Hydroinformatics On The Cloud: Data Integration, Modeling And Information Communication For Flood Risk Management

The Iowa Flood Information System (IFIS) is a web-based platform developed by the Iowa Flood Center (IFC) to provide access to flood inundation maps, real-time flood conditions, flood warnings and forecasts, flood-related data, information and interactive visualizations for communities in Iowa. The key elements of the IFIS are: (1) flood inundation maps, (2) autonomous “bridge sensors” that monitor water level in streams and rivers in real time, and (3) real-time flood forecasting models capable of providing flood warning to over 1000 communities in Iowa. The IFIS represents a hybrid of file and compute servers, including a High Performance Computing cluster, codes in different languages, data streams and web services, databases, scripts and visualizations. The IFIS processes raw data (50GB/day) from NEXRAD radars, creates rainfall maps (3GB/day) every 5 minutes, and integrates real-time data from over 600 sensors in Iowa. Even though the IFIS serves over 75,000 users in Iowa using local infrastructure, cloud computing can improve scalability, speed, cost efficiency, accessibility, security, resiliency and uptime. In this collaborative study between the Iowa Flood Center and the Nimbus team at the Argonne National Laboratory, we have analyzed feasibility and price/performance measures of moving the MPI-based computations to the cloud as well as assessment of response times from our interactive web-based system. Moving the system to the cloud, and making it independent and portable, would enable us to share our model easily with the flood research community. This presentation provides an overview of the tools and interfaces in the IFIS, and transition of the IFIS from a local infrastructure to cloud computing environment

Comprehensive Evaluation Of The IFloodS Radar Rainfall Products For Hydrologic Applications

This study describes the generation and testing of a reference rainfall product created from field campaign datasets collected during the NASA Global Precipitation Measurement (GPM) mission Ground Validation Iowa Flood Studies (IFloodS) experiment. The study evaluates ground-based radar rainfall (RR) products acquired during IFloodS in the context of building the reference rainfall product. The purpose of IFloodS was not only to attain a high-quality ground-based reference for the validation of satellite rainfall estimates but also to enhance understanding of flood-related rainfall processes and the predictability of flood forecasting. We assessed the six RR estimates (IFC, Q2, CSU-DP, NWS-DP, Stage IV, and Q2-Corrected) using data from rain gauge and disdrometer networks that were located in the broader field campaign area of central and northeastern Iowa. We performed the analyses with respect to time scales ranging from 1 h to the entire campaign period in order to compare the capabilities of each RR product and to characterize the error structure at scales that are frequently used in hydrologic applications. The evaluation results show that the Stage IV estimates perform superior to other estimates, demonstrating the need for gauge-based bias corrections of radar-only products. This correction should account for each product\u27s algorithm-dependent error structure that can be used to build unbiased rainfall products for the campaign reference. We characterized the statistical error structures (e.g., systematic and random components) of each RR estimate and used them for the generation of a campaign reference rainfall product. To assess the hydrologic utility of the reference product, we performed hydrologic simulations driven by the reference product over the Turkey River basin. The comparison of hydrologic simulation results demonstrates that the campaign reference product performs better than Stage IV in streamflow generation

Real-time Flood Forecasting And Information System For The State Of Iowa

Iowa Flood Center\u27s automated real-time flood forecasting and information system serves as a complement to the National Water Center\u27s proposed national system

Towards better utilization of NEXRAD data in hydrology: An overview of hydro-NEXRAD

With a very modest investment in computer hardware and the open-source local data manger (LDM) software from UCAR\u27s Unidata Program Center, an individual researcher can receive a variety of NEXRAD Level III gridded rainfall products, and the unprocessed Level II data in real-time from most NEXRAD radars. Additionally, the National Climatic Data Center has vast archives of these products and Level II data. Still, significant obstacles remain in order to unlock the full potential of the data. One set of obstacles is related to effective management of multi-terabyte data sets: storing, compressing, and backing up. A second set of obstacles, for hydrologists and hydrometeorologists in particular, is that the NEXRAD Level III products are not well suited for application in hydrology. There is a strong need for the generation of high-quality products directly from the Level II data with well-documented steps that include quality control, removal of false echoes, rainfall estimation algorithms with variety of corrections, coordinate conversion and georeferencing, conversion to a convenient data format(s), and integration with GIS. For hydrologists it is imperative that these procedures are basin-centered as opposed to radar-centered. Thirdly, the amount of data present in a multi-year, multi-radar dataset is such that simple cataloging and indexing of the data is not sufficient. Rather, sophisticated metadata extraction and management techniques are required. The authors describe and discuss the Hydro-NEXRAD software system that addresses the above three challenges. With support from the National Science Foundation through its ITR program, the authors are developing a basin-centered framework for addressing all these issues in a comprehensive manner, tailored specifically for use of NEXRAD data in hydrology and hydrometeorology. Through a flexible web interface users can search a large metadata database base, managed by a relational database, for subsets of interest. Well-chosen and documented defaults are provided for the flow from unprocessed NEXRAD data to basin-centered rainfall estimates at a desired space-time resolution. In addition to the web interface, there are web services that provide access to scripts and compiled programs. © 2007 ASCE

North Atlantic Tropical Cyclones and U.S. Flooding

Riverine flooding associated with North Atlantic tropical cyclones (TCs) is responsible for large societal and economic impacts. The effects of TC flooding are not limited to the coastal regions, but affect large areas away from the coast, and often away from the center of the storm. Despite these important repercussions, inland TC flooding has received relatively little attention in the scientific literature, although there has been growing media attention following Hurricanes Irene (2011) and Sandy (2012). Based on discharge data from 1981 to 2011, the authors provide a climatological view of inland flooding associated with TCs, leveraging the wealth of discharge measurements collected, archived, and disseminated by the U.S. Geological Survey (USGS). Florida and the eastern seaboard of the United States (from South Carolina to Maine and Vermont) are the areas that are the most susceptible to TC flooding, with typical TC flood peaks that are 2 to 6 times larger than the local 10-yr flood peak, causing major flooding. A secondary swath of extensive TC-induced flooding in the central United States is also identified. These results indicate that flooding from TCs is not solely a coastal phenomenon but affects much larger areas of the United States, as far inland as Illinois, Wisconsin, and Michigan. Moreover, the authors highlight the dependence of the frequency and magnitude of TC flood peaks on large-scale climate indices, and the role played by the North Atlantic Oscillation and the El Niño–Southern Oscillation phenomenon (ENSO), suggesting potential sources of extended-range predictability.</jats:p

Towards Better Utilization of NEXRAD Data in Hydrology: An Overview of Hydro-NEXRAD

With a very modest investment in computer hardware and the open-source local data manager (LDM) software from University Corporation for Atmospheric Research (UCAR) Unidata Program Center, a researcher can receive a variety of NEXRAD Level III rainfall products and the unprocessed Level II data in real-time from most NEXRAD radars in the USA. Alternatively, one can receive such data from the National Climatic Data Center in Ashville, NC. Still, significant obstacles remain in order to unlock the full potential of the data. One set of obstacles is related to effective management of multi-terabyte datasets. A second set of obstacles, for hydrologists and hydrometeorologists in particular, is that the NEXRAD Level III products are not well suited for applications in hydrology. There is a strong need for the generation of high-quality products directly from the Level II data with well-documented steps that include quality control, removal of false echoes, rainfall estimation algorithms, coordinate conversion, georeferencing and integration with GIS. For hydrologists it is imperative that these procedures are basin-centered as opposed to radar-centered. The authors describe the Hydro-NEXRAD system that addresses the above challenges. With support from the National Science Foundation through its ITR program, the authors have developed a basin-centered framework for addressing all these issues in a comprehensive manner, tailored specifically for use of NEXRAD data in hydrology and hydrometeorology. © IWA Publishing 2011

Deployment and Performance Analyses of High-Resolution Iowa XPOL Radar System during the NASA IFloodS Campaign

This article presents the data collected and analyzed using the University of Iowa's X-band polarimetric (XPOL) radars that were part of the spring 2013 hydrology-oriented Iowa Flood Studies (IFloodS) field campaign, sponsored by NASA's Global Precipitation Measurement (GPM) Ground Validation (GV) program. The four mobile radars have full scanning capabilities that provide quantitative estimation of the rainfall at high temporal and spatial resolutions over experimental watersheds. IFloodS was the first extensive test of the XPOL radars, and the XPOL radars demonstrated their field worthiness during this campaign with 46 days of nearly uninterrupted, remotely monitored, and controlled operations. This paper presents detailed postcampaign analyses of the high-resolution, research-quality data that the XPOL radars collected. The XPOL dual-polarimetric products and rainfall are compared with data from other instruments for selected diverse meteorological events at high spatiotemporal resolutions from unprecedentedly unique and vast data generated during IFloodS operations. The XPOL data exhibit a detailed, complex structure of precipitation viewed at multiple range resolutions (75 and 30 m). The inter-XPOL comparisons within an overlapping scanned domain demonstrate consistency across different XPOL units. The XPOLs employed a series of heterogeneous scans and obtained estimates of the meteorological echoes up to a range oversampling of 7.5 m. A finer-resolution (30 m) algorithm is described to correct the polarimetric estimates for attenuation at the X band and obtain agreement of attenuation-corrected products with disdrometers and NASA S-band polarimetric (NPOL) radar. The paper includes hardware characterization of Iowa XPOL radars conducted prior to the deployment in IFloodS following the GPM calibration protocol