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Application of GRACE Observations in Water Cycle and Climate Change
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Application of GRACE Observations in Water Cycle and Climate Change

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 (24 May 2024) | Viewed by 9908

Special Issue Editors

Dr. Wenjie Yin

E-Mail Website
Guest Editor
Satellite Application Center for Ecology and Environment, Ministry of Ecology and Environment, Beijing 100094, China
Interests: GRACE; machine learning; downscaling research; climate change; water resource management
Special Issues, Collections and Topics in MDPI journals
Dr. Yuyue Xu

E-Mail Website
Guest Editor
School of Geography and Ocean Science, Nanjing University, Nanjing, China
Interests: hydrology; remote sensing; terrestrial water storage change; climate change; water resources management
Dr. Nengfang Chao

E-Mail Website
Guest Editor
Hubei Key Laboratory of Marine Geological Resources, China University of Geosciences, Wuhan, China
Interests: GRACE; GRACE-FO; geodesy; satellite altimetry; climate change
Dr. Chang Huang

E-Mail Website
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

Special Issue Information

Dear Colleagues,

Due to global warming, a series of hydrological problems such as water shortage, melting glaciers and rising sea levels are disrupting the balance of the Earth system, leading to the intensification of flood and drought events in recent years. Hydro-geodetic techniques, including GRACE, GNSS, and INSAR satellites, use geodetic principles to monitor the Earth's environmental changes and generate data that can be applied to hydrological research. Particularly, GRACE can detect large-scale hydrological changes with an unprecedented accuracy. Moreover, quantifying the contribution of climate change and human activities can help humans realize their role in the water cycle. Recently, spatiotemporal downscaling of GRACE data has enabled their applicability at small scales and helps generate finer global datasets. Hydro-geodesy technology has great potential for monitoring water storage, glacier mass changes, and discharge.

This Special Issue focuses on the spatiotemporal variations of terrestrial and groundwater storage as well as its response to climate change. Moreover, some new technologies and measures are encouraged to improve GRACE solutions, to promote its application in the water cycle and water resources management. We welcome the submission of high-quality conceptual and empirical papers for ideas and inspirations related to our topics, as follows:

  • Analysis of water storage changes at global and regional scales;
  • Estimation of groundwater levels using remote sensing and physically models;
  • Spatiotemporal downscaling of GRACE data;
  • Forecast and hindcast of water storage variations;
  • Detection flood and drought events based on GRACE data;
  • Monitoring runoff and evapotranspiration in ungauged areas;
  • Response of water storage to climate change and human activities.

Dr. Wenjie Yin
Dr. Yuyue Xu
Dr. Nengfang Chao
Dr. Chang Huang
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

  • GRACE
  • GNSS, INSAR
  • water storage changes
  • flood and drought events
  • machine learning
  • downscaling researches
  • hydrology

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Published Papers (4 papers)

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Research

18 pages, 8811 KiB  
Article
Coastal Water Clarity in Shenzhen: Assessment of Observations from Sentinel-2
by Yelong Zhao, Jinsong Chen, Xiaoli Li, Hongzhong Li and Longlong Zhao
Water 2023, 15(23), 4102; https://doi.org/10.3390/w15234102 - 27 Nov 2023
Cited by 1 | Viewed by 1674
Abstract
Shenzhen is a crucial city in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). With high-intensity land development and rapid population growth, the ocean has become an essential space for expansion, leading to significant variations in water quality in the coastal area of Shenzhen. [...] Read more.
Shenzhen is a crucial city in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). With high-intensity land development and rapid population growth, the ocean has become an essential space for expansion, leading to significant variations in water quality in the coastal area of Shenzhen. Water clarity (Zsd) is a key indicator for evaluating water quality. We applied the quasi-analytical algorithm (QAA) to Sentinel-2 data and retrieved the Zsd of the coastal area of Shenzhen. By adjusting the red band for distinguishing water types, we avoided underestimating Zsd for clear water. This study pioneered the production of a 10 m Zsd product for the coastal area of Shenzhen from 2016 to 2021. The results showed that the coastal area of Shenzhen exhibited a spatial distribution pattern with low Zsd in the west and high in the east, with Pearl River Estuary (PRE: 0.41–0.67 m) and Shenzhen Bay (SZB: 0.30–0.58 m) being lower than Dapeng Bay (DPB: 2.7–2.9 m) and Daya Bay (DYB: 2.5–2.9 m). We analyzed the seasonal and interannual variations and driving factors of the four areas, where PRE and SZB showed similar variation patterns, while DPB and DYB showed similar variation patterns. PRE and SZB are important estuaries in southern China, significantly affected by anthropogenic activities. DPB and DYB are important marine aquaculture areas, mainly affected by natural factors (wind speed, precipitation, and sea level). The Zsd of the coastal area of Shenzhen, along with the analysis of its results and driving factors, contributes to promoting local water resource protection and providing a reference for formulating relevant governance policies. It also provides a practical method for assessing and monitoring near-shore water quality. Full article
(This article belongs to the Special Issue Application of GRACE Observations in Water Cycle and Climate Change)
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23 pages, 6259 KiB  
Article
Spatio-Temporal Distribution of Dissolved Inorganic Nitrogen in the Changshan Islands Archipelago Based on a Multiple Weighted Regression Model Considering Spatial Characteristics
by Xinmei Lan, Jin Qi, Weidong Song, Hongbo Zhu, Bing Zhang, Jiguang Dai, Yang Ye and Guokun Xue
Water 2023, 15(18), 3176; https://doi.org/10.3390/w15183176 - 5 Sep 2023
Viewed by 1660
Abstract
Ammonia nitrogen (NH4-N), nitrite nitrogen (NO2-N), and nitrate nitrogen (NO3-N) are important nutrients for maintaining the ecological balance of seawater archipelagos. Obtaining the concentrations of the three nitrogenous compounds simultaneously can allow us to comprehensively analyze nitrogen cycling in archipelago waters, which is [...] Read more.
Ammonia nitrogen (NH4-N), nitrite nitrogen (NO2-N), and nitrate nitrogen (NO3-N) are important nutrients for maintaining the ecological balance of seawater archipelagos. Obtaining the concentrations of the three nitrogenous compounds simultaneously can allow us to comprehensively analyze nitrogen cycling in archipelago waters, which is beneficial to the ecological protection of both agriculture and fisheries. The existing studies have usually considered a single nitrogen compound or dissolved inorganic nitrogen (DIN), which can only identify the water quality but cannot comprehensively judge the water purification situation or the toxicity of the nitrogen compounds in the water. In the process of constructing an inversion model, only the specific bands of remote sensing imageries used in training/learning are directly related to the actual measured values, ignoring the fact that the specific bands contain information on water quality parameters is different that would affect the fitting accuracy. Furthermore, the existing empirical models and machine learning models have not yet been applied to high-resolution inversion in archipelago waters with active fishing activities. In view of this, we constructed a multiple weighted regression model considering spatial characteristics (S-WSVR) to simultaneously retrieve the distribution of NH4-N, NO2-N, and NO3-N in archipelagic waters. By using the S-WSVR model and considering the complexity of the spatial distribution of the three nitrogen compounds in the mesoscale archipelagic waters, longitude and latitude were added to the experimental dataset as spatial features to fit the nonlinear spatial relationships. Meanwhile, a multivariate weighting module based on the Mahalanobis distance was integrated to calculate the contribution of the characteristic bands and improve the inversion accuracy. The S-WSVR model was applied in the water of Changshan Islands, China, with a retrieval resolution of 30 m, and the r-values of the three nitrogen compounds achieved 0.9063, 0.8900, and 0.9755, respectively. Notably, the sum of the three nitrogen compounds has an r-value of 0.9028 when compared with the measured DIN. In addition, we obtained the Landsat 8 characteristic bands for the three nitrogen compounds and plotted the spatial distributions of the nitrogen compounds in spring and autumn from 2013 to 2022. By analyzing the spatio-temporal variations, it was apparent that the three nitrogen compounds are controlled by human activities and river inputs, and the anoxic discharge of the Yalu River has a strong influence on NO2-N content. Therefore, the accurate estimation in this study can provide scientific support for the protection of sensitive archipelago ecosystems. Full article
(This article belongs to the Special Issue Application of GRACE Observations in Water Cycle and Climate Change)
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17 pages, 6694 KiB  
Article
The Influence of the South-to-North Water-Diversion Project on Terrestrial Water-Storage Changes in Hebei Province
by Tianxu Liu, Dasheng Zhang, Yanfeng Shi, Yi Li, Jianchong Sun and Xiuping Zhang
Water 2023, 15(17), 3112; https://doi.org/10.3390/w15173112 - 30 Aug 2023
Viewed by 1628
Abstract
The lack of water resources has emerged as a major factor limiting the high-quality economic and ecological development in Hebei Province. Therefore, it is of great significance to understand the dynamic changes in terrestrial water storage for effectively managing water resources in Hebei [...] Read more.
The lack of water resources has emerged as a major factor limiting the high-quality economic and ecological development in Hebei Province. Therefore, it is of great significance to understand the dynamic changes in terrestrial water storage for effectively managing water resources in Hebei Province. The evolution pattern and spatial distribution of TWS anomalies (TWSA) were analyzed utilizing gravity recovery and climate experiment (GRACE) solutions and the water balance method from 2003 to 2020, and the missing monthly data during GRACE and GRACE-FO missions were filled by combining the climate-driven model and meteorological products. Moreover, the impact of the south-to-north water-diversion (SNWD) project on alleviating the water-storage deficit was quantified. The results revealed that the water-balance method on the strength of the combination of CMA precipitation and Noahv2.1-simulated evapotranspiration and runoff data matches well with the TWSA data derived from GRACE, with a correlation coefficient up to 0.95. However, the accuracy was unsatisfactory during the process of characterizing the spatial characteristics of TWSA. After the SNWD project, GRACE-derived results showed that the downtrends of TWSA were reduced by 10.93%, especially in mountainous areas: by 79.78%. Concerning the spatial scale, the deficit trends were reduced to a certain extent in northern Hebei Province, while the decreasing trends cannot be reversed for a short time in southern areas where human activities are intensive. Full article
(This article belongs to the Special Issue Application of GRACE Observations in Water Cycle and Climate Change)
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22 pages, 21194 KiB  
Article
Improving the Resolution of GRACE/InSAR Groundwater Storage Estimations Using a New Subsidence Feature Weighted Combination Scheme
by Qingqing Wang, Wei Zheng, Wenjie Yin, Guohua Kang, Qihuan Huang and Yifan Shen
Water 2023, 15(6), 1017; https://doi.org/10.3390/w15061017 - 7 Mar 2023
Cited by 9 | Viewed by 3354
Abstract
GRACE observations and land subsidence data derived from InSAR both assess groundwater storage changes. However, GRACE data at local scales are restricted by the coarser spatial resolution of satellite systems, and inversion of Groundwater Storage Anomalies (GWSA) by InSAR requires extensive [...] Read more.
GRACE observations and land subsidence data derived from InSAR both assess groundwater storage changes. However, GRACE data at local scales are restricted by the coarser spatial resolution of satellite systems, and inversion of Groundwater Storage Anomalies (GWSA) by InSAR requires extensive and unavailable lithological data. Here, we propose a New Subsidence Feature Weighted Combination (NSFWC) scheme to enhance the spatial resolution of GRACE-derived GWSA from 0.5° to 0.05°. This method can not only retain the spatial distribution of groundwater changes but also reflect local details related to surface subsidence. A case study was executed to evaluate the performance of the NSFWC scheme in the Beijing Plain, which has seriously overexploited groundwater. Results showed that the simulated GWSA were consistent with in situ measurements in most regions, with a correlation coefficient of 0.85 and an RMSE of 4.41 mm/year. Additionally, there were 22 overexploited wells in the Beijing Plain, although groundwater levels generally recovered after the South to North Water Diversion Project. Simultaneously, four cones of depression were detected by the InSAR technology, where the maximum cumulative subsidence and subsidence rate achieved −198.52 mm and −53.09 mm/year, respectively. This paper provides data support and technical guarantees for small-scale groundwater resources management. Full article
(This article belongs to the Special Issue Application of GRACE Observations in Water Cycle and Climate Change)
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