INTRODUCTION<\/h2>\n
Water is an essential resource for life on Earth and at the\u00a0same time plays a\u00a0key role in\u00a0all areas of\u00a0human activity, from agriculture to industry, electricity and heat production to household operations. With climate change and changing water demands from different sectors, the\u00a0issue of\u00a0future water demand is becoming increasingly urgent. The\u00a0issue of\u00a0the\u00a0future availability of\u00a0water resources is a\u00a0complex topic that includes a\u00a0number of\u00a0key aspects, such as changes in\u00a0the\u00a0distribution of\u00a0precipitation in\u00a0time and space (some areas may experience periods of\u00a0drought, others periods of\u00a0torrential rain), increase in\u00a0temperature, increase in\u00a0water evaporation from vegetation and water bodies, economic development and industrialization requiring more water for industry and energy industry, increasing population living standards and the\u00a0associated higher water consumption in\u00a0households, and the\u00a0growing demand for water in\u00a0agriculture to ensure food security. The\u00a0basic prerequisite for solving the\u00a0aforementioned issue is to obtain\u00a0information about the\u00a0future demand for water in\u00a0various sectors and its distribution across the\u00a0Czech Republic, with a\u00a0subsequent comparison with future available sources. The\u00a0result should then be a\u00a0more efficient use of\u00a0water in\u00a0agriculture, industry, energy industry and households, associated with the\u00a0development of\u00a0technologies for water treatment and recycling, building water infrastructure for water retention and transport, and also with the\u00a0improvement of\u00a0forecasting systems for water management. It is a\u00a0key integrated approach that considers all the\u00a0aspects mentioned above and seeks levelled off solutions to ensure sustainable management of\u00a0water resources in\u00a0the\u00a0future. As\u00a0this is a\u00a0relatively extensive issue, it was dealt with by a\u00a0wider team of\u00a0experts of\u00a0various specializations divided into several teams focused on a\u00a0certain\u00a0area of\u00a0water demand estimation. Based on available data and forecasts, the\u00a0development of\u00a0water demand in\u00a0the\u00a0coming decades will be predicted. Based on these findings, the\u00a0follow-up activities of\u00a0other work packages within\u00a0the\u00a0\u201cWater Centre<\/span>\u201d will determine what strategies can be implemented to ensure sustainable and equal distribution of\u00a0this valuable resource.<\/span><\/p>\n The\u00a0goal of\u00a0the\u00a0researchers from UCT was to analyse the\u00a0current demand for water in\u00a0industry in\u00a0the\u00a0Czech Republic and to obtain\u00a0data for the\u00a0quantification of\u00a0future demand. The\u00a0input was data on registered surface and groundwater abstractions and wastewater discharges for 2009\u20132019, based on Decree\u00a0no.\u00a0431\/2001 Coll., managed by the\u00a0State River Basin\u00a0Authorities. These are data on direct abstractions and discharges reported by individual entities; therefore, they do not include information on the\u00a0use of\u00a0water from public water supply systems and the\u00a0discharge of\u00a0water into public sewers.<\/span><\/p>\n \u00a0<\/span>The\u00a0data was divided into three groups:<\/span><\/p>\n The\u00a0aggregated data was processed in\u00a0both tabular and graphical form, so that it was possible to determine the\u00a0most important sectors for individual territorial units and to monitor possible trends in\u00a0the\u00a0demand and consumption of\u00a0water. The\u00a0initial analysis was carried out at the\u00a0level of\u00a0the\u00a0Czech Republic and its regions, then it was extended to districts. In\u00a0addition to annual abstraction (or discharge), data on seasonal fluctuations were also processed, i.e. abstractions in\u00a0individual months.<\/span><\/p>\n It was found that in\u00a0the\u00a0case of\u00a0surface water, the\u00a0chemical industry is the\u00a0largest user in\u00a0the\u00a0Czech Republic, followed by paper production, metal processing, and mining. Groundwater abstraction is generally associated primarily with mining and food industry; other sectors show significantly lower values. There are also big between regions; at the\u00a0regional level, the\u00a0largest industrial surface water abstraction was recorded in\u00a0the\u00a0\u00dast\u00ed Region, mostly involving chemical and paper industries. Regarding groundwater, the\u00a0Moravian-Silesian and Central Bohemian Regions show the\u00a0highest values, with the\u00a0majority in\u00a0the\u00a0Moravian-Silesian Region associated with mining.<\/span><\/p>\n Although it is a\u00a0generally accepted fact that industrial demand for water in\u00a0the\u00a0Czech Republic has been decreasing for a\u00a0long time, this rule cannot be applied as universally valid under all conditions. Data analysis shows that there are differences both between industries as a\u00a0whole and between individual regions. However, despite these differences, it can be stated that the\u00a0prevailing trend toward the\u00a0end of\u00a0the\u00a0analysed period 2009-2019 was balancing the\u00a0volumes of\u00a0water abstracted, without extreme fluctuations.<\/span><\/p>\n At the\u00a0district level, the\u00a0resulting progress of\u00a0abstraction and discharges is in\u00a0many cases much more fluctuating, often without clear trends. This is partly due to the\u00a0fact that the\u00a0sources of\u00a0discrepancies found in\u00a0regional analysis are more pronounced in\u00a0smaller territorial units, and partly due to the\u00a0fact that at the\u00a0district level the\u00a0number of\u00a0entities of\u00a0one industry is limited. Sometimes an industry is represented by a\u00a0single enterprise whose operation defines the\u00a0entire progress of\u00a0time. It is in\u00a0such cases (i.e., there is only one important water management entity in\u00a0an area) that it is possible to observe the\u00a0convergence of\u00a0trends at the\u00a0regional and district level. A\u00a0typical example is the\u00a0\u00dast\u00ed Region and the\u00a0Litom\u011b\u0159ice District, where the\u00a0values of\u00a0abstraction and discharge of\u00a0paper industry are basically determined by a\u00a0single company, Mondi \u0160t\u011bt\u00ed, a. s.<\/span><\/p>\n As part of\u00a0the\u00a0research, the\u00a0seasonality of\u00a0abstraction was also determined. The\u00a0analysis confirmed that there are differences not only between sectors, but also within\u00a0individual sectors. Some sectors show more or less levelled off consumption throughout the\u00a0year; for others a\u00a0decrease in\u00a0the\u00a0summer is characteristic, indicating regular summer shutdowns, or other reasons for the\u00a0abstraction regime reducing abstractions in\u00a0the\u00a0summer period. In\u00a0contrast, there are companies showing abstraction peaks in\u00a0July and August. An important finding is the\u00a0fact that recorded monthly deviations can vary significantly from year to year for a\u00a0given entity.<\/span><\/p>\n Industry in\u00a0the\u00a0Czech Republic is still diverse, export-oriented, and not subject to central planning. It is therefore influenced by a\u00a0number of\u00a0factors (economic, social, political; not only at the\u00a0local but also international level), which are difficult or even impossible to predict with sufficient accuracy. More detailed outlooks for individual sectors as a\u00a0whole are not available, and obtaining information about specific entities is complicated.<\/p>\n With regard to the\u00a0above-mentioned facts, a\u00a0simplified approach was chosen based on a\u00a0combination of\u00a0monitoring current trends in\u00a0water abstraction and discharge, with an effort to obtain\u00a0at least a\u00a0general idea of\u00a0the\u00a0development of\u00a0individual industries until 2050.<\/p>\n The\u00a0results of\u00a0data analyses can be summarized in\u00a0a\u00a0relatively simple statement: as the\u00a0size of\u00a0the\u00a0analysed territorial units decreased, the\u00a0volatility of\u00a0the\u00a0data series increased and clear long-term trends disappeared. In\u00a0contrast, possible seasonal fluctuations became more apparent.<\/p>\n Based on the\u00a0results achieved, it was decided that the\u00a0issue of\u00a0future water demand in\u00a0industry will not be dealt with by predicting changes over time, but by setting three fixed levels which will enable the\u00a0comparison of\u00a0realistically available water resources at a\u00a0given time. The\u00a0starting point for their determination was the\u00a0abstraction analysis at the\u00a0regional level. This approach can be used not only for annual, but also for monthly values, to capture fluctuations in\u00a0abstraction during the\u00a0year.<\/p>\n Baseline values are based on the\u00a0assumption that industrial demand for water in\u00a0the\u00a0future will be similar to the\u00a0present, or by the\u00a0end of\u00a0the\u00a0evaluated period 2009\u20132019. The\u00a0value for each sector will be calculated as an average of\u00a0four years, which were selected based on data evaluation at the\u00a0regional level. In\u00a0most cases, it concerns years 2016\u20132019, when Czech industry was in\u00a0good shape and the\u00a0most common trend in\u00a0water abstraction was a\u00a0more or less steady state. For industries or regions where there were significant fluctuations in\u00a0these years, development of\u00a0water demand was analysed in\u00a0more detail and other years were selected for calculation (Fig.\u00a01<\/em>).<\/p>\n The\u00a0largest volume of\u00a0abstracted water recorded in\u00a02009\u20132019 will be used as the\u00a0maximum value of\u00a0future abstractions. This provides a\u00a0realistic estimate of\u00a0possible positive deviations from the\u00a0baseline (Fig.\u00a01<\/em>).<\/p>\n The data contains information not only on abstraction and discharge, but also on maximum permitted volumes. In the analysed period 2009\u20132019, the limits for groundwater and surface water abstractions were not fully used, and therefore provide a reserve that is at least theoretically available to the relevant businesses. It is a realistic assumption that the limits for specific entities will not be\u00a0increased in\u00a0the\u00a0future, and thus determine a\u00a0critical limit for the\u00a0use of\u00a0water resources, which can be compared with the\u00a0expected future demand (Fig.\u00a01<\/em>).<\/p>\n The\u00a0above-mentioned approach naturally brings with it certain\u00a0risks and uncertainties:<\/p>\n The\u00a0aim of\u00a0the\u00a0CTU working group was to try to outline the\u00a0development of\u00a0irrigation in\u00a0the\u00a0Czech Republic by 2050 and to hypothesize what technology will be used and whether the\u00a0irrigable area will increase or decrease; subsequently, in\u00a0cooperation with project partners, determine how many water resources for irrigation and other sectors of\u00a0human activity would need to be secured in\u00a0this time horizon in\u00a0individual regions.<\/span><\/p>\n An analysis of\u00a0the\u00a0available documents describing the\u00a0current state was used\u00a0[1\u20134]. It mainly concerned information on the\u00a0structure of\u00a0crop production and on the\u00a0technical parameters of\u00a0irrigation \u2013 i.e. where it is technically possible to irrigate crops with regard to the\u00a0availability of\u00a0resources and infrastructure (irrigable areas). The\u00a0irrigation detail enabling efficient irrigation was also dealt with (minimization of\u00a0water loss and accurate dosing of\u00a0irrigation water). For its current use for crop irrigation, the\u00a0values of\u00a0the\u00a0loss coefficients K1 <\/span>and K2<\/span> were specified; see Tab.\u00a02<\/span> (CzechGlobe). For the\u00a0prediction of\u00a0water requirements, the\u00a0long-term trend of\u00a0the\u00a0development of\u00a0climatic parameters determining the\u00a0demand for additional irrigation for individual crops in\u00a0the\u00a0event of\u00a0changes in\u00a0agroclimatic areas is also considered (Czech Statistical Office\u00a0\u2013 CZSO and the\u00a0Crop Research Institute \u2013 CRI).<\/span><\/p>\n Current data on irrigation (irrigated areas) was taken from the\u00a0ISMS database (SOWAC-GIS geoportal map project). Data from the\u00a0Land Parcel Identification System<\/span> (LPIS) were used for crop occurrence\u00a0[5, 6].<\/span><\/p>\n An analysis of\u00a0the\u00a0irrigation abstraction database (TGM WRI) was carried out for individual catchments, and the\u00a0ambiguities found were discussed with representatives of\u00a0the\u00a0State River Basin\u00a0Authorities\u00a0[7]. The\u00a0database provided the\u00a0amount of\u00a0surface and groundwater currently abstracted for irrigation for 2014\u20132021; the\u00a0data was subsequently processed for individual sub-basins and surface water bodies\u00a0[8].<\/span><\/p>\n By determining the\u00a0demand for water for individual crops (data from CZU)\u00a0[9], an estimate was subsequently created of\u00a0total demand for irrigation water for individual surface water bodies and quantification of\u00a0the\u00a0necessary water sources for irrigation. When predicting future water abstraction for irrigation, updated water losses forced by irrigation technology are already considered\u00a0[10], and all calculations and estimates were made for predicted climatic conditions.<\/span><\/p>\n For selected relevant data from the\u00a0TGM WRI database, the\u00a0annual volume of\u00a0water abstracted for irrigation in\u00a02014\u20132021 was in\u00a0the\u00a0range of\u00a018\u201331\u00a0million\u00a0m3<\/span><\/sup>, which accounted for roughly 1.4\u00a0% of\u00a0total annual water consumption in\u00a0the\u00a0Czech Republic. The\u00a0biggest amount of\u00a0irrigation water was abstracted in\u00a02018; the\u00a0amount has been gradually decreasing since. Water was abstracted mainly from surface water, with less than 10\u00a0% reported from groundwater. The\u00a0largest amount of\u00a0irrigation water for the\u00a0analysed period (45\u00a0% of\u00a0the\u00a0total average amount) was abstracted in\u00a0the\u00a0Dyje catchment. The\u00a0rate of\u00a0use of\u00a0the\u00a0monthly amount of\u00a0water legally abstracted (in\u00a0the\u00a0months of\u00a0the\u00a0general growing season) was recorded partly inaccurately; for example, collectively for the\u00a0growing season, by wrong reading of\u00a0the\u00a0water meter, or ambiguously in\u00a0the\u00a0case of\u00a0groundwater abstraction. In\u00a0some cases, the\u00a0permitted values were exceeded (around 30\u00a0%).<\/span><\/p>\n The\u00a0provided soil water balances of\u00a0individual crops (CZU) were evaluated; consequently, the\u00a0water demand for individual surface water bodies was recalculated for the\u00a0selected crops and the\u00a0considered periods.<\/span><\/p>\n As part of\u00a0determining scenarios for irrigation water abstraction, combinations of\u00a0irrigation water demand for \u201chop fields\u201d, \u201cvineyards\u201d, \u201corchards\u201d, \u201carable land\u201d, and \u201cpermanent grassland\u201d were created for each surface water body for irrigated and non-irrigated areas in\u00a0the\u00a0\u201caverage growing season GS\u201d, in\u00a0\u201cDry season \u2013 sensitive growing season SGS\u201d and as \u201chorizon 2050 prediction for growing season GS\u201d\u00a0[11\u201315]. All results are part of\u00a0the\u00a0overall CTU report in\u00a0tabular digital form and an example of\u00a0the\u00a0graphical display of\u00a0irrigation water demand for individual surface water bodies in\u00a0the\u00a0\u201cforecast GS\u201d variant; see Fig.\u00a01<\/span>.<\/span><\/p>\n <\/p>\n Considering the\u00a0ambiguities of\u00a0the\u00a0recorded values of\u00a0irrigation abstraction, the\u00a0rates of\u00a0use of\u00a0the\u00a0monthly amount of\u00a0water legally abstracted were discussed with the\u00a0employees of\u00a0the\u00a0State River Basin\u00a0Authorities. Calculations of\u00a0irrigation water demand are made on the\u00a0basis of\u00a0current knowledge and currently available data. Clearly, even these results are burdened with uncertainties; for example, there is a\u00a0lack of\u00a0updating of\u00a0the\u00a0database of\u00a0actually irrigated areas and their connection to abstraction points. When calculating the\u00a0amount of\u00a0water for irrigation, uncertainties arose due to the\u00a0inconsistency of\u00a0the\u00a0defined LPIS categories (\u201chop fields\u201d, \u201cvineyards\u201d, \u201corchards\u201d, \u201carable land\u201d, and \u201cpermanent grassland\u201d) with the\u00a0provided soil water balances of\u00a0individual specific agricultural crops (see CzechGlobe). Uncertainties also exist in\u00a0the\u00a0socio-economic area because the\u00a0structure of\u00a0crops, as well as the\u00a0decisions of\u00a0economic entities to support the\u00a0construction and subsequent use of\u00a0irrigation, are significantly influenced by the\u00a0economy, subsidy titles, and the\u00a0common European market. In\u00a0comparison to the\u00a0previous ones, the\u00a0uncertainties in\u00a0the\u00a0area of\u00a0regional climatic development are also lower (although not negligible).<\/span><\/p>\n The\u00a0analysis of\u00a0the\u00a0irrigation abstraction database determined the\u00a0used amounts of\u00a0water in\u00a0individual river basins, searched for and named ambiguities in\u00a0the\u00a0entries of\u00a0values.<\/span><\/p>\n Analysis of\u00a0irrigation technologies in\u00a0the\u00a0Czech Republic and estimation of\u00a0their irrigation water losses enabled calculation of\u00a0the\u00a0approximate maximum amount of\u00a0water needed for the\u00a0irrigation of\u00a0typical cultures \u201cvineyard\u201d, \u201chop fields\u201d and \u201corchards\u201d, including a\u00a0possible extrapolation to the\u00a0scenario of\u00a0covering the\u00a0entire area of\u00a0these cultures with irrigation. The\u00a0indicative amount of\u00a0water needed to irrigate \u201carable land\u201d and \u201cpermanent grassland\u201d was calculated; it is clear that irrigation on arable land will be decisively concentrated on vegetables and early potatoes, and on permanent grassland on meadows for the\u00a0production of\u00a0fodder for dairy cattle. Development towards full irrigation is not realistic here \u2013 it was only applied where irrigation is already in\u00a0place (which was considered an indicator of\u00a0the\u00a0fact that irrigated crops are grown there). This fact was verified according to CZSO data \u2013 which, however, are only available at the\u00a0district level until 2014.<\/span><\/p>\n Without being able to make a\u00a0realistic balance of\u00a0the\u00a0availability of\u00a0water resources for individual irrigated areas, it is quite obvious that groundwater should not be massively used for irrigation in\u00a0critical areas, as it is valuable water that should be reserved for drinking purposes. In\u00a0addition, there will obviously be simultaneous occurrences of\u00a0the\u00a0demand for irrigation (longer periods of\u00a0heat and drought) and, simultaneously, low flows in\u00a0watercourses (longer periods of\u00a0drought and heat). Water demand will thus be covered only by the\u00a0construction of\u00a0additional reservoirs, or by modifying the\u00a0handling regulations of\u00a0existing reservoirs (if they have free capacity).<\/span><\/p>\n Implementation of\u00a0irrigation mathematical models can help (e.g. the\u00a0AQUA CROP model, registered by FAO). These methods will rather help to optimize the\u00a0size and timing of\u00a0irrigation doses; however, they do not influence the\u00a0overall water balance.<\/span><\/p>\n We can see that the\u00a0state records a\u00a0large amount of\u00a0data and information, but often without a\u00a0concept, in\u00a0different places and without mutual continuity. Therefore, it is recommended to:<\/span><\/p>\n Based on analysis within\u00a0the\u00a0excellent research projects of\u00a0the\u00a0Operational Programme Research, Development and Education \u2013 Sustainability of\u00a0Ecosystem Services (OPVVV SustES) and the\u00a0Operational Programme Jan Amos Komensk\u00fd\u00a0\u2013 Advanced Methods of\u00a0Emission Reduction and Sequestration of\u00a0Greenhouse Gases in\u00a0Agricultural and Forest Landscapes (OP JAK AdAgriF), the\u00a0CzechGlobe team systematically tested the\u00a0suitability of\u00a0methods for the\u00a0preparation of\u00a0usable and robust data for estimating future climate developments. The\u00a0team considered the\u00a0fact that the\u00a0latest set of\u00a0intercomparison projects of\u00a0the\u00a0Coupled Model Phase 6 \u2013 Global Circulation Model (CMIP6 GCM) includes models with different degrees of\u00a0spatial detail. Most simulations of\u00a0climate development in\u00a0the\u00a021st century have a\u00a0horizontal spatial resolution of\u00a0around 100 or 250\u00a0km. There is also a\u00a0small subset of\u00a0Global Circulation Models (GCMs) with a\u00a0resolution of\u00a0around 50\u00a0km, but their simulations end in\u00a0the\u00a0mid-21st century. Individual GCMs also differ in\u00a0the\u00a0complexity of\u00a0the\u00a0descriptions of\u00a0events in\u00a0the\u00a0climate system, the\u00a0methods of\u00a0parametrization of\u00a0smaller-scale phenomena, as well as the\u00a0formulation and numerical solution of\u00a0basic physical equations. It is natural that the\u00a0simulated climate diverges to a\u00a0certain\u00a0extent from reality and this difference changes in\u00a0space, time, or across physical quantities. After five years\u2019 research, GCMs that best affect the\u00a0climate of\u00a0Central Europe were preferred for simulations of\u00a0the\u00a0future Central European climate. Simultaneously, it is necessary to ensure that the\u00a0preferred GCMs (which are only a\u00a0subset of\u00a0all available GCMs) affect the\u00a0future climate development in\u00a0the\u00a0same way, with the\u00a0same degree of\u00a0uncertainty, as the\u00a0full set of\u00a0all available GCMs. That is, for the\u00a0selected subset of\u00a0GCMs not to represent models that, under the\u00a0same conditions, expect e.g.\u00a0higher increase in\u00a0temperature (or changes in\u00a0precipitation, wind, sunshine, etc.) than models that are outside the\u00a0selection. The\u00a0narrowing of\u00a0the\u00a0set of\u00a0climate models was carried out by the\u00a0procedure proposed by Meitner\u00a0[16].<\/span><\/p>\n In\u00a0accordance with the\u00a0methodology, from the\u00a0set of\u00a0around twenty CMIP6\u00a0GCMs (which had all the\u00a0necessary elements and emission scenarios available), those models that were not able to reliably simulate the\u00a0Central European climate of\u00a0the\u00a0recent past were excluded based on validation. From the\u00a0other models, six GCMs with a\u00a0resolution of\u00a0100\u00a0km and representing all four emission scenarios were selected so that this narrower selection represented the\u00a0entire original set of\u00a0models with its statistical properties, but enabled working with a\u00a0smaller number of\u00a0simulations. GCM selection was done with regard to all basic meteorological elements, which are further analysed, or used for the\u00a0calculation of\u00a0reference evapotranspiration and soil moisture by the\u00a0SoilClim model. The\u00a0model selection, together with the\u00a0available climate change scenarios, is shown in\u00a0Tab.\u00a01<\/span> below. GCMs with finer spatial resolution (100\u00a0km versus 250\u00a0km) were preferred.<\/span><\/p>\n Climate change scenarios serve as a\u00a0source of\u00a0so-called boundary conditions for GCMs and reflect various possible future trajectories of\u00a0global development not only from the\u00a0point of\u00a0view of\u00a0emissions or resulting concentrations of\u00a0greenhouse gases in\u00a0the\u00a0atmosphere, but also in\u00a0terms of\u00a0various economic and social developments on the\u00a0planet. The\u00a0latest sixth assessment report of\u00a0the\u00a0IPCC (AR6) (available at: https:\/\/www.mzp.cz\/cz\/souhrnna_zprava_ipcc) works with scenarios of\u00a0socioeconomic development, known as Shared Socioeconomics Pathways (SSP). In\u00a0current nomenclature, the\u00a0SSP code includes both the\u00a0path of\u00a0socio-economic development (first number) and the\u00a0predicted impact of\u00a0anthropogenic emissions on the\u00a0greenhouse effect enhancement in\u00a0tenths of\u00a0W. m-2<\/span><\/sup> (watts per square metre \u2013 energy flow density).<\/span><\/p>\n <\/p>\n In\u00a0simple terms, the\u00a0individual climate change scenarios used for input into GCM simulations can be interpreted as follows:<\/span><\/p>\n Unless we are concerned only with the\u00a0relative change of\u00a0meteorological elements, GCM outputs cannot be used directly. They are burdened with systematic error (e.g., in\u00a0Central Europe \u2013 an underestimation of\u00a0temperature by 1\u00a0\u00b0C, or overestimation of\u00a0precipitation by 25\u00a0%, etc.), which must first be removed by so-called bias correction. Alternatively, it is possible to work with climate change resulting from climate model simulations, which is linked directly to observed data. The\u00a0second approach is referred to as the\u00a0\u201cincremental method\u201d or \u201cdirect modification\u201d and is commonly used in\u00a0the\u00a0Czech Republic for modelling the\u00a0climate change impacts (e.g. on hydrological balance) as there is greater robustness using this method than when using climate model simulations with systematic error correction (so-called bias correction). To use the\u00a0\u201cincremental method\u201d in\u00a0the\u00a0daily step, it is advisable to apply transformations that consider not only changes in\u00a0averages, but also variability. This is made possible, for example, by the\u00a0Advanced Delta Change (ADC) method. Thanks to the\u00a0ADC method, the\u00a0change in\u00a0variability can also be included in\u00a0the\u00a0transformation. This simply means that the\u00a0extremes can vary differently than the\u00a0average, which correctly reflects our experience in\u00a0the\u00a0real world. When deriving precipitation changes from the\u00a0climate model, the\u00a0ADC method also considers systematic simulation errors, which may not be linear. Further details can be found in\u00a0van Pelt et al.\u00a0[17]. The\u00a0development of\u00a0the\u00a0basic set of\u00a0scenarios using the\u00a0ADC method, as well as the\u00a0selection and analysis for the\u00a0purposes of\u00a0this project, were carried out iteratively and in\u00a0close cooperation between the\u00a0CzechGlobe, CZU, and TGM WRI teams.<\/span><\/p>\n These scenarios obtained as part of\u00a0the\u00a0OPVVV SustES and OP JAK AdAgriF projects were adapted for the\u00a0teams at the\u00a0\u201cWater Centre<\/span>\u201d into a\u00a0form suitable for the\u00a0model tools used here and tested in\u00a0detail. Although the\u00a0actual preparation of\u00a0scenarios and data analysis was not directly part of\u00a0the\u00a0contract for \u201cWater Centre<\/span>\u201d, it is necessary to mention the\u00a0basic description of\u00a0the\u00a0methods. At the\u00a0same time, the\u00a0individual simulation runs within\u00a0the\u00a0cascade of\u00a0irrigation and hydrological models are unique and used only within\u00a0the\u00a0\u201cWater Centre<\/span>\u201d.<\/span><\/p>\n With regard to the\u00a0interpretation of\u00a0results, in\u00a0addition to the\u00a0reference period 1981\u20132010, we are working with 30-year time windows for the\u00a0future climate: 2020\u20132050 As part of\u00a0the\u00a0project, the\u00a0SoilClim model was used, among other things, for drought monitoring and forecasting in\u00a0the\u00a0www.intersucho.cz system, which is based on the\u00a0recommended methodology of\u00a0FAO\u00a0[18] and ASCE\u00a0[19]. The\u00a0SoilClim model outputs for the\u00a0climatological water balance were compared in\u00a0the\u00a0past for greater robustness with the\u00a0model of\u00a0the\u00a0Czech Hydrometeorological Institute AVISO with goodness of\u00a0fit (e.g. \u0160t\u011bp\u00e1nek et al.\u00a0[20]). Model estimates of\u00a0water demand in\u00a0the\u00a0SoilClim model were made for each grid with a\u00a0resolution of\u00a0500\u00a0\u00d7\u00a0500\u00a0m across the\u00a0entire Czech Republic based on daily meteorological data, data on inclination and exposure of\u00a0the\u00a0land (for considering the\u00a0radiation and energy balance), data on the\u00a0retention capacity and soil depth, and the\u00a0possible influence of\u00a0groundwater. In\u00a0individual cases, the\u00a0calculation was limited only to grids with agricultural land, or to irrigable grids. The\u00a0dynamics of\u00a0vegetation growth in\u00a0the\u00a0SoilClim model took into account the\u00a0connection of\u00a0plant development (but also the\u00a0date of\u00a0sowing\/planting\/sensitive periods\/harvest) to weather. Key factors influencing water demand (e.g. variable leaf area or rooting depth) are considered and change dynamically during the\u00a0season. For the\u00a0cases of\u00a0calculating water demand in\u00a0the\u00a0expected climate, the\u00a0CO2<\/span> effect on the\u00a0water regime of\u00a0plants is also included. On the\u00a0basis of\u00a0previous studies dealing with irrigation in\u00a0our country and a\u00a0search of\u00a0world specialist literature, the\u00a0key parameters of\u00a0vegetation cover were determined, which represented a\u00a0total of\u00a020 crops\/cultures, some of\u00a0which were assessed in\u00a0different regimes (e.g. orchards with bare soil or active growth in\u00a0intermediate rows). It was thus possible to determine the\u00a0relative water demand of\u00a0individual cultures. The\u00a0methodology includes a\u00a0change in\u00a0the\u00a0onset of\u00a0phenological works, changes in\u00a0sowing and harvesting dates, and thus also reflects a\u00a0change in\u00a0the\u00a0seasonality of\u00a0the\u00a0need for irrigation.<\/span><\/p>\n When determining the\u00a0demand for soil water, all calculations were performed at the\u00a0level of\u00a0individual grids in\u00a0a\u00a0daily step, and the\u00a0irrigation dose was applied whenever soil water content of\u00a0a\u00a0root zone fell below 30\u00a0% of\u00a0retention capacity, i.e. the\u00a0limit was reached when water is relatively difficult for plants to access and their growth is subsequently significantly limited by lack of\u00a0soil water. With this \u201cmaintenance\u201d irrigation, the\u00a0survival of\u00a0the\u00a0culture is guaranteed. A\u00a0special regime was used for weeks when the\u00a0value of\u00a0the\u00a0irrigation efficiency factor taken from \u010cSN 75 0434 for the\u00a0given week and the\u00a0given crop indicated an efficiency factor higher than 40 (which means a\u00a0significant influence of\u00a0irrigation on economic yield). In\u00a0these cases, soil water content of\u00a0the\u00a0root zone was maintained at values of\u00a0at least 50\u00a0%. Such type of\u00a0irrigation would be relatively very effective.<\/span><\/p>\n Currently, the\u00a0final determination of\u00a0soil moisture demand is underway by the\u00a0cascade of\u00a0SoilClim and BILAN models, using the\u00a0knowledge obtained in\u00a0cooperation with WP1 partners. Currently, calculations of\u00a0the\u00a0possible irrigable area for the\u00a0following selected commodities were performed for each surface water body: spring barley, winter wheat, maize, winter rapeseed, early potatoes, apples \u2013 bare surface, apples \u2013 active surface, cherries \u2013 bare surface, cherries \u2013 active surface, apricots \u2013 bare surface, apricots \u2013 active surface, peaches \u2013 bare surface, peaches \u2013 active surface, vineyards, hop fields, strawberries, garlic, onions, carrots, peppers, cucumbers, cauliflower, cabbage.<\/span><\/p>\n After all the calculations were done, this soil moisture demand was determined, and in the next step, the TGM WRI team worked with the data not only for the current climate, but for the most current climate change scenarios based on the CMIP6 model suite. Based on the provided climate data and soil moisture from the SoilClim model, TGM WRI determined the available water resources for each surface water body for current and future climate. TGM WRI, in agreement with CzechGlobe, carries out calculations in variants, namely in the variant that takes into account the fact that water is managed in the entire system (that is, we have water available from reservoirs and from the catchment further downstream), but also in the variant where water management is limited to the given surface water body. From this available amount, for example, resources can be deducted to cover losses during the transport of water to irrigated land based on the methodology of the CTU team. Through a gradual iterative calculation, the available water in each surface water body can be divided for individual grids so that the water was first distributed to irrigable grids, according to the soil quality. If the water in the given surface water body was sufficient to cover the requirements of all irrigable grids, the irrigation water was subsequently distributed to other grids (again, according to soil quality). The result of the calculation is the potentially irrigable area, both in a normal year and in the case of a five- and ten-year drought. The calculation of irrigation demand for individual commodities is dynamic and is based on an analysis of the moisture demand of the given commodity in the root zone. Irrigation is indicated if soil moisture in the root zone drops below 0.3. The irrigable area was then determined in cooperation between CTU, TGM WRI and CzechGlobe,\u00a0<\/span>and simultaneously, based on CTU\u2019s\u00a0analysis, the\u00a0parameters for calculating irrigation water losses were changed as the\u00a0sum of\u00a0losses on the\u00a0line and irrigation detail.<\/span><\/p>\n The\u00a0value of\u00a0K1<\/span><\/sub> was defined as 0.12 (i.e. 12\u00a0%) and the\u00a0value of\u00a0K2<\/span><\/sub> was determined according to Tab.\u00a02<\/span><\/em>. Depending on the\u00a0crop, it is thus newly calculated with a\u00a0loss of\u00a017\u201337\u00a0%.<\/span><\/p>\n These changes represent a\u00a0relatively significant change in\u00a0the\u00a0entire methodological procedure. In\u00a0the\u00a0final calculation, sowing procedures were applied to potentially irrigated areas according to data from LPIS based on real data from 2015\u20132023, processed by CzechGlobe. This made it possible to determine the\u00a0\u201creal\u201d demand for water within\u00a0the\u00a0irrigation systems and subsequently to standardize the\u00a0calculations for the\u00a0future climate. The\u00a0outputs of\u00a0the\u00a0joint work are being prepared for publication in\u00a0an impact journal (Agricultural Water Management<\/span>).<\/span><\/p>\n The\u00a0final calculation of\u00a0moisture demand thus combines innovative procedures based on the\u00a0valid \u010cSN 75 0434, practical experience from irrigation practice and also the\u00a0real composition of\u00a0crops in\u00a0surface water bodies with irrigation, because the\u00a0specific use of\u00a0irrigation so far cannot be determined otherwise. Two scenarios were created to determine irrigation needs.<\/span><\/p>\n The\u00a0first was based on the\u00a0goal of\u00a0maximizing production and not allowing soil water content to drop below the\u00a0point of\u00a0reduced moisture availability, to which plants respond by reducing production (in\u00a0simple terms). The\u00a0second was aimed at not allowing soil water content to fall below values of\u00a0intense water stress, i.e. a\u00a0situation where crop production is significantly reduced due to a\u00a0lack of\u00a0water. While the\u00a0first procedure aims to maximize production in\u00a0conditions of\u00a0limited water resources, the\u00a0second procedure serves primarily to maintain\u00a0the\u00a0basal level of\u00a0production and conserve water resources to the\u00a0maximum extent possible. From the\u00a0point of\u00a0view of\u00a0profitability, the\u00a0first of\u00a0the\u00a0chosen procedures is suitable in\u00a0situations where water resources in\u00a0the\u00a0catchment are sufficient, the\u00a0second can be seen as an emergency scenario, as it does not guarantee producers an adequate yield; however, in\u00a0a\u00a0number of\u00a0seasons, especially during shorter episodes of\u00a0drought, it can fundamentally contribute to reducing damage with relatively less water consumption.<\/span><\/p>\n Simultaneously, the\u00a0calculations dealt with ensuring moisture demand for the\u00a0upper 40 cm variant or the\u00a0profile up to a\u00a0depth of\u00a0100 cm. In\u00a0Fig.\u00a04<\/span><\/em>, both variants are presented for ensuring soil moisture in\u00a0the\u00a0corresponding volume in\u00a0the\u00a0upper 40 cm of\u00a0the\u00a0profile as a\u00a0change in\u00a0demand compared to the\u00a0period 1981\u20132010 for the\u00a0realistic emission scenario SPSS 2-4.5. It is clear that the\u00a0entire spectrum of\u00a0expected changes cannot be covered on the\u00a0basis of\u00a0one GCM model, nor can it be done on the\u00a0basis of\u00a0using only one emission scenario.<\/span><\/p>\n The\u00a0results clearly show significant variability in\u00a0lines of\u00a0the\u00a0same GCM models for different emission scenarios, especially for the\u00a0periods 2015\u20132045 (2030) and 2035\u20132065 (2050). Even in\u00a0regions where, on average, there is a\u00a0reduction in\u00a0moisture demand, there is still a\u00a0need to irrigate. However, what still remains an unanswered question is the\u00a0impact of\u00a0the\u00a0not yet considered variant based on the\u00a0estimate of\u00a0the\u00a0GLOBIOM-CZ agro-economic model. It\u00a0shows the\u00a0considerable comparative advantage of\u00a0Czech agricultural production in\u00a0the\u00a0expected environmental conditions, and therefore the\u00a0possibility to increase the\u00a0profitability and market share of\u00a0Czech agriculture despite climate change. That is, a\u00a0situation where conditions on the\u00a0world markets will be economically favourable to the\u00a0expansion of\u00a0domestic production, potentially even without state intervention. In\u00a0such a\u00a0situation, there could be pressure on using two harvests per year, which with a\u00a0certain\u00a0combination of\u00a0crops grown today and\/or a\u00a0combination of\u00a0suitable varieties will be possible in\u00a0a\u00a0few years\/decades. However, the\u00a0success of\u00a0the\u00a0second crop will be determined by the\u00a0ability to harvest the\u00a0first crop in\u00a0time and, especially after sowing, to ensure good uptake of\u00a0the\u00a0second crop in\u00a0the\u00a0height of\u00a0summer. Without additional irrigation, the\u00a0latter will not be possible in\u00a0most years in\u00a0the\u00a0warmest regions of\u00a0Bohemia and Moravia.<\/p>\n The\u00a0aim of\u00a0the\u00a0CZU research, which is the\u00a0development of\u00a0water consumption by livestock in\u00a0the\u00a0Czech Republic, is to compile scenarios of\u00a0animal husbandry in\u00a0individual regions of\u00a0the\u00a0Czech Republic. The\u00a0result is finding out what kind of\u00a0livestock have been bred in\u00a0individual areas in\u00a0the\u00a0last 20 years and in\u00a0the\u00a0future, and what their water consumption will be, both throughout the\u00a0year and in\u00a0individual seasons. Livestock such as cows, pigs, sheep, goats, horses, and poultry are a\u00a0significant source of\u00a0commodities used by humans. In\u00a0connection with climate change, adaptation measures for livestock will be addressed, mainly with regard to their loading caused by the\u00a0increase in\u00a0spring and summer temperatures. There is also the\u00a0increasing number of\u00a0consecutive tropical days; such conditions cause thermal stress in\u00a0animals, which is manifested, for example, in\u00a0cattle by lower milk yield and weight gain\u00a0[21]. Stressful conditions will occur in\u00a0both stables and pastures, and animal performance will probably decrease.<\/span><\/p>\n Livestock have a\u00a0considerable consumption of\u00a0water. In\u00a0addition, growing human population and demand for animal products are expected to increase demand for water and changing precipitation patterns worldwide. Therefore, the\u00a0question arises whether there will be enough available water in\u00a0the\u00a0future and what effect the\u00a0(in)availability of\u00a0water will have on the\u00a0possibilities of\u00a0breeding livestock\u00a0[22].<\/span><\/p>\n As part of\u00a0the\u00a0data analysis, data were first collected on the\u00a0number of\u00a0livestock in\u00a0individual regions of\u00a0the\u00a0Czech Republic for the\u00a0period 2002\u20132020. The\u00a0obtained tables included data on the\u00a0number of\u00a0cattle, pigs, sheep, goats, horses, and poultry (Tab.\u00a03<\/span>). Due to the\u00a0fact that the\u00a0numbers of\u00a0cows, sows, and hens were additionally listed in\u00a0the\u00a0tables, it was necessary to adjust the\u00a0data. The\u00a0numbers of\u00a0cows, sows, and hens were subtracted from the\u00a0total numbers of\u00a0cattle, pigs, and poultry, so that the\u00a0resulting values correspond to the\u00a0number of\u00a0cattle without cows, pigs without sows, and poultry without hens.<\/span><\/p>\n In\u00a0the\u00a0next step, it was necessary to determine water consumption for livestock\u00a0[22]. In\u00a0the\u00a0overall table, water consumption is divided for young animals, for nursing\/lactating females, and for fattened animals. Minimum and maximum water consumption in\u00a0litres per piece per head are always indicated, as well as maximum consumption in\u00a0cubic metres per head per year. The\u00a0minimum water consumption per day applies to the\u00a0winter, the\u00a0maximum water consumption per day to the\u00a0summer. The\u00a0average of\u00a0these minimum and maximum values was determined as water consumption per day in\u00a0the\u00a0spring and autumn (Tab.\u00a04<\/span><\/em>). The\u00a0average water consumption per head during the\u00a0seasons (in\u00a0units of\u00a0l\/head\/season), the\u00a0average water consumption per head (in\u00a0the\u00a0units of\u00a0l\/head\/year and m3<\/span><\/sup>\/head\/year), as well as the\u00a0maximum water consumption per head (in\u00a0units m3<\/span><\/sup>\/head\/year) (Tab.\u00a04<\/span><\/em>).<\/span><\/p>\n <\/p>\n Since poultry includes not only chickens, but also ducks, turkeys and geese (which have different water consumption), it was necessary to determine the\u00a0approximate percentage representation of\u00a0individual animal species in\u00a0the\u00a0Czech Republic. For this, the\u00a0Situation and outlook report Poultry and eggs<\/span> was used (available at: https:\/\/mze.gov.cz\/public\/portal\/mze\/publikace\/situacni-vyhledove-zpravy\/zivocisne-komodity-hospodarska-zvirata\/drubez-a-vejce<\/span><\/a>); on its basis, the\u00a0percentage representation of\u00a0farmed poultry species between 2010 and 2018 was calculated. In\u00a0the\u00a0next step, by multiplying the\u00a0number of\u00a0individual species of\u00a0livestock and the\u00a0average (or maximum) water consumption per head of\u00a0a\u00a0single farm animal species, water consumption by individual farm animal species was determined; after adding up the\u00a0data, the\u00a0total water consumption by livestock per year was determined. This was calculated for each year between 2002 and 2018 and for each region separately. Estimates of\u00a0the\u00a0number of\u00a0individual farm animal species and water consumption were made for 2025, 2030, 2035, 2040, 2045, and 2050 using the\u00a0Forecast Sheet tool. The\u00a0tool calculated the\u00a0mean estimate and its lower and upper bounds. Estimates were again\u00a0carried out separately for each region. In\u00a0order to calculate water consumption by livestock during individual seasons, the\u00a0average percentage of\u00a0water consumption in\u00a0these seasons compared to the\u00a0whole year was first determined, which was 25.34\u00a0% for spring, 30.19\u00a0% for summer, 24.53\u00a0% for autumn, and 19.94\u00a0% for winter. Water consumption in\u00a0individual seasons was then calculated based on the\u00a0values found for the\u00a0entire year, namely for 2005, 2010, 2015, 2020, 2025, 2030, 2035, 2040, 2045, and 2050.<\/span><\/p>\n The\u00a0resulting values and conclusions always apply to the\u00a0year 2050 compared to 2005.<\/span><\/p>\n The\u00a0development of\u00a0water consumption by livestock was predicted for each region separately, with trends varying across individual regions. A\u00a0steady state of\u00a0water consumption by livestock is expected for the\u00a0South Moravian, \u00dast\u00ed, Zl\u00edn, and Vyso\u010dina regions; a\u00a0slight increase is expected in\u00a0the\u00a0South Bohemian and Pilsen regions; a\u00a0significant increase in\u00a0water consumption is predicted for the\u00a0Karlovy Vary, Liberec, and Moravian-Silesian regions; a\u00a0future decrease in\u00a0water consumption by livestock is expected in\u00a0the\u00a0Hradec Kr\u00e1lov\u00e9, Olomouc, and Pardubice regions, as well as in\u00a0Prague and the\u00a0Central Bohemian region. Water consumption trends in\u00a0individual regions are the\u00a0same for both average and maximum water consumption by livestock (Fig.\u00a06<\/span><\/em>).<\/span><\/p>\n The\u00a0results point to significant differences in\u00a0water consumption between regions, which is influenced both by the\u00a0specific conditions in\u00a0each region and by the\u00a0type and number of\u00a0livestock (Fig.\u00a06<\/span><\/em>). Forecasts for 2025\u20132050 point to possible changes in\u00a0agricultural practices that will have an impact on future water demand. A\u00a0detailed description of\u00a0the\u00a0results was published in\u00a0the\u00a0methodology\u00a0[22] entitled Metodika hodnocen\u00ed spot\u0159eby vody hospod\u00e1\u0159sk\u00fdmi zv\u00ed\u0159aty v\u00a0letech 2002\u20132020 a\u00a0predikce v\u00fdvoje spot\u0159eby vody hospod\u00e1\u0159sk\u00fdmi zv\u00ed\u0159aty v\u00a0letech 2030, 2035, 2040, 2045 a\u00a02050 v\u00a0jednotliv\u00fdch kraj\u00edch \u010cR<\/span><\/em> (Methodology for evaluating water consumption by livestock in\u00a0the\u00a0years 2002\u20132020 and prediction of\u00a0the\u00a0development of\u00a0water consumption by livestock in\u00a02030, 2035, 2040, 2045 and 2050 in\u00a0individual regions of\u00a0the\u00a0Czech Republic<\/em>), published by CZU\u00a0[22]. This publication provides a\u00a0detailed overview of\u00a0the\u00a0methodology and forecasts that were used in\u00a0this study and are key for the\u00a0further development and planning of\u00a0water management in\u00a0the\u00a0Czech Republic.<\/span><\/p>\n \u00a0<\/span><\/p>\n As part of\u00a0this analysis, the\u00a0numbers of\u00a0cattle, pigs, sheep, horses, goats, and poultry (hens, ducks, turkeys, geese) bred in\u00a02002\u20132020 were evaluated, and their number in\u00a0the\u00a0following years until 2050 was also predicted (Fig.\u00a07<\/span><\/em>). Based on the\u00a0livestock numbers, their water consumption was determined. By 2050, a\u00a0significant reduction in\u00a0the\u00a0breeding of\u00a0pigs and poultry is expected in\u00a0most regions of\u00a0the\u00a0Czech Republic and, in\u00a0contrast, a\u00a0significant increase in\u00a0the\u00a0number of\u00a0sheep, horses, and goats. This is probably related to the\u00a0subsidies for the\u00a0breeding of\u00a0these animals. Livestock numbers will increase in\u00a0some regions and decrease in\u00a0others. Significantly higher water consumption by livestock is expected in\u00a0the\u00a0Karlovy Vary, Liberec, and Moravian-Silesian regions, while consumption in\u00a0the\u00a0other regions will probably be similar or lower. In\u00a0very vulnerable areas from the\u00a0point of\u00a0view of\u00a0water shortage, such as South Moravia and the\u00a0Central Bohemian region, a\u00a0significant decrease in\u00a0the\u00a0amount of\u00a0water consumed by livestock is probable.<\/span><\/p>\n <\/p>\n To estimate the\u00a0water demand for energy industry sector in\u00a0the\u00a0Czech Republic, researchers from TGM WRI used a\u00a0systematic approach that includes data collection, analysis of\u00a0current conditions, and prediction of\u00a0future demand.<\/span><\/p>\n <\/p>\n <\/p>\n Overall, it can be assumed that more than a\u00a0third of\u00a0coal-fired power stations will be shut down, and those that remain\u00a0will switch to burning biomass. There will also be an increase in\u00a0water consumption for the\u00a0Temel\u00edn and Dukovany nuclear power stations. In\u00a0the\u00a0case of\u00a0most heating plants, it is expected that after the\u00a0necessary modernization, they will remain\u00a0in\u00a0operation and burn biomass.<\/span><\/p>\n The\u00a0prediction itself was determined by calculating the\u00a0average maximum and minimum quantity abstracted in\u00a02013\u20132022 for individual consumers. For each abstraction point, an index of\u00a0future demand was determined, which was then used to calculate the\u00a0average maximum and minimum amount per demand in\u00a02050. For the\u00a0maximum and minimum estimated demand, the\u00a0drop in\u00a0surface and groundwater abstraction amounts to about 18\u00a0%. Fig.\u00a010<\/span><\/em> shows a\u00a0comparison between the\u00a0maximum and minimum average energy consumption for 2013\u20132022 and the\u00a0prediction for 2050. Fig.\u00a011<\/span><\/em> shows this comparison broken down by regions.<\/span><\/p>\nWater demand analysis for\u00a0industry<\/h2>\n
METHODOLOGY AND SOURCES USED<\/h3>\n
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\n<\/li>\nSUMMARY OF RESULTS<\/h3>\n
CONCLUSIONS AND THEIR UNCERTAINTIES<\/h3>\n
Baseline value<\/h4>\n
![\"\"](\"https:\/\/www.vtei.cz\/wp-content\/uploads\/2024\/12\/Dlabal-obr-1-1.jpg\")
<\/a>\nFig. 1. Surface and groundwater abstraction scenarios for industry up to 2050 based on data from 2009\u20132019 in sub-sectors<\/h6>\n
Maximum value<\/h4>\n
Critical value (must not be exceeded)<\/h4>\n
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\nTotal demand for water in\u00a0industry in\u00a0the\u00a0Czech Republic has been decreasing for a\u00a0long time; however, simply projecting this fact into the\u00a0future could lead to completely wrong conclusions (theoretically to almost zero water demand). Conversely, any growth observed in\u00a0a\u00a0certain\u00a0industry and region cannot simply be extrapolated into the\u00a0future based on a\u00a0mathematical calculation. Even the\u00a0steady state observed in\u00a0a\u00a0number of\u00a0industries in\u00a0recent years does not mean that there will be no fundamental changes in\u00a0the\u00a0future.<\/li>\n
\nTrends valid at the\u00a0national or regional level may not be valid for a\u00a0smaller area. The\u00a0project envisages modelling water management balance at the\u00a0level of\u00a0small units \u2013 hydrogeological districts and water bodies, where it can be expected that the\u00a0situation will also be assessed at individual abstraction points, i.e. individual entities. In\u00a0such a\u00a0case, it will largely depend on local conditions.<\/li>\n
\nA\u00a0prediction based on the\u00a0analysis of\u00a0historical data cannot, in\u00a0principle, work with the\u00a0possible demise of\u00a0the\u00a0business (in\u00a0the\u00a0sense of\u00a0ending production) and especially with the\u00a0construction of\u00a0a\u00a0new one (primarily on so-called green field).<\/li>\n
\nAs mentioned earlier, permitted abstraction of\u00a0surface and groundwater will serve in\u00a0the\u00a0prediction of\u00a0water demand as a\u00a0limit that future development must not exceed. Given that in\u00a0some cases the\u00a0permitted values are significantly higher than the\u00a0real state, it is not guaranteed that the\u00a0current yield of\u00a0the\u00a0relevant water resources allows them to be achieved.<\/li>\n<\/ol>\nWater demand for agriculture: Irrigation water demand\u00a0\u2013 from\u00a0the\u00a0point of\u00a0view of\u00a0irrigation technology<\/h3>\n
METHODOLOGY<\/h3>\n
RESULTS<\/h3>\n
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<\/a>Fig. 2. Illustration of irrigation water requirements per growing season in m3<\/sup> in\u00a0individual UDPs, variant \u201eforecast GS\u201c. (Source: CTU)<\/h6>\nUNCERTAINTIES<\/span><\/h3>\n
CONCLUSIONS AND RECOMMENDATIONS<\/h3>\n
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Water demand for irrigation from the\u00a0point of\u00a0view of\u00a0plant demand modelling: preparation of\u00a0scenarios for the\u00a0development of\u00a0climate parameters \u2013 selection of\u00a0models<\/h2>\n
Tab.\u00a01. Overview of models and country of origin; the nominal grid size in the equatorial region was approximately 100\u00a0\u00d7\u00a0100\u00a0km, and simulations of all models were available for all socioeconomic scenarios (SSP \u2013 see below)<\/h5>\n
<\/a>\n<\/a>\nFig. 3. Illustration of the difference between the sum of precipitation and reference evapotranspiration in the so-called warm half-year (April\u2013September) for the reference period (a) 1981\u20132010 and the periods (b, e) 2020\u20132050, i.e. 2035, (c, f) 2030\u20132060, i.e. 2045 and (d, g) 2040\u20132070, i.e. 2055, for basin level IV. Maps b\u2013d show the change in absolute value, maps\u00a0e\u2013g show the nature of the climate signal, i.e. the relative change<\/h6>\n
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Preparation of\u00a0climate scenarios<\/h3>\n
\n(referred to as \u201c2035\u201d), 2030\u20132060 (\u201c2045\u201d), and 2040\u20132070 (\u201c2055\u201d). The\u00a0periods overlap each other. Within\u00a0these time windows, statistical characteristics (including extremes) for the\u00a0given period can be evaluated. Similar to climate model simulations, it does not make sense to analyse and present individual days or years, but only statistics for the\u00a0entire period. Long-term trends can then be evaluated by connecting individual (sliding) periods in\u00a0future climate. An example of\u00a0the\u00a0output for the\u00a0water balance (i.e. difference between ETref and precipitation) in\u00a0growing season is shown in\u00a0Fig.\u00a03<\/span><\/em>.<\/span><\/p>\nAnalysis of\u00a0water demand for crop production<\/h3>\n
Final iteration of\u00a0determining irrigation sources and\u00a0demands<\/h3>\n
<\/a>\nTab.\u00a02. Value of parameter K2<\/sub><\/h5>\n
<\/a>\n<\/a>\nFig. 4. Change in average annual irrigation demand for surface water bodies between the reference period (a) 1981\u20132010 and the periods 2030 (2015\u20132045); 2050 (2035\u20132065); 2070 (2055\u20132085) and 2085 (2070\u20132099), for the six Global Circulation Models from the\u00a0CMIP6\u00a0model suite for the SSP 2-4.5 emission scenario. The set of maps shows the\u00a0shift in moisture demand under production optimization efforts<\/h6>\n
<\/a>\nFig. 5. Change in average annual irrigation demand for surface water bodies between the reference period (a) 1981\u20132010 and the periods 2030 (2015\u20132045); 2050 (2035\u20132065); 2070 (2055\u20132085) and 2085 (2070\u20132099) for the six Global Circulation Models from the\u00a0CMIP6\u00a0model suite for the SSP 2-4.5 emission scenario. The set of maps shows the\u00a0change in\u00a0irrigation demand to avoid drought stress for crops<\/h6>\n
Water demand for animal husbandry<\/h2>\n
METHODOLOGY<\/h3>\n
Tab. 3. List of breeding animals (according to CSU tables)<\/h5>\n
<\/a>\nTab. 4. Water consumption by species (according to standards)<\/h5>\n
<\/a>\nRESULTS<\/h3>\n
Number of\u00a0livestock and average water consumption per\u00a0year for individual regions<\/h3>\n
Tab.\u00a05. Number of animals and average water consumption (m3<\/sup>\/year) for each animal group<\/h5>\n
<\/a>\n<\/a>\nFig. 6. Percentage change in average water consumption in individual regions of\u00a0the\u00a0Czech\u00a0Republic in 2050 compared to 2005<\/h6>\n
CONCLUSION<\/h2>\n
<\/a>\nFig. 7. Average water consumption by region 2005\u20132050<\/h6>\n
Analysis of\u00a0water demand for\u00a0energy\u00a0industry<\/h2>\n
METHODOLOGY<\/h3>\n
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\n<\/li>\nSUMMARY OF RESULTS<\/h3>\n
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\n<\/li>\n<\/a>\nFig. 8. Surface and groundwater abstraction locations for energy in 2013\u20132022 \u2013 differentiation by quantity and type of production<\/h6>\n
<\/a>\nFig. 9. Groundwater and surface water abstractions in the Czech Republic 1980\u20132022<\/h6>\n
Tab. 6. Corridors for primary energy sources (relative to their total annual consumption)<\/h5>\n
<\/a>\nTab. 7. Corridors for gross electricity generation (relative to total annual generation)<\/h5>\n
<\/a>\n<\/a>\nFig. 10. Maximum and minimum average surface water and groundwater abstractions for energy for 2013\u20132022 vs. estimated minimum and maximum abstractions for energy in 2050<\/h6>\n