Hydrometeorology of the catastrophic Blanco river flood in South Texas, May 2015

Furl, Chad; Sharif, Hatim O.; Zeitler, Jon W.; Hassan, Almoutaz El; Joseph, John F.

doi:10.1016/j.ejrh.2017.12.001

Cited by 12 publications

(8 citation statements)

References 44 publications

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“…The western region is typically covered by arid deserts while the central and eastern districts are generally more humid covered by forest, agricultural lands, and rangelands. The southeast is dominantly under the effect of subtropical weather condition which causes this region to be renowned as one of the most vulnerable regions to natural disasters such as hurricanes, tornados and flash-floods [52]. The majority of Texas population resides in the central and eastern regions causing growth demand for more infrastructures in this area.…”

Section: Study Areamentioning

confidence: 99%

How Well Can Global Precipitation Measurement (GPM) Capture Hurricanes? Case Study: Hurricane Harvey

2018

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Hurricanes and other severe coastal storms have become more frequent and destructive during recent years. Hurricane Harvey, one of the most extreme events in recent history, advanced as a category IV storm and brought devastating rainfall to the Houston, TX, region during 25–29 August 2017. It inflicted damage of more than $125 billion to the state of Texas infrastructure and caused multiple fatalities in a very short period of time. Rainfall totals from Harvey during the 5-day period were among the highest ever recorded in the United States. Study of this historical devastating event can lead to better preparation and effective reduction of far-reaching consequences of similar events. Precipitation products based on satellites observations can provide valuable information needed to understand the evolution of such devastating storms. In this study, the ability of recent Integrated Multi-satellitE Retrievals for Global Precipitation Mission (GPM-IMERG) final-run product to capture the magnitudes and spatial (0.1° × 0.1°)/temporal (hourly) patterns of rainfall resulting from hurricane Harvey was evaluated. Hourly gridded rainfall estimates by ground radar (4 × 4 km) were used as a reference dataset. Basic and probabilistic statistical indices of the satellite rainfall products were examined. The results indicated that the performance of IMERG product was satisfactory in detecting the spatial variability of the storm. It reconstructed precipitation with nearly 62% accuracy, although it systematically under-represented rainfall in coastal areas and over-represented rainfall over the high-intensity regions. Moreover, while the correlation between IMERG and radar products was generally high, it decreased significantly at and around the storm core.

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Section: Study Areamentioning

confidence: 99%

How Well Can Global Precipitation Measurement (GPM) Capture Hurricanes? Case Study: Hurricane Harvey

2018

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“…All of the storm event accumulations from the Stage IV precipitation record are presented in Figure 2. The hydrometeorology of several of these events has been examined in detail including Furl, Sharif [42] (May 2015 event), Furl, Sharif [40] (September 2010 event), and Sharif, Sparks [36] (November 2004 events). Total accumulations from stage IV data for individual storm events used in the analysis (mm).…”

Section: Storm Eventsmentioning

confidence: 99%

“…The Blanco watershed model was the primary model calibrated. Furl et al [42] calibrated the model to the November 2004 "early" event used here and achieved r2, Nash-Sutcliffe model efficiency (NSE), and percent bias (PBIAS) values of 0.91, 0.90, and 10.2%, respectively for the calibration run. Similar model parameter values were used for the Upper Guadalupe model.…”

Section: Hydrologic Modelmentioning

confidence: 99%

“…Surface properties for the Blanco River watershed are shown in Table 2. The readers are directed to Sharif, Sparks [36] and Furl et al [42] for detailed descriptions of the watershed models and their comparisons with measured flows.…”

Section: Hydrologic Modelmentioning

confidence: 99%

“…The two largest rain events from the dataset occurred in May and October of 2015, and both resulted in significant flash flood events along the Blanco River [42]. These events were captured by GPM and offer an initial look at GPM performance for short duration high magnitude storms.…”

Section: Gpm Rainfall Eventsmentioning

confidence: 99%

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Assessment of the Performance of Satellite-Based Precipitation Products for Flood Events across Diverse Spatial Scales Using GSSHA Modeling System

2018

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Accurate precipitation measurements for high magnitude rainfall events are of great importance in hydrometeorology and climatology research. The focus of the study is to assess the performance of satellite-based precipitation products against a gauge adjusted Next-Generation Radar (NEXRAD) Stage IV product during high magnitude rainfall events. The assessment was categorized across three spatial scales using watershed ranging from~200-10,000 km 2. The propagation of the errors from rainfall estimates to runoff estimates was analyzed by forcing a hydrologic-model with the satellite-based precipitation products for nine storm events from 2004 to 2015. The National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) Morphing Technique (CMORPH) products showed high correlation to the NEXRAD estimates in all spatial domains, and had an average Nash-Sutcliffe coefficient of 0.81. The Global Precipitation Measurement (GPM) Early product was inconsistent with a very high variance of Nash-Sutcliffe coefficient in all spatial domains (from −0.46 to 0.38), however, the variance decreased as the watershed size increased. Surprisingly, Tropical Rainfall Measuring Mission (TRMM) also showed a very high variance in all the performance statics. In contrast, the un-corrected product of the TRMM showed a relatively better performance. The errors of the precipitation estimates were amplified in the simulated hydrographs. Even though the products provide evenly distributed near-global spatiotemporal estimates, they significantly underestimate strong storm events in all spatial scales.

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An innovative approach of GSSHA model in flood analysis of large watersheds based on accuracy of DEM, size of grids, and stream density

et al. 2022

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Distributed modeling approach may have much better performance and accuracy compared with lumped-parameter hydrologic models. The main goals of this research are: investigating the possibility of combining distributed hydrological models with an one-dimensional hydraulic model and simulating waterways in large watersheds with limited hydrological and hydraulic data. Then performing sensitivity analysis on different parameters in order to identify the parameters containing the major influences on results. In the current research, an innovative approach in Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model, the cross-sections of all 414 waterways in the 3450 km2 Karvandar watershed, used for flow routing calculations, are uniquely extracted. Then, the effect of three essential factors are evaluated. These factors are accuracy of the digital topographic model, cell size of grid network, and density of streams, on the results of GSSHA model simulations. This watershed is located in southeastern Iran, has a dry climate with limited available hydrological data. Results showed that peak discharges obtained from the GSSHA model, developed based on a DEM with a spatial resolution of 12.5 m, are slightly (< 4%) lower than the corresponding values in the GSSHA model with a 30 m DEM resolution. This fact confirms that the use of the topographic model with a lower spatial resolution has no substantial effects on the accuracy of simulation. Also, the peak discharges increased significantly (44% to 57%) by increasing the density of waterways in the GSSHA model. Furthermore, results showed that peak discharge obtained from three models with grid cell sizes of 100, 150, and 200 m (base model), are close together. Comparing with two models of coarser grids (250 and 300 m), significant differences observed, which indicated that the grids larger than 200 m could induce substantial errors in results.

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Hydrometeorology of the catastrophic Blanco river flood in South Texas, May 2015

Cited by 12 publications

References 44 publications

How Well Can Global Precipitation Measurement (GPM) Capture Hurricanes? Case Study: Hurricane Harvey

How Well Can Global Precipitation Measurement (GPM) Capture Hurricanes? Case Study: Hurricane Harvey

Assessment of the Performance of Satellite-Based Precipitation Products for Flood Events across Diverse Spatial Scales Using GSSHA Modeling System

An innovative approach of GSSHA model in flood analysis of large watersheds based on accuracy of DEM, size of grids, and stream density

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