Assessment of Socio-Economic and Climate Change Impacts on Water Resources in Four European Lagoon Catchments

This study demonstrates the importance of considering potential land use and management changes in climate impact research. By taking into account possible trends of economic development and environmental awareness, we assess effects of global warming on water availability and quality in the catchments of four European lagoons: Ria de Aveiro (Portugal), Mar Menor (Spain), Vistula Lagoon (Poland and Russia), and Tyligulskyi Liman (Ukraine). Different setups of the process-based soil and water integrated model (SWIM), representing one reference and four socio-economic scenarios for each study area: the “business as usual”, “crisis”, “managed horizons”, and “set-aside” scenarios are driven by sets of 15 climate scenarios for a reference (1971–2000) and near future (2011–2040) scenario period. Modeling results suggest a large spatial variability of potential impacts across the study areas, due to differences in the projected precipitation trends and the current environmental and socio-economic conditions. While climate change may reduce water and nutrients input to the Ria de Aveiro and Tyligulsyi Liman and increase water inflow to the Vistula Lagoon the socio-economic scenarios and their implications may balance out or reverse these trends. In the intensely managed Mar Menor catchment, climate change has no notable direct impact on water resources, but changes in land use and water management may certainly aggravate the current environmental problems. The great heterogeneity among results does not allow formulating adaptation or mitigation measures at pan-European level, as initially intended by this study. It rather implies the need of a regional approach in coastal zone management. © 2019, The Author(s)

Michael Stephen Schiro, Curriculum Theory: Conflicting Visions and Enduring Concerns. Thousand Oaks: Sage Publications, 2008, 238 p.

This study was conducted within the project SuMaRiO (Sustainable Management of River Oases along the Tarim River; http://www.sumario.de/), funded by the German Federal Ministry of Education and Re- search (BMBF grants 01LL0918J and 01LL0918B). T. Bolch acknowledges funding by Deutsche Forschungs- gemeinschaft (DFG, Code BO3199/2-1). The authors gratefully acknowledge the European Regional Devel- opment Fund (ERDF), the German Federal Ministry of Education and Research and the Land Brandenburg for supporting this project by providing resources on the high performance computer system at the Potsdam Institute for Climate Impact Research.Glacierised river catchments have been shown to be highly sensitive to climate change, while large populations depend on the water resources originating from them. Hydrological models are used to aid water resource management, yet their treatment of glacier processes is either rudimentary in large-scale applications or linked to fully distributed glacier models that prevent larger model domains. Also, data scarcity in mountainous catchments has hampered the implementation of physically based approaches over entire river catchments. A fully integrated glacier dynamics module was developed for the hydrological model SWIM (SWIM-G) that takes full account of the spatial heterogeneity of mountainous catchments but keeps in line with the semi-distributed disaggregation of the hydrological model. The glacierised part of the catchment is disaggregated into glaciological response units that are based on subbasin, elevation zone and aspect classes. They seamlessly integrate into the hydrological response units of the hydrological model. Robust and simple approaches to ice ow, avalanching, snow accumulation and metamorphism as well as glacier ablation under consideration of aspect, debris cover and sublimation are implemented in the model, balancing process complexity and data availability. The fully integrated model is also capable of simulating a range of other hydrological processes that are common for larger mountainous catchments such as reservoirs, irrigation agriculture and runoff from a diverse soil and vegetation cover. SWIM-G is initialised and calibrated to initial glacier hypsometry, glacier mass balance and river discharge. While the model is intended to be used in medium to large river basins with data-scarce and glacierised headwaters, it is here validated in the data-scarce catchment of the Upper Aksu River, Kyrgyzstan/NW China and in the relatively data-abundant catchment of the Upper Rhone River, Switzerland.PostprintPeer reviewe

Intercomparison of regional-scale hydrological models and climate change impacts projected for 12 large river basins worldwide - A synthesis

An intercomparison of climate change impacts projected by nine regional-scale hydrological models for 12 large river basins on all continents was performed, and sources of uncertainty were quantified in the framework of the ISIMIP project. The models ECOMAG, HBV, HYMOD, HYPE, mHM, SWAT, SWIM, VIC and WaterGAP3 were applied in the following basins: Rhine and Tagus in Europe, Niger and Blue Nile in Africa, Ganges, Lena, Upper Yellow and Upper Yangtze in Asia, Upper Mississippi, MacKenzie and Upper Amazon in America, and Darling in Australia. The model calibration and validation was done using WATCH climate data for the period 1971–2000. The results, evaluated with 14 criteria, are mostly satisfactory, except for the low flow. Climate change impacts were analyzed using projections from five global climate models under four representative concentration pathways. Trends in the period 2070–2099 in relation to the reference period 1975–2004 were evaluated for three variables: the long-term mean annual flow and high and low flow percentiles Q 10 and Q 90, as well as for flows in three months high- and low-flow periods denoted as HF and LF. For three river basins: the Lena, MacKenzie and Tagus strong trends in all five variables were found (except for Q 10 in the MacKenzie); trends with moderate certainty for three to five variables were confirmed for the Rhine, Ganges and Upper Mississippi; and increases in HF and LF were found for the Upper Amazon, Upper Yangtze and Upper Yellow. The analysis of projected streamflow seasonality demonstrated increasing streamflow volumes during the high-flow period in four basins influenced by monsoonal precipitation (Ganges, Upper Amazon, Upper Yangtze and Upper Yellow), an amplification of the snowmelt flood peaks in the Lena and MacKenzie, and a substantial decrease of discharge in the Tagus (all months). The overall average fractions of uncertainty for the annual mean flow projections in the multi-model ensemble applied for all basins were 57% for GCMs, 27% for RCPs, and 16% for hydrological models

Multimodel assessment of flood characteristics in four large river basins at global warming of 1.5, 2.0 and 3.0 K above the pre-industrial level

This study assesses the flood characteristics (timing, magnitude and frequency) in the pre-industrial and historical periods, and analyzes climate change impacts on floods at the warming levels of 1.5, 2.0 and 3.0 K above the pre-industrial level in four large river basins as required by the Paris agreement. Three well-established hydrological models (HMs) were forced with bias-corrected outputs from four global climate models (GCMs) for the pre-industrial, historical and future periods until 2100. The long pre-industrial and historical periods were subdivided into multiple 31-year subperiods to investigate the natural variability. The mean flood characteristics in the pre-industrial period were derived from the large ensemble based on all GCMs, HMs and 31-year subperiods, and compared to the ensemble means in the historical and future periods. In general, the variance of simulated flood characteristics is quite large in the pre-industrial and historical periods. Mostly GCMs and HMs contribute to the variance, especially for flood timing and magnitude, while the selection of 31-year subperiods is an important source of variance for flood frequency. The comparison between the ensemble means shows that there are already some changes in flood characteristics between the pre-industrial and historical periods. There is a clear shift towards earlier flooding for the Rhine (1.5 K scenario) and Upper Mississippi (3.0 K scenario). The flood magnitudes show a substantial increase in the Rhine and Upper Yellow only under the 3.0 K scenario. The floods are projected to occur more frequently in the Rhine under the 1.5 and 2.0 K scenarios, and less frequently in the Upper Mississippi under all scenarios

Projected climate change and its impacts on glaciers and water resources in the headwaters of the Tarim River, NW China/Kyrgyzstan

This study was conducted within the project SuMaRiO (Sustainable Management of River Oases along the Tarim River; http://www.sumario.de/), funded by the German Federal Ministry of Education and Research (BMBF grants 01LL0918J, 01LL0918I and 01LL0918B). T. Bolch acknowledges funding by Deutsche Forschungsgemeinschaft (DFG, BO3199/2–1). Open Access funding enabled and organized by Projekt DEAL.Glacierised river catchments are highly sensitive to climate change, while large populations may depend on their water resources. The irrigation agriculture and the communities along the Tarim River, NW China, strongly depend on the discharge from the glacierised catchments surrounding the Taklamakan Desert. While recent increasing discharge has been beneficial for the agricultural sector, future runoff under climate change is uncertain. We assess three climate change scenarios by forcing two glacio-hydrological models with output of eight general circulation models. The models have different glaciological modelling approaches but were both calibrated to discharge and glacier mass balance observations. Projected changes in climate, glacier cover and river discharge are examined over the twenty-first century and generally point to warmer and wetter conditions. The model ensemble projects median temperature and precipitation increases of + 1.9–5.3 °C and + 9–24%, respectively, until the end of the century compared to the 1971–2000 reference period. Glacier area is projected to shrink by 15–73% (model medians, range over scenarios), depending on the catchment. River discharge is projected to first increase by about 20% in the Aksu River catchments with subsequent decreases of up to 20%. In contrast, discharge in the drier Hotan and Yarkant catchments is projected to increase by 15–60% towards the end of the century. The large uncertainties mainly relate to the climate model ensemble and the limited observations to constrain the glacio-hydrological models. Sustainable water resource management will be key to avert the risks associated with the projected changes and their uncertainties.Publisher PDFPeer reviewe

Climate impact emergence and flood peak synchronization projections in the Ganges, Brahmaputra and Meghna basins under CMIP5 and CMIP6 scenarios

The densely populated delta of the three river systems of the Ganges, Brahmaputra and Meghna is highly prone to floods. Potential climate change-related increases in flood intensity are therefore of major societal concern as more than 40 million people live in flood-prone areas in downstream Bangladesh. Here we report on new flood projections using a hydrological model forced by bias-adjusted ensembles of the latest-generation global climate models of CMIP6 (SSP5-8.5/SSP1-2.6) in comparison to CMIP5 (RCP8.5/RCP2.6). Results suggest increases in peak flow magnitude of 36% (16%) on average under SSP5-8.5 (SSP1-2.6), compared to 60% (17%) under RCP8.5 (RCP2.6) by 2070-2099 relative to 1971-2000. Under RCP8.5/SSP5-8.5 (2070-2099), the largest increase in flood risk is projected for the Ganges watershed, where higher flood peaks become the ‘new norm’ as early as mid-2030 implying a relatively short time window for adaptation. In the Brahmaputra and Meghna rivers, the climate impact signal on peak flow emerges after 2070 (CMIP5 and CMIP6 projections). Flood peak synchronization, when annual peak flow occurs simultaneously at (at least) two rivers leading to large flooding events within Bangladesh, show a consistent increase under both projections. While the variability across the ensemble remains high, the increases in flood magnitude are robust in the study basins. Our findings emphasize the need of stringent climate mitigation policies to reduce the climate change impact on peak flows (as presented using SSP1-2.6/RCP2.6) and to subsequently minimize adverse socioeconomic impacts and adaptation costs. Considering Bangladesh’s high overall vulnerability to climate change and its downstream location, synergies between climate change adaptation and mitigation and transboundary cooperation will need to be strengthened to improve overall climate resilience and achieve sustainable development

Performance evaluation of global hydrological models in six large Pan-Arctic watersheds

Global Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological processes in the data scarce high latitudes. Here we performed a systematic model performance evaluation in six major Pan-Arctic watersheds for different hydrological indicators (monthly and seasonal discharge, extremes, trends (or lack of), and snow water equivalent (SWE)) via a novel Aggregated Performance Index (API) that is based on commonly used statistical evaluation metrics. The machine learning Boruta feature selection algorithm was used to evaluate the explanatory power of the API attributes. Our results show that the majority of the nine GWMs included in the study exhibit considerable difficulties in realistically representing Pan-Arctic hydrological processes. Average APIdischarge (monthly and seasonal discharge) over nine GWMs is > 50% only in the Kolyma basin (55%), as low as 30% in the Yukon basin and averaged over all watersheds APIdischarge is 43%. WATERGAP2 and MATSIRO present the highest (APIdischarge > 55%) while ORCHIDEE and JULES-W1 the lowest (APIdischarge ≤ 25%) performing GWMs over all watersheds. For the high and low flows, average APIextreme is 35% and 26%, respectively, and over six GWMs APISWE is 57%. The Boruta algorithm suggests that using different observation-based climate data sets does not influence the total score of the APIs in all watersheds. Ultimately, only satisfactory to good performing GWMs that effectively represent cold-region hydrological processes (including snow-related processes, permafrost) should be included in multi-model climate change impact assessments in Pan-Arctic watersheds. © 2020, The Author(s)

Cross-comparison of climate change adaptation strategies across large river basins in Europe, Africa and Asia

A cross-comparison of climate change adaptation strategies across regions was performed, considering six large river basins as case study areas. Three of the basins, namely the Elbe, Guadiana, and Rhine, are located in Europe, the Nile Equatorial Lakes region and the Orange basin are in Africa, and the Amudarya basin is in Central Asia. The evaluation was based mainly on the opinions of policy makers and water management experts in the river basins. The adaptation strategies were evaluated considering the following issues: expected climate change, expected climate change impacts, drivers for development of adaptation strategy, barriers for adaptation, state of the implementation of a range of water management measures, and status of adaptation strategy implementation. The analysis of responses and cross-comparison were performed with rating the responses where possible. According to the expert opinions, there is an understanding in all six regions that climate change is happening. Different climate change impacts are expected in the basins, whereas decreasing annual water availability, and increasing frequency and intensity of droughts (and to a lesser extent floods) are expected in all of them. According to the responses, the two most important drivers for development of adaptation strategy are: climate-related disasters, and national and international policies. The following most important barriers for adaptation to climate change were identified by responders: spatial and temporal uncertainties in climate projections, lack of adequate financial resources, and lack of horizontal cooperation. The evaluated water resources management measures are on a relatively high level in the Elbe and Rhine basins, followed by the Orange and Guadiana. It is lower in the Amudarya basin, and the lowest in the NEL region, where many measures are only at the planning stage. Regarding the level of adaptation strategy implementation, it can be concluded that the adaptation to climate change has started in all basins, but progresses rather slowly

Intercomparison of regional-scale hydrological models and climate change impacts projected for 12 large river basins worldwide—a synthesis

An intercomparison of climate change impacts projected by nine regional-scale hydrological models for 12 large river basins on all continents was performed, and sources of uncertainty were quantified in the framework of the ISIMIP project. The models ECOMAG, HBV, HYMOD, HYPE, mHM, SWAT, SWIM, VIC and WaterGAP3 were applied in the following basins: Rhine and Tagus in Europe, Niger and Blue Nile in Africa, Ganges, Lena, Upper Yellow and Upper Yangtze in Asia, Upper Mississippi, MacKenzie and Upper Amazon in America, and Darling in Australia. The model calibration and validation was done using WATCH climate data for the period 1971–2000. The results, evaluated with 14 criteria, are mostly satisfactory, except for the low flow. Climate change impacts were analyzed using projections from five global climate models under four representative concentration pathways. Trends in the period 2070–2099 in relation to the reference period 1975–2004 were evaluated for three variables: the long-term mean annual flow and high and low flow percentiles Q10 and Q90, as well as for flows in three months high- and low-flow periods denoted as HF and LF. For three river basins: the Lena, MacKenzie and Tagus strong trends in all five variables were found (except for Q10 in the MacKenzie); trends with moderate certainty for three to five variables were confirmed for the Rhine, Ganges and Upper Mississippi; and increases in HF and LF were found for the Upper Amazon, Upper Yangtze and Upper Yellow. The analysis of projected streamflow seasonality demonstrated increasing streamflow volumes during the high-flow period in four basins influenced by monsoonal precipitation (Ganges, Upper Amazon, Upper Yangtze and Upper Yellow), an amplification of the snowmelt flood peaks in the Lena and MacKenzie, and a substantial decrease of discharge in the Tagus (all months). The overall average fractions of uncertainty for the annual mean flow projections in the multi-model ensemble applied for all basins were 57% for GCMs, 27% for RCPs, and 16% for hydrological models.Intercomparison of regional-scale hydrological models and climate change impacts projected for 12 large river basins worldwide—a synthesispublishedVersio

Assessing the impacts of 1.5 °C global warming – simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b)

In Paris, France, December 2015, the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) invited the Intergovernmental Panel on Climate Change (IPCC) to provide a "special report in 2018 on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways". In Nairobi, Kenya, April 2016, the IPCC panel accepted the invitation. Here we describe the response devised within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) to provide tailored, cross-sectorally consistent impact projections to broaden the scientific basis for the report. The simulation protocol is designed to allow for (1) separation of the impacts of historical warming starting from pre-industrial conditions from impacts of other drivers such as historical land-use changes (based on pre-industrial and historical impact model simulations); (2) quantification of the impacts of additional warming up to 1.5°C, including a potential overshoot and long-term impacts up to 2299, and comparison to higher levels of global mean temperature change (based on the low-emissions Representative Concentration Pathway RCP2.6 and a no-mitigation pathway RCP6.0) with socio-economic conditions fixed at 2005 levels; and (3) assessment of the climate effects based on the same climate scenarios while accounting for simultaneous changes in socio-economic conditions following the middle-of-the-road Shared Socioeconomic Pathway (SSP2, Fricko et al., 2016) and in particular differential bioenergy requirements associated with the transformation of the energy system to comply with RCP2.6 compared to RCP6.0. With the aim of providing the scientific basis for an aggregation of impacts across sectors and analysis of cross-sectoral interactions that may dampen or amplify sectoral impacts, the protocol is designed to facilitate consistent impact projections from a range of impact models across different sectors (global and regional hydrology, lakes, global crops, global vegetation, regional forests, global and regional marine ecosystems and fisheries, global and regional coastal infrastructure, energy supply and demand, temperature-related mortality, and global terrestrial biodiversity)