scholarly journals Continuous modelling of the Bouregreg watershed (Morocco) using the HEC-HMS model

2021 ◽  
Vol 314 ◽  
pp. 05001
Author(s):  
Oussama Laassilia ◽  
Driss Ouazar ◽  
Ahmed Bouziane ◽  
Moulay Driss Hasnaoui
Keyword(s):  
Annual Variation ◽  
Hydrological Model ◽  
Deep Understanding ◽  
Rainfall Runoff ◽  
Unit Hydrograph ◽  
Soil Moisture Accounting ◽  
Change Impact ◽  
Loss Method ◽  
Acceptable Agreement ◽  
Simulated Flow

A deep understanding of the rainfall-runoff mechanism is essential to estimate the runoff generated in a given basin. In this regard, this paper aims to develop a continuous hydrological model of the Bouregreg watershed. The objective of this modelling is to evaluate the inflow to the Sidi Mohamed Ben Abdellah (SMBA) dam, located at the outlet of this basin. To this end, using the HEC-HMS model, the Soil Moisture Accounting (SMA) Loss Method was used to model infiltration losses. The SCS Unit hydrograph (SCS UH) and the Recession method were chosen as transform model and baseflow model, respectively. As a result, the comparison shows an acceptable agreement between observed and simulated flow in terms of streamflow distribution and peak values (NSE=0.57, R2=0.58). During validation, the model retained its ability to sufficiently reproduce the rainfall-runoff mechanism of the studied basin with a slight overestimation of peaks (NSE=0.61, R2=0.60). This study allows to assess and predict the inter-annual and intra-annual variation of the SMBA dam reservoir’ inflows, and therefore to forecast the climate change impact on this basin.

scholarly journals The February 2000 floods on the Sabie River, South Africa: an examination of their magnitude and frequency

Koedoe ◽  
2001 ◽  
Vol 44 (1) ◽  
Author(s):  
G.L. Heritage ◽  
B.P. Moon ◽  
G.P. Jewitt ◽  
A.R.G. Large ◽  
M. Rountree
Keyword(s):  
Cross Sections ◽  
National Park ◽  
Hydrological Model ◽  
Peak Flow ◽  
Kruger National Park ◽  
Rainfall Runoff ◽  
Major Tributary ◽  
Flood Flow ◽  
Simulated Flow ◽  
Channel Type

The floods that affected much of Southern Africa in February 2000 have been reported as the largest in living memory by many observers. However, the force of the floods damaged the majority of the gauging stations located on the affected rivers, many of which were not constructed to measure flows of such a magnitude. This paper presents an estimation of the peak flood discharge on 6 February 2000 for the bedrock influenced Sabie River in the Kruger National Park, by simulating the hydraulic and geometric characteristics of the peak flow and relating these to the roughness character of the channel. Peak water surface slope data in the form of strandline measurements at channel type breaks along the river were collected for six sites along the Sabie River within the Kruger National Park. Flood conditions within each channel type were considered to approximate to uniform flow. The cross-sections are located between major tributary inputs allowing for approximate sub-catchment flow contributions to be estimated. The results indicate that the flow peaked at around 3000 mVs at the Kruger Gate entrance to the Kruger National Park, increasing to approximately 5500mVs at Skukuza and 7000 mVs at Lower Sabie close to the Mozambique border following inputs from the Sand River sub-catchment. These estimates compare well with the simulated rainfall runoff total of 4300 mVs at Skukuza, however, precipitation inputs over the lowveld appear to indicate that the discharge only rises to 4950 mmVs at Lower Sabie. A flood flow of this magnitude has never been experienced based on the simulated flow data generated by the ACRU hydrological model calibrated against measured flows therefore suggesting a return period in excess of the 60 years of record.

scholarly journals Infiltration Losses Calculated for the Flash Flood in the Upper Catchment of Geru River, Galaţi County, Romania

2016 ◽  
Vol 10 (2) ◽  
pp. 219-234
Author(s):  
Isabela Balan ◽  
Loredana Crenganiş ◽  
Flaviana Corduneanu ◽  
Claudiu Pricop ◽  
Loredana Andreea Popoiu
Keyword(s):  
Mathematical Modelling ◽  
Input Data ◽  
Flash Flood ◽  
Rainfall Runoff ◽  
Unit Hydrograph ◽  
Phase Errors ◽  
Loss Method ◽  
Hydrometric Station ◽  
The Village ◽  
Amplitude And Phase Errors

Abstract MIKE software created by Danish Institute of Hydraulics can be used to perform mathematical modelling of rainfall-runoff process on the hillslopes, resulting in a runoff hydrograph in the closing section of a catchment. The software includes a unitary hydrograph method - UHM in the hydrological module Rainfall - Runoff. Excess rainfall is routed to the river and transited through unit hydrograph method. The model divides the flood generating precipitation in excess rainfall (net rainfall) and losses (infiltration). This paper analyzes data from the flash flood that occurred between the 11th and 13th of September 2013 in the upper catchment of the river Geru. The catchment chosen for study, is controlled by the hydrometric station located in the village Cudalbi. Simulations of this flash flood were performed with MIKE by DHI –UHM software, alternatively using as input data the precipitations recorded by AHSS (Automated Hydrological Sensor Station) Cudalbi and radar precipitations generated by ROFFG (Romanian Flash Flood Guidance) software system in ArcGIS module for determining the areas affected by flash floods. The Unitary Hydrograph Method - UHM from the hydrological module Rainfall – Runoff calculates excess rainfall and determines infiltration losses by four methods. For each set of input data, the four methods for calculating infiltration losses were subsequently used. The comparison between the results highlights that the amplitude and phase errors for the maximum discharge are smaller when the model uses for simulation radar precipitations as input data, and calculates infiltration losses with the Proportional Loss method. This method reproduces with a better accuracy the peaks of the discharge hydrograph. The model can be used in the future to forecast a discharge hydrograph based on estimated radar precipitations in the catchment

scholarly journals Rainfall-Runoff Modeling Using the HEC-HMS Model for the Al-Adhaim River Catchment, Northern Iraq

Hydrology ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 58
Author(s):  
Ahmed Naseh Ahmed Hamdan ◽  
Suhad Almuktar ◽  
Miklas Scholz
Keyword(s):  
Geographical Information Systems ◽  
Hydrological Model ◽  
Daily Rainfall ◽  
Curve Number ◽  
Geographical Information ◽  
Coefficient Of Determination ◽  
Rainfall Runoff ◽  
Time Step ◽  
River Catchment ◽  
Northern Iraq

It has become necessary to estimate the quantities of runoff by knowing the amount of rainfall to calculate the required quantities of water storage in reservoirs and to determine the likelihood of flooding. The present study deals with the development of a hydrological model named Hydrologic Engineering Center (HEC-HMS), which uses Digital Elevation Models (DEM). This hydrological model was used by means of the Geospatial Hydrologic Modeling Extension (HEC-GeoHMS) and Geographical Information Systems (GIS) to identify the discharge of the Al-Adhaim River catchment and embankment dam in Iraq by simulated rainfall-runoff processes. The meteorological models were developed within the HEC-HMS from the recorded daily rainfall data for the hydrological years 2015 to 2018. The control specifications were defined for the specified period and one day time step. The Soil Conservation Service-Curve number (SCS-CN), SCS Unit Hydrograph and Muskingum methods were used for loss, transformation and routing calculations, respectively. The model was simulated for two years for calibration and one year for verification of the daily rainfall values. The results showed that both observed and simulated hydrographs were highly correlated. The model’s performance was evaluated by using a coefficient of determination of 90% for calibration and verification. The dam’s discharge for the considered period was successfully simulated but slightly overestimated. The results indicated that the model is suitable for hydrological simulations in the Al-Adhaim river catchment.

scholarly journals SHETRAN and HEC HMS Model Evaluation for Runoff and Soil Moisture Simulation in the Jičinka River Catchment (Czech Republic)

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 872
Author(s):  
Vesna Đukić ◽  
Ranka Erić
Keyword(s):  
Soil Moisture ◽  
Czech Republic ◽  
Hydrological Model ◽  
Flash Flood ◽  
Model Performance ◽  
Rainfall Runoff ◽  
The Czech Republic ◽  
River Catchment ◽  
Hydrological Variable ◽  
Model Structures

Due to the improvement of computation power, in recent decades considerable progress has been made in the development of complex hydrological models. On the other hand, simple conceptual models have also been advanced. Previous studies on rainfall–runoff models have shown that model performance depends very much on the model structure. The purpose of this study is to determine whether the use of a complex hydrological model leads to more accurate results or not and to analyze whether some model structures are more efficient than others. Different configurations of the two models of different complexity, the Système Hydrologique Européen TRANsport (SHETRAN) and Hydrologic Modeling System (HEC-HMS), were compared and evaluated in simulating flash flood runoff for the small (75.9 km2) Jičinka River catchment in the Czech Republic. The two models were compared with respect to runoff simulations at the catchment outlet and soil moisture simulations within the catchment. The results indicate that the more complex SHETRAN model outperforms the simpler HEC HMS model in case of runoff, but not for soil moisture. It can be concluded that the models with higher complexity do not necessarily provide better model performance, and that the reliability of hydrological model simulations can vary depending on the hydrological variable under consideration.

scholarly journals Derivation of S-Curve from Oscillatory Hydrograph Using Digital Filter

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1456
Author(s):  
Kee-Won Seong ◽  
Jang Hyun Sung
Keyword(s):  
Digital Filter ◽  
Model Performance ◽  
Performance Criteria ◽  
Rainfall Runoff ◽  
Small Watershed ◽  
Unit Hydrograph ◽  
Time To Peak ◽  
S Curve ◽  
And Performance ◽  
Smooth Data

An oscillatory S-curve causes unexpected fluctuations in a unit hydrograph (UH) of desired duration or an instantaneous UH (IUH) that may affect the constraints for hydrologic stability. On the other hand, the Savitzky–Golay smoothing and differentiation filter (SG filter) is a digital filter known to smooth data without distorting the signal tendency. The present study proposes a method based on the SG filter to cope with oscillatory S-curves. Compared to previous conventional methods, the application of the SG filter to an S-curve was shown to drastically reduce the oscillation problems on the UH and IUH. In this method, the SG filter parameters are selected to give the minimum influence on smoothing and differentiation. Based on runoff reproduction results and performance criteria, it appears that the SG filter performed both smoothing and differentiation without the remarkable variation of hydrograph properties such as peak or time-to peak. The IUH, UH, and S-curve were estimated using storm data from two watersheds. The reproduced runoffs showed high levels of model performance criteria. In addition, the analyses of two other watersheds revealed that small watershed areas may experience scale problems. The proposed method is believed to be valuable when error-prone data are involved in analyzing the linear rainfall–runoff relationship.

scholarly journals The importance of hydrological uncertainty assessment methods in climate change impact studies

2014 ◽  
Vol 18 (8) ◽  
pp. 3301-3317 ◽  
Author(s):  
M. Honti ◽  
A. Scheidegger ◽  
C. Stamm
Keyword(s):  
Climate Change ◽  
Climate Change Impact ◽  
Hydrological Model ◽  
Uncertainty Assessment ◽  
Assessment Method ◽  
Calibration Data ◽  
Relative Importance ◽  
Impact Studies ◽  
Uncertainty Sources ◽  
Change Impact

Abstract. Climate change impact assessments have become more and more popular in hydrology since the middle 1980s with a recent boost after the publication of the IPCC AR4 report. From hundreds of impact studies a quasi-standard methodology has emerged, to a large extent shaped by the growing public demand for predicting how water resources management or flood protection should change in the coming decades. The "standard" workflow relies on a model cascade from global circulation model (GCM) predictions for selected IPCC scenarios to future catchment hydrology. Uncertainty is present at each level and propagates through the model cascade. There is an emerging consensus between many studies on the relative importance of the different uncertainty sources. The prevailing perception is that GCM uncertainty dominates hydrological impact studies. Our hypothesis was that the relative importance of climatic and hydrologic uncertainty is (among other factors) heavily influenced by the uncertainty assessment method. To test this we carried out a climate change impact assessment and estimated the relative importance of the uncertainty sources. The study was performed on two small catchments in the Swiss Plateau with a lumped conceptual rainfall runoff model. In the climatic part we applied the standard ensemble approach to quantify uncertainty but in hydrology we used formal Bayesian uncertainty assessment with two different likelihood functions. One was a time series error model that was able to deal with the complicated statistical properties of hydrological model residuals. The second was an approximate likelihood function for the flow quantiles. The results showed that the expected climatic impact on flow quantiles was small compared to prediction uncertainty. The choice of uncertainty assessment method actually determined what sources of uncertainty could be identified at all. This demonstrated that one could arrive at rather different conclusions about the causes behind predictive uncertainty for the same hydrological model and calibration data when considering different objective functions for calibration.

scholarly journals Fuzzy committees of specialized rainfall-runoff models: further enhancements and tests

2013 ◽  
Vol 17 (11) ◽  
pp. 4441-4451 ◽  
Author(s):  
N. Kayastha ◽  
J. Ye ◽  
F. Fenicia ◽  
V. Kuzmin ◽  
D. P. Solomatine
Keyword(s):  
Hydrological Model ◽  
Weighting Function ◽  
Hydrological Models ◽  
Membership Functions ◽  
Rainfall Runoff ◽  
Objective Functions ◽  
Hydrological Regimes

Abstract. Often a single hydrological model cannot capture the details of a complex rainfall–runoff relationship, and a possibility here is building specialized models to be responsible for a particular aspect of this relationship and combining them to form a committee model. This study extends earlier work of using fuzzy committees to combine hydrological models calibrated for different hydrological regimes – by considering the suitability of the different weighting function for objective functions and different class of membership functions used to combine the specialized models and compare them with the single optimal models.

scholarly journals Benefits and limitations of data assimilation for discharge forecasting using an event-based rainfall–runoff model

2013 ◽  
Vol 13 (3) ◽  
pp. 583-596 ◽  
Author(s):  
M. Coustau ◽  
S. Ricci ◽  
V. Borrell-Estupina ◽  
C. Bouvier ◽  
O. Thual
Keyword(s):  
Data Assimilation ◽  
Hydrological Model ◽  
Peak Discharge ◽  
State Variables ◽  
Rainfall Runoff ◽  
Discharge Data ◽  
Southern France ◽  
Flood Peak ◽  
Event Based ◽  
The Impact

Abstract. Mediterranean catchments in southern France are threatened by potentially devastating fast floods which are difficult to anticipate. In order to improve the skill of rainfall-runoff models in predicting such flash floods, hydrologists use data assimilation techniques to provide real-time updates of the model using observational data. This approach seeks to reduce the uncertainties present in different components of the hydrological model (forcing, parameters or state variables) in order to minimize the error in simulated discharges. This article presents a data assimilation procedure, the best linear unbiased estimator (BLUE), used with the goal of improving the peak discharge predictions generated by an event-based hydrological model Soil Conservation Service lag and route (SCS-LR). For a given prediction date, selected model inputs are corrected by assimilating discharge data observed at the basin outlet. This study is conducted on the Lez Mediterranean basin in southern France. The key objectives of this article are (i) to select the parameter(s) which allow for the most efficient and reliable correction of the simulated discharges, (ii) to demonstrate the impact of the correction of the initial condition upon simulated discharges, and (iii) to identify and understand conditions in which this technique fails to improve the forecast skill. The correction of the initial moisture deficit of the soil reservoir proves to be the most efficient control parameter for adjusting the peak discharge. Using data assimilation, this correction leads to an average of 12% improvement in the flood peak magnitude forecast in 75% of cases. The investigation of the other 25% of cases points out a number of precautions for the appropriate use of this data assimilation procedure.

scholarly journals Calibration of Conceptual Rainfall-Runoff Models Using Global Optimization

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Chao Zhang ◽  
Ru-bin Wang ◽  
Qing-xiang Meng
Keyword(s):  
Global Optimization ◽  
Parameter Optimization ◽  
Hydrological Model ◽  
Optimization Method ◽  
Difficult Problem ◽  
Rainfall Runoff ◽  
True Parameter ◽  
Shuffled Complex Evolution ◽  
Structure Lead ◽  
Parameter Values

Parameter optimization for the conceptual rainfall-runoff (CRR) model has always been the difficult problem in hydrology since watershed hydrological model is high-dimensional and nonlinear with multimodal and nonconvex response surface and its parameters are obviously related and complementary. In the research presented here, the shuffled complex evolution (SCE-UA) global optimization method was used to calibrate the Xinanjiang (XAJ) model. We defined the ideal data and applied the method to observed data. Our results show that, in the case of ideal data, the data length did not affect the parameter optimization for the hydrological model. If the objective function was selected appropriately, the proposed method found the true parameter values. In the case of observed data, we applied the technique to different lengths of data (1, 2, and 3 years) and compared the results with ideal data. We found that errors in the data and model structure lead to significant uncertainties in the parameter optimization.

scholarly journals Estimating the Relative Uncertainties Sourced from GCMs and Hydrological Models in Modeling Climate Change Impact on Runoff

2012 ◽  
Vol 13 (1) ◽  
pp. 122-139 ◽  
Author(s):  
Jin Teng ◽  
Jai Vaze ◽  
Francis H. S. Chiew ◽  
Biao Wang ◽  
Jean-Michel Perraud
Keyword(s):  
Climate Change ◽  
Climate Change Impact ◽  
Daily Rainfall ◽  
Low Flow ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Runoff Modeling ◽  
Change Impact ◽  
The Difference ◽  
Climate Series

Abstract This paper assesses the relative uncertainties from GCMs and from hydrological models in modeling climate change impact on runoff across southeast Australia. Five lumped conceptual daily rainfall–runoff models are used to model runoff using historical daily climate series and using future climate series obtained by empirically scaling the historical climate series informed by simulations from 15 GCMs. The majority of the GCMs project a drier future for this region, particularly in the southern parts, and this is amplified as a bigger reduction in the runoff. The results indicate that the uncertainty sourced from the GCMs is much larger than the uncertainty in the rainfall–runoff models. The variability in the climate change impact on runoff results for one rainfall–runoff model informed by 15 GCMs (an about 28%–35% difference between the minimum and maximum results for mean annual, mean seasonal, and high runoff) is considerably larger than the variability in the results between the five rainfall–runoff models informed by 1 GCM (a less than 7% difference between the minimum and maximum results). The difference between the rainfall–runoff modeling results is larger in the drier regions for scenarios of big declines in future rainfall and in the low-flow characteristics. The rainfall–runoff modeling here considers only the runoff sensitivity to changes in the input climate data (primarily daily rainfall), and the difference between the hydrological modeling results is likely to be greater if potential changes in the climate–runoff relationship in a warmer and higher CO2 environment are modeled.

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