PUDDLE JUMP: Promoting Upstream-Downstream Directed Linkages in the Environment: “Joined-Up” Management Perspectives
PUDDLE JUMP will contribute to “joined up” thinking about hydrological and other ecosystem services (ES) that can be provided by small artificial waterbodies (SAWs: ponds and wetlands). SAWs are found in many urban, agricultural and forest landscapes. When designed, located and managed appropriately, they can be multifunctional solutions for flood and drought risk mitigation, biodiversity promotion and ES delivery. We will highlight the need to consider upstream/downstream hydrological and institutional connectivity when evaluating the (dis-)benefits SAWs offer to society and nature. Through an in-depth and co-created study of Mälardalen (Stockholm, Uppsala, Knivsta) SAWs, we develop guidelines for Swedish municipal stakeholders to integrate SAWs into their planning processes. We will use a “local first” approach to engage with municipalities where a lack of joined-up thinking has limited the optimal use of SAWs for ES delivery. Using a catchment-oriented approach, we will test how SAWs can manage water flows and will focus on SAW placement to mitigate against extreme hydrological events (both floods and drought). We will investigate the recreational and social ES offered by SAWs, and use citizen science methods to increase public awareness of the multiple ES that SAWs provide. Finally, we will analyse the national and international policy context for SAWs focusing on multi-level governance and actions to meet both Water Framework and Floods Directive requirements.
ESSENCE – The Swedish e-Science collaboration: The Swedish Water-Energy-Food-Ecosystem Nexus and its response to hydroclimatic EXTreme events
In this project, we aim to contribute in bridging this gap by applying data-driven methods to detect interlinkages among four nexus components in Sweden, and to discover patterns and potential feedback mechanisms based on a comprehensive data set of environmental, hydroclimatic and socio-economic data. One of the key questions that we would like to answer is whether the impacts of extreme hydroclimatic events (e.g., the 2018 drought) on individual nexus sectors and on the nexus as a whole, can be predicted with state-of-the-art data-driven methods. The results will provide a solid ground for designing coherent policies and optimal resource management in a changing climate in Sweden.
NEXOGENESIS: Facilitating the next generation of effective and intelligent water-related policies utilising artificial intelligence and reinforcement learning to assess the water-energy-food-ecosystem (WEFE) nexus
Water, energy, food, and ecosystems (the WEFE nexus) are interconnected and are influenced by climatic and socio-economic drivers. Resource constraints and the general lack of consideration by policies of various interconnections could hamper economic development and resource security itself, as well as affect actor behaviour and policy formulation initiatives.
NEXOGENESIS is a 4-year European collaborative project financed by the European Commission under the H2020 programme. It gathers 20 partners from Europe and South Africa focusing on facilitating the next generation of effective and intelligent water-related policies using artificial intelligence and machine learning to assess policy impacts on the WEFE nexus to suggest new ways to design better, more harmonious policy.
NEXOGENESIS will develop and validate 3 solutions:
- A cross-sectoral policy-making framework developed for and validated by stakeholders;
- A Self-Learning Nexus Assessment Engine taking different aspects into account and exploring the consequences of possible policy options;
- A WEFE Nexus Footprint to track impacts of policy objectives and communicate results in a more digestible way.
LANDPATHS: The landscapes of the future: barriers and drivers for transformation paths
LANDPATHS is a large research programme that aims to promote multifunctional landscapes that are both biodiversity rich and provide multiple benefits for a range of actors.
We are addressing governance and management challenges within a broad set of landscapes and applying cross-cutting and integrative analyses. LANDPATHS will deliver innovative and practically applicable knowledge and recommendations for practitioners and public agencies. The practical outcome of the programme will be a portfolio of implementable good practises and innovative management and governance tools and practises that facilitate cross-sectoral collaboration and support the development of landscapes that deliver multiple ecological and socio-economic functions while maintaining high biodiversity. The programme will contribute to achieving several important national and international policies, particularly on biodiversity and climate change.
The programme’s consortium consists of researchers with social and natural science expertise in biodiversity conservation, a broad experience of transdisciplinary work and a rich network of contacts among stakeholders in different sectors and governance contexts. The planned research will focus on key landscape governance and decision-making processes to strengthen biodiversity and landscape multifunctionality.
The programme employs a transdisciplinary approach, combining expertise of researchers and stakeholders to co-create and explore:
- a set of imaginaries of future multifunctional landscapes;
- scenarios, including barriers and opportunities, for achieving such futures;
- transformative governance pathways to catalyse such multifunctional landscapes.
The focus is on five types of landscape – forest, agricultural, sea and coast, urban and mountain landscapes (SPs5-9).
There is a significant global North–South divide that has implications for how science is designed, produced, interpreted and used in practice and how policies are developed and implemented on the ground. Despite efforts to address the problem of this divide by a range of actors, ranging from intergovernmental organizations, international donor organizations, national governments, or research councils, improvement in the situation has progressed in slow motion.
At the same time, the Paris Agreement under the United Nations Framework Convention on Climate Change (UNFCCC) and the Agenda 2030 both entail substantial global investments through cost-efficient, long-term financing. SDG 17 has a great potential to facilitate mobilizing and sharing knowledge, expertise, technologies and financial resources. While there are some reports on SDGs partnerships, very few have focused on how they address the global North-South divide. Therefore, in this project, we will investigate the relationships between SDG 17 and financial resources including green FDI, green bonds, and international aid with the aim of clarifying how SDG 17 addresses the global North-South divide in the aspect of mobilizing financial resources. FDI serves not just as a great source of capital, but also as an important channel for introducing more productive technology and techniques in a lot of developing countries. Various studies have shown sector specific policies have strong influence on the location choice of FDI, but little research has been published on how partnerships such as SDG 17 influence the flow of the capital.
The objective of the project is thus to analyse the relationships between multi-actor partnerships from different countries and SDGs related capital flow, such as green FDI, green bonds, and international aid to investigate how the partnership links influenced private and public capital flow to close the North-South gap.
PONDERFUL: Pond Ecosystems for Resilient FUture Landscapes in a changing climate
Because of their small size, the significance of ponds has long been underestimated. They are, for example, largely excluded from the Water Framework Directive in Europe, even though the Directive is actually intended to protect ‘all waters’. In North America, their inclusion in the protections provided by the Clean Water Act are contested, and in other areas they lie largely outside regulatory systems. However, research over the last 10-15 years has shown that, because of their abundance, heterogeneity, exceptional biodiversity, inherent naturalness and biogeochemical potency, ponds play a role in catchments, landscapes, and potentially at continental scale which is completely out of proportion to their small size.
The main aims of the research in PONDERFUL will be to increase understanding of the ways in which ponds, as a Nature-Based Solution (NBS), can help society to mitigate and adapt to climate change, protect biodiversity and deliver ecosystem services. The project starts in December 2020, and runs for 4 years.
The project has five main components:
- Developing a strategic approach to engagement with stakeholders, to ensure that they are able to effectively implement the benefits of ponds as Nature-Based Solutions
- Through the generation of extensive new biodiversity and ecosystem services datasets, to better establish the relationship between pond biodiversity and the delivery of ecosystem services
- Establish models that enable us to test and optimise practical scenarios for the use of ponds and Nature-Based Solutions
- Create a set of demonstration sites across Europe which show to practitioners and policy makers how ponds can help to mitigate and adapt to the effects of climate change
- Ensure that the project’s outputs are widely known to policy makes, practitioners and other stakeholder.
The full project team comprises: the University of Vic – Central University of Catalonia; IGB Leibniz-Institute of Freshwater Ecology and Inland Fisheries; Katholieke Universiteit Leuven; Haute Ecole Specialisée de Suisse Occidentale; Universitat de Girona; Ecologic Institute, Berlin; University College London; Middle East Technical University; CIIMAR – Centro Interdisciplinar de Investigação Marinha e Ambiental; Aarhus Universitet; Uppsala Universitet; Bangor University; Technische Universitaet Muenchen; Institut Superieur d’agriculture Rhone Alpes I.S.A.R.A; Freshwater Habitats Trust; Universidad de la Republica, Uruguay; Randbee Consultants and Amphi International.
The overall goal of this project is to provide practitioners, land owners, water managers and relevant authorities with a toolkit to evaluate and promote the implementation of wetlands in agricultural landscapes. This toolkit will support a holistic and multi-functional approach to climate adaptation in line with existing socio-economic and institutional contexts by optimizing the delivery of hydrologically related ecosystem services (ES) with a view to maximizing co-benefits whilst minimizing negative consequences.
With WetKit we aim to contribute to the development of context-sensitive, evidence-based policies and strategies using wetland management to improve landscape resilience to climate-change while maintaining food and fibre production and ES delivery
RESEARCH QUESTIONS
- What is the impact of constructed agricultural wetlands on hydrologic processes at a local and a catchment scale?
- What is the best way to optimize wetland multifunctionality?
- Controlled and uncontrolled factors influencing wetland hydrologic functioning and
multifunctionality? - How are agricultural wetlands perceived by relevant stakeholders?
One rationale to construct and restore wetlands is to reduce the risk of droughts and floods. To be able place the wetlands at optimal sites in the landscape to fulfill this goal more knowledge is needed about the storage of water in the wetlands.
In the EviWet project, high-frequency measurements of the water balance (evaporation and transpiration) in different types of wetlands are being compared with those from forests. The purpose is to get a better understanding of how wetlands influence the storage and release of water from landscapes. The analyses will be used to improve the hydrological modelling of wetlands used in decision support.
The project is led by Kevin Bishop from the Department of Aquatic Sciences and Assessment. Post-Doc Reinert Huseby Karlsen works on the project at SLU. Niclas Hjerdt is leading the half of the project based at SMHI, while Uppsala University and the University of Zurich are also involved.
SMHI is responsible for the development of the decision support functions based on S-Hype.
Through the collection of hydro-climatic data, the application of big-data analyses methods and hydrological/agricultural modelling techniques, we will fill existing knowledge gaps in terms of how El-Niño events influence
- key hydrological processes and water use
- performance of major water resources infrastructures during El-Niño events in meeting the water and energy demands of the region under existing operational practices
- agricultural activities (such as cropping patterns or planting periods)
Vision: Five important knowledge gaps currently limit much of the present effort to understand and project climate change impacts on water resources. The goal of the proposed project is to fill these existing knowledge gaps and strengthen the basis for robust projections of future hydrological climate change impacts by carefully assessing existing approaches and by developing new dynamic and multi-dimensional methods to reduce uncertainties.
Hydrological climate change impact studies rely on complex serial modeling chains (Figure 1) which typically involve several methodological decisions including choices of greenhouse gas emission scenarios as a basis for a global climate model (GCM). GCM simulations are then used as boundary conditions for regional climate models (RCMs). Climate ensemble simulations of such RCMs with resolutions of 10-50 km for Europe can be downloaded from public web portals such as CORDEX1 or ENSEMBLES2. For hydrological impact studies at the catchment scale, RCM-simulated variables such as temperature (T) and precipitation (P) are most commonly used to drive a hydrological model. These RCM variables are, however, often affected by considerable systematic model errors3,4 (also called biases), and consequently require suitable bias correction approaches5. Bias correction is the process of re-scaling climate model outputs to reduce the effects of systematic errors in the climate models and to make the output more suitable as driving force for the hydrological model, which in turn provides simulations of a hydrological component (e.g., streamflow) under varying climate conditions. Bias correction methods typically do not consider the physical reasons of the biases and can introduce inconsistencies between simulated variables (knowledge gap 1). Furthermore, a crucial assumption of common bias correction methods is that the RCM simulation bias is assumed to be invariant over time (i.e. stationary), which is often not the case in reality (knowledge gap 2). Another limitation of the above mentioned type of modeling chain is that the decisions made along the way have a considerable impact on the resulting hydrological projections, because different models/methods have different skill levels6 and therefore cause highly variable results (knowledge gap 3). This does not only apply to the climate models, but also to the hydrological models at the end of the modeling chain. Especially the way of calculating certain hydrological components within the model (e.g. potential evaporation or snow pack) and their dependence on the driving RCM data is a source of large uncertainties (knowledge gap 4). And finally, stationary model parameterization (i.e., fixed model parameter values) can be problematic as it does not allow the hydrological model to respond to physical changes in the catchments caused by climate change or anthropogenic modifications (knowledge gap 5).
Objectives
- Bridge knowledge gap 1: Develop a higher-dimensional bias correction (i.e., multivariate distribution scaling, MVDS) that is able to maintain physical links among multiple variables to effectively reduce RCM biases and evaluate its suitability for hydrological impacts simulations in Sweden
- Bridge knowledge gap 2: Add a dynamic component to MVDS, so that it will become sensitive to time-variant RCM biases for hydrological impacts simulations in Sweden
- Bridge knowledge gap 3: Investigate the skill levels of different hydrological models under climate conditions unlike those used for model training, while considering different ensemble averaging techniques when examining inter-period transferability
- Bridge knowledge gap 4: Benchmark approaches for deriving potential evaporation conditions (for Swedish climate) based on RCM simulations in a changing climate context
- Bridge knowledge gap 5: Evaluate whether time-varying hydrological model parameters better reflect changes in hydrological processes in a changing climate
Publications
But the prediction and characterization of hydrological drought events is challenging because: (1) Droughts are complex phenomena involving many interacting climate processes, (2) The sensitivity of regions to droughts depends on multiple factors, from storage properties and natural resilience to water use and social systems’ vulnerability, (3) Even though evapotranspiration is a key input variable to many hydrological models, the question of how to best derive it from climate models is still unanswered, (4) The combined effects of evapotranspiration and topographic/geological controls on different gain/loss processes are not fully understood, which adds another dimension of uncertainty to the already existing uncertainties in ensemble-based modeling.
We believe that there is now an urgent need to estimate water availability in a changing climate and a developing society. Our project thus aims at the characterization and early recognition of critical hydrological drought conditions in Sweden. It will also facilitate the development of a universal modeling framework for reliable simulations of droughts for integrated climate change modeling.