Statistical Analysis and Stochastic Modelling of Hydrological Extremes

ISBN 10: 3039216643 / ISBN 13: 9783039216642

Published by MDPI AG, 2019

About this Item

Statistical Analysis and Stochastic Modelling of Hydrological Extremes | Taschenbuch | Englisch | 2019 | MDPI AG | EAN 9783039216642 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Seller Inventory # 130684631

Bibliographic Details

• Title: Statistical Analysis and Stochastic Modelling of Hydrological Extremes
• Publisher: MDPI AG
• Publication Date: 2019
• Language: English
• ISBN 10: 3039216643
• ISBN 13: 9783039216642
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 244W x 170H x 19D millimeters 244 millimeters width by 170 millimeters height by 19 millimeters depth
• Weight: 756 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Hydrological extremes have become a major concern because of their devastating consequences and their increased risk as a result of climate change and the growing concentration of people and infrastructure in high-risk zones. The analysis of hydrological extremes is challenging due to their rarity and small sample size, and the interconnections between different types of extremes and becomes further complicated by the untrustworthy representation of meso-scale processes involved in extreme events by coarse spatial and temporal scale models as well as biased or missing observations due to technical difficulties during extreme conditions. The complexity of analyzing hydrological extremes calls for robust statistical methods for the treatment of such events. This Special Issue is motivated by the need to apply and develop innovative stochastic and statistical approaches to analyze hydrological extremes under current and future climate conditions. The papers of this Special Issue focus on six topics associated with hydrological extremes:

• Historical changes in hydrological extremes;
• Projected changes in hydrological extremes;
• Downscaling of hydrological extremes;
• Early warning and forecasting systems for drought and flood;
• Interconnections of hydrological extremes;
• Applicability of satellite data for hydrological studies.