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Research on Applications of Remote Sensing and Geographic Information Systems (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: closed (20 November 2022) | Viewed by 10490

Special Issue Editors

Dr. Zhenhuan Liu

E-Mail Website
Guest Editor
School of Geography and Planning, Sun Yat-Sen University, Guangzhou, China
Interests: water quality; landscape change; landscape ecology; physical geography; spatial analysis
Dr. Huabing Huang

E-Mail Website
Guest Editor
School of Geography and Planning, Sun Yat-sen University, Guangzhou, China
Interests: urban flood modelling; urban hydrology; urban resilience; machine learning; spatial analysis; terrian anlysis
Special Issues, Collections and Topics in MDPI journals
Dr. Haiyan Yang

E-Mail Website
Guest Editor
College of Water Conservancy and Civil Engineering, South China Agricultural University, Guangzhou, China
Interests: GIS technology; numerical simulation tools

Special Issue Information

Dear Colleagues,

Water resources became a huge task in sustainable development, which is closely related to human well-being. However, facing the rapid urbanization and climate change, the water resource security has been more vulnerability to safe supply. GIS and RS have been increasingly used for water resources, water quality monitoring, water resources planning, and flood management. GIS is a robust tool to managing huge volumes of data, mapping the flood risk, assessing the quantity and quality of water resource. Till now, the RS and GIS datasets in water resources, including both groundwater and surface water, is further facilitated by different sensors and technology. Water resources planning and management using RS is necessary to meet the demands of fast urbanization and increasing population. Therefore, the research of water resources based on RS and GIS has become popular during recent decades. This Research Topic aims to extent the application of RS and GIS in water resource field. We are welcome the research topic of water quality in river, stream, lake, and groundwater. We also welcome more extensive water related research to join our Special Issue.

Dr. Zhenhuan Liu
Dr. Huabing Huang
Dr. Haiyan Yang
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 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

  • remote sensing
  • GIS
  • water resource
  • water quality
  • water quantity
  • hydrology
  • flood management

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Published Papers (3 papers)

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Research

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21 pages, 2812 KiB  
Article
Detection of Water Hyacinth (Eichhornia crassipes) in Lake Tana, Ethiopia, Using Machine Learning Algorithms
by Getachew Bayable, Ji Cai, Mulatie Mekonnen, Solomon Addisu Legesse, Kanako Ishikawa, Hiroki Imamura and Victor S. Kuwahara
Water 2023, 15(5), 880; https://doi.org/10.3390/w15050880 - 24 Feb 2023
Cited by 13 | Viewed by 3908
Abstract
Lake Tana is Ethiopia’s largest lake and is infested with invasive water hyacinth (E. crassipes), which endangers the lake’s biodiversity and habitat. Using appropriate remote sensing detection methods and determining the seasonal distribution of the weed is important for decision-making, water [...] Read more.
Lake Tana is Ethiopia’s largest lake and is infested with invasive water hyacinth (E. crassipes), which endangers the lake’s biodiversity and habitat. Using appropriate remote sensing detection methods and determining the seasonal distribution of the weed is important for decision-making, water resource management, and environmental protection. As the demand for the reliable estimation of E. crassipes mapping from satellite data grows, comparing the performance of different machine learning algorithms could help in identifying the most effective method for E. crassipes detection in the lake. Therefore, this study aimed to examine the ability of random forest (RF), support vector machine (SVM), and classification and regression tree (CART) machine learning algorithms to detect E. crassipes and estimating seasonal spatial coverage of the weed on the Google Earth Engine (GEE) platform using Landsat 8 and Sentinel 2 images. Cloud-masked monthly median composite Landsat 8 and Sentinel 2 data from October 2021 and 2022, January 2022 and 2023, March 2022, and June 2022 were used to represent autumn, winter, spring, and summer, respectively. Four spectral indices were derived and used in combination with spectral bands to improve the E. crassipes detection accuracy. All methods achieved greater than 95% and 90% overall accuracy when using Sentinel 2 and Landsat 8 images, respectively. Using both data sets, all methods achieved a greater than 93% F1 score for E. crassipes detection. Though the difference in performance between the methods was small, the RF was the most accurate, while the SVM and CART methods had the same accuracy. The maximum E. crassipes coverage area was observed in autumn (22.4 km2), while the minimum (2.2 km2) was observed in summer. Based on Sentinel 2 data, the E. crassipes area coverage decreased significantly by 62.5% from winter to spring and increased significantly by 81.7% from summer to autumn. The findings suggested that the RF classifier was the most accurate E. crassipes detection algorithm, and autumn was an appropriate season for E. crassipes detection in Lake Tana. Full article
(This article belongs to the Special Issue Research on Applications of Remote Sensing and Geographic Information Systems (GIS) in Water Resources)
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22 pages, 6507 KiB  
Article
Geomatics-Based Modeling and Hydrochemical Analysis for Groundwater Quality Mapping in the Egyptian Western Desert: A Case Study of El-Dakhla Oasis
by Hanaa A. Megahed, Hossam M. GabAllah, Mohamed A. E. AbdelRahman, Paola D’Antonio, Antonio Scopa and Mahmoud H. Darwish
Water 2022, 14(24), 4018; https://doi.org/10.3390/w14244018 - 9 Dec 2022
Cited by 5 | Viewed by 2646
Abstract
Groundwater is the single source of water in El-Dakhla Oasis, western desert, Egypt. The main objective of this study is an assessment of groundwater in the area for agriculture and drinking compared to Egyptian and World Health Organization criteria. Most the contamination of [...] Read more.
Groundwater is the single source of water in El-Dakhla Oasis, western desert, Egypt. The main objective of this study is an assessment of groundwater in the area for agriculture and drinking compared to Egyptian and World Health Organization criteria. Most the contamination of water in the study area comes from human and agricultural activities. Thirty soil profiles were studied in the area and we assessed soil quality. Seventy-four samples were taken from the area’s groundwater wells to assess the chemical characteristics of the groundwater. Moreover, the contamination of groundwater by farming and anthropogenic activities was assessed using a land use/land cover (LULC) map. Nine standard water criteria were determined to assess groundwater quality for agriculture. Furthermore, the resulting risk to human health and agricultural crops has been addressed. Therefore, the drinking quality of groundwater samples is graded as low as the hydrochemical study showed high TH, EC, TDS, Ca2+, Mg2+, Mn2+, and Fe2+ contents of 40.5%, 2.7%, 1.4%, 3.8%, 1.6%, 86.5%, and 100%, respectively. Human health is risked by drinking this water, which negatively affects hair, skin, and eyes, with greatest exposure to enteric pathogens. Using these criteria, the majority of groundwater samples cause harmful effects on soil types and are toxic to sensitive crops (vegetable crops). In conclusion, the output of this research is a map showing groundwater suitable for consumption and agriculture in El-Dakhla Oasis based on all indices using the Geographic Information Systems (GIS) model. Additionally, there was evidence of a linear relationship between soil quality and irrigation water quality (R2 = 0.90). This emphasis on tracking changes in soil/water quality was brought on by agricultural practices and environmental variables. Full article
(This article belongs to the Special Issue Research on Applications of Remote Sensing and Geographic Information Systems (GIS) in Water Resources)
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Review

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13 pages, 13065 KiB  
Review
A Review of Numerical Modelling of Morphodynamics in Braided Rivers: Mechanisms, Insights and Challenges
by Youfei Hu, Haiyan Yang, Haolan Zhou and Qianwen Lv
Water 2023, 15(3), 595; https://doi.org/10.3390/w15030595 - 2 Feb 2023
Cited by 4 | Viewed by 2979
Abstract
In the past decade, the numerical modelling of braided river morphodynamics has experienced a significant advance due to the increasing computer power and the development of numerical techniques. Numerical models are quite efficient in exploring scenarios with different settings, and they can be [...] Read more.
In the past decade, the numerical modelling of braided river morphodynamics has experienced a significant advance due to the increasing computer power and the development of numerical techniques. Numerical models are quite efficient in exploring scenarios with different settings, and they can be applied to investigate the complicated physics laws of natural braided rivers and manage complex river engineering problems. However, braided river models are far from fully developed, e.g., the representation of flow and sediment transport, model sensitivity, essential effects of sediment transport, bank erosion and vegetation, and require intensive refinement and validation to enhance their prediction accuracy. The recent application of advanced field measurement techniques offers model development a new chance by providing abundant measurement data of a high quality. The present study reviews the essential mechanisms and applications of typical braided river models; compares their accuracy; discusses the recent progress, advantages and shortcomings; and illustrates the challenges and future research trends. Full article
(This article belongs to the Special Issue Research on Applications of Remote Sensing and Geographic Information Systems (GIS) in Water Resources)
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