Role of Extreme Precipitation and Initial Hydrologic Conditions on Floods in Godavari River Basin, India

2019 ◽  
Vol 55 (11) ◽  
pp. 9191-9210 ◽  
Author(s):  
Shailesh Garg ◽  
Vimal Mishra
Keyword(s):  
River Basin ◽  
Extreme Precipitation ◽  
Godavari River ◽  
Hydrologic Conditions

scholarly journals Two-Dimensional Flood Inundation Modeling in the Godavari River Basin, India—Insights on Model Output Uncertainty

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 191
Author(s):  
Vimal Chandra Sharma ◽  
Satish Kumar Regonda
Keyword(s):  
Model Calibration ◽  
Water Surface ◽  
Flood Inundation ◽  
Multiple Sources ◽  
Godavari River ◽  
Flood Inundation Modeling ◽  
Hydrologic Conditions ◽  
Inundation Modeling ◽  
2D Model

Most flood inundation models do not come with an uncertainty analysis component chiefly because of the complexity associated with model calibration. Additionally, the fact that the models are both data- and compute-intensive, and since uncertainty results from multiple sources, adds another layer of complexity for model use. In the present study, flood inundation modeling was performed in the Godavari River Basin using the Hydrologic Engineering Center—River Analysis System 2D (HEC-RAS 2D) model. The model simulations were generated for six different scenarios that resulted from combinations of different geometric, hydraulic and hydrologic conditions. Thus, the resulted simulations account for multiple sources of uncertainty. The SRTM-30 m and MERIT-90 m Digital elevation Model (DEM), two sets of Manning’s roughness coefficient (Manning’s n) and observed and estimated boundary conditions, were used to reflect geometric, hydraulic and hydrologic uncertainties, respectively. The HEC-RAS 2D model ran in an unsteady state mode for the abovementioned six scenarios for the selected three flood events that were observed in three different years, i.e., 1986, 2005 and 2015. The water surface elevation (H) was compared in all scenarios as well as with the observed values at selected locations. In addition, ‘H’ values were analyzed for two different structures of the computational model. The average correlation coefficient (r) between the observed and simulated H values is greater than 0.85, and the highest r, i.e., 0.95, was observed for the combination of MERIT-90 m DEM and optimized (obtained via trial and error) Manning’s n. The analysis shows uncertainty in the river geometry information, and the results highlight the varying role of geometric, hydraulic and hydrologic conditions in the water surface elevation estimates. In addition to the role of the abovementioned, the study recommends a systematic model calibration and river junction modeling to understand the hydrodynamics upstream and downstream of the junction.

A dual role of dams in fragmentation and support of fish diversity across the Godavari River basin in India

Ecohydrology ◽  
2014 ◽  
Vol 7 (6) ◽  
pp. 1560-1573 ◽  
Author(s):  
Gulab Dattarao Khedkar ◽  
Sigal Lutzky ◽  
Sandeep Rathod ◽  
Amol Kalyankar ◽  
Lior David
Keyword(s):  
River Basin ◽  
Dual Role ◽  
Fish Diversity ◽  
Godavari River

scholarly journals The Role of Hydrological Initial Conditions on Atmospheric River Floods in the Russian River Basin

2019 ◽  
Vol 20 (8) ◽  
pp. 1667-1686 ◽  
Author(s):  
Qian Cao ◽  
Ali Mehran ◽  
F. Martin Ralph ◽  
Dennis P. Lettenmaier
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Extreme Precipitation ◽  
Initial Conditions ◽  
Winter Precipitation ◽  
Antecedent Soil Moisture ◽  
Coastal Watershed ◽  
Antecedent Precipitation ◽  
Russian River

Abstract A body of work over the last decade or so has demonstrated that most major floods along the U.S. West Coast are attributable to atmospheric rivers (ARs). Recent studies suggest that observed changes in extreme precipitation associated with a general warming of the western United States have not necessarily led to corresponding changes in floods, and changes in antecedent hydrological conditions could be a primary missing link. Here we examine the role of antecedent soil moisture (ASM) conditions on historical AR flooding on California’s Russian River basin, a coastal watershed whose winter precipitation extremes are dominated by ARs. We examined the effect of observed warming on ASM for the period 1950–2017. We first constructed an hourly precipitation product at 1/32° spatial resolution. We used the Distributed Hydrology Soil Vegetation Model (DHSVM) to estimate storm total runoff volumes and soil moisture. We found that up to 95% of peaks-over-threshold (POT) extreme discharge events were associated with ARs. The storm runoff–precipitation ratio generally increased with wetter prestorm conditions, and the relationship was stronger as drainage area increased. We found no trends in extreme precipitation but weak downward trends in extreme discharge. The latter were mostly consistent with weak downward trends in the first 2-day storm precipitation. We found no trends in ASM; however, ASM was significantly correlated with peak flow. The ASM was affected more by antecedent precipitation than evapotranspiration, and hence temperature increases had weak effects on ASM.

scholarly journals Floods due to Atmospheric Rivers along the U.S. West Coast: The Role of Antecedent Soil Moisture in a Warming Climate

2020 ◽  
Vol 21 (8) ◽  
pp. 1827-1845 ◽  
Author(s):  
Qian Cao ◽  
Alexander Gershunov ◽  
Tamara Shulgina ◽  
F. Martin Ralph ◽  
Ning Sun ◽  
...  
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
West Coast ◽  
Extreme Precipitation ◽  
Antecedent Soil Moisture ◽  
Extreme Precipitation Events ◽  
Warming Climate ◽  
The U.S ◽  
Precipitation Events

AbstractPrecipitation extremes are projected to become more frequent along the U.S. West Coast due to increased atmospheric river (AR) activity, but the frequency of less intense precipitation events may decrease. Antecedent soil moisture (ASM) conditions can have a large impact on flood responses, especially if prestorm precipitation decreases. Taken together with increased antecedent evaporative demand due to warming, this would result in reduced soil moisture at the onset of extreme precipitation events. We examine the impact of ASM on AR-related floods in a warming climate in three basins that form a transect along the U.S. Pacific Coast: the Chehalis River basin in Washington, the Russian River basin in Northern California, and the Santa Margarita River basin in Southern California. We ran the Distributed Hydrology Soil Vegetation Model (DHSVM) over the three river basins using forcings downscaled from 10 global climate models (GCMs). We examined the dynamic role of ASM by comparing the changes in the largest 50, 100, and 150 extreme events in two periods, 1951–2000 and 2050–99. In the Chehalis basin, the projected fraction of AR-related extreme discharge events slightly decreases. In the Russian basin, this fraction increases, however, and more substantially so in the Santa Margarita basin. This is due to increases in AR-related extreme precipitation events, as well as the fact that the relationship of extreme precipitation to extreme discharge is strengthened by projected increases in year-to-year volatility of annual precipitation in California, which increases the likelihood of concurrent occurrence of large storms and wet ASM conditions.

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