PhD Defence Alexander Kaune

  • 27 Sep 2019
  • 15:00 - 17:00
  • Westvest 7, 2611 AX Delft, Auditorium A1b
Western Europe
Delft, The Netherlands

On Friday 27 September, 2019, the Public Defence and awarding Ceremony of Mr. Alexander Kaune Schmidt, from Germany / Costa Rica will take place. Professor Charlotte de Fraiture is his promotor and Dr. Micha Werner his co-promotor.

The title of his thesis is

The value of using hydrological datasets for water allocation decisions: earth observations, hydrological models, and seasonal forecasts

15:00  - 15:15              Presentation in the Auditorium of IHE Delft (A1b)

15:30  - 17:00              Public Defence and Awarding Ceremony

17:00  - 18:00              Drinks in the IHE Delft Restaurant

Summary

An increasing number of hydrological datasets from earth observations, hydrological models and seasonal forecasts have become available for water managers, consultants and the general public. These datasets are state-of-the-art products which are usually accessible online and may contribute to develop hydrological studies and support water resources management. However, the added value of these datasets has not been completely explored in decision-making processes. Research studies have assessed how well data can help in predicting climate, but there is a lack of knowledge on how well data can help in water allocation decisions. This work provides numerical tools, methods and results to evaluate the value of using hydrological datasets to support water allocation decisions at river basin and irrigation district scale. An integrated approach is used to predict climate, improve decisions and reduce negative impacts. Results show that investing in hydrological data with finer spatial and temporal resolution and longer periods of record improves water allocation decisions and reduces agricultural production loss in large irrigation schemes. Using river discharge data from hydrological models and global precipitation enhances irrigation area planning when little in-situ data is available. Moreover, using seasonal streamflow forecasts improves available water estimates resulting in better water allocation decisions. The framework was tested in Costa Rica, Colombia and Australia, but can be applied in any case study around the world.

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