scholarly journals A rainfall-runoff simulation model for estimation of flood peaks for small drainage basins

1972 ◽  
Author(s):  
D.R. Dawdy ◽  
Robert W. Lichty ◽  
James M. Bergmann
2021 ◽  
Vol 930 (1) ◽  
pp. 012040
Author(s):  
G A P Eryani ◽  
I M S Amerta ◽  
M W Jayantari

Abstract In water resource planning, information on water availability is needed. Nowadays, data on water availability is still difficult to obtain. With technology in the form of a rainfall-runoff simulation model that can predict water availability in the Unda watershed. It can add information about the potential for water in the Unda watershed. It can be used to prepare water resources management in the Unda watershed so that the existing potential can be used sustainably. Based on the rainfall simulation model results in the Unda watershed, it can be concluded that after running the initial model and calibration. The results are obtained R2 value was 0.68 and increased by 9.81% to 0.754. Both the initial model and the calibration model show an efficient R2 value, NASH value increases by 49.93% to 0.713, which includes satisfactory criteria, RMSE value of 1.135 and decreased by 49.47% to 0.758, and the PBIAS value was 44.70% which was classified as unsatisfactory and decreased from 80.24% to 24.80% at the time of calibration which was classified as satisfactory. In general, the overall simulation results are quite good for representing the watershed’s efficient hydrological process.


2020 ◽  
Vol 10 (4) ◽  
pp. 183-190
Author(s):  
Salil Sahu, et al., Salil Sahu, et al., ◽  

2021 ◽  
Vol 5 (1) ◽  
pp. 33-37
Author(s):  
Shimelis Sishah

Understanding hydrological behavior is an important part of effective watershed management and planning. Runoff resulted from rainfall is a component of hydrological behavior that is needed for efficient water resource planning. In this paper, GIS based SCS-CN runoff simulation model was applied to estimate rainfall runoff in Awash river basin. Global Curve Number (GCN250), Maximum Soil Water Retention (S) and Rainfall was used as an input for SCS-CN runoff simulation model. The final surface runoff values for the Awash river basin were generated on the basis of total annual rainfall and maximum soil water retention potential (S) of the year 2020. Accordingly, a runoff variation that range from 83.95 mm/year to a maximum of 1,416.75 mm/year were observed in the study region. Conversely, recently developed Global Curve Number (GCN250) data was tested with Pearson correlation coefficient to be used as an input for SCS-CN runoff simulation model. In doing so, predicted runoff generated in SCS-CN using GCN250 as a model input was validated with observed runoff obtained from station gauges in the study region. The results of validation show that, predicted runoff was well correlated with observed runoff with correlation coefficient of 0.9253. From this stand point, it is observed that the new GCN250 data can be used as an input for SCS-CN model to estimate rainfall runoff at basin level. Furthermore, correlation analysis was performed to explain the relationship between mean annual rainfall and surface runoff. The relationship between these two variables indicates a strong linear relationship with correlation coefficient of 0.9873.


1998 ◽  
Vol 37 (11) ◽  
pp. 155-162 ◽  
Author(s):  
B. Maul-Kötter ◽  
Th. Einfalt

Continuous raingauge measurements are an important input variable for detailed rainfall-runoff simulation. In North Rhine-Westphalia, more than 150 continuous raingauges are used for local hydrological design through the use of site specific rainfall runoff models. Requiring gap-free data, the State Environmental Agency developed methods to use a combination of daily measurements and neighbouring continuous measurements for filling periods of lacking data in a given raindata series. The objective of such a method is to obtain plausible data for water balance simulations. For more than 3500 station years the described methodology has been applied.


1988 ◽  
Vol 114 (4) ◽  
pp. 399-413 ◽  
Author(s):  
Alfred Garcia ◽  
Wesley P. James

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