TY - GEN A1 - Prahl, Boris F. A1 - Boettle, Markus A1 - Costa, Luís Fílípe Carvalho da A1 - Kropp, Jürgen A1 - Rybski, Diego T1 - Damage and protection cost curves for coastal floods within the 600 largest European cities T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - The economic assessment of the impacts of storm surges and sea-level rise in coastal cities requires high-level information on the damage and protection costs associated with varying flood heights. We provide a systematically and consistently calculated dataset of macroscale damage and protection cost curves for the 600 largest European coastal cities opening the perspective for a wide range of applications. Offering the first comprehensive dataset to include the costs of dike protection, we provide the underpinning information to run comparative assessments of costs and benefits of coastal adaptation. Aggregate cost curves for coastal flooding at the city-level are commonly regarded as by-products of impact assessments and are generally not published as a standalone dataset. Hence, our work also aims at initiating a more critical discussion on the availability and derivation of cost curves. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 938 KW - sea-level rise KW - topographic data KW - climate-change KW - adaptation KW - scale KW - exposure KW - model Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-459672 SN - 1866-8372 IS - 938 ER - TY - GEN A1 - Kruse, Stefan A1 - Gerdes, Alexander A1 - Kath, Nadja J. A1 - Herzschuh, Ulrike T1 - Implementing spatially explicit wind-driven seed and pollen dispersal in the individual-based larch simulation model BT - LAVESI-WIND 1.0 T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - It is of major interest to estimate the feedback of arctic ecosystems to the global warming we expect in upcoming decades. The speed of this response is driven by the potential of species to migrate, tracking their climate optimum. For this, sessile plants have to produce and disperse seeds to newly available habitats, and pollination of ovules is needed for the seeds to be viable. These two processes are also the vectors that pass genetic information through a population. A restricted exchange among subpopulations might lead to a maladapted population due to diversity losses. Hence, a realistic implementation of these dispersal processes into a simulation model would allow an assessment of the importance of diversity for the migration of plant species in various environments worldwide. To date, dynamic global vegetation models have been optimized for a global application and overestimate the migration of biome shifts in currently warming temperatures. We hypothesize that this is caused by neglecting important fine-scale processes, which are necessary to estimate realistic vegetation trajectories. Recently, we built and parameterized a simulation model LAVESI for larches that dominate the latitudinal treelines in the northernmost areas of Siberia. In this study, we updated the vegetation model by including seed and pollen dispersal driven by wind speed and direction. The seed dispersal is modelled as a ballistic flight, and for the pollination of ovules of seeds produced, we implemented a wind-determined and distance-dependent probability distribution function using a von Mises distribution to select the pollen donor. A local sensitivity analysis of both processes supported the robustness of the model's results to the parameterization, although it highlighted the importance of recruitment and seed dispersal traits for migration rates. This individual-based and spatially explicit implementation of both dispersal processes makes it easily feasible to inherit plant traits and genetic information to assess the impact of migration processes on the genetics. Finally, we suggest how the final model can be applied to substantially help in unveiling the important drivers of migration dynamics and, with this, guide the improvement of recent global vegetation models. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 929 KW - long-distance dispersal KW - climate-change KW - genetic-structure KW - plant migration KW - larix-sibirica KW - DNA variation KW - large-scale KW - vegetation KW - landscape KW - future Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-445978 SN - 1866-8372 IS - 929 SP - 4451 EP - 4467 ER - TY - GEN A1 - Jing, Miao A1 - Heße, Falk A1 - Kumar, Rohini A1 - Wang, Wenqing A1 - Fischer, Thomas A1 - Walther, Marc A1 - Zink, Matthias A1 - Zech, Alraune A1 - Samaniego, Luis A1 - Kolditz, Olaf A1 - Attinger, Sabine T1 - Improved regional-scale groundwater representation by the coupling of the mesoscale Hydrologic Model (mHM v5.7) to the groundwater model OpenGeoSys (OGS) T2 - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe N2 - Most large-scale hydrologic models fall short in reproducing groundwater head dynamics and simulating transport process due to their oversimplified representation of groundwater flow. In this study, we aim to extend the applicability of the mesoscale Hydrologic Model (mHM v5.7) to subsurface hydrology by coupling it with the porous media simulator OpenGeoSys (OGS). The two models are one-way coupled through model interfaces GIS2FEM and RIV2FEM, by which the grid-based fluxes of groundwater recharge and the river-groundwater exchange generated by mHM are converted to fixed-flux boundary conditions of the groundwater model OGS. Specifically, the grid-based vertical reservoirs in mHM are completely preserved for the estimation of land-surface fluxes, while OGS acts as a plug-in to the original mHM modeling framework for groundwater flow and transport modeling. The applicability of the coupled model (mHM-OGS v1.0) is evaluated by a case study in the central European mesoscale river basin - Nagelstedt. Different time steps, i.e., daily in mHM and monthly in OGS, are used to account for fast surface flow and slow groundwater flow. Model calibration is conducted following a two-step procedure using discharge for mHM and long-term mean of groundwater head measurements for OGS. Based on the model summary statistics, namely the Nash-Sutcliffe model efficiency (NSE), the mean absolute error (MAE), and the interquartile range error (QRE), the coupled model is able to satisfactorily represent the dynamics of discharge and groundwater heads at several locations across the study basin. Our exemplary calculations show that the one-way coupled model can take advantage of the spatially explicit modeling capabilities of surface and groundwater hydrologic models and provide an adequate representation of the spatiotemporal behaviors of groundwater storage and heads, thus making it a valuable tool for addressing water resources and management problems. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 851 KW - travel-time distributions KW - surface-water KW - land-surface KW - surface/subsurface flow KW - parameter-estimation KW - subsurface flow KW - transport model KW - climate-change KW - river-basins KW - catchment Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-427030 SN - 1866-8372 IS - 851 SP - 1989 EP - 2007 ER - TY - GEN A1 - Ayzel, Georgy A1 - Izhitskiy, Alexander T1 - Coupling physically based and data-driven models for assessing freshwater inflow into the Small Aral Sea T2 - Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe N2 - The Aral Sea desiccation and related changes in hydroclimatic conditions on a regional level is a hot topic for past decades. The key problem of scientific research projects devoted to an investigation of modern Aral Sea basin hydrological regime is its discontinuous nature – the only limited amount of papers takes into account the complex runoff formation system entirely. Addressing this challenge we have developed a continuous prediction system for assessing freshwater inflow into the Small Aral Sea based on coupling stack of hydrological and data-driven models. Results show a good prediction skill and approve the possibility to develop a valuable water assessment tool which utilizes the power of classical physically based and modern machine learning models both for territories with complex water management system and strong water-related data scarcity. The source code and data of the proposed system is available on a Github page (https://github.com/SMASHIproject/IWRM2018). T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 703 KW - climate-change KW - river-basin KW - runoff KW - catchments KW - Asia Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-427873 SN - 1866-8372 IS - 703 SP - 151 EP - 158 ER - TY - GEN A1 - Fuchs, Matthias A1 - Grosse, Guido A1 - Strauss, Jens A1 - Günther, Frank A1 - Grigoriev, Mikhail N. A1 - Maximov, Georgy M. A1 - Hugelius, Gustaf T1 - Carbon and nitrogen pools in thermokarst-affected permafrost landscapes in Arctic Siberia T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Ice-rich yedoma-dominated landscapes store con- siderable amounts of organic carbon (C) and nitrogen (N) and are vulnerable to degradation under climate warming. We investigate the C and N pools in two thermokarst-affected yedoma landscapes – on Sobo-Sise Island and on Bykovsky Peninsula in the north of eastern Siberia. Soil cores up to 3 m depth were collected along geomorphic gradients and anal- ysed for organic C and N contents. A high vertical sampling density in the profiles allowed the calculation of C and N stocks for short soil column intervals and enhanced under- standing of within-core parameter variability. Profile-level C and N stocks were scaled to the landscape level based on landform classifications from 5 m resolution, multispectral RapidEye satellite imagery. Mean landscape C and N storage in the first metre of soil for Sobo-Sise Island is estimated to be 20.2 kg C m −2 and 1.8 kg N m −2 and for Bykovsky Penin- sula 25.9 kg C m −2 and 2.2 kg N m −2 . Radiocarbon dating demonstrates the Holocene age of thermokarst basin de- posits but also suggests the presence of thick Holocene- age cover layers which can reach up to 2 m on top of in- tact yedoma landforms. Reconstructed sedimentation rates of 0.10–0.57 mm yr −1 suggest sustained mineral soil accu- mulation across all investigated landforms. Both yedoma and thermokarst landforms are characterized by limited accumu- lation of organic soil layers (peat). We further estimate that an active layer deepening of about 100 cm will increase organic C availability in a sea- sonally thawed state in the two study areas by ∼ 5.8 Tg (13.2 kg C m −2 ). Our study demonstrates the importance of increasing the number of C and N storage inventories in ice- rich yedoma and thermokarst environments in order to ac- count for high variability of permafrost and thermokarst en- vironments in pan-permafrost soil C and N pool estimates. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 654 KW - soil organic-carbon KW - Lena River Delta KW - ice-rich permafrost KW - thaw-lake basins KW - climate-change KW - northern Siberia KW - Late Quaternary KW - periglacial landscape KW - Tundra ecosystem KW - Yedoma region Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-418026 SN - 1866-8372 VL - 15 IS - 654 ER -