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 Using hydroclimatic extremes to guide future hydrologic predictions

2016 ◽  
Author(s):  
S. K. Oni ◽  
M. N. Futter ◽  
J. L. J. Ledesma ◽  
C. Teutschbein ◽  
J. Buttle ◽  
...  
Keyword(s):  
Model Calibration ◽  
Climate Models ◽  
Climate Change Impacts ◽  
Climate Impact ◽  
Hydrologic Model ◽  
Climatic Conditions ◽  
Forest Hydrology ◽  
Landscape Processes ◽  
Behavioural Parameter ◽  
Headwater Catchment

Abstract. There are growing numbers of studies on climate change impacts on forest hydrology but limited attempts have been made to use current hydroclimatic extremes to constrain future climatic conditions. Here we used historical wet and dry years as a proxy for expected future extremes in a boreal headwater catchment. Hydrologic model ling assessments showed that runoff could be underestimated by at least 35 % when dry year parameterization was used for wet year conditions. Uncertainty analysis showed that behavioural parameter sets from wet and dry year separated mainly on precipitation related parameters and to a lesser extent on parameter sets related to landscape processes. While inherent uncertainty in climate models still drives the overall uncertainty in runoff projections, hydrologic model calibration for climate impact studies should be based on years that best approximate future conditions to constrain uncertainty in projecting future conditions.

scholarly journals Using dry and wet year hydroclimatic extremes to guide future hydrologic projections

2016 ◽  
Vol 20 (7) ◽  
pp. 2811-2825 ◽  
Author(s):  
Stephen Oni ◽  
Martyn Futter ◽  
Jose Ledesma ◽  
Claudia Teutschbein ◽  
Jim Buttle ◽  
...  
Keyword(s):  
Model Calibration ◽  
Climate Models ◽  
Performance Metrics ◽  
Climate Change Impacts ◽  
Climate Impact ◽  
Hydrologic Model ◽  
Climatic Conditions ◽  
Extreme Conditions ◽  
Landscape Processes ◽  
Behavioural Parameter

Abstract. There are growing numbers of studies on climate change impacts on forest hydrology, but limited attempts have been made to use current hydroclimatic variabilities to constrain projections of future climatic conditions. Here we used historical wet and dry years as a proxy for expected future extreme conditions in a boreal catchment. We showed that runoff could be underestimated by at least 35 % when dry year parameterizations were used for wet year conditions. Uncertainty analysis showed that behavioural parameter sets from wet and dry years separated mainly on precipitation-related parameters and to a lesser extent on parameters related to landscape processes, while uncertainties inherent in climate models (as opposed to differences in calibration or performance metrics) appeared to drive the overall uncertainty in runoff projections under dry and wet hydroclimatic conditions. Hydrologic model calibration for climate impact studies could be based on years that closely approximate anticipated conditions to better constrain uncertainty in projecting extreme conditions in boreal and temperate regions.

scholarly journals Assessing biophysical and socio-economic impacts of climate change on regional avian biodiversity

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Simon Kapitza ◽  
Pham Van Ha ◽  
Tom Kompas ◽  
Nick Golding ◽  
Natasha C. R. Cadenhead ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Change Impacts ◽  
Integrated Modelling ◽  
Land Use Patterns ◽  
Economic Changes ◽  
Use Patterns ◽  
Modelling Framework ◽  
Avian Biodiversity ◽  
Biodiversity Change ◽  
Impacts Of Climate Change

AbstractClimate change threatens biodiversity directly by influencing biophysical variables that drive species’ geographic distributions and indirectly through socio-economic changes that influence land use patterns, driven by global consumption, production and climate. To date, no detailed analyses have been produced that assess the relative importance of, or interaction between, these direct and indirect climate change impacts on biodiversity at large scales. Here, we apply a new integrated modelling framework to quantify the relative influence of biophysical and socio-economically mediated impacts on avian species in Vietnam and Australia and we find that socio-economically mediated impacts on suitable ranges are largely outweighed by biophysical impacts. However, by translating economic futures and shocks into spatially explicit predictions of biodiversity change, we now have the power to analyse in a consistent way outcomes for nature and people of any change to policy, regulation, trading conditions or consumption trend at any scale from sub-national to global.

Global scale hydrological modelling at 100 m, 1 h resolution, in Python

2021 ◽  
Author(s):  
Kor de Jong ◽  
Marc van Kreveld ◽  
Debabrata Panja ◽  
Oliver Schmitz ◽  
Derek Karssenberg
Keyword(s):  
Large Scale ◽  
Model Building ◽  
Flow Direction ◽  
Building Blocks ◽  
Global Scale ◽  
Data Availability ◽  
Hydrological Models ◽  
Continental Scale ◽  
Modelling Framework ◽  
Scale Models

<p>Data availability at global scale is increasing exponentially. Although considerable challenges remain regarding the identification of model structure and parameters of continental scale hydrological models, we will soon reach the situation that global scale models could be defined at very high resolutions close to 100 m or less. One of the key challenges is how to make simulations of these ultra-high resolution models tractable ([1]).</p><p>Our research contributes by the development of a model building framework that is specifically designed to distribute calculations over multiple cluster nodes. This framework enables domain experts like hydrologists to develop their own large scale models, using a scripting language like Python, without the need to acquire the skills to develop low-level computer code for parallel and distributed computing.</p><p>We present the design and implementation of this software framework and illustrate its use with a prototype 100 m, 1 h continental scale hydrological model. Our modelling framework ensures that any model built with it is parallelized. This is made possible by providing the model builder with a set of building blocks of models, which are coded in such a manner that parallelization of calculations occurs within and across these building blocks, for any combination of building blocks. There is thus full flexibility on the side of the modeller, without losing performance.</p><p>This breakthrough is made possible by applying a novel approach to the implementation of the model building framework, called asynchronous many-tasks, provided by the HPX C++ software library ([3]). The code in the model building framework expresses spatial operations as large collections of interdependent tasks that can be executed efficiently on individual laptops as well as computer clusters ([2]). Our framework currently includes the most essential operations for building large scale hydrological models, including those for simulating transport of material through a flow direction network. By combining these operations, we rebuilt an existing 100 m, 1 h resolution model, thus far used for simulations of small catchments, requiring limited coding as we only had to replace the computational back end of the existing model. Runs at continental scale on a computer cluster show acceptable strong and weak scaling providing a strong indication that global simulations at this resolution will soon be possible, technically speaking.</p><p>Future work will focus on extending the set of modelling operations and adding scalable I/O, after which existing models that are currently limited in their ability to use the computational resources available to them can be ported to this new environment.</p><p>More information about our modelling framework is at https://lue.computationalgeography.org.</p><p><strong>References</strong></p><p>[1] M. Bierkens. Global hydrology 2015: State, trends, and directions. Water Resources Research, 51(7):4923–4947, 2015.<br>[2] K. de Jong, et al. An environmental modelling framework based on asynchronous many-tasks: scalability and usability. Submitted.<br>[3] H. Kaiser, et al. HPX - The C++ standard library for parallelism and concurrency. Journal of Open Source Software, 5(53):2352, 2020.</p>

scholarly journals Climate Change Impacts Assessment on Wine-Growing Bioclimatic Transition Areas

Agriculture ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 605
Author(s):  
Alba Piña-Rey ◽  
Estefanía González-Fernández ◽  
María Fernández-González ◽  
Mª. Nieves Lorenzo ◽  
Fco. Javier Rodríguez-Rajo
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Climate Change Impacts ◽  
Mediterranean Area ◽  
Cultural Practice ◽  
Climatic Conditions ◽  
Study Region ◽  
Bioclimatic Indices ◽  
Northwestern Spain ◽  
The Mediterranean

Viticultural climatic indices were assessed for the evaluation of the meteorological variations in the requirements of wine cultivars. The applied bioclimatic indices have been widely used to provide an initial evaluation of climate change impacts on grapevine and to delineate wine regions and suitable areas for planting around the world. The study was carried out over a period of 16 years (from 2000 to 2015) in five Designation of Origin areas in Northwestern Spain located in the Eurosiberian region, the transition zone between the Eurosiberian and the Mediterranean areas, and in the Mediterranean area. In addition, the high-resolution meteorological dataset “Spain02” was applied to the bioclimatic indices for the period 1950–2095. To further assess the performance of “Spain02”, Taylor diagrams were elaborated for the different bioclimatic indices. A significant trend to an increase of the Winkler, Huglin, Night Cold Index and GSS Indices was detected in the North-western Spain, whereas slight negative trends for BBLI and GSP Indices were observed. To analyze future projections 2061–2095, data from the high-resolution dynamically downscaled daily climate simulations from EURO-CORDEX project were used. To further assess the performance of Spain02, Taylor diagrams were elaborated for the different bioclimatic indices. A trend to an increase of the Winkler, Huglin, Night Cold Index and GSP Indices was detected in Northwestern Spain, whereas slight negative trends for BBLI and GSP Indices were observed. Our results showed that climatic conditions in the study region could variate for the crop in the future, more for Mediterranean than Eurosiberian bioclimatic area. Due to an advance in the phenological events or the vintage data, more alcohol-fortified wines and variations in the acidity level of wines could be expected in Northwestern Spain, these processes being most noticeable in the Mediterranean area. The projections for the BBLI and GSP Indices will induce a decrease in the pressure of the mildew attacks incidence in the areas located at the Eurosiberian region and the nearest transition zones. Projections showed if the trend of temperature increase continues, some cultural practice variations should be conducted in order to preserve the grape cultivation suitability in the studied area.

scholarly journals Climate change impacts model parameter sensitivity – What does this mean for calibration?

2020 ◽  
Author(s):  
Lieke Anna Melsen ◽  
Björn Guse
Keyword(s):  
Climate Change ◽  
Climate Change Impacts ◽  
The United States ◽  
Parameter Sensitivity ◽  
Model Parameters ◽  
Hydrological Models ◽  
The Future ◽  
Influence Parameter ◽  
Sensitivity Changes ◽  
Sensitive Parameters

Abstract. Hydrological models are useful tools to explore the hydrological impact of climate change. Many of these models require calibration. A frequently employed strategy is to calibrate the five parameters that were found to be most relevant as identified in a sensitivity analysis. However, parameter sensitivity varies over climate, and therefore climate change could influence parameter sensitivity. In this study we explore the change in parameter sensitivity within a plausible climate change rate, and investigate if changes in sensitivity propagate into the calibration strategy. We employed three frequently used hydrological models (SAC, VIC, and HBV), and explored parameter sensitivity changes across 605 catchments in the United States by comparing a GCM-forced historical and future period. Consistent among all models is that the sensitivity of snow parameters decreases in the future. Which parameters increase in sensitivity is less consistent among the models. In 43 % to 49 % of the catchments, dependent on the model, at least one parameter changes in the future in the top-5 most sensitive parameters. The maximum number of changes in the parameter top-5 is two, in 2–4 % of the investigated catchments. The value of the parameters that enter the top-5 cannot easily be identified based on historical data, because the model is not yet sensitive to these parameters. This requires an adapted calibration strategy for long-term projections, for which we provide several suggestions. The disagreement among the models on processes becoming relevant in future projections also calls for a strict evaluation of the adequacy of the model structure and the model parameters implemented therein.

scholarly journals HYRES: A Multi-Objective Optimization Tool for Proper Configuration of Renewable Hybrid Energy Systems

Energies ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 26 ◽  
Author(s):  
Katheryn Donado ◽  
Loraine Navarro ◽  
Christian G. Quintero M. ◽  
Mauricio Pardo
Keyword(s):  
Life Cycle Cost ◽  
Cost Benefit ◽  
Energy Systems ◽  
Energy System ◽  
Climatic Conditions ◽  
Hybrid Energy ◽  
Multi Objective ◽  
Viability Analysis ◽  
Hybrid Renewable Energy System ◽  
Cost Benefit Ratio

This paper presents the Hybrid Renewable Energy System (HYRES), a powerful tool to contribute to the viability analysis of energy systems involving renewable generators. HYRES considers various input parameters related to climatic conditions, statistical reliability, and economic views; in addition to offering multi-objective optimizations using Genetic Algorithms (GAs) that have a better cost-benefit ratio than mono-objective optimization, which is the technique used in several commercial systems like HOMER, a worldwide leader in microgrid modeling. The use of intelligent techniques in HYRES allows optimal sizing of hybrid renewable systems with wind and solar energy generators adapted to different conditions and case studies. The elements that affect the system design like buying and selling energy from/to the grid and the use of storage units can be included in system configuration according to the need. Optimization approaches are selectable and include Initial Cost, Life Cycle Cost, Loss of Power Probability, and Loss of Power Supply Probability.

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