A grid-based rainfall-runoff model for flood simulation including paddy fields

2010 ◽  
Vol 9 (3) ◽  
pp. 275-290 ◽  
Author(s):  
In-Kyun Jung ◽  
Jong-Yoon Park ◽  
Geun-Ae Park ◽  
Mi-Seon Lee ◽  
Seong-Joon Kim
Keyword(s):  
Paddy Fields ◽  
Rainfall Runoff ◽  
Flood Simulation ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Grid Based

scholarly journals Sensitivity Analysis to Investigate the Reliability of the Grid-Based Rainfall-Runoff Model

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1839 ◽  
Author(s):  
Mun-Ju Shin ◽  
Yun Choi
Keyword(s):  
Water Movement ◽  
Parameter Sensitivity ◽  
Low Flow ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Rainfall Events ◽  
Flow Calculation ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Grid Based

This study aimed to assess the suitability of the parameters of a physically based, distributed, grid-based rainfall-runoff model. We analyzed parameter sensitivity with a dataset of eight rainfall events that occurred in two catchments of South Korea, using the Sobol’ method. Parameters identified as sensitive responded adequately to the scale of the rainfall events and the objective functions employed. Parameter sensitivity varied depending on rainfall scale, even in the same catchment. Interestingly, for a rainfall event causing considerable runoff, parameters related to initial soil saturation and soil water movement played a significant role in low flow calculation and high flow calculation, respectively. The larger and steeper catchment exhibited a greater difference in parameter sensitivity between rainfall events. Finally, we found that setting an incorrect parameter range that is physically impossible can have a large impact on runoff simulation, leading to substantial uncertainty in the simulation results. The proposed analysis method and the results from our study can help researchers using a distributed rainfall-runoff model produce more reliable analysis results.

scholarly journals Ensemble flood simulation for a small dam catchment in Japan using nonhydrostatic model rainfalls. Part 2: Flood forecasting using 1600 member 4D-EnVAR predicted rainfalls

2019 ◽  
Author(s):  
Kenichiro Kobayashi ◽  
Le Duc ◽  
Tsutao Oizumi ◽  
Kazuo Saito ◽  
Keyword(s):  
Flood Control ◽  
Optimization Technique ◽  
Flood Forecasting ◽  
Rainfall Runoff ◽  
Flood Simulation ◽  
Nonhydrostatic Model ◽  
Rainfall Runoff Model ◽  
Inflow Discharge ◽  
Runoff Model ◽  
Assimilation System

Abstract. This paper elaborated the feasibility of flood forecasting using a distributed rainfall-runoff model and huge number of ensemble rainfalls with an advanced data assimilation system. Specifically, 1600 ensemble rainfalls simulated by a four-dimensional ensemble variational assimilation system with the JMA nonhydrostatic model (4D-EnVAR-NHM) were given to the rainfall-runoff model to simulate the inflow discharge to a small dam catchment (Kasahori dam; approx. 70 km2) in Niigata, Japan. The results exhibited that the ensemble flood forecasting can indicate the necessity of flood control operation and emergency flood operation with the occurrence probability and a lead time (e.g. 12 hours). Thus, the ensemble flood forecasting may be able to inform us the necessity of the early evacuation of the inhabitant living downstream of the dam e.g. half day before the occurrence. On the other hand, the results also showed that the exact forecasting to reproduce the discharge hydrograph several hours before the occurrence is yet difficult, and some optimization technique is necessary such as the selection of the good ensemble members.

scholarly journals Effects of streamflow isotope sampling strategies on the calibration of a tracer‐aided rainfall‐runoff model

2021 ◽  
Author(s):  
Jamie Lee Stevenson ◽  
Christian Birkel ◽  
Aaron J. Neill ◽  
Doerthe Tetzlaff ◽  
Chris Soulsby
Keyword(s):  
Sampling Strategies ◽  
Rainfall Runoff ◽  
Rainfall Runoff Model ◽  
Runoff Model
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