TY - JOUR A1 - Trautmann, Tina A1 - Koirala, Sujan A1 - Carvalhais, Nuno A1 - Güntner, Andreas A1 - Jung, Martin T1 - The importance of vegetation in understanding terrestrial water storage variations JF - Hydrology and Earth System Sciences N2 - So far, various studies have aimed at decomposing the integrated terrestrial water storage variations observed by satellite gravimetry (GRACE, GRACE-FO) with the help of large-scale hydrological models. While the results of the storage decomposition depend on model structure, little attention has been given to the impact of the way that vegetation is represented in these models. Although vegetation structure and activity represent the crucial link between water, carbon, and energy cycles, their representation in large-scale hydrological models remains a major source of uncertainty. At the same time, the increasing availability and quality of Earth-observation-based vegetation data provide valuable information with good prospects for improving model simulations and gaining better insights into the role of vegetation within the global water cycle. In this study, we use observation-based vegetation information such as vegetation indices and rooting depths for spatializing the parameters of a simple global hydrological model to define infiltration, root water uptake, and transpiration processes. The parameters are further constrained by considering observations of terrestrial water storage anomalies (TWS), soil moisture, evapotranspiration (ET) and gridded runoff ( Q) estimates in a multi-criteria calibration approach. We assess the implications of including varying vegetation characteristics on the simulation results, with a particular focus on the partitioning between water storage components. To isolate the effect of vegetation, we compare a model experiment in which vegetation parameters vary in space and time to a baseline experiment in which all parameters are calibrated as static, globally uniform values. Both experiments show good overall performance, but explicitly including varying vegetation data leads to even better performance and more physically plausible parameter values. The largest improvements regarding TWS and ET are seen in supply-limited (semi-arid) regions and in the tropics, whereas Q simulations improve mainly in northern latitudes. While the total fluxes and storages are similar, accounting for vegetation substantially changes the contributions of different soil water storage components to the TWS variations. This suggests an important role of the representation of vegetation in hydrological models for interpreting TWS variations. Our simulations further indicate a major effect of deeper moisture storages and groundwater-soil moisture-vegetation interactions as a key to understanding TWS variations. We highlight the need for further observations to identify the adequate model structure rather than only model parameters for a reasonable representation and interpretation of vegetation-water interactions. Y1 - 2022 U6 - https://doi.org/10.5194/hess-26-1089-2022 SN - 1027-5606 SN - 1607-7938 VL - 26 IS - 4 SP - 1089 EP - 1109 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Vargas-Ruiz, Salome A1 - Schulreich, Christoph A1 - Kostevic, Angelika A1 - Tiersch, Brigitte A1 - Koetz, Joachim A1 - Kakorin, Sergej A1 - von Klitzing, Regine A1 - Jung, Martin A1 - Hellweg, Thomas A1 - Wellert, Stefan T1 - Extraction of model contaminants from solid surfaces by environmentally compatible microemulsions JF - Journal of colloid and interface science N2 - In the present contribution, we evaluate the efficiency of eco-friendly microemulsions to decontaminate solid surfaces by monitoring the extraction of non-toxic simulants of sulfur mustard out of model surfaces. The extraction process of the non-toxic simulants has been monitored by means of spectroscopic and chromatographic techniques. The kinetics of the removal process was analyzed by different empirical models. Based on the analysis of the kinetics, we can assess the influence of the amounts of oil and water and the microemulsion structure on the extraction process. (C) 2016 Elsevier Inc. All rights reserved. KW - Microemulsions KW - Decontamination KW - Surface removal KW - Kinetic analysis KW - Extraction Y1 - 2016 U6 - https://doi.org/10.1016/j.jcis.2016.03.006 SN - 0021-9797 SN - 1095-7103 VL - 471 SP - 118 EP - 126 PB - Elsevier CY - San Diego ER - TY - JOUR A1 - Walther, Sophia A1 - Duveiller, Gregory A1 - Jung, Martin A1 - Guanter, Luis A1 - Cescatti, Alessandro A1 - Camps-Valls, Gustau T1 - Satellite Observations of the Contrasting Response of Trees and Grasses to Variations in Water Availability JF - Geophysical research letters N2 - Interannual variations in ecosystem primary productivity are dominated by water availability. Until recently, characterizing the photosynthetic response of different ecosystems to soil moisture anomalies was hampered by observational limitations. Here, we use a number of satellite-based proxies for productivity, including spectral indices, sun-induced chlorophyll fluorescence, and data-driven estimates of gross primary production, to reevaluate the relationship between terrestrial photosynthesis and water. In contrast to nonwoody vegetation, we find a resilience of forested ecosystems to reduced soil moisture. Sun-induced chlorophyll fluorescence and data-driven gross primary production indicate an increase in photosynthesis as a result of the accompanying higher amounts of light and temperature despite lowered light-use-efficiency. Conversely, remote sensing indicators of greenness reach their detection limit and largely remain stable. Our study thus highlights the differential responses of ecosystems along a tree cover gradient and illustrates the importance of differentiating photosynthesis indicators from those of greenness for the monitoring and understanding of ecosystems. Plain Language Summary The capacity of vegetation to thrive and to sequester carbon depends on how much water they can have access to. In this work, we evaluate how different types of satellite observations can describe the response of vegetation to changes in soil moisture over the entire planet. The first source of observation measures only the greenness of the land surface, the second measures light that is emitted by pigments in plants which are photosynthetically active (chlorophyll fluorescence), and the third are simulations of gross carbon uptake derived from machine learning techniques. For periods of water shortage all three indicate a reduction of growth in ecosystems with few trees. However, in cold boreal forests, when soil moisture is particularly low, we still detect an increase in photosynthesis due to higher light and temperature conditions, but this is not reflected in the greenness indicator. This work illustrates how lack of water is not necessarily harmful for catching carbon through photosynthesis, but to monitor this effect, we need remote sensing indicators that measure more than just how green the plants are, and fluorescence is likely a good candidate. Y1 - 2019 U6 - https://doi.org/10.1029/2018GL080535 SN - 0094-8276 SN - 1944-8007 VL - 46 IS - 3 SP - 1429 EP - 1440 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Walther, Sophia A1 - Guanter, Luis A1 - Heim, Birgit A1 - Jung, Martin A1 - Duveiller, Gregory A1 - Wolanin, Aleksandra A1 - Sachs, Torsten T1 - Assessing the dynamics of vegetation productivity in circumpolar regions with different satellite indicators of greenness and photosynthesis JF - Biogeosciences N2 - High-latitude treeless ecosystems represent spatially highly heterogeneous landscapes with small net carbon fluxes and a short growing season. Reliable observations and process understanding are critical for projections of the carbon balance of the climate-sensitive tundra. Space-borne remote sensing is the only tool to obtain spatially continuous and temporally resolved information on vegetation greenness and activity in remote circumpolar areas. However, confounding effects from persistent clouds, low sun elevation angles, numerous lakes, widespread surface inundation, and the sparseness of the vegetation render it highly challenging. Here, we conduct an extensive analysis of the timing of peak vegetation productivity as shown by satellite observations of complementary indicators of plant greenness and photosynthesis. We choose to focus on productivity during the peak of the growing season, as it importantly affects the total annual carbon uptake. The suite of indicators are as follows: (1) MODIS-based vegetation indices (VIs) as proxies for the fraction of incident photosynthetically active radiation (PAR) that is absorbed (fPAR), (2) VIs combined with estimates of PAR as a proxy of the total absorbed radiation (APAR), (3) sun-induced chlorophyll fluorescence (SIF) serving as a proxy for photosynthesis, (4) vegetation optical depth (VOD), indicative of total water content and (5) empirically upscaled modelled gross primary productivity (GPP). Averaged over the pan-Arctic we find a clear order of the annual peak as APAR <= GPP < SIF < VIs/VOD. SIF as an indicator of photosynthesis is maximised around the time of highest annual temperatures. The modelled GPP peaks at a similar time to APAR. The time lag of the annual peak between APAR and instantaneous SIF fluxes indicates that the SIF data do contain information on light-use efficiency of tundra vegetation, but further detailed studies are necessary to verify this. Delayed peak greenness compared to peak photosynthesis is consistently found across years and land-cover classes. A particularly late peak of the normalised difference vegetation index (NDVI) in regions with very small seasonality in greenness and a high amount of lakes probably originates from artefacts. Given the very short growing season in circumpolar areas, the average time difference in maximum annual photosynthetic activity and greenness or growth of 3 to 25 days (depending on the data sets chosen) is important and needs to be considered when using satellite observations as drivers in vegetation models. Y1 - 2018 U6 - https://doi.org/10.5194/bg-15-6221-2018 SN - 1726-4170 SN - 1726-4189 VL - 15 IS - 20 SP - 6221 EP - 6256 PB - Copernicus CY - Göttingen ER - TY - GEN A1 - Walther, Sophia A1 - Guanter, Luis A1 - Heim, Birgit A1 - Jung, Martin A1 - Duveiller, Gregory A1 - Wolanin, Aleksandra A1 - Sachs, Torsten T1 - Assessing the dynamics of vegetation productivity in circumpolar regions with different satellite indicators of greenness and photosynthesis T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - High-latitude treeless ecosystems represent spatially highly heterogeneous landscapes with small net carbon fluxes and a short growing season. Reliable observations and process understanding are critical for projections of the carbon balance of the climate-sensitive tundra. Space-borne remote sensing is the only tool to obtain spatially continuous and temporally resolved information on vegetation greenness and activity in remote circumpolar areas. However, confounding effects from persistent clouds, low sun elevation angles, numerous lakes, widespread surface inundation, and the sparseness of the vegetation render it highly challenging. Here, we conduct an extensive analysis of the timing of peak vegetation productivity as shown by satellite observations of complementary indicators of plant greenness and photosynthesis. We choose to focus on productivity during the peak of the growing season, as it importantly affects the total annual carbon uptake. The suite of indicators are as follows: (1) MODIS-based vegetation indices (VIs) as proxies for the fraction of incident photosynthetically active radiation (PAR) that is absorbed (fPAR), (2) VIs combined with estimates of PAR as a proxy of the total absorbed radiation (APAR), (3) sun-induced chlorophyll fluorescence (SIF) serving as a proxy for photosynthesis, (4) vegetation optical depth (VOD), indicative of total water content and (5) empirically upscaled modelled gross primary productivity (GPP). Averaged over the pan-Arctic we find a clear order of the annual peak as APAR ≦ GPP