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 Fuzzy committees of specialised rainfall-runoff models: further enhancements

2013 ◽  
Vol 10 (1) ◽  
pp. 675-697 ◽  
Author(s):  
N. Kayastha ◽  
J. Ye ◽  
F. Fenicia ◽  
D. P. Solomatine
Keyword(s):  
Hydrological Model ◽  
Weighting Function ◽  
Hydrological Models ◽  
Local Models ◽  
Membership Functions ◽  
Rainfall Runoff ◽  
Objective Functions ◽  
Global Optimal ◽  
Hydrological Regimes

Abstract. Often a single hydrological model cannot capture the details of a complex rainfall-runoff relationship, and a possibility here is building specialised models to be responsible for a particular aspect of this relationship and combining them forming 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 local models and compare them with global optimal models.

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.

Usage of Differential Evolution Algorithm in the Calibration of Parametric Rainfall-Runoff Modeling

2018 ◽  
pp. 481-499 ◽  
Author(s):  
Umut Okkan ◽  
Nuray Gedik ◽  
Halil Uysal
Keyword(s):  
Climate Change ◽  
Global Optimization ◽  
Differential Evolution ◽  
Hydrological Model ◽  
Optimization Algorithms ◽  
Differential Evolution Algorithm ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Lumped Model ◽  
Evolution Algorithm

In recent years, global optimization algorithms are used in many engineering applications. Calibration of certain parameters at conceptualization of hydrological models is one example of these. An important issue in interpreting the effects of climate change on the basin depends on selecting an appropriate hydrological model. Not only climate change impact assessment studies, but also many water resources planning studies refer to such modeling applications. In order to obtain reliable results from these hydrological models, calibration phase of the models needs to be done well. Hence, global optimization methods are utilized in the calibration process. In this chapter, the differential evolution algorithm (DEA), which has rare application in the hydrological modeling literature, was explained. As an application, the use of the DEA algorithm in the hydrological model calibration phase was mentioned. DYNWBM, a lumped model with five parameters, was selected as the hydrological model. The calibration and then validation period performances of the DEA based DYNWBM model were tested and also compared with other global optimization algorithms. According to the results derived from the study, hydrological model appropriately reflects the rainfall-runoff relation of basin for both periods.

scholarly journals Evaluation of Permeable Brick Pavement on the Reduction of Stormwater Runoff Using a Coupled Hydrological Model

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2821
Author(s):  
Xiaoran Fu ◽  
Jiahong Liu ◽  
Weiwei Shao ◽  
Chao Mei ◽  
Dong Wang ◽  
...  
Keyword(s):  
Urban Areas ◽  
Hydrological Model ◽  
Peak Flow ◽  
Stormwater Runoff ◽  
Coupled Model ◽  
Potential Effect ◽  
Watershed Scale ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Storm Duration

In several cities, permeable brick pavement (PBP) plays a key role in stormwater management. Although various hydrological models can be used to analyze the mitigation efficiency of PBP on rainfall runoff, the majority do not consider the effect of multi-layered pavement on infiltration in urban areas. Therefore, we developed a coupled model to evaluate the potential effect of PBP in reducing stormwater runoff at a watershed scale. Specifically, we compared the hydrological responses (outflow and overflow) of three different PBP scenarios. The potential effects of PBP on peak flow (PF), total volume (TV), and overflow volume (OV) were investigated for 20 design rainstorms with different return periods and durations. Our results indicate that an increase in PBP ratio reduces both PF (4.2–13.5%) and TV (4.2–10.5%) at the outfall as well as the OV (15.4–30.6%) across networks. The mitigation effect of PBP on OV is linearly correlated to storm return period and duration, but the effects on PF and TV are inversely correlated to storm duration. These results provide insight on the effects of infiltration-based infrastructure on urban flooding.

scholarly journals Regionalization of hydrological model parameters using data depth

2011 ◽  
Vol 42 (5) ◽  
pp. 356-371 ◽  
Author(s):  
András Bárdossy ◽  
Shailesh Kumar Singh
Keyword(s):  
Hydrological Model ◽  
Data Depth ◽  
Model Parameters ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Catchment Characteristics ◽  
Rainfall Runoff Model ◽  
Using Data ◽  
Runoff Model

The parameters of hydrological models with no or short discharge records can only be estimated using regional information. We can assume that catchments with similar characteristics show a similar hydrological behaviour. A regionalization of hydrological model parameters on the basis of catchment characteristics is therefore plausible. However, due to the non-uniqueness of the rainfall/runoff model parameters (equifinality), a procedure of a regional parameter estimation by model calibration and a subsequent fit of a regional function is not appropriate. In this paper, a different procedure based on the depth function and convex combinations of model parameters is introduced. Catchment characteristics to be used for regionalization can be identified by the same procedure. Regionalization is then performed using different approaches: multiple linear regression using the deepest parameter sets and convex combinations. The assessment of the quality of the regionalized models is also discussed. An example of 28 British catchments illustrates the methodology.

scholarly journals A strategy to overcome adverse effects of autoregressive updating of streamflow predictions

2014 ◽  
Vol 11 (6) ◽  
pp. 6035-6063
Author(s):  
M. Li ◽  
Q. J. Wang ◽  
J. C. Bennett ◽  
D. E. Robertson
Keyword(s):  
Adverse Effects ◽  
Hydrological Model ◽  
Model Simulation ◽  
Ar Model ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Streamflow Forecasting ◽  
Popular Approach ◽  
Ar Models ◽  
Simulation Errors

Abstract. For streamflow forecasting applications, rainfall–runoff hydrological models are often augmented with updating procedures that correct streamflow predictions based on the latest available observations of streamflow and their departures from model simulations. The most popular approach uses autoregressive (AR) models that exploit the "memory" in hydrological model simulation errors. AR models may be applied to raw errors directly or to normalised errors. In this study, we demonstrate that AR models applied in either way can sometimes cause over-correction of predictions. In using an AR model applied to raw errors, the over-correction usually occurs when streamflow is rapidly receding. In applying an AR model to normalised errors, the over-correction usually occurs when streamflow is rapidly rising. Furthermore, when parameters of a hydrological model and an AR model are estimated jointly, the AR model applied to normalised errors sometimes degrades the stand-alone performance of the base hydrological model. This is not desirable for forecasting applications, as predictions should rely as much as possible on the base hydrological model, and updating should be applied only to correct minor errors. To overcome the adverse effects of the ordinary AR models, a restricted AR model applied to normalised errors is introduced. The new model is evaluated on a number of catchments and is shown to reduce over-correction and to improve the performance of the base hydrological model considerably.

scholarly journals Objective functions used as performance metrics for hydrological models: state-of-the-art and critical analysis

RBRH ◽  
2020 ◽  
Vol 25 ◽  
Author(s):  
Paloma Mara de Lima Ferreira ◽  
Adriano Rolim da Paz ◽  
Juan Martín Bravo
Keyword(s):  
Time Series ◽  
Model Calibration ◽  
Hydrological Model ◽  
Performance Metrics ◽  
Low Flow ◽  
Hydrological Models ◽  
Objective Functions ◽  
Flow Rates ◽  
Daily Streamflow ◽  
Synthetic Time Series

ABSTRACT Hydrological models (HMs) can be applied for different purposes, and a key step is model calibration using objective functions (OF) to quantify the agreement between observed and calculated discharges. Fully understanding the OF is important to properly take advantage of model calibration and interpret the results. This study evaluates 36 OF proposed in the literature, considering two watersheds of different hydrological regimes. Daily simulated streamflow time-series, using a distributed hydrological model (MGB-IPH), and ten daily streamflow synthetic time-series, generated from the observed and calculated streamflows, were used in the analysis of each watershed. These synthetic data were used to evaluate how does each metric evaluate hypothetical cases that present isolated very well known error behaviors. Despite of all NSE-derived (Nash-Sutcliffe efficiency) metrics that use the square of the residuals in their formulation have shown higher sensitivity to errors in high flows, the ones that use daily and monthly averages of flow rates in absolute terms were more stringent than the others to assess HMs performance. Low flow errors were better evaluated by metrics that use the flow logarithm. The constant presence of zero flow rates deteriorate them significantly, with the exception of the metrics TRMSE (Transformed root mean square error) did not demonstrate this problem. An observed limitation of the formulations of some metrics was that the errors of overestimation or underestimation are compensated. Our results reassert that each metric should be interpreted specifically thinking about the aspects it has been proposed for, and simultaneously taking into account a set of metrics would lead to a broader evaluation of HM ability (e.g. multiobjective model evaluation). We recommend that the use of synthetic time series as those proposed in this work could be useful as an auxiliary step towards better understanding the evaluation of a calibrated hydrological model for each study case, taking into account model capabilities and observed hydrologic regime characteristics.

Can a hydrological model be efficient and robust at the same time?

2020 ◽  
Author(s):  
Paul Royer-Gaspard ◽  
Vazken Andréassian ◽  
Guillaume Thirel
Keyword(s):  
Objective Function ◽  
Hydrological Model ◽  
Flow Regimes ◽  
Calibration Procedure ◽  
Automatic Calibration ◽  
Rainfall Runoff ◽  
Objective Functions ◽  
Robust Parameter ◽  
High Flows ◽  
Large Catchment

<p>It has been shown in various experiments that many conceptual rainfall-runoff models experience difficulties to simulate annual or longer-term variations of the streamflow (e.g. Coron et al., 2014). Whether this problem is inherent to the structure of the model in question or could be solved by a change of the calibration procedure is still a matter of debate: for example, the work of Coron (2013) tended to show that no parameter set able to solve the issue can be found, while Fowler et al. (2018) argued that such parameter sets exist, and should be identifiable by a change of objective function.</p><p>The aim of this study is to explore further the existence of such a parameter set in the case of the GR4J model (Perrin et al., 2003). Parameters sets were in particular tested against their ability to provide efficient (i.e. with good performance) and robust (i.e. transposable in time) discharge simulations over three flow ranges (low, mean and high flows). To this purpose, a large number of parameters sets of GR4J were sampled in 545 French and Australian catchments. The obtained performances were confronted to those obtained with automatic calibration with a range of objective functions focusing on diverse streamflow ranges.</p><p>Because of our large catchment set, we were able to identify a variety of cases: catchments for which highly robust parameter sets exist, catchments for which relatively robust parameter sets exist, and catchments for which no robust parameter sets can be found. Compared to the best sampled parameters sets, those derived through automatic calibration often yielded poorer performances regarding at the same time efficiency and robustness of the discharge simulations over the three flow ranges. We discuss the link between model failures and catchments characteristics, as well as the ability of the GR4J model to adequately simulate streamflow on different timescales and flow regimes.</p>

scholarly journals Selection of a Hydrological Model and Objective Function for Water Resources Management in Predominantly Rural Watershed using Criteria-Based Evaluation

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Pratik Singh Thakuri ◽  
NT Sohan Wijesekera
Keyword(s):  
Water Resources ◽  
Objective Function ◽  
Water Resources Management ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
Suitable Model ◽  
Hydrological Models ◽  
Objective Functions ◽  
Resources Management ◽  
Selection Of

Selection of a fitting up-to-date hydrological model using an evaluation of the functionality, modeler’s requirements, and modeling experiences are very important for water resources management in rural watersheds. Similarly, the selection of appropriate objective function is equally crucial in hydrological modeling processes. Accordingly, A review study was carried to select an appropriate model and objective function for water resources modeling in the predominantly rural watershed. Hydrological models namely HEC-HMS, MIKE SHE, SWAT, TOPMODEL, and SWMM, and objective functions namely NSE, RMSE, MRAE, and RAEM were reviewed. Hydrological models were reviewed under several criteria viz. temporal scale, spatial scale, hydrological processes, documentation, resources requirement, user interface and, model acquisition cost. Whereas, criteria for the review of objective functions were mathematical implication, flow regime, and modeling purpose. Each of the review criteria was comprised of several factors. The criteria-based evaluation was done to quantify the review outcome of the hydrological model and objective function. SWMM was found to be the most suitable model for simulating rural watersheds for water resources management purposes whereas, MRAE was found to be the most appropriate objective function to evaluate the performance of the model selected for rural watershed modeling.

scholarly journals Predicting Surface Runoff from Catchment to Large Region

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Hongxia Li ◽  
Yongqiang Zhang ◽  
Xinyao Zhou
Keyword(s):  
Surface Runoff ◽  
Land Surface ◽  
Hydrological Model ◽  
Large Region ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Ungauged Catchments ◽  
Research Fields ◽  
Surface Models ◽  
Distributed Hydrological Models

Predicting surface runoff from catchment to large region is a fundamental and challenging task in hydrology. This paper presents a comprehensive review for various studies conducted for improving runoff predictions from catchment to large region in the last several decades. This review summarizes the well-established methods and discusses some promising approaches from the following four research fields: (1) modeling catchment, regional and global runoff using lumped conceptual rainfall-runoff models, distributed hydrological models, and land surface models, (2) parameterizing hydrological models in ungauged catchments, (3) improving hydrological model structure, and (4) using new remote sensing precipitation data.

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