scholarly journals Variability and change of precipitation and flood discharge in a Japanese river basin

2019 ◽  
Vol 21 ◽  
pp. 68-79 ◽  
Author(s):  
Makoto Higashino ◽  
Heinz G. Stefan
Keyword(s):  
River Basin ◽  
Flood Discharge

scholarly journals Influence of Landscape Retention Capacity Upon Flood Processes in Jičínka River Basin

2014 ◽  
Vol 62 (1) ◽  
pp. 191-199
Author(s):  
František Pavlík ◽  
Miroslav Dumbrovský
Keyword(s):  
River Basin ◽  
Daily Precipitation ◽  
Original Method ◽  
Important Criterion ◽  
Retention Capacity ◽  
Flood Discharge ◽  
Disastrous Flood ◽  
Final Profile

In a survey of landscape retention capability results of measurements obtained during the disastrous flood in June 2009 were used. The original method based on the balance among the daily precipitation fallen on the basin with discharges in the final profile was used on the analogy with transformation of the flood discharge through a reservoir. Following basin retention are defined: dynamic Rd, static Rs including the underground retention Rug and evaporation E, and total Rt. Main principal criteria were the effective static retention of the basin Rsef and a coefficient of the effective static basin retention ρsef (3). The coefficient of reducing flood culmination λcul (4) was calculated, too. Also investigated factors having the most influence on a retention capacity of a basin are introduced. Summary of results are shown in the Tab. I. Values of the most important criterion quantities are marked in shadow colour. The results show, for example, that the found out coefficient ρsef is 0.52. It means that the soil (and slightly a vapour, too) in the basin caught 52% of volume of wave in the time of culmination discharge in a basin. Also some further interested findings are introduced in the results and conclusions.

scholarly journals Adequacy of Near Real-Time Satellite Precipitation Products in Driving Flood Discharge Simulation in the Fuji River Basin, Japan

2021 ◽  
Vol 11 (3) ◽  
pp. 1087
Author(s):  
Li Zhou ◽  
Mohamed Rasmy ◽  
Kuniyoshi Takeuchi ◽  
Toshio Koike ◽  
Hemakanth Selvarajah ◽  
...  
Keyword(s):  
Real Time ◽  
River Basin ◽  
Bias Correction ◽  
Large Scale ◽  
River Flow ◽  
Hydrologic Model ◽  
Satellite Precipitation ◽  
Flood Discharge ◽  
Discharge Simulation ◽  
The Impact

Flood management is an important topic worldwide. Precipitation is the most crucial factor in reducing flood-related risks and damages. However, its adequate quality and sufficient quantity are not met in many parts of the world. Currently, near real-time satellite precipitation products (NRT SPPs) have great potential to supplement the gauge rainfall. However, NRT SPPs have several biases that require corrections before application. As a result, this study investigated two statistical bias correction methods with different parameters for the NRT SPPs and evaluated the adequacy of its application in the Fuji River basin. We employed Global Satellite Mapping of Precipitation (GSMaP)-NRT and Integrated Multi-satellitE Retrievals for GPM (IMERG)-Early for NRT SPPs as well as BTOP model (Block-wise use of the TOPMODEL (Topographic-based hydrologic model)) for flood runoff simulation. The results showed that the corrected SPPs by the 10-day ratio based bias correction method are consistent with the gauge data at the watershed scale. Compared with the original SPPs, the corrected SPPs improved the flood discharge simulation considerably. GSMaP-NRT and IMERG-Early have the potential for hourly river-flow simulation on a basin or large scale after bias correction. These findings can provide references for the applications of NRT SPPs in other basins for flood monitoring and early warning applications. It is necessary to investigate the impact of number of ground observation and their distribution patterns on bias correction and hydrological simulation efficiency, which is the future direction of this study.

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 Application and Flood Discharge Analysis with Hydrological Model (WEB-DHM) in Bago River Basin

2020 ◽  
Vol 15 (3) ◽  
pp. 344-352
Author(s):  
Sann Win Maung ◽  
Zin Mar Lar Tin San ◽  
Win Win Zin ◽  
Akiyuki Kawasaki ◽  
Kyu Kyu Thin ◽  
...  
Keyword(s):  
River Basin ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
Monsoon Season ◽  
Meteorological Data ◽  
Historical Record ◽  
Japan Meteorological Agency ◽  
Distributed Hydrological Model ◽  
Flood Discharge ◽  
Storm Rainfall

Flooding has always been one of the major hazards in Myanmar, accounting for 11% of all disasters. The Bago River Basin is a floodprone area in Myanmar, where, during the last decade, many severe floods occurred during the monsoon season, usually in July and August. Most of these floods are caused by storm rainfall. The 2011 and 2018 floods form part of the historical record of Bago. The main objective of this research paper is to develop a new hydrological model (WEB-DHM) for the Bago River Basin using observed station data to represent floods in the study area. The Water and Energy Budget-based Distributed Hydrological Model (WEB-DHM) was used for hydrological modeling as determined for the discharge of floods. The HydroSHEDS digital elevation model is used for the discharge estimation and analysis of the WEB-DHM. The Japanese 55-year Reanalysis JRA-55 data, from the Japan Meteorological Agency (JMA), were used for the preparation of meteorological data for this model. The results of flood discharge from the hydrological modeling and the observed data of the past three years (2014, 2015 and 2016) are provided in this study.

scholarly journals Flood Frequency Analysis in Sabarmati River basin and Estimation of Peak Discharge under Climate Change Scenario

2019 ◽  
Vol 8 (2) ◽  
pp. 6095-6099
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Frequency Analysis ◽  
Climate Change Scenario ◽  
Frequency Factor ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Change Scenario ◽  
Flood Discharge ◽  
Sabarmati River

Due to climate change, there is an increased/decreased frequency of peak flood discharge in river and streams. The most important concern of planning is to safe passing of the extreme flood discharge influenced by extreme climatic changes. It is a concern for planning for the storage capacity to safely store extreme discharge/inflow of the river. In this paper, probability theories and statistics for flood frequency factor (K) are applied and based on the results; it is found that the Extreme value model results in to a best model for frequency factor K, as it is yielding the minimum relative error. Using the frequency factor, the flood frequency analysis for peak flood is carried out for climate change scenario/Advance scenario. The peak discharge in advance scenario is more as compare to the base line scenario at most of the stations except three stations located on the south-east of the Sabarmati river basin.

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