Project:NUFFIC Tailor-Made Training on Water Resources Modelling to support decision making for ARA-Sul
Cliënt:NUFFIC
Programma:Netherlands Fellowship Programmes (NFP) / Tailor-Made Training (TMT) Programme
Partners:ARA-Sul, ARA-Norte
Doel:To equip these ARA-Sul and ARA-Norte with additional knowledge to work with a Water Resources Model in order to have a stronger advisory role towards decision makers and people living in their area.

A Tailor-Made Training on Water Resources Modelling was required to equip the staff of the water agencies in Mozambique (ARAs) with additional knowledge to have a stronger advisory role towards policy and decision makers, and people living in the area. FutureWater provided this training to ARA-Sul and ARA-Norte. This training was funded by NUFFIC’s Tailor-Made Training Programme (TMT), which is part of the Netherlands Fellowship Programmes (NFP), and is specifically meant to enhance the overall functioning of an organization by training a selected group of its staff members. The training covered theory on hydrological modelling concepts and on data requirements, data quality and data availability in data scarce environments. Furthermore the training consisted of exercises to practice the use of GIS software and to set up and apply a Water Resources Model.

The mission of ARA-Sul and ARA-Norte is to make sure that the appropriate amount of good-quality water is delivered to the water-users at the desired place and time. In order to realize this mission, the ARAs deliver products in the form of data, advice, services and permits. Data that is gathered consists of rainfall, discharge, water quality, and water-extraction by users. Besides data gathering and delivery, ARAs have an advisory role towards policy makers and people living in their management area. The advisory role towards policy makers focuses on water planning issues on the long-term, like e.g. potential areas for construction of new reservoirs, expansion of current reservoirs, the required capacity of reservoirs, potential areas for irrigation, and the maximum area that can be developed for irrigated agriculture. The advisory role towards people living in their management area consists of early-warning and evacuation advice when there is a potential danger of floods.

NufficCurrently, ARA-Sul and ARA-Norte face a knowledge gap to manage their water resources and to serve their clients. This knowledge gap consists of a mixed interplay between insufficient knowledge of water resources in their respective regions, missing tools to analyze their water systems, and the ability to apply those tools. In order to close this knowledge gap, a Tailor-Made Training is required to equip the staff of these ARAs with additional knowledge to have a stronger advisory role towards policy and decision makers, and people living in the area. FutureWater was granted to provide a training on Water Resources Modelling to ARA-Sul and ARA-Norte. This training was funded by NUFFIC’s Tailor-Made Training Programme (TMT), which is part of the Netherlands Fellowship Programmes (NFP), and is specifically meant to enhance the overall functioning of an organization by training a selected group of its staff members.

The training is organized in two blocks and will cover the following topics:

  • Theory on hydrological modelling concepts
  • Data requirements, quality and availability in data scarce environments
  • Using free and user-friendly open-source GIS software
  • Setup and apply a Water Resources Model (WRM) for a case-study basin in Mozambique
  • Use the WRM to forecast river discharge under a meteorological forecast, and if required, give a Flood-Early-Warning
  • Evaluate the impact of climate change on the available water resources

Publicaties

  • 2016 - FutureWater Report 160Terink, W., S. Khanal. 2016. SPHY: Spatial Processes in Hydrology. Advanced training: input data, sensitivity analysis, model calibration, and scenario analyses. FutureWater Report 160.X

    SPHY: Spatial Processes in Hydrology. Advanced training: input data, sensitivity analysis, model calibration, and scenario analyses

    Terink, W., S. Khanal