Comparing catchment scale subsurface celerities estimated from recession analysis and infiltration experiments.

2020 ◽  
Author(s):  
Thomas Skaugen ◽  
Knut Møen ◽  
Søren Boje
Keyword(s):  
Moving Average ◽  
Hydrological Models ◽  
Catchment Scale ◽  
Temporal Scales ◽  
Efficiency Criterion ◽  
Infiltration Test ◽  
Recession Analysis ◽  
Rainfall Runoff Model ◽  
Southern Norway ◽  
Unit Hydrographs

<p>Catchment scale hydrological models all have some representation of the dynamics of subsurface flow and hence direct or indirect estimates of the celerities (velocities) involved. Parameters representing these celerities (for example recession coefficients of linear reservoirs) are often calibrated against runoff instead of being estimated directly from measured data. Such a procedure, when applied for hydrological models with (too) many parameters to be calibrated, may lead to unrealistic estimates of subsurface celerity due to equifinality issues. Our aim with this study is to obtain an estimate of the distributions of subsurface celerites corresponding to the distribution of saturation levels through recession analysis. Using the recession characteristic Λ=log(Q(t)/Q(t+∆t) and looking for sequences of recession in a moving average filtered time series of runoff, we find, for many catchments, no clear structure in the relationship between Q(t) and Λ.  In order to better understand the recession process we let the runoff be represented by four (parallel) unit hydrographs (UH) of different temporal scales. The UHs thus represent different subsurface celerities through their different temporal scales and different levels of saturation.  Only when there was a systematic build up of saturation from below, i.e. the slowest UH had to be filled to (a chosen max) capacity before the next UH received water, a clear structure between Q(t) and Λ emerged, where for each value of Q(t) the maximum Λ represented the true recession to be used for estimating the celerity.  At the tiny Muren catchment (7500 m2) in southern Norway we performed an infiltration test and estimated the saturated hydraulic conductivity to be 0.00045 m/s. The mean celerity estimated from recession analysis for the same catchment was found to be 0.00034 m/s, and when the distribution of celerities from the recession analysis was used in the Distance Distribution Dynamics (DDD) rainfall runoff model a Kling Gupta efficiency criterion of KGE = 0.86 was obtained for runoff simulations at 15 minutes temporal resolution.</p>

scholarly journals Investigation of variable threshold level approaches for hydrological drought identification

2014 ◽  
Vol 11 (11) ◽  
pp. 12765-12797 ◽  
Author(s):  
B. S. Beyene ◽  
A. F. Van Loon ◽  
H. A. J. Van Lanen ◽  
P. J. J. F. Torfs
Keyword(s):  
Time Series ◽  
Moving Average ◽  
Threshold Level ◽  
Snow Melt ◽  
Rainfall Runoff ◽  
Catchment Scale ◽  
Climate Conditions ◽  
Variable Threshold ◽  
Rainfall Runoff Model ◽  
Runoff Model

Abstract. Threshold level approaches are widely used to identify drought events in time series of hydrometeorological variables. However, the method used for calculating the threshold level can influence the quantification of drought events or even introduce artefact drought events. In this study, four methods of variable threshold calculation have been tested on catchment scale, namely (1) moving average of monthly quantile (M_MA), (2) moving average of daily quantile (D_MA), (3) thirty days moving window quantile (30D) and (4) fast Fourier transform of daily quantile (D_FF). The levels obtained by these methods were applied to hydrometeorological variables that were simulated with a semi-distributed conceptual rainfall-runoff model (HBV) for five European catchments with contrasting catchment properties and climate conditions. There are no physical arguments to prefer one method over the other for drought identification. The only way to investigate this is by applying the methods and visually inspecting the results. Therefore, drought statistics (i.e. number of droughts, mean duration, mean deficit) and time series plots were studied to compare drought propagation patterns determined by different threshold calculation methods. We found that all four approaches are sufficiently suitable to quantify drought propagation in contrasting catchments. Only the D_FF approach showed lower performance in two catchments. The 30D approach seems to be optimal in snow-dominated catchments, because it follows fast changes in discharge caused by snow melt more accurately. The proposed approaches can be successfully applied by water managers in regions where drought quantification and prediction are essential.

scholarly journals Are streamflow recession characteristics really characteristic?

2013 ◽  
Vol 17 (2) ◽  
pp. 817-828 ◽  
Author(s):  
M. Stoelzle ◽  
K. Stahl ◽  
M. Weiler
Keyword(s):  
Extraction Method ◽  
Storage Capacity ◽  
Extraction Methods ◽  
Model Parameters ◽  
Catchment Scale ◽  
Model Parameterization ◽  
Recession Curves ◽  
Recession Analysis ◽  
Meso Scale

Abstract. Streamflow recession has been investigated by a variety of methods, often involving the fit of a model to empirical recession plots to parameterize a non-linear storage–outflow relationship based on the dQ/dt−Q method. Such recession analysis methods (RAMs) are used to estimate hydraulic conductivity, storage capacity, or aquifer thickness and to model streamflow recession curves for regionalization and prediction at the catchment scale. Numerous RAMs have been published, but little is known about how comparably the resulting recession models distinguish characteristic catchment behavior. In this study we combined three established recession extraction methods with three different parameter-fitting methods to the power-law storage–outflow model to compare the range of recession characteristics that result from the application of these different RAMs. Resulting recession characteristics including recession time and corresponding storage depletion were evaluated for 20 meso-scale catchments in Germany. We found plausible ranges for model parameterization; however, calculated recession characteristics varied over two orders of magnitude. While recession characteristics of the 20 catchments derived with the different methods correlate strongly, particularly for the RAMs that use the same extraction method, not all rank the catchments consistently, and the differences among some of the methods are larger than among the catchments. To elucidate this variability we discuss the ambiguous roles of recession extraction procedures and the parameterization of the storage–outflow model and the limitations of the presented recession plots. The results suggest strong limitations to the comparability of recession characteristics derived with different methods, not only in the model parameters but also in the relative characterization of different catchments. A multiple-methods approach to investigating streamflow recession characteristics should be considered for applications whenever possible.

scholarly journals Using satellite-based evapotranspiration estimates to improve the structure of a simple conceptual rainfall–runoff model

2017 ◽  
Vol 21 (2) ◽  
pp. 879-896 ◽  
Author(s):  
Tirthankar Roy ◽  
Hoshin V. Gupta ◽  
Aleix Serrat-Capdevila ◽  
Juan B. Valdes
Keyword(s):  
Model Performance ◽  
Hydrologic Model ◽  
Actual Evapotranspiration ◽  
Hydrologic Models ◽  
Catchment Scale ◽  
Model Driven ◽  
Alternative Approach ◽  
Precipitation Estimates ◽  
Daily Water ◽  
Rainfall Runoff Model

Abstract. Daily, quasi-global (50° N–S and 180° W–E), satellite-based estimates of actual evapotranspiration at 0.25° spatial resolution have recently become available, generated by the Global Land Evaporation Amsterdam Model (GLEAM). We investigate the use of these data to improve the performance of a simple lumped catchment-scale hydrologic model driven by satellite-based precipitation estimates to generate streamflow simulations for a poorly gauged basin in Africa. In one approach, we use GLEAM to constrain the evapotranspiration estimates generated by the model, thereby modifying daily water balance and improving model performance. In an alternative approach, we instead change the structure of the model to improve its ability to simulate actual evapotranspiration (as estimated by GLEAM). Finally, we test whether the GLEAM product is able to further improve the performance of the structurally modified model. Results indicate that while both approaches can provide improved simulations of streamflow, the second approach also improves the simulation of actual evapotranspiration significantly, which substantiates the importance of making diagnostic structural improvements to hydrologic models whenever possible.

RAIN Project: Results after 8 Years of Experimentally Reduced Acid Deposition to a Whole Catchment

1993 ◽  
Vol 50 (2) ◽  
pp. 258-268 ◽  
Author(s):  
Richard F. Wright ◽  
Erik Lotse ◽  
Arne Semb
Keyword(s):  
Acid Deposition ◽  
Soil Chemistry ◽  
Nitrogen Saturation ◽  
Base Cations ◽  
Strong Acid ◽  
Catchment Scale ◽  
Exclusion Experiment ◽  
Surface Water Chemistry ◽  
Southern Norway

At Risdalsheia (southern Norway), an ongoing catchment-scale acid-exclusion experiment has been conducted since 1984 as part of the RAIN project (Reversing Acidification In Norway). Acid precipitation is collected on a 1200-m2 transparent roof, treated by ion exchange, sea salts readded, and reapplied as clean rain beneath the roof Up to 1990 annual surveys of soil chemistry have revealed no significant trends. The chemical composition of runoff has changed: sulfate decreased from about 111 μeq/L in 1984 to 38 μeq/L in 1992 and nitrate from about 33 to 5 μeq/L. Base cations decreased and alkalinity increased over the 8-yr period from −88 to −29 μeq/L to compensate for this change in strong acid anions. Much of the alkalinity change is due to the increased role of organic anions. The results fit an empirical nomograph relating alkalinity, base cations, and strong acid anions and a new empirical nomograph relating alkalinity, H+, and total organic carbon. The acid-exclusion experiment provides the first catchment-scale evidence for the reversibility of nitrogen saturation; RAIN results corroborate field observations of changes in surface water chemistry in response to reduced acid deposition as well as process-oriented, conceptual acidification models.

scholarly journals Continuous state-space representation of a bucket-type rainfall-runoff model: a case study with the GR4 model using state-space GR4 (version 1.0)

2018 ◽  
Vol 11 (4) ◽  
pp. 1591-1605 ◽  
Author(s):  
Léonard Santos ◽  
Guillaume Thirel ◽  
Charles Perrin
Keyword(s):  
Water Balance ◽  
State Space ◽  
Operator Splitting ◽  
Space Representation ◽  
Rainfall Runoff ◽  
Integration Technique ◽  
State Space Representation ◽  
Rainfall Runoff Model ◽  
Unit Hydrographs ◽  
Runoff Model

Abstract. In many conceptual rainfall–runoff models, the water balance differential equations are not explicitly formulated. These differential equations are solved sequentially by splitting the equations into terms that can be solved analytically with a technique called “operator splitting”. As a result, only the solutions of the split equations are used to present the different models. This article provides a methodology to make the governing water balance equations of a bucket-type rainfall–runoff model explicit and to solve them continuously. This is done by setting up a comprehensive state-space representation of the model. By representing it in this way, the operator splitting, which makes the structural analysis of the model more complex, could be removed. In this state-space representation, the lag functions (unit hydrographs), which are frequent in rainfall–runoff models and make the resolution of the representation difficult, are first replaced by a so-called “Nash cascade” and then solved with a robust numerical integration technique. To illustrate this methodology, the GR4J model is taken as an example. The substitution of the unit hydrographs with a Nash cascade, even if it modifies the model behaviour when solved using operator splitting, does not modify it when the state-space representation is solved using an implicit integration technique. Indeed, the flow time series simulated by the new representation of the model are very similar to those simulated by the classic model. The use of a robust numerical technique that approximates a continuous-time model also improves the lag parameter consistency across time steps and provides a more time-consistent model with time-independent parameters.

scholarly journals State-space representation of a bucket-type rainfall-runoff model: a case study with State-Space GR4 (version 1.0)

2017 ◽  
Author(s):  
Léonard Santos ◽  
Guillaume Thirel ◽  
Charles Perrin
Keyword(s):  
Water Balance ◽  
Differential Equations ◽  
State Space ◽  
Operator Splitting ◽  
Space Representation ◽  
Rainfall Runoff ◽  
State Space Representation ◽  
Rainfall Runoff Model ◽  
Unit Hydrographs ◽  
Runoff Model

Abstract. In many conceptual rainfall-runoff models, the water balance differential equations are not explicitly formulated. These differential equations are solved sequentially by splitting the equations into terms that can be solved analytically with a technique called "operator splitting". As a result, only the resolutions of the split equations are used to present the different models. This article provides a methodology to make the governing water balance equations of a bucket-type rainfall-runoff model explicit. This is done by setting up a comprehensive state-space representation of the model. By representing it in this way, the operator splitting, which complexifies the structural analysis of the model, is removed. In this state-space representation, the lag functions (unit hydrographs), which are frequent in this type of model and make the resolution of the representation difficult, are replaced by a so-called "Nash cascade". This substitution also improves the lag parameter consistency across time steps. To illustrate this methodology, the GR4J model is taken as an example. The flow time series simulated by the new representation of the model are very similar to those simulated by the classic model. The state-space representation provides a more time-consistent model with time-independent parameters.

An experimental approach to reduce the parametric dimensionality for rainfall–runoff models

2016 ◽  
Vol 48 (1) ◽  
pp. 48-65 ◽  
Author(s):  
Jie Chen ◽  
Richard Arsenault ◽  
François P. Brissette
Keyword(s):  
Experimental Approach ◽  
Model Performance ◽  
Optimal Number ◽  
Model Parameters ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Efficiency Criterion ◽  
Performance Loss ◽  
The Past ◽  
Multi Objective Genetic Algorithm

Sobol’ sensitivity analysis has been used successfully in the past to reduce the parametric dimensionality for hydrological models. However, the effects of its limitation, in that it assumes an independence of parameters, need to be investigated. This study proposes an experimental approach to assess the commonly used Sobol’ analysis for reducing the parameter dimensionality of hydrological models. In this approach, the number of model parameters is directly pitted against an efficiency criterion within a multi-objective genetic algorithm (MOGA), thus allowing both the identification of key model parameters and the optimal number of parameters to be used within the same analysis. The proposed approach was tested and compared with the Sobol’ method based on a conceptual lumped hydrological model (HSAMI) with 23 free parameters. The results show that both methods performed very similarly, and allowed 11 out of 23 HSAMI parameters to be reduced with little loss in model performance. Based on this comparison, Sobol’ appears to be an effective and robust method despite its limitations. On the other hand, the MOGA algorithm outperformed Sobol’ analysis for further reduction of the parametric space and found optimal solutions with as few as eight parameters with minimal performance loss in validation.

Comparing runoff statistics simulated with a hydrological model utilizing stochastically generated lumped catchment rainfall and multiple point rainfall

2020 ◽  
Author(s):  
Luisa-Bianca Thiele ◽  
Ross Pidoto ◽  
Uwe Haberlandt
Keyword(s):  
Time Series ◽  
Hydrological Modelling ◽  
Flood Frequency ◽  
Multiple Point ◽  
Rainfall Time Series ◽  
Rainfall Runoff ◽  
Design Flood ◽  
Catchment Scale ◽  
Time Step ◽  
Rainfall Runoff Model

<p>For derived flood frequency analyses, stochastic rainfall models can be linked with rainfall-runoff models to improve the accuracy of design flood estimations when the length of observed rainfall and runoff data is not sufficient. In the past, when using stochastic rainfall time series for hydrological modelling purposes, catchment rainfall for use in hydrological modelling was calculated from the multiple point rainfall time series. As an alternative to this approach, it will be tested whether catchment rainfall can be modelled directly, negating the drawbacks (and need) encountered in generating spatially consistent time series. An Alternating Renewal rainfall model (ARM) will be used to generate multiple point and lumped catchment rainfall time series in hourly resolution. The generated rainfall time series will be used to drive the rainfall-runoff model HBV-IWW with an hourly time step for mesoscale catchments in Germany. Validation will be performed by comparing modelled runoff regarding runoff and flood statistics using stochastically generated lumped catchment rainfall versus multiple point rainfall. It would be advantageous if the results based on catchment rainfall are comparable to those using multiple point rainfall, so catchment rainfall could be generated directly with the stochastic rainfall models. Extremes at the catchment scale may also be better represented if catchment rainfall is generated directly.</p>

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.

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