Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Vamsi Krishna Vema"'
Publikováno v:
Journal of Water and Climate Change, Vol 15, Iss 2, Pp 476-498 (2024)
This study assessed the impacts of climate change on the water balance of the Krishna River Basin (KRB) in India. A frequency-based metric, known as symmetric uncertainty, was used to select the top 50% of global climate models (GCMs) from a pool of
Externí odkaz:
https://doaj.org/article/00a2df6179764b8f82de6a3cfd9ed694
Autor:
Silpa Senan, Jobin Thomas, Vamsi Krishna Vema, P. J. Jainet, Sinan Nizar, Shyama Sivan, K. P. Sudheer
Publikováno v:
Journal of Water and Climate Change, Vol 13, Iss 12, Pp 4234-4254 (2022)
Rainfall is a vital input to model watershed hydrology, and the availability of numerous gridded and point-observed rainfall datasets poses a major challenge to the modellers to choose the appropriate data. This study compares three gridded rainfall
Externí odkaz:
https://doaj.org/article/a7105ef2741245eea0dcf332eb955415
Autor:
Dasari Indhu, Vamsi Krishna Vema
The major socioeconomic issue affecting the nation's economy is flooding. The use of hydrologic models to predict floods has been the subject of numerous well-founded research, but little is still known about how spatial variability of rainfall affec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::29960d3cebfa033033bb572ff5e40fb2
https://doi.org/10.5194/egusphere-egu23-143
https://doi.org/10.5194/egusphere-egu23-143
Publikováno v:
Water Resources Management. 36:1627-1644
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3edea76f1365c0fdf4275fcd184fc7b1
https://doi.org/10.1007/s11269-022-03094-4
https://doi.org/10.1007/s11269-022-03094-4
Autor:
Vamsi Krishna Vema, Manikanta Velpuri
Publikováno v:
Water Resources Research. 58
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9f1391273f874531b43258a013d2635a
https://doi.org/10.1029/2020wr029355
https://doi.org/10.1029/2020wr029355
Publikováno v:
Stochastic Environmental Research and Risk Assessment. 34:973-991
The uncertainties associated with the simulation models are often ignored in operational hydrology. While many methods are available for evaluation of simulation uncertainty, most of them focus on construction of prediction bands, which alone may not
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::55053fb8eab2c97022c250bfd0bc9fe7
https://doi.org/10.1007/s00477-020-01814-z
https://doi.org/10.1007/s00477-020-01814-z
Publikováno v:
Agricultural Water Management. 218:82-93
Watershed management (WM) aims at enhancing the water availability in rainfed areas through water conservation structures, which facilitate storage of water and recharge to ground water. Identification of suitable locations for placing these structur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::569a427ef6fda694ff756d99fca38733
https://doi.org/10.1016/j.agwat.2019.03.028
https://doi.org/10.1016/j.agwat.2019.03.028
Publikováno v:
Stochastic Environmental Research and Risk Assessment.
The increasing demand for food and clean energy, such as biofuel calls for a sustainable food-energy nexus in the agriculture sector. Mixed cropping pattern of food and biofuel crops is a viable strategy to meet the escalating demands of the biofuel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f360d96689897b739c28c710756ed5b7
https://doi.org/10.1007/s00477-021-01983-5
https://doi.org/10.1007/s00477-021-01983-5
Publikováno v:
Journal of Hydrology. 563:460-469
Watershed management in rainfed agricultural areas of arid and semi-arid regions aims at alleviating agricultural drought by employing water conservation measures. Water conservation measures serve as mechanisms for recharging groundwater, and also f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec824ac62c9cae0459fed1b0b494d45b
https://doi.org/10.1016/j.jhydrol.2018.06.020
https://doi.org/10.1016/j.jhydrol.2018.06.020
Publikováno v:
Journal of Hydrology. 587:124945
Artificial neural network has been acknowledged as a promising tool for accurately forecasting the streamflow. However, several constraints limit its application in operational hydrology; the primary one being, the non-availability (practically not a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::48c30152bce1d2b75bd54dab29706b18
https://doi.org/10.1016/j.jhydrol.2020.124945
https://doi.org/10.1016/j.jhydrol.2020.124945