@article{AgarwalMarwanMaheswaranetal.2020, author = {Agarwal, Ankit and Marwan, Norbert and Maheswaran, Rathinasamy and {\"O}zt{\"u}rk, Ugur and Kurths, J{\"u}rgen and Merz, Bruno}, title = {Optimal design of hydrometric station networks based on complex network analysis}, series = {Hydrology and Earth System Sciences}, volume = {24}, journal = {Hydrology and Earth System Sciences}, number = {5}, publisher = {Copernicus Publ.}, address = {G{\"o}ttingen}, issn = {1027-5606}, doi = {10.5194/hess-24-2235-2020}, pages = {2235 -- 2251}, year = {2020}, abstract = {Hydrometric networks play a vital role in providing information for decision-making in water resource management. They should be set up optimally to provide as much information as possible that is as accurate as possible and, at the same time, be cost-effective. Although the design of hydrometric networks is a well-identified problem in hydrometeorology and has received considerable attention, there is still scope for further advancement. In this study, we use complex network analysis, defined as a collection of nodes interconnected by links, to propose a new measure that identifies critical nodes of station networks. The approach can support the design and redesign of hydrometric station networks. The science of complex networks is a relatively young field and has gained significant momentum over the last few years in different areas such as brain networks, social networks, technological networks, or climate networks. The identification of influential nodes in complex networks is an important field of research. We propose a new node-ranking measure - the weighted degree-betweenness (WDB) measure - to evaluate the importance of nodes in a network. It is compared to previously proposed measures used on synthetic sample networks and then applied to a real-world rain gauge network comprising 1229 stations across Germany to demonstrate its applicability. The proposed measure is evaluated using the decline rate of the network efficiency and the kriging error. The results suggest that WDB effectively quantifies the importance of rain gauges, although the benefits of the method need to be investigated in more detail.}, language = {en} } @misc{AgarwalMarwanMaheswaranetal.2020, author = {Agarwal, Ankit and Marwan, Norbert and Maheswaran, Rathinasamy and {\"O}zt{\"u}rk, Ugur and Kurths, J{\"u}rgen and Merz, Bruno}, title = {Optimal design of hydrometric station networks based on complex network analysis}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {951}, issn = {1866-8372}, doi = {10.25932/publishup-47100}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-471006}, pages = {19}, year = {2020}, abstract = {Hydrometric networks play a vital role in providing information for decision-making in water resource management. They should be set up optimally to provide as much information as possible that is as accurate as possible and, at the same time, be cost-effective. Although the design of hydrometric networks is a well-identified problem in hydrometeorology and has received considerable attention, there is still scope for further advancement. In this study, we use complex network analysis, defined as a collection of nodes interconnected by links, to propose a new measure that identifies critical nodes of station networks. The approach can support the design and redesign of hydrometric station networks. The science of complex networks is a relatively young field and has gained significant momentum over the last few years in different areas such as brain networks, social networks, technological networks, or climate networks. The identification of influential nodes in complex networks is an important field of research. We propose a new node-ranking measure - the weighted degree-betweenness (WDB) measure - to evaluate the importance of nodes in a network. It is compared to previously proposed measures used on synthetic sample networks and then applied to a real-world rain gauge network comprising 1229 stations across Germany to demonstrate its applicability. The proposed measure is evaluated using the decline rate of the network efficiency and the kriging error. The results suggest that WDB effectively quantifies the importance of rain gauges, although the benefits of the method need to be investigated in more detail.}, language = {en} } @article{OlenBookhagenStrecker2016, author = {Olen, Stephanie M. and Bookhagen, Bodo and Strecker, Manfred}, title = {Role of climate and vegetation density in modulating denudation rates in the Himalaya}, series = {Earth \& planetary science letters}, volume = {445}, journal = {Earth \& planetary science letters}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0012-821X}, doi = {10.1016/j.epsl.2016.03.047}, pages = {57 -- 67}, year = {2016}, abstract = {Vegetation has long been hypothesized to influence the nature and rates of surface processes. We test the possible impact of vegetation and climate on denudation rates at orogen scale by taking advantage of a pronounced along-strike gradient in rainfall and vegetation density in the Himalaya. We combine 12 new Be-10 denudation rates from the Sutlej Valley and 123 published denudation rates from fluvially-dominated catchments in the Himalaya with remotely-sensed measures of vegetation density and rainfall metrics, and with tectonic and lithologic constraints. In addition, we perform topographic analyses to assess the contribution of vegetation and climate in modulating denudation rates along strike. We observe variations in denudation rates and the relationship between denudation and topography along strike that are most strongly controlled by local rainfall amount and vegetation density, and cannot be explained by along-strike differences in tectonics or lithology. A W-E along-strike decrease in denudation rate variability positively correlates with the seasonality of vegetation density (R = 0.95, p < 0.05), and negatively correlates with mean vegetation density (R = -0.84, p < 0.05). Vegetation density modulates the topographic response to changing denudation rates, such that the functional relationship between denudation rate and topographic steepness becomes increasingly linear as vegetation density increases. We suggest that while tectonic processes locally control the pattern of denudation rates across strike of the Himalaya (i.e., S-N), along strike of the orogen (i.e., E-W) climate exerts a measurable influence on how denudation rates scatter around long-term, tectonically-controlled erosion, and on the functional relationship between topography and denudation. (C) 2016 Elsevier B.V. All rights reserved.}, language = {en} }