De Gezondheidsdienst voor Dieren (GD) heeft in de afgelopen jaren een analyse van leverbotbesmettingen uitgevoerd. Dit onderzoek heeft laten zien dat verschillende omgevingsfactoren een rol spelen zoals grondwaterstand, neerslag, temperatuur en bodemtype. Daarnaast is op basis van landsdekkende bodemvochtschattingen door FutureWater vastgesteld dat ook bodemvocht en leverbotbesmettingen gecorreleerd zijn, wat verklaard wordt doordat de leverbotslak in vochtige omstandigheden het beste gedijt. De GD geeft jaarlijks een leverbotprognose uit op basis van modelresultaten. Op basis van de eerdere onderzoeksresultaten heeft de GD sinds enkele jaren ook voorspellingen van bodemvocht in haar model opgenomen, welke jaarlijks door FutureWater worden geleverd voor elk postcodegebied in Nederland.

In het huidige project wordt een ontwikkelingsslag toegepast door het gebruik van de meest recent beschikbare datasets in het hydrologische model SPHY, om zo historische bodemvochtdata te leveren met een 100 x 100 m (1 ha) resolutie voor de periode van 2012 t/m 2021. Deze gegevens worden door de Gezondheidsdienst voor Dieren gebruikt om meer inzicht te verkrijgen in het risico op diergezondheidsproblemen die door klimaat worden beïnvloed.

The new project, with the name “Consultancy Services for Integrated Strategic Water Resources Planning and Management for Rwanda” has the general objective to develop integrated strategic water resources plans and management guidelines in order to meet Rwanda’s National Strategy for Transformation (NST1) and Vision 2050 targets. Specifically, the assignment will:

  1. Assess and evaluate the availability and vulnerability of the country’s water resources up to around 2050 taking climate change into consideration,
  2. Formulate sustainable and environmentally friendly water resources investment plans towards the year 2050 and guidelines for green development for each 20 Level two catchments,
  3. Prepare a revised water resources policy that is in line with water security and SDG 6,
  4. Carry out a cost benefit analysis of the proposed investment plans and prepare quick win projects

In order to meet this objective five tasks have been defined. The main activities of those Tasks are:

  • Task 1 (detailed hydrological assessment) will result in the water availability per sub-catchment up to 2050. This task is technically oriented and will use available data and models as developed over the last decade by various studies.
  • Task 2 (detailed water allocation assessment) will address water needs for the various users and will result in water needs up to 2050. This task is technically oriented and will use available data and models as developed over the last decade. It is expected that this component will need major upgrades compared to previous studies.
  • Task 3 (strategic water resources conservation and development) will rely on Task 1 and Task 2 and can be considered as the scenario analysis task. Based on various projections water availability and demands will be evaluated. Focus will be on dry years and dry periods as it is known that the overall water resources are in general sufficient for Rwanda. From the evaluation, a selection of potential artificial and strategic storage development sites will be done.
  • Task 4 (strategic water resources management options) will be stakeholder driven where stakeholders include technical water experts as well. Based on the results of Task 3 various options will be discussed and most likely some refinement of Task 3 (scenario assessment) is needed. The latter might include different priority settings fine tuning of demands and refinement of strategic storage development sites.
  • Task 5 (revised national policy for water resources management) will focus on defining new policy statements and actions informed by the results from the previous tasks and developing a new water resources policy that will guide the country towards achieving the NST1 and Vision 2050 targets.

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.

We are excited to announce that our high resolution dataset with global maps for Soil Hydraulic Properties HiHydroSoil v2.0 is now available on Google Earth Engine! 

It’s made available through the github page “Awesome GEE Community Datasets” by Samapriya Roy. A sample code on how to access the HiHydroSoil v2.0 dataset in Google Earth Engine can be found here (Google Earth Engine account required).

The HiHydroSoil v2.0 database can also be downloaded from the FutureWater website using the form below. Interested in HiHydroSoil v.20? Read more on the project page!

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).

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.

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/

 

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.

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:

WEAP:

  • 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

 

Last week FutureWater has finished the Tailor Made Training for the Rwanda Water Resources Board (RWB) on Water Allocation Modeling and Remote Sensing Analysis. We taught about 20 participants of the RWB how to work with the Water Evaluation And Planning model WEAP and the Remote Sensing platform of Google Earth Engine (GEE), state of the art technologies that are excellent for Integrated Water Resources Management (IWRM).

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.

When COVID-19 restrictions were less strict in November 2020 and Rwanda was considered as one of the few safe countries to go to, FutureWater colleagues Jonna van Opstal and Reinier Koster went to Kigali to host a 3 day on-site training session. The training adhered to strict measures (social distancing, mouth masks, disinfectant and full time ventilation) to prevent the spread of COVID-19. The on-site training really added value to the course, since the trainers were capable of explaining things in more detail and look over shoulders of participants when they were working on assignments.

During the final 6 weeks of the training, the participants worked in 4 groups on a case study with a subject relevant for the Rwanda Water Resources board. Two groups worked on a WEAP-related subject and the other 2 groups worked on a subject using GEE. A final online session was held where each group had the chance to present their results.

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Official opening of the on-site training by Deputy Director General of the Rwanda Water Resources Board Niyotwambaza Hitimana Christine.

Hydropower is essential to fulfill future energy demands. Water scarcity is likely to increase due to climate change and aase in water demand. Therefore, Climate Risk Assessments are required before large investments in new and large hydropower stations (>100 MW) are made. Small hydropower (1 – 20 MW) does not require these Climate Risk Assessments yet, but this will eventually happen in the future. Investors are highly interested in the profitability of these small hydropower stations, especially because of the uncertainty caused by future climate change. Current methods for Climate Risk Assessments (CRA) are however still too costly for these small-hydro projects because they are very labor intensive and require specific knowledge.

FutureWater has carried out a feasibility study to assess the possibilities for the development of a “Small-Hydro Climate Risk Assessment tool” (SH-CRA) that can make CRA’s for small-hydro projects cost effective. The starting point of this project to develop the SH-CRA is the recent change in the approach to CRA’s: until a few years ago, these were based purely on climate models, also known as the “Top-down” approach. Nowadays however, investors require a more pragmatic approach in which climate risks are balanced against other risks and presented in a clear way. This new “Bottom-up” approach makes it possible for small-hydro projects to include climate risks in the investment decision.

This feasibility project has therefore investigated whether the “bottom-up” climate risk analysis approach can make it possible to develop such a SH-CRA solution, based on a combination of literature research, an inventory of available technology and potential partners, and competition analysis.