Manish Shrestha

Mr. Manish Shrestha

orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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21 June 2017 in Meteorological Applications
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Journal Article
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MSManish Shrestha
Manish Shrestha
SASuwash Acharya
Suwash Acharya
PSPallav Shrestha
Pallav Shrestha

1 January 2017 in Science of The Total Environment
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Journal Article
Closed access
NTNguyen Thi Thuy Trang
Nguyen Thi Thuy Trang
SSSangam Shrestha
Sangam Shrestha
MSManish Shrestha
Manish Shrestha
ADAvishek Datta
Avishek Datta
Akiyuki KawasakiAkiyuki Kawasaki
Akiyuki Kawasaki

9 February 2016 in Environmental Earth Sciences
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Journal Article
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SSSangam Shrestha
Sangam Shrestha
MSManish Shrestha
Manish Shrestha
MBMukand. S. Babel
Mukand. S. Babel


29 December 2015 in Theoretical and Applied Climatology
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Journal Article
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SSSangam Shrestha
Sangam Shrestha
MSManish Shrestha
Manish Shrestha
MBMukand S. Babel
Mukand S. Babel

1 September 2021 in Natural Hazards
Verified
Journal Article
Open access
PDF file
KTKarma Tsering
Karma Tsering
MSManish Shrestha
Manish Shrestha
KSKiran Shakya
Kiran Shakya
BBBirendra Bajracharya
Birendra Bajracharya
MMMir Matin
Mir Matin
ABArifuzzaman Bhuyan
Arifuzzaman Bhuyan
The Hindu Kush Himalayan region is extremely susceptible to periodic monsoon floods. Early warning systems with the ability to predict floods in advance can benefit tens of millions of people living in the region. Two web-based flood forecasting tools (ECMWF-SPT and HIWAT-SPT) are therefore developed and deployed jointly by SERVIR-HKH and NASA-AST to provide early warning to Bangladesh, Bhutan, and Nepal. ECMWF-SPT provides ensemble forecast up to 15-day lead time, whereas HIWAT-SPT provides deterministic forecast up to 3-day lead time covering almost 100% of the rivers. Hydrological models in conjunction with forecast validation contribute not only to advancing the processes of a forecasting system, but also objectively assess the joint distribution of forecasts and observations in quantifying forecast accuracy. The validation of forecast products has emerged as a priority need to evaluate the worth of the predictive information in terms of quality and consistency. This paper describes the effort made in developing the hydrological forecast systems, the current state of the flood forecast services, and the performance of the forecast evaluation. Both tools are validated using a selection of appropriate metrics in measurement in both probabilistic and deterministic space. The numerical metrics are further complemented by graphical representations of scores and probabilities. It was found that the models had a good performance in capturing high flood events. The evaluation across multiple locations indicates that the model performance and forecast goodness are variable on spatiotemporal scale. The resulting information is used to support good decision-making in risk and resource management.