TY  - JOUR
A1  - Norris, Jesse
A1  - Carvalho, Leila M. V.
A1  - Jones, Charles
A1  - Cannon, Forest
A1  - Bookhagen, Bodo
A1  - Palazzi, Elisa
A1  - Tahir, Adnan Ahmad
T1  - The spatiotemporal variability of precipitation over the Himalaya: evaluation of one-year WRF model simulation
JF  - Climate dynamics : observational, theoretical and computational research on the climate system
N2  - The Weather Research and Forecasting (WRF) model is used to simulate the spatiotemporal distribution of precipitation over central Asia over the year April 2005 through March 2006. Experiments are performed at 6.7 km horizontal grid spacing, with an emphasis on winter and summer precipitation over the Himalaya. The model and the Tropical Rainfall Measuring Mission show a similar inter-seasonal cycle of precipitation, from extratropical cyclones to monsoon precipitation, with agreement also in the diurnal cycle of monsoon precipitation. In winter months, WRF compares better in timeseries of daily precipitation to stations below than above 3-km elevation, likely due to inferior measurement of snow than rain by the stations, highlighting the need for reliable snowfall measurements at high elevations in winter. In summer months, the nocturnal precipitation cycle in the foothills and valleys of the Himalaya is captured by this 6.7-km WRF simulation, while coarser simulations with convective parameterization show near zero nocturnal precipitation. In winter months, higher resolution is less important, serving only to slightly increase precipitation magnitudes due to steeper slopes. However, even in the 6.7-km simulation, afternoon precipitation is overestimated at high elevations, which can be reduced by even higher-resolution (2.2-km) simulations. These results indicate that WRF provides skillful simulations of precipitation relevant for studies of water resources over the complex terrain in the Himalaya.
KW  - WRF
KW  - Himalayas
KW  - Mesoscale
KW  - Precipitation
KW  - Climate change
KW  - Orographicprecipitation
KW  - Water resources
Y1  - 2017
U6  - https://doi.org/10.1007/s00382-016-3414-y
SN  - 0930-7575
SN  - 1432-0894
VL  - 49
SP  - 2179
EP  - 2204
PB  - Springer
CY  - New York
ER  - 
TY  - THES
A1  - Huang, Shaochun
T1  - Modelling of environmental change impacts on water resources and hydrological extremes in Germany
T1  - Modellierung der Auswirkungen von Umweltveränderungen auf Wasserressourcen und Extremereignisse in Deutschland
N2  - Water resources, in terms of quantity and quality, are significantly influenced by environmental changes, especially by climate and land use changes. The main objective of the present study is to project climate change impacts on the seasonal dynamics of water fluxes, spatial changes in water balance components as well as the future flood and low flow conditions in Germany. This study is based on the modeling results of the process-based eco-hydrological model SWIM (Soil and Water Integrated Model) driven by various regional climate scenarios on one hand. On the other hand, it is supported by statistical analysis on long-term trends of observed and simulated time series. In addition, this study evaluates the impacts of potential land use changes on water quality in terms of NO3-N load in selected sub-regions of the Elbe basin. In the context of climate change, the actual evapotransipration is likely to increase in most parts of Germany, while total runoff generation may decrease in south and east regions in the scenario period 2051-2060. Water discharge in all six studied large rivers (Ems, Weser, Saale, Danube, Main and Neckar) would be 8 – 30% lower in summer and autumn compared to the reference period (1961 – 1990), and the strongest decline is expected for the Saale, Danube and Neckar. The 50-year low flow is likely to occur more frequently in western, southern and central Germany after 2061 as suggested by more than 80% of the model runs. The current low flow period (from August to September) may be extended until the late autumn at the end of this century. Higher winter flow is expected in all of these rivers, and the increase is most significant for the Ems (about 18%). No general pattern of changes in flood directions can be concluded according to the results driven by different RCMs, emission scenarios and multi-realizations. An optimal agricultural land use and management are essential for the reduction in nutrient loads and improvement of water quality. In the Weiße Elster and Unstrut sub-basins (Elbe), an increase of 10% in the winter rape area can result in 12-19% more NO3-N load in rivers. In contrast, another energy plant, maize, has a moderate effect on the water environment. Mineral fertilizers have a much stronger effect on the NO3-N load than organic fertilizers. Cover crops, which play an important role in the reduction of nitrate losses from fields, should be maintained on cropland. The uncertainty in estimating future high flows and, in particular, extreme floods remain high due to different RCM structures, emission scenarios and multi-realizations. In contrast, the projection of low flows under warmer climate conditions appears to be more pronounced and consistent. The largest source of uncertainty related to NO3-N modelling originates from the input data on the agricultural management.
N2  - Wasserressourcen werden in Quantität und Qualität von Veränderungen in der Umwelt, insbesondere von Änderungen des Klimas und der Landnutzung, in signifikantem Maße beeinflusst. In dieser Arbeit wurden die Auswirkungen von Klimavariabilität und Klimawandel auf die Wasserressourcen und Extremereignisse wie Hoch- und Niedrigwasser in Deutschland untersucht. Die Analyse erfolgte auf der einen Seite modellgestützt, wobei die Ergebnisse aus verschiedenen regionalen Klimamodellen durch ein ökohydrologisches Modell in Änderungen in den hydrologischen Prozessen transformiert wurden, zum anderen aber auch datengestützt, z.B. durch die statistische Interpretation von beobachteten und simulierten Zeitreihen. Zusätzlich wurden die Auswirkungen von Landnutzungsänderungen auf Umsatz von Stickstoff in der Landschaft und im Wasser untersucht, wobei dasselbe ökohydrologische Modell zum Einsatz kam. Im Rahmen des Klimawandels wird zur Mitte dieses Jahrhunderts die aktuelle Evapotranspiration in den meisten Teilen Deutschlands mit großer Wahrscheinlichkeit zunehmen. Die täglichen Abflussmengen der fünf größten Flussgebiete in Deutschland (Ems, Weser, Elbe, Obere Donau und Rhein) werden dieser Untersuchung zur Folge im Sommer und Herbst um 8%-30% geringer sein als in der Referenzperiode (1961-1990). 80% der Szenariensimulationen stimmen darin überein, dass die 50-jährigen Niedrigwasserereignisse zum Ende dieses Jahrhunderts mit großer Wahrscheinlichkeit häufiger in den westlichen, den südlichen und den zentralen Teilen Deutschlands auftreten werden. Die gegenwärtige Niedrigwasserperiode (August-September) könnte sich zudem dann bis in den späten Herbst ausweiten. Für alle Flüsse werden höhere Winterabflüsse erwartet, wobei diese Zunahme für die Ems am stärksten ausfällt (ca. 18%). Mit größerer Unsicherheit sind dagegen die Aussagen zur Entwicklung der Hochwasser behaftet. Aus den Ergebnissen, die durch unterschiedliche regionale Klimamodelle und Szenarien getrieben wurden, kann jedoch kein allgemeingültiges Muster für die Änderungen der 50-jährigen Hochwässer ausgemacht werden. Eine optimierte Landnutzung und ein optimiertes Landmanagement sind für die Reduzierung der NO3-Einträge in die Oberflächengewässer essentiell. In den Einzusgebieten der Weißen Elster und der Unstrut (Elbe) kann eine Zunahme von 10% in der Anbaufläche von Winterraps zu einer 12-19% höheren NO3 Fracht führen. Mais, eine weitere Energiepflanze, hat hingegen einen mäßigeren Effekt auf die Oberflächengewässer. Die Höhe der Gabe von mineralischen Düngern beeinflußt zudem in starkem Maße die Nitratbelastung von Flüssen. Zwischenfrüchte können den NO3-Austrag im Sommer zusätzlich erheblich verringern. Insgesamt bleibt die Unsicherheit in der Vorhersage von Spitzenabflüssen und im Besonderen von Extrem-Hochwässern als Folge unterschiedlicher regionaler Klimamodelle, Emissionsszenarien und Realisationen sehr hoch. Im Gegensatz dazu erscheinen die Projektionen zu den Niedrigwasserereignissen unter wärmeren Bedingungen sehr viel deutlicher und einheitlicher. Die größte Unsicherheit in der Modellierung von NO3 dagegen sind die Eingangsdaten z.B. für das lokale landwirtschaftliche Management.
KW  - Climate change
KW  - Land use change
KW  - Water resources
KW  - Hydrological extremes
KW  - Germany
Y1  - 2012
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-59748
ER  - 
TY  - JOUR
A1  - Mantzouki, Evanthia
A1  - Campbell, James
A1  - van Loon, Emiel
A1  - Visser, Petra
A1  - Konstantinou, Iosif
A1  - Antoniou, Maria
A1  - Giuliani, Gregory
A1  - Machado-Vieira, Danielle
A1  - de Oliveira, Alinne Gurjao
A1  - Maronic, Dubravka Spoljaric
A1  - Stevic, Filip
A1  - Pfeiffer, Tanja Zuna
A1  - Vucelic, Itana Bokan
A1  - Zutinic, Petar
A1  - Udovic, Marija Gligora
A1  - Plenkovic-Moraj, Andelka
A1  - Tsiarta, Nikoletta
A1  - Blaha, Ludek
A1  - Geris, Rodan
A1  - Frankova, Marketa
A1  - Christoffersen, Kirsten Seestern
A1  - Warming, Trine Perlt
A1  - Feldmann, Tonu
A1  - Laas, Alo
A1  - Panksep, Kristel
A1  - Tuvikene, Lea
A1  - Kangro, Kersti
A1  - Haggqvist, Kerstin
A1  - Salmi, Pauliina
A1  - Arvola, Lauri
A1  - Fastner, Jutta
A1  - Straile, Dietmar
A1  - Rothhaupt, Karl-Otto
A1  - Fonvielle, Jeremy Andre
A1  - Grossart, Hans-Peter
A1  - Avagianos, Christos
A1  - Kaloudis, Triantafyllos
A1  - Triantis, Theodoros
A1  - Zervou, Sevasti-Kiriaki
A1  - Hiskia, Anastasia
A1  - Gkelis, Spyros
A1  - Panou, Manthos
A1  - McCarthy, Valerie
A1  - Perello, Victor C.
A1  - Obertegger, Ulrike
A1  - Boscaini, Adriano
A1  - Flaim, Giovanna
A1  - Salmaso, Nico
A1  - Cerasino, Leonardo
A1  - Koreiviene, Judita
A1  - Karosiene, Jurate
A1  - Kasperoviciene, Jurate
A1  - Savadova, Ksenija
A1  - Vitonyte, Irma
A1  - Haande, Sigrid
A1  - Skjelbred, Birger
A1  - Grabowska, Magdalena
A1  - Karpowicz, Maciej
A1  - Chmura, Damian
A1  - Nawrocka, Lidia
A1  - Kobos, Justyna
A1  - Mazur-Marzec, Hanna
A1  - Alcaraz-Parraga, Pablo
A1  - Wilk-Wozniak, Elzbieta
A1  - Krzton, Wojciech
A1  - Walusiak, Edward
A1  - Gagala, Ilona
A1  - Mankiewicz-Boczek, Joana
A1  - Toporowska, Magdalena
A1  - Pawlik-Skowronska, Barbara
A1  - Niedzwiecki, Michal
A1  - Peczula, Wojciech
A1  - Napiorkowska-Krzebietke, Agnieszka
A1  - Dunalska, Julita
A1  - Sienska, Justyna
A1  - Szymanski, Daniel
A1  - Kruk, Marek
A1  - Budzynska, Agnieszka
A1  - Goldyn, Ryszard
A1  - Kozak, Anna
A1  - Rosinska, Joanna
A1  - Szelag-Wasielewska, Elzbieta
A1  - Domek, Piotr
A1  - Jakubowska-Krepska, Natalia
A1  - Kwasizur, Kinga
A1  - Messyasz, Beata
A1  - Pelechata, Aleksandra
A1  - Pelechaty, Mariusz
A1  - Kokocinski, Mikolaj
A1  - Madrecka, Beata
A1  - Kostrzewska-Szlakowska, Iwona
A1  - Frak, Magdalena
A1  - Bankowska-Sobczak, Agnieszka
A1  - Wasilewicz, Michal
A1  - Ochocka, Agnieszka
A1  - Pasztaleniec, Agnieszka
A1  - Jasser, Iwona
A1  - Antao-Geraldes, Ana M.
A1  - Leira, Manel
A1  - Hernandez, Armand
A1  - Vasconcelos, Vitor
A1  - Morais, Joao
A1  - Vale, Micaela
A1  - Raposeiro, Pedro M.
A1  - Goncalves, Vitor
A1  - Aleksovski, Boris
A1  - Krstic, Svetislav
A1  - Nemova, Hana
A1  - Drastichova, Iveta
A1  - Chomova, Lucia
A1  - Remec-Rekar, Spela
A1  - Elersek, Tina
A1  - Delgado-Martin, Jordi
A1  - Garcia, David
A1  - Luis Cereijo, Jose
A1  - Goma, Joan
A1  - Carmen Trapote, Mari
A1  - Vegas-Vilarrubia, Teresa
A1  - Obrador, Biel
A1  - Garcia-Murcia, Ana
A1  - Real, Monserrat
A1  - Romans, Elvira
A1  - Noguero-Ribes, Jordi
A1  - Parreno Duque, David
A1  - Fernandez-Moran, Elisabeth
A1  - Ubeda, Barbara
A1  - Angel Galvez, Jose
A1  - Marce, Rafael
A1  - Catalan, Nuria
A1  - Perez-Martinez, Carmen
A1  - Ramos-Rodriguez, Eloisa
A1  - Cillero-Castro, Carmen
A1  - Moreno-Ostos, Enrique
A1  - Maria Blanco, Jose
A1  - Rodriguez, Valeriano
A1  - Juan Montes-Perez, Jorge
A1  - Palomino, Roberto L.
A1  - Rodriguez-Perez, Estela
A1  - Carballeira, Rafael
A1  - Camacho, Antonio
A1  - Picazo, Antonio
A1  - Rochera, Carlos
A1  - Santamans, Anna C.
A1  - Ferriol, Carmen
A1  - Romo, Susana
A1  - Soria, Juan Miguel
A1  - Hansson, Lars-Anders
A1  - Urrutia-Cordero, Pablo
A1  - Ozen, Arda
A1  - Bravo, Andrea G.
A1  - Buck, Moritz
A1  - Colom-Montero, William
A1  - Mustonen, Kristiina
A1  - Pierson, Don
A1  - Yang, Yang
A1  - Verspagen, Jolanda M. H.
A1  - Domis, Lisette N. de Senerpont
A1  - Seelen, Laura
A1  - Teurlincx, Sven
A1  - Verstijnen, Yvon
A1  - Lurling, Miquel
A1  - Maliaka, Valentini
A1  - Faassen, Elisabeth J.
A1  - Latour, Delphine
A1  - Carey, Cayelan C.
A1  - Paerl, Hans W.
A1  - Torokne, Andrea
A1  - Karan, Tunay
A1  - Demir, Nilsun
A1  - Beklioglu, Meryem
A1  - Filiz, Nur
A1  - Levi, Eti E.
A1  - Iskin, Ugur
A1  - Bezirci, Gizem
A1  - Tavsanoglu, Ulku Nihan
A1  - Celik, Kemal
A1  - Ozhan, Koray
A1  - Karakaya, Nusret
A1  - Kocer, Mehmet Ali Turan
A1  - Yilmaz, Mete
A1  - Maraslioglu, Faruk
A1  - Fakioglu, Ozden
A1  - Soylu, Elif Neyran
A1  - Yagci, Meral Apaydin
A1  - Cinar, Sakir
A1  - Capkin, Kadir
A1  - Yagci, Abdulkadir
A1  - Cesur, Mehmet
A1  - Bilgin, Fuat
A1  - Bulut, Cafer
A1  - Uysal, Rahmi
A1  - Koker, Latife
A1  - Akcaalan, Reyhan
A1  - Albay, Meric
A1  - Alp, Mehmet Tahir
A1  - Ozkan, Korhan
A1  - Sevindik, Tugba Ongun
A1  - Tunca, Hatice
A1  - Onem, Burcin
A1  - Richardson, Jessica
A1  - Edwards, Christine
A1  - Bergkemper, Victoria
A1  - Beirne, Eilish
A1  - Cromie, Hannah
A1  - Ibelings, Bastiaan W.
T1  - Data Descriptor: A European Multi Lake Survey dataset of environmental variables, phytoplankton pigments and cyanotoxins
JF  - Scientific Data
N2  - Under ongoing climate change and increasing anthropogenic activity, which continuously challenge ecosystem resilience, an in-depth understanding of ecological processes is urgently needed. Lakes, as providers of numerous ecosystem services, face multiple stressors that threaten their functioning. Harmful cyanobacterial blooms are a persistent problem resulting from nutrient pollution and climate-change induced stressors, like poor transparency, increased water temperature and enhanced stratification. Consistency in data collection and analysis methods is necessary to achieve fully comparable datasets and for statistical validity, avoiding issues linked to disparate data sources. The European Multi Lake Survey (EMLS) in summer 2015 was an initiative among scientists from 27 countries to collect and analyse lake physical, chemical and biological variables in a fully standardized manner. This database includes in-situ lake variables along with nutrient, pigment and cyanotoxin data of 369 lakes in Europe, which were centrally analysed in dedicated laboratories. Publishing the EMLS methods and dataset might inspire similar initiatives to study across large geographic areas that will contribute to better understanding lake responses in a changing environment.
KW  - Climate-change ecology
KW  - Limnology
KW  - Water resources
Y1  - 2018
U6  - https://doi.org/10.1038/sdata.2018.226
SN  - 2052-4463
VL  - 5
PB  - Nature Publ. Group
CY  - London
ER  -