Rainfall runoff modelling of the Upper Ganga and Brahmaputra basins using PERSiST

2015 ◽  
Vol 17 (6) ◽  
pp. 1070-1081 ◽  
Author(s):  
M. N. Futter ◽  
P. G. Whitehead ◽  
S. Sarkar ◽  
H. Rodda ◽  
J. Crossman
Keyword(s):  
Model Performance ◽  
Structural Uncertainty ◽  
Rainfall Runoff ◽  
Rainfall Runoff Model ◽  
Runoff Model

While tensions exist between parsimony and completeness, it appears that structural uncertainty is more important than parameter equifinality in controlling rainfall-runoff model performance.

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 Can a Calibration-Free Dynamic Rainfall‒Runoff Model Predict FDCs in Data-Scarce Regions? Comparing the IDW Model with the Dynamic Budyko Model in South India

Hydrology ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 32 ◽  
Author(s):  
Nag ◽  
Biswal
Keyword(s):  
Model Performance ◽  
Data Availability ◽  
Ungauged Basins ◽  
Rainfall Runoff ◽  
Discharge Data ◽  
Study Region ◽  
Calibration Free ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Free Dynamic

Construction of flow duration curves (FDCs) is a challenge for hydrologists as most streams and rivers worldwide are ungauged. Regionalization methods are commonly followed to solve the problem of discharge data scarcity by transforming hydrological information from gauged basins to ungauged basins. As a consequence, regionalization-based FDC predictions are not very reliable where discharge data are scarce quantitatively and/or qualitatively. In such a scenario, it is perhaps more meaningful to use a calibration-free rainfall‒runoff model that can exploit easily available meteorological information to predict FDCs in ungauged basins. This hypothesis is tested in this study by comparing a well-known regionalization-based model, the inverse distance weighting (IDW) model, with the recently proposed calibration-free dynamic Budyko model (DB) in a region where discharge observations are not only insufficient quantitatively but also show apparent signs of observational errors. The DB model markedly outperformed the IDW model in the study region. Furthermore, the IDW model’s performance sharply declined when we randomly removed discharge gauging stations to test the model in a variety of data availability scenarios. The analysis here also throws some light on how errors in observational datasets and drainage area influence model performance and thus provides a better picture of the relative strengths of the two models. Overall, the results of this study support the notion that a calibration-free rainfall‒runoff model can be chosen to predict FDCs in discharge data-scarce regions. On a philosophical note, our study highlights the importance of process understanding for the development of meaningful hydrological models.

scholarly journals Conceptual Rainfall–Runoff Model Performance with Different Spatial Rainfall Inputs

2011 ◽  
Vol 12 (5) ◽  
pp. 1100-1112 ◽  
Author(s):  
J. Vaze ◽  
D. A. Post ◽  
F. H. S. Chiew ◽  
J.-M. Perraud ◽  
J. Teng ◽  
...  
Keyword(s):  
Model Simulation ◽  
Model Performance ◽  
Daily Rainfall ◽  
Grid Cell ◽  
Rainfall Series ◽  
Data Availability ◽  
Rainfall Time Series ◽  
Rainfall Runoff ◽  
Rainfall Runoff Model ◽  
Runoff Model

Abstract Different methods have been used to obtain the daily rainfall time series required to drive conceptual rainfall–runoff models, depending on data availability, time constraints, and modeling objectives. This paper investigates the implications of different rainfall inputs on the calibration and simulation of 4 rainfall–runoff models using data from 240 catchments across southeast Australia. The first modeling experiment compares results from using a single lumped daily rainfall series for each catchment obtained from three methods: single rainfall station, Thiessen average, and average of interpolated rainfall surface. The results indicate considerable improvements in the modeled daily runoff and mean annual runoff in the model calibration and model simulation over an independent test period with better spatial representation of rainfall. The second experiment compares modeling using a single lumped daily rainfall series and modeling in all grid cells within a catchment using different rainfall inputs for each grid cell. The results show only marginal improvement in the “distributed” application compared to the single rainfall series, and only in two of the four models for the larger catchments. Where a single lumped catchment-average daily rainfall series is used, care should be taken to obtain a rainfall series that best represents the spatial rainfall distribution across the catchment. However, there is little advantage in driving a conceptual rainfall–runoff model with different rainfall inputs from different parts of the catchment compared to using a single lumped rainfall series, where only estimates of runoff at the catchment outlet is required.

scholarly journals Calibration of hydrological model parameters for ungauged catchments

2007 ◽  
Vol 11 (2) ◽  
pp. 703-710 ◽  
Author(s):  
A. Bárdossy
Keyword(s):  
Hydrological Model ◽  
Model Performance ◽  
Model Parameters ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Ungauged Catchments ◽  
Rainfall Runoff Model ◽  
Climate Statistics ◽  
Runoff Model ◽  
German Part

Abstract. The parameters of hydrological models for catchments with few or no discharge records can be estimated using regional information. One can assume that catchments with similar characteristics show a similar hydrological behaviour and thus can be modeled using similar model parameters. Therefore a regionalisation of the hydrological model parameters on the basis of catchment characteristics is plausible. However, due to the non-uniqueness of the rainfall-runoff model parameters (equifinality), a workflow of regional parameter estimation by model calibration and a subsequent fit of a regional function is not appropriate. In this paper a different approach for the transfer of entire parameter sets from one catchment to another is discussed. Parameter sets are considered as tranferable if the corresponding model performance (defined as the Nash-Sutclife efficiency) on the donor catchment is good and the regional statistics: means and variances of annual discharges estimated from catchment properties and annual climate statistics for the recipient catchment are well reproduced by the model. The methodology is applied to a set of 16 catchments in the German part of the Rhine catchments. Results show that the parameters transfered according to the above criteria perform well on the target catchments.

scholarly journals Performance Evaluation of Mike Nam Rainfall-Runoff (R-R) Model in Daily Flow Simulation (Case Study: Gonbad Catchment in Hamedan)

2020 ◽  
Vol 10 (1) ◽  
pp. 1-6
Author(s):  
Yasamin Sajadi Bami ◽  
Jahangir Porhemmat ◽  
Hossein Sedghi ◽  
Navid Jalalkamali
Keyword(s):  
Flow Rate ◽  
Model Performance ◽  
Flow Simulation ◽  
Coefficient Of Determination ◽  
Rainfall Runoff ◽  
Mean Flow ◽  
Rainfall Runoff Model ◽  
The Right ◽  
Runoff Model

AbstractNowadays, many hydrological rainfall-runoff (R-R) models, both distributed and lumped, have been developed to simulate the catchment. However, selecting the right model to simulate a specific catchment has always been a challenge. A proper understanding of the model and its advantages and limitations is essential for selecting the appropriate model for the purpose of the study. To this end, several studies have been carried out to evaluate the performance of hydrological models for specific areas (mountainous, marshy and so on). This study was conducted aimed at evaluating the performance of MIKE11 NAM lumped conceptual hydrological rainfall-runoff model in simulation of daily flow rate in Gonbad catchment. The NAM model was calibrated and validated using flow rate data of three hydrometric stations of the Gonbad catchment. The model performance was evaluated using Percent bias (PBIAS) and the coefficient of determination or Nash-Sutcliffe coefficient. A Nash Sutcliffe efficiency (NSE) of 0.80, 0.89 and 080 were obtained during calibration, whereas, for the validation period, NSE of 0.81, 0.87 and 0.71 were obtained for Nemooneh sub catchment, Shahed sub catchment and Gonbad catchment respectively. Percent bias of -0.6, 1.5 and 6.3 were achieved for calibration, while -2.7, 7.6 and -4.2 were acquired during validation for Nemooneh sub catchment, Shahed sub catchment and Gonbad catchment respectively. Based on the results, the MIKE 11 NAM lumped conceptual model was capable of simulating daily mean flow rate and mean flow volume.

regionalization of the potential to increase rainfall-runoff model performance by multi-objective calibration using modis data over Austria

2020 ◽  
Author(s):  
Martin Kubáň ◽  
Patrik Sleziak ◽  
Adam Brziak ◽  
Kamila Hlavčová ◽  
Ján Szolgay
Keyword(s):  
Soil Moisture ◽  
Hydrological Model ◽  
Snow Water Equivalent ◽  
Model Performance ◽  
State Variables ◽  
Rainfall Runoff ◽  
Multi Objective ◽  
Snow Water ◽  
Rainfall Runoff Model ◽  
Runoff Model

<p>A multi-objective calibration of the parameters of conceptual hydrologic models has the potential to improve the consistency of the simulated model states, their representativeness with respect to catchment states and thereby to reduce the uncertainty in the estimation of hydrological model outputs. Observed in-situ or remotely sensed state variables, such as the snow cover distribution, snow depth, snow water equivalent and soil moisture were often considered as additional information in such calibration strategies and subsequently utilized in data assimilation for operational streamflow forecasting. The objective of this paper is to assess the effects of the inclusion of MODIS products characterizing soil moisture and the snow water equivalent in a multi-objective calibration strategy of an HBV type conceptual hydrological model under the highly variable physiographic conditions over the whole territory of Austria.</p><p>The methodology was tested using the Technical University of Vienna semi-distributed rainfall-runoff model (the TUW model), which was calibrated and validated in 213 Austrian catchments. For calibration we use measured data from the period 2005 to 2014. Subsequently, we simulated discharges, soil moisture and snow water equivalents based on parameters from the multi-objective calibration and compared these with the respective MODIS values. In general, the multi-objective calibration improved model performance when compared to results of model parametrisation calibrated only on discharge time series. Sensitivity analyses indicate that the magnitude of the model efficiency is regionally sensitive to the choice of the additional calibration variables. In the analysis of the results we indicate ranges how and where the runoff, soil moisture and snow water equivalent simulation efficiencies were sensitive to different setups of the multi-objective calibration strategy over the whole territory of Austria. It was attempted to regionalize the potential to increase of the overall model performance and the improvement in the consistency of the simulation of the two-state variables. Such regionalization may serve model users in the selection which remotely sensed variable or their combination is to be preferred in local modelling studies.</p>

scholarly journals Step wise Multi-criteria Performance Evaluation of Rainfall-Runoff Models using WETSPRO

1970 ◽  
Vol 7 (1) ◽  
pp. 18-29 ◽  
Author(s):  
PC Shakti ◽  
NK Shrestha ◽  
P Gurung
Keyword(s):  
Time Series ◽  
Performance Evaluation ◽  
Assessment Tool ◽  
Model Performance ◽  
Rainfall Runoff ◽  
Peak Flows ◽  
Low Flows ◽  
Flow Components ◽  
Rainfall Runoff Model ◽  
Runoff Model

This paper illustrates a methodology to evaluate model’s performance of rainfall runoff model using a tool called WETSPRO (Water Engineering Time Series PROcessing tool). Simulated results of physically based semidistributed model - SWAT (Soil and Water Assessment Tool) for Kliene Nete watershed (581 km2), Belgium are considered in this study. Paper presents a series of sequential time series processing tasks to be performed to evaluate model’s performance thoroughly. The problem of serial dependence and heteroscedasticity is addressed and model performance evaluation on different flow components (peak flows, low flows and volume) and flow volume is carried. Performance evaluation of both flow components on their extremes is also performed. Two most commonly used goodness-fit-statistics (Mean Square Error – MSE and Nash Sutcliff Efficiency − NSE) are used with number of complementary graphical plots for evaluation propose. Results indicated model’s robust performance on peak flows although base flows are slightly underestimated especially for lower return periods. Cumulative flow volumes tend to be overestimated. Based upon the study, some recommendations are summarized to enhance model’s ability to simulate the flows events. Keywords: Rainfall runoff model; SWAT; WETSPRO; Kliene Nete; peak flows; low flows. DOI: http://dx.doi.org/10.3126/jhm.v7i1.5613 JHM 2010; 7(1): 18-29

scholarly journals Assessing the impact of PET estimation methods on hydrologic model performance

2020 ◽  
Author(s):  
Dilhani Ishanka Jayathilake ◽  
Tyler Smith
Keyword(s):  
Potential Evapotranspiration ◽  
Model Performance ◽  
Monte Carlo Sampling ◽  
Hydrologic Model ◽  
Estimation Methods ◽  
Rainfall Runoff ◽  
Data Set ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Runoff Model

Abstract Evapotranspiration is a necessary input and one of the most uncertain hydrologic variables for quantifying the water balance. Key to accurately predicting hydrologic processes, particularly under data scarcity, is the development of an understanding of the regional variation of the impact of potential evapotranspiration (PET) data inputs on model performance and parametrization. This study explores this impact using four different potential evapotranspiration products (of varying quality). For each data product, a lumped conceptual rainfall–runoff model (GR4J) is tested on a sample of 57 catchments included in the MOPEX data set. Monte Carlo sampling is performed, and the resulting parameter sets are analyzed to understand how the model responds to differences in the forcings. Test catchments are classified as energy- or water-limited using the Budyko framework and by eco-region, and the results are further analyzed. While model performance (and parameterization) in water-limited sites was found to be largely unaffected by the differences in the evapotranspiration inputs, in energy-limited sites model performance was impacted as model parameterizations were clearly sensitive to evapotranspiration inputs. The quality/reliability of PET data required to avoid negatively impacting rainfall–runoff model performance was found to vary primarily based on the water and energy availability of catchments.

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