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Multi-model ensembles have become a standard tool for assessing global climate change impacts. Interpretation of such ensembles is complicated because each model group has a different modeling concept and framework. For example, global scale land surface, water and vegetation models have been widely applied to understand the complex hydrological cycle of the Earth and to assess associated past and future changes. Additionally to this purpose, land surface models assess energy and biogeochemical cycles while vegetation models assess vegetation and carbon cycles. Therefore, all these models differ with respect to the specific processes of the hydrological cycle included in their structure. In this study, we demonstrate how the similarities and differences between models can be better understood and illustrated by using a standard representation of the main model features. We analyze twelve models from the global water sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) phase 2b: six land surface models (LSMs), five global hydrological models (GHMs) and one dynamic global vegetation model (DGVM). The majority of the models are run with a daily temporal resolution and with a spatial resolution of 0.5°. Part of these models include a reservoir scheme and water use sectors. The heuristic mappings of the models are designed to ensure the opportunity to choose a model at the initial stage of the analysis, based on the most important qualities, relationships and characteristics, which provide users with significant time saving. Therefore, the review study will provide the basis for: (i) achieving further model (inter)comparison; (ii) selecting the right model(s) output(s) for specific applications; and (iii) assessing the similarities and differences among the models. The models characteristics will be presented in three levels of complexity allowing to reach a large audience. The target audience includes the modeling community, the stakeholder community, and the general public interested in understanding large-scale models, simulating climate change and its impacts. Additionally, stakeholder insights, gathered mostly in Eastern Europe and West Africa, have been considered in the study design. Stakeholders were identified according to their need for climate-impact information provided within the ISIMIP framework and included academics, government officials, employees working in international organizations, NGOs, consultancies, and private companies. In conclusion, the presentation describes the study approach and preliminary results, with particular emphasis on the standard model diagram, differences between the models, and the stakeholder engagement. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau is an important water source in Asia. As the "Third Pole" of the Earth, the Tibetan Plateau has significant dynamic and thermal effects on East Asian climate patterns, the Asian monsoon process and atmospheric circulation in the Northern Hemisphere. However, little systematic knowledge is available regarding the changing climate system of the Tibetan Plateau and the mechanisms underlying its impact on third pole region (Tibetan Plateau and the nearby surrounding region). This study was based on "water-cryosphere-atmosphere-biology" multi-sphere interactions, primarily considering global climate change in relation to the Tibetan Plateau –third pole climate system and its mechanisms. This study also analyzed the Tibetan Plateau to clarify global climate change by considering multi-sphere energy and water processes. Additionally, the impacts of climate change in the third pole and the associated impact mechanisms were revealed, and changes in water cycle processes and water conversion mechanisms were studied. The changes in surface thermal anomalies, vegetation, local circulation and the atmospheric heat source on the Tibetan Plateau were studied, specifically, their effects on the East Asian monsoon and energy balance mechanisms. Additionally, the relationships between heating mechanisms and monsoon changes were explored. The research plan and initial progress for the land-atmospheric interaction over the Pan-Third Pole region is shown in the last. [ABSTRACT FROM AUTHOR]

The Pyrenees range is a transboundary region shared by Spain, France and Andorre. As many other mountain regions, it is exceedntary in water resources that are used in a much larger area that includes important urban concentrations and productive rural areas. This territory is particularly vulnerable to the consequences of climate change. The PIRAGUA project, funded by FEDER through the POCTEFA Programme of the EU, addresses the assessment of the hydrological cycle of the Pyrenees in the context of climate change. The goals of the project are to unify and homogenise the existing information, prospect future scenarios, develop indicators of change, and propose adaptation strategies with impact on the territory, with the ultimate goal of supporting investment aimed at adapting to climate change in relation to water resources. Thus, the project evaluates the components of the hydrological cycle and the water resources of the Pyrenees range in the recent past (1985–2015), and in future scenarios (2030–2050). In addition, it will develop seven case studies about adaptation strategies at the local and regional scales, focusing on different socio-economic sectors, including hydropower production; sensitive headwater ecosystems; water and forests; irrigation agriculture; extreme events; tourism and areas of high ecological value; and multi-sector analysis, including the water-energy connection. [ABSTRACT FROM AUTHOR]

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]

The hydrological cycle is a fundamental component of the Earth’s climate system. Modelingthe time response of this cycle and the implied physical processes challenges thegeneral circulation models (GCM) used to study the climate system and to projectfuture climate. Water stable isotopes (H216O, H218O and HD16O) are integratedtracers of climate processes occurring in various branches of the hydrological cycle.Changes of the isotopic composition, which can be measured in various naturalclimate archives, have been used, for example, to reconstruct past temperatureschanges at high resolution or to study the past dynamics of the monsoon. However, thequantitative translations of isotope signals recorded in the natural archives to climatevariables is still challenging. The explicit modeling of these isotopes in GCMs isone way to improve our understanding of the mechanisms controlling the waterisotopes distribution link with the variations of climate and to evaluate the modelperformance. We present here the results, under pre-industrial (PI) and mid-Holocene (6k) conditions,of the new isotope-enhanced version of the fully coupled Earth system model MPI-ESM,called hereafter MPI-ESM-wiso. For that, the water isotopes have been implementedin all the components of the model (ECHAM6: atmosphere, JSBACH: dynamicvegetation, MPIOM: ocean/sea-ice). The related isotope masses of H216O, H218Oand HD16O are exchanged between the atmosphere and the ocean via the couplerOASIS3. The mid-Holocene, one of the PMIP4-CMIP6 entry cards to evaluate theperformance of the coupled GCMs [1], provides the opportunity to evaluate the modelresponse to changes in the seasonal and latitudinal distribution of insolation induced bydifferent orbital forcing conditions. Especially, this period is characterized by enhancedAfrican and Indian monsoons with depleted isotopic contents of precipitation. Inaddition to classical variables (temperatures, precipitation amount...), we evaluatethe isotopic composition of precipitation, water vapor, ocean, etc. simulated byMPI-ESM-wiso against available observations. We also investigate the variability of theisotope-to-climate gradients (spatial and temporal) during and between the PI and 6kperiods. This work will be an important contribution to the Paleoclimate ModellingIntercomparison Project. Indeed, the models with an explicit water stable isotope diagnosticsmake it possible to perform direct comparisons, at different time periods, with environmentalrecords and to reduce the uncertainties resulting from the interpretation of these records interms of climate signals in model-data comparisons. The project is part of the PalModinitiative ("Paleo Modelling: A national paleo climate modelling initiative"), funded by theGerman Federal Ministry of Education and Science (BMBF). [1] Kageyama et al., Geosci. Model Dev., 11, 1033-1057, 2018. [ABSTRACT FROM AUTHOR]

Many recent studies indicate climate change as a phenomenon that can potentially alter the water cycle, also implying new challenges in drought risk management. Impacts of drought are difficult to study, as this phenomenon is usually characterized by multiannual evolution scales, meaning that few occurrences may take place in a climatologic period of 30-years. Hence, it is of key importance to assess the quality of Regional climate models (RCMs), which are commonly used for assessing future impacts of climate change on hydrological events. To this end, a common approach consists in evaluating models' capability to simulate historic climate by comparing models' simulations to observational gridded datasets, available at global or continental spatial scales. Regardless of the specific methods used to assess the differences between simulated and observed data, a main limitation in this approach is that the considered spatial resolution is too coarse for reliable climate change impact studies at hydrologically relevant scales, especially in areas of complex topography. From this point of view, large scale observational gridded datasets are of poor applicability, since they are built upon low-density hydro-meteorological networks.The Coordinated Regional Climate Downscaling Experiment (CORDEX) initiative provides climate data simulated by RCMs developed by several research centers all over the world. In the present study we use climate data for the Euro-Mediterranean area, known as EURO-CORDEX (www.euro-cordex.net). In particular, simulations for an historic reference period (baseline) and for future projections up to 2100, with a 12.5 km grid resolution, are available for four different greenhouse gas concentration trajectories (Representative Concentration Pathways). We propose a statistical methodological framework to assess the quality of the EURO-CORDEX RCMs with respect to their ability to simulate historic climate by a comparison with high-density and high-quality ground-based observational datasets. In particular, the focus of this study is on observed thermometric and pluviometric regimes in Southern Italy at time scales from monthly to annual, which are particularly useful for drought analyses. To this aim, performances indicators relevant for assessing the accuracy of assessments are also considered. The proposed methodology is applied to Sicily and Calabria regions, where long historical precipitation and temperature series have been recorded by the ground-based networks operated by the formerly Regional Hydrographic Offices, whose density is considerably greater than observational gridded datasets available at European level, such as E-OBS. Results show that the proposed methodology is capable to highlight clearly skills and weaknesses of different RCMs and can help to properly select the models for climate projections in the investigated areas, with respect to the examined hydrologic processes. [ABSTRACT FROM AUTHOR]

Alterations in global/regional climate conditions lead to changes in the hydrological cycle due to close inter-relations with the energy budget. In this perspective, evapotranspiration (ET) is the direct and most important link between the energy budget and the hydrological cycle since latent heat (energy flux) is equivalent to ET (water mass flux). Regarding the anthropogenic use and management of water resources, freshwater availability in rivers and lakes plays a crucial role for water supply, irrigation farming, and hydropower production for instance. In this perspective, hydro-systems with scarce water availability are particularly prone to climate change since water scarcity may be aggravated by decreased precipitation and/or increased ET.Here, we have analyzed the Lake Malawi Basin situated in semi-humid East Africa, sharing borders with Malawi, Tanzania, and Mozambique, regarding the susceptibility to climate change. Lake Malawi is the 9th largest lake on Earth (is in terms of water volume) and has only one outlet in the south, the Shire River which is intensively used for hydropower production. The installed electricity capacity and generation of hydropower accounts for 80.2 % and 98 %, respectively, of the Malawi's total electrical grid power generation.Analyzing data for the last five decades, it shows that annual inflow into the lake (~620 m³/s) is significantly compared to the annual outflow to the Shire River (~490 m³/s). This difference between in- and outflow is due to lake evaporation that exceeds average rainfall in the basin (~1,400 mm) by 20 to 30 %. In this perspective, water resources and electricity production are endangered by two phenomena: (1) Intra-annual variability of rainfall and ET may strongly affect discharge in the Shire River, which is only a small fraction of the basins´ overall water budget, meaning that small changes in rainfall or ET will lead to larger relative changes in Shire River discharge. Moreover, during drought years with low rainfall rates, lake evaporation will be on particular high levels, instead. (2) Global/regional warming will impact both the catchment- and lake water balances. Although trends in catchment rainfall over the last decades are not consistent and/or significant (yet), there is strong evidence that lake evaporation has already increased and will further increase in the future.Applying a catchment hydrology- and lake water balance model including sensitivity- and uncertainty analyses, we (i) show first results regarding changes in the water balance of Lake Malawi under recent and future climate change, and (ii) discuss the effects of these changes on streamflow in the Shire River and its consequences for water availability and (future) hydropower production. The results show that the water balance of the Lake Malawi Basin is particular sensitive to climate change, and similar conditions might occur in other semi-humid catchments in the tropics, too. [ABSTRACT FROM AUTHOR]

Changes to the snowmelt regime are of critical importance to the hydrological cycle in many regions of the world. Recently Musselman et al (2017, Nature Climate Change) presented evidence to show that snowmelt rates are slower when temperatures are warmer in the western USA, while Wu et al's (2018, Geophysical Research Letters) study of the northern hemisphere suggested slower snowmelt rates for warmer temperatures in many places, but also faster snowmelt rates in regions with deeper snowpack. Musselman et al (2017) suggested that the reason for slower snowmelt might be that warming led to smaller snowpacks, which could be completely melted earlier in the warm season, on days when available energy was relatively low, and, crucially, not leaving any water to melt in late spring or summer, when incoming energy is higher. Wu et al (2018) suggested that the reason for faster snowmelt in deeper snowpacks (cf shallow snowpacks) might be the extra energy available for melt in late spring or early summer. At this stage the explanations for impact of warming on snowmelt rates remain ad hoc, without a unified explanation of the phenomena.Using a generalisation of Woods (2009, Advances in Water Resources), we present a simple theoretical explanation for the varying responses of melt rate to warming. The theory predicts that warming will lead to (i) faster snowmelt in very cold climates (ii) slower snowmelt in intermediate climates (iii) faster snowmelt in warm climates. The mechanisms are consistent with the explanations proposed by Musselman et al (2017) and Wu et al (2018). According to this theory, the dimensionless temperatures which define transitions from faster to slower and back to faster snowmelt are dependent on the precipitation regime: if the precipitation rate is higher, then the transition is predicted to occur at a higher (dimensionless) temperature.With this theory, it is possible to provide coherent first order explanations for the variety of snowmelt responses to warming, which may provide a useful organising principle for further data-based investigations into this issue, especially across large climate ranges. [ABSTRACT FROM AUTHOR]

In this study we investigate the effect of different downscaling methods on the hydrologic cycle of a Mediterranean catchment in Sardinia (Italy) that is prone to extreme flooding. To this aim, we use an ensemble of four combinations of GCM - RCM projections (see Deidda et al., 2013, and Langousis et al., 2016), statistically downscaled using: a) the parametric statistical scheme of Mamalakis et al. (2017), and b) its widely used non-parametric variant based on empirically derived Q-Q (quantile-quantile) correction relationships. In particular, we analyze differences in the climate projections of the available downscaled climate model outputs, considering or not the elevation factor (in the latter case by re-projecting outputs at the mean elevation of the basin). We further quantify the impact of these differences on modeled hydrologic variables. The hydrologic impact of climate change is evaluated during five 30-year periods (1951-1980, 1981-2010, 2011-2040, 2041-2070, 2071-2100), focusing on a set of variables that characterize the water balance, including precipitation, air temperature, discharge, leakage, and actual evapotranspiration. The response of the basin is quantified at the outlet and also at 33 subcatchments, analyzing the influence of features such as the area and mean elevation of the subcatchments. The results show that the choice of climate model and downscaling method leads to variations in the simulated hydrologic response of the basin, and that this effect varies also by subwatershed. Notwithstanding these differences, the reduction in precipitation predicted by the climate models is more pronounced as the watershed area increases, and as the altitude decreases. References:Deidda, R., M. Marrocu, G. Caroletti, G. Pusceddu, A. Langousis, V. Lucarini, M. Puliga, and A. Speranza (2013). Regional climate models' performance in representing precipitation and temperature over selected Mediterranean areas, Hydrol. Earth Syst. Sci., 17(12), 5041-5059, doi:10.5194/hess-17-5041-2013.Langousis, A., A. Mamalakis, R. Deidda and M. Marrocu (2016). Assessing the relative effectiveness of statistical downscaling and distribution mapping in reproducing rainfall statistics based on climate model results, Water Resour. Res., 52, doi:10.1002/2015WR017556.Mamalakis, A., A. Langousis, R. Deidda, and M. Marrocu (2017). A parametric approach for simultaneous bias correction and high-resolution downscaling of climate model rainfall, Water Resour. Res., 53, doi:10.1002/2016WR019578. [ABSTRACT FROM AUTHOR]

While future climate simulations with Regional Climate models are becoming increasingly common, there is increased interest about the effects of climate change on the hydrological cycle at small spatial scales.We present a new hydrological RCP8.5 scenario simulation over Italy using the high resolution CHyM model, driven by the RegCM Regional Climate Model at 12km. The simulation spans the period 1976-2100, with a resolution ranging from 300 to 900m (depending on the region). Future changes both in terms of mean and extreme discharges under the RCP8.5 climate scenario are presented and discussed.Average discharges show a shift towards increased fall and winter flows by the end of the century, especially for the northern regions fed by the Alpine mountain range. The patterns follow changes in the average precipitation provided by the driving RCM.Several flood proxy metrics are analysed, including mean annual peak discharge, peak over threshold events and 100-year return period projected flow (Q100).In particular, the Q100 metric shows a strong increase in future extreme discharge, on average doubling the intensity of such events by the end of the century. Extreme flow changes are uniform across most of the Italian territory, but are particularly marked over the eastern coast of central Italy, where Q100 change values can exceed +200%. [ABSTRACT FROM AUTHOR]

Vegetation plays a major role in the water cycle through transpiration. In a global sense, evapotranspiration accounts for two thirds of the precipitation over the continents, with higher figures in arid than humid climates. Vegetation functional types (i.e. tree, shrub, grass) differ in their transpiration rate and resilience to water and climatic conditions, from which a connection between the vegetation distribution and the water cycle emanates. Hence, the interest of hydrologists in understanding the reasons why vegetation distributes differently across watersheds of diverse climates. This understanding is of key importance in the assessment of the effects of global change on the water cycle as vegetation is expected to vary due to climate change; therefore, we need models that can generate vegetation distributions under changing climatic conditions.Plant optimization theories predict vegetation distributions based on the hypothesis that vegetation optimizes a state variable, e.g. productivity or water stress. The applicability of these theories is constrained to arid and semi-arid climates, in which water availability is the limiting factor for plant development. Furthermore, they usually require a simple hydrological model to quantify the required water fluxes. In this context, machine learning arises as a powerful set of techniques to apply for predicting vegetation distributions in ecosystems where other climatic, topographic or edaphic descriptors might be those defining the spatial distribution of vegetation. This set of techniques does not require assuming a hypothesis as optimization theories do; instead, they can identify from a list of predictors those of higher importance in the vegetation distribution.In this research, we apply machine learning for predicting the spatial distribution of vegetation functional types in two different climates of the Iberian Peninsula: Oceanic (Cfb) and warm-summer Mediterranean (Csb). As predictive variables we use descriptors of the hydrology, edaphology and morphology obtained from meteorological records, soil data bases and a digital terrain model. The target variable is the vegetation functional type obtained by classification of Landsat images. The result is a model that predicts the climax vegetation of a point in space characterised by a set of descriptors; applied in a catchment scale, it predicts a map of potential vegetation to be used as input in a hydrological model.The fitted model could predict climax vegetation distributions for climate change scenarios, which in turn would feed a hydrological model to appraise the combined impacts of vegetation and climate change in the water cycle.The authors would like to thank "Agencia Estatal de Investigación (AEI)" from the Spanish Ministry of Economy, Industry and Competitiveness, and the European Regional Development Fund (ERDF) for the funding provided through grant BIA2016-78397-P (AEI/FEDER, UE) for the development of this work. [ABSTRACT FROM AUTHOR]

Aim of this work is the assessment of the individual and combined impacts of land use land cover change (LULC) and climate change (CC) on hydrologic processes, especially over regions like India which are affected by extensive land use land cover change. In this study, we quantify the contributions of LULC and CC on hydrological changes over the Indian subcontinent through a scenario-based approach, with Community Land Model version 4.5 (CLM4.5) model runs from 1981-2017. The approach involves four simulation scenarios: (i) the first scenario considers the ideal conditions without any LULC changes or CC (LULC is fixed and the atmospheric forcings for 1981-1990 are repeated in the decades afterwards); (ii) the second scenario considered only the impact of CC; (iii) the third scenario considered only the effect of LULC by updating the LULC every 10 years, and (iv) the fourth scenario considered the combined impact of LULC and CC. The results for the scenarios are analysed for various Koeppen- Geiger climate zones over India. Based on the results, it is observed that the LULC changes cause an overall decrease in the evapotranspiration (ET) by 2.64 %, while the available energy remains unaffected. On the other hand, CC caused an increase in the ET and available energy by 6.08 % and 0.63 % respectively. Among the LULC transitions, deforestation and urbanization are found to be the major causes for hydrological changes over the decades; their impact much smaller when compared to the impact of CC, however. The combined effect of LULC and CC also shows an increase in ET and available energy by 2.44 % and 0.97 % respectively. However, this increase in ET is less as compared to the impact of CC only, which may be due to the averaging-out of the opposite effects of LULC and CC on the water and energy cycles. CC has a greater impact on the hydrology over India than LULC, over the considered period 1981-2017. The outcome of this study is helpful in providing an in-depth understanding of the distinct contributions of LULC and CC on the hydrological processes in the tropical regions. Keywords: Climate change, Landuse Landcover, Impact assessment, CLM4.5, India. [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]

Tropical areas are currently experiencing rapid environmental change due to the combined effects of climate change and human impact on the landscape. Climate variations in Southeast Asia play a key role in the global hydrological cycle, but past changes in the Asian monsoon system and its effects on local ecosystems are poorly constrained due to a shortage of well-dated palaeoenvironmental records that can provide a longer-term perspective on environmental change. This study investigates sediment cores from Tasik (Lake) Chini situated on the Malaysian Peninsular and provides the first lacustrine record of palaeoenvironmental change from the area. The flood pulse wetland is one of the few lake basins in the lowlands of this region and is of great ecological importance, contributing to the site's UNESCO designation. Tasik Chini comprises twelve interconnected basins with a hydrology dependent on monsoonal rainfall, therefore the lake is highly sensitive to variations in hydroclimate. Here, we provide new information on past environmental changes at Tasik Chini using the carbon isotope composition (δ13Corg) and Rock-Eval pyrolysis of sedimentary organic matter, diatom assemblage, elemental analysis, and chlorophyll and carotenoid pigments. An established chronology based on 14C and 210Pb dating shows that the cores span the last ca. 4.8 ka, covering the lakes inception as a permanent water body as well as a transition to higher sedimentation rates since the late 19th century. The multi-proxy record indicates large changes in organic matter production and preservation, hydrology, and water quality over the lake's history with the most pronounced variations occurring during the past 150 years, especially since the 1950s. Together, these proxies demonstrate major shifts in the Tasik Chini ecosystem that were most likely driven by a dynamic monsoonal system during the Middle to Late Holocene, and more recently initiated by anthropogenic catchment land use changes. This rare wetland record offers the potential to better understand past hydroclimate development in Southeast Asia and provide context for the human impact-related changes that have occurred, and are likely to continue, in this rapidly developing region. [ABSTRACT FROM AUTHOR]

The Indonesian throughflow (ITF), going through the maritime continent and providing the only low-latitude connection of the global ocean circulation system, is important to physical and biogeochemistry processes of the ocean as well as to climate variability. Seasonal variation of sea surface salinity (SSS) in the maritime continent is known to affect the vertical structure and transports of the ITF. However, the sources of the freshwaters that influence the regional SSS variation are poorly understood in large part due to the paucity of in-situ salinity measurements in the region both in space and time. Here we conduct a comprehensive analysis of SSS measurements from the SMAP and SMOS satellites and a suite of other ocean-atmosphere-land satellite observations. The results show that the main sources of the freshwater are derived directly from the Java Sea precipitation and the runoff from Kalimantan (Indonesian part of the Borneo island) during boreal winter and spring associated with the maritime continent monsoonal water cycle. These freshwater sources cause low SSS values in the southern part of Makassar Strait (the main channel of the ITF). The low SSS anomalies are associated with higher local sea level, which works against the predominant North-to-South pressure gradient that drives the southward ITF flows. Therefore, the monsoonal water cycle in the maritime continent plays a critical role in regulating the seasonality of the ITF. The results also have implications to ITF variations and the related impacts associated with longer-term changes of Indo-Pacific climate variability and water cycle in the maritime continent region. [ABSTRACT FROM AUTHOR]

The Mediterranean region has been identified as one of the main climate change hotspots: its sensitivity to global change is high and its evolution remains uncertain. The region experiences many interactions and feedbacks at the oceanic, atmospheric, and hydrological levels, while facing high anthropogenic activities. Analysing the water cycle over the Mediterranean region is of major importance to environmental and socio-economic aspects. The satellite monitoring of the Mediterranean water cycle represents one of the key challenges for the hydrological community.The presentation will show recent results on using satellite soil moisture and precipitation products for hydrometeorological prediction in the Mediterranean region, and particularly for the prediction of floods and landslides. Specifically, we will show the comparison of multiple satellite precipitation products for predicting flood in 100+ basins over the Mediterranean Basin by also using different hydrological models. Moreover, the assessment of satellite precipitation products for predicting the occurrence of landslides in Italy is carried out. Among the investigated satellite products, we have firstly considered state-of-the-art products such as TMPA (TRMM Multisatellite Precipitation Analysis), GPM (Global Precipitation Measurement), and H SAF (EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management). Secondly, we have tested the innovative products using the SM2RAIN algorithm for rainfall retrieval from multiple satellite soil moisture products including ASCAT (Advanced SCATterometer), SMOS (Soil Moisture and Ocean Salinity mission) and SMAP (Soil Moisture Active and Passive mission). [ABSTRACT FROM AUTHOR]

A key challenge in the projection of climate change (CC) impacts on hydrological hazards is the uncertainty, mainly from climate projections and hydrological modelling. Therefore, it is state of the art to use multi-model ensemble (MME) based information for quantifying potential CC impacts. A considerable amount of studies have been done based on these MMEs. However, little attention has been paid on how to best utilize MME derived information in CC risk management and adaptation. This type of research is done best jointly by data providers and users. The major objective of the CO-MICC project is to co-develop methods for providing and utilizing multi-model ensemble data on freshwater-related hazards computed by global hydrological models (GHMs) for risk and adaptation assessments. The project covers various spatial scales, and it provides CC risk and adaptation knowledge on a web portal. We aim to increase availability and applicability of salient and credible information for different types of end-users, with focus on how to embrace uncertainties. The project focuses on three spatial scales; global, transboundary (Morocco: Moulouya basin, Algeria: Chelif basin, and Tunisia: Mejerda basin) and basin (Ebro River basin, Spain). At each scale, two to three expert workshops will be carried out to facilitate the co-development of methods to utilize MME based information. At the global scale, we co-develop better methods in collaboration with international companies. The presentation is to share the first results of the focus basins along with a concise introduction to the CO-MICC project and its methods. For testing the validity and applicability of GHM outputs, streamflow simulated by four GHMs (WaterGAP, LPJML, CWatM, ORCHIDEE) driven by observation-based historical meteorological data (GSWP3) is compared to observed streamflow, and the relevance of this type of comparison for estimating the impact of climate change on streamflow is discussed. Accordingly, the climate change impact on the hydrological cycle is assessed using two indicators. 1) sensitivity of annual streamflow to inter-annual precipitation variability and 2) inter-annual variability of annual streamflow. In two expert workshops, user needs, as well as suitable hydrological hazard indicators, were identified. In addition, the experts provided feedback on potential ways for the presentation of hazards regarding precipitation, streamflow and renewable water resources by tables and maps. Outcomes of these expert workshops will be presented. [ABSTRACT FROM AUTHOR]

As a typical alpine marsh wetland on the Qinghai-Tibet Plateau, the Zoige Wetland plays an important role in the water source recharge of Yellow River. Meanwhile, it is more sensitive to climate change. Therefore, it is necessary to study the hydrological cycle of Zoige Wetland and the impact of climate change, which will also provide important support and reference for the study of hydrological process, and protection of wetland water resources in Alpine areas. Based on the distributed hydrological model, this paper analyzed the runoff process in the Zoige wetland basin, and explored the trend of runoff variation in the Zoige wetland basin under different climate change scenarios in the next 30 years from 2020 to 2050. The impact of climate change on wetland runoff were also discussed. Results showed that the runoff in the Zoige Wetland basin decreased under the future climate change scenario. The rate of runoff reduction was the largest in Machu station, followed by Zoige station, and finally Tangke station. The reduction in non-flooding runoff is significantly higher than that in the flood season. The runoff during non-flood season in the Zoige Wetland basin from 2020 to 2050 will decrease by more than 25% in the future climate change scenario. The sharp decline in non-flooded runoff may have an impact on the protection of the Zoige Wetland and the management of water resources in the middle reaches of the Yellow River and downstream areas. This poses more stringent requirements for the protection of the Zoige Wetland in response to future climate change. Under future climate change scenarios, how to strengthen the management and protection of wetland water resources and prevent the degradation and atrophy of wetlands is the issue we need to further discuss and consider. [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]

An accurate characterization of the global hydrologic cycle is essential not only to study and forecast climate variations, but also for extreme event mitigation and agricultural planning. Since precipitation is the major driving force of the hydrological cycle, current and future satellite missions with a focus on precipitation are critical to estimate hydrological variables globally. Error estimates associated with satellite precipitation retrievals are crucial to allow inferences about the reliability of such products in their operational applications. However, evaluating satellite precipitation error characteristics is challenging because of the inherent temporal and spatial variability of precipitation, measurement errors, and sampling uncertainties, especially at fine temporal and spatial resolutions.This study proposes to use a stochastic error model – PUSH (Probability Uncertainty in Satellite Hydrology) – for estimating uncertainties associated with fine resolution satellite precipitation products. The framework is tested on the daily IMERG (Integrated Multi-satellitE Retrievals for GPM) infrared-only (IR) precipitation component using a satellite-based radar product (the Level-3 Dual-frequency Precipitation Radar, 3DPRD) as reference. PUSH decomposes the error into four components and employs different modeling approaches for each case: correct no-precipitation detection; missed precipitation; false alarm; hit bias. PUSH is calibrated globally over land for different climatological regions. The calibrated parameters are validated using an independent period to verify whether they can be applied to estimate uncertainties associated with future IR retrievals without degrading the model performance. The four error components are then investigated as a function of climate region to study their spatial variability. [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]

We are faced with negative changes concerning social and the natural environment induced the degradation of permafrost, which is related to recent global warming. Thawing permafrost affects the hydrological cycle, geomorphological processes, as well as vegetation changes. Mongolia territory is by about 63 % within permafrost zone. Therefore, it is important to understand the dynamic of the process and controlling factors responsible for the permafrost degradation. We studied two peatlands Khar Zurkhnii Khukh Nuur in the Khentii mountain range (NE Mongolia). This part of Mongolia is characterized by the occurrence of the forest-steppe mosaic in the area of discontinuous permafrost. We aimed to reconstruct dependence between vegetation composition, fire regime shift and timing of permafrost degradation during the last 1600 years from two peat archive. For this purpose, we worked on peat archive and used multi-proxy analysis (pollen, plant macrofossils, testate amoebae, Cladocera, macro-charcoal, and geochemistry). Two profiles: 36-cm (KH-1) and 55-cm (KH-2) have been extracted from two nearby peatlands, which are only 1 km away. Chronology of the KH-1 core was based on 6 AMS 14C dates, 137Cs, and 210Pb analyses, while the second core KH-2 was based on 11 AMS 14C dates. Respectively, the core KH-1 covers the last 250 years and the core KH-2 covers the last 1600 years. Our first results indicate a strong relationship between degradation permafrost, droughts, vegetation forest-steppe mosaic composition and fire regime shifts, which caused intensified erosion in the catchment. Palaeoecological and geochemical data allowed tracing the dynamics of degradation permafrost and impact of fire regime shifts on the ecosystems, both triggered by recent and past climate changes. The research was funded by the National Science Centre (Poland) – grants 2017/01/X/ST10/01216 [ABSTRACT FROM AUTHOR]

The Future Climate For Africa programme aims to generate fundamentally new climate science focused on Africa, and to ensure that this science has an impact on human development across the continent. Funded by the UK Department for International Development and the Natural Environment Research Council, this programme is generating new insights into drivers of climate variability and change in the different regions of Africa. The programme has a focus on areas of climate science which can inform development decisions with long-term consequences. For example, the considerable investments being made in new infrastructure across the continent need to be future-climate proofed. This drives a need to improve knowledge of how climate change will affect, amongst other things, the frequency and severity of intense storms and droughts, and the occurrence of agriculturally-damaging dry spells. The provision of reliable future climate information for Africa is compromised by uncertainties in the water cycle and in the projections of variability of regional circulations within CMIP5 and CORDEX simulations. The representation of extreme rainfall is considered to be particularly uncertain due to the limitations of convective parameterisations used within global and regional climate models. We will present examples of new insights from the programme, including analysis of a unique convection-permitting pan-African simulation of current and future climate. [ABSTRACT FROM AUTHOR]

Dynamic Global Vegetation Models (DGVMs), e.g. LPJ-Guess model, have been widely applied to study transient aspects of ecosystem response (e.g. vegetation dynamics and biogeochemistry) to climate change and certain other aspects of global change. However, there are still considerable disagreements between model simulations and observations, especially in tropic region. It has been observed that Amazon rainforest green up during dry seasons while model simulations show plant productivity in Amazon rainforest rapidly decreases during drought. Amazon rainforest is the planet's largest forest and biologically richest ecosystem, and the changes in the biophysical state of the Amazon rainforest have a strong effect on global climate through associated changes in carbon and hydrological cycles. Therefore, it is of significance to study mechanisms that are not correctly treated in models in order to improve the understanding about carbon and hydrological cycle in Amazonia.The Gross Primary Production (GPP), one of ecological term to describe terrestrial carbon balance, provide important information about the environmental under global climate change, as the critical component of the global carbon cycle is the vegetation, mainly due to photosynthesis. Thus GPP is considered for uncertainty analysis and matiodel evaluon. In addition, LPJ-Guess model is used to model GPP. Results show that increasing soil depth, and considering rooting depth and groundwater depth, allow broadleaf evergreen forests in tropical Amazonia to maintain biophysical function through seasonal drought, as a result of better agreement between modeled GPP and observed GPP. [ABSTRACT FROM AUTHOR]

Under the framework of the EU-Horizon 2020 project BINGO (Bringing INnovation to onGOing water management), climate change impacts on the water cycle in the Wupper catchment area are being studied. For this purpose, the Soil and Water Assessment Tool (SWAT) has been set up, calibrated and validated. The model integrates detailed spatially and temporarily distributed soil, land-surface and meteorological information and can therefore closely link the impact of changes in climate variables to future changes in the numerous hydrological system variables. In this study, short-term (decadal) as well as long-term (centennial) impacts of climate change scenarios are examined, for the Wupper sub-catchment "Große Dhünn". This sub-catchment generates the inflow to a large reservoir, which is used as drinking water source for about 0.5 million people and as flood protection system for downstream areas. Changes of principal water balance components due to climate change, are therefore of high importance in this region.Climate change information are derived from medium-term decadal predictions, based on the MiKlip framework, for the time span 2015-2024, as well as from long-term IPCC-RCP scenarios, for the years 2006-2100. The study assesses potential future hydrological changes in the "Große Dhünn" catchment, based on both data sets and compares the projected changes for the overlapping time period (2015-2024).Decadal predictions as well as IPCC-RCP scenarios indicate that in the near future, winter months will experience reduced reservoir inflow, while summer inflow will slightly increase. The main reason for the decreasing winter discharge rates lays in decreasing precipitation during the respective winter months. In addition, temperature and concurrently also ET rates will increase during winter, which will intensify the decrease in discharge rates. Increasing summer temperatures and ET rates are compensated by increasing summer precipitation rates, and are resulting in a slight increase in summer discharge rates.For long-term predictions however, RCP scenarios indicate that under both RCP scenarios a significant reduction of inflow to the reservoir is expected in all seasons. Furthermore low flows will shift from early to late summer, making a careful management and saving of water resources until later in the hydrological year necessary.A comparison of simulated runoff based on decadal predictions and IPCC-RCP runoff scenarios reveals the interesting fact, that decadal predictions might underestimate the variability of future runoff responses to climate change. While RCP scenarios show a similar variability in runoff compared to historical data, decadal predictions indicate a significant reduction in future runoff variability. This is especially important to consider for future reservoir management, considering the range of potential extreme high and low flows in the near-future. [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]