A systems approach to routing global gridded runoff through local high-resolution stream networks for flood early warning systems

Qiao, Xiaohui; Nelson, Everett J.; Ames, Daniel P.; Li, Zhiyu; David, Cédric H.; Williams, Gustavious P.; Roberts, Wade; Lozano, Jorge Luis Sánchez; Edwards, Christopher G.; Souffront, Michael; Matin, Mir A.

doi:10.1016/j.envsoft.2019.104501

Cited by 26 publications

(8 citation statements)

References 42 publications

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“…HTESSEL runoff was an input into the Routing Application for Parallel Computation of Discharge (RAPID) streamflow routing model (David et al, 2011(David et al, , 2015 that routes runoff and upstream streamflow through a HydroSHEDS-delineated hydrography with a 150-km 2 average catchment size (Ashby et al, 2021;Hales et al, 2022;Lozano et al, 2021). The methodologies underlying the GEOGloWS ECMWF Streamflow Model streamflow estimates have performed favorably when compared to other global streamflow datasets (Qiao et al, 2019;Sikder et al, 2019). The GEOGloWS ECMWF Streamflow Model streamflow estimates lacked full calibration to observed streamflow (Hales et al, 2022), but the HTESSEL runoff did assimilate land surface observations, such as soil moisture (de Rosnay et al, 2014;Harrigan et al, 2020).…”

Section: Geoglows Ecmwf Streamflow Modeling Frameworkmentioning

confidence: 99%

Case study of continental‐scale hydrologic modeling's ability to predict daily streamflow percentiles for regulatory application

Gutenson,

Sparrow,

Brown

et al. 2024

J American Water Resour Assoc

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Regulatory practitioners use hydroclimatic data to provide context to observations typically collected through field site visits and aerial imagery analysis. In the absence of site‐specific data, regulatory practitioners must use proxy hydroclimatic data and models to assess a stream's hydroclimatology. One intent of current‐generation continental‐scale hydrologic models is to provide such hydrologic context to ungaged watersheds. In this study, the ability of two state‐of‐the‐art, operational, continental‐scale hydrologic modeling frameworks, the National Water Model and the Group on Earth Observation Global Water Sustainability (GEOGloWS) European Centre for Medium‐Range Weather Forecasts (ECMWF) Streamflow Model, to produce daily streamflow percentiles and categorical estimates of the streamflow normalcy was examined. The modeled streamflow percentiles were compared to observed daily streamflow percentiles at four United States Geological Survey stream gages. The model's performance was then compared to a baseline assessment methodology, the Antecedent Precipitation Tool. Results indicated that, when compared to baseline assessment techniques, the accuracy of the National Water Model (NWM) or GEOGloWS ECMWF Streamflow Model was greater than the accuracy of the baseline assessment methodology at four stream gage locations. The NWM performed best at three of the four gages. This work highlighted a novel application of current‐generation continental‐scale hydrologic models.

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Section: Geoglows Ecmwf Streamflow Modeling Frameworkmentioning

confidence: 99%

Case study of continental‐scale hydrologic modeling's ability to predict daily streamflow percentiles for regulatory application

Gutenson,

Sparrow,

Brown

et al. 2024

J American Water Resour Assoc

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“…The use of Sentinel-1 satellite-based soil moisture products can ultimately improve water resource management and decision-making processes. Integrating satellite data with hydrological models also facilitates the development of early warning systems for floods and other hydrological events (Koriche and Rientjes 2016;Qiao et al 2019). This contributes to disaster risk reduction and management (Manfré et al 2012;Hoque et al 2017;Khan et al 2023).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Sentinel-1 Satelite-based Soil Moisture Products for Runoff Modelling with Karst Formation Characteristics

Mawandha,

Pratama,

Ghifari

et al. 2024

Preprint

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Soil moisture content is a crucial factor in hydrological studies as it helps to determine the rainfall and runoff response in the catchment. Land use, particularly cropping, can have a significant effect on soil moisture content. Hilly topography with karst features is more prone to flooding and soil erosion due to its low water holding capacity. Remote sensing technology has recently been applied to agriculture and disaster management. The aim of this research is to identify soil moisture characteristics in karst formations for runoff estimation using remotely sensed imagery from Sentinel-1. Soil moisture is calculated using the Topp model equation based on the soil dielectric value obtained from the Dubois model. By using different types of land use and soil moisture data from Sentinel-1, CN values can be generated and then used to estimate runoff. The results of the study show that extracting soil moisture information from Sentinel-1A with VV polarisation for karst areas is still challenging due to the high bias. The Sentinel-1 satellite soil moisture products could provide a real-time CN value that can be integrated with the rainfall runoff model. This research highlights the importance of monitoring soil moisture to determine CN values for flood mitigation.

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“…Development of a high‐quality river channel hydrography is critical to conduct large‐scale hydrological modeling and improve monitoring and forecasting of hydrological conditions. These analyses can improve readiness for extreme conditions and aid in the management of water resources (Fan et al., 2021; Linke et al., 2019; Qiao et al., 2019; Wing et al., 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Increasing demand for improved hydrologic forecasting has led to the development of large‐scale routing and flood inundation models (Linke et al., 2019; Qiao et al., 2019; Trambauer et al., 2013; Van Der Knijff et al., 2010). Use of these models relies on digital river networks, typically in the form of grid‐based flowpath segments connected by boundary conditions at nodal points (Arora, 2001; Fan et al., 2021; Lohmann et al., 2004; Wing et al., 2019; Xia et al., 2012).…”

Section: Introductionmentioning

confidence: 99%

Effect of User Decision and Environmental Factors on Computationally Derived River Networks

et al. 2023

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Despite recent developments of continental and global vector‐based river networks, the impact of digital elevation model selection, stream initiation area and environmental parameters including land cover, and elevation, remain unexplored at large scales. To fill this gap, vector river networks based on multiple data sets are compared to the National Hydrography Dataset Plus High Resolution flowpaths. Using TauDEM, river networks from three conditioned Digital Elevation Models (DEMs) were produced at multiple thresholds for stream initiation. OpenCLC, a software package for the comparison of hydrographic networks, was used to compare digital hydrographic networks with the NHDPlus HR flowlines data set over more than 35,00 basins. Networks derived from the 12 m Tandem‐X data set showed similar results as the MERIT Hydro with 90 m resolution until the application of a sophisticated stream burning methodology improved performance significantly. The optimal CLC is obtained at 1‐km threshold for Hydrological Data and Maps Based on SHuttle Elevation Derivatives at multiple Scales and MERIT Hydro‐gridded data sets, quality declined with smaller thresholds. Spatial patterns in river‐network quality were observed and were associated with dominant land classification, with greater forest coverage associated with significantly better quality and greater wetland presence with lower quality networks. This study demonstrates user selection of DEM, and threshold combined with environmental factors (vegetation, water coverage, and precipitation) play a significant role in river‐network quality compared to the DEM selection, and that without sophisticated conditioning, a higher resolution base DEM does not necessarily produce a better river network.

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A systems approach to routing global gridded runoff through local high-resolution stream networks for flood early warning systems

Cited by 26 publications

References 42 publications

Case study of continental‐scale hydrologic modeling's ability to predict daily streamflow percentiles for regulatory application

Case study of continental‐scale hydrologic modeling's ability to predict daily streamflow percentiles for regulatory application

Evaluation of Sentinel-1 Satelite-based Soil Moisture Products for Runoff Modelling with Karst Formation Characteristics

Effect of User Decision and Environmental Factors on Computationally Derived River Networks

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