Using Remote Sensing Observations and Model Simulations for the Analysis of Hydrological Extremes

Using Remote Sensing Observations and Model Simulations for the Analysis of Hydrological Extremes
Author :
Publisher :
Total Pages : 0
Release :
ISBN-10 : OCLC:1336502918
ISBN-13 :
Rating : 4/5 ( Downloads)

Book Synopsis Using Remote Sensing Observations and Model Simulations for the Analysis of Hydrological Extremes by : Lanxin Hu

Download or read book Using Remote Sensing Observations and Model Simulations for the Analysis of Hydrological Extremes written by Lanxin Hu and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hydrological extremes can harm society and ecosystems. However, many parts of the world lack in situ observations for quantifying hydrological extremes. Physically-based distributed hydrological model simulations driven by atmospheric simulations and remote sensing precipitation observations can be used to alleviate the issue of data scarcity in estimating return periods of hydrological extremes, but the short data record length associated with these datasets limits the application of traditional statistical methods (GEV/LP3/GPD) that rely on extreme value theory. Also, the errors in these indirect measurements or model simulations may lead to large biases in the quantification of extremes. The novel Metastatistical Extreme Value Distribution (MEVD) framework is proposed in this research as a mean of overcoming the limitations imposed by the short record length and obtaining more reliable assessment of high quantiles. The error estimates of MEVD applied on the data generated from satellite-based precipitation products and hydrological model simulations are thoroughly evaluated across different regions and hydroclimatic conditions. It is shown that MEVD is able to address the fundamental issue of data record limitations in deriving robust estimation of hydrological extremes, and alleviate the biases in hydrological model simulations of flood peaks. The application of the MEVD framework in conjunction with simulated streamflows and high-resolution precipitation products from remote sensing observations bring new opportunities for estimating hydrological extremes at global scale, including areas with limited or no in situ records.


Using Remote Sensing Observations and Model Simulations for the Analysis of Hydrological Extremes Related Books

Using Remote Sensing Observations and Model Simulations for the Analysis of Hydrological Extremes
Language: en
Pages: 0
Authors: Lanxin Hu
Categories:
Type: BOOK - Published: 2021 - Publisher:

DOWNLOAD EBOOK

Hydrological extremes can harm society and ecosystems. However, many parts of the world lack in situ observations for quantifying hydrological extremes. Physica
Remote Sensing of Hydrological Extremes
Language: en
Pages: 256
Authors: Venkat Lakshmi
Categories: Technology & Engineering
Type: BOOK - Published: 2016-11-03 - Publisher: Springer

DOWNLOAD EBOOK

This volume provides in-depth coverage of the latest in remote sensing of hydrological extremes: both floods and droughts. The book is divided into two distinct
Congo Basin Hydrology, Climate, and Biogeochemistry
Language: en
Pages: 596
Authors: Raphael M. Tshimanga
Categories: Science
Type: BOOK - Published: 2022-03-22 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

New scientific discoveries in the Congo Basin as a result of international collaborations The Congo is the world's second largest river basin and home to 120 mi
Understanding Hydrological Extremes and their Impact in a Changing Climate: Observations, Modeling and Attribution
Language: en
Pages: 96
Authors: Xingcai Liu
Categories: Science
Type: BOOK - Published: 2021-03-12 - Publisher: Frontiers Media SA

DOWNLOAD EBOOK

Hydrologic Remote Sensing
Language: en
Pages: 455
Authors: Yang Hong
Categories: Nature
Type: BOOK - Published: 2016-10-26 - Publisher: CRC Press

DOWNLOAD EBOOK

Environmental remote sensing plays a critical role in observing key hydrological components such as precipitation, soil moisture, evapotranspiration and total w