scholarly journals Estimation of Peak Flood Discharge for an Ungauged River: A Case Study of the Kunur River, West Bengal

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Suvendu Roy ◽  
Biswaranjan Mistri
Keyword(s):  
River Basin ◽  
Peak Discharge ◽  
Wave Parameter ◽  
Sudden Increase ◽  
Hydrological Models ◽  
Gangetic Plain ◽  
Discharge Data ◽  
Channel Geometry ◽  
Flood Discharge ◽  
Peak Flood

Due to unavailability of sufficient discharge data for many rivers, hydrologists have used indirect methods for deriving flood discharge amount, that is, application of channel geometry and hydrological models, for the estimation of peak discharge in the selected ungauged river basin(s) in their research/project works. This paper has studied the estimation of peak flood discharge of the Kunur River Basin, a major tributary of the Ajay River in the lower Gangetic plain. To achieve this objective, field measurements, GIS technique, and several channel geometry equations are adopted. Three important geomorphic based hydrological models—manning’s equation, kinematic wave parameter (KWP), and SCS curve number (CN) method—have been used for computing peak discharge during the flood season, based on daily rainfall data of September, 2000. Peak discharges, calculated by different given models, are 239.44 m3/s, 204.08 m3/s, and 146.52 m3/s, respectively. The hydrograph has demonstrated the sudden increase with heavy rainfall from the 18th to the 22nd of September, 2000. As a result, a havoc flood condition was generated in the confluence zone of Ajay and Kunur Rivers. This hydrograph might be not only successful application for flood forecasting but also for management of the lower Ajay River Basin as well as the downstream area of Kunur Basin.

scholarly journals River discharge prediction for ungauged mountainous river basins during heavy rain events based on seismic noise data

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Shakti P.C. ◽  
Kaoru Sawazaki
Keyword(s):  
River Basin ◽  
Seismic Noise ◽  
River Discharge ◽  
Heavy Rain ◽  
River Basins ◽  
Peak Discharge ◽  
Discharge Data ◽  
Noise Data ◽  
Rain Events ◽  
Mountainous River

AbstractSeveral mountainous river basins in Japan do not have a consistent hydrological record due to their complex environment and remoteness, as discharge measurements are not economically feasible. However, understanding the flow rate of rivers during extreme events is essential for preventing flood disasters around river basins. In this study, we used the high-sensitivity seismograph network (Hi-net) of Japan to identify the time and peak discharge of heavy rain events. Hi-net seismograph stations are distributed almost uniformly at distance intervals of approximately 20 km, while being available even in mountainous regions. The Mogami River Basin in Northeastern Japan was selected as a target area to compare the seismic noise data of two Hi-net stations with the hydrological response of a nearby river. These stations are not located near hydrological stations; therefore, direct comparison of seismic noise and observed discharge was not possible. Therefore, discharge data simulated using a hydrological model were first validated with gauging station data for two previous rain events (10–23 July 2004 and 7–16 September 2015). Then, the simulated river discharge was compared with Hi-net seismic noise data for three recent events (10–23 July 2004, 7–16 September 2015, and 10–15 October 2019). The seismic noise data exhibited a similar trend to the time series of simulated discharge in a frequency range of 1–2 Hz for the selected events. Discharge values predicted from the noise data effectively replicate the simulated discharge values in many cases, especially the timing and amount of peak discharge.Simulated and predicted discharge near NIED Hi-net seismic stations in the Mogami River Basin for the event of October 2019 (Typhoon Hagibis).

scholarly journals Optimal application of conceptual rainfall–runoff hydrological models in the Jinshajiang River basin, China

2015 ◽  
Vol 368 ◽  
pp. 227-232 ◽  
Author(s):  
M. Tayyab ◽  
J. Zhou ◽  
X. Zeng ◽  
L. Chen ◽  
L. Ye
Keyword(s):  
River Basin ◽  
Suitable Model ◽  
Hydrological Models ◽  
Discharge Data ◽  
Specific Research ◽  
Research Areas ◽  
Antecedent Precipitation ◽  
Hourly Rainfall ◽  
Xin’Anjiang Model ◽  
Different Characteristics

Abstract. For specific research areas different hydrological models have shown different characteristics. By comparing different hydrological models on the same area we should get better and more authentic results. The objective of this research study is to highlight the importance of model selection for specific research areas. For the Jinshajiang River basin, three conceptual hydrological models including the Xin’anjiang model, the Antecedent precipitation index (API) model and the Tank model are applied to select the most suitable model for flood forecasting, based on the hourly rainfall and hourly discharge data. Data were analysed by comparing the simulation outputs of the three models with the Nash-Sutcliffe efficiency and Correlation coefficient index. Results showed that the performance of the three models were not very different. On the basis of data need and the characteristics of the research basin, the Xin’anjiang model was selected as the optimal and practical conceptual hydrological model for the Jinshajiang River basin.

scholarly journals Analisis Hidrograf DAS Poso dengan Metode Hidrograf Satuan Sintetis Snyder dan Hidrograf Satuan Sintetis Soil Conversation Service (SCS)

2021 ◽  
pp. 121-128
Author(s):  
A. Kahffi ◽  
S. Lipu
Keyword(s):  
Power Plant ◽  
Peak Discharge ◽  
Hydropower Plant ◽  
Peak Time ◽  
Hydroelectric Power ◽  
Unit Hydrograph ◽  
Discharge Data ◽  
Flood Discharge ◽  
Base Time ◽  
Synthetic Unit Hydrograph

The Poso River is a river located in Poso Regency, Central Sulawesi Province, which has a length of 74.58 km, and watershed area of 1092.810 km2. Energy in the Poso River is used for hydroelectric power plant (PLTA). With the construction of the Poso hydropower plant, maximum flood discharge data is needed for the prevention of Poso hydro power plant safety. In calculating the flood discharge, the method used is a synthetic unit hydrograph. Synthetic unit hydrograph is a graph of the relationship between flow rate (Q) and time (t). In this study, the method used to calculate the designed flood discharge is the Snyder synthetic unit hydrograph method and the Soil Conversation Service (SCS) synthetic unit hydrograph. The aims of this study are to determine the largest flood discharge value and to determine the hydrograph shapes of the two methods. The parameters that will be obtained from both methods are peak time (Tp), base time (Tb) and peak discharge (Qp). From the analysis it can be found that in the Snyder SUH method, the peak time (Tp) is 12.616 hours, the base time (Tb) is 67.276 hours with a peak discharge (Qp) of 21.672 m3sec. Whereas in the SCS SUH method, the peak time (Tp) is 10.954 hours, the base time (Tb) is 57.268 hours with a peak discharge (Qp) of 20.751 m3/sec. The result demonstrates the result that the largest flood discharge has occurred in the Snyder SUH method.

scholarly journals Flood discharge analysis of Brang Ode River as a disaster mitigation effort in Kalimango Village

2021 ◽  
Vol 331 ◽  
pp. 08004
Author(s):  
Imam Solihin Al-Abbas ◽  
Eko Pradjoko ◽  
Heri Sulistiyono
Keyword(s):  
Data Accuracy ◽  
Peak Discharge ◽  
Disaster Mitigation ◽  
Flood Inundation ◽  
Raster Data ◽  
Village Community ◽  
Inundation Area ◽  
Flood Discharge ◽  
Mitigation Effort ◽  
Peak Flood

Flood is a hydrometeorological disaster that often occurs in West Nusa Tenggara, especially in the Brang Ode River, Kalimango Village, Alas District, Sumbawa Regency. One of the worst floods ever happened was on December 12th, 2016, which caused several villages to be inundated and houses along the river to wash away. This study aims to obtain the peak discharge from the worst flood that has ever occurred. This model is simulated using HEC-RAS 5.0.7 and QGIS for mapping the flood inundation area. Terrain data used DEMNAS. The peak discharge is obtained from the modeling results based on the flood inundation area, validated with the flood map from the DESTANA (disaster resilient village) Community of Kalimango Village. The modeling results showed that the peak flood discharge is 950 m3/s, with the inundation area 150,752.07 m2. The actual peak flood discharge can be smaller or larger than the modeling results. It may be affected by the DEMNAS raster data accuracy.

scholarly journals The Rise of Climate-Driven Sediment Discharge in the Amazonian River Basin

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 208 ◽  
Author(s):  
Nazzareno Diodato ◽  
Naziano Filizola ◽  
Pasquale Borrelli ◽  
Panos Panagos ◽  
Gianni Bellocchi
Keyword(s):  
River Basin ◽  
Amazon Basin ◽  
Global Climate ◽  
Climate Extremes ◽  
Temporal Variations ◽  
Sediment Discharge ◽  
Storm Events ◽  
Discharge Data ◽  
Magdalena River ◽  
Sediment Export

The occurrence of hydrological extremes in the Amazon region and the associated sediment loss during rainfall events are key features in the global climate system. Climate extremes alter the sediment and carbon balance but the ecological consequences of such changes are poorly understood in this region. With the aim of examining the interactions between precipitation and landscape-scale controls of sediment export from the Amazon basin, we developed a parsimonious hydro-climatological model on a multi-year series (1997–2014) of sediment discharge data taken at the outlet of Óbidos (Brazil) watershed (the narrowest and swiftest part of the Amazon River). The calibrated model (correlation coefficient equal to 0.84) captured the sediment load variability of an independent dataset from a different watershed (the Magdalena River basin), and performed better than three alternative approaches. Our model captured the interdecadal variability and the long-term patterns of sediment export. In our reconstruction of yearly sediment discharge over 1859–2014, we observed that landscape erosion changes are mostly induced by single storm events, and result from coupled effects of droughts and storms over long time scales. By quantifying temporal variations in the sediment produced by weathering, this analysis enables a new understanding of the linkage between climate forcing and river response, which drives sediment dynamics in the Amazon basin.

scholarly journals Process-Based Modeling of the High Flow of a Semi-Mountain River under Current and Future Climatic Conditions: A Case Study of the Iya River (Eastern Siberia)

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1042
Author(s):  
Andrey Kalugin
Keyword(s):  
Water Level ◽  
River Basin ◽  
21St Century ◽  
Residential Buildings ◽  
High Flow ◽  
Peak Discharge ◽  
Future Climate ◽  
Future Climate Change ◽  
Generation Model ◽  
Annual Peak

The purpose of the study was to analyze the formation conditions of catastrophic floods in the Iya River basin over the observation period, as well as a long-term forecast of the impacts of future climate change on the characteristics of the high flow in the 21st century. The semi-distributed process-based Ecological Model for Applied Geophysics (ECOMAG) was applied to the Iya River basin. Successful model testing results were obtained for daily discharge, annual peak discharge, and discharges exceeding the critical water level threshold over the multiyear period of 1970–2019. Modeling of the high flow of the Iya River was carried out according to a Kling–Gupta efficiency (KGE) of 0.91, a percent bias (PBIAS) of −1%, and a ratio of the root mean square error to the standard deviation of measured data (RSR) of 0.41. The preflood coefficient of water-saturated soil and the runoff coefficient of flood-forming precipitation in the Iya River basin were calculated in 1980, 1984, 2006, and 2019. Possible changes in the characteristics of high flow over summers in the 21st century were calculated using the atmosphere–ocean general circulation model (AOGCM) and the Hadley Centre Global Environment Model version 2-Earth System (HadGEM2-ES) as the boundary conditions in the runoff generation model. Anomalies in values were estimated for the middle and end of the current century relative to the observed runoff over the period 1990–2019. According to various Representative Concentration Pathways (RCP-scenarios) of the future climate in the Iya River basin, there will be less change in the annual peak discharge or precipitation and more change in the hazardous flow and its duration, exceeding the critical water level threshold, at which residential buildings are flooded.

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