Initial evaluation of a simple coupled surface and ground water hydrological model to assess sustainable ground water abstractions at the regional scale

2009 ◽  
Vol 41 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Denis A. Hughes ◽  
Evison Kapangaziwiri ◽  
Kathleen Baker
Keyword(s):  
Ground Water ◽  
Regional Scale ◽  
Model Parameters ◽  
Parameter Uncertainties ◽  
Ungauged Catchments ◽  
Model Configuration ◽  
Data Deficient ◽  
Rainfall Runoff Model ◽  
Available Information ◽  
Runoff Model

Additional surface–ground water interaction routines were recently added to the Pitman monthly rainfall–runoff model, widely used in South Africa for quantifying water resources in ungauged catchments. Some evaluations of the model have demonstrated that it can realistically simulate interactions between surface and ground water at catchment scales of approximately 100 to 5,000 km2. The model allows ground water abstractions to be simulated, but no reported evaluations of this component are available. This study uses the model to estimate sustainable abstraction volumes in a semi-arid catchment and includes an assessment of model parameter uncertainties. In recognition of potential spatial scale issues related to the model structure an alternative model configuration, based on splitting the total catchment into recharge and abstraction sub-catchments, was also tested. While the results appear to be conceptually appropriate, there is insufficient available information to quantitatively confirm the model parameters and results. The same would apply regardless of the type of model being applied in such a data-deficient area. Additional geo-hydrological information is required to resolve the model uncertainties and improve the parameter estimation process. This pilot study has highlighted the type of information required, but further work is needed to identify how best to obtain that information.

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 Accounting for dependencies in regionalized signatures for predictions in ungauged catchments

2015 ◽  
Vol 12 (6) ◽  
pp. 5389-5426 ◽  
Author(s):  
S. Almeida ◽  
N. Le Vine ◽  
N. McIntyre ◽  
T. Wagener ◽  
W. Buytaert
Keyword(s):  
Joint Probability ◽  
Joint Probability Distribution ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Ungauged Catchments ◽  
Independent Information ◽  
Streamflow Data ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Selection Of

Abstract. A recurrent problem in hydrology is the absence of streamflow data to calibrate rainfall-runoff models. A commonly used approach in such circumstances conditions model parameters on regionalized response signatures. While several different signatures are often available to be included in this process, an outstanding challenge is the selection of signatures that provide useful and complementary information. Different signatures do not necessarily provide independent information, and this has led to signatures being omitted or included on a subjective basis. This paper presents a method that accounts for the inter-signature error correlation structure so that regional information is neither neglected nor double-counted when multiple signatures are included. Using 84 catchments from the MOPEX database, observed signatures are regressed against physical and climatic catchment attributes. The derived relationships are then utilized to assess the joint probability distribution of the signature regionalization errors that is subsequently used in a Bayesian procedure to condition a rainfall-runoff model. The results show that the consideration of the inter-signature error structure may improve predictions when the error correlations are strong. However, other uncertainties such as model structure and observational error may outweigh the importance of these correlations. Further, these other uncertainties cause some signatures to appear repeatedly to be disinformative.

scholarly journals Accounting for dependencies in regionalized signatures for predictions in ungauged catchments

2016 ◽  
Vol 20 (2) ◽  
pp. 887-901 ◽  
Author(s):  
Susana Almeida ◽  
Nataliya Le Vine ◽  
Neil McIntyre ◽  
Thorsten Wagener ◽  
Wouter Buytaert
Keyword(s):  
Joint Probability ◽  
Joint Probability Distribution ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Ungauged Catchments ◽  
Independent Information ◽  
Streamflow Data ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Selection Of

Abstract. A recurrent problem in hydrology is the absence of streamflow data to calibrate rainfall–runoff models. A commonly used approach in such circumstances conditions model parameters on regionalized response signatures. While several different signatures are often available to be included in this process, an outstanding challenge is the selection of signatures that provide useful and complementary information. Different signatures do not necessarily provide independent information and this has led to signatures being omitted or included on a subjective basis. This paper presents a method that accounts for the inter-signature error correlation structure so that regional information is neither neglected nor double-counted when multiple signatures are included. Using 84 catchments from the MOPEX database, observed signatures are regressed against physical and climatic catchment attributes. The derived relationships are then utilized to assess the joint probability distribution of the signature regionalization errors that is subsequently used in a Bayesian procedure to condition a rainfall–runoff model. The results show that the consideration of the inter-signature error structure may improve predictions when the error correlations are strong. However, other uncertainties such as model structure and observational error may outweigh the importance of these correlations. Further, these other uncertainties cause some signatures to appear repeatedly to be misinformative.

scholarly journals Calibration of hydrological model parameters for ungauged catchments

2006 ◽  
Vol 3 (3) ◽  
pp. 1105-1124 ◽  
Author(s):  
A. Bárdossy
Keyword(s):  
Model Calibration ◽  
Hydrological Model ◽  
Model Parameters ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Regional Function ◽  
Ungauged Catchments ◽  
Rainfall Runoff Model ◽  
Climate Statistics ◽  
Runoff Model

Abstract. The parameters of hydrological models for catchments with few or no discharge records can only 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. Transferable parameter sets are identified using regional statistics: means and variances of annual discharges estimated from catchment properties and annual climate statistics.

scholarly journals Regionalizing rainfall–runoff model parameters to predict the daily streamflow of ungauged catchments in the dry tropics

2009 ◽  
Vol 40 (5) ◽  
pp. 433-444 ◽  
Author(s):  
David A. Post
Keyword(s):  
Input Data ◽  
Water Yield ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Wet Season ◽  
Daily Streamflow ◽  
Total Length ◽  
Dry Tropics ◽  
Rainfall Runoff Model ◽  
Runoff Model

A methodology has been derived which allows an estimate to be made of the daily streamflow at any point within the Burdekin catchment in the dry tropics of Australia. The input data requirements are daily rainfall (to drive the rainfall–runoff model) and mean average wet season rainfall, total length of streams, percent cropping and percent forest in the catchment (to regionalize the parameters of the rainfall–runoff model). The method is based on the use of a simple, lumped parameter rainfall–runoff model, IHACRES (Identification of unit Hydrographs And Component flows from Rainfall, Evaporation and Streamflow data). Of the five parameters in the model, three have been set to constants to reflect regional conditions while the other two have been related to physio-climatic attributes of the catchment under consideration. The parameter defining total catchment water yield (c) has been estimated based on the mean average wet season rainfall, while the streamflow recession time constant (τ) has been estimated based on the total length of streams, percent cropping and percent forest in the catchment. These relationships have been shown to be applicable over a range of scales from 68–130,146 km2. However, three separate relationships were required to define c in the three major physiographic regions of the Burdekin: the upper Burdekin, Bowen and Suttor/lower Burdekin. The invariance of the relationships with scale indicates that the dominant processes may be similar across a range of scales. The fact that different relationships were required for each of the three major regions indicates the geographic limitations of this regionalization approach. For most of the 24 gauged catchments within the Burdekin the regionalized rainfall–runoff models were nearly as good as or better than the rainfall–runoff models calibrated to the observed streamflow. In addition, models often performed better over the simulation period than the calibration period. This indicates that future improvements in regionalization should focus on improving the quality of input data and rainfall–runoff model conceptualization rather than on the regionalization procedure per se.

Analysis of parameter uncertainty of a flow and quality stormwater model

2009 ◽  
Vol 60 (3) ◽  
pp. 717-725 ◽  
Author(s):  
C. B. S. Dotto ◽  
A. Deletic ◽  
T. D. Fletcher
Keyword(s):  
Water Quality ◽  
Bayesian Methods ◽  
Flow Model ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Sources Of Uncertainty ◽  
Music Model ◽  
Rainfall Runoff Model ◽  
Water Quality Models ◽  
Runoff Model

Uncertainty is intrinsic to all monitoring programs and all models. It cannot realistically be eliminated, but it is necessary to understand the sources of uncertainty, and their consequences on models and decisions. The aim of this paper is to evaluate uncertainty in a flow and water quality stormwater model, due to the model parameters and the availability of data for calibration and validation of the flow model. The MUSIC model, widely used in Australian stormwater practice, has been investigated. Frequentist and Bayesian methods were used for calibration and sensitivity analysis, respectively. It was found that out of 13 calibration parameters of the rainfall/runoff model, only two matter (the model results were not sensitive to the other 11). This suggests that the model can be simplified without losing its accuracy. The evaluation of the water quality models proved to be much more difficult. For the specific catchment and model tested, we argue that for rainfall/runoff, 6 months of data for calibration and 6 months of data for validation are required to produce reliable predictions. Further work is needed to make similar recommendations for modelling water quality.

Effect of rainfall data errors on the optimized values of model parameters

Soil Research ◽  
1982 ◽  
Vol 20 (1) ◽  
pp. 15
Author(s):  
WC Boughton ◽  
FT Sefe
Keyword(s):  
Storage Capacity ◽  
Rainfall Data ◽  
Model Parameters ◽  
Similar Magnitude ◽  
Rainfall Runoff ◽  
Data Errors ◽  
Cast Doubt ◽  
Rainfall Runoff Model ◽  
Induced Changes ◽  
Runoff Model

The rainfall input to a rainfall-runoff model was arbitrarily increased and decreased in order to determine the magnitude of corresponding changes in optimized values of the model parameters. The optimized capacities of moisture stores representing surface storage capacity of a catchment changed by average amounts of +24% and -20% as rainfall input was changed by +10% and -10%, respectively. Values of other parameters showed changes of similar magnitude, but there was no uniformity in the magnitude of induced changes from catchment to catchment. The results cast doubt on the validity of relating optimized values of model parameters to physical characteristics of catchments.

scholarly journals Assimilating scatterometer soil moisture data into conceptual hydrologic models at the regional scale

2006 ◽  
Vol 10 (3) ◽  
pp. 353-368 ◽  
Author(s):  
J. Parajka ◽  
V. Naeimi ◽  
G. Blöschl ◽  
W. Wagner ◽  
R. Merz ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Regional Scale ◽  
Hydrologic Model ◽  
Hydrologic Models ◽  
Ungauged Catchments ◽  
Soil Moisture Dynamics ◽  
Model Efficiency ◽  
The Relationship ◽  
Runoff Model ◽  
Moisture Dynamics

Abstract. This paper examines the potential of scatterometer data from ERS satellites for improving hydrological simulations in both gauged and ungauged catchments. We compare the soil moisture dynamics simulated by a semidistributed hydrologic model in 320 Austrian catchments with the soil moisture dynamics inferred from the satellite data. The most apparent differences occur in the Alpine areas. Assimilating the scatterometer data into the hydrologic model during the calibration phase improves the relationship between the two soil moisture estimates without any significant decrease in runoff model efficiency. For the case of ungauged catchments, assimilating scatterometer data does not improve the daily runoff simulations but does provide more consistent soil moisture estimates. If the main interest is in obtaining estimates of catchment soil moisture, reconciling the two sources of soil moisture information seems to be of value because of the different error structures.

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