Remote Sensing for Monitoring and Assessment of Hydrological and Water Quality Parameters

Dear Colleagues,

In recent years, climate change and increased pressure from agricultural and anthropogenic activities have threatened aquatic ecosystems by causing major alterations in the hydrological cycle and water quality. Heavy rainfalls or floods can determine high variability of pollutants (nitrate, phosphorous, heavy metals, or pesticides) in soil-, ground-, and river waters with related impacts (eutrophication and water quality degradation) on the ecological status of waterbodies, from inland to coastal and open ocean waters. The discharge of particles and dissolved organic material into the sea may alter the underwater light field of the marine environment, negatively impacting marine biota and related carbon cycle. In this scenario, it is of paramount importance to implement sustainable monitoring strategies to manage water resources, focusing on the strict interactions between hydrology and water quality.

Remote sensing data can provide useful information on hydrological variables, such as precipitation, evapotranspiration, runoff, soil moisture and on bio-optical water quality indicators (i.e., chlorophyll-a (chl-a), total suspended matter (TSM), and coloured dissolved organic matter (CDOM)). The wide availability of polar/geostationary spaceborne platforms and the improvements in remote sensing technologies offer new possibilities for establishing data-driven approaches for spatial calibration and validation of hydrological models. Furthermore, the suitability of new generation multispectral and hyperspectral sensors and their joint use has created unprecedented opportunities for monitoring coastal and inland water quality at rates that have never been possible before. While remote sensing data have allowed for a timely characterization of water cycle processes, the research community is overwhelmed by the sheer quantities of big data. Thus, there is an urgent need to maximize the benefit of increased observations and remotely sensed data using physically based, statistical and machine learning approaches.

This Special Issue is aimed at highlighting the recent advancements in the use of remote sensing to assess water cycle processes with a particular focus on hydrological and water quality parameters. We encourage submissions on innovative methodologies of data analysis that can handle multimission and multisource remote sensing data for monitoring spatiotemporal dynamics of extreme hydrological events and/or water quality variations and assessing their impacts on ecosystems.

Topics of interest include, but are not limited to, the following:

• Soil moisture modelling and mapping;
• Infiltration, discharge, runoff, and storage of water;
• Water storage in ice and snow, glaciers, ice fields and snow fields;
• Water cycle, climate, and ecosystems;
• Traditional and new remote sensing sensors/products for estimating hydrological and water quality variables;
• Remote retrieval of water quality parameters in water ecosystems;
• Climate or human-induced spatiotemporal variation of water quality in coastal, estuarine, and inland waters;
• Applications of artificial intelligence (AI) and/or machine learning approaches;
• Time series of remote sensing data for long-term analyses;
• EO observations to support decision-making processes.

Dr. Emanuele Ciancia
Dr. Caterina Samela
Dr. Emanuele Organelli
Dr. Rossana Paciello
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. Remote Sensing 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 2700 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.

• sustainable water management
• climate change effects
• hydrological processes
• soil moisture and flooding
• coastal and inland water dynamics
• retrieval of water quality parameters
• remote sensing
• machine learning