INTRODUCTION<\/h2>\n
Climate change represents one of\u00a0the\u00a0most significant environmental challenges, fundamentally affecting the\u00a0availability and quality of\u00a0water resources\u00a0[1,\u00a02]. In\u00a0the\u00a0Czech Republic, climate change manifests itself mainly through an increase in\u00a0air temperatures, changes in\u00a0precipitation distribution, increased frequency and intensity of\u00a0drought and, conversely, short-term extreme precipitation events that can lead to floods\u00a0[3, 4]. These changes disrupt the\u00a0hydrological balance of\u00a0the\u00a0landscape, affect water balance, and contribute to the\u00a0reduced availability of\u00a0groundwater and surface water supplies, which are key for supplying the\u00a0population, agriculture\u00a0[5], and industry.<\/p>\n
In\u00a0some areas of\u00a0the\u00a0Czech Republic, which are already classified as deficient in\u00a0terms of\u00a0water regime, climate change impacts are deepening. The\u00a0lack of\u00a0water manifests itself both in\u00a0the\u00a0dry season, when river levels drop and the\u00a0availability of\u00a0water for various purposes decreases, and in\u00a0the\u00a0winter months, when reduced water reserves via snow cover contribute to low flows in\u00a0the\u00a0spring season. These issues are exacerbated by rising air temperatures, which increase evaporation and thus further reduce water availability in\u00a0the\u00a0landscape.<\/p>\n
The\u00a0HYMOD-KZ database is a tool that shows the\u00a0results of\u00a0hydrological modelling and water balance analysis for current and future climate conditions in\u00a0the\u00a0Czech Republic. This tool uses advanced hydrological modelling methods that include both spatial interpolation of\u00a0meteorological data and simulations of\u00a0water regime changes based on different climate scenarios. The\u00a0database provides spatially explicit information on water balance, which enables a\u00a0detailed assessment of\u00a0the\u00a0impacts of\u00a0climate change on individual basins and water bodies.<\/p>\n
Within\u00a0the\u00a0HYMOD-KZ database, so-called deficit areas are also identified, where the\u00a0climatological water balance is significantly negative, which indicates risks for sustainable management of\u00a0water resources. This information is key for planning water management measures, such as building new retention reservoirs, optimizing the\u00a0use of\u00a0water resources, or implementing adaptation strategies aimed at improving the\u00a0landscape\u2019s storage capacity. The\u00a0database is therefore a tool (base) for experts in\u00a0water management, who can use the\u00a0data to support decision-making and create long-term strategies to mitigate the\u00a0impacts of\u00a0climate change.<\/p>\n
METHODOLOGY AND DATA<\/h2>\nCurrent climate conditions<\/h3>\n
Climate data for 1961\u20132020 was used for the\u00a0actual assessment of\u00a0current conditions, namely a time series of\u00a0air temperatures and precipitation totals. Since long time series contain\u00a0measurement errors, inhomogeneities caused by moving the\u00a0station, changing instruments or observers, or measurement failures, it is necessary to clean the\u00a0data series from these influences. For this purpose, the\u00a0data underwent a quality control within\u00a0the\u00a0CLIDATA database at CHMI. All data were tested for inhomogeneities in\u00a0the\u00a0series and these were corrected using the\u00a0proprietary DAP method. Any missing data from 1961\u20132020 were added based on interpolation methods. Station data processed in\u00a0this way were subsequently interpolated into a grid network with a spatial resolution of\u00a0500\u00a0m. For each day, the\u00a0dependence on terrain\u00a0parameters (altitude, slope, roughness) was determined as well as on latitude and longitude. The\u00a0basis for spatial interpolation is a terrain\u00a0map with a resolution of\u00a0500\u00a0\u00d7\u00a0500\u00a0m. The\u00a0result of\u00a0spatial interpolation are layers (GeoTIFF) of\u00a0meteorological variables in\u00a0a\u00a0daily time step, which were used to derive time series for the\u00a0studied area (to the\u00a0centre of\u00a0individual surface water bodies). The\u00a0period 1991\u20132020, which corresponds to the\u00a0current reference period, was used for the\u00a0assessment itself.<\/p>\n
Climate change scenarios in\u00a0water management<\/h3>\n
Climate models are mathematical representations of\u00a0the\u00a0physical processes that take place in\u00a0the\u00a0atmosphere, oceans, ice sheets, and land. They are used to simulate past, present, and future climate on Earth. Global climate models (GCMs) work with a coarse spatial resolution, which means that smaller geographical areas, such as the\u00a0Czech Republic, are not accurately represented in\u00a0these models. Therefore, regional climate models (RCMs) are used at the\u00a0regional level, spatially refining the\u00a0GCM outputs. Both GCM and RCM have their advantages and disadvantages\u00a0[6].<\/p>\n
The most recent CMIP6 GCM [7, 8] simulations include models with different spatial resolutions, mostly around 100 or 250 km. However, some models with a resolution of 50 km end the simulations in the mid-21st century. The models differ in complexity of the climate system description and parameterization\u00a0of\u00a0smaller scales, which leads to differences between simulated climate and reality. For Central Europe, GCMs that best simulate its climate were selected, ensuring that this selection was representative of\u00a0the\u00a0entire original set of\u00a0models. Six models with a resolution of\u00a0up to 100 km were selected that cover all emission scenarios and take into account basic meteorological elements.<\/p>\n
Climate change scenarios (Shared Socioeconomic Pathways: SSP\u00a0[9]) reflect different possible future global trajectories in\u00a0terms of\u00a0emissions and socio-economic development:<\/p>\n
- \n
- SSP1\u20132.6: sustainable development<\/li>\n
- SSP2\u20134.5: middle path with deterioration of\u00a0environmental systems<\/li>\n
- SSP3\u20137.0: regional rivalry and limited economic development<\/li>\n
- SSP5\u20138.5: development based on fossil fuels<\/li>\n<\/ul>\n
The\u00a0selection of\u00a0GCM models was carried out according to the\u00a0methodology\u00a0[10] and ensures reliable climate simulations of\u00a0Central Europe. Furthermore, the\u00a0ALADIN-CLIMATE\/CZ regional model, which is characterized by high spatial resolution, was included. The\u00a0ALADIN-CLIMATE\/CZ model calculation area includes almost all of\u00a0Europe with the\u00a0Czech Republic in\u00a0its centre, which is important for the\u00a0actual modelling of\u00a0the\u00a0future climate; however, it is no longer needed for further processing of\u00a0the\u00a0results, so it was reduced\u00a0[11]. The\u00a0resulting set of\u00a0used simulations is shown in\u00a0Tab.\u00a01<\/em>.<\/p>\n
Tab. 1. Selected GCM models from CMIP6 and ALADIN-CLIMATE\/CZ simulations, their spatial resolution, and available SSP scenarios<\/h5>\n
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<\/a>\n<\/p>\n
For the\u00a0creation of\u00a0SSP scenarios in\u00a0the\u00a0context of\u00a0estimating changes in\u00a0the\u00a0hydrological balance, the\u00a0so-called incremental method is used as standard in\u00a0the\u00a0Czech Republic, especially for studies in\u00a0monthly step. This method consists in\u00a0transforming the\u00a0observed data so that changes in\u00a0transformed quantities correspond to changes derived from climate model simulations. In\u00a0the\u00a0monthly step, changes in\u00a0average monthly precipitation totals and average monthly temperature are normally considered. In\u00a0the\u00a0daily step, it is also necessary to consider changes in\u00a0the\u00a0variability of\u00a0quantities. Therefore, the\u00a0Advanced Delta Change (ADC) incremental method was used to create SSP scenarios. The\u00a0incremental method is based on transforming the\u00a0observed data in\u00a0a way that guarantees that the\u00a0changes between the\u00a0transformed and the\u00a0original series are the\u00a0same as the\u00a0changes derived from the\u00a0regional climate model. For precipitation and temperature (especially in\u00a0the\u00a0daily step) it is desirable that the\u00a0considered transformations take into account changes in\u00a0both average and variability. This simply means that the\u00a0extremes can change in\u00a0a different way than the\u00a0average. When deriving precipitation changes from the\u00a0climate model, the\u00a0ADC method also considers systematic simulation errors. Since the\u00a0temperature is transformed linearly, systematic error has no effect on the\u00a0resulting temperature transformation\u00a0[12]. For individual water bodies, selected\u00a0[13] Global Circulation Models (GCM) and ALADIN-CLIMATE\/CZ Regional Circulation Model were transformed by the\u00a0selected method.<\/p>\n
Hydrological balance modelling<\/h3>\n
To calculate hydrological balance, the\u00a0BILAN conceptual model was used, which has been developed for more than 20 years in\u00a0TGM WRI Department of\u00a0Hydrology. The\u00a0model calculates the\u00a0chronological hydrological balance of\u00a0the\u00a0basin\u00a0or area in\u00a0daily and monthly time steps. It expresses the\u00a0basic balance relationships on the\u00a0surface of\u00a0the\u00a0catchment area, in\u00a0the\u00a0aerated zone (which also includes the\u00a0basin\u00a0vegetation cover), and in\u00a0the\u00a0groundwater zone. Air temperature is used as an indicator of\u00a0energy balance, which significantly affects hydrological balance. Using the\u00a0calculation, the\u00a0potential evapotranspiration, land evaporation, infiltration into the\u00a0aerated zone, seepage through this zone, water supply in\u00a0snow, water supply in\u00a0soil, and groundwater supply is modelled. Runoff is modelled as the\u00a0sum of\u00a0three components: two components of\u00a0direct runoff (including subsurface runoff) and base runoff\u00a0[15\u201318]. The\u00a0daily version of\u00a0the\u00a0model, which is controlled by six parameters, was used to model the\u00a0hydrological balance. The\u00a0model uses linear and non-linear reservoirs to transform precipitation into runoff. The\u00a0main\u00a0inputs of\u00a0the\u00a0model are precipitation and air temperature (also measured runoff for calibration), the\u00a0output is the\u00a0modelled runoff from the\u00a0basin\u00a0and other hydrological balance components.<\/p>\n
The\u00a0calibrated BILAN hydrological model within\u00a0the\u00a0HAMR system\u00a0[19] was used for the\u00a0actual simulations.<\/p>\n
Hydrological modelling of\u00a0climate change<\/h3>\n
The\u00a0procedure for modelling the\u00a0climate change impact on the\u00a0hydrological regime can be briefly summarized as follows:<\/p>\n
- \n
- The\u00a0selected hydrological model is calibrated for the\u00a0selected catchment area using observed data. A hydrological model should be based on physics to guarantee that it will provide acceptable results even for unobserved conditions.
\n
\n<\/li>\n - The\u00a0input variables from the\u00a0global or regional climate model are converted to time series of\u00a0scenarios for individual basins, in\u00a0this case by subsequent processing of\u00a0the\u00a0climate model output, i.e. using the\u00a0incremental method or\u00a0correction of\u00a0systematic errors. It is often necessary to use spatial interpolation to relate the\u00a0data from the\u00a0calculation cells of\u00a0the\u00a0climate model to the\u00a0centre of\u00a0the\u00a0given basin. For the\u00a0correct use of\u00a0the\u00a0methods, it is necessary to have the\u00a0observed data available.
\n
\n<\/li>\n - Using a calibrated hydrological model and time series of\u00a0scenarios, hydrological balance for the\u00a0corresponding period is simulated.<\/li>\n<\/ol>\n
The\u00a0procedures are described in\u00a0more detail in\u00a0[15\u201319].<\/p>\n
Deficit areas<\/h3>\n
Within the database, deficit areas of landscape water regime are displayed from a climatological point of view, without the water management aspect. Based on the analyses of the input variables, a simple interpretation of deficit\u00a0areas was chosen based on the\u00a0so-called climatological water balance, which is expressed by the\u00a0following equation<\/p>\n
<\/a>\nwhere:<\/p>\n
B\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 is\u00a0\u00a0\u00a0\u00a0 climatological water balance<\/p>\n
P\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 precipitation total<\/p>\n
PET\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 potential evapotranspiration<\/p>\n
The balance was calculated for current and future conditions based on the aforementioned simulations, aggregated and divided into categories:<\/p>\n
\n- \n
- Problem-free area: B > 0 mm
\n
\n<\/li>\n - Risk area: 0 mm > B > -100 mm
\n
\n<\/li>\n - Threatened area: -100 mm > B > -200 mm
\n
\n<\/li>\n - Critical area: B < -200 mm.<\/li>\n<\/ol>\n
HYMOD-KZ database: Specialized public database<\/h3>\n
Based on the\u00a0outputs (dealing with modelling climate change impacts on water regime) of\u00a0TA CR projects (\u201cWater Centre\u201d<\/span> and \u201cPERUN\u201d<\/span>), the\u00a0HYMOD-KZ database was created; it is available at https:\/\/shiny.vuv.cz\/HYMOD- KZ\/. The\u00a0database runs on the\u00a0equipment of\u00a0TGM WRI in\u00a0Prague. The\u00a0aim of\u00a0the\u00a0database is to provide users with comprehensive information on water availability (natural water regime) for current and future conditions with an emphasis on individual climate model simulations.<\/span><\/p>\n
Technical specification<\/h3>\n
The\u00a0HYMOD-KZ database was created in\u00a0the\u00a0R programming language (version\u00a04.3.1). The\u00a0application\u2019s interactive web interface is provided through an\u00a0open-source superstructure in\u00a0the\u00a0form of\u00a0Shiny packages (version 1.7.5.1) and flexdashboard (version 0.6.2), where Shiny provides the\u00a0functionality of\u00a0the\u00a0user interface (i.e. contains all functions and calculations as well as instructions necessary for layout and appearance), while flexdashboard allows linking all Shiny components in\u00a0the\u00a0form of\u00a0a single RMarkdown document. Furthermore, the\u00a0application uses tools in\u00a0the\u00a0form of\u00a0packages, such as tidyr (version 1.3.0) and dplyr (version 1.1.2), used for editing and transforming data, sf (version 1.0\u201313)
\nenabling work with the\u00a0OpenGIS geographic data standard, Simple Features, and Leaflet (version 2.2.0), enabling the\u00a0display of\u00a0spatial data in\u00a0the\u00a0form of\u00a0interactive maps.<\/span><\/p>\nHome page<\/h3>\n
The\u00a0main\u00a0menu for the\u00a0database is via the\u00a0opening page (Fig.\u00a01<\/span><\/em>), which shows:<\/span><\/p>\n
\n- \n
- Logo and project name, and database logo.
\n
\n<\/li>\n - Public Database Section: Contains links to sections such as \u201cHydrological Balance\u201d and \u201cDeficit areas\u201d that provide users with access to relevant information and data.
\n
\n<\/li>\n - Contact information: On the\u00a0right, the\u00a0contact information for the\u00a0researchers, including their institutions and locations, is listed.
\n
\n<\/li>\n - Project summary.<\/li>\n<\/ol>\n<\/a>\n
Fig. 1. Main menu of the HYMOD-KZ database home page<\/h6>\n
Hydrological balance<\/h3>\n
The\u00a0\u201cHydrological balance\u201d component displays a summary of\u00a0basic hydro-climatological parameters for individual water bodies. Fig.\u00a02<\/span> shows the\u00a0user interface with different selection options. The\u00a0user can select different variables:<\/span><\/p>\n
- \n
- BF \u2013 basic runoff\u00a0[mm],<\/li>\n
- ET \u2013 current evapotranspiration\u00a0[mm],<\/li>\n
- INF \u2013 infiltration\u00a0[mm],<\/li>\n
- P \u2013 precipitation total\u00a0[mm],<\/li>\n
- PET \u2013 potential evapotranspiration\u00a0[mm],<\/li>\n
- RM \u2013 modelled runoff\u00a0[mm],<\/li>\n
- SS \u2013 water supply in\u00a0snow\u00a0[mm],<\/li>\n
- SW \u2013 water supply in\u00a0soil\u00a0[mm],<\/li>\n
- T \u2013 air temperature\u00a0[o<\/span><\/sup>C].<\/li>\n<\/ul>\n<\/a>\n
Fig. 2. HYMOD-KZ database main menu: options for selecting variables and time period in\u00a0the \u201cHydrological balance\u201d component<\/h6>\n
<\/a>\nFig. 3. Development of the selected variable in a\u00a0specific water body based on\u00a0individual SSP scenarios and the ALADIN-CLIMATE\/CZ model<\/h6>\n
The\u00a0values are aggregated into monthly (\u201cMonthly\u201d tab) and annual values (\u201cTotal\u201d tab) and further derived basic static quantities such as the\u00a0average (\u201cValue\u201d) or partial quantiles (10%, 25%, 75%, and 95% ). Within\u00a0the\u00a0application, it is also possible to choose between different periods (2030, 2050, 2070, 2085) and different socioeconomic pathways (SSP126, SSP245, SSP370, SSP585), indicating possible future development scenarios.<\/p>\n
Ater this choice, climate models such as MEAN (average of\u00a0all models), CMCC-ESM2, EC-EARTH3, GFDL-ESM4, MPI-ESM1-2-HR, MRI-ESM2-0, TAIESM1, and ALADIN (ALADIN- CLIMATE\/CZ) are listed, which represent different climate models used for simulations. It is also possible to display values for the\u00a0present 1991\u20132020, \u201cHistory\u201d, scenario values (\u201cScenario\u201d) for the\u00a02030, 2050, 2070, and 2085, and absolute differences between the\u00a0future and the\u00a0present for the\u00a0selected quantity.<\/p>\n
The\u00a0graph (Fig.\u00a03<\/em>) shows development of\u00a0the\u00a0selected variable, quantile, and water body according to individual SSP scenarios and simulations by the\u00a0ALADIN-CLIMATE\/CZ model for individual time horizons.<\/p>\n
Fig.\u00a04<\/em> shows overall output composition, which consists of\u00a0a map window and graphs based on the\u00a0selected combination (in\u00a0this case, absolute values \u200b\u200bof\u00a0precipitation total for the\u00a0variant: outlook to 2050, SSP126, and MEAN \u2013 arithmetic mean of\u00a0all simulations).<\/p>\n
<\/a>\nFig. 4. Precipitation total for scenarios: outlook to 2050, SSP126, and MEAN (arithmetic mean of all simulations)<\/h6>\n
<\/a>\nFig. 5. Evaluated deficit areas<\/h6>\n
Deficit areas<\/h3>\n
At the\u00a0beginning of\u00a0the\u00a0\u201cWater Centre<\/em>\u201d<\/span> project (2020), so-called deficit areas of\u00a0the\u00a0Czech Republic were defined, which were determined by expert assessment based on previous studies dealing with the\u00a0impact of\u00a0climate change on water regime and the\u00a0definition of\u00a0problematic hydrogeological regions. As part of\u00a0the\u00a0\u201cWater Centre<\/em>\u201d<\/span> project, these areas were specified based on the\u00a0use of\u00a0hydrological balance modelling in\u00a0the\u00a0distinction of\u00a0water bodies and the\u00a0updating of\u00a0outputs from climate models. Adaptation measures should be proposed for deficit areas and their impact on the\u00a0water regime of\u00a0the\u00a0given location should be evaluated.<\/span><\/p>\n
Based on the\u00a0aforementioned methodology for calculating deficit areas, the\u00a0\u201cDeficit areas\u201d component shows a map of\u00a0the\u00a0Czech Republic (Fig.\u00a05<\/span><\/em>) with the\u00a0delineation of\u00a0updated areas. In\u00a0the\u00a0course of\u00a0the\u00a0project (by the\u00a0end of\u00a02024), the\u00a0map should be supplemented with a layer that will also provide information on deficit areas from a water management point of\u00a0view. To finalize the\u00a0map, the\u00a0materials showing the\u00a0individual future simulations were also used.<\/span><\/p>\n
Fig.\u00a06<\/span><\/span> shows mean absolute changes in\u00a0precipitation totals for the\u00a0summary of\u00a0simulations according to SSP scenarios and for partial time steps. Absolute mean changes in\u00a0runoff heights are shown analogously in\u00a0Fig.\u00a07<\/span><\/em>. An increase in\u00a0precipitation totals can be observed in\u00a0most simulations which, however, often cannot compensate for the\u00a0increase in\u00a0evapotranspiration primarily caused by increased air temperature. This has an impact on runoff levels.<\/span><\/p>\n
<\/a>\nFig. 6. Absolute changes in precipitation based on individual climate model simulations<\/h6>\n
<\/a>\nFig. 7. Absolute changes in runoff based on individual climate model simulations<\/h6>\n
- Logo and project name, and database logo.
- Problem-free area: B > 0 mm
- The\u00a0selected hydrological model is calibrated for the\u00a0selected catchment area using observed data. A hydrological model should be based on physics to guarantee that it will provide acceptable results even for unobserved conditions.
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<\/a>Fig. 8. Evaluation of deficit areas based on individual climate model simulations (grey polygons indicate the non-updated layer of deficit areas)<\/h6>\n