The objectives of this climate risk assessment for the Li River in China is to assess current flood risk and future flood risk in the Li river basin in China. With an average of 1800 mm annual total rainfall, floods are severe and frequent in the region. Additionally to rainfall, severe floods in are often related to discharges from upstream reservoirs
Given the fact that this area is data scarce, global datasets with climatic data (ERA5-Land), soil parameters (HiHydroSoil) and land cover (Copernicus) were used to feed a hydrological HEC-HMS model to calculate the discharge for the extreme event of June 2020. Based on measured water levels and discharge, it was possible to develop rating curves and with these rating curves, it was possible to estimate water levels in the river for current (validation) and future conditions. This analysis served as input for the full climate risk assessment, in which possible interventions were proposed to reduce flood risk in the future.
The objectives of the Norfolk Water Fund is to secure good quality, long-term water resources for all water users, while protecting the environment and showcasing the county as an international exemplar for collaborative water management. The programme seeks to demonstrate how cross-sector, integrated water management and can deliver multiple benefits and help achieve the county’s net zero targets.
Water Funds are a well-established model for facilitating collective action to address water security challenges through the implementation of nature-based solutions (NBS) as a complement for more traditional so-called ‘grey’ infrastructure such as pipelines and treatment plants. Norfolk is one of two European pilots selected for Water Funds by The Nature Conservancy (TNC), to add to their global portfolio of Water Funds.
To deliver this programme, a variety of technical activities are required. These include assessing Water Security Challenges in the county, identifying the most relevant NBS to the context, and prioritising the most effective locations and strategies for their implementation. FutureWater will support these technical activities with NBS and water resources expertise alongside coordinating technical partners.
The MRCS regularly undertakes periodic regional and basin-wide studies on behalf of Member Countries to assess potential effects of increasing development, growing population and uncertainty in climate variability in the Lower Mekong Basin (LMB). Recent basin-wide assessment and reporting were found to be hampered by data limitations across a range of areas. With the basin undergoing rapid and extensive change, tracking changes in conditions, analyzing the potential implications, and working cooperatively to leverage the benefits and avoid the problems are seen as critical to achieving the objectives of the 1995 Mekong Agreement.
To provide a greater strategic direction to the monitoring and assessment effort, the Mekong River Basin Indicator Framework (MRB-IF) was developed and approved aiming at providing a consistent and streamlined approach to data collection, analysis, and reporting. Through the MRB-IF, the MRC Member Countries and stakeholders can be alerted to the key issues and trends across five core dimensions (environment, social, economic, climate change and cooperation). Included in the MRB-IF are (i) the extent of salinity intrusion in the Mekong Delta (MD) – Assessment Indicator 14 and (ii) the condition of riverine, estuarine, and coastal habitats – Assessment Indicator 16. A systematic process of collection and analysis of the data for status and trends evaluation regarding these indicators is currently missing.
The aim of this project is therefore to develop a basin-specific systematic approach to periodically assess the extent of salinity intrusion in the Mekong Delta and the conditions of the riverine, estuarine, and coastal habitats across the LMB. Methodologies to evaluate both indicators are developed relying on integration of satellite remote sensing data, GIS databases, and station data. The project involves an elaborate review of existing methodologies tested in the LMB and other river basins, an assessment of these methods regarding technical, economic and institutional aspects, and the development of a recommended methodology for adoption by MRCS, including guidance documentation for its stepwise implementation.
Nature-based Solutions (NbS) can help ensure the long-term reliability of water resources. Research has shown they can – depending on circumstance – be more cost-effective and longer-lasting than grey infrastructure, while generating multiple co-benefits for carbon, biodiversity and human health. Despite the promise of NbS, however, water sector actors and their financiers usually prioritize investments in traditional grey infrastructure because they are more familiar with its costs, benefits and returns. Most of them are unfamiliar with how to develop and assess the value of NbS projects, though research shows they’re interested in tapping into their multi-faceted benefits.
The Financing Nature for Water Security project of The Nature Conservancy (TNC) aims to produce and disseminate guidance that enables water sector actors (government agencies, water utilities, grass-root NGOs) and their funders (donors, development banks and private investors) to invest in NbS-WS, at scale, by mobilizing sustainable funding and repayable financing. The project comprises of technical modules, guidance documents, supporting databases and training materials.
FutureWater has been contracted by TNC to support the development of one of the content modules assembled under the project. The module “Technical Options” will help the reader understand the water security challenge(s) they are confronted with and identify the types of NbS that could help address those challenges. In particular, Futurewater works on the creation of 12 technical factsheets to be included in an annex to the main documentation, with each factsheet highlighting the key technical aspects, benefits and risks, and economic dimensions of an NbS. In addition, an inventory of relevant NbS databases, platforms, and references is delivered.
«Gabon is a rapidly developing country that contains substantial amount of intact natural areas and biodiversity, and large untapped natural resource stocks, placing the country at the forefront of a green economic development opportunities. TNC supports the government in preserving Hydrologic Ecosystem Services which are essential to include into development projects as for example hydropower.
This study will assess these services for the Komo basin where certain pressure already exists due to forestry operations and planned hydropower. It will evaluate various management scenarios which may improve and sustain hydrological flow conditions and hydropower options. The analysis will help the government in implementing an integrated water resources management (IWRM) approach in this basin.
FutureWater will deliver this study through hydrological modeling and scenario analysis to assess how hydrological ecosystem services provision in the Komo basin can be improved by a series of potential alternative scenarios based.»
The proposed Mombasa Water Fund should secure and improve the quantity and quality of source waters for Mombasa City by channelling investments into source protection and catchment conservation measures of the watersheds. Current spring- and groundwater-based water supply infrastructure is insufficient to meet the city’s growing demands. Focus of the study is therefore on the watershed that serves a new water reservoir (Mwache Dam).
The design study will:
Assess the biophysical, financial, economic and socio-economic benefits of the MWF; and
Identify the potential governance and financing models to establish the MWF
FutureWater performs the biophysical analysis of this study. It aims to link activities in the watershed with positive outcomes for water security. Different combinations of solutions (nature-based primarily) are simulated through an hydrological modelling tool to assess impacts on water quantity and quality, including erosion and sediment yield. The model allows also to assess water demand versus supplies and resulting possible future shortages. Outputs are used in the economic analysis that will cost and valuate different alternative scenarios. The business case study should enable the creation of another successful Water Fund in sub-Saharan Africa promoted by The Nature Conservancy.
The purpose of these calculations was to provide a definite answer about the usefulness and necessity of the proposed storm water retention areas that were seen as necessary in 2009. Various scenario calculations were performed using a Sobek model in which water levels and discharges were compared under the current and future climate and with and without integration of the storm water retention areas.
The activities in this project included:
Testing of discharge and water levels at critical locations for the climate scenario at different recurrence times (flood risk assessment using climate scenario),
Comparison to the results of the flood risk assessment using historical climate data,
Integration of storm water retention areas in the Sobek model and analysis of their impact on water levels, discharge at critical locations (usefulness and necessity for storm water retention areas, answer to LBW),
An initial estimate of critical locations along specific flood defense barriers for the different scenarios (high resolution comparison of water levels and defenses barrier heights) and
A comparison of the results with a number of previously conducted studies.
During the project, the flood risk assessment method, which was developed by Arcadis in 2020, was (further) automated, so that the method can be applied more quickly and for other comparable projects within Vechtstromen Water Board. Based on the results of the calculations, clear advice could be given on the usefulness and necessity of the proposed storm water retention areas as they were proposed in 2009.
The Swiss Agency for Development and Cooperation’s (SDCs) Global Programme Climate Change and Environment (GP CCE) India is supporting the operationalization of climate change adaptation actions in the mountain states of Uttarakhand, Sikkim and Himachal Pradesh through the phase two of the “Strengthening State Strategies for Climate Action” (3SCA) project that was launched in 2020. The second phase of 3SCA (2020-23), known as the Strengthening Climate Change Adaptation in Himalayas (SCA-Himalayas), while building on the experience and achievements of Phase 1, aims to showcase mountain ecosystem appropriate scalable approaches for climate resilience in water and disaster risk management sectors; using these efforts to enhance the capacities of the institutions across the Indian Himalayan Region (IHR) to plan, implement and mainstream adaptation actions into their programmes and policy frameworks; and disseminating the experiences and lessons at the regional and global level.
Within this programme, SDC has granted a project to FutureWater, together with Utrecht University, The Energy and Resources Institute (TERI), the University of Geneva and a few individual experts. The activities in this project focus on the development and application of climate responsive models and approaches for integrated water resources management (IWRM) for a selected glacier-fed sub-basin system in Uttarakhand and that at the same will find place in relevant policy frameworks paving way for their replication across IHR and other mountainous regions. This will allow the policy makers from the mountain states in India to manage the available water resources in an efficient and effective manner, benefiting the populations depending on these resources.
The combination of future climate change and socio-economic development poses great challenges for water security in areas depending on mountain water (Immerzeel et al., 2019). Climate change affects Asia’s high mountain water supply by its impact on the cryosphere. Changes in glacier ice storage, snow dynamics, evaporation rates lead to changes in runoff composition, overall water availability, seasonal shifts in hydrographs, and increases in extremely high and low flows (Huss and Hock, 2018; Lutz et al., 2014a). On the other and, downstream water demand in South Asia increases rapidly under population growth and increasing welfare boosting the demand for and electricity generation through hydropower. To address and adapt to these challenges integrated water resource management (IWRM) approaches and decision support systems (DSS) tailored to glacier- and snow-fed subbasins are required.
To fulfil the mandate outlined by SDC a framework is presented for IWRM and DSS for Himalayan subbasins consisting of three integrated platforms. (i) A modelling and decision support platform built around a multi-scale modelling framework for glacier and snow fed subbasins, based on state-of-the art and “easy to use” modelling technology. (ii) A stakeholder engagement platform to consult key stakeholders, identify key IWRM issues and co-design a new IWRM plan for Bhagirathi subbasin. (iii) A capacity building platform with on-site training and e-learning modules for the key project components: glacio-hydrological modelling, IWRM and DSS, to ensure the sustainability of the approach and pave the way for upscaling to other subbasins in the Indian Himalayan Region.
The three platforms are designed designed to be flexible, integrated and interactive. Moreover they align with the three outcomes of the project, thus contributing to: develop and validate an integrated climate resilient water resource management approach (Outcome 1); increase technical and institutional capacity in the fields of hydrological modelling, IWRM and DSS (Outcome 2); support the embedding of the IWRM approach tailored to glacier-fed Indian Himalayan subbasins in policies, and provide generic outputs and guidelines to facilitate upscaling to other subbasins in the Indian Himalayan Region (Outcome 3).
The modelling and decision support platform is designed for operation under the data scarce conditions faced in Himalayan catchments, and yields reliable outputs and projections. The modelling toolset covers the Bhagirathi watershed (Figure below) and consists of 3 hydrological models: (i) a high resolution glacio-hydrological model for the Dokriani glacier catchment (SPHY-Dokriani). Key parameters derived with this model are upscaled to (ii) a distributed glacio-hydrological model that covers the Bhagirathi subbasin (SPHYBhagirathi). Outputs of this model feed into (iii) a water allocation model that overlays the SPHY-Bhagirathi model in the downstream parts of the basin, where water demands are located (WEAP–PODIUMSIM Bhagirathi). This modelling toolset is forced with downscaled climate change projections and socio-economic projections to simulate future changes in water supply and demand in the subbasin. On the basis of stakeholder inputs, adaptation options are identified and implemented in the water allocation model for scenario analysis. Thus, socio-economic projections and adaptation options are co-designed with the stakeholders to ensure maximum applicability, and are tailored to the requirements for formulation of the new IWRM plan. The outputs of the modelling toolset feed into the Decision Support System, where they are presented in such a way that they can truly support decision making in this subbasin. Results of the modelling, decision support and stakeholder engagement platforms jointly support the co-design of an IWRM plan for the subbasin. Capacity in glacio-hydrological modelling, IWRM and the use of DSS is built through a combination of on-site training and e-learning; replicable training modules are developed for glacio-hydrological modelling, IWRM and DSS in general and for this particular approach to support implementation and sustainability.
Water and food security are at risk in many places in the world: now and most likely even more in the future, having large economic and humanitarian consequences. Risk managers and decision-makers, such as water management authorities and humanitarian-aid agencies/NGOs, can prevent harmful consequences more efficiently if information is available on-time on (1) the impact on the system, economy or society, and also (2) the probabilities for a failure in the system. EO information has proven to be extremely useful for (1). For looking into the future, considering the uncertainties, novel machine learning techniques are becoming available.
The proposed development is incorporated into an existing solution for providing Drought and Early Warning Systems (DEWS), called InfoSequia. InfoSequia is a modular and flexible toolbox for the operational assessment of drought patterns and drought severity. Currently, the InfoSequia toolbox provides a comprehensive picture of current drought status, based mainly on EO data, through its InfoSequia-MONITOR module. The proposed additional module, called InfoSequia-4CAST, is a major extension of current InfoSequia capabilities, responding to needs that have been assessed in several previous experiences.
InfoSequia-4CAST provides the user with timely, future outlooks of drought impacts on crop yield and water supply. These forecasts are provided on the seasonal scale, i.e. 3-6 months ahead. Seasonal outlooks are computed by a novel state-of-the-art Machine Learning technique. This technique has already been tested for applications related to crop production forecasting and agricultural drought risk financing. The FFTrees algorithm uses predictor datasets (in this case, a range of climate variability indices alongside other climatic and vegetative indices) to generate FFTs predicting a binary outcome – crop yields or water supply-demand balance above or below a given threshold (failure: yes/no).
The activity includes intensive collaboration with stakeholders in Spain, Colombia and Mozambique, in order to establish user requirements, inform system design, and achieve pilot implementation of the system in the second project year. Generic machine learning procedures for training the required FFTs will be developed, and configured for these pilot areas. An intuitive user interface is developed for disseminating the output information to the end users. In addition to development of the forecasting functionality, InfoSequia-MONITOR will be upgraded by integrating state-of-the art ESA satellite data and creating multi-sensor blended drought indices.
This glacio-hydrological assessment delivered river flow estimates for three intake locations of hydropower plants in Nakra, Georgia. The assessment included the calibration of a hydrological model, daily river discharge simulation for an extended period of record (1980-2015), and the derived flow duration curves and statistics to evaluate the flow operation of hydropower turbines. The daily flow calculations for the three sites (HPP1, HPP2 and HPP3) can be used in the hydropower calculations, and to assess the overall profitability of the planned investment, considering energy prices, demand, etc.
In the Nakra basin, glacier and snow model parameters were tuned to obtain accurate river flow predictions. Also, the latest technology of remote sensing data on precipitation and temperature (product ERA5) was used to reduce potential errors in flow estimates. Even though these flow estimates are useful for short-medium term evaluations on profitability of the planned investment, climate change pose a challenge for long-term evaluations. Glacier-fed and snow-fed systems, such as the Nakra basin, are driven by a complex combination of temperature and precipitation. Due to future increasing temperature, and changing rainfall patterns, glacier and snow cover dynamics change under climate warming. This can lead to shifts in the flows, like a reduction in lowest flows, and higher discharge peaks when the hydrological system shifts towards a more rainfall-runoff influenced system (Lutz et al. 2016). This can jeopardize the sustainability of the project on the long-term. To provide a better understanding of future river flows, it is recommended to develop a climate change impact assessment.