Assessment of multi-scale drought datasets to quantify drought severity and impacts in agriculture: a case study for Slovenia

Real-time information on the development of the drought conditions is one of the fundamental requisites for reinforcing the drought mitigation and preparedness. The EuroGEOSS interoperability approach promotes the development of monitoring and early warning systems based on real-time information. Different climatic databases, which are based on publicly available meteorological information, are available on real time by climatic research institutions. Commonly, publicly available information has much lower spatial resolution than the existing available national datasets. The capability of low resolution climatic datasets to quantify drought severity and drought impacts is limited and has therefore been analysed in the framework of the EuroGEOSS project. Initial operating capacity, which was built during the project, provided the framework for the analysis. The Standardized Precipitation Index, obtained from the lowresolution precipitation datasets, has been compared to the national highresolution datasets in Slovenia. The areas of low spatial agreement between different drought datasets were determined. In addition, various statistical measures were used to compare the drought characteristics, originating from different drought datasets. Furthermore, the capabilities of these datasets to This work is licensed under the Creative Commons Attribution-Non commercial Works 3.0 License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/ or send a letter to Creative Commons, 543 Howard Street, 5 th Floor, San Francisco, California, 94105, USA. DOI: 10.2902/1725-0463.2012.07.art21 International Journal of Spatial Data Infrastructures Research, 2012, Vol.7, 464-487 465 identify the drought impacts in different drought prone systems were analyzed. Even though, low resolution datasets failed to realistically detect the spatial patterns of specific drought episodes, they were able to reproduce the general drought temporal variability, especially at the short time scales. The low resolution dataset also provided reliable outputs in terms of knowing the impacts of drought on agriculture.