water-logo

Journal Browser

Journal Browser

Application of Remote Sensing and GIS in Water Resources

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "New Sensors, New Technologies and Machine Learning in Water Sciences".

Deadline for manuscript submissions: 25 March 2027 | Viewed by 1613

Editors


E-Mail Website
Guest Editor
Environmental Science, College of Coastal Georgia, Brunswick, GA 31520, USA
Interests: vadose zone hydrology; urban hydrology; watershed hydrology; stormwater; low-impact development (LID); green infrastructure (GI); best management practice (BMP); stormwater control measures (SCM); remote sensing; SWMM; geographic information system (GIS); heat islands
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China
Interests: remote sensing; urban heat islands; BIM; GIS; CFD
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor Assistant
Environmental Science, College of Coastal Georgia, Brunswick, GA 31520, USA
Interests: hydrology; water quality; wetlands; streams; geology; ecology

Special Issue Information

Dear Colleagues,

The application of remote sensing (RS) and Geographic Information Systems (GISs) has become indispensable for the effective and sustainable management of water resources. By leveraging these powerful tools, researchers can acquire, analyze, and visualize vast amounts of spatial data, leading to a comprehensive understanding of complex hydrological systems. RS technologies, including satellite imagery, airborne LiDAR, and various sensors, provide critical surface-level data on a wide range of water-related parameters. This information includes the extent of surface water bodies, snow cover, soil moisture, land use, and changes in vegetation, which are all crucial for assessing water availability and demand.

The true strength of this approach lies in the integration of this data within a GIS environment. GISs serve as a robust platform for compiling, processing, and analyzing diverse datasets from multiple sources. GISs allow for advanced spatial analysis, enabling the identification of patterns, relationships, and trends that are not apparent from a single data source. By combining RS data with other information—such as climate data, topographic maps, and field measurements—GISs facilitate powerful hydrological modeling, water resource planning, and environmental impact assessments. This integration significantly enhances our ability to monitor, predict, and respond to challenges like floods, droughts, and water quality degradation, ultimately supporting informed decision-making for water conservation and allocation.

This Special Issue aims to provide a comprehensive overview of the latest advancements and innovative applications of RS and GISs in water resources. By showcasing high-quality original research and review articles, this Special Issue will highlight the transformative potential of these technologies in addressing pressing global water challenges. Based on this framework, the Special Issue focuses on papers that address one or more of the following topics:

  • Hydrological Modeling and Forecasting: Using RS and GISs for rainfall-runoff, flood, and drought modeling.
  • Water Quality Assessment and Monitoring: Employing satellite imagery to monitor water bodies for pollutants, turbidity, and algal blooms.
  • Surface and Groundwater Interaction: Mapping and analyzing the connectivity between surface water bodies and groundwater systems.
  • Irrigation and Agricultural Water Management: Applying RS for crop water stress detection, irrigation scheduling, and water use efficiency analysis.
  • Watershed Management and Planning: Utilizing GISs for spatial analysis to support land use planning and conservation strategies within a watershed.
  • Glacier and Snow Cover Dynamics: Assessing changes in cryosphere water resources using remote sensing data.
  • Regional Water Resource Assessment: Evaluating water availability and demand at regional scales to support transboundary water agreements.
  • Urban Water Management: Using geospatial tools to monitor urban water supply, drainage networks, and flood risk.

Dr. Min-Cheng Tu
Dr. Hong-Yuan Huo
Guest Editors

Dr. James Deemy
Guest Editor Assistant

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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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 2600 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

  • GIS
  • remote sensing
  • hydrology
  • satellite
  • drone
  • surface water
  • groundwater
  • cryosphere
  • flood
  • drought
  • rainfall-runoff
  • water quality
  • irrigation

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

30 pages, 4484 KB  
Article
Regional-Scale Snow Depth Estimation in the Moroccan Atlas Mountains Using MODIS Remote Sensing Data and Empirical Modeling
by Haytam Elyoussfi, Abdelghani Boudhar, Salwa Belaqziz, Mostafa Bousbaa, Mohamed Elgarnaoui, Fatima Benzhair, Rahma Azamz, Marouane Insaf and Abdelghani Chehbouni
Water 2026, 18(10), 1244; https://doi.org/10.3390/w18101244 - 21 May 2026
Viewed by 1017
Abstract
In Morocco, snow constitutes a crucial freshwater resource, particularly in the Atlas Mountains, where seasonal snowpack significantly contributes to surface water availability, groundwater recharge, and down-stream water supply. However, snow monitoring in these regions remains challenging due to the scarcity and uneven distribution [...] Read more.
In Morocco, snow constitutes a crucial freshwater resource, particularly in the Atlas Mountains, where seasonal snowpack significantly contributes to surface water availability, groundwater recharge, and down-stream water supply. However, snow monitoring in these regions remains challenging due to the scarcity and uneven distribution of ground-based snow depth measurements, especially at high altitudes. This lack of observations limits the accurate assessment of snowpack dynamics and hampers hydrological modeling and water resource management. In this study, we assessed the performance of an empirical approach to estimate snow depth from satellite-derived fractional snow cover (FSC) obtained from MODIS observations. Five empirical FSC snow depth models, including linear and nonlinear exponential formulations, are developed and applied across multiple regions of the Moroccan Atlas Mountains. Model coefficients are calibrated independently for each region using three complementary optimization techniques, nonlinear least squares regression, genetic algorithms, and simulated annealing. Model skill was evaluated during calibration and validation using the Kling–Gupta Efficiency (KGE), Pearson correlation coefficient (R), and absolute error metrics (RMSE and MAE). Results show substantial performance differences across formulations and regions. The most flexible exponential model achieved highest efficiency (KGE up to 0.87; R > 0.85) and 0.26 cm (MAE) under moderate snow conditions. Linear formulations exhibited limited robustness, whereas exponential models better captured snow depth dynamics, particularly in high-altitude areas with deep and persistent snowpacks. These results highlight the potential of FSC-based empirical modeling as a practical and operational solution for snow depth estimation in data-scarce mountainous regions of Morocco. Full article
(This article belongs to the Special Issue Application of Remote Sensing and GIS in Water Resources)
Show Figures

Figure 1

Back to TopTop