INTRODUCTION<\/h2>\n
Hydrological drought represents one of\u00a0the\u00a0most significant challenges for water management under Central European\u00a0conditions. Hydrological drought is characterised by a\u00a0long-term decrease in\u00a0streamflow, a\u00a0reduction in\u00a0groundwater storage, and limited replenishment of\u00a0accumulated water resources. Its impacts are particularly pronounced in\u00a0water supply reservoirs, whose operation is based on the\u00a0assumption of\u00a0a\u00a0relatively stable hydrological regime and long-term statistical stationarity of\u00a0input series. However, this assumption has been systematically disrupted in\u00a0recent decades by ongoing climate change.<\/span><\/p>\n Projections from regional climate models indicate a\u00a0gradual increase in\u00a0air temperature over the\u00a0Czech Republic, along with changes in\u00a0the\u00a0seasonal distribution of\u00a0precipitation and increased evapotranspiration. These changes are reflected in\u00a0a\u00a0decline in\u00a0average summer streamflow, a\u00a0more frequent occurrence of\u00a0multi-year drought episodes, and increased variability in\u00a0runoff. The\u00a0extreme period of\u00a02014\u20132020 demonstrated that even in\u00a0regions traditionally considered stable in\u00a0terms of\u00a0water management, significant declines in\u00a0water levels in\u00a0water supply reservoirs may occur, potentially threatening the\u00a0reliability of\u00a0water abstractions. From a\u00a0legislative perspective, the\u00a0issue of\u00a0drought adaptation is emphasised, for example, through the\u00a0implementation of\u00a0the\u00a0Water Framework Directive, which highlights the\u00a0principles of\u00a0sustainable water resource management and the\u00a0need for integrated river basin\u00a0management. At the\u00a0same time, national climate change adaptation strategies emphasise the\u00a0need to strengthen the\u00a0resilience of\u00a0water management infrastructure to extreme hydrological events. In\u00a0this context, not only the\u00a0construction of\u00a0new water infrastructure but, above all, the\u00a0optimisation of\u00a0the\u00a0operation of\u00a0existing reservoirs is gaining importance. Traditional operating rules for water supply reservoirs are typically based on fixed abstractions and predefined rule curves, the\u00a0parameters of\u00a0which are derived from historical data. Such an\u00a0approach is relatively robust under stationary climate conditions; however, under a\u00a0systematic decline in\u00a0inflows, it may lead to increasing deficit volumes, failure to meet the\u00a0required reliability of\u00a0water abstractions, and significant fluctuations in\u00a0water levels. Pronounced drops in\u00a0water levels have secondary impacts not only on water supply use but also on the\u00a0morphology of\u00a0the\u00a0littoral zone, the\u00a0thermal and oxygen regime of\u00a0the\u00a0reservoir, and eutrophication processes. Fluctuations in\u00a0water levels may therefore adversely affect raw water quality and increase the\u00a0demands placed on its treatment.<\/span><\/p>\n The\u00a0motivation for the\u00a0present research is the\u00a0need to develop a\u00a0methodological framework that enables a\u00a0flexible response to changing hydrological conditions without the\u00a0need for costly structural interventions. Adaptive reservoir management represents a\u00a0promising non-structural measure based on the\u00a0gradual regulation of\u00a0abstractions and, where appropriate, the\u00a0adjustment of\u00a0minimum residual flows depending on the\u00a0current state of\u00a0storage and the\u00a0expected development of\u00a0inflows. In\u00a0addition to increasing the\u00a0reliability of\u00a0water abstractions, this approach also has the\u00a0potential to stabilise water level fluctuations in\u00a0the\u00a0reservoir. Gradual and timely restriction of\u00a0abstractions can\u00a0prevent deep declines in\u00a0water levels towards the\u00a0end of\u00a0dry periods, thereby limiting the\u00a0development of\u00a0undesirable physico-chemical and biological processes affecting water quality. The\u00a0aim of\u00a0this research is to develop and validate a\u00a0methodology for the\u00a0adaptive management of\u00a0water supply reservoirs during hydrological drought, based on a\u00a0combination of\u00a0hydrological modelling, climate change scenarios, and the\u00a0optimisation of\u00a0operating rules. The\u00a0specific objectives are: (1) to quantify the\u00a0impacts of\u00a0future climate scenarios on the\u00a0reliability of\u00a0water abstractions; (2) to design a\u00a0system of\u00a0regulation levels and rule curves enabling the\u00a0gradual restriction of\u00a0abstractions; and (3) to compare the\u00a0effectiveness of\u00a0conventional and adaptive operational regimes in\u00a0terms of\u00a0both supply reliability and water level stability. The\u00a0expected outcome is a\u00a0methodological tool applicable to various types of\u00a0water supply reservoirs, supporting long-term sustainable water resources management under conditions of\u00a0intensifying hydrological drought and contributing to the\u00a0stabilisation of\u00a0the\u00a0internal environment of\u00a0reservoirs in\u00a0terms of\u00a0water quality.<\/span><\/p>\n Adaptive reservoir management is addressed in\u00a0the\u00a0scientific literature as a\u00a0response to increasing hydrological uncertainty driven by climate change, variable streamflow, and the\u00a0growing frequency of\u00a0multi-year drought periods. Traditional approaches to reservoir operation, which maintain\u00a0constant operating rules derived from historical hydrological series, provide good water management stability under conditions of\u00a0a\u00a0relatively stationary climate. However, as early as the\u00a01980s and 1990s, the\u00a0first methodological studies began\u00a0to consider, in\u00a0a\u00a0water management context, greater operational flexibility and rules for restricting abstractions during drought periods in\u00a0order to distribute water deficits more evenly over time. These concepts were derived from economic theories and subsequently applied to the\u00a0evaluation of\u00a0reservoir operation strategies under climatically variable conditions\u00a0[1]. Management rules are often designed to optimise a\u00a0loss function representing the\u00a0total financial losses incurred by water users due to water supply deficits. As early as 1982, Hashimoto et al.\u00a0[2] demonstrated that, with a\u00a0non-linear loss function, early restriction of\u00a0abstractions is advantageous, as a\u00a0single severe water deficit causes greater damage than\u00a0several smaller deficits distributed over time, even if they amount to the\u00a0same total shortage\u00a0[3]. In\u00a0the\u00a0Czech Republic, models of\u00a0adaptive reservoir management and water management systems were first studied at the\u00a0Faculty of\u00a0Civil Engineering, Czech Technical University in\u00a0Prague, through the\u00a0work of\u00a0Nach\u00e1zel and Patera [4, 5].<\/span><\/p>\n The\u00a0study by Ahmadi, Haddad, and Lo\u00e1iciga\u00a0[6] represents one of\u00a0the\u00a0first comprehensive models of\u00a0adaptive reservoir operation rules with respect to the\u00a0impacts of\u00a0climate change. The\u00a0authors used climate projections for the\u00a0mid- and late 21st century and subsequently optimised rule curves to increase reliability and reduce the\u00a0vulnerability of\u00a0water supply reservoir operation during prolonged drought periods. The\u00a0principle of\u00a0adaptation was also applied to the\u00a0strategic management of\u00a0water management systems by Marton et al. [7, 8].<\/span><\/p>\n At present, adaptive management has attracted increasing attention, particularly in\u00a0the\u00a0context of\u00a0combining climate scenarios, hydrological modelling, and optimisation methods. Research applies various approaches, including heuristic algorithms, model predictive control, and optimisation techniques aimed at ensuring the\u00a0reliability of\u00a0storage function performance under future hydrological conditions\u00a0[9]. Studies show that adaptive operating rules can\u00a0significantly improve the\u00a0reliability of\u00a0water supply during drought while simultaneously reducing extreme fluctuations in\u00a0storage levels\u00a0[10].<\/span><\/p>\n Another important direction is the\u00a0research of\u00a0optimisation strategies for the\u00a0management of\u00a0multi-purpose reservoirs. For example, study\u00a0[11] demonstrates how operating rules can\u00a0be modified using regulation levels in\u00a0response to multi-year drought periods, thereby improving the\u00a0operational efficiency of\u00a0the\u00a0system. Modern approaches are also increasingly turning to the\u00a0use of\u00a0machine learning models for reservoir management decision-making, reflecting the\u00a0complex interactions between hydrological inputs and operational constraints\u00a0[12].<\/span><\/p>\n In\u00a0the\u00a0Czech Republic, the\u00a0implementation of\u00a0adaptive reservoir management is supported by legislative and strategic documents. The\u00a0legal framework is primarily based on the\u00a0Water Act No. 254\/2001 Coll., which sets out the\u00a0principles of\u00a0water management and the\u00a0operating rules for water structures, including the\u00a0requirement to minimise the\u00a0adverse impacts of\u00a0drought and water scarcity. In\u00a0addition, Drought Management Plans are developed at both regional and national levels, complementing river basin\u00a0management plans through operational measures in\u00a0accordance with the\u00a0requirements of\u00a0the\u00a0EU Water Framework Directive 2000\/60\/EC.<\/span><\/p>\n These regulations support adaptive approaches that can\u00a0be implemented within\u00a0operating rules and the\u00a0planning of\u00a0minimum residual flows, with an\u00a0emphasis on drinking water supply as a\u00a0priority function. Such approaches are already being tested or applied in\u00a0practice by river basin\u00a0authorities in\u00a0the\u00a0Czech Republic. An\u00a0example is the\u00a0adaptive reservoir management system in\u00a0the\u00a0Oder River Basin, based on study\u00a0[13].<\/span><\/p>\n The\u00a0fundamental principle of\u00a0adaptive reservoir management is the\u00a0replacement of\u00a0rigid operation with constant abstractions by a\u00a0flexible management system that continuously responds to the\u00a0development of\u00a0hydrological conditions. A\u00a0key element of\u00a0this approach is the\u00a0optimisation of\u00a0rule curves, which define regulation levels of\u00a0storage for individual calendar months. As storage volume decreases below defined thresholds, abstractions are gradually restricted according to predefined priorities of\u00a0individual users, while minimum residual flows downstream of\u00a0the\u00a0reservoirs are adjusted in\u00a0a\u00a0controlled manner. This flexible regime enables a\u00a0timely response to the\u00a0onset of\u00a0drought and distributes the\u00a0impacts of\u00a0water scarcity over time, thereby preventing sudden and severe disruptions in\u00a0water supply.<\/span><\/p>\n As part of\u00a0the\u00a0research, a\u00a0system of\u00a0rule curves and regulation levels was developed to define optimal abstractions and minimum residual flows for individual months and climate conditions. The\u00a0methodology was pilot-tested on selected water supply reservoirs in\u00a0the\u00a0Czech Republic, namely \u0160vihov, Kl\u00ed\u010dava, \u017dlutice, Obecnice, Pilsk\u00e1, L\u00e1z, and Vrchlice.<\/span><\/p>\n The\u00a0verification of\u00a0the\u00a0proposed adaptive reservoir management approach was carried out for current climatic conditions and for future conditions corresponding to time horizons around 2050 and 2100. For \u0160vihov reservoir, optimisation of\u00a0adaptive management was based on the\u00a0so-called Medium Climate Change Scenario for Water Management in\u00a0the\u00a0Czech Republic, developed by the\u00a0TGM\u00a0WRI in\u00a02019\u00a0[14]. For the\u00a0other reservoirs, climate data are derived from the\u00a0latest results of\u00a0the\u00a0\u201cWater Centre\u201d project. Within\u00a0this project, the\u00a0publicly available HYMOD database\u00a0[15] was developed, providing detailed results of\u00a0hydrological modelling and analyses of\u00a0the\u00a0hydrological balance of\u00a0catchments (water bodies) under current and future climatic conditions. The\u00a0database is available via a\u00a0web application (https:\/\/shiny.vuv.cz\/HYMOD-KZ\/) and provides a\u00a0comprehensive set of\u00a0climatic and hydrological characteristics derived from multiple climate models. Based on a\u00a0detailed analysis of\u00a0the\u00a0climate scenarios included in\u00a0the\u00a0HYMOD database, changes in\u00a0key meteorological variables, particularly air temperature and precipitation totals, were determined for individual catchments of\u00a0interest for future time horizons up to the\u00a0end of\u00a0the\u00a021st century. The\u00a0database includes results from a\u00a0wide range of\u00a0global and regional climate models, including MEAN (the\u00a0average of\u00a0all models), CMCC-ESM2, EC-EARTH3, GFDL-ESM4, MPI-ESM1-2-HR, MRI-ESM2-0, TAIESM1, and the\u00a0regional climate model ALADIN-CLIMATE\/CZ, representing a\u00a0broad spectrum of\u00a0possible future climate development.<\/span><\/p>\n For the\u00a0purposes of\u00a0verifying adaptive reservoir management, a\u00a0single representative climate scenario was selected for methodological reasons. The\u00a0regional climate model ALADIN-CLIMATE\/CZ under the\u00a0SSP5-8.5 scenario was chosen as the\u00a0most suitable basis. For the\u00a0Czech Republic, this scenario projects a\u00a0gradual increase in\u00a0mean\u00a0annual air temperature of\u00a0approximately 1.0 to 1.4 \u00b0C by 2050 and approximately 3.1 to 3.8 \u00b0C by 2085 (or 2100). These values are also broadly consistent with the\u00a0long-term warming trend observed since the\u00a01980s. In\u00a0contrast, projected changes in\u00a0annual precipitation totals remain\u00a0within\u00a0a\u00a0relatively narrow range across most models and, compared to temperature changes, are not considered a\u00a0dominant factor in\u00a0terms of\u00a0the\u00a0overall water balance.<\/span><\/p>\n The\u00a0selection of\u00a0a\u00a0single climate scenario was motivated by the\u00a0fact that the\u00a0aim of\u00a0the\u00a0research was not to project future climate or to assess uncertainties in\u00a0climate models, but rather to test the\u00a0robustness of\u00a0the\u00a0proposed adaptive reservoir management system under systematically worsening hydrological conditions. The\u00a0selected scenario makes it possible to evaluate the\u00a0effect of\u00a0warming on the\u00a0hydrological response of\u00a0catchments, to ensure consistent inputs for water management simulations, and to clearly interpret the\u00a0behaviour of\u00a0reservoir operating and regulation rules. By contrast, the\u00a0use of\u00a0an\u00a0ensemble of\u00a0multiple global climate models would lead to a\u00a0substantial increase in\u00a0uncertainty and would complicate the\u00a0evaluation of\u00a0the\u00a0effectiveness of\u00a0specific measures in\u00a0the\u00a0management of\u00a0reservoir storage functions.<\/span><\/p>\n The\u00a0defined climate scenario was subsequently used to adjust input hydrological series and to simulate the\u00a0operation of\u00a0selected water supply reservoirs under both current and future climatic conditions. The\u00a0results of\u00a0these simulations provided a\u00a0consistent basis for assessing the\u00a0effectiveness of\u00a0adaptive management as a\u00a0non-structural measure for mitigating the\u00a0impacts of\u00a0climate change on the\u00a0reliability of\u00a0water resources.<\/span><\/p>\n To simulate hydrological conditions in\u00a0the\u00a0catchments of\u00a0the\u00a0selected water supply reservoirs, a\u00a0hydrological model capable of\u00a0representing the\u00a0key processes of\u00a0runoff and water storage within\u00a0the\u00a0catchment, including the\u00a0influence of\u00a0snow cover, was used. The\u00a0main\u00a0tool was the\u00a0application of\u00a0the\u00a0GR4J hydrological model\u00a0[16], supplemented by the\u00a0CemaNeige module\u00a0[17], which enables the\u00a0simulation of\u00a0snow storage and its gradual melt. The\u00a0GR4J model is a\u00a0conceptual model of\u00a0the\u00a0hydrological cycle that transforms daily precipitation and potential evapotranspiration into catchment runoff using four main\u00a0parameters. These parameters represent water retention within\u00a0the\u00a0catchment as well as both the\u00a0fast and slow components of\u00a0runoff, thereby enabling a\u00a0realistic simulation of\u00a0daily flows at the\u00a0reservoir dam profile. The\u00a0CemaNeige module is used to represent snow accumulation and melt, which significantly influences spring flows. The\u00a0catchments were divided into five elevation zones according to altitude in\u00a0order to account for differences in\u00a0snow accumulation and melting conditions between higher and lower elevations. For each day, excess precipitation and snowmelt were calculated for individual zones, with the\u00a0resulting inflow to the\u00a0reservoir being the\u00a0sum of\u00a0contributions from the\u00a0respective elevation zones.<\/span><\/p>\n Model calibration was carried out using natural flow series derived at a\u00a0monthly time step from measured flows at the\u00a0dam profile of\u00a0each reservoir. These series were corrected for the\u00a0effects of\u00a0controlled abstractions, releases, and operational water management, using detailed operational records, primarily for the\u00a0period 1981\u20132024. Daily precipitation and air temperature data were used as input meteorological variables, with runoff also simulated at a\u00a0daily time step. For calibration purposes, daily runoff values were aggregated to a\u00a0monthly time step in\u00a0order to minimise daily variability and enable comparison with aggregated monthly flow series. The\u00a0quality of\u00a0calibration was evaluated using a\u00a0combination of\u00a0standard criteria, namely Kling\u2013Gupta Efficiency (KGE), Nash\u2013Sutcliffe Efficiency (NSE), and PBIAS, which assess the\u00a0agreement between simulated and observed flow values, the\u00a0variability of\u00a0the\u00a0time series, and systematic deviations. The\u00a0values of\u00a0these criteria for individual reservoirs are presented in\u00a0Tab.\u00a01<\/span> and confirm good agreement between simulated and reference flows.<\/span><\/p>\n <\/p>\n For calibration, the KGE criterion was used, confirming very good model performance with values ranging from 80.1 % to 89.5 %. NSE values range from 60.0 % to 80.2 %. The PBIAS criterion falls within the range of very good performance for all catchments. These values, specifically from -0.4 % to 1.6 %,\u00a0<\/span>indicate that the\u00a0model does not exhibit a\u00a0significant tendency to overestimate or underestimate the\u00a0total flow volume. It can\u00a0therefore be concluded that the\u00a0optimised parameters are reliable and suitable for subsequent application.<\/span><\/p>\n After calibration, the\u00a0simulated series for the\u00a02050 and 2100 time horizons were corrected for systematic errors using a\u00a0multiplicative method, which adjusts runoff series proportionally to reflect historical differences between modelled and observed flows. This approach ensures that the\u00a0simulated series retain\u00a0a\u00a0realistic flow dynamics while enabling the\u00a0testing of\u00a0adaptive reservoir management under scenarios of\u00a0progressively worsening hydrological conditions derived from the\u00a0climate model. The\u00a0resulting hydrological series form a\u00a0consistent input for simulations of\u00a0the\u00a0operation of\u00a0selected reservoirs with the\u00a0application of\u00a0adaptive management, enabling a\u00a0comprehensive evaluation of\u00a0the\u00a0effectiveness of\u00a0the\u00a0proposed regulation rules under both current climatic conditions and future conditions corresponding to the\u00a0years 2050 and 2100. This approach ensures that the\u00a0testing of\u00a0adaptive management is based on realistic, climate- and operation-informed scenarios, while maintaining a\u00a0clear interpretation of\u00a0the\u00a0results and enabling unambiguous quantification of\u00a0the\u00a0benefits of\u00a0individual regulatory measures.<\/span><\/p>\n The\u00a0first and fundamental step in\u00a0adaptive management is the\u00a0development of\u00a0rule curves. A\u00a0rule curve represents a\u00a0key tool for controlling reservoir outflow, as it defines the\u00a0relationship between regulated outflow and the\u00a0current storage level of\u00a0the\u00a0reservoir over the\u00a0course of\u00a0the\u00a0year. Within\u00a0the\u00a0storage zone of\u00a0the\u00a0selected reservoirs, three rule curves (DG1, DG2, and DG3) were defined, together with three regulation levels that vertically divide this zone, as shown in\u00a0Fig.\u00a01<\/span><\/em>, into:<\/span><\/p>\n The\u00a0rule curves were defined to ensure the\u00a0required reliability of\u00a0water supply abstractions (Op) and the\u00a0minimum residual flow (MRF) downstream of\u00a0the\u00a0dam, under different climate change time horizons, as shown in\u00a0Tab.\u00a02<\/span><\/em>.<\/span><\/p>\n As follows from Fig.\u00a01<\/span><\/em> and the\u00a0description above, rule curve DG1 in\u00a0this configuration does not serve as an\u00a0active control element for transitions between individual regulation levels. In\u00a0practice, when the\u00a0reservoir level is above DG1, controlled pre-release of\u00a0storage down to the\u00a0DG1\u00a0level can\u00a0be implemented without compromising the\u00a0reliability of\u00a0the\u00a0storage function, for example to enhance flood protection or to optimise hydropower use.<\/span><\/p>\n To derive the\u00a0rule curves, a\u00a0function based on an\u00a0iterative search for minimum reservoir levels was developed. Its objective is to determine the\u00a0lowest safe reservoir level for each month of\u00a0the\u00a0year while ensuring that the\u00a0required reliability is maintained. For each climate scenario, the\u00a0algorithm generates a\u00a0separate rule curve based on the\u00a0specified target values for abstractions (Op) and minimum residual flow (MRF).<\/span><\/p>\n The\u00a0essence of\u00a0adaptive management in\u00a0this algorithm lies in\u00a0its dynamic response to the\u00a0current reservoir storage level. Whereas conventional management assumes fixed abstractions, this model actively adjusts its targets according to the\u00a0prevailing conditions. Based on a\u00a0comparison of\u00a0the\u00a0current storage volume with the\u00a0rule curves, the\u00a0water supply abstraction (Op) is immediately switched between three operating modes:<\/span><\/p>\n For each of\u00a0the\u00a0analysed reservoirs, the\u00a0threshold values Op1 to Op3 were defined within\u00a0a\u00a0range from the\u00a0permitted abstraction specified in\u00a0the\u00a0valid water use permit down to the\u00a0level of\u00a0the\u00a0actual abstractions. This approach made it possible to test the\u00a0adaptive response of\u00a0the\u00a0system across the\u00a0realistic range of\u00a0operational demands of\u00a0the\u00a0given hydraulic structure. A\u00a0similar approach was applied to MRF values, with an\u00a0effort to maintain\u00a0the\u00a0first and second levels at their full values. Reduction to lower values occurred only when the\u00a0storage level fell into the\u00a0third regulation level, thereby maximising the\u00a0protection of\u00a0the\u00a0remaining water reserves in\u00a0the\u00a0reservoir under critical conditions.<\/span><\/p>\n The\u00a0proposed methodological approach is demonstrated in\u00a0detail for the\u00a0management of\u00a0Kl\u00ed\u010dava reservoir. Kl\u00ed\u010dava reservoir is located in\u00a0the\u00a0Vltava River basin\u00a0on the\u00a0Kl\u00ed\u010dava stream, a\u00a0left-bank tributary of\u00a0the\u00a0Berounka River. The\u00a0dam of\u00a0the\u00a0hydraulic structure is situated at river kilometre 3.1 in\u00a0the\u00a0cadastral area of\u00a0the\u00a0municipality of\u00a0Zbe\u010dno in\u00a0the\u00a0Central Bohemian\u00a0Region. The\u00a0division of\u00a0storage zones of\u00a0Kl\u00ed\u010dava reservoir is presented in\u00a0Tab.\u00a03<\/span><\/em>.<\/span><\/p>\n Kl\u00ed\u010dava reservoir serves the\u00a0following functions, listed in\u00a0order of\u00a0priority:<\/p>\n The\u00a0reservoir supplies drinking water to fewer than\u00a050,000 inhabitants and ensures the\u00a0MRF downstream of\u00a0the\u00a0dam. According to \u010cSN 75 2405\u00a0[18], Kl\u00ed\u010dava reservoir is classified as category B in\u00a0terms of\u00a0importance, and the\u00a0required reliability must be ensured with a\u00a0duration of\u00a0at least pt<\/sub> \u2265 98.5%.<\/p>\n For Kl\u00ed\u010dava reservoir, the\u00a0rules for individual regulation levels were defined (Tab.\u00a04<\/em>) such that the\u00a0first level ensures abstractions in\u00a0accordance with the\u00a0water use permit, while the\u00a0third level limits abstraction for the\u00a0water treatment plant to the\u00a0actual average value over the\u00a0last five years of\u00a0operation. The\u00a0second level is defined as a\u00a0transitional stage. In\u00a0the\u00a0first and second levels, the\u00a0MRF is maintained at its full value, while in\u00a0the\u00a0third regulation level it is reduced to half. The\u00a0resulting configuration of\u00a0rule curves and regulation levels is shown in\u00a0Fig.\u00a02<\/em>.<\/p>\n <\/p>\n For clarity, graphs showing the variation of reservoir water levels and water supply abstractions were included for both constant abstraction and MRF without restriction (in accordance with the water use permit) and for adaptive\u00a0management. The\u00a0graphs are presented in\u00a0Fig.\u00a03<\/em> for current climatic conditions, in\u00a0Fig.\u00a04<\/em> for the\u00a02050 time horizon, and in\u00a0Fig.\u00a05<\/em> for the\u00a02100 time horizon. The\u00a0water level and abstraction time series show that adaptive management significantly reduces water level fluctuations, while the\u00a0actual abstraction for the\u00a0water treatment plant (65 L\u00a0\u2219\u00a0s-1) remains secured up to 2100. By contrast, under conventional management, it can\u00a0be observed that in\u00a0several cases the\u00a0water supply dropped well below current demand levels, particularly for more distant climate change time horizons.<\/p>\n The\u00a0differences between management based on constant abstraction according to the\u00a0water use permit and adaptive management are also quantified in\u00a0Tab.\u00a05<\/em>. The\u00a0table presents reliability values (pt<\/sub>) for Kl\u00ed\u010dava reservoir and for other analysed reservoirs: Obecnice, L\u00e1z, Pilsk\u00e1, Vrchlice, and \u0160vihov. Cells in\u00a0which the\u00a0required reliability of\u00a0abstraction is achieved are highlighted. In\u00a0the\u00a0case of\u00a0\u0160vihov reservoir, adaptive management was designed using two regulation levels based on the\u00a0so-called Medium Climate Change Scenario for Water Management in\u00a0the\u00a0Czech Republic\u00a0[14]. The\u00a0management design was developed as part of\u00a0study\u00a0[19], and the\u00a0derived rules for adaptive restriction of\u00a0abstractions were incorporated into the\u00a0reservoir operating rules. For the\u00a0optimisation of\u00a0rule curve storage levels, generated synthetic series with a\u00a0length of\u00a01,000 years were also used, derived for current climate conditions and for the\u00a02041\u20132060 time horizon according to\u00a0[14].<\/p>\n For the\u00a02100 time horizon, adaptive management rules were not included in\u00a0the\u00a0analysis, as their future revision is anticipated.<\/span><\/p>\n The\u00a0results summarised in\u00a0Tab.\u00a05<\/span><\/em> demonstrate the\u00a0effectiveness of\u00a0the\u00a0proposed adaptive management, which was tested on a\u00a0set of\u00a0selected water supply reservoirs. In\u00a0all cases, timely restriction of\u00a0abstractions makes it possible to ensure the\u00a0required reliability of\u00a0water supply abstractions for all considered climate change horizons. The\u00a0simulations further show that the\u00a0benefits of\u00a0adaptive management increase with longer climate change horizons. While differences between conventional and adaptive management are relatively small under current hydrological conditions, under scenarios for 2050 and especially 2100, the\u00a0adaptive approach becomes a\u00a0key tool for maintaining an\u00a0acceptable level of\u00a0reliability of\u00a0water supply abstractions. This trend confirms that the\u00a0importance of\u00a0non-structural measures will likely increase in\u00a0the\u00a0future. It should be emphasised, however, that the\u00a0simulation results are subject to certain\u00a0uncertainties arising from the\u00a0climate and hydrological models used. In\u00a0this study, a\u00a0single representative climate scenario was applied for methodological reasons, enabling a\u00a0consistent interpretation of\u00a0the\u00a0behaviour of\u00a0the\u00a0proposed management system. In\u00a0the\u00a0future, it would be appropriate to consider a\u00a0broader set of\u00a0climate scenarios and to carry out a\u00a0robustness analysis of\u00a0the\u00a0proposed rules with respect to uncertainties in\u00a0future climate development.<\/span><\/p>\n The results obtained indicate that adaptive management represents a key and essential tool for the future operation of water supply reservoirs under climate change conditions. It enables the identification of an operationally acceptable compromise between user demands and the actual capacity of water resources, enhances the operational safety of hydraulic structures, and contributes to the long-term sustainability of water management. At the same time, adaptive management has a positive impact on water quality in reservoirs, as limiting deep and prolonged declines in water levels contributes to more stable thermal and quality conditions within the reservoir. This reduces the risk of eutrophication processes and deterioration of raw water quality, which are expected\u00a0<\/span>to occur more frequently under a\u00a0warming climate. The\u00a0proposed approach can\u00a0also be regarded as an\u00a0effective non-structural adaptation measure that is fully compatible with existing legislative frameworks and provides a\u00a0practical basis for the\u00a0modification of\u00a0reservoir operating rules in\u00a0the\u00a0Czech Republic. At the\u00a0same time, it is necessary to prepare new reservoirs and expand storage capacities, particularly in\u00a0deficit areas, in\u00a0order to ensure a\u00a0sufficient long-term water supply for future abstractions and increased variability of\u00a0hydrological conditions resulting from climate change.<\/span><\/p>\n The\u00a0article was supported by the\u00a0Technology Agency of\u00a0the\u00a0Czech Republic under research project No. SS02030027, \u201cWater systems and water management in\u00a0the\u00a0Czech Republic under climate change conditions (Centre Water)\u201d, carried out in\u00a0the\u00a0period 2020\u20132026.<\/span><\/span><\/em><\/p>\n The\u00a0Czech version of\u00a0this article was peer-reviewed, the\u00a0English version was translated from the\u00a0Czech original by Environmental Translation Ltd.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":" This article presents a methodology for the adaptive management of water reservoirs designed to ensure a reliable water supply under condi-tions of hydrological drought and climate change. The proposed approach combines hydrological modelling, climate change scenarios, and the optimisation of rule curves with regulation levels. The management system allows for flexible restrictions on water abstractions and the adjustment of minimum residual flows depending on the current state of the reservoir. A pilot application of the methodology was carried out on selected Czech reservoirs (\u0160vihov, Kl\u00ed\u010dava, \u017dlutice, Obecnice, Pilsk\u00e1, L\u00e1z, Vrchlice) under current climate conditions and future scenarios for 2050 and 2100. <\/p>\n","protected":false},"author":8,"featured_media":39132,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[94,86,93],"tags":[4153,96,113,4154,4155,95],"coauthors":[702,4111],"class_list":["post-39134","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-current-issue","category-hydraulics-hydrology-and-hydrogeology","category-two-articles","tag-adaptive-management","tag-climate-change","tag-hydrological-drought","tag-rule-curve","tag-supply-reliability","tag-water-reservoir"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/posts\/39134","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/comments?post=39134"}],"version-history":[{"count":5,"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/posts\/39134\/revisions"}],"predecessor-version":[{"id":39199,"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/posts\/39134\/revisions\/39199"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/media\/39132"}],"wp:attachment":[{"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/media?parent=39134"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/categories?post=39134"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/tags?post=39134"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/coauthors?post=39134"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}CURRENT STATE OF KNOWLEDGE<\/h2>\n
METHODOLOGY<\/h2>\n
Climatic conditions<\/h3>\n
Hydrological model<\/h3>\n
Tab.\u00a01. Performance criteria for hydrological model calibration for the\u00a0catchments of\u00a0the\u00a0selected reservoirs<\/h5>\n
![\"\"](\"https:\/\/www.vtei.cz\/wp-content\/uploads\/2026\/06\/Fosumpaur-tab-1-3.jpg\")
<\/a>\nMethodology of\u00a0adaptive management<\/h3>\n
\n
<\/a><\/h6>\nFig. 1. Diagram of\u00a0rule curves and operation levels for reducing water supply withdrawals and minimum residual flow<\/h6>\n
Tab.\u00a02. Conditions for defining rule curves<\/h5>\n
<\/a>\n\n
Evaluation of\u00a0the\u00a0effectiveness of\u00a0adaptive management<\/h3>\n
Tab. 3. Division of storage zones in Kl\u00ed\u010dava reservoir<\/h5>\n
<\/a>\n
\n\n
\n
\n<\/li>\n
\n
\n<\/li>\n
\n
\n<\/li>\nTab. 4. Operating levels with restrictions on water supply withdrawals (Op) and minimum residual flow (MZP)<\/h5>\n
<\/a>\n<\/a><\/h6>\nFig. 2. Rule curves (DG) and operation levels for Kl\u00ed\u010dava reservoir<\/h6>\n
<\/a><\/h6>\nFig. 3. Comparison of\u00a0water levels and water supply to the\u00a0treatment plant under constant withdrawal and adaptive reservoir management of Kl\u00ed\u010dava reservoir under\u00a0current climate conditions<\/h6>\n
<\/a><\/h6>\nFig. 4. Comparison of\u00a0water levels and water supply to the\u00a0treatment plant under constant withdrawal and adaptive reservoir management of Kl\u00ed\u010dava reservoir under\u00a02050 climate conditions<\/h6>\n
<\/a><\/h6>\nFig. 5. Comparison of\u00a0water levels and water supply to the\u00a0treatment plant under constant withdrawal and adaptive reservoir management of Kl\u00ed\u010dava reservoir under\u00a02100 climate conditions<\/h6>\n
Tab. 5. Comparison of water supply reliability under constant withdrawal and minimum residual flow according to water use permits and under adaptive management for the studied reservoirs<\/h5>\n
<\/a>\nCONCLUSION<\/h2>\n
Acknowledgements<\/h3>\n