Venkatesh Merwade

GIS techniques for creating river terrain models for hydrodynamic modeling and flood inundation mapping

Two- and three-dimensional (2D/3D) hydrodynamic models require the geometric description of river bathymetry and its surrounding area as a continuous surface. These surface representations of river systems are also required in mapping flood inundation extents. Creating surface representations of river systems is a challenging task because of issues associated with interpolating river bathymetry, and then integrating this bathymetry with surrounding topography. The objectives of this paper are to highlight key issues associated with creating an integrated river terrain, and propose GIS techniques to overcome these issues. The following techniques are presented in this paper: mapping and analyzing river channel data in a channel fitted coordinate system; interpolation of river cross-sections to create a 3D mesh for main channel; and integration of interpolated 3D mesh with surrounding topography. These techniques are applied and cross-validated by using datasets from Brazos River in Texas, Kootenai River in Montana, and Strouds Creek in North Carolina. Creation of a 3D mesh for the main channel using a channel-fitted coordinate system and subsequent integration with surrounding topography produces a coherent river terrain model, which can be used for 2D/3D hydrodynamic modeling and flood inundation mapping. Although techniques presented in this paper produce better results compared to existing GIS methods, the linear approach has some limitations which can be overcome by accounting for channel meanders, sinuosity and thalweg location.

Evaluation of Temperature and Precipitation Trends and Long-Term Persistence in CMIP5 Twentieth-Century Climate Simulations

AbstractThe authors have analyzed twentieth-century temperature and precipitation trends and long-term persistence from 19 climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). This study is focused on continental areas (60°S–60°N) during 1930–2004 to ensure higher reliability in the observations. A nonparametric trend detection method is employed, and long-term persistence is quantified using the Hurst coefficient, taken from the hydrology literature. The authors found that the multimodel ensemble–mean global land–average temperature trend (0.07°C decade−1) captures the corresponding observed trend well (0.08°C decade−1). Globally, precipitation trends are distributed (spatially) at about zero in both the models and in the observations. There are large uncertainties in the simulation of regional-/local-scale temperature and precipitation trends. The models’ relative performances are different for temperature and precipitation trends. The models capture the long-ter...

The effect of land cover change on duration and severity of high and low flows

Land cover has been increasingly recognized as an important factor affecting hydrologic processes at the basin and regional level. Therefore, improved understanding of how land cover change affects hydrologic systems is needed for better management of water resources. The objective of this study is to investigate the effects of land cover change on the duration and severity of high and low flows by using the Soil Water Assessment Tool (SWAT) model, Bayesian Model Averaging (BMA) and copulas. Two basins dominated by different land cover in the Ohio River basin are used as study area in this study. Two historic land covers from the 1950s and 1990s are considered as input to the SWAT model, thereby investigating the hydrologic high and low flow response of different land cover conditions of these two basins. The relationships between the duration and severity of both low and high flow are defined by applying the copula method; changes in the frequency of the duration and severity are investigated. The results show that land cover changes affect both the duration and severity of both high and low flows. An increase in forest area leads to a decrease in the duration and severity during both high and low flows, but its impact is highest during extreme flows. The results also show that the land cover changes have had significant influences on changes in the joint return periods of duration and severity of low and high flows. While this study sheds light on the role of land cover change on severity and duration of high and low flow conditions, more studies using various land cover conditions and climate types are required in order to draw more reliable conclusions in future. This article is protected by copyright. All rights reserved.

A Faster and Economical Approach to Floodplain Mapping Using Soil Information

Flood inundation maps play a key role in assessment and mitigation of potential flood hazards. However, owing to high costs associated with the conventional flood mapping methods, many communities in the United States lack flood inundation maps. The objective of this study is to develop and examine an economical alternative approach to floodplain mapping using widely available soil survey geographic (SSURGO) database. In this study, floodplain maps are developed for the entire state of Indiana, and some counties in Minnesota, Wisconsin, and Washington states by identifying flood-prone soil map units based on their attributes. For validation, the flood extents obtained from SSURGO database are compared with the extents from other floodplain maps such as the Federal Emergency Management Agency issued flood insurance rate maps (FIRMs), flood extents observed during past floods, and flood maps derived using digital elevation models. In general, SSURGO-based floodplain maps (SFMs) are largely in agreement with other flood inundation maps. Specifically, the floodplain extents from SFMs cover 78-95% area compared to FIRMs and observed flood extents. Thus, albeit with a slight loss in accuracy, the SSURGO approach offers an economical and fast alternative for floodplain mapping. In particular, it has potentially high utility in areas where no detailed flood studies have been conducted.

Incorporating Surface Storage and Slope to Estimate Clark Unit Hydrographs for Ungauged Indiana Watersheds

Application of Soil Conservation Service’s (SCS) dimensionless unit hydrograph method for ungauged basins in Indiana yields very high peak flows and short time to peaks for the northern region, thus producing unrealistic flow estimates for design purposes. It is hypothesized that the overestimation of peak flows in northern region using SCS method is due to the flat terrain and high surface storage caused by the Wiconsinan glaciations. To incorporate the slope and storage characteristics, the application of Clark synthetic unit hydrograph (SUH), which incorporates time of concentration ( tc ) and a storage parameter (R) to produce runoff hydrograph, is explored for Indiana. A statistical analysis of 29 geomorphic attributes and past storm hydrographs for thirty watersheds in Indiana show that watersheds in north, central and southern regions are statistically different in terms of slope and storage characteristics. A statistical comparison of Clark parameters ( R and tc ) estimated for past storm events a...

Role of Watershed Geomorphic Characteristics on Flooding in Indiana, United States

AbstractDespite the documented evidence of geomorphic characteristics on flooding, an understanding of the relative effects of the geomorphic characteristics on flooding remains elusive. The objective of this study is to investigate the relationship between flooding and geomorphic characteristics in Indiana, United States, by using data at 94 streamflow gauging stations. The flood magnitude as determined through the flash flood index is categorized into three groups, including moderate, extreme, and severe. The flood in each group is then related to geomorphic characteristics, including topography, morphometry, slope, land use, soil, channel network, and aspect through stepwise regression. Results show that extreme flooding is most affected by watershed morphometry, particularly watershed length, whereas severe flooding is most affected by watershed slope and land use type. The methodology used in this study also highlights that the stronger the severity of flooding, the more it is explained by geomorphic...

Spatiotemporal Evaluation of Simulated Evapotranspiration and Streamflow over Texas Using the WRF-Hydro-RAPID Modeling Framework

This study assesses a large-scale hydrologic modeling framework (WRF-Hydro-RAPID) in terms of its high-resolution simulation of evapotranspiration (ET) and streamflow over Texas (drainage area: 464,135 km). The reference observations used include eight-day ET data from MODIS and FLUXNET, and daily river discharge data from 271 U.S. Geological Survey gauges located across a climate gradient. A recursive digital filter is applied to decompose the river discharge into surface runoff and base flow for comparison with the model counterparts. While the routing component of the model is pre-calibrated, the land component is uncalibrated. Results show the model performance for ET and runoff is aridity-dependent. ET is better predicted in a wet year than in a dry year. Streamflow is better predicted in wet regions with the highest efficiency ~0.7. In comparison, streamflow is most poorly predicted in dry regions with a large positive bias. Modeled ET bias is more strongly correlated with the base flow bias than surface runoff bias. These results complement previous evaluations by incorporating more spatial details. They also help identify potential processes for future model improvements. Indeed, improving the dry region streamflow simulation would require synergistic enhancements of ET, soil moisture and groundwater parameterizations in the current model configuration. Our assessments are important preliminary steps towards accurate large-scale hydrologic forecasts. (KEY TERMS: evapotranspiration; streamflow; surface runoff; base flow; MODIS; WRF-Hydro; Noah-MP; RAPID.) Lin, Peirong, Mohammad Adnan Rajib, Zong-Liang Yang, Marcelo Somos-Valenzuela, Venkatesh Merwade, David R. Maidment, Yan Wang, and Li Chen, 2018. Spatiotemporal Evaluation of Simulated Evapotranspiration and Streamflow over Texas Using the WRF-Hydro-RAPID Modeling Framework. Journal of the American Water Resources Association (JAWRA) 54(1): 40-54. https://doi.org/10.1111/1752-1688.12585

A GIS-based relational data model for multi-dimensional representation of river hydrodynamics and morphodynamics

The emerging capabilities of the geo-based information systems to integrate spatial and temporal attributes of in-situ measurements is a long-waited solution to efficiently organize, visualize, and analyze the vast amount of data produced by the new generations of river instruments. This paper describes the construct of a river data model linked to a relational database that can be populated with both measured and simulated river data to facilitate descriptions of river features and processes using hydraulic/hydrologic terminology. The proposed model, labeled Arc River, is built in close connection with the existing Arc Hydro data model developed for water-related features to ensure the connection of the river characteristics with their floodplains and watersheds. This paper illustrates Arc River data model capabilities in conjunction with Acoustic Doppler Current Profiler measurements to demonstrate that essential river morphodynamics and hydrodynamics aspects can be described using data on the flow and its boundaries. Represent river data in a curvilinear coordinate system to support river channel oriented spatial analyses.Represent multidimensional river features through points, lines, polygons, and volumes.Represent simulated gridded data for river channels that can be readily coupled with observed data.Represent spatio-temporal evolution of dynamic river objects using Eulerian or Lagrangian observational frameworks.Efficiently store and retrieve data acquired in-situ along with the ancillary metadata.

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

Bring integrated GIS data and modeling capabilities into HUBzero platform

The rapid advancement in the collection of environmental data, geospatial analysis and modeling software calls for new GIS-enabled cyberinfrastructure (CI) capable of support large scale integrated data and modeling activities. Although the HUBzero platform is gaining popularity as a portal development framework for many science and engineering communities, it has limited success in earth and environmental science domains, mainly due to its lack of native support for large geospatial data management and GIS functionalities in the Rappture toolkit. In this paper, we describe our initial work on bringing integrated GIS data and modeling capabilities into the HUBzero platform. We describe the overall architecture of our CI solution which is scalable, extensible and portable to other gateway framework as well. Two prototype applications are presented as a proof-of-concept. Coupling the scalable GIS capabilities with a wealth of tools for user participation and community building on the HUBzero platform, we hope to help new science communities in utilizing this platform.