scholarly journals Application of a rainfall-runoff model in estimating flood peaks for selected small natural drainage basins in Texas

1977 ◽  
Author(s):  
B.C. Massey ◽  
Elmer E. Schroeder
Keyword(s):  
Rainfall Runoff ◽  
Drainage Basins ◽  
Flood Peaks ◽  
Rainfall Runoff Model ◽  
Runoff Model

Sensitivity analysis of Xinanjiang rainfall–runoff model parameters: a case study in Lianghui, Zhejiang province, China

2012 ◽  
Vol 43 (1-2) ◽  
pp. 123-134 ◽  
Author(s):  
Danrong Zhang ◽  
Liru Zhang ◽  
Yiqing Guan ◽  
Xi Chen ◽  
Xinfang Chen
Keyword(s):  
Water Balance ◽  
Rainfall Runoff ◽  
Parameter Calibration ◽  
Drainage Basins ◽  
Xinanjiang Model ◽  
Rainfall Runoff Model ◽  
Sensitive Parameters ◽  
Runoff Model ◽  
Runoff Routing ◽  
Balance Parameter

The Xinanjiang rainfall–runoff model has been successfully applied in many humid and sub-humid areas in China since 1973. The wide application is due to the simple model structure, the clear physical meaning of the parameters and the well-defined model calibration procedure. However, due to a data scarcity problem and short runoff concentration time, its applications to small drainage basins are difficult. Therefore, we investigate the model application in Lianghui, a small drainage basin of Zhejiang province in China. By using generalized likelihood uncertainty estimation (GLUE) methodology, the sensitivity of parameters of Xinanjiang model was investigated. The data clearly showed that equifinality phenomenon was evident in both water balance parameter calibration and runoff routing parameter calibration procedures. The results showed that K (evapotranspiration conversion coefficient), Cs (recession constant in channel system) and Sm (areal free water storage capacity of surface soil) are the most sensitive parameters for the water balance parameter calibration while Cs, Sm and Wm (mean area tension water capacity) are the most sensitive parameters for runoff routing parameter calibration. The conclusion is favourable for understanding parameters of Xinanjiang model in order to provide valuable scientific information for simulating hydrological processes in small drainage basins.

scholarly journals A dynamic river network method for the prediction of floods using a parsimonious rainfall-runoff model

2019 ◽  
Vol 51 (2) ◽  
pp. 146-168 ◽  
Author(s):  
Aynalem Tassachew Tsegaw ◽  
Thomas Skaugen ◽  
Knut Alfredsen ◽  
Tone M. Muthanna
Keyword(s):  
Relative Error ◽  
Flood Forecasting ◽  
River Network ◽  
Rainfall Runoff ◽  
Design Flood ◽  
Study Results ◽  
Network Method ◽  
Flood Peaks ◽  
Rainfall Runoff Model ◽  
Runoff Model

Abstract Floods are one of the major climate-related hazards and cause casualties and substantial damage. Accurate and timely flood forecasting and design flood estimation are important to protect lives and property. The Distance Distribution Dynamic (DDD) is a parsimonious rainfall-runoff model which is being used for flood forecasting at the Norwegian flood forecasting service. The model, like many other models, underestimates floods in many cases. To improve the flood peak prediction, we propose a dynamic river network method into the model. The method is applied for 15 catchments in Norway and tested on 91 flood peaks. The performance of DDD in terms of KGE and BIAS is identical with and without dynamic river network, but the relative error (RE) and mean absolute relative error (MARE) of the simulated flood peaks are improved significantly with the method. The 0.75 and 0.25 quantiles of the RE are reduced from 41% to 23% and from 22% to 1%, respectively. The MARE is reduced from 32.9% to 15.7%. The study results also show that the critical support area is smaller in steep and bare mountain catchments than flat and forested catchments.

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

scholarly journals Performance Evaluation of a Two-Parameters Monthly Rainfall-Runoff Model in the Southern Basin of Thailand

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1226
Author(s):  
Pakorn Ditthakit ◽  
Sirimon Pinthong ◽  
Nureehan Salaeh ◽  
Fadilah Binnui ◽  
Laksanara Khwanchum ◽  
...  
Keyword(s):  
Exchange Rate ◽  
Rainfall Runoff ◽  
Management Planning ◽  
Runoff Variation ◽  
Groundwater Exchange ◽  
Monthly Runoff ◽  
Rainfall Runoff Model ◽  
Two Parameters ◽  
Runoff Model

Accurate monthly runoff estimation is crucial in water resources management, planning, and development, preventing and reducing water-related problems, such as flooding and droughts. This article evaluates the monthly hydrological rainfall-runoff model’s performance, the GR2M model, in Thailand’s southern basins. The GR2M model requires only two parameters: production store (X1) and groundwater exchange rate (X2). Moreover, no prior research has been reported on its application in this region. The 37 runoff stations, which are located in three sub-watersheds of Thailand’s southern region, namely; Thale Sap Songkhla, Peninsular-East Coast, and Peninsular-West Coast, were selected as study cases. The available monthly hydrological data of runoff, rainfall, air temperature from the Royal Irrigation Department (RID) and the Thai Meteorological Department (TMD) were collected and analyzed. The Thornthwaite method was utilized for the determination of evapotranspiration. The model’s performance was conducted using three statistical indices: Nash–Sutcliffe Efficiency (NSE), Correlation Coefficient (r), and Overall Index (OI). The model’s calibration results for 37 runoff stations gave the average NSE, r, and OI of 0.657, 0.825, and 0.757, respectively. Moreover, the NSE, r, and OI values for the model’s verification were 0.472, 0.750, and 0.639, respectively. Hence, the GR2M model was qualified and reliable to apply for determining monthly runoff variation in this region. The spatial distribution of production store (X1) and groundwater exchange rate (X2) values was conducted using the IDW method. It was susceptible to the X1, and X2 values of approximately more than 0.90, gave the higher model’s performance.

Effects of conditional parameterization on performance of rainfall-runoff model regarding hydrologic non-stationarity

2012 ◽  
Vol 26 (26) ◽  
pp. 3953-3961 ◽  
Author(s):  
Jiangmei Luo ◽  
Enli Wang ◽  
Shuanghe Shen ◽  
Hongxing Zheng ◽  
Yongqiang Zhang
Keyword(s):  
Rainfall Runoff ◽  
Rainfall Runoff Model ◽  
Runoff Model

Improvement of Nonlinear Rainfall-Runoff Model

1982 ◽  
Vol 108 (7) ◽  
pp. 813-822
Author(s):  
Otto J. Helweg ◽  
Jaime Amorocho ◽  
Ralph H. Finch
Keyword(s):  
Rainfall Runoff ◽  
Rainfall Runoff Model ◽  
Runoff Model
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