TY - JOUR A1 - Agarwal, Ankit A1 - Guntu, Ravikumar A1 - Banerjee, Abhirup A1 - Gadhawe, Mayuri Ashokrao A1 - Marwan, Norbert T1 - A complex network approach to study the extreme precipitation patterns in a river basin JF - Chaos : an interdisciplinary journal of nonlinear science N2 - The quantification of spatial propagation of extreme precipitation events is vital in water resources planning and disaster mitigation. However, quantifying these extreme events has always been challenging as many traditional methods are insufficient to capture the nonlinear interrelationships between extreme event time series. Therefore, it is crucial to develop suitable methods for analyzing the dynamics of extreme events over a river basin with a diverse climate and complicated topography. Over the last decade, complex network analysis emerged as a powerful tool to study the intricate spatiotemporal relationship between many variables in a compact way. In this study, we employ two nonlinear concepts of event synchronization and edit distance to investigate the extreme precipitation pattern in the Ganga river basin. We use the network degree to understand the spatial synchronization pattern of extreme rainfall and identify essential sites in the river basin with respect to potential prediction skills. The study also attempts to quantify the influence of precipitation seasonality and topography on extreme events. The findings of the study reveal that (1) the network degree is decreased in the southwest to northwest direction, (2) the timing of 50th percentile precipitation within a year influences the spatial distribution of degree, (3) the timing is inversely related to elevation, and (4) the lower elevation greatly influences connectivity of the sites. The study highlights that edit distance could be a promising alternative to analyze event-like data by incorporating event time and amplitude and constructing complex networks of climate extremes. Y1 - 2022 U6 - https://doi.org/10.1063/5.0072520 SN - 1054-1500 SN - 1089-7682 VL - 32 IS - 1 PB - American Institute of Physics CY - Woodbury, NY ER - TY - JOUR A1 - Aichner, Bernhard A1 - Ott, Florian A1 - Slowinski, Michal A1 - Norygkiewicz, Agnieszka M. A1 - Brauer, Achim A1 - Sachse, Dirk T1 - Leaf wax n-alkane distributions record ecological changes during the Younger Dryas at Trzechowskie paleolake (northern Poland) without temporal delay JF - Climate of the past : an interactive open access journal of the European Geosciences Union N2 - While of higher plant origin, a specific source assignment of sedimentary leaf wax n-alkanes remains difficult. In addition, it is unknown how fast a changing catchment vegetation would be reflected in sedimentary leaf wax archives. In particular, for a quantitative interpretation of n-alkane C and H isotope ratios in terms of paleohydrological and paleoecological changes, a better understanding of transfer times and dominant sedimentary sources of leaf wax n-alkanes is required. In this study we tested to what extent compositional changes in leaf wax n-alkanes can be linked to known vegetation changes by comparison with high-resolution palynological data from the same archive. We analyzed leaf wax n-alkane concentrations and distributions in decadal resolution from a sedimentary record from Trzechowskie paleolake (TRZ, northern Poland), covering the Late Glacial to early Holocene (13 360-9940 yr BP). As an additional source indicator of targeted n-alkanes, compound-specific carbon isotopic data have been generated in lower time resolution. The results indicated rapid responses of n-alkane distribution patterns coinciding with major climatic and paleoecological transitions. We found a shift towards higher average chain length (ACL) values at the Allerod-Younger Dryas (YD) transition between 12 680 and 12 600 yr BP, co-evaled with a decreasing contribution of arboreal pollen (mainly Pinus and Betula) and a subsequently higher abundance of pollen derived from herbaceous plants (Poaceae, Cyperaceae, Artemisia), shrubs, and dwarf shrubs (Juniperus and Salix). The termination of the YD was characterized by a successive increase in n-alkane concentrations coinciding with a sharp decrease in ACL values between 11 580 and 11 490 yr BP, reflecting the expansion of woodland vegetation at the YD-Holocene transition. A gradual reversal to longer chain lengths after 11 200 yr BP, together with decreasing n-alkane concentrations, most likely reflects the early Holocene vegetation succession with a decline of Betula. These results show that n-alkane distributions reflect vegetation changes and that a fast (i.e., subdecadal) signal transfer occurred. However, our data also indicate that a standard interpretation of directional changes in biomarker ratios remains difficult. Instead, responses such as changes in ACL need to be discussed in the context of other proxy data. In addition, we find that organic geochemical data integrate different ecological information compared to pollen, since some gymnosperm genera, such as Pinus, produce only a very low amount of n-alkanes and for this reason their contribution may be largely absent from biomarker records. Our results demonstrate that a combination of palynological and n-alkane data can be used to infer the major sedimentary leaf wax sources and constrain leaf wax transport times from the plant source to the sedimentary sink and thus pave the way towards quantitative interpretation of compound-specific hydrogen isotope ratios for paleohydrological reconstructions. Y1 - 2018 U6 - https://doi.org/10.5194/cp-14-1607-2018 SN - 1814-9324 SN - 1814-9332 VL - 14 IS - 11 SP - 1607 EP - 1624 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Akpniar, Seda A1 - Maas, Desiree A1 - Rooth, Anneke T1 - Deepening Understanding JF - Potsdamer geographische Praxis N2 - 1. Background information 2. Explanations during the lessons 3. Deepening under standing in some assignments 4. Conclusion KW - Europäische Werteerziehung KW - Familie KW - Lehrevaluation KW - Studierendenaustausch KW - Unterrichtseinheiten KW - Curriculum Framework KW - European values education KW - Family KW - lesson evaluation KW - student exchange KW - teaching units KW - curriculum framework Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-65859 SN - 2194-1599 SN - 2194-1602 IS - 1 SP - 81 EP - 85 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Akçay, Pinar A1 - Düşer, Ece A1 - Nozon, Hannes A1 - Strehmel, Christian T1 - Deepening understanding JF - Potsdamer geographische Praxis N2 - 1. Introduction 2. What is deepening understanding and why do we need it? 3. Which concepts were offered to explainthe differences between countries? 4. Maps 5. Summary of the appreciation andperception of the student teachers 6. Summary of the appreciation and perception of the pupils KW - Europäische Werteerziehung KW - Familie KW - Lehrevaluation KW - Studierendenaustausch KW - Unterrichtseinheiten KW - Curriculum Framework KW - European values education KW - Family KW - lesson evaluation KW - student exchange KW - teaching units KW - curriculum framework Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-65957 SN - 2194-1599 SN - 2194-1602 IS - 3 SP - 53 EP - 59 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Altuntaş, Kezban A1 - Akçay, Pinar A1 - Kools, Suzanne A1 - Schnabel, Richard T1 - Assignments, curriculum framework and background information as the base of developing lessons JF - Potsdamer geographische Praxis N2 - 1. What are the general strengths of the assignments? 2. Structure of the assignment 3. Resources of the assignment 4. Fostering self-expression 5. How could you improve the assignment? 6. Lack of specific examples 7. Not relating the issue to the students 8. Language Problems 9. Infeasibility to adaptation 10. In what ways was the additional information useful ? How could this be improved? 11. Was the framework useful for you and in what way? 12. In what ways did the assignments reflect the steps identified in the framework? KW - Europäische Werteerziehung KW - Familie KW - Lehrevaluation KW - Studierendenaustausch KW - Unterrichtseinheiten KW - Curriculum Framework KW - European values education KW - Family KW - lesson evaluation KW - student exchange KW - teaching units KW - curriculum framework Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-65877 SN - 2194-1599 SN - 2194-1602 IS - 1 SP - 93 EP - 98 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Amour, Frederic A1 - Mutti, Maria A1 - Christ, Nicolas A1 - Immenhauser, Adrian A1 - Agar, Susan M. A1 - Benson, Gregory S. A1 - Tomas, Sara A1 - Alway, Robert A1 - Kabiri, Lachen T1 - Capturing and modelling metre-scale spatial facies heterogeneity in a Jurassic ramp setting (Central High Atlas, Morocco) JF - Sedimentology : the journal of the International Association of Sedimentologists N2 - Each simulation algorithm, including Truncated Gaussian Simulation, Sequential Indicator Simulation and Indicator Kriging is characterized by different operating modes, which variably influence the facies proportion, distribution and association of digital outcrop models, as shown in clastic sediments. A detailed study of carbonate heterogeneity is then crucial to understanding these differences and providing rules for carbonate modelling. Through a continuous exposure of Bajocian carbonate strata, a study window (320 m long, 190 m wide and 30 m thick) was investigated and metre-scale lithofacies heterogeneity was captured and modelled using closely-spaced sections. Ten lithofacies, deposited in a shallow-water carbonate-dominated ramp, were recognized and their dimensions and associations were documented. Field data, including height sections, were georeferenced and input into the model. Four models were built in the present study. Model A used all sections and Truncated Gaussian Simulation during the stochastic simulation. For the three other models, Model B was generated using Truncated Gaussian Simulation as for Model A, Model C was generated using Sequential Indicator Simulation and Model D was generated using Indicator Kriging. These three additional models were built by removing two out of eight sections from data input. The removal of sections allows direct insights on geological uncertainties at inter-well spacings by comparing modelled and described sections. Other quantitative and qualitative comparisons were carried out between models to understand the advantages/disadvantages of each algorithm. Model A is used as the base case. Indicator Kriging (Model D) simplifies the facies distribution by assigning continuous geological bodies of the most abundant lithofacies to each zone. Sequential Indicator Simulation (Model C) is confident to conserve facies proportion when geological heterogeneity is complex. The use of trend with Truncated Gaussian Simulation is a powerful tool for modelling well-defined spatial facies relationships. However, in shallow-water carbonate, facies can coexist and their association can change through time and space. The present study shows that the scale of modelling (depositional environment or lithofacies) involves specific simulation constraints on shallow-water carbonate modelling methods. KW - 3D facies modelling KW - carbonate ramp KW - facies heterogeneity KW - Jurassic KW - modelling algorithms KW - scale Y1 - 2012 U6 - https://doi.org/10.1111/j.1365-3091.2011.01299.x SN - 0037-0746 VL - 59 IS - 4 SP - 1158 EP - 1189 PB - Wiley-Blackwell CY - Malden ER - TY - JOUR A1 - Andreev, Andrei A1 - Nazarova, Larisa B. A1 - Lenz, Marlene M. A1 - Böhmer, Thomas A1 - Syrykh, Ludmila A1 - Wagner, Bernd A1 - Melles, Martin A1 - Pestryakova, Luidmila A. A1 - Herzschuh, Ulrike T1 - Late Quaternary paleoenvironmental reconstructions from sediments of Lake Emanda (Verkhoyansk Mountains, East Siberia) JF - Journal of quaternary science : JQS N2 - Continuous pollen and chironomid records from Lake Emanda (65 degrees 17'N, 135 degrees 45'E) provide new insights into the Late Quaternary environmental history of the Yana Highlands (Yakutia). Larch forest with shrubs (alders, pines, birches) dominated during the deposition of the lowermost sediments suggesting its Early Weichselian [Marine Isotope Stage (MIS) 5] age. Pollen- and chironomid-based climate reconstructions suggest July temperatures (T-July) slightly lower than modern. Gradually increasing amounts of herb pollen and cold stenotherm chironomid head capsules reflect cooler and drier environments, probably during the termination of MIS 5. T-July dropped to 8 degrees C. Mostly treeless vegetation is reconstructed during MIS 3. Tundra and steppe communities dominated during MIS 2. Shrubs became common after similar to 14.5 ka BP but herb-dominated habitats remained until the onset of the Holocene. Larch forests with shrub alder and dwarf birch dominated after the Holocene onset, ca. 11.7 ka BP. Decreasing amounts of shrub pollen during the Lateglacial are assigned to the Older Dryas and Younger Dryas with T-July similar to 7.5 degrees C. T-July increased up to 13 degrees C. Shrub stone pine was present after similar to 7.5 ka BP. The vegetation has been similar to modern since ca. 5.8 ka BP. Chironomid diversity and concentration in the sediments increased towards the present day, indicating the development of richer hydrobiological communities in response to the Holocene thermal maximum. KW - chironomids KW - environmental reconstructions KW - Late Quaternary KW - pollen Y1 - 2022 U6 - https://doi.org/10.1002/jqs.3419 SN - 0267-8179 SN - 1099-1417 VL - 37 IS - 5 SP - 884 EP - 899 PB - Wiley CY - New York, NY [u.a.] ER - TY - JOUR A1 - Andreev, Andrei A1 - Raschke, Elena A1 - Biskaborn, Boris A1 - Vyse, Stuart Andrew A1 - Courtin, Jérémy A1 - Böhmer, Thomas A1 - Stoof-Leichsenring, Kathleen R. A1 - Kruse, Stefan A1 - Pestryakova, Luidmila Agafyevna A1 - Herzschuh, Ulrike T1 - Late Pleistocene to Holocene vegetation and climate changes in northwestern Chukotka (Far East Russia) deduced from lakes Ilirney and Rauchuagytgyn pollen records JF - Boreas : an international journal of quaternary research N2 - This paper presents two new pollen records and quantitative climate reconstructions from northern Chukotka documenting environmental changes over the last 27.9 ka. Open tundra- and steppe-like habitats dominated between 27.9 and 18.7 cal. ka BP. Betula and Alnus shrubs might have grown in sheltered microhabitats but disappeared after 18.7 cal. ka BP. Although the climate was rather harsh, local herb-dominated communities supported herbivores as is evident by the presence of coprophilous spores in the sediments. The increase in Salix and Cyperaceae similar to 16.1 cal. ka BP suggests climate amelioration. Shrub Betula appeared similar to 15.9 cal. ka BP, and became dominant after similar to 15.52 cal. ka BP, whilst typical steppe communities drastically reduced. Very high presence of Botryococcus in the Lateglacial sediments reflects widespread shallow habitats, probably due to lake level increase. Shrub Alnus became common after similar to 13 cal. ka BP reflecting further climate amelioration. Simultaneously, herb communities gradually decreased in the vegetation reaching a minimum similar to 11.8 cal. ka BP. A gradual decrease of algae remains suggests a reduction of shallow-water habitats. Shrubby and graminoid tundra was dominant similar to 11.8-11.1 cal. ka BP, later Salix stands significantly decreased. The forest-tundra ecotone established in the Early Holocene, shortly after 11.1 cal. ka BP. Low contents of green algae in the Early Holocene sediments likely reflect deeper aquatic conditions. The most favourable climate conditions were between similar to 10.6 and 7 cal. ka BP. Vegetation became similar to the modern after similar to 7 cal. ka BP but Pinus pumila came to the Ilirney area at about 1.2 cal. ka BP. It is important to emphasize that the study area provided refugia for Betula and Alnus during MIS 2. It is also notable that our records do not reflect evidence of Younger Dryas cooling, which is inconsistent with some regional environmental records but in good accordance with some others. Y1 - 2021 U6 - https://doi.org/10.1111/bor.12521 SN - 0300-9483 SN - 1502-3885 VL - 50 IS - 3 SP - 652 EP - 670 PB - Wiley-Blackwell CY - Oxford [u.a.] ER - TY - JOUR A1 - Arguello de Souza, Felipe Augusto A1 - Samprogna Mohor, Guilherme A1 - Guzman Arias, Diego Alejandro A1 - Sarmento Buarque, Ana Carolina A1 - Taffarello, Denise A1 - Mendiondo, Eduardo Mario T1 - Droughts in São Paulo BT - challenges and lessons for a water-adaptive society JF - Urban water journal N2 - Literature has suggested that droughts and societies are mutually shaped and, therefore, both require a better understanding of their coevolution on risk reduction and water adaptation. Although the Sao Paulo Metropolitan Region drew attention because of the 2013-2015 drought, this was not the first event. This paper revisits this event and the 1985-1986 drought to compare the evolution of drought risk management aspects. Documents and hydrological records are analyzed to evaluate the hazard intensity, preparedness, exposure, vulnerability, responses, and mitigation aspects of both events. Although the hazard intensity and exposure of the latter event were larger than the former one, the policy implementation delay and the dependency of service areas in a single reservoir exposed the region to higher vulnerability. In addition to the structural and non-structural tools implemented just after the events, this work raises the possibility of rainwater reuse for reducing the stress in reservoirs. KW - droughts KW - urban water supply KW - water crisis KW - drought risk KW - paired event KW - analysis KW - vulnerability Y1 - 2022 U6 - https://doi.org/10.1080/1573062X.2022.2047735 SN - 1573-062X SN - 1744-9006 VL - 20 IS - 10 SP - 1682 EP - 1694 PB - Taylor & Francis CY - London [u.a.] ER - TY - JOUR A1 - Asche, Hartmut T1 - Mapping and map use in the age of information technology Y1 - 1998 ER - TY - JOUR A1 - Asche, Hartmut A1 - Hermann, Christian T1 - Thematic cartography Y1 - 2001 SN - 0-7506-4996-8 ER - TY - JOUR A1 - Athare, Tushar Ramchandra A1 - Pradhan, Prajal A1 - Kropp, Jürgen T1 - Environmental implications and socioeconomic characterisation of Indian diets JF - The science of the total environment N2 - India is facing a double burden of malnourishment with co-existences of under- and over-nourishment. Various socioeconomic factors play an essential role in determining dietary choices. Agriculture is one of the major emitters of greenhouse gases (GHGs) in India, contributing 18% of total emissions. It also consumes freshwater and uses land significantly. We identify eleven Indian diets by applying k-means cluster analysis on latest data from the Indian household consumer expenditure survey. The diets vary in calorie intake [2289-3218 kcal/Consumer Unit (CU)/day] and dietary composition. Estimated embodied GHG emissions in the diets range from 1.36 to 3.62 kg CO2eq./CU/day, land footprint from 4 to 5.45 m(2)/CU/day, whereas water footprint varies from 2.13 to 2.97m(3)/CU/day. Indian diets deviate from a healthy reference diet either with too much or too little consumption of certain food groups. Overall, cereals, sugar, and dairy products intake are higher. In contrast, the consumption of fruits and vegetables, pulses, and nuts is lower than recommended. Our study contributes to deriving required polices for the sustainable transformation of food systems in India to eliminate malnourishment and to reduce the environmental implications of the food systems. (c) 2020 Elsevier B.V. All rights reserved. KW - Indian diets KW - GHG emissions KW - land and water footprint KW - healthy diets KW - socioeconomic factors Y1 - 2020 U6 - https://doi.org/10.1016/j.scitotenv.2020.139881 SN - 0048-9697 SN - 1879-1026 VL - 737 PB - Elsevier Science CY - Amsterdam [u.a.] ER - TY - JOUR A1 - Athare, Tushar Ramchandra A1 - Pradhan, Prajal A1 - Singh, S. R. K. A1 - Kropp, Jürgen T1 - India consists of multiple food systems with scoioeconomic and environmental variations JF - PLOS ONE / Public Library of Science N2 - Agriculture in India accounts for 18% of greenhouse gas (GHG) emissions and uses significant land and water. Various socioeconomic factors and food subsidies influence diets in India. Indian food systems face the challenge of sustainably nourishing the 1.3 billion population. However, existing studies focus on a few food system components, and holistic analysis is still missing. We identify Indian food systems covering six food system components: food consumption, production, processing, policy, environmental footprints, and socioeconomic factors from the latest Indian household consumer expenditure survey. We identify 10 Indian food systems using k-means cluster analysis on 15 food system indicators belonging to the six components. Based on the major source of calorie intake, we classify the ten food systems into production-based (3), subsidy-based (3), and market-based (4) food systems. Home-produced and subsidized food contribute up to 2000 kcal/consumer unit (CU)/day and 1651 kcal/CU/day, respectively, in these food systems. The calorie intake of 2158 to 3530 kcal/CU/day in the food systems reveals issues of malnutrition in India. Environmental footprints are commensurate with calorie intake in the food systems. Embodied GHG, land footprint, and water footprint estimates range from 1.30 to 2.19 kg CO(2)eq/CU/day, 3.89 to 6.04 m(2)/CU/day, and 2.02 to 3.16 m(3)/CU/day, respectively. Our study provides a holistic understanding of Indian food systems for targeted nutritional interventions on household malnutrition in India while also protecting planetary health. Y1 - 2022 U6 - https://doi.org/10.1371/journal.pone.0270342 SN - 1932-6203 VL - 17 IS - 8 PB - PLoS CY - San Fransisco ER - TY - JOUR A1 - Avrami, Lydia A1 - Sprinz, Detlef F. T1 - Measuring and explaining the EU’s effect on national climate performance JF - Environmental Politics N2 - To what extent has the European Union (EU) had a benign or retarding effect on what its member states would have undertaken in the absence of EU climate policies during 2008–2012? A measurement tool for the EU policy’s effect is developed and shows a benign average EU effect with considerable variation across countries. The EU’s policy effectiveness vis-à-vis its member states is explained by the EU’s non-compliance mechanism, the degree of usage of the Kyoto flexible mechanisms, and national pre-Kyoto emission reduction goals. Time-series cross-sectional analyses show that the EU’s non-compliance mechanism has no effect, while the ex-ante plans for using Kyoto flexible mechanisms and/or the ambitious pre-Kyoto emission reduction targets allow member states to escape constraints imposed by EU climate policy. KW - Climate change KW - policy effectiveness KW - EU KW - kyoto protocol KW - non-compliance KW - Kyoto (flexible) mechanisms Y1 - 2018 U6 - https://doi.org/10.1080/09644016.2018.1494945 SN - 0964-4016 SN - 1743-8934 VL - 28 IS - 5 SP - 822 EP - 846 PB - Routledge, Taylor & Francis Group CY - Abingdon ER - TY - JOUR A1 - Ayzel, Georgy T1 - Deep neural networks in hydrology BT - the new generation of universal and efficient models BT - новое поколение универсальных и эффективных моделей JF - Vestnik of Saint Petersburg University. Earth Sciences N2 - 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. N2 - В течение последнего десятилетия глубокое обучение - область машинного обучения, относящаяся к искусственным нейронным сетям, состоящим из множества вычислительных слоев, - изменяет ландшафт развития статистических моделей во многих областях исследований, таких как классификация изображений, машинный перевод, распознавание речи. Географические науки, а также входящая в их состав область исследования гидрологии суши, не стоят в стороне от этого движения. В последнее время применение современных технологий и методов глубокого обучения активно набирает популярность для решения широкого спектра гидрологических задач: моделирования и прогнозирования речного стока, районирования модельных параметров, оценки располагаемых водных ресурсов, идентификации факторов, влияющих на современные изменения водного режима. Такой рост популярности глубоких нейронных сетей продиктован прежде всего их высокой универсальностью и эффективностью. Представленные качества в совокупности с быстрорастущим количеством накопленной информации о состоянии окружающей среды, а также ростом доступности вычислительных средств и ресурсов, позволяют говорить о глубоких нейронных сетях как о новом поколении математических моделей, призванных если не заменить существующие решения, то значительно обогатить область моделирования геофизических процессов. В данной работе представлен краткий обзор текущего состояния области разработки и применения глубоких нейронных сетей в гидрологии. Также в работе предложен качественный долгосрочный прогноз развития технологии глубокого обучения для решения задач гидрологического моделирования на основе использования «кривой ажиотажа Гартнера», в общих чертах описывающей жизненный цикл современных технологий. T2 - Глубокие нейронные сети в гидрологии KW - deep neural networks KW - deep learning KW - machine learning KW - hydrology KW - modeling KW - глубокие нейронные сети KW - глубокое обучение KW - машинное обучение KW - гидрология KW - моделирование Y1 - 2021 U6 - https://doi.org/10.21638/spbu07.2021.101 SN - 2541-9668 SN - 2587-585X VL - 66 IS - 1 SP - 5 EP - 18 PB - Univ. Press CY - St. Petersburg ER - TY - JOUR A1 - Ayzel, Georgy A1 - Heistermann, Maik T1 - The effect of calibration data length on the performance of a conceptual hydrological model versus LSTM and GRU BT - a case study for six basins from the CAMELS dataset JF - Computers & geosciences : an international journal devoted to the publication of papers on all aspects of geocomputation and to the distribution of computer programs and test data sets ; an official journal of the International Association for Mathematical Geology N2 - We systematically explore the effect of calibration data length on the performance of a conceptual hydrological model, GR4H, in comparison to two Artificial Neural Network (ANN) architectures: Long Short-Term Memory Networks (LSTM) and Gated Recurrent Units (GRU), which have just recently been introduced to the field of hydrology. We implemented a case study for six river basins across the contiguous United States, with 25 years of meteorological and discharge data. Nine years were reserved for independent validation; two years were used as a warm-up period, one year for each of the calibration and validation periods, respectively; from the remaining 14 years, we sampled increasing amounts of data for model calibration, and found pronounced differences in model performance. While GR4H required less data to converge, LSTM and GRU caught up at a remarkable rate, considering their number of parameters. Also, LSTM and GRU exhibited the higher calibration instability in comparison to GR4H. These findings confirm the potential of modern deep-learning architectures in rainfall runoff modelling, but also highlight the noticeable differences between them in regard to the effect of calibration data length. KW - Artificial neural networks KW - Calibration KW - Deep learning KW - Rainfall-runoff KW - modelling Y1 - 2021 U6 - https://doi.org/10.1016/j.cageo.2021.104708 SN - 0098-3004 SN - 1873-7803 VL - 149 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Ayzel, Georgy A1 - Heistermann, Maik A1 - Winterrath, Tanja T1 - Optical flow models as an open benchmark for radar-based precipitation nowcasting (rainymotion v0.1) JF - Geoscientific model development N2 - Quantitative precipitation nowcasting (QPN) has become an essential technique in various application contexts, such as early warning or urban sewage control. A common heuristic prediction approach is to track the motion of precipitation features from a sequence of weather radar images and then to displace the precipitation field to the imminent future (minutes to hours) based on that motion, assuming that the intensity of the features remains constant (“Lagrangian persistence”). In that context, “optical flow” has become one of the most popular tracking techniques. Yet the present landscape of computational QPN models still struggles with producing open software implementations. Focusing on this gap, we have developed and extensively benchmarked a stack of models based on different optical flow algorithms for the tracking step and a set of parsimonious extrapolation procedures based on image warping and advection. We demonstrate that these models provide skillful predictions comparable with or even superior to state-of-the-art operational software. Our software library (“rainymotion”) for precipitation nowcasting is written in the Python programming language and openly available at GitHub (https://github.com/hydrogo/rainymotion, Ayzel et al., 2019). That way, the library may serve as a tool for providing fast, free, and transparent solutions that could serve as a benchmark for further model development and hypothesis testing – a benchmark that is far more advanced than the conventional benchmark of Eulerian persistence commonly used in QPN verification experiments. KW - machine KW - system Y1 - 2019 U6 - https://doi.org/10.5194/gmd-12-1387-2019 SN - 1991-9603 SN - 1991-959X IS - 12 SP - 1387 EP - 1402 PB - Copernicus Publications CY - Göttingen ER - TY - JOUR A1 - Ayzel, Georgy A1 - Izhitskiy, Alexander T1 - Climate Change Impact Assessment on Freshwater Inflow into the Small Aral Sea JF - Water N2 - 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. KW - Small Aral Sea KW - hydrology KW - climate change KW - modeling KW - machine learning Y1 - 2019 U6 - https://doi.org/10.3390/w11112377 SN - 2073-4441 VL - 11 IS - 11 PB - MDPI CY - Basel ER - TY - JOUR A1 - Azar, Elif Zeynep A1 - Erdönmez, Çağlayan A1 - Verscheijden, Desirée T1 - Developing Critical Thinking JF - Potsdamer geographische Praxis N2 - 1. Critical thinking in curriculum framework 2. A general look at critical thinking 3. How critical thinking take s place in the classroom and some specific examples 4. Suggestions 5. Conclusion KW - Europäische Werteerziehung KW - Familie KW - Lehrevaluation KW - Studierendenaustausch KW - Unterrichtseinheiten KW - Curriculum Framework KW - European values education KW - Family KW - lesson evaluation KW - student exchange KW - teaching units KW - curriculum framework Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-65867 SN - 2194-1599 SN - 2194-1602 IS - 1 SP - 87 EP - 92 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Baars, Daniela A1 - Bajzík, Michal A1 - Pisarčík, Stanislav A1 - Weiser, Ines T1 - Developing critical thinking JF - Potsdamer geographische Praxis N2 - 1. What does critical thinking mean? 2. Critical thinking in school 3. Critical thinking as a process 4. Analysing and evaluating the questionnaire 5. Interview with one of the students 6. Analysis and evaluation of the assignments 7. Conclusion KW - Europäische Werteerziehung KW - Familie KW - Lehrevaluation KW - Studierendenaustausch KW - Unterrichtseinheiten KW - Curriculum Framework KW - European values education KW - Family KW - lesson evaluation KW - student exchange KW - teaching units KW - curriculum framework Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-65798 SN - 2194-1599 SN - 2194-1602 IS - 1 SP - 45 EP - 51 PB - Universitätsverlag Potsdam CY - Potsdam ER -