Appraisal of Hydrological Components Using Soft Computing Techniques

Erscheinungsjahr 2024
ISBN: 978-0-323-91216-7
Verlag: Elsevier Science

Buch, Englisch, 300 Seiten, Format (B × H): 191 mm x 235 mm

Appraisal of Hydrological Components Using Soft Computing Techniques provides a detailed account of the various available hydrological components, including precipitation, stream flow, draught, Infiltration, evapotranspiration, etc. The book presents modeling related issues, including over fitting, input variable selection, data separation, and performance evaluation indices. Case studies are also presented to enable a better understanding of how these techniques can be used and worked. The latest data and soft computing techniques for the estimation of hydrological components are also covered, making the content ideal for graduates and researchers in Hydrology, Environmental Science and Environmental Engineering. The hydrological cycle is a very complex phenomenon of continuous movement of water in different forms among the earth and atmosphere. There are several classical models available in literature to solve or estimate different hydrological components, but these classical models are very complex. In the past few decades soft computing-based models have been successfully used for the solution of complex problems in various fields. Through this book precipitation, stream flow, drought, evapotranspiration, humidity, wind speed, infiltration, soil temperature etc. are estimated using soft computing techniques.

Autoren/Hrsg.

Kumar, Vinod

Sihag, Parveen

Fachgebiete

• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Abfallwirtschaft, Abfallentsorgung
• Geowissenschaften Umweltwissenschaften Abfallbeseitigung, Abfallentsorgung

Inhaltsverzeichnis

1. Introduction of hydrological cycle
2. Machine Learning and soft computing based techniques
3. Hydrological data and processes
4. Precipitation estimation
5. Stream flow modeling using M5P and multivariate adaptive regression splines (MARS)
6. Prediction of Drought using Gene Expression Programming(GEP)  and artificial neural network
7. Evapotranspiration modeling using Random Forest, Random Tree and M5P
8. Humidity modelling using pruned, unpruned and bagged approach based M5P
9. Wind speed estimation using tree based techniques
10. Soil temperature prediction using artificial neural network and adaptive neuro fuzzy inference system
11. Estimation of Infiltration of soil using multivariate adaptive regression splines (MARS) and Group method of data handling (GMDH)
12. Ensemble and Hybrid Models for Hydrological Cycles

Über Autor(innen)

Sihag, Parveen
Currently working as Assistant Professor in Civil Engineering Department, Shoolini University, Solan-173229, Himachal Pradesh, India. Dr. Sihag has more than 65 research articles in his credit. He completed his Ph.D. from National Institute of Technology, Kurukshetra -136119.

Kumar, Vinod
Vinod Kumar is Assistant Professor in the Department of Botany and Environmental Studies at DAV University. Dr. Kumar has more than 70 research articles to his credit. He completed his Ph.D. from Guru Nanak Dev University. His area of interest is assessment of soil, water and sediment pollution, remote sensing, phyto-sociology, system modeling, and multivariate statistical techniques.