Application of IHACRES rainfall-runoff model to the Wadi Dhuliel arid catchment, Jordan

2011 ◽  
Vol 2 (1) ◽  
pp. 56-71 ◽  
Author(s):  
Eyad H. Abushandi ◽  
Broder J. Merkel
Keyword(s):  
Daily Basis ◽  
Calibration Data ◽  
Storm Events ◽  
Rainfall Runoff ◽  
Antecedent Soil Moisture ◽  
North East ◽  
Flood Estimation ◽  
Rainfall Runoff Model ◽  
Moisture Conditions ◽  
Parameter Values

With increasing stress on water resources in Jordan, application of rainfall-runoff models can be part of the solution to manage and sustain the water sector. In this paper, the metric conceptual IHACRES model is applied to the Wadi Dhuliel arid catchment, north-east Jordan. Rainfall-runoff data from 19 storm events during 1986 to 1992 have been used in this study. Flood estimation was performed on the basis of daily scales and storm events scales. The model was extended for snowfall in order to cope with such extreme events. Although the best performance of the IHACRES model on a daily basis is poor, the performance on storm events scale showed a good agreement between observed and simulated streamflow. Apart from model parameter values, the principal reasons for IHACRES model success in this region are thought to be based on antecedent soil moisture conditions, rainfall duration and rainfall intensity before and during each storm. The model outputs were likely to be sensitive when the monitored flood was relatively small. The optimum parameter values were influenced by the length of calibration data and event specific changes.

scholarly journals Flood Estimation in Ungauged Catchment Using ENKI Simulation: A Case Study in Norway

10.29007/hrpj ◽  
2018 ◽  
Author(s):  
Yueyang Chen ◽  
Oddbjørn Bruland ◽  
Tiejian Li
Keyword(s):  
Efficiency Index ◽  
Rainfall Runoff ◽  
Ungauged Catchments ◽  
Ungauged Catchment ◽  
Flood Estimation ◽  
Model Efficiency ◽  
Rainfall Runoff Model ◽  
Parameter Values ◽  
Runoff Model

This paper deals with flood estimation in ungauged catchment using continuous rainfall-runoff model. The rainfall-runoff model used in this study is developed based on the ENKI hydrological framework. In this study, flood estimation in ungauged catchment is based on transfer of parameter values from nearby station. The catchment used in this study to test the suitability of the ENKI system in flood estimation of ungauged catchment is the Gaula catchment located in Norway. This catchment has three main sub-catchments where flow records are available. The ENKI system is calibrated for each sub-catchment. In order to test its suitability in flood estimation, the average of the parameter set obtained from any of the two sub-catchments is used in the remaining sub-catchments. The performance of the ENKI system in flood estimation is evaluated in terms of the Nash–Sutcliffe (NSE) model efficiency index and the model ability to simulate the daily observed Annual Maximum Series (AMS). The result of this study shows that the ENKI framework has considerable potential in flood estimation in ungauged catchments.

scholarly journals A reliable rainfall–runoff model for flood forecasting: review and application to a semi-urbanized watershed at high flood risk in Italy

2016 ◽  
Vol 48 (3) ◽  
pp. 726-740 ◽  
Author(s):  
Daniele Masseroni ◽  
Alessio Cislaghi ◽  
Stefania Camici ◽  
Christian Massari ◽  
Luca Brocca
Keyword(s):  
Flood Risk ◽  
Climatic Conditions ◽  
Rainfall Runoff ◽  
Number Of Factors ◽  
Wide Range ◽  
Median Volume ◽  
Flood Estimation ◽  
High Flood ◽  
Rainfall Runoff Model ◽  
Flooding Events

Many rainfall–runoff (RR) models are available in the scientific literature. Selecting the best structure and parameterization for a model is not straightforward and depends on a broad number of factors, including climatic conditions, catchment characteristics, temporal/spatial resolution and model objectives. In this study, the RR model ‘Modello Idrologico Semi-Distribuito in continuo’ (MISDc), mainly developed for flood simulation in Mediterranean basins, was tested on the Seveso basin, which is stressed several times a year by flooding events mainly caused by excessive urbanization. The work summarizes a compendium of the MISDc applications over a wide range of catchments in European countries and then it analyses the performances over the Seveso basin. The results show a good fit behaviour during both the calibration and the validation periods with a Nash–Sutcliffe coefficient index larger than 0.9. Moreover, the median volume and peak discharge errors calculated on several flood events were less than 25%. In conclusion, we can be assured that the reliability and computational speed could make the MISDc model suitable for flood estimation in many catchments of different geographical contexts and land use characteristics. Moreover, MISDc will also be useful for future support of real-time decision-making for flood risk management in the Seveso basin.

scholarly journals The HYDROMED model and its application to semi-arid Mediterranean catchments with hill reservoirs 2: Rainfall-runoff model applications to three Mediterranean hill reservoirs

2001 ◽  
Vol 5 (4) ◽  
pp. 554-562 ◽  
Author(s):  
R. Ragab ◽  
D. Moidinis ◽  
J. Albergel ◽  
J. Khouri ◽  
A. Drubi ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Model Performance ◽  
Limited Information ◽  
Rainfall Runoff ◽  
Significant Events ◽  
Reliable Parameter ◽  
Rainfall Runoff Model ◽  
Parameter Values ◽  
Runoff Model

Abstract. The objective of this work was to assess the performance of the newly developed HYDROMED model. Three catchments with hill reservoirs were selected. They are El-Gouazine and Kamech in Tunisia and Es Sindiany in Syria. The rainfall, the spillway flow and volume of water in the reservoirs were used as input to the model. Events that generated spillway flow were preferred for calibration. The results confirmed that the HYDROMED model is capable of reproducing the runoff volume at all the three sites. In calibrating single events, the model performance was high as measured by the Nash-Sutcliffe criterion for goodness of fit. In some events this value was as high as 98%. In simulation mode, the highest Nash-Sutcliffe criterion value was close to 70% in the El-Gouazine and Kamech catchments and close to 50% in the Es Sindiany catchment. Given the limited information available, especially on the unrecorded releases in the three catchments, the hydrological impact of site geology (e.g. Kamech), the unrecorded operator intervention during the spillway flow (e.g. Es Sindiany) and other unaccounted factors (e.g siltation, evaporation, etc.), these results are by and large very encouraging. However, they could be further improved as and when more information on the unrecorded parameters becomes available. Additionally, the results of this work highlighted the need for long term records with a large number of significant events that are able to generate spillway flow to obtain more consistent and reliable parameter values. It also highlights the need for more accurately recorded releases for irrigation and other uses. As these results are encouraging, more tests on those three and other sites are planned. Keywords: HYDROMED, rainfall-runoff model, Mediterranean, conceptual model

scholarly journals Preliminary Study of Computational Time Steps in a Physically Based Distributed Rainfall–Runoff Model

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1269 ◽  
Author(s):  
Yun Choi ◽  
Mun-Ju Shin ◽  
Kyung Kim
Keyword(s):  
Optimal Parameter ◽  
Computational Time ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Stream Network ◽  
Time Step ◽  
Simulation Results ◽  
Rainfall Runoff Model ◽  
Parameter Values ◽  
Runoff Model

The choice of the computational time step (dt) value and the method for setting dt can have a bearing on the accuracy and performance of a simulation, and this effect has not been comprehensively researched across different simulation conditions. In this study, the effects of the fixed time step (FTS) method and the automatic time step (ATS) method on the simulated runoff of a distributed rainfall–runoff model were compared. The results revealed that the ATS method had less peak flow variability than the FTS method for the virtual catchment. In the FTS method, the difference in time step had more impact on the runoff simulation results than the other factors such as differences in the amount of rainfall, the density of the stream network, or the spatial resolution of the input data. Different optimal parameter values according to the computational time step were found when FTS and ATS were used in a real catchment, and the changes in the optimal parameter values were smaller in ATS than in FTS. The results of our analyses can help to yield reliable runoff simulation results.

Multidimensional context for extreme analysis of daily streamflow, rainfall and accumulated rainfall across USA

2020 ◽  
Author(s):  
Maria Nezi ◽  
Ioannis Tsoukalas ◽  
Charalampos Ntigkakis ◽  
Andreas Efstratiadis
Keyword(s):  
Soil Moisture ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Annual Rainfall ◽  
Event Analysis ◽  
Antecedent Soil Moisture ◽  
Daily Streamflow ◽  
Accumulated Rainfall ◽  
Moisture Conditions ◽  
Parameter Values

<p>Statistical analysis of rainfall and runoff extremes plays a crucial role in hydrological design and flood risk management. Usually this analysis is performed separately for the two processes of interest, thus ignoring their dependencies, which appear at multiple temporal scales. Actually, the generation of a flood strongly depends on soil moisture conditions, which in turn depends on past rainfall. Using daily rainfall and runoff data from about 400 catchments in USA, retrieved from the MOPEX repository, we investigate the statistical behavior of the corresponding annual rainfall and streamflow maxima, also accounting for the influence of antecedent soil moisture conditions. The latter are quantified by means of accumulated daily rainfall at various aggregation scales (i.e., from 5 up to 30 days) before each extreme rainfall and streamflow event. Analysis of maxima is employed by fitting the Generalized Extreme Value (GEV) distribution, using the L-moments method for extracting the associated parameters (shape, scale, location). Significant attention is paid for ensuring statistically consistent estimations of the shape parameter, which is empirically adjusted in order to minimize the influence of sample uncertainty. Finally, we seek for the possible correlations among the derived parameter values and hydroclimatic characteristics of the studied basins, and also depict their spatial distribution across USA.</p>

scholarly journals Effects of antecedent soil moisture on runoff modeling in small semiarid watersheds of southeastern Arizona

2011 ◽  
Vol 15 (10) ◽  
pp. 3171-3179 ◽  
Author(s):  
Y. Zhang ◽  
H. Wei ◽  
M. A. Nearing
Keyword(s):  
Soil Moisture ◽  
Standard Deviation ◽  
Soil Layer ◽  
Arid Environment ◽  
Storm Events ◽  
Runoff Generation ◽  
Antecedent Soil Moisture ◽  
Small Watersheds ◽  
Runoff Modeling ◽  
Moisture Conditions

Abstract. This study presents unique data on the effects of antecedent soil moisture on runoff generation in a semi-arid environment, with implications for process-based modeling of runoff. The data were collected from four small watersheds measured continuously from 2002 through 2010 in an environment where evapo-transpiration approaches 100% of the infiltrated water on the hillslopes. Storm events were generally intense and of short duration, and antecedent volumetric moisture conditions were dry, with an average in the upper 5 cm soil layer over the nine year period of 8% and a standard deviation of 3%. Sensitivity analysis of the model showed an average of 0.05 mm change in runoff for each 1% change in soil moisture, indicating an approximate 0.15 mm average variation in runoff accounted for by the 3% standard deviation of measured antecedent soil moisture. This compared to a standard deviation of 4.7 mm in the runoff depths for the measured events. Thus the low variability of soil moisture in this environment accounts for a relative lack of importance of storm antecedent soil moisture for modeling the runoff. Runoff characteristics simulated with a nine year average of antecedent soil moisture were statistically identical to those simulated with measured antecedent soil moisture, indicating that long term average antecedent soil moisture could be used as a substitute for measured antecedent soil moisture for runoff modeling of these watersheds. We also found no significant correlations between measured runoff ratio and antecedent soil moisture in any of the four watersheds.

scholarly journals Regionalization of a Rainfall-Runoff Model: Limitations and Potentials

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2257 ◽  
Author(s):  
Jung-Hun Song ◽  
Younggu Her ◽  
Kyo Suh ◽  
Moon-Seong Kang ◽  
Hakkwan Kim
Keyword(s):  
Hydrological Modeling ◽  
Rainfall Runoff ◽  
Tank Model ◽  
Statistical Relationships ◽  
Function Selection ◽  
Rainfall Runoff Model ◽  
Parameter Values ◽  
Runoff Model ◽  
Selection Of

Regionalized lumped rainfall-runoff (RR) models have been widely employed as a means of predicting the streamflow of an ungauged watershed because of their simple yet effective simulation strategies. Parameter regionalization techniques relate the parameter values of a model calibrated to the observations of gauged watersheds to the geohydrological characteristics of the watersheds. Thus, the accuracy of regionalized models is dependent on the calibration processes, as well as the structure of the model used and the quality of the measurements. In this study, we have discussed the potentials and limitations of hydrological model parameter regionalization to provide practical guidance for hydrological modeling of ungauged watersheds. This study used a Tank model as an example model and calibrated its parameters to streamflow observed at the outlets of 39 gauged watersheds. Multiple regression analysis identified the statistical relationships between calibrated parameter values and nine watershed characteristics. The newly developed regional models provided acceptable accuracy in predicting streamflow, demonstrating the potential of the parameter regionalization method. However, uncertainty associated with parameter calibration processes was found to be large enough to affect the accuracy of regionalization. This study demonstrated the importance of objective function selection of the RR model regionalization.

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