Employing sensitivity analysis to catchments having scanty data-Reference-Cited by-同舟云学术

Employing sensitivity analysis to catchments having scanty data

Published:2022-05-09 Issue:45 Volume:29 Page:68118-68131
ISSN:0944-1344
Container-title:Environmental Science and Pollution Research
language:en
Short-container-title:Environ Sci Pollut Res

Author:

Nabi Sakiba^ORCID,Ahanger Manzoor Ahmad,Dar Abdul Qayoom

Publisher

Springer Science and Business Media LLC

Subject

Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s11356-022-20514-5.pdf

Reference47 articles.

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2. Bárdossy A, Anwar F Seidel J (2020) Hydrological modelling in data sparse environment: inverse modelling of a historical flood event. Water (Switzerland) 12(11). https://doi.org/10.3390/w12113242.

3. Blasone R et al (2008) Generalized likelihood uncertainty estimation ( GLUE ) using adaptive Markov Chain Monte Carlo sampling. Adv Water Resour Elsevier Ltd 31(4):630–648. https://doi.org/10.1016/j.advwatres.2007.12.003

4. Bournas A, Baltas E (2021) ‘Increasing the efficiency of the sacramento model on event basis in a mountainous river basin.’ Environ Proc Springer Sci Bus Media Deutschland GmbH 8(2):943–958. https://doi.org/10.1007/S40710-021-00504-4/TABLES/4

5. Burnash RJC (1995) Computer models of watershed hydrology. In: Singh VP (ed) The NWS river forecast system - catchment modeling. Water Resources Publications, Colorado, USA, pp 311–366

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