Improving Hourly Precipitation Estimates for Flash Flood Modeling in Data-Scarce Andean-Amazon Basins: An Integrative Framework Based on Machine Learning and Multiple Remotely Sensed Data
Accurate estimation of spatiotemporal precipitation dynamics is crucial for flash flood forecasting; however, it is still a challenge in Andean-Amazon sub-basins due to the lack of suitable rain gauge networks. This study proposes a framework to improve hourly precipitation estimates by integrating...
Enregistré dans:
Auteurs principaux: | Juseth E. Chancay, Edgar Fabian Espitia-Sarmiento |
---|---|
Format: | article |
Langue: | EN |
Publié: |
MDPI AG
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/11fab83c49de43be9debe5c34e8c9300 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Are the Latest GSMaP Satellite Precipitation Products Feasible for Daily and Hourly Discharge Simulations in the Yellow River Source Region?
par: Jiayong Shi, et autres
Publié: (2021) -
Daily Flood Monitoring Based on Spaceborne GNSS-R Data: A Case Study on Henan, China
par: Wentao Yang, et autres
Publié: (2021) -
Optimization of Rain Gauge Networks for Arid Regions Based on Remote Sensing Data
par: Mona Morsy, et autres
Publié: (2021) -
Evaluation of Satellite-Derived Products for the Daily Average and Extreme Rainfall in the Mearim River Drainage Basin (Maranhão, Brazil)
par: Ana Carolina Freitas Xavier, et autres
Publié: (2021) -
AP-1 Recruits SMAP-1/SMAPs to the trans-Golgi Network to Promote Sorting in Polarized Epithelia
par: Shimin Wang, et autres
Publié: (2021)