Advances in Meteorology

Advances in Remote Sensing to Understand Extreme Hydrological Events


Publishing date
01 Aug 2019
Status
Published
Submission deadline
29 Mar 2019

Lead Editor

1Hongik University, Seoul, Republic of Korea

2Sungkyunkwan University, Suwon, Republic of Korea

3University of Ulsan, Ulsan, Republic of Korea

4Cleveland State University, Ohio, USA


Advances in Remote Sensing to Understand Extreme Hydrological Events

Description

Extreme hydrological events often lead to catastrophes for humans and the environment. While identification, understanding, modeling, validation, and prediction of extreme hydrological events are crucial for preventing such catastrophes and eventually developing a system that is resilient to them, such tasks are challenging. In particular, it is difficult to obtain a comprehensive understanding of an extreme event and the corresponding damage that typically occurs over a spatial extent of several thousand kilometers within which spatio-temporal characteristics vary significantly.

Emerging techniques such as remote sensing and radar from multiple platforms have been actively applied to resolve these issues. Near-real-time precise and accurate observation of precipitation has become possible with the help of satisfactorily-confirmed radar, and information derived from satellites enables us to observe a variety of components of hydrological cycle at a global spatial scale.

In this special issue, we call for papers discussing how observations based on emerging techniques including remote sensing have broadened our understanding of hydrological disasters.

Potential topics include but are not limited to the following:

  • Emerging techniques, methodologies, and developments to detect, forecast, or predict disasters related to extreme hydrological events such as floods and droughts
  • Calibration, verification, and bias correction techniques for remotely sensed data, quantitative precipitation estimation/forecasting, and any types of weather or climate estimates dealing with extreme events
  • Spatial and temporal downscaling of remotely sensed data, quantitative precipitation estimation/forecasting, and any types of weather or climate estimates in terms of extreme meteorological events
  • Spatial and temporal compositions of remotely sensed and in-situ measurements in accounting for serial and spatial correlations at larger and longer spatiotemporal scales

Articles

  • Special Issue
  • - Volume 2019
  • - Article ID 8235037
  • - Editorial

Advances in Remote Sensing to Understand Extreme Hydrological Events

Dongkyun Kim | Minha Choi | ... | Ungtae Kim
  • Special Issue
  • - Volume 2019
  • - Article ID 6542410
  • - Research Article

Assessing the Applicability of Random Forest, Stochastic Gradient Boosted Model, and Extreme Learning Machine Methods to the Quantitative Precipitation Estimation of the Radar Data: A Case Study to Gwangdeoksan Radar, South Korea, in 2018

Ju-Young Shin | Yonghun Ro | ... | Jong-Chul Ha
  • Special Issue
  • - Volume 2019
  • - Article ID 5789358
  • - Research Article

Coverage of China New Generation Weather Radar Network

Chao Min | Sheng Chen | ... | Chaoying Huang
  • Special Issue
  • - Volume 2019
  • - Article ID 3572431
  • - Research Article

Combination of Radar and Rain Gauge Information to Map the Snowy Region in Jeju Island, Korea: A Case Study

Jung Mo Ku | Chulsang Yoo
  • Special Issue
  • - Volume 2019
  • - Article ID 4631609
  • - Research Article

Seasonal and Regional Differences in Extreme Rainfall Events and Their Contribution to the World’s Precipitation: GPM Observations

Shailendra Kumar | Yamina Silva | ... | Daniel Martínez-Castro
  • Special Issue
  • - Volume 2019
  • - Article ID 8512727
  • - Research Article

Hydrological Drought Assessment of Energy-Based Water Deficit Index (EWDI) at Different Geographical Regions

Chanyang Sur | Dongkyun Kim | ... | Minha Choi
  • Special Issue
  • - Volume 2019
  • - Article ID 8413964
  • - Research Article

Using CHIRPS Dataset to Assess Wet and Dry Conditions along the Semiarid Central-Western Argentina

Juan A. Rivera | Sofía Hinrichs | Georgina Marianetti
Advances in Meteorology
 Journal metrics
Acceptance rate37%
Submission to final decision118 days
Acceptance to publication49 days
CiteScore2.600
Impact Factor1.491
 Submit

We are committed to sharing findings related to COVID-19 as quickly and safely as possible. Any author submitting a COVID-19 paper should notify us at help@hindawi.com to ensure their research is fast-tracked and made available on a preprint server as soon as possible. We will be providing unlimited waivers of publication charges for accepted articles related to COVID-19. Sign up here as a reviewer to help fast-track new submissions.