense of many hydraulic models renders their use impractical for ensemble forecasting. To address this challenge, we developed a rating curve library method for flood inundation forecasting. This method involves pre-running a hydraulic model using multiple inflows and extracting rating curves, which prescribe a relation between streamflow and stage at various cross sections along a river reach. For a given streamflow, flood stage at each cross section is interpolated from the pre-computed rating curve library to delineate flood inundation depths and extents at a lower computational cost. In this article, we describe the workflow for our rating curve library method and the Rating Curve based Automatic Flood Forecasting (RCAFF) software that automates this workflow. We also investigate the feasibility of using this method to transform ensemble streamflow forecasts into local, probabilistic flood inundation delineations for the Onion and Shoal Creeks in Austin, Texas. While our results show water surface elevations from RCAFF are comparable to those from the hydraulic models, the ensemble streamflow forecasts used as inputs to RCAFF are the largest source of uncertainty in predicting observed floods. (KEY TERMS: ensemble flood forecasting; flood inundation modeling; hydraulic modeling; probabilistic flood inundation maps; rating curves.) Buahin, Caleb A., Nikhil Sangwan, Cassandra Fagan, David R. Maidment, Jeffery S. Horsburgh, E. James Nelson, Venkatesh Merwade, and Curtis Rae, 2017. Probabilistic Flood Inundation Forecasting Using Rating Curve Libraries. Journal of the American Water Resources Association (JAWRA) 53(2):300-315. DOI: 10.1111/ 1752-1688.12500

From Global to Local: Providing Actionable Flood Forecast Information in a Cloud-Based Computing Environment†

Global and continental scale flood forecast provide coarse resolution flood forecast, but from the perspective of emergency management, flood warnings should be detailed and specific to local conditions. The desired refinement can be provided by the use of downscaling global scale models and through the use of distributed hydrologic models to produce a high-resolution flood forecast. Three major challenges associated with transforming global flood forecasting to a local scale are addressed in this work. The first is using open-source software tools to provide access to multiple data sources and lowering the barriers for users in management agencies at local level. This can be done through the Tethys Platform that enables web water resources modeling applications. The second is finding a practical solution for the computational requirements associated with running complex models and performing multiple simulations. This is done using Tethys Cluster that manages distributed and cloud computing resources as a companion to the Tethys Platform for web app development. The third challenge is discovering ways to downscale the forecasts from the global extent to the local context. Three modeling strategies have been tested to address this, including downscaling of coarse resolution global runoff models to high-resolution stream networks and routing with Routing Application for Parallel computatIon of Discharge (RAPID), the use of hierarchical Gridded Surface and Subsurface Hydrologic Analysis (GSSHA) distributed models, and pre-computed distributed GSSHA models.

Numerical Modeling of Culvert Hydraulics: Modernization of Existing HY8 Software

Several software programs have been developed to assist in the hydraulic design and analysis of culverts. Of the available programs, HY8 is the most widely used and distributed. The first version of HY8 was provided by the Federal Highway Administration (FHWA) for distribution in the 1980s. Since that time, understanding of culvert hydraulics has increased significantly and acceptable modeling techniques have been further developed. Computer capabilities have also advanced to facilitate better graphical displays and post processing options. As a result, modernization of HY8 is timely. This paper will provide a brief overview of the existing HY8 software in order to understand its capabilities and limitations. Further, the need for and status of an updated version of HY8 will be presented, including a comparison of the old and new HY8 interfaces.

Cyberinfrastructure and Web Apps for Managing and Disseminating the National Water Model

Hydrologic modeling can be used to provide warnings before, and to support operations during and after floods. Recent technological advances have increased our ability to create hydrologic models over large areas. In the United States (U.S.), a new National Water Model (NWM) that generates hydrologic variables at a national scale was released in August 2016. This model represents a substantial step forward in our ability to predict hydrologic events in a consistent fashion across the entire U.S. Nevertheless, for these hydrologic results to be effectively communicated, they need to be put in context and be presented in a way that is straightforward and facilitates management-related decisions. The large amounts of data produced by the NWM present one of the major challenges to fulfill this goal. We created a cyberinfrastructure to store NWM results, “accessibility” web applications to retrieve NWM results, and a REST API to access NWM results programmatically. To demonstrate the utility of this cyberinfrastructure, we created additional web apps that illustrate how to use our REST API and communicate hydrologic forecasts with the aid of dynamic flood maps. This work offers a starting point for the development of a more comprehensive toolset to validate the NWM while also improving the ability to access and visualize NWM forecasts, and develop additional national-scale-derived products such as flood maps. (KEY TERMS: data management; cyberinfrastructure; hydrologic modeling; data visualization; flooding; decision support systems.) Souffront Alcantara, Michael A., Christian Kesler, Michael J. Stealey, E. James Nelson, Daniel P. Ames, and Norm L. Jones, 2018. Cyberinfrastructure and Web Apps for Managing and Disseminating the National Water Model. Journal of the American Water Resources Association (JAWRA) 54 (4): 859–871. https://doi.org/10.1111/ 1752-1688.12608