Data Model for Water Resource Management

Water management data is scattered across many platforms, providers or websites, which makes the task of efficiently planning the utilization of water resources difficult for managers and authorities. Inspired by the WaM-DaM idea to merge heterogenous datasets, we selected 10 water sources (rivers, lakes and reservoirs) and concatenated data related to water height, precipitation and drought. After the correlation of the height related data with both the precipitation and measurements by calculating the Pearson coefficients, we found almost no correlation (except for the Danube River). We also provide two possible reallife use cases. The first utilization refers to the anticipation of floods by analysing the effects precipitation had over a water source’s height in the past, together with the weather forecast for the near future. A model that brings together different data sources could also be used by water resource managers for planning the water usage of industry and population.