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This study examines the usefulness of Recurrence Plot (RP) and its quantification as novel tools to analyze recurring characteristics of hydrological time series (i.e. discharge), in particular the shape of hydrological signature (also known as hydrograph). Conventionally, such time series analysis has been approached either as discrete point (e.g. recurring flood peaks as often found in flood frequency analysis), or a linear part or an aggregate index of the hydrograph (e.g. recession slope and discharge volume), but not the continuous shape of it. The problem with the mentioned conventional approaches is the uncertainty of different type of events (i.e. resulted from different processes/boundary conditions) being mistaken as the same. In addition, the continuous shape of the hydrograph also implies the process dynamics of the hydrological cycle and therefore could be a substantial proxy to deduce changes in boundary conditions and responses of a catchment and river system. The choice of using RP is very much in accordance with today's scientific pursuit of the field, especially with the hypothesis that linearity and stationarity are no longer valid. Using this method, we no longer assume the type of the event typology to be classified loosely on the fixed time range of a season (e.g. March to April defined as snowmelt flood), but instead from its unique phase space characteristics. Since the use of RP in analyzing hydrological change is novel and suitable, we decide to spearhead the challenge on using RP as big data mining tool to study the dynamics of hydrological signature.
In the wake of changing hydro-climatological, geo-physical and socio-economic conditions the magnitude, frequency and impact of certain types of natural hazards are likely bound to change as well. This is highly of utmost importance for many regions in the world where risks due to natural hazards have to be managed and mitigated and this is where the research training group “Natural hazards and risks in a changing world (NatRiskChange)” aims to foster the scientific knowledge basis. This research training group started on October 1st 2015 and is funded by the Deutsche Forschungsgemeinschaft DFG. The central goal of NatRiskChange is to pursue the development of methods to improve hazard and risk analysis and quantification based on the transient, non-stationary nature of hazards and risks in response to changing natural and anthropogenically altered components of the Earth system. Key scientific aims are the development, testing, and pilot application of studies on identification, quantification (mechanisms) and prediction of transient natural hazards and associated risks.
Within NatRiskChange, a telephone aided survey was conducted in October and November 2017 among companies, which were affected from heavy rainfall or flash flood events in 2014 to 2016. We aim at gathering information about the companies experiences with severe weather warning systems, the type and extent of the damage as well es the state of recovery. Results shall identify improved mitigation measures for the management of eavy rainfall events. We thank all participants of the survey for their support!