@article{AgarwalMaheswaranMarwanetal.2018, author = {Agarwal, Ankit and Maheswaran, Rathinasamy and Marwan, Norbert and Caesar, Levke and Kurths, J{\"u}rgen}, title = {Wavelet-based multiscale similarity measure for complex networks}, series = {The European physical journal : B, Condensed matter and complex systems}, volume = {91}, journal = {The European physical journal : B, Condensed matter and complex systems}, number = {11}, publisher = {Springer}, address = {New York}, issn = {1434-6028}, doi = {10.1140/epjb/e2018-90460-6}, pages = {12}, year = {2018}, abstract = {In recent years, complex network analysis facilitated the identification of universal and unexpected patterns in complex climate systems. However, the analysis and representation of a multiscale complex relationship that exists in the global climate system are limited. A logical first step in addressing this issue is to construct multiple networks over different timescales. Therefore, we propose to apply the wavelet multiscale correlation (WMC) similarity measure, which is a combination of two state-of-the-art methods, viz. wavelet and Pearson's correlation, for investigating multiscale processes through complex networks. Firstly we decompose the data over different timescales using the wavelet approach and subsequently construct a corresponding network by Pearson's correlation. The proposed approach is illustrated and tested on two synthetics and one real-world example. The first synthetic case study shows the efficacy of the proposed approach to unravel scale-specific connections, which are often undiscovered at a single scale. The second synthetic case study illustrates that by dividing and constructing a separate network for each time window we can detect significant changes in the signal structure. The real-world example investigates the behavior of the global sea surface temperature (SST) network at different timescales. Intriguingly, we notice that spatial dependent structure in SST evolves temporally. Overall, the proposed measure has an immense potential to provide essential insights on understanding and extending complex multivariate process studies at multiple scales.}, language = {en} } @article{OzturkWendiCrisologoetal.2018, author = {Ozturk, Ugur and Wendi, Dadiyorto and Crisologo, Irene and Riemer, Adrian and Agarwal, Ankit and Vogel, Kristin and Andres Lopez-Tarazon, Jose and Korup, Oliver}, title = {Rare flash floods and debris flows in southern Germany}, series = {The science of the total environment : an international journal for scientific research into the environment and its relationship with man}, volume = {626}, journal = {The science of the total environment : an international journal for scientific research into the environment and its relationship with man}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0048-9697}, doi = {10.1016/j.scitotenv.2018.01.172}, pages = {941 -- 952}, year = {2018}, abstract = {Flash floods and debris flows are iconic hazards inmountainous regions with steep relief, high rainfall intensities, rapid snowmelt events, and abundant sediments. The cuesta landscapes of southern Germany hardly come to mind when dealing with such hazards. A series of heavy rainstorms dumping up to 140mm in 2 h caused destructive flash floods and debris flows in May 2016. The most severe damage occurred in the Braunsbach municipality, which was partly buried by 42,000 m(3) of boulders, gravel, mud, and anthropogenic debris from the small catchment of Orlacher Bach (similar to 6 km(2)). We analysed this event by combining rainfall patterns, geological conditions, and geomorphic impacts to estimate an average sediment yield of 14,000 t/km(2) that mostly (similar to 95\%) came from some 50 riparian landslides and channel-bed incision of similar to 2 m. This specific sediment yield ranks among the top 20\% globally, while the intensity-duration curve of the rainstormis similarly in the upper percentile range of storms that had triggered landslides. Compared to similar-sized catchments in the greater region hit by the rainstorms, we find that the Orlacher Bach is above the 95th percentile in terms of steepness, storm-rainfall intensity, and topographic curvatures. The flash flood transported a sediment volume equal to as much as 20-40\% of the Pleistocene sediment volume stored in the Orlacher Bach fan, andmay have had several predecessors in the Holocene. River control structures from 1903 and records of a debris flow in the 1920s in a nearby catchment indicate that the local inhabitants may have been aware of the debris-flow hazards earlier. Such recurring and destructive events elude flood-hazard appraisals in humid landscapes of gentle relief, and broaden mechanistic views of how landslides and debris flows contribute to shaping small and deeply cut tributaries in the southern Germany cuesta landscape.}, language = {en} } @article{AgarwalMarwanMaheswaranetal.2018, author = {Agarwal, Ankit and Marwan, Norbert and Maheswaran, Rathinasamy and Merz, Bruno and Kurths, J{\"u}rgen}, title = {Quantifying the roles of single stations within homogeneous regions using complex network analysis}, series = {Journal of hydrology}, volume = {563}, journal = {Journal of hydrology}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0022-1694}, doi = {10.1016/j.jhydrol.2018.06.050}, pages = {802 -- 810}, year = {2018}, abstract = {Regionalization and pooling stations to form homogeneous regions or communities are essential for reliable parameter transfer, prediction in ungauged basins, and estimation of missing information. Over the years, several clustering methods have been proposed for regional analysis. Most of these methods are able to quantify the study region in terms of homogeneity but fail to provide microscopic information about the interaction between communities, as well as about each station within the communities. We propose a complex network-based approach to extract this valuable information and demonstrate the potential of our approach using a rainfall network constructed from the Indian gridded daily precipitation data. The communities were identified using the network-theoretical community detection algorithm for maximizing the modularity. Further, the grid points (nodes) were classified into universal roles according to their pattern of within- and between-community connections. The method thus yields zoomed-in details of individual rainfall grids within each community.}, language = {en} } @article{BronstertAgarwalBoessenkooletal.2018, author = {Bronstert, Axel and Agarwal, Ankit and Boessenkool, Berry and Crisologo, Irene and Fischer, Madlen and Heistermann, Maik and Koehn-Reich, Lisei and Andres Lopez-Tarazon, Jose and Moran, Thomas and Ozturk, Ugur and Reinhardt-Imjela, Christian and Wendi, Dadiyorto}, title = {Forensic hydro-meteorological analysis of an extreme flash flood}, series = {The science of the total environment : an international journal for scientific research into the environment and its relationship with man}, volume = {630}, journal = {The science of the total environment : an international journal for scientific research into the environment and its relationship with man}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0048-9697}, doi = {10.1016/j.scitotenv.2018.02.241}, pages = {977 -- 991}, year = {2018}, abstract = {The flash-flood in Braunsbach in the north-eastern part of Baden-Wuerttemberg/Germany was a particularly strong and concise event which took place during the floods in southern Germany at the end of May/early June 2016. This article presents a detailed analysis of the hydro-meteorological forcing and the hydrological consequences of this event. A specific approach, the "forensic hydrological analysis" was followed in order to include and combine retrospectively a variety of data from different disciplines. Such an approach investigates the origins, mechanisms and course of such natural events if possible in a "near real time" mode, in order to follow the most recent traces of the event. The results show that it was a very rare rainfall event with extreme intensities which, in combination with catchment properties, led to extreme runoff plus severe geomorphological hazards, i.e. great debris flows, which together resulted in immense damage in this small rural town Braunsbach. It was definitely a record-breaking event and greatly exceeded existing design guidelines for extreme flood discharge for this region, i.e. by a factor of about 10. Being such a rare or even unique event, it is not reliably feasible to put it into a crisp probabilistic context. However, one can conclude that a return period clearly above 100 years can be assigned for all event components: rainfall, peak discharge and sediment transport. Due to the complex and interacting processes, no single flood cause or reason for the very high damage can be identified, since only the interplay and the cascading characteristics of those led to such an event. The roles of different human activities on the origin and/or intensification of such an extreme event are finally discussed. (C) 2018 Elsevier B.V. All rights reserved.}, language = {en} } @article{ShuklaAgarwalSachdevaetal.2018, author = {Shukla, Roopam and Agarwal, Ankit and Sachdeva, Kamna and Kurths, J{\"u}rgen and Joshi, P. K.}, title = {Climate change perception}, series = {Climatic change : an interdisciplinary, intern. journal devoted to the description, causes and implications of climatic change}, volume = {152}, journal = {Climatic change : an interdisciplinary, intern. journal devoted to the description, causes and implications of climatic change}, number = {1}, publisher = {Springer}, address = {Dordrecht}, issn = {0165-0009}, doi = {10.1007/s10584-018-2314-z}, pages = {103 -- 119}, year = {2018}, abstract = {Climate change and variability have created widespread risks for farmers' food and livelihood security in the Himalayas. However, the extent of impacts experienced and perceived by farmers varies, as there is substantial diversity in the demographic, social, and economic conditions. Therefore, it is essential to understand how farmers with different resource-endowment and household characteristics perceive climatic risks. This study aims to analyze how farmer types perceive climate change processes and its impacts to gain insight into locally differentiated concerns by farming communities. The present study is based in the Uttarakhand state of Indian Western Himalayas. We examine farmer perceptions of climate change and how perceived impacts differ across farmer types. Primary household interviews with farming households (n = 241) were done in Chakrata and Bhikiyasian tehsil in Uttarakhand, India. In addition, annual and seasonal patterns of historical data of temperature (1951-2013) and precipitation (1901-2013) were analyzed to estimate trends and validate farmers' perception. Using statistical methods farmer typology was constructed, and five unique farmer types are identified. Majority of respondents across all farmer types noticed a decrease in summer and winter precipitation and an increase in summer temperature. Whereas the perceptions of impacts of climate change diverged across farmer types, as specific farmer types exclusively experienced few impacts. Impact of climatic risks on household food security and income was significantly perceived stronger by low-resource-endowed subsistence farmers, whereas the landless farmer type exclusively felt impacts on the communities social bond. This deeper understanding of the differentiated perception of impacts has strong implications for agricultural and development policymaking, highlighting the need for providing flexible adaptation options rather than specific solutions to avoid inequalities in fulfilling the needs of the heterogeneous farming communities.}, language = {en} }