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Hydrology and Drought Analysis

TopicLeading institutions, researchers & key papers

This cluster of papers focuses on the monitoring, assessment, and impacts of drought at a global scale. It covers various aspects such as the development of drought indices, the influence of global warming and climate change on drought severity and frequency, hydrological implications, remote sensing techniques for drought monitoring, and the use of evapotranspiration data. The research also delves into the challenges and future directions in drought assessment.

18
Works

How has Hydrology and Drought Analysis's publication output changed over time?

ScholarIQpublication output · 2014–2023

Output grew0% over the shown period — from 1 works in 2014 to 1 in 2023.

1
1
1
201420212023

What are the most-cited papers on Hydrology and Drought Analysis?

ScholarIQmost cited works
Estimation of SPEI Meteorological Drought Using Machine Learning Algorithms
Ali Mokhtar, Mohammadnabi Jalali, Hongming He, Nadhir Al‐Ansari, Ahmed Elbeltagi, Karam Alsafadi, Hazem Ghassan Abdo, Saad Sh. Sammen, Yeboah Gyasi‐Agyei, Jesús Rodrigo‐Comino
IEEE Access. 2021234 CitationsOPEN ACCESS
Use of four drought indices for evaluating drought characteristics under climate change in Shaanxi, China: 1951–2012
Rengui Jiang, Jiancang Xie, Hailong He, Jungang Luo, Jiwei Zhu
S86860186. 2014117 Citations
Assessment of remote sensing-based indices for drought monitoring in the north-western region of Bangladesh
Ashim Chandra Das, Shihab Ahmad Shahriar, Md. Arif Chowdhury, Lokman Hossain, Shahed Mahmud, Md. Kamruzzaman TUSAR, Romel Ahmed, Mohammed Abdus Salam
Heliyon. 202356 CitationsOPEN ACCESS

Where is Hydrology and Drought Analysis research published, and who funds it?

ScholarIQvenues & funding sources

TOP JOURNALS

S86860186117

TOP FUNDERS

National Science Foundation
NIH
Wellcome Trust
European Research Council
Funder breakdown is a member featureSign up free to unlock

How much of the research on Hydrology and Drought Analysis is open access?

ScholarIQopen access share
67%OPEN ACCESS
Gold
67%
Green
0%
Hybrid
0%
Bronze
0%
Closed
33%

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Estimation of SPEI Meteorological Drought Using Machine Learning Algorithms
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