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.

In Angola, more and better-quality data is required to improve crop suitability assessments over large extensions of arable land to ensure sustainable food and income security. For example, environmental data on soil texture, soil water storage capacity, vegetation growth, terrain slopes, rainfall and air temperature are key to develop reliable crop suitability assessments. These datasets are available from state-of-the-art satellite-based products and machine learning observations (de Boer, 2016; Funk et al., 2015; Hengl et al., 2014, 2017). The benefit of these data products is that data can be obtained for any province, municipality, or farm in Angola. On top of that, data can be shown in maps to easily visualize spatial variation and identify the most suitable location and area to grow desired crops. Land-crop suitability maps are obtained by calculating a weighted average of the environmental variables that influence crop growth (e.g. rainfall, air temperature, soil water storage capacity), providing an integrated and complete assessment on where to plant. Also, potential crop yields are determined for desired cropping seasons using the FAO AquaCrop model to provide more information about potential income.

Irrigated agriculture in Angola has been developed in commercial farms using mainly central pivot and drip irrigation systems. The installation of new irrigation systems is foreseen in large extensions of land over 5000 hectares. Irrigated agriculture results in higher crop yields and allows higher incomes to farmers. However, commercial farms must invest in high energy supply to operate irrigation systems with water pumping stations. The challenge for irrigation system operators is to know exactly when and how much to irrigate during the cropping season. If better information about irrigation volumes and intervals are provided a significal reduction in energy costs could be achieved. The objective is to predict irrigation demand volumes during the cropping season and provide a user-friendly decision tool to irrigation operators. To achieve this, weather forecasts, remote sensing, and the SPHY model will be used.

There is great potential for hydropower in Georgia, and this natural resource is likely to be increasingly utilised for power generation in the future. With the escalating demand for energy, government authorities are keen to harness renewable energy from the country’s main rivers. Often these projects aim at remote communities for which connecting to the national power grid is expensive. Hence, local hydropower production is an attractive and sometimes viable option. Critical is to conduct accurate feasibility assessments for hydropower generation at the different potential sites of interest considering climate change impacts. This work is a glacio-hydrological assessment of the expected river discharge at the planned hydropower sites in the Mestiachala river, Georgia.

Based on the requirements of the project, the Spatial Processes in Hydrology (SPHY) cryospheric-hydrological model was selected for the assignment. SPHY is a hydrological model that simulates the runoff at any location within the basin at a daily timescale. SHPY is ideal to assess glacier and snow influence in the river discharge and evaluate the impact of climate change. SPHY was used to predict the river discharge for the extended period of record and provide enhanced flow duration curves for hydropower assessment. In addition, total runoff components were quantified such as snow and glacier runoff.

This glacio-hydrological assessment delivered river discharge estimates for intake locations of two planned runoff river hydropower plants near Mestia, Georgia. The assessment included the calibration of a hydrological model, daily river discharge simulation for an extended period of record (1980-2015), climate change scenarios, and the derived flow duration curves to evaluate the flow operation of hydropower turbines. In addition, total runoff components were quantified such as snow and glacier runoff.

The daily river discharge was simulated at the two intake locations for two future periods (for the end of the concession period and for the end of century period) considering two climate change scenarios (RCP4.5 and RCP8.5). Hydrological model simulations were developed using future precipitation and temperature predictions and future glacier extent predictions. The climate change scenarios provide an evaluation of flow operation uncertainty. The daily flow calculations for the two sites can be used in the hydropower calculations, and to assess the overall profitability of the planned investment, taking into account energy prices, demand, etc.

The SREB is part of the Belt and Road Initiative, being a development strategy that focuses on connectivity and cooperation between Eurasian countries. Essentially, the SREB includes countries situated on the original Silk Road through Central Asia, West Asia, the Middle East, and Europe. The initiative calls for the integration of the region into a cohesive economic area through building infrastructure, increasing cultural exchanges, and broadening trade. A major part of the SREB traverses Asia’s high-altitude areas, also referred to as the Third Pole or the Asian Water Tower. In the light of the planned development for the SREB traversing the Third Pole and its immediate surroundings, the “Pan-Third Pole Environment study for a Green Silk Road (Pan-TPE)” program will be implemented.

The project will assess the state and fate of water resources in the region under following research themes:

1. Observed and projected Pan-TPE climate change
2. Impacts on the present and future Water Tower of Asia
3. The Green Silk Road and changes in water demand
4. Adaptation for green development

For the two study catchments, satellite imagery and field observations were combined to perform a land degradation assessment and to identify trends. Secondly, baseline hydrological conditions were assessed using a hydrological simulation model. Future changes in hydrology and hydropower generation were evaluated by running the biophysical model for a Business-as-Usual scenario, accounting for land degradation trends, changes in water use, and climate change.

Subsequently, the impacts of three catchment investment portfolios (low, medium, high) containing different catchment activities were quantified with respect to the BaU scenario. Benefits and costs were analysed for the hydropower developers to evaluate whether it makes sense for them to invest in improved catchment activities. For one of the catchments this is clearly the case (Kiwira, Tanzania).

The analysis shows that the impacts of climate change on revenue from hydropower are in the same order of magnitude as the other negative anthropogenic factors: increased domestic water use demand in the catchment and land degradation due to poor conservation of natural areas and poor agricultural practices.

At the outlet of the 60 km-long Muhazi Lake there is currently an earth fill dyke which is prone to overtopping or even complete collapse during the wet season. The dyke’s instability causes a potential hazard to inhabitants of the downstream Nyabugogo area, a commercial hub in Kigali town, which threatens lives and properties.

The project consisted of a feasibility and a design phase. For the project, a large number of field- and desktop-tasks were performed. Field-activities included a topographical survey of the project immediate area for design purposes, a detailed mapping of areas around the lake shore sensitive to changes in water level, and a Geotechnical investigation programme due to the complexities related to the peat-soils.

FutureWater conducted a full hydrological assessment of the Lake Muhazi catchment, including the study of flood flows to provide design values, considering climate change, and routing of the lake. Besides, a detailed water resources assessment was performed using WEAP and a study on the operational rule curves, future demands, among others.

Muhazi Lake and dam.

The outputs of this analysis fed directly into the design of the Dyke (serving as a dam): the dimensions and outlet structures, performed by the lead partner (Z&A). Besides the project included an Environmental and Social Impact Assessment

Stakeholders were involved actively during all phases of work and several training and capacity building activities were organized.

There is interest to develop run-off river hydropower plants in a watershed in southwestern Georgia: a cascade of two projects of around 25 MW each. Before the actual development phase can start, a hydrological assessment is necessary to assess expected flows at the two locations with higher accuracy than currently available from limited flow measurements.

FutureWater was contracted by the developers to undertake an assessment of the expected daily flows at the two site locations , based on satellite data and hydrological modelling. Only very limited streamflow data were available, so the assessment was based mainly on hydrological modelling of the basin upstream of the points of interest. Principally global datasets were used for the input requirements of the hydrological modelling. Validation of the model was done using limited recent streamflow data available and satellite-based snowcover measurements. The principal output of the work are daily flows and a flow duration curve, based on model simulations. The flow duration curve includes confidence bounds based on the uncertainties that can be expected originating from data and model parameters.

From this hydrological assessment, a number of recommendations are put forward that aim at increasing the level of accuracy in the outcomes and narrow the uncertainty range for the following feasibility stage. Recommendations are done for data improvements, model improvements and field validation.Outcomes of this study will be used by the developer to analyse the hydropower potential and evaluate the economic feasibility.

The project should turn this renewable energy opportunity into a source of economic empowerment for the region and a sustainable source of electricity for the people living in North Sumatra. A pre-feasibility study is undertaken to the expected flows at the intake of the proposed Tripa hydro-electric power plant to indicate whether a more detailed feasibility study is feasible.

For the analysis of the expected flow at the intake a hydrological model, called HEC-HMS is used. This hydrological model simulates rainfall-runoff at any point within a watershed given physical characteristics of the watershed. The model is freely available, somewhat less data demanding, and easy to apply. The outputs of the model are analysed by means of streamflow hydrographs, and flow duration curves that serves as a basis for economic feasibility studies to the capacity of the proposed power plants. In addition, flood flows with recurrence intervals up to 10.000 years are analysed.

Project description

The groundwater discharge of irrigation return flows to the Mar Menor lagoon (Murcia, SE Spain), the largest coastal lagoon in Europe, is among one of the possible causes that would explain the high levels of eutrophication (hypereutrophication) and the several algal blooms accounted in this lagoon ecosystem in the last years. Previous studies, led and/or participated by FutureWater staff (e.g. Contreras et al., 2014; Jiménez-Martínez et al., 2017) suggest that the contribution of groundwater discharges from the Quaternary aquifer to the Mar Menor would reach values much higher than the ones officially recognized.

The construction of subsurface drainage system to intersect the groundwater flows in the surroundings of the lagoon is one of the potential solutions proposed to reduce the load of polluted groundwaters that reach the Mar Menor (Figure 1). Once pumped, these waters can be again reused for irrigation after a desalination and denitrification treatment. A large network of subsurface drainage channels are being currently operated by the Arco Sur-Mar Menor Irrigator Association (Arco Sur IA).

Flows and relationship between the Campo de Cartagena Quaternaty aquifer and the Mar Menor lagoon with (left panel) and without (left panel) a subsurface drainage system.

The Arco-Sur IA has commissioned FutureWater, in collaboration with Hydrogeomodels, this project in order to evaluate the usefulness of these infrastructures, and to explore the possibilities of extending them to the rest of the Campo de Cartagena region. The use of numerical modelling to simulate the groundwater dynamics in the Quaternary aquifer, and to quantify the spatial patterns of groundwater discharge to the Mar Menor lagoon would help to demonstrate the effectiveness of these type of infrastructures, but also to evaluate the best locations and exploitation regimes possible to reduce the discharges to the Mar Menor without compromising the provision of other ecosystem services (e.g. ecological status of coastal wetlands).

The development and calibration of the hydrogeological model for the Quaternary aquifer of the Campo de Cartagena has been rested on an intense collection of all the data available in the region, and their integration with the most advanced hydrological and hydrogeological simulation techniques. This hydrogeological model is considered a key tool to support decision making, and to evaluate the potential effectiveness of different water management strategies proposed for the region (pumping batteries, drainage networks), but also for assessing the potential impacts that would emerge due to land cover and climate change scenarios.

Objective and Methods

The objective of this study is to quantify the water balance in the Campo de Cartagena, to simulate the groundwater flow regime in the Quaternary aquifer, and to evaluate the spatial pattern of groundwater discharge to the Mar Menor lagoon for average and extreme hydrological conditions, through the calibration and implementation of a hydrogeological model.

The project has been organized into four tasks (Figure 2): 1) collection and processing of input data, 2) hydrological modeling, 3) hydrogeological modeling, and 4) reporting and and outreach activities.

Methodological diagram and execution phases.