Operational testing of a water balance model for predicting climate change impacts (original) (raw)
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Acta Hydrologica Slovaca, 2020
Conceptual rainfall-runoff models are routinely used in practical water resources investigations. Common uncertainties associated with these models (in addition to the uncertainty related to schematization and structure of the models) include for example errors in the inputs, calibration/validation uncertainties (e.g., choice of the suitable lengths of the two periods), uncertainties related to the use of the models in other climatic conditions, etc. This study addresses the uncertainties related to the choice of calibration/validation periods for the long data sets with varying climatic inputs. It is conducted in the pilot catchment of the Jalovecký Creek (area 22.2 km 2) in Slovakia and uses data from the 30-years long period 1989-2018. A HBV type model (the TUW model) is used for the modelling. Two different approaches to selection of calibration period are compared. In the first approach, the calibration period is determined by division of the available data into three equally long periods (each of them is then used in model calibration and validation). Such an arbitrary division is the common practice in hydrological modelling. In the second approach, the selection of calibration periods is based on the cycles found in the measured data. The wavelet transform method revealed cyclical components in air temperature with period of 6-years. Periods in other data sets were less significant. In accordance with this finding, the model is calibrated for five 6-years long periods. Model performance for the two approaches to selection of the calibration periods is evaluated by visual comparison of measured and simulated monthly flows in different climatic periods and by the Nash-Sutcliffe efficiency coefficient. The two approaches to the selection of calibration period provided similar results. However, the model calibrated in colder period represents monthly flows more reliably than the model that was calibrated in warmer period. In terms of predictions related to climate change impacts it would mean that hydrological models calibrated in current period should provide reasonable simulations for warmer climate.
An integrated procedure to evaluate hydrological models
Hydrological Processes, 2010
The growing concern for health-related problems deriving from pollutants leaching is driving national and international administrations to support the development of tools for evaluating the effects of alternate management scenarios and identifying vulnerable areas. Cropping systems models are powerful tools for evaluating leachates under different environmental, social, and management conditions. As percolating water is the transport vehicle for pollutants transport in soil, a reliable evaluation of water balance models is a fundamental prerequisite for investigating pesticides and nitrate fate. As specific approaches for the evaluation of multi-layer evolution of state variables are missing, we propose a fuzzy-based, integrated indicator (I SWC : 0, best; 1, worst) for a comprehensive evaluation of soil water content (SWC) simulations. We aggregated error metrics with others quantifying the homogeneity of errors across different soil layers, the capability of models to reproduce complex dynamics function of both time and soil depth, and model complexity. We tested I SWC on a sample dataset where the models CropSyst and CERES-Wheat were used to simulate SWC for winter wheat systems. I SWC revealed that, in the explored conditions, the global assessment of the two models' performances allowed identification of CropSyst as the best (average I SWC D 0Ð441, with a value of 0Ð537 obtained by CERES-Wheat), although each model prevailed for some of the metrics. CropSyst presented the highest accuracy (average agreement module D 0Ð400), whereas CERES-Wheat's accuracy was slightly worse, although achieved with a simplified modelling approach (average Akaike Information Criterion D 230Ð44), thereby favouring largearea applicability. The non-univocal scores achieved by the models for the different metrics support the use of multi-metric evaluation approaches for quantifying the different aspects of water balance model performances.
Physics and Chemistry of the Earth, Parts A/B/C, 2012
In this paper, we discuss validation of hydrological models, namely the process of evaluating performance of a simulation and/or prediction model. We briefly review the validation procedures that are frequently used in hydrology making a distinction between scientific validation and performance validation. Finally, we propose guidelines for carrying out model validation with the aim of providing agreed methodologies to efficiently assess model peculiarities and limitations, and to quantify simulation performance.
Hydrology and Earth System Sciences Discussions, 2011
Conceptual hydrological models are widely used for climate change impact assessment. The implicit assumption in most such work is that the parameters estimated from observations remain valid for future climatic conditions. This paper evaluates a simple threshold based approach for testing this assumption, where a set of behavioural simulators are identified for different climatic conditions for the future simulation i.e. wet, average and dry conditions. These simulators were derived using three different data sets that are generated by sampling a block of one year of data without replacement from the observations such that they define the different climatic conditions. The simulators estimated from the wet climatic data set showed the tendency to underestimate flow when applied to dry data set and vice versa. However, the performances of the three sets of basin simulators on chronologically coherent data are identical to the simulators identified from a sufficiently long data series that contains both wet and dry climatic conditions. The results presented suggest that the issue of time invariance in the value of parameters has a minimal effect on the simulation if the change in precipitation is less than 10 % of the data used for calibration.
Validation of catchment models for predicting land-use and climate change impacts. 1. Method
1996
Computer simulation models are increasingly being proposed as tools capable of giving water resource managers accurate predictions of the impact of changes in land-use and climate. Previous validation testing of catchment models is reviewed, and it is concluded that the methods used do not clearly test a model's fitness for such a purpose. A new generally applicable method is proposed. This involves the direct testing of fitness for purpose, uses established scientific techniques, and may be implemented within a quality assured programme of work. The new method is applied in Part 2 of this study (
Water Resources Research, 2012
This paper investigates the actual extrapolation capacity of three hydrological models in differing climate conditions. We propose a general testing framework, in which we perform series of split-sample tests, testing all possible combinations of calibration-validation periods using a 10 year sliding window. This methodology, which we have called the generalized split-sample test (GSST), provides insights into the model's transposability over time under various climatic conditions. The three conceptual rainfall-runoff models yielded similar results over a set of 216 catchments in southeast Australia. First, we assessed the model's efficiency in validation using a criterion combining the root-mean-square error and bias. A relation was found between this efficiency and the changes in mean rainfall (P) but not with changes in mean potential evapotranspiration (PE) or air temperature (T). Second, we focused on average runoff volumes and found that simulation biases are greatly affected by changes in P. Calibration over a wetter (drier) climate than the validation climate leads to an overestimation (underestimation) of the mean simulated runoff. We observed different magnitudes of these models deficiencies depending on the catchment considered. Results indicate that the transfer of model parameters in time may introduce a significant level of errors in simulations, meaning increased uncertainty in the various practical applications of these models (flow simulation, forecasting, design, reservoir management, climate change impact assessments, etc.). Testing model robustness with respect to this issue should help better quantify these uncertainties.
2021
Prior to their use under future changing climate conditions, all hydrological models should be thoroughly evaluated regarding their temporal transferability (application in different time periods) and extrapolation capacity (application beyond the range of known past conditions). This note presents a straightforward evaluation framework aimed at detecting potential undesirable climate dependencies in hydrological models: the robustness assessment test (RAT). Although it is conceptually inspired by the classic differential split-sample test of Klemeš (1986), the RAT presents the advantage of being applicable to all types of models, be they calibrated or not (i.e. regionalized or physically based). In this note, we present the RAT, illustrate its application on a set of 21 catchments, verify its applicability hypotheses and compare it to previously published tests. Results show that the RAT is an efficient evaluation approach, passing it successfully can be considered a prerequisite for any hydrological model to be used for climate change impact studies.