Text

Forecast future disasters using hydro-meteorological datasets in the Yamuna river basin, Western Himalaya: Using Markov Chain and LSTM approaches

This research aim to evaluate hydro-meteorological data from the Yamuna River Basin, Uttarakhand, India, utilizing Extreme Value Distribution of Frequency Analysis and the Markov Chain Approach. This method assesses persistence and allows for combinatorial probability estimations such as initial and transitional probabilities. The hydrologic data was generated (in-situ) and received from Uttarakhand Jal Vidut Nigam Limited (UJVNL), and meteorological data was acquired from NASA's archives MERRA-2 product. A total of sixteen years (2005–2020) of data was used to foresee daily Precipitation from 2020 to 2022. MERRA-2 products are utilized as observed and forecast values for daily Precipitation throughout the monsoon season, which runs from July to September. Markov Chain and Long Short-Term Memory (LSTM) findings for 2020, 2021, and 2022 were observed, and anticipated values for daily rainfall during the monsoon season between July and September. According to test findings, the artificial intelligence technique cannot anticipate future regional meteorological formations; the correlation coefficient R2 is around 0.12. According to the randomly verified precipitation data findings, the Markov Chain model has a success rate of 79.17 percent. The results suggest that extended return periods should be a warning sign for drought and flood risk in the Himalayan region. This study gives a better knowledge of the water budget, climate change variability, and impact of global warming, ultimately leading to improved water resource management and better emergency planning to the establishment of the Early Warning System (EWS) for extreme occurrences such as cloudbursts, flash floods, landslides hazards in the complex Himalayan region.

Availability

Detail Information

Series Title

Artificial Intelligence in Geosciences

Call Number

551

Publisher

Beijing : KeAi Communications Co. Ltd.., 2024

Collation

23 hlm PDF, 18,684 KB

Language

Inggris

ISBN/ISSN

2666-5441

Classification

551

Content Type

text

Media Type

-

Carrier Type

-

Edition

Vol.5, December 2024

Subject(s)

LSTM
Forecast disasters
Western Himalaya
Hydro-meteorological hazards
Markov chain
Yamuna river basin

Specific Detail Info

-

Statement of Responsibility

-

Other version/related

File Attachment

Comments