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Remote Sensing Application in Support of Water-Soil-Plant Relationships

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Soil and Water".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 743

Special Issue Editors


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Guest Editor
College of Soil and Water Conservation Science and Engineering, Northwest A&F University, Xianyang, China
Interests: plant photosynthesis; remote sensing; solar induced chlorophyll fluorescence; plant water use; climate change

E-Mail Website
Guest Editor
Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, China
Interests: soil erosion; soil and water conservation; remote sensing; hydrology; watershed management; soil erosion and carbon cycle

Special Issue Information

Dear Colleagues,

Remote sensing technologies have become indispensable tools in the study and management of natural resources, particularly in understanding the complex interactions between water, soil, and plant systems. These relationships are fundamental to sustainable agriculture, ecosystem health, and environmental conservation. The ability to monitor and analyze these components at various spatial and temporal scales using remote sensing enhances our capacity to make informed decisions addressing challenges such as water scarcity, soil degradation, and the impacts of climate change. Recognizing the pivotal role of remote sensing in advancing our knowledge of water–soil–plant dynamics, we are pleased to invite you to contribute to a Special Issue titled "Remote Sensing Application Support for Water–Soil–Plant Relationships".

In this Special Issue, we welcome original research articles and review papers. Potential topics of interest include, but are not limited to:

  • Remote Sensing Methodologies: Techniques for assessing soil moisture, texture, and hydrology.
  • Water Monitoring and Irrigation: Satellite and UAV-based monitoring of water resources and irrigation.
  • Vegetation Health and Water Stress: Remote sensing tools for evaluating plant health and water stress.
  • Soil and Water Conservation: Remote sensing for soil conservation and water management.
  • Land Use Changes on Water–Soil–Plant systems: Assessing land use impacts on water, soil, and plants via remote sensing.
  • Precision Agriculture: Remote sensing to optimize water and soil management in farming.
  • Soil Erosion and Degradation: Monitoring erosion and degradation with remote sensing.
  • Climate Change Impacts: Remote sensing to study climate effects on water, soil, and plants.
  • Advanced Data Processing: Advanced data processing for analyzing remote sensing in water–soil-plant systems.
  • Case Studies: Real-world examples of remote sensing in water–soil–plant relationships.

We look forward to receiving your contributions.

Prof. Dr. Genghong Wu
Dr. Yi Zeng
Guest Editors

Manuscript Submission Information

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Keywords

  • remote sensing
  • water–soil–plant relationships
  • soil moisture
  • vegetation monitoring
  • hydrological modeling
  • precision agriculture
  • uavs
  • satellite imagery
  • climate change
  • data fusion

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Published Papers (1 paper)

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Research

24 pages, 7521 KiB  
Article
Developing a Remote Sensing-Based Approach for Agriculture Water Accounting in the Amman–Zarqa Basin
by Raya A. Al-Omoush, Jawad T. Al-Bakri, Qasem Abdelal, Muhammad Rasool Al-Kilani, Ibraheem Hamdan and Alia Aljarrah
Water 2025, 17(14), 2106; https://doi.org/10.3390/w17142106 - 15 Jul 2025
Viewed by 448
Abstract
In water-scarce regions such as Jordan, accurate tracking of water flows is critical for informed water management. This study applied the Water Accounting Plus (WA+) framework using open-source remote sensing data from the FAO WaPOR portal to develop agricultural water accounting (AWA) for [...] Read more.
In water-scarce regions such as Jordan, accurate tracking of water flows is critical for informed water management. This study applied the Water Accounting Plus (WA+) framework using open-source remote sensing data from the FAO WaPOR portal to develop agricultural water accounting (AWA) for the Amman–Zarqa Basin (AZB) during 2014–2022. Inflows, outflows, and water consumption were quantified using WaPOR and other open datasets. The results showed a strong correlation between WaPOR precipitation (P) and rainfall station data, while comparisons with other remote sensing sources were weaker. WaPOR evapotranspiration (ET) values were generally lower than those from alternative datasets. To improve classification accuracy, a correction of the WaPOR-derived land cover map was performed. The revised map achieved a producer’s accuracy of 15.9% and a user’s accuracy of 86.6% for irrigated areas. Additionally, ET values over irrigated zones were adjusted, resulting in a fivefold improvement in estimates. These corrections significantly enhanced the reliability of key AWA indicators such as basin closure, ET fraction, and managed fraction. The findings demonstrate that the accuracy of P and ET data strongly affects AWA outputs, particularly the estimation of percolation and beneficial water use. Therefore, calibrating remote sensing data is essential to ensure reliable water accounting, especially in agricultural settings where data uncertainty can lead to misleading conclusions. This study recommends the use of open-source datasets such as WaPOR—combined with field validation and calibration—to improve agricultural water resource assessments and support decision making at basin and national levels. Full article
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