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.

The training aimed at building and enhancing capabilities of the participants in environmental and hydrological monitoring and modeling and was funded by the Orange Knowledge Program of Nuffic. It gave the participants valuable and necessary knowledge on IWRM and it provided the participants with relevant hands-on experience and cutting-edge knowledge on innovative solutions in water allocation modeling and earth observation technologies.

Due to the ongoing COVID-19 situation, the training was held online using our eLearning platform FutureWater Moodle School. The beauty of this platform is that all online sessions can be recorded and they are still available for the participants to have another look at it. All material (exercises, manuals etc.) developed during the course is also still available on our FutureWater Moodle School. The Rwanda Water Resources Board is recruiting new staff in the future and this new staff will also have access to all material.

Topics covered in the training are:


  • Build a WEAP model from scratch
  • Work with WEAP’ Basic Tools
  • Create and run Scenarios in WEAP
  • Extract water balances from WEAP
  • Generate a hydrological model using WEAP’ Automatic Catchment Delineation Tool

Google Earth Engine:

  • First glance at JavaScript Syntax
  • Explore and visualize Landsat 8 Imagery
  • Create charts with Monthly NDVI Values
  • Use WaPOR for Water Productivity calculations
  • Work with CHIRPS Rainfall data
  • Evaluate the water balance of a catchment


A large Dutch consortium has joined in the project “Dutch network on small spaceborne radar instruments and applications (NL-RIA)”, led by TU Delft. The objective is to bundle the radar-related knowhow available in The Netherlands, and fill the knowledge gaps, in order to boost SmallSat radar-based Earth Observation technology. The focus of the project is on microwave remote sensing.

A key advantage of microwave remote sensing compared to optimal imagery is the all-weather/day and night observation capability, which greatly enhances the observation opportunities. This includes the ability to observe through clouds. Microwave remote sensing system include passive (radiometers) and active ones (radar altimeters, Synthetic Aperture Radars, precipitation radars, scatterometers, etc). This study will focus on altimeters and thus on active radar.

Continuous monitoring of fresh water bodies like rivers, lakes and artificial reservoirs, is important for water resources management, and thus for the principal water users in river basins, such as domestic, industrial and irrigation demands. Also, potentially there can be applications of this information for flood early warning, renewable energy (hydropower) and for the transport sector (shipping).

For the management of fresh water resources at the basin level, information on the status of surface water bodies is critical. In many areas in the world however, this information is scarce. Especially in developing countries, water level measurements of lakes and reservoirs are hardly available. In Europe, ground-based measurements are more common but sometimes performed by the entity operating the reservoir or river abstraction, and thus not available to water resources managers for the purpose of water resources planning. Also in transboundary (international) river basins, ground-based information is often not shared, so satellite-based information can be of high value for certain end-users (Zhang et al., 2014).

Altimeter measurements of rivers, lakes and artificial reservoirs and be used for two purposes:

  • Strategic planning of water resources, which requires water resources assessments to support for example river basin management plans
  • Operational management of water resources, for example for the hour-by-hour operational management of water release from reservoirs for hydropower.

The study performed by FutureWater focused on the first type of applications: strategic planning and decision making on the long-term. Especially for this purpose, satellite-based altimeter data has the potential to fill an important information gap. For the second type of applications: operational water management and short-term decision making, typically ground-level water level sensors are more cost-effective than satellite-based solutions.

Key results

From the analysis performed by FutureWater and based on literature review, the following key considerations are proposed for shaping a low-cost altimetry mission useful for assessing inland water bodies and water resources planning:

  • Altimetry information can be extremely useful for complex systems as for example swamps, where data on surface water levels and flows are scarce, as often the case in developing countries. Altimetry data can support the management and conservation of these systems that provide key ecosystem services for people and the environment.
  • To build hydrological models for water resources assessments, historic data is required to calibrate and validate the tools. To capture the variability in water resources systems and thus perform a successful validation, a period of around 10 years of altimetry data is recommendable.
  • A revisit frequency of 1 month is typically sufficient for water resources assessments. Higher frequencies are normally not necessary as they may only lead to minor improvements in the performance of the modeling tools. Lower frequencies (e.g. two months) are not sufficient to capture the seasonal pattern adequately.
  • The required accuracy is highly dependent on the characteristics of the water body and is a function principally of the annual dynamics in storage, and the depth-storage relationship. In case study I, with a very large but shallow water body, an accuracy of approx. 10 cm was considered necessary. For case study II, with a smaller and deeper water body, it was found that up to an error of 180 cm the performance of the model was not significantly affected.
  • The accuracy requirement can possibly also be expressed as a percentage of the annual variability in water levels, of a particular water body of interest. For example:
    • In case study I, annual increases of approximately 1 m are common. The accuracy requirement is approximately 10% of this (10 cm)
    • In case study II, water level increases or decreases within a year of around 15 m are possible. Also here, the accuracy requirement is in the order of 10-15% of this annual variability.
  • Finally it has to be noted, that the usefulness of the altimetry data is also dependent on the availability and quality of other datasets necessary for the hydrological modeling. These datasets are primarily the depth-volume relationship, ideally from in-situ measurements but possibly extracted from satellite data (Duan and Bastiaanssen, 2013b); as well as discharge data upstream or downstream of the water body. Without these data sources it is not possible to establish a reliable water balance of the water body.

In 2017, AFD approved to finance the Water Resources Management and Agro-ecological Transition for Cambodia “WAT4CAM” Program Phase 1. This program will contribute to reduce poverty, develop the economy and reduce the vulnerability of rural populations to climate change by implementing a hydro-agricultural infrastructures rehabilitation program through an integrated approach, targeting the whole chain of water resources management, water services and agricultural production.

The strategy is to achieve intensification of cropping, modernization and climate smart practices to provide farmers with secure access to water. This is a challenging objective and a good understanding of the hydraulics of water flows in dry and wet season is needed. A consortium led by FutureWater was hired to perform WAT4CAM subcomponent 3.1, which concentrates on providing this understanding of both flood and dry season flows, demands and balance in the Preks intended for rehabilitation.

The initial stages of the project include the identification of current data, models and previous work, as well as a field survey with stakeholders. This information will be used to create an accurate and reliable modelling ensemble that makes maximum use of existing capacity in Cambodia. In addition, the consortium will use satellite-derived data products to (i) provide input to the simulation models, and (ii) calibrate and validate model results. Various sources of satellite imagery will be explored to map floods and irrigation practices, to implement an integrated “space hydrology” approach.

The modelling and knowledge generation from this study must support the other WAT4CAM components for the successful implementation of the Prek irrigation system improvements. The modelling itself is thus not the ultimate purpose, but rather the understanding and knowledge imparted to MoWRAM and the other components of the WAT4CAM program.

FutureWater’s role in the project is the overall project coordination and administration, as well as the implementation of satellite remote sensing and climate change analyses in support of the modelling components.

The Directorate of Water Resources and Improvement of River Systems (DWIR) is one of the key government agencies in the field of integrated water resources management in Myanmar. DWIR consists, next to its national head offices, of twelve regional offices. Regional DWIR offices concentrate on flood protection by maintenance of the river and its embankments.

National-level DWIR staff attended previous trainings on Google Earth Engine (GEE) organized by FutureWater and HKV in Myanmar, during which GEE was identified as a particularly relevant tool to support DWIR’s mission. FutureWater and HKV have also successfully collaborated in a Partners for Water project focusing on operational rainfall monitoring. In particular, regional-level DWIR staff can benefit from using GEE for successfully complying with their mandate concerning design and practical implementation of riverbank and flood protection measures. They need to work with geospatial data on historical river morphology, flood extent, as well as hydrological baseline data on e.g. rainfall and evapotranspiration. With the overall capacity of the regional-level staff somewhat lower than the national level staff, this TMT aims to achieve a great leap forward by acquainting regional staff with geodata access, analyses and interpretation using GEE, to benefit the quality of flood protection measures and overall water safety in Myanmar.

The training is implemented by a mix of Dutch and Burmese trainers, who provide a program consisting of a month on-distance support, a two-and-a-halve-week in-country training followed by a period of 6 months of regular on-distance support. Following the COVID-19 pandemic, in-country training components are converted to an eLearning approach.

Aim of the training

The training will enhance capacity of Egerton educational staff in accessing and using innovative data and tools in the public domain, to analyse crop performance and irrigation management. During the training, university participants will be specifically supported in developing course modules based on the skills gained. To maximize the impact in addressing the need for increased quality of higher education in the agricultural sector, representatives from other institutes, ministries and private sector companies will also be invited. The training will allow the staff to gain advanced skills in working with flying sensors (drones) and satellite-derived data to support agricultural and water-related challenges, such as pests and diseases, water efficiency in agriculture to enhance food security, and drought monitoring. They will acquire insight in and knowledge on analyzing the performance of crops, making the right intervention decisions and giving irrigation advice. For public sector representatives, the training objective is to obtain skills that can be directly and sustainably implemented in their respective organizations.

Overall, the Kenyan society at large will benefit from improved food security provided by well-educated agricultural researchers and professionals. This project forms an important step in the capacity building strategy as it focuses on strengthening the universities and preparing them to provide high quality education to the future generation agronomists and agricultural managers, as well as upgrading the knowledge of current professionals.

The training costs of four stages: an online training course, followed by an in-country training program, symposium and post-training support.

Stage 1: eTraining course

The first stage involved a weekly online training course that will start in January 2021, with a total of six sessions in six weeks. Participants will be consisting of University and TVET faculty members, university students, PhD candidates, researchers, Kenya Agricultural & Livestock Research Organization (KALRO) staff members, Agriculture Extension Staff from the County Government who are already involved in agricultural research and training and other private sector partners. Staff members from the university will be those that are involved in teaching agronomy, horticulture, agriculture engineering and agriculture extension courses and programs, i.e., soil, nutrient and water management, dryland farming, irrigated agriculture and crop protection. Non-university attendants will be technical staff who are close to the decision makers within their organizations. This will enhance the impact of the training by embedding the use of flying sensor and satellite-derived data for agriculture within these organizations and make sure that Kenya will pursue its activities in making use of this kind of information.

This first stage of the training course will be online and will focus on:

  1. Real Water Savings in Agricultural Systems including potential field interventions
  2. The use of WAPOR to access remotely sensed derived data
  3. The use of flying sensors (drones) in agriculture

The course will end with a test and evaluation and graduates will receive a certificate.

Stage 2: Targeted in-country training

After the first stage training a second in-country training will take place with a smaller group, focusing on the use of drones in agriculture. Here a selected group of 12 to 18 members will be trained. Focus will be on staff with lecturing responsibilities, to ensure impact on higher education provision and transfer of the new skills to students.

The in-depth training will consist of:

  1. Operating flying sensors manually and automatic, the processing of the collected data using open source software, interpretation and the subsequent decision making (recommendations to increase productivity) for (smallholder) farmers and actors
  2. Use satellite derived (precipitation) products to run crop growth models to provide advice on when and how much to irrigate in agricultural fields

Participants will work on hands-on exercises related to crop performance analyses, water demands and crop growth modelling. Application of the new skills will be further stimulated by assigning the participants clear, tailor-made goals at the end of the second training session, to be worked on during the distant-support period.

Stage 3: Symposium/knowledge sharing

Right after the second training session, a symposium will be organized for a larger audience including the superiors/managers (who most of the times are the final decision makers) of the training participants and representatives of similar organizations. During this knowledge sharing event, trainees and trainers will actively provide contributions to showcase the newly gained skills and their added value to the respective institutions and the Kenyan agricultural sector in general. By acquainting the responsible decision makers in these organizations with the potential applications of flying sensor and satellite-derived data relevant to them, this event will be crucial in ensuring a sustainable impact of the TMT.

Stage 4: Post-training support

In this period, progress will be actively monitored and the trainers will provide post-training support to the participants. The support will be both remotely (e.g. through Skype) by the Dutch training providers but also in-person by ThirdEye Kenya staff visiting the participants for Q&A sessions and to evaluate the implementation of the skills they obtained.

La Sierra Nevada de Santa Marta, declarada Reserva de la Biosfera por la UNESCO, es un complejo montañoso aislado de aproximadamente 17.000 km², apartado de la cadena de los Andes que atraviesa Colombia. La Sierra Nevada tiene el pico costero más alto del mundo (5.775 m sobre el nivel del mar) a solo 42 kilómetros de la costa del Caribe. La Sierra Nevada es la fuente de 36 cuencas hidrográficas, lo que la convierte en la principal «fábrica de agua» regional que abastece a 1.5 millones de habitantes, así como vastas áreas agrícolas en las llanuras circundantes utilizadas principalmente para el cultivo de banano y palma aceitera. Los principales problemas por resolver en estas cuencas son: i) Disminución de la disponibilidad de agua para riego, ii) Disminución de la disponibilidad y calidad del agua para consumo humano, iii) Aumento de la salinización de aguas subterráneas y suelos, iv) Aumento de la incidencia de inundaciones.

Este proyecto es un estudio de factibilidad sobre la adopción de técnicas de riego más eficientes por parte de los productores de palma aceitera en la cuenca del río Sevilla (713 km²), una de las cuencas más relevantes en la Sierra Nevada. El objetivo general es identificar el entorno local a nivel de cuenca hidrográfica, los factores limitantes y las intervenciones adecuadas en fincas de palma aceitera para mejorar el uso del agua. Se desarrolló una fase de preparación e implementación que incluyó una evaluación del clima, la disponibilidad hídrica, la amenaza de sequía, las características del suelo, el uso de la tierra y la topografía. Se caracterizaron las variedades de palma aceitera, y las prácticas de campo (por ejemplo, manejo de nutrientes y prácticas de riego), y se determinaron las necesidades de agua de los cultivos. Además, se evaluaron los costos y beneficios asociados a la implementación de tecnologías de riego eficientes como ferti-riego y métodos de cosecha de agua. Se evaluaron ubicaciones potenciales, riesgos y oportunidades para la captación de agua con la idea de almacenar agua en la época lluvioso para poder utilizar el recurso de manera eficiente en la época seca. Se utilizó una variedad de conjuntos de datos SIG y satelitales (por ejemplo, CHIRPS, MODIS-ET, MODIS-NDVI, HiHydroSoil) para evaluar las condiciones ambientales, y los socios colombianos Cenipalma y Solidaridad proporcionaron datos e información local para generar una evaluación integral a nivel de cuenca y de finca. La expectativa es que productores de palma aceitera puedan adoptar técnicas de ferti-riego y cosecha de agua para reducir el déficit hídrico y pérdida de fertilizantes para lograr una producción ambientalmente más sostenible.

The Paris Agreement requests each country to outline and communicate their post-2020 climate actions, known as their NDCs. These embody efforts by each country to reduce national emissions and adapt to the impacts of climate change. As ratifying parties, Armenia, Georgia and Uzbekistan must therefore outline how they intend to implement their NDCs and provide information on what the focus of this spending will be. To support this effort, the Asian Development Bank (ADB) is implementing a knowledge and support technical assistance cluster which will help enhance capacities of developing member countries (DMCs) in meeting their climate objectives by assisting in refining and translating nationally determined contributions (NDCs) into climate investment plans.

In this work package, ADB aims to support Georgia, Armenia, and Uzbekistan with the implementation of their NDCs through developing urban climate assessments (UCAs) and mainstreaming low carbon and climate resilience measures into urban planning processes. FutureWater contributed to this effort by supporting knowledge creation in relation to climate change and adaptation which will help each country to make more informed climate investment decisions.This was accomplished by conducting analysis of downscaled climate model ensembles for different climate change scenarios and synthesising data related to urban climate risk.

Climate change trend assessments were conducted using the NASA-NEX downscaled climate model ensemble combined with ERA-5 climate reanalysis products. To determine climate risk at the urban level, a number of openly available datasets were analysed and compiled using a spatial aggregation approach for 16 cities in the area. Results were presented as user-friendly climate risk profiles at the national and urban scales, allowing for insights into climate trends and risks over the coming century. These will be presented to non-expert decision makers to help support Armenia, Georgia and Uzbekistan develop targeted and informed NDCs.