scholarly journals A multi‐objective approach to select hydrological models and constrain structural uncertainties for climate impact assessments

2021 ◽  
Author(s):  
Danny Saavedra ◽  
Pablo A. Mendoza ◽  
Nans Addor ◽  
Harold Llauca ◽  
Ximena Vargas
Keyword(s):  
Climate Impact ◽  
Hydrological Models ◽  
Multi Objective ◽  
Structural Uncertainties

scholarly journals A multi-objective approach to select hydrological models and constrain structural uncertainties for climate impact assessments

2021 ◽  
Author(s):  
Danny Saavedra ◽  
Pablo Mendoza ◽  
Nans Addor ◽  
Harold Llauca ◽  
Ximena Vargas
Keyword(s):  
Model Selection ◽  
Climate Change Impacts ◽  
Climate Impact ◽  
Climatic Conditions ◽  
Hydrological Models ◽  
Multi Objective ◽  
Modelling Framework ◽  
Structural Uncertainties ◽  
Low Performance ◽  
Model Structures

The assessment of climate change impacts on water resources and flood risk is typically underpinned by hydrological models calibrated and selected based on observed streamflow records. Yet, changes in climate are rarely accounted for when selecting hydrological models, which compromises their ability to robustly represent future changes in catchment hydrology. In this paper, we test a simple framework for selecting an ensemble of calibrated hydrological model structures in catchments where changing climatic conditions have been observed. We start by considering 78 model structures produced using the FUSE modular modelling framework and rely on a Pareto scheme to select model structures maximizing model efficiency in both wet and dry periods. The application of this approach in three case study basins in Peru enables the identification of structures with good robustness, but also good performance according to hydrological signatures not used for model selection. We also highlight that some model structures that perform well according to traditional efficiency metrics have low performance in contrasting climates or suspicious internal states and fluxes. Importantly, the model selection approach followed here helps to reduce the spread in precipitation elasticities and temperature sensitivities, providing a clearer picture of future hydrological changes. Overall, this work demonstrates the potential of using contrasting climatic conditions in a multi-objective framework to produce robust and credible simulations, and to constrain structural uncertainties in hydrological projections.

scholarly journals Are we using the right fuel to drive hydrological models? A climate impact study in the Upper Blue Nile

2018 ◽  
Vol 22 (4) ◽  
pp. 2163-2185 ◽  
Author(s):  
Stefan Liersch ◽  
Julia Tecklenburg ◽  
Henning Rust ◽  
Andreas Dobler ◽  
Madlen Fischer ◽  
...  
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Models ◽  
Regional Climate ◽  
Model Performance ◽  
Climate Impact ◽  
Hydrological Models ◽  
Blue Nile ◽  
Projected Change ◽  
Model Ensembles

Abstract. Climate simulations are the fuel to drive hydrological models that are used to assess the impacts of climate change and variability on hydrological parameters, such as river discharges, soil moisture, and evapotranspiration. Unlike with cars, where we know which fuel the engine requires, we never know in advance what unexpected side effects might be caused by the fuel we feed our models with. Sometimes we increase the fuel's octane number (bias correction) to achieve better performance and find out that the model behaves differently but not always as was expected or desired. This study investigates the impacts of projected climate change on the hydrology of the Upper Blue Nile catchment using two model ensembles consisting of five global CMIP5 Earth system models and 10 regional climate models (CORDEX Africa). WATCH forcing data were used to calibrate an eco-hydrological model and to bias-correct both model ensembles using slightly differing approaches. On the one hand it was found that the bias correction methods considerably improved the performance of average rainfall characteristics in the reference period (1970–1999) in most of the cases. This also holds true for non-extreme discharge conditions between Q20 and Q80. On the other hand, bias-corrected simulations tend to overemphasize magnitudes of projected change signals and extremes. A general weakness of both uncorrected and bias-corrected simulations is the rather poor representation of high and low flows and their extremes, which were often deteriorated by bias correction. This inaccuracy is a crucial deficiency for regional impact studies dealing with water management issues and it is therefore important to analyse model performance and characteristics and the effect of bias correction, and eventually to exclude some climate models from the ensemble. However, the multi-model means of all ensembles project increasing average annual discharges in the Upper Blue Nile catchment and a shift in seasonal patterns, with decreasing discharges in June and July and increasing discharges from August to November.

scholarly journals How evaluation of global hydrological models can help to improve credibility of river discharge projections under climate change

2020 ◽  
Vol 163 (3) ◽  
pp. 1353-1377 ◽  
Author(s):  
Valentina Krysanova ◽  
Jamal Zaherpour ◽  
Iulii Didovets ◽  
Simon N. Gosling ◽  
Dieter Gerten ◽  
...  
Keyword(s):  
Impact Assessment ◽  
Model Evaluation ◽  
Model Performance ◽  
Poor Performance ◽  
Climate Impact ◽  
Hydrological Models ◽  
Weighted Mean ◽  
Climate Impact Assessment ◽  
Ensemble Mean ◽  
The Mean

AbstractImportance of evaluation of global hydrological models (gHMs) before doing climate impact assessment was underlined in several studies. The main objective of this study is to evaluate the performance of six gHMs in simulating observed discharge for a set of 57 large catchments applying common metrics with thresholds for the monthly and seasonal dynamics and summarize them estimating an aggregated index of model performance for each model in each basin. One model showed a good performance, and other five showed a weak or poor performance in most of the basins. In 15 catchments, evaluation results of all models were poor. The model evaluation was supplemented by climate impact assessment for a subset of 12 representative catchments using (1) usual ensemble mean approach and (2) weighted mean approach based on model performance, and the outcomes were compared. The comparison of impacts in terms of mean monthly and mean annual discharges using two approaches has shown that in four basins, differences were negligible or small, and in eight catchments, differences in mean monthly, mean annual discharge or both were moderate to large. The spreads were notably decreased in most cases when the second method was applied. It can be concluded that for improving credibility of projections, the model evaluation and application of the weighted mean approach could be recommended, especially if the mean monthly (seasonal) impacts are of interest, whereas the ensemble mean approach could be applied for projecting the mean annual changes. The calibration of gHMs could improve their performance and, consequently, the credibility of projections.

scholarly journals How evaluation of hydrological models influences results of climate impact assessment—an editorial

2020 ◽  
Vol 163 (3) ◽  
pp. 1121-1141
Author(s):  
Valentina Krysanova ◽  
Fred F. Hattermann ◽  
Zbigniew W. Kundzewicz
Keyword(s):  
Impact Assessment ◽  
Model Evaluation ◽  
Regional Scale ◽  
Global Scale ◽  
Climate Impact ◽  
Climate Impacts ◽  
Hydrological Models ◽  
Calibration And Validation ◽  
Climate Impact Assessment ◽  
Scale Models

AbstractThis paper introduces the Special Issue (SI) “How evaluation of hydrological models influences results of climate impact assessment.” The main objectives were as follows: (a) to test a comprehensive model calibration/validation procedure, consisting of five steps, for regional-scale hydrological models; (b) to evaluate performance of global-scale hydrological models; and (c) to reveal whether the calibration/validation methods and the model evaluation results influence climate impacts in terms of the magnitude of the change signal and the uncertainty range. Here, we shortly describe the river basins and large regions used as case studies; the hydrological models, data, and climate scenarios used in the studies; and the applied approaches for model evaluation and for analysis of projections for the future. After that, we summarize the main findings. The following general conclusions could be drawn. After successful comprehensive calibration and validation, the regional-scale models are more robust and their projections for the future differ from those of the model versions after the conventional calibration and validation. Therefore, climate impacts based on the former models are more trustworthy than those simulated by the latter models. Regarding the global-scale models, using only models with satisfactory or good performance on historical data and weighting them based on model evaluation results is a more reliable approach for impact assessment compared to the ensemble mean approach that is commonly used. The former method provides impact results with higher credibility and reduced spreads in comparison to the latter approach. The studies for this SI were performed in the framework of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP).

Multi-objective parameter optimization of the HYPE model using shuffled frog-leaping algorithm

2021 ◽  
Author(s):  
Xinyu Li ◽  
Prajna Kasargodu Anebgailu ◽  
Jörg Dietrich
Keyword(s):  
Optimization Problems ◽  
Population Based ◽  
Optimization Techniques ◽  
Model Parameters ◽  
Hydrological Models ◽  
Watershed Model ◽  
Shuffled Frog Leaping Algorithm ◽  
Multi Objective ◽  
Combinatorial Optimization Problems ◽  
Shuffled Frog Leaping

<p>The calibration of hydrological models using bio-inspired meta-heuristic optimization techniques has been extensively tested to find the optimal parameters for hydrological models. Shuffled frog-leaping algorithm (SFLA) is a population-based cooperative search technique containing virtual interactive frogs distributed into multiple memeplexes. The frogs search locally in each memeplex and are periodically shuffled into new memeplexes to ensure global exploration. Though it is developed for discrete optimization, it can be used to solve multi-objective combinatorial optimization problems as well.</p><p>In this study, a hydrological catchment model, Hydrological Predictions for the Environment (HYPE) is calibrated for streamflow and nitrate concentration in the catchment using SFLA. HYPE is a semi-distributed watershed model that simulates runoff and other hydrological processes based on physical as well as conceptual laws. SFLA with 200 runtimes and 5 memeplexes containing 10 frogs each is used to calibrate 22 model parameters. It is compared with manual calibration and Differential Evolution Markov Chain (DEMC) method from the HYPE-tool. The preliminary results of the statistical performance measures for streamflow calibration show that SFLA has the fastest convergence speed and higher stability when compared with the DEMC method. NSE of 0.68 and PBIAS of 7.72 are recorded for the best run of SFLA during the calibration of streamflow. In comparison, the HYPE-tool DEMC produced the best NSE of 0.45 and a PBIAS of -3.37 while the manual calibration resulted in NSE of 0.64 and PBIAS of 2.01.</p>

scholarly journals Can multi-objective calibration of streamflow guarantee better hydrological model accuracy?

2018 ◽  
Vol 20 (3) ◽  
pp. 687-698 ◽  
Author(s):  
Ruqiang Zhang ◽  
Junguo Liu ◽  
Hongkai Gao ◽  
Ganquan Mao
Keyword(s):  
Northwest China ◽  
High Flow ◽  
Low Flow ◽  
Heihe River ◽  
Hydrological Models ◽  
Model Accuracy ◽  
Multi Objective ◽  
Simulation Based ◽  
Single Calibration ◽  
Single Objective

Abstract Hydrological models often require calibration. Multi-objective calibration has been more widely used than single-objective calibration. However, it has not been fully ascertained that multi-objective calibration will necessarily guarantee better model accuracy. To test whether multi-calibration was effective in comparison to single-calibration in terms of model accuracy, two strategies were tested out. For these strategies, the objective functions used included the Nash–Sutcliffe efficiency and its logarithmic form, which highlight high flow and low flow, respectively. These two indexes were first used for multi-objective calibration, and then they were separately employed for single-objective calibration. To assess the calibration strategies' accuracy, the simulated streamflow was compared with observed streamflow, particularly high flow and low flow. This study was conducted in the upper stream of the Heihe River basin in northwest China using the FLEX-Topo model and MOSCEM-UA algorithm. The results show that the simulation based on the Nash–Sutcliffe efficiency performed best both in modelling the dynamics and simulating the high flow of the observed streamflow. Thus, it seems that multi-objective calibration does not necessarily lead to better model accuracy. This conclusion might provide useful information for hydrologists in calibrating their models, making their simulations more reliable.

scholarly journals Multi-model climate impact assessment and intercomparison for three large-scale river basins on three continents

2014 ◽  
Vol 5 (2) ◽  
pp. 849-900 ◽  
Author(s):  
T. Vetter ◽  
S. Huang ◽  
V. Aich ◽  
T. Yang ◽  
X. Wang ◽  
...  
Keyword(s):  
Impact Assessment ◽  
Climate Models ◽  
Water Discharge ◽  
River Basins ◽  
Climate Impact ◽  
Climate Impacts ◽  
Hydrological Models ◽  
Climate Scenarios ◽  
Climate Impact Assessment ◽  
The Impact

Abstract. Climate change impacts on hydrological processes should be simulated for river basins using validated models and multiple climate scenarios in order to provide reliable results for stakeholders. In the last 10–15 years climate impact assessment was performed for many river basins worldwide using different climate scenarios and models. Nevertheless, the results are hardly comparable and do not allow to create a full picture of impacts and uncertainties. Therefore, a systematic intercomparison of impacts is suggested, which should be done for representative regions using state-of-the-art models. Our study is intended as a step in this direction. The impact assessment presented here was performed for three river basins on three continents: Rhine in Europe, Upper Niger in Africa and Upper Yellow in Asia. For that, climate scenarios from five GCMs and three hydrological models: HBV, SWIM and VIC, were used. Four "Representative Concentration Pathways" (RCPs) covering a range of emissions and land-use change projections were included. The objectives were to analyze and compare climate impacts on future trends considering three runoff quantiles: Q90, Q50 and Q10 and on seasonal water discharge, and to evaluate uncertainties from different sources. The results allow drawing some robust conclusions, but uncertainties are large and shared differently between sources in the studied basins. The robust results in terms of trend direction and slope and changes in seasonal dynamics could be found for the Rhine basin regardless which hydrological model or forcing GCM is used. For the Niger River scenarios from climate models are the largest uncertainty source, providing large discrepancies in precipitation, and therefore clear projections are difficult to do. For the Upper Yellow basin, both the hydrological models and climate models contribute to uncertainty in the impacts, though an increase in high flows in future is a robust outcome assured by all three hydrological models.

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