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.

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 Sous-Massa basin is located in central Morocco. It represents an arid area that will likely face water resources challenges into the coming decades due to the influence of climate change and socioeconomic development. Indeed, increases in temperatures and decreases in precipitation are anticipated in the Sous-Massa region, alongside more extreme intense precipitation and drought events. It is therefore important the the impacts of climate change on water availability are better constrained to target resilience measures and better prepare for potential future water scarcity.

With the results of this project, IMWI will be able to apply the Water Accounting Plus framework to the Sous-Massa basin, helping to better constrain the likely impacts of climate change on future water availability. This project therefore helps support the targeting and prioritisation of climate resilient interventions which can be taken by the government and other members of the water sector in this area of Morocco.

This project is part of the technical-innovation support provided by FutureWater to ECOPRADERAS, an EIP-AGRI Operational Group led by Ambienta Ing. and co-funded by the EU and the Spanish Ministry of Agriculture. As a general objective, ECOPRADERAS aims to improve the sustainable management of grasslands located at the Alagon Valley (Extremadura, Spain) through: (1) the transfer and implementation of innovative technologies, (2) the identification and strengthening of good cultural practices, and (3) the dissemination of the most relevant information and results among end users.

In the frame of ECOPRADERAS, FutureWater is tasked with the development of an operational monitoring tool able to inform, at the regional scale, on the health status of the grasslands by using satellite data of moderate spatial resolution. The ECOPRADERAS monitor includes the following innovative features:

  • Generation of a categorical index indicative of the health status of grasslands based on the combination of indices of spatial and temporal greenness anomalies.
  • Higher spatial details by using satellite images of moderate spatial resolution (collection of Landsat-8TM of 30 m resolution)
  • Large improvement for collecting and processing large satellite datasets by using the Google Earth Engine cloud-based geoprocessing platform (collection of Landsat-8TM from January 2014 onwards)
  • A user friendly web-mapping interface to visualize outputs

The methodology used by FutureWater uses massive data processing technologies in the cloud (Google Earth Engine) to compute a pixel-based categorical index that result of the combination of a spatial and a temporal anomaly of the greenness index (NDVI). After a local calibration that needs to be adopted, this qualitative index, called the Combined Index of Normalized Anomalies (ICAN) (figure), classifies the status of grasslands in the region of interest into different categories that informs on the health grasslands and how are they being managed. With the ICAN, land managers and local actors can early detect those portions in the landscape in which management practices may pose a risk for the sustainability of the agropastoral system and then would require special attention for improving them.

Logic diagram for computing the Combined Index of Normalized Anomalies (ICAN) in the ECOPRADERAS Monitor.The specific tasks developed by FutureWater included: the definition of a methodological framework for monitor the health of grasslands at the regional scale, the design of a processing and web-mapping platform and its practical implementation in the Alagon Valley (182 km2) from September 2019 to July 2020, and the calibration-validation of the results by comparing outputs with field observations collected in different pilot sites by other project partners.

An evaluation of the results points out to the strength of the methodology. The processing architecture is also easily scalable to other regions and rangeland landscapes. Further improvements have been also envisioned. The ECOPRADERAS Monitor stands as a very powerful tool to guide landscape managers local stakeholders on better decisions.

ECOPRADERAS Monitor at the Alagon Valley (Extremadura, Spain)

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.

In 2016, FutureWater released a new dataset: HiHydroSoil v1.2, containing global maps with a spatial resolution of 1 km of soil hydraulic properties to support hydrological modeling. Since then, the maps of the HiHydroSoil v1.2 database have been used a lot in hydrological modeling throughout the world in numerous (scientific) projects. A few examples of the use of HiHydoSoil v1.2 are shown in the report.

Important input of the HiHydroSoil database is ISRICS’ SoilGrids database: a high resolution dataset with soil properties and classes on a global scale. In May 2020, ISRIC has released the latest version (v2.0) of its Soilgrids250m product. This release has made it possible for FutureWater to update its HiHydroSoil v1.2 database with newer, more precise and with a higher resolution soil data, which resulted in the development and release of HiHydroSoil v2.0.

Soil information is the basis for all environmental studies. Since local soil maps of good quality are often not available, global soil maps with a low resolution are used. Furthermore, soil maps do not include information about soil hydraulic properties, which are of importance in, for example, hydrological modeling, erosion assessment and crop yield modelling. HiHydroSoil v2.0 can fill this data gap. HiHydroSoil v2.0 includes the following data:

  • Organic Matter Content
  • Soil Texture Class
  • Saturated Hydraulic Conductivity
  • Mualem van Genuchten parameters Alfa and N
  • Saturated Water Content
  • Residual Water Content
  • Water content at pF2, pF3 and pF4.2
  • Hydrologic Soil Group (USDA)

Download HiHydroSoil v2.0

The HiHydroSoil v2.0 database can be accessed after filling the brief request form below. A download link to the full dataset will then be provided. The HiHydroSoil v2.0 dataset is organized in two folders, one containing the original data for each of the six depths, and one with the aggregated subsoil and topsoil data. All data layers are delivered in geotiff raster format.

Important! To avoid lengthy download times, the data layers originally consisting of float data type were multiplied by a factor of 10,000, and subsequently converted to integer type. It is therefore required to translate the data to the proper units by multiplying with 0.0001. These steps are also described in the readme file delivered with the data.

Today, FutureWater has released a new high resolution dataset containing global maps for Soil Hydraulic Properties: HiHydroSoil v2.0! It is the second generation HiHydroSoil dataset, after the first release in 2016. HiHydroSoil v2.0 is a definite upgrade of the first version, since it is build with higher quality input layers and with a higher spatial resolution of 250 m.

In 2016, FutureWater released a new dataset: HiHydroSoil v1.2, containing global maps with a spatial resolution of 1 km of soil hydraulic properties to support hydrological modeling. Since then, the maps of the HiHydroSoil v1.2 database have been used a lot in hydrological modeling throughout the world in numerous (scientific) projects. A few examples of the use of HiHydoSoil v1.2 are shown in the report.

Important input of the HiHydroSoil database is ISRICS’ SoilGrids database: a high resolution dataset with soil properties and classes on a global scale. In May 2020, ISRIC has released the latest version (v2.0) of its Soilgrids250m product. This release has made it possible for FutureWater to update its HiHydroSoil v1.2 database with newer, more precise and with a higher resolution soil data, which resulted in the development and release of HiHydroSoil v2.0.

Soil information is the basis for all environmental studies. Since local soil maps of good quality are often not available, global soil maps with a low resolution are used. Furthermore, soil maps do not include information about soil hydraulic properties, which are of importance in, for example, hydrological modeling, erosion assessment and crop yield modelling. HiHydroSoil v2.0 can fill this data gap. HiHydroSoil v2.0 includes the following data:

  • Organic Matter Content
  • Soil Texture Class
  • Saturated Hydraulic Conductivity
  • Mualem van Genuchten parameters Alfa and N
  • Saturated Water Content
  • Residual Water Content
  • Water content at pF2, pF3 and pF4.2
  • Hydrologic Soil Group (USDA)
Saturated Hydraulic Conductivity (m/d) of the Topsoil (0-30 cm).

The HiHydroSoil v2.0 database can be accessed through the FutureWater website (also attached to this news article): https://www.futurewater.eu/projects/hihydrosoil/. After filling the brief request from, a download link to the full dataset will be provided. The HiHydroSoil v2.0 dataset is organized in two folders, one containing the original data for each of the six depths, and one with the aggregated subsoil and topsoil data. All data layers are delivered in geotiff raster format.

Important! To avoid lengthy download times, the data layers originally consisting of float data type were multiplied by a factor of 10,000, and subsequently converted to integer type. It is therefore required to translate the data to the proper units by multiplying with 0.0001. These steps are also described in the readme file delivered with the data.

This month, FutureWater has published an article in the International Water Power & Dam Construction Magazine focusing on the business case for small hydropower (small facilities without significant storage dams) to invest in catchment protection based hydropower. The hydropower sector is showing increasing interest in revenue sharing schemes that promote improved catchment protection activities. 

The article is based on two case studies in Kenya and Tanzania where FutureWater assessed the impacts of various investment portfolios for catchment management activities on the cost-benefits of small hydropower schemes and analyzed the return-on-investment for the hydropower developers. Modeling and satellite data analysis were used, considering climate change and land degradation impacts among others, as input for the return-on-investment analysis.

Interested in the article? Download it here!

The Ridge to Coast, Rain to Tap: Sustainable Water Supply Project (R2CR2T) is an integrated approach to addressing flooding in the Cagayan River basin on Mindanao in the Philippines. R2CR2T is a Public Private Partnership led by VEI together with the partners COWD (Cagayan de Oro Water District), FITC, UTPI/Hineleban Foundation Inc. (HFI), Philippines- and Netherlands Red Cross, Cagayan de Oro River Basin Management Council (CDORBMC), and Wetlands International. R2CR2T is funded by RVO through the Sustainable Water Fund programme.

The Cagayan River Basin is characterized by an upstream mountainous area with steeply sloping terrain towards downstream Cagayan de Oro city. Upstream deforestation and land degradation are known to increase risk of flooding in the city, which is at present already at a high level. One expected outcome of R2CR2T is to have an enabling environment for stakeholders, both private and public sector, to undertake activities related to sustainable land management in the Cagayan River Basin. A Decision Support Tool (DST) for identifying critical areas and approaches for rehabilitation and its benefits regarding flood risk reduction, soil erosion reduction, and enhancing dry season flows, will be developed based on a scientifically-sound hydrological model for the watershed of the Cagayan River.

FutureWater was hired to advise on the development of the DST and hydrological model, critically review the quality and applicability of (intermediate) outputs by the local team and their service providers, and provide an external and international ‘helicopter view’ on the eco-hydrological aspects of the project. In a general sense, FutureWater supports the R2CR2T project team to maximize the impact of the DST will have for the CDORB region and stakeholders.