Results 51 to 60 of about 127,186 (201)

Decision Making Under Uncertainty in Systems Hydrology

, 1971
Design of engineering projects involve a certain amount of uncertainty. How should design decisions be taken in face of the uncertainty? What is the most efficient way of handling the data?
Davis, Donald Ross
core  

The global hydrology education resource

, 2011
This article is a selective overview of a range of contemporary teaching resources currently available globally for university hydrology educators, with an emphasis on web-based resources.
Yueh, Mei-Chun Michelle, Bardsley, W. Earl   +1 more
core  

AGU hydrology days 2003 [PDF]

, 2003
Includes bibliographical references.23rd annual AGU hydrology days was held on March 31-April 2, 2003 at Colorado State University.
Colorado State University, author, American Geophysical Union, author, Ramírez, Jorge A., editor, Colorado State University, publisher   +3 more
core   +1 more source

A Review of Canadian Prairie Hydrology: Principles, Modelling and Response to Land Use and Drainage Change [PDF]

, 2007
© Centre for Hydrology, University of Saskatchewan, Saskatoon, Saskatchewan, October 2007This report reviews research on the hydrological cycle, runoff generation, hydrological modelling and the influence of changes to land cover and wetlands on the same
Minke, Adam, Fang, Xing, Guangul, Seifu, Brown, Tom, Guo, Xulin, Westbrook, Cherie, Pomeroy, John   +6 more
core   +1 more source

Water Resource Management: Hydrological Modelling, Hydrological Cycles, and Hydrological Prediction

Water
This editorial provides a definitive review of ten articles published in the Special Issue of the journal Water, entitled “Water Resource Management: Hydrological Modelling, Hydrological Cycles, and Hydrological Prediction” [...]
Katarzyna Baran-Gurgul, Agnieszka Rutkowska   +1 more
openaire   +1 more source

Applications of machine learning and deep learning in hydrology from a bibliometric perspective: a comprehensive review

Discover Artificial Intelligence
Hydrology faces significant challenges, including water resource prediction and natural disaster mitigation. Consequently, integrating machine learning with hydrology is pivotal for enhancing research accuracy and efficiency.
Ying Nie, Kok Hwa Yu, Yang Wang, PeiSen Liu   +3 more
doaj   +1 more source

SpongeScapes: Understanding the role of nature-based solutions in improving sponge functioning of landscapes – the case of regenerative agriculture [PDF]

E3S Web of Conferences
The SpongeScapes project aims to accelerate understanding Nature-based Solutions (NBS) that enhance the sponge functioning of soil, groundwater, and surface water ecosystems, improving landscape resilience against hydrometeorological extremes across ...
Sah Neeraj, Blake James, D’Acunha Brenda, Bell Vicky, Evans Jon, Morrison Ross, Dussaillant Alejandro   +6 more
doaj   +1 more source

AGU hydrology days 2000 [PDF]

, 2000
Twentieth annual AGU hydrology days was held in the Cherokee Park Room, Lory Student Center, Colorado State University on April 3-6.
Colorado State University, author, American Geophysical Union, author, Colorado State University, publisher   +2 more
core   +1 more source

Automated high-temporal-resolution multi-element river water monitoring with ICP-MS

Environmental Sciences Europe
Background Real-time monitoring of multi-element concentrations in rivers is highly desirable due to potential hazardous impacts and a better understanding of geochemical cycles.
Mohamed Harhash, Jan G. Wiederhold, Ingrid Nett, Julia Arndt, Alexander Zavarsky, Thomas A. Ternes, Lars Duester   +6 more
doaj   +1 more source

Entropy in Hydrology

Perspectives of Earth and Space Scientists
Although the concept of thermodynamic entropy due to Clausius dates back to the early 1850s, the mathematical theory of informational entropy was not developed until the pioneering work of Shannon in 1948, the development of principle of maximum entropy (
Vijay P. Singh
doaj   +1 more source