On October 8, 2025, a symposium in Leiden will bring together scientists to explore historical Dutch coastal data, such as maps, measurements, and logbooks. These sources reveal how the coastline has changed over centuries, often due to human activity. By combining this knowledge with modern tools, we can better address sea level rise and flood risks. The data also holds value for heritage and local communities.

Every day, more microplastics (< 5 mm) are introduced into the aquatic environment, but where do they end up and do they influence natural processes? Increasing microplastic concentrations threaten ecosystems and the navigability of our waterways, as microplastics likely increase the settling of sediments by ‘gluing’ them together. This project will shed light on this aggregation process, by combining laboratory experiments, field studies and computer models. Ports will be used as practical examples, as they are heavily polluted. The results will inform scientists, practitioners and politicians on how to tackle plastic pollution of our rivers, ports and seas.

This research aims at providing scientific understanding on the hydrological functioning and the impact of agricultural water management of the Hindon subbasin of the Ganges river. Three areas of research are distinguished: 1. Integrated water systems analysis to understand the spatio-temporal relations between surface water and groundwater quantity and quality, and the impact of human activities and climate characteristics by setting up a monitoring network. Existing and new data will be used to develop a hydrological model that enables simulation of the spatio-temporal functioning of the hydrological system as a function of climate characteristics and human interventions. 2. Interventions to improve agricultural water management and reduce negative impacts on water quantity and quality. We will employ the WOFOST model coupled with obtained farm and economic revenue information, to understand the impact of current agricultural practices on the environment. These results will be compared with alternative more sustainable practices and evaluated in terms of yield, crop-diversity, economic revenue, irrigation water demand, environmental impact and resilience to climate change. 3. Develop recommendations for improvements in Hindon basin water quantity and quality, food production and economic revenues. The results from subproject 1 and 2 will be integrated in a comprehensive modelling platform, enabling evaluation and incorporates the impact of future socio-economy and climate changes. This platform will serve as the scientific basis for stakeholder discussions on future water management and sustainable agricultural practices. This project is innovative in: • that it lays the basis for an enhanced observation network for long term hydrological monitoring. • creating an integrated modelling platform to be used for stakeholder discussions, impact assessment and knowledge sharing. • enlarging the possibilities to develop pathways to a more sustainable agriculture and water management of the Hindon basin, which may serve as a template for upscaling to the larger Ganges basin.

Water management in a densely populated area with a strong interplay between meteorological, hydrological and socio-economic drivers is a complex topic. In order to guarantee the supply of water, and to avoid drought and flood damage an efficient system of weather forecasting, impact assessment and hydrological engineering is required. Even in a well-developed country as The Netherlands the current operational systems still lack skill and appropriate interconnectivity to ensure efficient water management at various time and spatial scales. Apart from precipitation, uncertainty in surface evaporation forms a strong bottleneck for water management at local, regional and national scale. The proposed research focuses on enhancing the added value of available observations and medium- to seasonal range weather forecasts of particularly evaporation and related quantities (soil moisture, ground water, streamflow, lake levels). It will develop an upgraded monitoring and forecasting system for surface evaporation, using a scientific methodology to reduce existing gaps between different modelling and observational approaches. The system will be demonstrated in a case study area that is governed by the complex interactions determining water supply and demand.

River floods are among the most dangerous natural disasters in the world and cause enormous damage. Timely and accurate prediction of floods can therefore save lives and reduce damage. Floods can be triggered different events, such as heavy rain, long-duration rain or melting snow, which change with climate change. This project will be the first to incorporate the various triggers of flooding and their relationship to precipitation and the soil into flood prediction. For this purpose, statistical and deterministic information will be combined so that climate change and thus future changes in floods can also be taken into account.