Andreas Efstratiadis

One decade of multi-objective calibration approaches in hydrological modelling: a review

Abstract One decade after the first publications on multi-objective calibration of hydrological models, we summarize the experience gained so far by underlining the key perspectives offered by such approaches to improve parameter identification. After reviewing the fundamentals of vector optimization theory and the algorithmic issues, we link the multi-criteria calibration approach with the concepts of uncertainty and equifinality. Specifically, the multi-criteria framework enables recognition and handling of errors and uncertainties, and detection of prominent behavioural solutions with acceptable trade-offs. Particularly in models of complex parameterization, a multi-objective approach becomes essential for improving the identifiability of parameters and augmenting the information contained in calibration by means of both multi-response measurements and empirical metrics (“soft” data), which account for the hydrological expertise. Based on the literature review, we also provide alternative techniques for dealing with conflicting and non-commeasurable criteria, and hybrid strategies to utilize the information gained towards identifying promising compromise solutions that ensure consistent and reliable calibrations. Citation Efstratiadis, A. & Koutsoyiannis, D. (2010) One decade of multi-objective calibration approaches in hydrological modelling: a review. Hydrol. Sci. J. 55(1), 58–78.

On the credibility of climate predictions

Abstract Geographically distributed predictions of future climate, obtained through climate models, are widely used in hydrology and many other disciplines, typically without assessing their reliability. Here we compare the output of various models to temperature and precipitation observations from eight stations with long (over 100 years) records from around the globe. The results show that models perform poorly, even at a climatic (30-year) scale. Thus local model projections cannot be credible, whereas a common argument that models can perform better at larger spatial scales is unsupported.

A comparison of local and aggregated climate model outputs with observed data

Abstract We compare the output of various climate models to temperature and precipitation observations at 55 points around the globe. We also spatially aggregate model output and observations over the contiguous USA using data from 70 stations, and we perform comparison at several temporal scales, including a climatic (30-year) scale. Besides confirming the findings of a previous assessment study that model projections at point scale are poor, results show that the spatially integrated projections are also poor. Citation Anagnostopoulos, G. G., Koutsoyiannis, D., Christofides, A., Efstratiadis, A. & Mamassis, N. (2010) A comparison of local and aggregated climate model outputs with observed data. Hydrol. Sci. J. 55(7), 1094–1110.

Uncertainty Assessment of Future Hydroclimatic Predictions: A Comparison of Probabilistic and Scenario-Based Approaches

Abstract During the last decade, numerous studies have been carried out to predict future climate based on climatic models run on the global scale and fed by plausible scenarios about anthropogenic forcing to climate. Based on climatic model output, hydrologic models attempt then to predict future hydrologic regimes at regional scales. Much less systematic work has been done to estimate climatic uncertainty and to assess the climatic and hydrologic model outputs within an uncertainty perspective. In this study, a stochastic framework for future climatic uncertainty is proposed, based on the following lines: 1) climate is not constant but rather varying in time and expressed by the long-term (e.g., 30 yr) time average of a natural process, defined on a finescale; 2) the evolution of climate is represented as a stochastic process; 3) the distributional parameters of a process, marginal and dependence, are estimated from an available sample by statistical methods; 4) the climatic uncertainty is the result of...

A decision support system for the management of the water resource system of Athens

Abstract The main components of a decision support system (DSS) developed to support the management of the water resource system of Athens are presented. The DSS includes information systems that perform data acquisition, management and visualisation, and models that perform simulation and optimisation of the hydrosystem. The models, which are the focus of the present work, are organised into two main modules. The first one is a stochastic hydrological simulator, which, based on the analysis of historical hydrological data, generates simulations and forecasts of the hydrosystem inputs. The second one allows the detailed study of the hydrosystem under alternative management policies implementing the parameterisation–simulation–optimisation methodology. The mathematical framework of this new methodology performs the allocation of the water resources to the different system components, keeping the number of control variables small and thus reducing the computational effort, even for a complex hydrosystem like the one under study. Multiple, competitive targets and constraints with different priorities can be set, which are concerned among others, with the system reliability and risk, the overall average operational cost and the overall guaranteed yield of the system. The DSS is now in the final stage of its development and its results, some of which are summarised in the paper, have been utilised to support the new masterplan of the hydrosystem management.

A multivariate stochastic model for the generation of synthetic time series at multiple time scales reproducing long-term persistence

A time series generator is presented, employing a robust three-level multivariate scheme for stochastic simulation of correlated processes. It preserves the essential statistical characteristics of historical data at three time scales (annual, monthly, daily), using a disaggregation approach. It also reproduces key properties of hydrometeorological and geophysical processes, namely the long-term persistence (Hurst-Kolmogorov behaviour), the periodicity and intermittency. Its efficiency is illustrated through two case studies in Greece. The first aims to generate monthly runoff and rainfall data at three reservoirs of the hydrosystem of Athens. The second involves the generation of daily rainfall for flood simulation at five rain gauges. In the first emphasis is given to long-term persistence - a dominant characteristic in the management of large-scale hydrosystems, comprising reservoirs with carry-over storage capacity. In the second we highlight to the consistent representation of intermittency and asymmetry of daily rainfall, and the distribution of annual daily maxima. We provide a multivariate generator based on a three-level disaggregation scheme.The model preserves the statistical behaviour of observed data at multiple scales.Long-term persistence is reproduced through a used-defined autocovariance function.Highly-skewed and intermittent processes, e.g. rainfall, are effectively modelled.The methodology is applicable for both steady-state and terminating simulations.

Calibration of a semi-distributed model for conjunctive simulation of surface and groundwater flows / Calage d’un modèle semi-distribué pour la simulation conjointe d’écoulements superficiels et souterrains

Abstract Abstract A hydrological simulation model was developed for conjunctive representation of surface and groundwater processes. It comprises a conceptual soil moisture accounting module, based on an enhanced version of the Thornthwaite model for the soil moisture reservoir, a Darcian multi-cell groundwater flow module and a module for partitioning water abstractions among water resources. The resulting integrated scheme is highly flexible in the choice of time (i.e. monthly to daily) and space scales (catchment scale, aquifer scale). Model calibration involved successive phases of manual and automatic sessions. For the latter, an innovative optimization method called evolutionary annealing-simplex algorithm is devised. The objective function involves weighted goodness-of-fit criteria for multiple variables with different observation periods, as well as penalty terms for restricting unrealistic water storage trends and deviations from observed intermittency of spring flows. Checks of the unmeasured catchment responses through manually changing parameter bounds guided choosing final parameter sets. The model is applied to the particularly complex Boeoticos Kephisos basin, Greece, where it accurately reproduced the main basin response, i.e. the runoff at its outlet, and also other important components. Emphasis is put on the principle of parsimony which resulted in a computationally effective modelling. This is crucial since the model is to be integrated within a stochastic simulation framework.

Hydrological modelling of temporally-varying catchments: facets of change and the value of information

Abstract River basins are by definition temporally-varying systems: changes are apparent at every temporal scale, in terms of changing meteorological inputs and catchment characteristics due to inherently uncertain natural processes and anthropogenic interventions. In an operational context, the ultimate goal of hydrological modelling is predicting responses of the basin under conditions that are similar or different to those observed in the past. Since water management studies require that anthropogenic effects are considered known and a long hypothetical period is simulated, the combined use of stochastic models, for generating the inputs, and deterministic models that also represent the human interventions in modified basins, is found to be a powerful approach for providing realistic and statistically consistent simulations (in terms of product moments and correlations, at multiple time scales, and long-term persistence). The proposed framework is investigated on the Ferson Creek basin (USA) that exhibits significantly growing urbanization during the last 30 years. Alternative deterministic modelling options include a lumped water balance model with one time-varying parameter and a semi-distributed scheme based on the concept of hydrological response units. Model inputs and errors are respectively represented through linear and nonlinear stochastic models. The resulting nonlinear stochastic framework maximizes the exploitation of the existing information by taking advantage of the calibration protocol used in this issue.

Minimizing water cost in water resource management of Athens

This paper considers the minimization of the cost of water through an integrated water resources planning and management model, implemented within the decision support system for the management of the Athens water supply system. The mathematical framework employs a simulation-optimization scheme, where simulation is applied to faithfully represent the system operation, whereas optimization is applied to derive the optimal management policy, which simultaneously minimizes the risk and cost of decision-making. Real economic criteria in addition to artificial costs are appropriately assigned to preserve the physical constraints and water use priorities, ensuring also the lowest-cost transportation of water from sources to the point of consumption. The proposed model is tested on the hydrosystem of Athens, in order to minimize the expected operational costs for several system configurations.

Scientific dialogue on climate: is it giving black eyes or opening closed eyes? Reply to “A black eye for the Hydrological Sciences Journal” by D. Huard

Citation Koutsoyiannis, D., Christofides, A., Efstratiadis, A., Anagnostopoulos, G.G. and Mamassis, N. (2011) Scientific dialogue on climate: is it giving black eyes or opening closed eyes? Reply to “A black eye for the Hydrological Sciences Journal” by D. Huard, Hydrol. Sci. J. 56(7), 1334–1339.