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In the context of climate change, more severe and extended periods of low flows are expected, which will affect the quantity and quality of water sources. Evapotranspiration is an important process in the water cycle and is particularly significant during low-flow events. Therefore, it is important to study the effects of uncertainty in evapotranspiration modelling in the hydroclimatic modelling chain to understand the impacts of climate change on the water availability. As evapotranspiration is a rather hard and expensive process to measure, formulas are used to determine potential evapotranspiration (PET), which is the maximum water quantity that can be evaporated and transpired without any limiting factors. The objective is to determine the contribution of PET formulas to uncertainty in the full modelling chain in the context of climate change. Eleven simple PET formulas that only require minimum and maximum temperatures as well as the latitude are used. These formulas are applied to 2080 watersheds in North America (235 in Canada, 1825 in United States, and 20 in Mexico). As PET is directly related to climatic conditions, studying a large quantity of watersheds that cover many climatic zones increases the robustness of the conclusions. Three global hydrological models (GR4J, HMETS and Mohyse) calibrated with the Nash-Sutcliffe criterion are employed for the hydrologic modelling aspect of the work. Subsequently, the study of transferability under future climate is conducted with simulations from ten climate models and two different greenhouse gas emission scenarios. These simulations outputs (precipitations and temperatures) are post processed with two bias correction methods and are then introduced into the three hydrological models. The PET contribution in the global modelling chain in climate change and its uncertainty are estimated with different analyses such as variance decomposition. The analysis of different low-flow indices allows studying the climate change trends as expressed through the PET formulas. For instance, low-flow values over a period of several consecutive days for a certain recurrence period are compared to see if changes in the PET affect low-flows. Results show that the PET increases and the low-flow decreases are different according to climatic zones. Despite a great variability between the different formulas, results show similar trends under climate change. This project also shows that some specific formulas do not adapt well to future climate. This project results in a better comprehension and an increase in knowledge regarding the impacts of the PET formula choice in hydroclimatic modelling chain under climate change. The conclusions can be used for water resources management to identify adequate adaptation measures, such as preventing the drying up of water resources during low-flow periods. [ABSTRACT FROM AUTHOR]

Assessment of the impacts of climate change on hydrological regime is important for sustainable water resources management. The objective of this study is to assess the impacts of future climate changes on the hydrological regime of the headwater catchment of the Vistucky Creek (area 9.8 km2) in south-western Slovakia. Changes in climatic characteristics (i.e., precipitation and air temperature) for periods 2022-2060 and 2062-2100 were prepared by two regional climate models KNMI and MPI using the A1B emission scenario (average related to fossil carbon production). Both climatic scenarios assume increase in the air temperature and precipitation (higher in winter than in summer). A lumped conceptual rainfall-runoff model (the HBV-based TUW model) was used to simulate the catchment hydrological behaviour. The TUW model was calibrated for the reference period of 1982 – 2008. The calibration of the model was performed 50 times with a differential evolution algorithm. After obtaining the collection of the 50 parameter sets, the best set (in terms of Nash-Sutcliffe efficiency and the volume error) was chosen. This set of model parameters was used for the simulation of long-term mean monthly runoff for the three periods (i.e., 1982-2008, 2022-2060, and 2062-2100).The results show that changes in the long-term runoff seasonality and extremality of hydrological cycle could be expected in the future if the climate changes as the scenarios assume. The runoff should increase in autumn and winter months (i.e., from September to February) and decrease in spring and summer months (i.e, from April to August) compared to the reference period. Peakflows should increase in period 2062-2100 while discharge minima should slightly decrease (only for the climatic data from the KNMI model). It indicates possible increase in flow extremality. Catchment water storage as expressed by the soil moisture index and baseflow should decrease in period 2062-2100, especially according to climatic data from the KNMI model. Our contribution will discuss these changes in hydrological regime in the climate change context.AcknowledgmentThis work was supported by the Slovak Research and Development Agency under the contract No. APVV-15-0497. [ABSTRACT FROM AUTHOR]

Climate change jeopardizes the future of hydropower across the world. Precipitation patterns evolve, glacier retreat affects sedimentation, and rising temperatures perturb both the water cycle and the energy-price seasonality. The energy sector also faces an energy turnaround. The growing penetration of intermittent wind and solar energy increases supply variability, thus price volatility. These trends raise concerns about the future profitability of traditional hydropower. This work quantifies these impacts with an integrated, transferable, and parsimonious model. It integrates a semi-distributed hydrological with hydropower management models to translate climate change and energy scenarios into future energy generation and revenue. We simulated nine future streamflow scenarios for an Italian and a Swiss case study. These inputs fueled a hydropower management model, which maximizes revenue accordingly to five Italian and twenty-eight Swiss electricity prices scenarios. The simulations couple both types of scenario for the period 2016-2045. This time horizon especially matters for current decisions in climate and energy policy. Results show that variations of climate regime adversely influence the hydroelectric production. Climate change will modify the seasonality of inflows and volumes that are exploitable for hydropower generation. However, smart hydropower management could mitigate revenue losses. This research represents a toolkit for dam operators and decision makers to assess future generation capacity in a warming climate. Key words: Climate Change, Hydropower, Electricity Market, Water-Energy Nexus, Modelling [ABSTRACT FROM AUTHOR]

This study presents the first insights into the intensifying impact of global warming on extreme hydrological shifts between wet and dry conditions at the sub-seasonal to seasonal scale. For instance, the flood in England during the summer of 2007 was followed by heavy drought conditions, and a switch took place in the recent past from extreme drought to severe flooding in California. Most recently, the 2018 flood to drought transition in Japan brought on one of the most intense heatwaves the country has ever faced. These are just a few real-world examples. Considering the interconnected nature of the processes governing the increases in wet and dry events, we introduce a new index called 'Event to event variability (E2E)' as a proxy of the hydrological cycle, taking the aforementioned shifts in wet to dry (or dry to wet) transition into account. Based on multi-model large ensemble climate simulations, we assessed the impact of half a degree of additional warming from 1.5°C to 2°C for the global mean temperature, reflecting the warming targets of the Paris agreement of 2015 that were adopted at the 21st Conference of the Parties (COP) of the United Nations Framework Convention on Climate Change (UNFCC). Our results show that for an additional 0.5°C warming, mean intensification of the wet-dry (or dry-wet) transition will be significant on a global scale. The E2E index was further utilized to investigate the extreme conditions of said intensification, which showed extremes will increase 10 times compared to the mean state intensification. We found that event-to-event variability increases with warming for Western North America, Japan, and the UK, exhibiting intensification in both wet and dry conditions, which is potentially attributable to the increased occurrence of the aforementioned extreme events. We believe that our study will provide a new perspective into hydroclimatic stress under the future climate, in particular, for the additional 0.5°C warming and the importance of adhering to the Paris Agreement. [ABSTRACT FROM AUTHOR]

High quality climate data at a high spatial and temporal resolution are essential to develop and provide adequate climate services for Africa. Rainfall characteristics such as the number of dry and wet days, extreme rainfall or the length of rainy seasons are derived from regional climate data to create climate service products, e.g. for the agricultural sector. A common method to produce regional climate data is to dynamically downscale global climate change simulations by means of regional climate models (RCMs). These RCMs have to be able to simulate realistically the hydrological cycle in the different African climate zones including the movement of the intertropical convergence zone (ITCZ) over the continent. Deficiencies in the representation of the sea surface temperatures (SSTs) in global ocean models due to a too coarse spatial resolution and missing atmosphere-ocean interactions in RCMs contribute to the rainfall bias over regions affected by the moisture transport from the ocean. The application of a regionally coupled atmosphere-ocean model may reduce the rainfall biases over the African continent.In our work, we analyze the potential impact of the atmosphere-ocean coupling on the simulation of rainfall characteristics over Africa and identify those regions providing an added value using the regionally coupled atmosphere-ocean model ROM. For this purpose, we downscaled the ERA-Interim dataset and the MPI-ESM-LR historical simulation for present climate and the MPI-ESM-LR RCP8.5 simulation for future climate with ROM. Each simulation was downscaled for a time slice of at least 30 years at a spatial resolution of 25 x 25 km² for the whole African continent and the West Atlantic Ocean. In detail, we will show the potential impact of the atmosphere-ocean coupling on droughts and extreme rainfall using different rainfall indices such as consecutive dry days (CDDs), consecutive wet days (CWDs) and very wet days (R95p). Moreover, the effect of the atmosphere-ocean coupling on rainy season parameters will also be analyzed. Finally, a comparison between the bandwidths of the rainfall parameters derived from the uncoupled/coupled projections and the bandwidths of the parameters from the uncoupled CORDEX-CORE Africa ensemble will be shown. [ABSTRACT FROM AUTHOR]