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Tools for Water Resources Monitoring, Water Erosion and Geomorphological Research

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

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 2870

Special Issue Editors


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Guest Editor
Research Institute for Sustainable Territorial Development, University of Extremadura, 10071 Cáceres, Spain
Interests: geomorphology; photogrammetry; UAV; LIDAR; digital terrain analysis; spatial modelling
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Art and Territory Science, INTERRA Research Institute for Sustainable Territorial Development, University of Extremadura, 10071 Cáceres, Spain
Interests: environmental modeling; land degradation; GIS; land use/cover management; land use/cover dynamics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Geomorphology in general, and soil erosion by water in particular, have experienced a great development in tools, methods and techniques in the past decade. The result has been a democratization in the availability of accurate and high-resolution spatial data that can be used to monitor, model and quantify geomorphological processes and water resources. Developments in photogrammetry have allowed the production of point clouds, orthophotos and DEMs of surface and submerged topography with consumer-grade cameras. Light, low-cost and accurate GNSS devices have provided the support for georeferencing these datasets and also for direct RTK referencing of UAV platforms. Laser technology (aerial and terrestrial) has also contributed to the production of high-density point clouds of geomorphological features. Many of these sensors, platforms and techniques have been integrated in systems for continuous and/or real-time monitoring that produce valuable information about the role of individual events.

Finally, the availability of big data datasets together with remote sensing technologies and the generalization of data mining, machine learning and model ensembling techniques have provided the tools for a better understanding of geomorphological processes and resources availability.

All these developments have been adopted as tools for the study and monitoring of water resources and geomorphological processes-features (sheet erosion, gullies, landslides, etc.) or to perform restoration activities in degraded areas. As these tools provide the frame for a better assessment of water resources, understanding of the processes (magnitude–frequency relationships) and the underlying factors, the present Special Issue covers works on the application of these techniques, methodological developments for the study of water resources, water erosion and geomorphological processes in general. Outstanding study cases but also review papers on specific topics on the subject are welcome.

Dr. Álvaro Gómez-Gutierrez
Dr. J. Francisco Lavado Contador
Guest Editors

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Keywords

  • Soil erosion
  • Water resources
  • Photogrammetry
  • UAV
  • LIDAR
  • TLS
  • 4D monitoring
  • Data mining
  • Machine learning
  • Big data

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Published Papers (1 paper)

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Research

19 pages, 76779 KiB  
Article
Application of Multi-Source Data Fusion Method in Updating Topography and Estimating Sedimentation of the Reservoir
by Yu Liu, Shiguo Xu, Tongxin Zhu and Tianxiang Wang
Water 2020, 12(11), 3057; https://doi.org/10.3390/w12113057 - 30 Oct 2020
Cited by 8 | Viewed by 2330
Abstract
The underwater terrain of a reservoir can experience significant changes due to the effects of erosion and siltation during decades of operation. Therefore, existing topographic data no longer reflect current reservoir terrains and need to be updated. In this paper, we propose a [...] Read more.
The underwater terrain of a reservoir can experience significant changes due to the effects of erosion and siltation during decades of operation. Therefore, existing topographic data no longer reflect current reservoir terrains and need to be updated. In this paper, we propose a fast and economical method for updating the topography of a reservoir. According to multi-source data fusion, we effectively integrated sonar sounding data, cartographic data, and manual measurement data to update and reconstruct the bottom topography of a reservoir in Northeast China. By comparing the updated topography with the measured elevation, the average error of the simulation results is only 0.56%, which shows that the updated topography can accurately reflect the actual topography of the reservoir. Furthermore, by using the surface volume tool in ArcGIS, we developed the original and updated the elevation and volume curves of the reservoir. Finally, the amount of silting and its distribution in the reservoir were obtained by calculating the difference between the original and updated elevation and volume curves. The results show that the total sedimentation volume in the researching reservoir is about 4.3 million m3, which is mainly concentrated in the areas with an elevation below 50 m and above 60 m. Full article
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