Hydrological Alteration Index as an Indicator of the Calibration Complexity of Water Quantity and Quality Modeling in the Context of Global Change

Modeling is a useful way to understand human and climate change impacts on the water resources of agricultural watersheds. Calibration and validation methodologies are crucial in forecasting assessments. This study explores the best calibration methodology depending on the level of hydrological alteration due to human-derived stressors. The Soil and Water Assessment Tool (SWAT) model is used to evaluate hydrology in South-West Europe in a context of intensive agriculture and water scarcity. The Index of Hydrological Alteration (IHA) is calculated using discharge observation data. A comparison of two SWAT calibration methodologies are done; a conventional calibration (CC) based on recorded in-stream water quality and quantity and an additional calibration (AC) adding crop managements practices. Even if the water quality and quantity trends are similar between CC and AC, water balance, irrigation and crop yields are different. In the context of rainfall decrease, water yield decreases in both CC and AC, while crop productions present opposite trends (+33% in CC and -31% in AC). Hydrological performance between CC and AC is correlated to IHA: When the level of IHA is under 80%, AC methodology is necessary. The combination of both calibrations appears essential to better constrain the model and to forecast the impact of climate change or anthropogenic influences on water resources

Continental-scale high-resolution river geometry and real-time inundation mapping

Flooding is the most threatening natural disaster worldwide considering the fatalities and property damage it causes. Recent flood disasters have raised concerns for accurate and responsive inundation forecast due to the rapid spread and astonishing destructive power of these events. Although recent development in large scale hydrologic simulation has enabled the real-time streamflow simulation operating on millions of river reaches, a framework for converting the forecast discharge into corresponding water surface elevation and inundation maps at a continental-scale is absent to better support local flood response. To accurately map flood inundation extent, a comprehensive description of the geometry of the channel is indispensable. As such, this dissertation presents an innovative approach for estimating river geometry and conducting inundation mapping at a continental-scale with a high spatial resolution. This approach is based on the concept of Height Above Nearest Drainage (HAND). Advanced hydrologic terrain analysis workflows have been designed to derive channel hydraulic properties, stage-discharge rating curves, and inundation extents using HAND. After the mechanism being presented, the implementation of this approach across the contiguous United States has been demonstrated using the 10-meter National Elevation Dataset. The integrity of the outputs has been validated through the comparison with best available references at multiple test sites. Considering the increasingly availability of high-resolution topographic data derived from lidar technology, the dissertation further presents how advanced geomorphic feature extraction tools are integrated into the proposed approach to overcome the challenges associated with the enrichment of terrain details. At last, this dissertation presents how banklines, an essential piece of river geometry characteristic as the boundary differentiates channel zone from floodplain, is detected with enhanced geomorphic feature extraction tools for improving large-scale hydrologic simulation and inundation mapping accuracy.Civil, Architectural, and Environmental Engineerin

On the application of dynamical measures of hydrologic response to prediction and similarity assessment in watersheds

The Prediction in Ungauged Basins (PUB) initiative set out to improve the understanding of hydrological processes with an aim of improving hydrologic models for application in ungauged basins. With a majority of basins around the world essentially ungauged, this suggests the need to shift from calibration-based models that rely on observed streamflow data to models based on process understanding. This is especially important in natural infrastructure planning projects such as investments in the conservation of wetlands across the watershed, where the lack of streamflow data hinders the quantification of their benefits (such as flood attenuation), resulting in a difficulty in prioritization. This research sought to contribute to this growing body of literature by (a) developing visual tools and metrics for assessing flow dynamics and flood attenuation benefits of wetlands in relation to their position in the watershed, (b) examining distribution-based topographic metrics in regard to their efficacy in predicting hydrologic response and providing a methodology for examining other metrics in future studies, (c) building robust functional forms for two important catchment metrics: the width function and hypsometric curve, and (d) devising a hierarchical clustering approach to assess hydrological similarity and find analogous basins that is computationally efficient and has a potential for large-scale applications. Taken together, this study paves the way toward an analytical formulation of the geomorphological instantaneous unit hydrograph (GIUH) that can be used to assess the hydrological behavior in ungauged or data-scarce basins

Topography data harmonisation and uncertainties applying SRTM, laser scanner and cartographic elevation models

International audienceOnly a few studies have attempted to quantify topography-depending water fluxes, to evaluate retention and reservoir capacities and surface run-off paths within large river basins because data availability and data quality are critical issues to face this objective. It becomes most relevant if water balance has to be calculated in large or transboundary river basins. The advance of space based earth observation data offers a solution to this information problem. Therefore, this paper mainly focuses on weaknesses and strengths analyzing topography with SRTM (Shuttle Radar Topography Mission) digital height data and thus provides techniques for their improved application in river network derivation, floodplain analysis, watershed hydrology in large as well as in large river basins (>1000 km2). In the analysis different types of digital elevation models (DEM), terrain models (DTM) and land cover classification data (biotope map, Corine Land Cover 1994) have been used. The DHMs are generated from Airborne Laser Scanning (0.5 m), topographic maps (10.0/50.0 m) and SRTM at 30.0 m and 90.0 m spatial resolution. SRTM digital height models are generated by Synthetic Aperture Radar (SAR) and show a high spatial variance in urban areas, regions of dense vegetation canopy, floodplains and water bodies. As study area serve the Elbe basin (Czech Republic, Germany) with its sub-basins and the Saale river basin (Germany, different federal countries Saxony-Anhalt, Saxony and Thuringia)

Geo-Spatial Analysis in Hydrology

Geo-spatial analysis has become an essential component of hydrological studies to process and examine geo-spatial data such as hydrological variables (e.g., precipitation and discharge) and basin characteristics (e.g., DEM and land use land cover). The advancement of the data acquisition technique helps accumulate geo-spatial data with more extensive spatial coverage than traditional in-situ observations. The development of geo-spatial analytic methods is beneficial for the processing and analysis of multi-source data in a more efficient and reliable way for a variety of research and practical issues in hydrology. This book is a collection of the articles of a published Special Issue Geo-Spatial Analysis in Hydrology in the journal ISPRS International Journal of Geo-Information. The topics of the articles range from the improvement of geo-spatial analytic methods to the applications of geo-spatial analysis in emerging hydrological issues. The results of these articles show that traditional hydrological/hydraulic models coupled with geo-spatial techniques are a way to make streamflow simulations more efficient and reliable for flood-related decision making. Geo-spatial analysis based on more advanced methods and data is a reliable resolution to obtain high-resolution information for hydrological studies at fine spatial scale

Analysis of the behavior of three digital elevation model correction methods on critical natural scenarios

Abstract Study region The methods explored in this study were tested in two study areas: Italy and Cuba. Study focus Virtually all Digital Elevation Models (DEM) contain flat areas or depression pixels that may be artifacts or actual landscape representations. These features must be removed before any further hydrological application can proceed. Diverse algorithms have been developed for the purpose of correcting these aspects, differing in how they handle the nature of the depressions, as well as the adopted mathematical procedures. In the present work, the behavior of a standard ( Fill ) and two advanced ( TOPAZ and PEM4PIT ) DEM correction methods on three critical natural scenarios is analyzed. Extensive flat areas, abrupt slope changes and large depressions − expressed in terms of: (1) geomorphological changes (elevation, affected area and slope); (2) flow velocity; (3) river network and width functions (WF) − are affected. New hydrological insights for the region Results confirm improved performance of the advanced methods over the standard method for each case study in Italy and Cuba. The analyzed parameters also show that correction processes are strongly influenced by the relief, the size of the predominating depressions and the neighbouring depressions. There is no one method among those compared which works optimally for every type of correction, and given that the majority of basins have diverse topographical conditions, a different approach to the corrections process and its computational procedures is likely needed

A multi-scale method to assess pesticide contamination risks in agricultural watersheds

The protection of water is now a major priority for environmental managers, especially around drinkingpumping stations. In view of the new challenges facing water agencies, we developed a method designedto support their public policy decision-making, at a variety of different spatial scales. In this paper, wepresent this new spatial method, using remote sensing and a GIS, designed to determine the contami-nation risk due to agricultural inputs, such as pesticides. The originality of this method lies in the useof a very detailed spatial object, the RSO (Reference Spatial Object), which can be aggregated to manyworking and managing scales. This has been achieved thanks to the pixel size of the remote sensing, witha grid resolution of 30 m × 30 m in our application.The method – called PHYTOPIXAL – is based on a combination of indicators relating to the environmen-tal vulnerability of the surface water environment (slope, soil type and distance to the stream) and theagricultural pressure (land use and practices of the farmers). The combination of these indicators for eachpixel provides the contamination risk. The scoring of variables was implemented according knowledgein literature and of experts.This method is used to target specific agricultural input transfer risks. The risk values are first calculatedfor each pixel. After this initial calculation, the data are then aggregated for decision makers, accordingto the most suitable levels of organisation. These data are based on an average value for the watershedareas.In this paper we detail an application of the method to an area in the hills of Southwest France. Weshow the pesticide contamination risk by in areas with different sized watersheds, ranging from 2 km2to 7000 km2, in which stream water is collected for consumption by humans and animals. The resultswere recently used by the regional water agency to determine the protection zoning for a large pumpingstation. Measures were then proposed to farmers with a view to improving their practices.The method can be extrapolated to different other areas to preserve or restore the surface water

River Channel Geometry and Rating Curve Estimation Using Height Above the Nearest Drainage

River channel geometry is an important input to hydraulic and hydrologic models. Traditional approaches to quantify river geometry have involved surveyed river cross-sections, which cannot be extended to ungauged basins. In this paper, we describe a method for developing a synthetic rating curve to relate flow to water level in a stream reach based on reach-averaged channel geometry properties developed using the Height Above Nearest Drainage (HAND) method. HAND uses a digital elevation model of the terrain and computes the elevation difference between each land surface cell and the stream bed cell to which it drains. Taking increments in water level in the stream, HAND defines the inundation zone and a water depth grid within this zone, and the channel characteristics are defined from this water depth grid. We apply our method to the Blanco River (TX) and the Tar River (NC) using 10-meter terrain data from the USGS 3DEP Elevation dataset. We evaluate the method’s performance by comparing the reach-average stage-river geometry relationships and rating curves to those from calibrated HEC-RAS models and USGS gage observations. The results demonstrate that after some adjustment, the river geometry information and rating curves derived from HAND using national-coverage datasets are comparable to those obtained from hydraulic models or gage measurements. We evaluate the inundation extent and show that our approach is able to capture the majority of the FEMA 100-year floodplain