@article{CochLamoureuxKnoblauchetal.2018,
  author    = {Coch, Caroline and Lamoureux, Scott F. and Knoblauch, Christian and Eischeid, Isabell and Fritz, Michael and Obu, Jaroslav and Lantuit, Hugues},
  title     = {Summer rainfall dissolved organic carbon, solute, and sediment fluxes in a small Arctic coastal catchment on Herschel Island (Yukon Territory, Canada)},
  series = {Artic science},
  volume    = {4},
  journal   = {Artic science},
  number    = {4},
  publisher = {Canadian science publishing},
  address   = {Ottawa},
  issn      = {2368-7460},
  doi       = {10.1139/as-2018-0010},
  pages     = {750 -- 780},
  year      = {2018},
  abstract  = {Coastal ecosystems in the Arctic are affected by climate change. As summer rainfall frequency and intensity are projected to increase in the future, more organic matter, nutrients and sediment could bemobilized and transported into the coastal nearshore zones. However, knowledge of current processes and future changes is limited. We investigated streamflow dynamics and the impacts of summer rainfall on lateral fluxes in a small coastal catchment on Herschel Island in the western Canadian Arctic. For the summer monitoring periods of 2014-2016, mean dissolved organic matter flux over 17 days amounted to 82.7 +/- 30.7 kg km(-2) and mean total dissolved solids flux to 5252 +/- 1224 kg km(-2). Flux of suspended sediment was 7245 kg km(-2) in 2015, and 369 kg km(-2) in 2016. We found that 2.0\% of suspended sediment was composed of particulate organic carbon. Data and hysteresis analysis suggest a limited supply of sediments; their interannual variability is most likely caused by short-lived localized disturbances. In contrast, our results imply that dissolved organic carbon is widely available throughout the catchment and exhibits positive linear relationship with runoff. We hypothesize that increased projected rainfall in the future will result in a similar increase of dissolved organic carbon fluxes.},
  language  = {en}
}
@article{MusterRileyRothetal.2019,
  author    = {Muster, Sina and Riley, William J. and Roth, Kurt and Langer, Moritz and Aleina, Fabio Cresto and Koven, Charles D. and Lange, Stephan and Bartsch, Annett and Grosse, Guido and Wilson, Cathy J. and Jones, Benjamin M. and Boike, Julia},
  title     = {Size distributions of arctic waterbodies reveal consistent relations in their statistical moments in space and time},
  series = {Frontiers in Earth Science},
  volume    = {7},
  journal   = {Frontiers in Earth Science},
  publisher = {Frontiers Research Foundation},
  address   = {Lausanne},
  issn      = {2296-6463},
  doi       = {10.3389/feart.2019.00005},
  pages     = {15},
  year      = {2019},
  abstract  = {Arctic lowlands are characterized by large numbers of small waterbodies, which are known to affect surface energy budgets and the global carbon cycle. Statistical analysis of their size distributions has been hindered by the shortage of observations at sufficiently high spatial resolutions. This situation has now changed with the high-resolution (<5 m) circum-Arctic Permafrost Region Pond and Lake (PeRL) database recently becoming available. We have used this database to make the first consistent, high-resolution estimation of Arctic waterbody size distributions, with surface areas ranging from 0.0001 km(2) (100 m(2)) to 1 km(2). We found that the size distributions varied greatly across the thirty study regions investigated and that there was no single universal size distribution function (including power-law distribution functions) appropriate across all of the study regions. We did, however, find close relationships between the statistical moments (mean, variance, and skewness) of the waterbody size distributions from different study regions. Specifically, we found that the spatial variance increased linearly with mean waterbody size (R-2 = 0.97, p < 2.2e-16) and that the skewness decreased approximately hyperbolically. We have demonstrated that these relationships (1) hold across the 30 Arctic study regions covering a variety of (bio)climatic and permafrost zones, (2) hold over time in two of these study regions for which multi-decadal satellite imagery is available, and (3) can be reproduced by simulating rising water levels in a high-resolution digital elevation model. The consistent spatial and temporal relationships between the statistical moments of the waterbody size distributions underscore the dominance of topographic controls in lowland permafrost areas. These results provide motivation for further analyses of the factors involved in waterbody development and spatial distribution and for investigations into the possibility of using statistical moments to predict future hydrologic dynamics in the Arctic.},
  language  = {en}
}
@article{MikolajReichGuentner2019,
  author    = {Mikolaj, Michal and Reich, Marvin and G{\"u}ntner, Andreas},
  title     = {Resolving geophysical signals by terrestrial gravimetry},
  series = {Journal of geophysical research : Solid earth},
  volume    = {124},
  journal   = {Journal of geophysical research : Solid earth},
  number    = {2},
  publisher = {American Geophysical Union},
  address   = {Washington},
  issn      = {2169-9313},
  doi       = {10.1029/2018JB016682},
  pages     = {2153 -- 2165},
  year      = {2019},
  abstract  = {Terrestrial gravimetry is increasingly used to monitor mass transport processes in geophysics boosted by the ongoing technological development of instruments. Resolving a particular phenomenon of interest, however, requires a set of gravity corrections of which the uncertainties have not been addressed up to now. In this study, we quantify the time domain uncertainty of tide, global atmospheric, large-scale hydrological, and nontidal ocean loading corrections. The uncertainty is assessed by comparing the majority of available global models for a suite of sites worldwide. The average uncertainty expressed as root-mean-square error equals 5.1nm/s(2), discounting local hydrology or air pressure. The correction-induced uncertainty of gravity changes over various time periods of interest ranges from 0.6nm/s(2) for hours up to a maximum of 6.7nm/s(2) for 6months. The corrections are shown to be significant and should be applied for most geophysical applications of terrestrial gravimetry. From a statistical point of view, however, resolving subtle gravity effects in the order of few nanometers per square second is challenged by the uncertainty of the corrections. Plain Language Summary Many scientists are exploring ways to benefit from gravity measurements in fields of high societal relevance such as monitoring of volcanoes or measuring the amount of water in underground. Any application of such new methods, however, requires careful preparation of the gravity measurements. The intention of the preparation process is to ensure that the measurements do not contain information about processes that are not of interest. For that reason, the influence of atmosphere, ocean, tides, and hydrology needs to be reduced from the gravity. In this study, we investigate how this reduction process influences the quality of the measurement. We found that the precision degrades especially owing to the hydrology. The ocean plays an important role at sites close to the coast and the atmosphere at sites located in mountains. The overall errors of the reductions may complicate a reliable use of gravity measurements in certain studies focusing on very small signals. Nevertheless, the precision of gravity reductions alone does not obstruct a meaningful use of gravity measurements in most research fields. Details specifying the reduction precision are provided in this study allowing scientist dealing with gravity measurements to decide if their signal of interest can be reliably resolved.},
  language  = {en}
}
@article{MarquartEldridgeGeissleretal.2020,
  author    = {Marquart, Arnim and Eldridge, David J. and Geissler, Katja and Lobas, Christoph and Blaum, Niels},
  title     = {Interconnected effects of shrubs, invertebrate-derived macropores and soil texture on water infiltration in a semi-arid savanna rangeland},
  series = {Land degradation \& development},
  volume    = {31},
  journal   = {Land degradation \& development},
  number    = {16},
  publisher = {Wiley},
  address   = {Chichester, Sussex},
  issn      = {1085-3278},
  doi       = {10.1002/ldr.3598},
  pages     = {2307 -- 2318},
  year      = {2020},
  abstract  = {Many semi arid savannas are prone to degradation, caused for example, by overgrazing or extreme climatic events, which often lead to shrub encroachment. Overgrazing by livestock affects vegetation and infiltration processes by directly altering plant composition (selective grazing) or by impacting soil physical properties (trampling). Water infiltration is controlled by several parameters, such as macropores (created by soil-burrowing animals or plant roots) and soil texture, but their effects have mostly been studied in isolation. Here we report on a study, in which we conducted infiltration experiments to analyze the interconnected effects of invertebrate-created macropores, shrubs and soil texture (sandy soil and loamy sand) on infiltration in two Namibian rangelands. Using structural equation modeling, we found a direct positive effect of shrub size on infiltration and indirectly via invertebrate macropores on both soil types. On loamy sands this effect was even stronger, but additionally, invertebrate-created macropores became relevant as a direct driver of infiltration. Our results provide new insights into the effects of vegetation and invertebrates on infiltration under different soil textures. Pastoralists should use management strategies that maintain a heterogeneous plant community that supports soil fauna to sustain healthy soil water dynamics, particularly on soils with higher loam content. Understanding the fundamental functioning of soil water dynamics in drylands is critical because these ecosystems are water-limited and support the livelihoods of many cultures worldwide.},
  language  = {en}
}
@phdthesis{Baese2016,
  author    = {B{\"a}se, Frank},
  title     = {Interception loss of changing land covers in the humid tropical lowland of Latin America},
  school      = {Universit{\"a}t Potsdam},
  pages     = {ix, 85 Seiten},
  year      = {2016},
  abstract  = {Das Gebiet der feuchten Tropen ist die am st{\"a}rksten durch den Landnutzungswandel betroffene Region der Erde. Vor allem die Rodung tropischer W{\"a}lder, um Platz f{\"u}r Rinderweiden oder den Anbau von Soja zu schaffen, aber auch seit j{\"u}ngster Zeit die Bem{\"u}hungen um Wiederaufforstungen pr{\"a}gen diesen Landnutzungswandel. Dabei beeinflusst die {\"A}nderung der Vegetationsbedeckung den regionalen Wasserhaushalt auf vielf{\"a}ltige Weise. Betroffen ist unter anderem die Verdunstung von feuchten Oberfl{\"a}chen. Die so genannte Interzeptionsverdunstung bzw. der Interzeptionsverlust tr{\"a}gt erheblich zum Wasserdampfgehalt in der unteren Atmosph{\"a}re und schließlich zur Niederschlagsbildung bei. Ziele dieser Dissertation waren (1) die experimentelle Untersuchung der Interzeptionsverlustunterschiede zwischen einem nat{\"u}rlichen, tropischen Wald und einer Sojaplantage im s{\"u}dlichen Amazonasgebiet, (2) die Modellierung des Interzeptionsverlustes dieser beiden Vegetationsformen im Vergleich zu einem jungen Sekund{\"a}rwald unter dem Aspekt der Unsicherheiten bei der Ableitung notwendiger Modellparameter sowohl im S{\"u}damazonas als auch im Einzugsgebietes des Panamakanals sowie (3) die Wasserhaushaltsanalyse eines vom Landnutzungswandel gepr{\"a}gten Teileinzugsgebietes des Panamakanals in Hinblick auf die Ver{\"a}nderung der Interzeptionsverdunstung durch sich ver{\"a}ndernde Landnutzung und der {\"A}nderung der klimatischen Bedingungen. Die Messung des Interzeptionsverlustes zeigte, dass in der Hauptwachstumsphase vom Soja von dessen Oberfl{\"a}che mehr Wasserverdunstet als von der Oberfl{\"a}che des Waldes. Allerdings ist in der Jahresbilanz der Interzeptionsverlust vom Wald h{\"o}her, da diese Studie nur eine Momentaufnahme zur Zeit der vollen Vegetationsentwicklung des Sojas mit einem Zeitfenster von zwei Monaten widerspiegelt. Durch die geringere ganzj{\"a}hrige Verdunstung von den mit Soja bestandenen Fl{\"a}chen, wird hier der Niederschlag schneller dem Abfluss zugef{\"u}hrt und schell aus der Region ausgetragen. Somit tr{\"a}gt der Landnutzungswandel von Wald zu Soja zu einer mittelfristigen Reduktion des in der Region verf{\"u}gbaren Wassers bei. Die anschließende Modellierung des Interzeptionsverlustes zeigte Einerseits einen starken Einfluss der Datenqualit{\"a}t auf die Plausibilit{\"a}t der Ergebnisse und Andererseits, dass die Sensitivit{\"a}t der einzelnen Parameter zwischen den Untersuchungsgebieten variiert. Eine Schl{\"u}sselrolle nimmt die Wasserspeicherkapazit{\"a}t der Vegetationskrone ein. Dennoch ist die Evaporationsrate die treibende Gr{\"o}ße im Interzeptionsprozess, so dass von ihr die gr{\"o}ßte Unsicherheit ausgeht. Je nach verwendeter Methode zur Ableitung dieses Parameters unterscheiden sich die gewonnenen Parameterwerte erheblich. Die Wirkungsanalyse der Interzeptionsverdunstung auf den Wasserhaushalt im Wirkungsgeflecht der {\"A}nderungen von Temperatur, Niederschlag und Landnutzung im Landschaftsmosaik eines Flusseinzugsgebiets mit Hilfe eines Wasserhaushaltsmodels zeigte den Einfluss der Landnutzungs{\"a}nderung auf die Abflussbildung mittels verschiedener Landnutzungsszenarien. Die Ergebnisse belegen, dass die Landnutzungs{\"a}nderung im Gebiet nur einen geringen Einfluss auf den Jahresabfluss hat. St{\"a}rker scheint sich der gemessene Temperaturanstieg auf die Verdunstung auszuwirken. Der mit einer h{\"o}heren Temperatur einhergehende Anstieg der Transpiration und Interzeptionsverdunstung gleicht die gemessene Zunahme des Gebietsniederschlages aus, sodass keine signifikanten {\"A}nderungen im Jahresabfluss nachgewiesen werden konnten. Die Ergebnisse der drei Studien verdeutlichen den Einfluss der Landnutzung auf die Interzeptionsverdunstung. Allerdings veranschaulichten die Resultate der Wasserhaushalts-modellierung, wie sehr dieser Einfluss durch die Ver{\"a}nderung der {\"a}ußeren Rahmenbedingungen, vor allem durch den Anstieg der Temperatur, {\"u}berpr{\"a}gt werden kann. Dies belegt, dass eine einfache {\"U}bertragung der Ergebnisse zwischen den Untersuchungsgebiet nicht m{\"o}glich ist. Somit bleibt die experimentelle Erhebung von Vegetationsparametern sowie des Interzeptionsverlustes an den jeweils zu untersuchenden Standort f{\"u}r die Anwendung von Modellen unerl{\"a}sslich.},
  language  = {en}
}
@article{AichnerMakhmudovRajabovetal.2019,
  author    = {Aichner, Bernhard and Makhmudov, Zafar and Rajabov, Iljomjon and Zhang, Qiong and Pausata, Francesco Salvatore R. and Werner, Martin and Heinecke, Liv and Kuessner, Marie L. and Feakins, Sarah J. and Sachse, Dirk and Mischke, Steffen},
  title     = {Hydroclimate in the Pamirs Was Driven by Changes in Precipitation-Evaporation Seasonality Since theLast Glacial Period},
  series = {Geophysical research letters},
  volume    = {46},
  journal   = {Geophysical research letters},
  number    = {23},
  publisher = {American Geophysical Union},
  address   = {Washington},
  issn      = {0094-8276},
  doi       = {10.1029/2019GL085202},
  pages     = {13972 -- 13983},
  year      = {2019},
  abstract  = {The Central Asian Pamir Mountains (Pamirs) are a high-altitude region sensitive to climatic change, with only few paleoclimatic records available. To examine the glacial-interglacial hydrological changes in the region, we analyzed the geochemical parameters of a 31-kyr record from Lake Karakul and performed a set of experiments with climate models to interpret the results. delta D values of terrestrial biomarkers showed insolation-driven trends reflecting major shifts of water vapor sources. For aquatic biomarkers, positive delta D shifts driven by changes in precipitation seasonality were observed at ca. 31-30, 28-26, and 17-14 kyr BP. Multiproxy paleoecological data and modelling results suggest that increased water availability, induced by decreased summer evaporation, triggered higher lake levels during those episodes, possibly synchronous to northern hemispheric rapid climate events. We conclude that seasonal changes in precipitation-evaporation balance significantly influenced the hydrological state of a large waterbody such as Lake Karakul, while annual precipitation amount and inflows remained fairly constant.},
  language  = {en}
}
@article{Ayzel2021,
  author    = {Ayzel, Georgy},
  title     = {Deep neural networks in hydrology},
  series = {Vestnik of Saint Petersburg University. Earth Sciences},
  volume    = {66},
  journal   = {Vestnik of Saint Petersburg University. Earth Sciences},
  number    = {1},
  publisher = {Univ. Press},
  address   = {St. Petersburg},
  issn      = {2541-9668},
  doi       = {10.21638/spbu07.2021.101},
  pages     = {5 -- 18},
  year      = {2021},
  abstract  = {For around a decade, deep learning - the sub-field of machine learning that refers to artificial neural networks comprised of many computational layers - modifies the landscape of statistical model development in many research areas, such as image classification, machine translation, and speech recognition. Geoscientific disciplines in general and the field of hydrology in particular, also do not stand aside from this movement. Recently, the proliferation of modern deep learning-based techniques and methods has been actively gaining popularity for solving a wide range of hydrological problems: modeling and forecasting of river runoff, hydrological model parameters regionalization, assessment of available water resources. identification of the main drivers of the recent change in water balance components. This growing popularity of deep neural networks is primarily due to their high universality and efficiency. The presented qualities, together with the rapidly growing amount of accumulated environmental information, as well as increasing availability of computing facilities and resources, allow us to speak about deep neural networks as a new generation of mathematical models designed to, if not to replace existing solutions, but significantly enrich the field of geophysical processes modeling. This paper provides a brief overview of the current state of the field of development and application of deep neural networks in hydrology. Also in the following study, the qualitative long-term forecast regarding the development of deep learning technology for managing the corresponding hydrological modeling challenges is provided based on the use of "Gartner Hype Curve", which in the general details describes a life cycle of modern technologies.},
  language  = {en}
}
@article{HayhoeNeillPorderetal.2011,
  author    = {Hayhoe, Shelby J. and Neill, Christopher and Porder, Stephen and McHorney, Richard and Lefebvre, Paul and Coe, Michael T. and Elsenbeer, Helmut and Krusche, Alex V.},
  title     = {Conversion to soy on the Amazonian agricultural frontier increases streamflow without affecting stormflow dynamics},
  series = {Global change biology},
  volume    = {17},
  journal   = {Global change biology},
  number    = {5},
  publisher = {Wiley-Blackwell},
  address   = {Malden},
  issn      = {1354-1013},
  doi       = {10.1111/j.1365-2486.2011.02392.x},
  pages     = {1821 -- 1833},
  year      = {2011},
  abstract  = {Large-scale soy agriculture in the southern Brazilian Amazon now rivals deforestation for pasture as the region's predominant form of land use change. Such landscape-level change can have substantial consequences for local and regional hydrology, but these effects remain relatively unstudied in this ecologically and economically important region. We examined how the conversion to soy agriculture influences water balances and stormflows using stream discharge (water yields) and the timing of discharge (stream hydrographs) in small (2.5-13.5 km2) forested and soy headwater watersheds in the Upper Xingu Watershed in the state of Mato Grosso, Brazil. We monitored water yield for 1 year in three forested and four soy watersheds. Mean daily water yields were approximately four times higher in soy than forested watersheds, and soy watersheds showed greater seasonal variability in discharge. The contribution of stormflows to annual streamflow in all streams was low (< 13\% of annual streamflow), and the contribution of stormflow to streamflow did not differ between land uses. If the increases in water yield observed in this study are typical, landscape-scale conversion to soy substantially alters water-balance, potentially altering the regional hydrology over large areas of the southern Amazon.},
  language  = {en}
}
@article{AyzelIzhitskiy2019,
  author    = {Ayzel, Georgy and Izhitskiy, Alexander},
  title     = {Climate Change Impact Assessment on Freshwater Inflow into the Small Aral Sea},
  series = {Water},
  volume    = {11},
  journal   = {Water},
  number    = {11},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2073-4441},
  doi       = {10.3390/w11112377},
  pages     = {19},
  year      = {2019},
  abstract  = {During the last few decades, the rapid separation of the Small Aral Sea from the isolated basin has changed its hydrological and ecological conditions tremendously. In the present study, we developed and validated the hybrid model for the Syr Darya River basin based on a combination of state-of-the-art hydrological and machine learning models. Climate change impact on freshwater inflow into the Small Aral Sea for the projection period 2007-2099 has been quantified based on the developed hybrid model and bias corrected and downscaled meteorological projections simulated by four General Circulation Models (GCM) for each of three Representative Concentration Pathway scenarios (RCP). The developed hybrid model reliably simulates freshwater inflow for the historical period with a Nash-Sutcliffe efficiency of 0.72 and a Kling-Gupta efficiency of 0.77. Results of the climate change impact assessment showed that the freshwater inflow projections produced by different GCMs are misleading by providing contradictory results for the projection period. However, we identified that the relative runoff changes are expected to be more pronounced in the case of more aggressive RCP scenarios. The simulated projections of freshwater inflow provide a basis for further assessment of climate change impacts on hydrological and ecological conditions of the Small Aral Sea in the 21st Century.},
  language  = {en}
}
@article{MooijTrolleJeppesenetal.2010,
  author    = {Mooij, Wolf M. and Trolle, Dennis and Jeppesen, Erik and Arhonditsis, George B. and Belolipetsky, Pavel V. and Chitamwebwa, Deonatus B. R. and Degermendzhy, Andrey G. and DeAngelis, Donald L. and Domis, Lisette Nicole de Senerpont and Downing, Andrea S. and Elliott, J. Alex and Fragoso Jr, Carlos Ruberto and Gaedke, Ursula and Genova, Svetlana N. and Gulati, Ramesh D. and H{\aa}kanson, Lars and Hamilton, David P. and Hipsey, Matthew R. and 't Hoen, Jochem and H{\"u}lsmann, Stephan and Los, F. Hans and Makler-Pick, Vardit and Petzoldt, Thomas and Prokopkin, Igor G. and Rinke, Karsten and Schep, Sebastiaan A. and Tominaga, Koji and Van Dam, Anne A. and Van Nes, Egbert H. and Wells, Scott A. and Janse, Jan H.},
  title     = {Challenges and opportunities for integrating lake ecosystem modelling approaches},
  series = {Aquatic ecology},
  volume    = {44},
  journal   = {Aquatic ecology},
  publisher = {Springer Science + Business Media B.V.},
  address   = {Dordrecht},
  issn      = {1573-5125},
  doi       = {10.1007/s10452-010-9339-3},
  pages     = {633 -- 667},
  year      = {2010},
  abstract  = {A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.},
  language  = {en}
}