Special Issue "Advances in Data-Driven Water-Cycling Analyses"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Resources Management, Policy and Governance".

Deadline for manuscript submissions: 31 December 2022 | Viewed by 1202

Special Issue Editors

Dr. Guanhui Cheng
E-Mail Website
Guest Editor
Institute for Energy, Environment, and Sustainable Communities, University of Regina, 3737 Wascana Pkwy, Regina, Canada
Interests: environmental statistics; non-deterministic optimization; hydroclimatic modeling; water resource management; energy systems management; environmental systems management
Prof. Dr. Gordon Huang
E-Mail Website
Guest Editor
Faculty of Engineering and Applied Science, University of Regina, 3737 Wascana Pkwy, Regina, Canada
Interests: hydrological and environmental systems simulation; climate modeling and downscaling; resources, environmental, and economic systems optimization; synchrotron-based environmental chemistry and biochemistry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Massive water-related data (e.g., hydrologic observations, climatic re-analyses, satellite images, environmental monitoring, socioeconomic statistics, and experimental analyses) are available in the current era of big data. Numerous data-driven methods, algorithms, approaches, or software are continuously developed or employed to quantitatively analyze the data. The analyses are helpful for revealing complicated mechanisms of water cycling, e.g., its associations with climate, energy, agriculture, environment, geology, ecology, health, social economy, technological advancement, engineering construction, and other related systems at large scales. They can also help to identify the optimal policy, technological, or engineering solutions for addressing diverse water crises all over the world under natural and anthropogenic impacts.

This Special Issue focuses on emerging advances in data-driven water-related studies, summarizes recent findings of water cycling obtained from extensive data analyses, discusses existing gaps and challenges in both methodology and applications, and explores the reformation of this field in the next phase from the perspective of sustainable development of global communities.

Dr. Guanhui Cheng
Prof. Dr. Gordon Huang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Water
  • Data-driven
  • Modeling
  • Optimization
  • Sustainable development

Published Papers (1 paper)

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Research

Article
Impact of Sediment Deposition on Flood Carrying Capacity of an Alluvial Channel: A Case Study of the Lower Indus Basin
Water 2022, 14(20), 3321; https://doi.org/10.3390/w14203321 - 20 Oct 2022
Viewed by 602
Abstract
Impacts of climate change and human-made interventions have altered the fluvial regime of most rivers. The increasingly uncertain floods would further threaten the flow delivery system in regions such as Pakistan. In this study, an alluvial reach of the Indus River below Kotri [...] Read more.
Impacts of climate change and human-made interventions have altered the fluvial regime of most rivers. The increasingly uncertain floods would further threaten the flow delivery system in regions such as Pakistan. In this study, an alluvial reach of the Indus River below Kotri barrage was investigated for the geomorphologic effects of sediments deposited over the floodplain as well as the influences on the downstream flood-carrying capacity. The hydrodynamic modeling suite HEC-RAS in combination with ground and remotely sensed data were used to undertake this analysis. Results suggest that the morphology of the river reach has degraded due to depleted flows over a long period and hydrological extremes that have led to excessive sediment deposition over the floodplain and an enhancement in flood water extension possibility over the banks. A deposition of 4.3 billion cubic meters (BCM) of sediment increased the elevation of the channel bed which in turn reduced a 17.75% flood-carrying capacity of the river reach. Moreover, the excessive deposition of sediments and the persistence of low flows have caused a loss of 48.34% bank-full discharges over the past 24 years. Consequently, the river’s active reach has been flattened, with a live threat of left levee failure and the inundation of the populous city of Hyderabad. The study would gain insights into characterizing the impacts associated with a reduction in the flood-carrying capacity of the alluvial channel on account of the inadequate sediment transport capacity after heavy flow regulations. Full article
(This article belongs to the Special Issue Advances in Data-Driven Water-Cycling Analyses)
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