runoff model Articles
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A conceptual grey rainfall-runoff model for simulation with uncertainty
This paper presents an approach based on grey numbers to represent the total uncertainty of a conceptual rainfall-runoff model. Using this approach, once the grey numbers representing the model parameters have been properly defined, it is possible to obtain simulated discharges in the form of intervals (grey numbers) whose envelope defines a band which represents the total model uncertainty. ...
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A new hybrid algorithm for rainfall–runoff process modeling based on the wavelet transform and genetic fuzzy system
In this paper, two hybrid artificial intelligence (AI) based models were introduced for rainfall–runoff modeling. In the first model, a genetic fuzzy system (GFS) was developed and evolved for the prediction of watersheds' runoff one time step ahead. In the second model, the wavelet-GFS (WGFS) model, wavelet transform was also used as a data pre-processing method prior to GFS ...
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Rainfall-runoff model parameter conditioning on regional hydrological signatures: application to ungauged basins in southern Italy
Parameter estimation for rainfall-runoff models in ungauged basins is a key aspect for a wide range of applications where streamflow predictions from a hydrological model can be used. The need for more reliable estimation of flow in data scarcity conditions is, in fact, thoroughly related to the necessity of reducing uncertainty associated with parameter estimation. This study extends the ...
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Rainfall–runoff modelling using genetic programming
This paper presents the application of genetic programming to the generation of models to assess the total runoff of a basin starting from the total rainfall in it and using data recorded in a sub-basin at the valley of Mexico (the Mixcoac sub-basin to the west of Mexico City). The modelling process is developed contrasting two types of models with different complexity degree: (1) a nonlinear ...
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Assessment of the suitability of rainfall–runoff models by coupling performance statistics and sensitivity analysis
Conceptual rainfall–runoff models are widely used to understand the hydrologic responses of catchments of interest. Modellers calculate the model performance statistics for the calibration and validation periods to investigate whether these models serve as satisfactory representations of the natural hydrologic phenomenon. Another useful method to investigate model suitability is sensitivity ...
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Quantitative analysis of runoff reduction in the Laohahe basin
In order to determine the reason for runoff reduction, daily natural runoff series were restored using a conceptual rainfall–runoff model. The period of 1970–1979 was regarded as a base period with little human activity; model parameters for each subcatchment within the Laohahe basin were calibrated for this period. The effects of human activity and climate change on runoff were quantified by ...
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Regionalisation of the parameters of the rainfall–runoff model PQRUT
This paper presents the regionalisation of the three parameter event-based PQRUT model, which is used for design flood analyses. The PQRUT model is used for the analysis of peak flows for which a sub-daily temporal resolution is required. The availability of high-resolution discharge data and disaggregated precipitation data have made it possible to re-evaluate the regional regression ...
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Initial conditions of urban permeable surfaces in rainfall-runoff models using Horton's infiltration
Infiltration is a key process controlling runoff, but varies depending on antecedent conditions. This study provides estimates on initial conditions for urban permeable surfaces via continuous simulation of the infiltration capacity using historical rain data. An analysis of historical rainfall records show that accumulated rainfall prior to large rain events does not depend on the return ...
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Conjunction of SOM-based feature extraction method and hybrid wavelet-ANN approach for rainfall–runoff modeling
In rainfall–runoff modeling, the wavelet-ANN model, which includes a wavelet transform to capture multi-scale features of the process, as well as an artificial neural network (ANN) to predict the runoff discharge, is a beneficial approach. One of the essential steps in any ANN-based development process is determination of dominant input variables. This paper presents a two-stage ...
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Multi-basin and regional calibration based identification of distributed precipitation–runoff models for hourly runoff simulation: calibration and transfer of full and partial parameters
Identification of distributed precipitation–runoff models for hourly runoff simulation based on transfer of full parameters (FP) and partial parameters (PP) are lacking for boreal mid-Norway. We evaluated storage–discharge relationships based model (Kirchmod), the Basic-Grid-Model (BGM) and a simplified Hydrologiska Byråns Vattenbalansavdelning (HBV) model for multi-basins (26 catchments). A ...
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Hydrologic forecasting using artificial neural networks: a Bayesian sequential Monte Carlo approach
Sequential Monte Carlo (SMC) methods are known to be very effective for the state and parameter estimation of nonlinear and non-Gaussian systems. In this study, SMC is applied to the parameter estimation of an artificial neural network (ANN) model for streamflow prediction of a watershed. Through SMC simulation, the probability distribution of model parameters and streamflow estimation is ...
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Comparative evaluation of performances of different conceptualisations of distributed HBV runoff response routines for prediction of hourly streamflow in boreal mountainous catchments
Unidentifiability and equifinality of parameters pose challenges to calibration and prediction by conceptual precipitation-runoff models. Evaluation of prediction performances of parametrical parsimonious and more complex conceptualisations is lacking for hourly simulation. We conducted a comparative evaluation of four configurations of the distributed (1 × 1 km2 grids) HBV (Hydrologiska ...
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Improving WetSpa model to predict streamflows for gaged and ungaged catchments
In the second phase of the Distributed Model Intercomparison Project (DMIP2), the WetSpa model is applied to simulate flows at basin and subbasin scales. Parent basins and their nested subbasins are modeled as gaged and ungaged basins, respectively. Available observations in the subbasins were only used to validate the model predictions. Gaged basins simulation results show that the predictions ...
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Uncertainty analysis and prediction of river runoff with multi-time scales
Increasing water-issues demand that water resources managers know and predict the uncertain characteristics of river runoff well. In this paper, the fluctuating periods and local features of runoff with multi-time scales are analyzed by the empirical mode decomposition method. With the set pair analysis method, the uncertainty properties of runoff series with different multi-time scales are ...
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Geomorphology-based genetic programming approach for rainfall–runoff modeling
Nowadays, artificial intelligence approaches such as artificial neural network (ANN) as a self-learn non-linear simulator and genetic programming (GP) as a tool for function approximations are widely used for rainfall–runoff modeling. Both approaches are usually created based on temporal characteristics of the process. Hence, the motivation to present a comprehensive model which also ...
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Comparing the impact of time displaced and biased precipitation estimates for online updated urban runoff models
When an online runoff model is updated from system measurements, the requirements of the precipitation input change. Using rain gauge data as precipitation input there will be a displacement between the time when the rain hits the gauge and the time where the rain hits the actual catchment, due to the time it takes for the rain cell to travel from the rain gauge to the catchment. Since this ...
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Investigation of the performance of a simple rainfall disaggregation scheme using semi-distributed hydrological modelling of the Lee catchment, UK
A simple and practical spatial–temporal disaggregation scheme to convert observed daily rainfall to hourly data is presented, in which the observed sub-daily temporal profile available at one gauge is applied linearly to all sites over the catchment to reproduce the spatially varying daily totals. The performance of the methodology is evaluated using an event-based, semi-distributed, nonlinear ...
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Probabilistic nature of storage delay parameter of the hydrologic model RORB: a case study for the Cooper's Creek catchment in Australia
In rainfall–runoff modeling, Design Event Approach is widely adopted in practice, which assumes that the rainfall depth of a given annual exceedance probability (AEP), can be converted to a flood peak of the same AEP by assuming a representative fixed value for the other model inputs/parameters such as temporal pattern, losses and storage-delay parameter of the runoff routing model. This ...
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Urban drainage models – simplifying uncertainty analysis for practitioners
There is increasing awareness about uncertainties in the modelling of urban drainage systems and, as such, many new methods for uncertainty analyses have been developed. Despite this, all available methods have limitations which restrict their widespread application among practitioners. Here, a modified Monte-Carlo based method is presented that reduces the subjectivity inherent in typical ...
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Overcoming the challenges of using a rainfall–runoff model to estimate the impacts of groundwater extraction on low flows in an ephemeral stream
Simple modelling approaches such as a spatially lumped, rainfall–runoff model offer a number of advantages in the management of water resources including the relative ease with which groundwater and surface water accounts can be evaluated at the river-reach scale in data-poor areas. However, rainfall–runoff models are generally not well suited for use in ephemeral river systems ...
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