“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.

Het doel van deze berekeningen was om uitsluitsel te kunnen geven over de nut en noodzaak van de geplande bergingsgebieden ter invulling van de wateropgave uit 2009. Met behulp van een Sobek-model zijn verschillende scenarioberekeningen uitgevoerd waarbij waterstanden, afvoeren en NBW-knelpunten zijn vergeleken onder het huidige en toekomstig klimaat en met en zonder integratie van bergingsgebieden.

De werkzaamheden bestonden onder meer uit:

  1. Toetsing van afvoer en waterstanden op kritieke locaties voor het klimaatscenario bij verschillende herhalingstijden (NBW-toetsing voor toekomstig klimaat),
  2. Vergelijking van NBW-knelpunten onder het huidige en toekomstige klimaat,
  3. Integratie van bergingsgebieden in het Sobek model en analyse van de impact op waterstanden, afvoer en toekomstige NBW-knelpunten (resultaat nut en noodzaak bergingsgebieden: antwoord op het LBW-vraagstuk),
  4. Een eerste inschatting van kritieke locaties langs de overige keringen voor de verschillende scenarios (hoge resolutie vergelijking van waterstanden en keringenhoogtes) en
  5. Een vergelijking van de resultaten met een aantal eerder uitgevoerde studies.

Tijdens het project is de NBW-toetingsmethode, die in 2020 was ontwikkeld door Arcadis, (verder) geautomatiseerd, zodat de methode sneller en voor andere vergelijkbare projecten binnen Vechtstromen kan worden toegepast. Op basis van de uitkomsten uit de berekeningen kon een duidelijk advies worden gegeven over de nut en noodzaak van de voorgestelde bergingsgebieden uit 2009.

Meer informatie over de methode rondom de normering van regionale wateroverlast (NBW / LBW) die wordt gehanteerd door waterschap Vechtstromen is te vinden op de volgende website: https://www.vechtstromen.nl/over/klimaat/wateroverlast/normering/werkt-normering/

 

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 (WEAPPODIUMSIM 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.

Overview of the Bhagirathi sub-basin. The inset on the right shows the Dokriani glacier watershed

 

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.

Recently, the Central Asia Regional Economic Cooperation (CAREC) Program introduced agriculture and water as a new cluster in its strategic framework. Recognizing the complexities of the water sector and the existing landscape of cooperation activities, the strategic framework proposes a complementary approach that uses the strengths of CAREC to further promote dialogue on water issues. A scoping study was commissioned, supported by the Asian Development Bank (ADB), to develop a framework for the Water Pillar for further consideration by the governing bodies of CAREC. It was agreed that the initial focus of the Water Pillar should be on the five Central Asian states with consideration given to expanding to other CAREC member countries over time.

The objective of the study is to develop the scope of a Water Pillar Framework that includes a roadmap of national development interventions for each of the five Central Asian Republics that responds to the prevailing challenges and opportunities in water resources management.

The framework will be derived from three specific outputs:

  • Output 1: Projection of future availability and demand for water resources for the Central Asia region up to 2050 including implications of climate change.
  • Output 2: Identification of future water resources development and management opportunities in the form of a sector specific framework for water resources infrastructure taking into consideration sustainability issues through a comparative assessment of cost recovery mechanisms and operation and maintenance (O&M) practices.
  • Output 3: Preparation of a framework for policy and institutional strengthening that addresses common themes and issues related to national water resources legislation and the capacity and knowledge development needs of water resources agencies with an emphasis on economic aspects and sustainable financing.

For this work, several consultants were recruited. FutureWater provides key inputs on the climate change and water resources aspects, including desk review, stakeholder consultations across the five regions and across all sectors, and analysis of climate change risks and identification of adaptation options that have a regional dimension and can be taken up through regional or bilateral cooperation.

Several catchment plans have been already developed through the Dutch-funded Water for Growth programme. FutureWater played a paramount role in this programme by developing the water allocation models (WEAP) at national level and for several priority catchments. Moreover, FutureWater provided capacity building to local experts and staff on using and further developing and fine-tuning those WEAP models.

The current project aims at developing two catchment plans, for:

  1. Mukungwa catchment
  2. Akagera Lower catchment

These catchments were included in a previous national-level water resources allocation study performed by FutureWater. Four catchments were selected from this national level assessment to make catchment-level WEAP models to inform the catchment plans. A next step for the Rwanda Water Resources Board (RWB), is to prepare catchment plans for the above two catchments, for which this project will be instrumental.

For the two catchments, this study aims at (1) providing detailed information on available and renewable water resources, both surface and groundwater, and their spatial and temporal variations; and (2) to map and quantify water uses and water demands, to develop water allocation models that can be used as tools to manage operationally and plan the catchments in a sustainable way. The scenarios (options) assessed can also be essential input into the catchment management plan. This study will produce water allocation models based on current and potential uses in a time-horizon of 30 years.

The project is carried out in collaboration with a team of local experts and one of our partners Dr. Kaan Tuncok as a team leader.

Mukungwa and Akagera Lower catchments

This hydrological assessment delivered river flow estimates for an intake location of a potential hydropower plant in the Lukhra river, Georgia. The assessment included a tuning of a hydrological model based on knowledge of neighboring basins, daily river discharge simulation for an extended period of record (1989-2019), and the derived flow duration curves and statistics to evaluate the flow operation of hydropower turbines. The daily flow calculations for the site can be used in the hydropower calculations, and to assess the overall profitability of the planned investment, considering energy prices, demand, etc.

In the Lukhra basin, 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-Land) 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. Snow-fed systems, such as the Lukhra basin, are driven by a complex combination of temperature and precipitation. Due to future increasing temperature, and changing rainfall patterns, 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.

Kyrgyzstan is a highly mountainous country with relatively high precipitation in upslope areas. This, alongside the development and deforestation of basins to make way for industry and agriculture means that land has become increasingly degraded and vulnerable to erosion over recent decades. Reservoirs in the country provide access to water resources and energy in the form of hydropower, but are highly susceptible to sedimentation by eroded material. Sedimentation necessitates increased maintenance costs, reduces storage capacity and disrupts hydropower generation. It is therefore proposed that landscape scale restoration measures (e.g. tree planting) can provide key ecosystem services by reducing vulnerability to erosion and decreasing sediment delivery to reservoirs. This project therefore identifies highly degraded areas of land and determines in which of these interventions are possible. With the outcomes of this study, the World Bank – in partnership with the government of Kyrgyzstan – can prioritise investments in terms of landscape restoration efforts. The outcomes of this project will therefore reduce maintenance costs for reservoirs and contribute to the afforestation and restoration of multiple areas in Kyrgyzstan.