Information Needs for Water Resource and Risk Management : Hydro-Meteorological Data Value and Non-Traditional Information

Abstract: Data availability is extremely important for water management. Without data it would not be possible to know how much water is available or how often extreme events are likely to occur. The usually available hydro-meteorological data often have a limited representativeness and are affected by errors and uncertainties. Additionally, their collection is resource-intensive and, thus, many areas of the world are severely under-monitored. Other areas are seeing an unprecedented – yet local – wealth of data in the last decades. Additionally, the spread of new technologies together with the integration of different approaches to water management science and practice have uncovered a large amount of soft information that can potentially complement and expand the possibilities of water management.This thesis presents a series of studies that address data opportunities for water management. Firstly, the hydro-meteorological data needs for correctly estimating key processes for water resource management such as precipitation and discharge were evaluated. Secondly, the use of non-traditional sources of information such as social media and human behaviour to improve the efficiency of flood mitigation actions were explored. The results obtained provide guidelines for determining basic hydro-meteorological data needs. For instance, an upper density of 24 rain gauges per 1000 km2 for spatial precipitation estimation beyond which improvements are negligible was found. Additionally, a larger relative value of discharge data respect to precipitation data for calibrating hydrological models was observed. Regarding non-traditional sources of information, social memory of past flooding events was found to be a relevant factor determining the efficiency of flood early warning systems and therefore their damage mitigation potential. Finally, a new methodology to use social media data for probabilistic estimates of flood extent was put forward and shown to achieve results comparable to traditional approaches.This thesis significantly contributes to integrated water management by improving the understanding of data needs and opportunities of new sources of information thus making water management more efficient and useful for society.