Deutsch
 
Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Zeitschriftenartikel

Climate informed seasonal forecast of water availability in Central Asia: State-of-the-art and decision making context

Urheber*innen
/persons/resource/lgerlitz

Gerlitz,  Lars
4.4 Hydrology, 4.0 Geosystems, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/vorogus

Vorogushyn,  S.
4.4 Hydrology, 4.0 Geosystems, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/gafurov

Gafurov,  Abror
4.4 Hydrology, 4.0 Geosystems, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Externe Ressourcen
Es sind keine externen Ressourcen hinterlegt
Volltexte (frei zugänglich)

5001836.pdf
(Verlagsversion), 4MB

Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Gerlitz, L., Vorogushyn, S., Gafurov, A. (2020): Climate informed seasonal forecast of water availability in Central Asia: State-of-the-art and decision making context. - Water Security, 10, 100061.
https://doi.org/10.1016/j.wasec.2020.100061


Zitierlink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5001836
Zusammenfassung
Central Asia is characterized by a continental climate and a pronounced inter-annual variability of precipitation and discharge. In the past, hydro-climatological droughts led to serious water shortages, resulting in crop shortfalls, significant economic loss and inter-state political tensions. Robust forecasts of anomalous climatic and hydrological conditions may reduce regional vulnerability to hydro-climatic extremes and thus can serve as a scientific basis for national and trans-national water management. Based on a synthesis of international literature and on our decadal-long experience in the region, we systematically review the scientific progress in seasonal forecasting and evaluate the potential for a scientifically-informed water management. Additionally, we discuss to what extent the scientific progress meets the requirements of stakeholders and reveal major obstacles for a sustainable knowledge transfer. Our review shows that exceptionally skillful discharge forecasts for the agricultural relevant vegetation season can be derived by means of statistical models taking remote-sensing based estimations of the snow coverage in the Central Asian mountain regions as independent covariates. The consideration of global climate indices, in particular El Niño, allows to extend the forecast lead-times. However, decision makers are often not aware of the scientific progress and its implications for improved water management. Despite the continuous international effort with regard to knowledge transfer and capacity development, modernization at Central Asian water management institutions is proceeding slowly. A continuous engagement in the field of capacity development and knowledge dissemination at various institutional levels (including academia, forecast centers and water management institutions) appears necessary in order to stimulate a multi-disciplinary network and to support a sustainable regional collaboration in the water sector.