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Understanding Surface Water Dynamics Based on Multisource Remote Sensing Data

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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 (31 October 2022) | Viewed by 24679

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Special Issue Editors

Dr. Chang Huang

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Guest Editor

Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi’an 710127, China
Interests: remote sensing of surface water; river discharge; flood inundation; image fusion; Google Earth Engine
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Guiping Wu

E-Mail Website
Guest Editor

Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
Interests: remote sensing of hydrology; lake volume; surface water extent and level monitoring; remote sensing of rivers; wetland mapping; satellite image processing

Special Issue Information

Dear Colleagues,

Surface water, presenting in liquid form as lakes, reservoirs and rivers, or in solid form as snow, glaciers and river/lake ices, represents a critical freshwater resource. In either form, surface water plays an essential role in earth systems. However, its presence and dynamics are yet not fully understood at regional to global scales.

Remote sensing provides an effcient approach for estimating the areal extent and water content of both liquid and solid forms. Optical and microwave satellite remote sensing offers the potential to address knowledge gaps in surface water entities, including rivers, lakes, reservoirs and wetlands. Multi-source remote sensing data can not only facilitate an improved understanding of the long term variability and trends of surface water dynamics, but can also provide observations on a near real-time basis for monitoring and prediction, particularly in data-sparse regions.

We are calling for innovative research papers that employ multi-source, remotely sensed data to study surface water processes (e.g., river discharge, lake volume variation, wetland inundation, snow/ice melting) and support the development of novel applications (e.g., new algorithms/datasets, integration with models). The Special Issue focuses on but is not limited to exploring the roles of surface water bodies and wetlands in water management, hydrological cycles, ecosystem services, and land–atmosphere interactions.

Prof. Dr. Chang Huang
Prof. Dr. Guiping Wu
Guest Editors

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Keywords

synthetic aperture radar (SAR)
optical remote sensing
surface water
flood inundation
river discharge
lake volume
wetland inundation
snow
river/lake ice
glacier

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Published Papers (4 papers)

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Research

21 pages, 7462 KiB

Open AccessFeature PaperArticle

The Influence of River Morphology on the Remote Sensing Based Discharge Estimation: Implications for Satellite Virtual Gauge Establishment

by Zhuolin Shi, Qianqian Chen and Chang Huang

Water 2022, 14(23), 3854; https://doi.org/10.3390/w14233854 - 26 Nov 2022

Cited by 4 | Viewed by 1966

Abstract

Monitoring of river discharge is a key process for water resources management, soil and water conservation, climate change, water cycling, flood or drought warning, agriculture and transportation, especially for the sustainable development of rivers and their surrounding ecological environment. Continuous and comprehensive discharge monitoring was usually impossible before, due to sparse gauges and gauge deactivation. Satellite remote sensing provides an advanced approach for estimating and monitoring river discharge at regional or even global scales. River morphology is generally considered to be a direct factor that affects the accuracy of remote sensing estimation, but the specific indicators and the extent to which it affects the estimation accuracy have not yet been explored, especially for medium to small rivers (width < 100 m). In this paper, six sites with hydrological gauges in the upper Heihe River Basin (HRB) of northwestern China and the Murray Darling Basin (MDB) of southeastern Australia were selected as the study cases. River discharge was estimated from Landsat imagery using the C/M method accordingly. River gradient, sinuosity, and width were obtained from Digital Elevation Model data for each site. Global Surface Water Dataset (GSWD) was also employed for indicating the dynamic status of river morphology. A series of methods were applied to analyze the influence of river morphology on estimation accuracy qualitatively and quantitatively, based on which we established inference about the theory of selecting satellite virtual gauges (SVGs). The results confirm the feasibility of the C/M method for discharge estimation, with the accuracy affected by multiple river morphological indicators. Among them, river width was found to be the most significant one. Moreover, water occurrence and water extent extracted from GSWD also have impact on the discharge estimation accuracy. Another independent river section in MDB was set as an example to demonstrate the reasonability of the established theory. It is anticipated that this study would promote the application of remote sensing for discharge estimation by providing practical guidance for establishing appropriate SVGs. Full article

(This article belongs to the Special Issue Understanding Surface Water Dynamics Based on Multisource Remote Sensing Data)

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16 pages, 6017 KiB

Open AccessFeature PaperArticle

The Morphological Evolution of a Step–Pool Stream after an Exceptional Flood and Subsequent Ordinary Flow Conditions

by Giacomo Pellegrini, Riccardo Rainato, Lorenzo Martini and Lorenzo Picco

Water 2021, 13(24), 3630; https://doi.org/10.3390/w13243630 - 17 Dec 2021

Cited by 8 | Viewed by 3336

Abstract

Mountain streams are frequently characterized by step–pool morphology that provides stability and energy dissipation to the channel network. Large flooding events can overturn the equilibrium of the step–pool condition by altering the entire configuration. This work focuses on the impact of the “Vaia” storm (27–30 October 2018) on a step–pool mountain stream (Rio Cordon, Northeast Italy) and on its evolution after two years of ordinary flow conditions. To achieve the aims, this work uses both remote sensing data (LiDAR and UAV) and direct field measurements (i.e., longitudinal profiles and grain sizes distributions) performed pre-event, post-event, and 2 years later (current conditions). The results show a significant widening (width +81%, area +68%) and the creation of a new avulsion after the storm and a substantial change between the number of units (51 in the pre-event, 22 post-event, and 51 in the current conditions) and characteristics of step–pool sequences between pre- and post-conditions. Furthermore, it proves the ongoing processes of morphological stabilization since the current step–pool sequences parameters are heading back to the pre-event values. Such results suggest clear susceptibility of step–pool to exceptional events and fast recovery of such setting during barely two years of ordinary flow conditions. Full article

(This article belongs to the Special Issue Understanding Surface Water Dynamics Based on Multisource Remote Sensing Data)

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17 pages, 4968 KiB

Open AccessEditor’s ChoiceArticle

An Effective Water Body Extraction Method with New Water Index for Sentinel-2 Imagery

by Wei Jiang, Yuan Ni, Zhiguo Pang, Xiaotao Li, Hongrun Ju, Guojin He, Juan Lv, Kun Yang, June Fu and Xiangdong Qin

Water 2021, 13(12), 1647; https://doi.org/10.3390/w13121647 - 11 Jun 2021

Cited by 60 | Viewed by 16010

Abstract

Surface water bodies, such as rivers, lakes, and reservoirs, play an irreplaceable role in global ecosystems and climate systems. Sentinel-2 imagery provides new high-resolution satellite remote sensing data. Based on the analysis of the spectral characteristics of the Sentinel-2 satellite, a novel water index called the Sentinel-2 water index (SWI) that is based on the vegetation-sensitive red-edge band (Band 5) and shortwave infrared (Band 11) bands was developed. Four representative water body types, namely, Taihu Lake, Yangtze River, Chaka Salt Lake, and Chain Lake, were selected as study areas to conduct a water body extraction performance comparison with the normalized difference water index (NDWI). We found that (1) the contrast value of the SWI was larger than that of the NDWI in terms of various water body types, including purer water, turbid water, salt water, and floating ice, which suggested that the SWI could achieve better enhancement performance for water bodies. (2) An effective water body extraction method was proposed by integrating the SWI and Otsu algorithm, which could accurately extract various water body types with high overall accuracy. (3) The method effectively extracted large water bodies and wide river channels by suppressing shadow noise in urban areas. Our results suggested that the novel method can achieve efficient water body extraction for rapidly and accurately extracting various water bodies from Sentinel-2 data and the novel method has application potential for larger-scale surface water mapping. Full article

(This article belongs to the Special Issue Understanding Surface Water Dynamics Based on Multisource Remote Sensing Data)

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11 pages, 3812 KiB

Open AccessArticle

Remote Sensing Investigation of the Offset Effect between Reservoir Impoundment and Glacier Meltwater Supply in Tibetan Highland Catchment

by Jingying Zhu, Chunqiao Song, Linghong Ke, Kai Liu and Tan Chen

Water 2021, 13(9), 1307; https://doi.org/10.3390/w13091307 - 7 May 2021

Cited by 4 | Viewed by 2233

Abstract

This article presents multi-source remote sensing measurements to quantify the water impoundment and regulation of the Zhikong Reservoir (ZKR) and Pangduo Reservoir (PDR), together with the estimation of the glacier mass balance to explore whether the increased glacier meltwater supply can buffer the influences of the reservoir impoundment to some degree in the Tibetan highland catchment. The ZKR and PDR are two reservoirs constructed on the upper Lhasa River that originate from the Nyainqentanglha glaciers in the remote headwater in the Tibetan Plateau (TP) and lacks historical in situ hydrological observations in the long term. Therefore, the Joint Research Center (JRC) Global Surface Water dataset (GSW), and the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) data were used for estimating the total amount of water storage of the two reservoirs, and the SRTM and TanDEM-X DEMs were used for estimating the glacier mass balance. The result shows that the total amount of water impounded by reservoirs is 0.76 Gt, roughly 54% of their design capacities. The mass balance of the glaciers is estimated by comparing the elevation changes between the SRTM and TanDEM-X DEMs. The glaciers in this region melt at an average rate of 0.09 ± 0.02 Gt·year⁻¹ from 2000 to circa 2013, and the impounded water of these reservoirs is comparable to the amount of glacier-fed meltwater in eight years. Full article

(This article belongs to the Special Issue Understanding Surface Water Dynamics Based on Multisource Remote Sensing Data)

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