scholarly journals Impact of the Mean Areal Rainfall Calculation on a Modular Rainfall-Runoff Model

2020 ◽  
Vol 8 (12) ◽  
pp. 980
Author(s):  
Jose Valles ◽  
Gerald Corzo ◽  
Dimitri Solomatine
Keyword(s):  
Divide And Conquer ◽  
Low Flow ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
The Mean ◽  
Areal Rainfall ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
The Relationship ◽  
Runoff Model

Hydrological models are based on the relationship between rainfall and discharge, which means that a poor representation of rainfall produces a poor streamflow result. Typically, a poor representation of rainfall input is produced by a gauge network that is not able to capture the rainfall event. The main objective of this study is to evaluate the impact of the mean areal rainfall on a modular rainfall-runoff model. These types of models are based on the divide-and-conquer approach and two specialized hydrological models for high and low regimes were built and then combined to form a committee of model that takes the strengths of both specialized models. The results show that the committee of models produces a reasonable reproduction of the observed flow for high and low flow regimes. Furthermore, a sensitivity analysis reveals that Ilopango and Jerusalem rainfall gauges are the most beneficial for discharge calculation since they appear in most of the rainfall subset that produces low Root Mean Square Error (RMSE) values. Conversely, the Puente Viejo and Panchimalco rainfall gauges are the least beneficial for the rainfall-runoff model since these gauges appear in most of the rainfall subset that produces high RMSE value.

scholarly journals The Impact of the Variability of Precipitation and Temperatures on the Efficiency of a Conceptual Rainfall-Runoff Model

2016 ◽  
Vol 24 (4) ◽  
pp. 1-7 ◽  
Author(s):  
P. Sleziak ◽  
J. Szolgay ◽  
K. Hlavčová ◽  
J. Parajka
Keyword(s):  
Hydrological Model ◽  
Differential Evolution Algorithm ◽  
Rainfall Runoff ◽  
University Of Technology ◽  
Wide Range ◽  
Evolution Algorithm ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
The Relationship ◽  
Runoff Model

AbstractThe main objective of the paper is to understand how the model’s efficiency and the selected climatic indicators are related. The hydrological model applied in this study is a conceptual rainfall-runoff model (the TUW model), which was developed at the Vienna University of Technology. This model was calibrated over three different periods between 1981-2010 in three groups of Austrian catchments (snow, runoff, and soil catchments), which represent a wide range of the hydroclimatic conditions of Austria. The model’s calibration was performed using a differential evolution algorithm (Deoptim). As an objective function, we used a combination of the Nash-Sutcliffe coefficient (NSE) and the logarithmic Nash-Sutcliffe coefficient (logNSE). The model’s efficiency was evaluated by Volume error (VE). Subsequently, we evaluated the relationship between the model’s efficiency (VE) and changes in the climatic indicators (precipitation ΔP, air temperature ΔT). The implications of findings are discussed in the conclusion.

scholarly journals Constraining a lumped rainfall-runoff model with piezometry to improve low-flow simulation

2021 ◽  
Author(s):  
Antoine Pelletier ◽  
Vakzen Andréassian
Keyword(s):  
Flow Simulation ◽  
Daily Rainfall ◽  
Climatic Conditions ◽  
Low Flow ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Low Flows ◽  
Sample Test ◽  
Rainfall Runoff Model ◽  
Runoff Model

<p>Most lumped hydrological models are focused on the rainfall-runoff relationship, since climatic conditions are the driving force of the hydrological behaviour of a catchment. Many hydrological models, like the ones used by the French national PREMHYCE platform, only take climatic variables as inputs – daily rainfall and potential evaporation – to simulate and forecast low-flows. Yet, a hydrological drought is generally a medium- to long-term phenomenon, which is the consequence of long records of dry climatic conditions. Daily lumped hydrological models often struggle to integrate these records to reproduce catchment memory.</p><p>In many French catchments, it was observed that this memory of past hydroclimatic conditions is well represented in piezometric signals that are broadly available over the national territory. Indeed, aquifers, especially the large ones, do store water on the long, feeding rivers during droughts: aquifers are not only <em>water carriers</em> – the etymology for the word <em>aquifer </em>– they are also <em>memory carriers</em>. A dataset of 108 catchments, each of them being associated with one or several piezometers, was used to investigate whether the GR6J daily lumped rainfall-runoff model could be constrained by piezometric time series to improve low-flow simulations. We found that a particular state of the model, the exponential store, is particularly well correlated with piezometry in most studied catchments.</p><p>In order to get a univocal relationship between the exponential store and piezometry, a multi-objective calibration approach was implemented, optimising both (i) flow simulation with a criterion focused on low-flows and (ii) affine correspondence between the exponential store level and piezometry. For that purpose, a new parameter was added to the model. The modified calibration was then evaluated through a split-sample test and the performance in simulating particular drought events. The calibrated store-piezometry relationship can now be used for data assimilation to improve low-flow forecasting.</p>

scholarly journals Analysis of low flow indices under varying climatic conditions in Poland

2017 ◽  
Vol 49 (2) ◽  
pp. 373-389 ◽  
Author(s):  
Marzena Osuch ◽  
Renata Romanowicz ◽  
Wai K. Wong
Keyword(s):  
Climate Models ◽  
Climatic Conditions ◽  
Low Flow ◽  
Test Results ◽  
Rainfall Runoff ◽  
Objective Functions ◽  
Rcp 8.5 ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Simulated Time

Abstract Changes in low flow indices under future climates are estimated for eight catchments in Poland. A simulation approach is used to derive daily flows under changing climatic conditions, following RCP 4.5 and RCP 8.5 emission scenarios. The HBV rainfall–runoff model is used to simulate low flows. The model is calibrated and validated using streamflow observations from periods 1971–2000 and 2001–2010. Two objective functions are used for calibration: Nash–Sutcliffe and log transformed Nash–Sutcliffe. Finally, the models are run using the bias-corrected precipitation and temperature data simulated by GCM/RCM models for the periods 2021–2050 and 2071–2100. We estimate low flow indices for the simulated time series, including annual minima of 7-day mean river flows and number, severity and duration of low flow events. We quantify the biases of low flow indices by N-way analysis of variance (ANOVA) analysis and Tukey test. Results indicate a large effect of climate models, as well as objective functions, on the low flow indices obtained. A comparison of indices from the two future periods with the reference period 1971–2000 confirms the trends obtained in previous studies, in the form of a projected decrease in the frequency and intensity of low flow events.

scholarly journals Sensitivity Analysis to Investigate the Reliability of the Grid-Based Rainfall-Runoff Model

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1839 ◽  
Author(s):  
Mun-Ju Shin ◽  
Yun Choi
Keyword(s):  
Water Movement ◽  
Parameter Sensitivity ◽  
Low Flow ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Rainfall Events ◽  
Flow Calculation ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Grid Based

This study aimed to assess the suitability of the parameters of a physically based, distributed, grid-based rainfall-runoff model. We analyzed parameter sensitivity with a dataset of eight rainfall events that occurred in two catchments of South Korea, using the Sobol’ method. Parameters identified as sensitive responded adequately to the scale of the rainfall events and the objective functions employed. Parameter sensitivity varied depending on rainfall scale, even in the same catchment. Interestingly, for a rainfall event causing considerable runoff, parameters related to initial soil saturation and soil water movement played a significant role in low flow calculation and high flow calculation, respectively. The larger and steeper catchment exhibited a greater difference in parameter sensitivity between rainfall events. Finally, we found that setting an incorrect parameter range that is physically impossible can have a large impact on runoff simulation, leading to substantial uncertainty in the simulation results. The proposed analysis method and the results from our study can help researchers using a distributed rainfall-runoff model produce more reliable analysis results.

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 Uncertainty and sensitivity analysis of GIS based continuous hydrological modelling

2021 ◽  
Author(s):  
Harry R. Manson
Keyword(s):  
Sensitivity Analysis ◽  
Curve Number ◽  
Monte Carlo Analysis ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Lumped Model ◽  
Daily Average ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Runoff Model

The impact of uncertainty in spatial and a-spatial lumped model parameters for a continuous rainfall-runoff model is evaluated with respect to model prediction. The model uses a modified SCS-Curve Number approach that is loosely coupled with a geographic information system (GIS). The rainfall-runoff model uses daily average inputs and is calibrated using a daily average streamflow record for the study site. A Monte Carlo analysis is used to identify total model uncertainty while sensitivity analysis is applied using both a one-at-a-time (OAT) approach as well as through application of the extended Fourier Amplitude Sensitivity Technique (FAST). Conclusions suggest that the model is highly followed by model inputs and finally the Curve Number. While the model does not indicate a high degree of sensitivity to the Curve Number at present conditions, uncertainties in Curve Number estimation can potentially be the cause of high predictive errors when future development scenarios are evaluated.

scholarly journals A coupled stochastic rainfall-evapotranspiration model for hydrological impact analysis

2017 ◽  
Author(s):  
Minh Tu Pham ◽  
Hilde Vernieuwe ◽  
Bernard De Baets ◽  
Niko E. C. Verhoest
Keyword(s):  
Time Series ◽  
Impact Analysis ◽  
Hydrological Model ◽  
Hydrological Cycle ◽  
Rainfall Runoff ◽  
Hydrological Impact ◽  
Long Time ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Runoff Model

Abstract. A hydrological impact analysis concerns the study of the consequences of certain scenarios on one or more variables or fluxes in the hydrological cycle. In such exercise, discharge is often considered, as especially extreme high discharges often cause damage due to the coinciding floods. Investigating extreme discharges generally requires long time series of precipitation and evapotranspiration that are used to force a rainfall-runoff model. However, such kind of data may not be available and one should resort to stochastically-generated time series, even though the impact of using such data on the overall discharge, and especially on the extreme discharge events is not well studied. In this paper, stochastically-generated rainfall and coinciding evapotranspiration time series are used to force a simple conceptual hydrological model. The results obtained are comparable to the modelled discharge using observed forcing data. Yet, uncertainties in the modelled discharge increase with an increasing number of stochastically-generated time series used. Notwithstanding this finding, it can be concluded that using a coupled stochastic rainfall-evapotranspiration model has a large potential for hydrological impact analysis.

scholarly journals A coupled stochastic rainfall–evapotranspiration model for hydrological impact analysis

2018 ◽  
Vol 22 (2) ◽  
pp. 1263-1283 ◽  
Author(s):  
Minh Tu Pham ◽  
Hilde Vernieuwe ◽  
Bernard De Baets ◽  
Niko E. C. Verhoest
Keyword(s):  
Time Series ◽  
Impact Analysis ◽  
Hydrological Cycle ◽  
Rainfall Runoff ◽  
Hydrological Impact ◽  
Long Time ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Vine Copulas ◽  
Runoff Model

Abstract. A hydrological impact analysis concerns the study of the consequences of certain scenarios on one or more variables or fluxes in the hydrological cycle. In such an exercise, discharge is often considered, as floods originating from extremely high discharges often cause damage. Investigating the impact of extreme discharges generally requires long time series of precipitation and evapotranspiration to be used to force a rainfall-runoff model. However, such kinds of data may not be available and one should resort to stochastically generated time series, even though the impact of using such data on the overall discharge, and especially on the extreme discharge events, is not well studied. In this paper, stochastically generated rainfall and corresponding evapotranspiration time series, generated by means of vine copulas, are used to force a simple conceptual hydrological model. The results obtained are comparable to the modelled discharge using observed forcing data. Yet, uncertainties in the modelled discharge increase with an increasing number of stochastically generated time series used. Notwithstanding this finding, it can be concluded that using a coupled stochastic rainfall–evapotranspiration model has great potential for hydrological impact analysis.

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.

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