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Remote Sensing
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Remote Sensing in Hydrogeology; New Sensors, Applications, and Combined Methods
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Remote Sensing in Hydrogeology; New Sensors, Applications, and Combined Methods

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 7142

Special Issue Editors

Prof. Dr. Timothy D. Bechtel

E-Mail Website
Guest Editor
Department of Earth and Environment, Franklin & Marshall College, Lancaster, PA 17603, USA
Interests: hydrogeophysics; karst hydrogeology; wetland hydrogeology; remote sensing
Prof. Dr. Robert C. Walter

E-Mail Website
Guest Editor
Department of Earth and Environment, Franklin & Marshall College, Lancaster, PA 17603, USA
Interests: hydrogeology; geochemistry; geochronology

Special Issue Information

Dear Colleagues,

Over 90% of Earth’s liquid freshwater is underground.  As traditional sources of surface water and shallow subsurface waters continue to be over-exploited and contaminated, climate change is altering weather patterns around the world, making water availability less predictable and shifting many water-stressed regions toward even dryer climates. It is now inescapable that new approaches are needed to supply water for drinking, sanitation, hygiene, agriculture, and industry. Understanding shifts in the water balance, including groundwater occurrence, movement, recharge, exploitation, depletion, and contamination on a large scale, and especially in under-studied regions and developing countries, is not just an intractable problem but its solution is critical for survival. There is no greater challenge on Earth today.

To solve this urgent dilemma, we call on researchers from around the world to contribute to this Special Issue by presenting new data, new ideas, and new ways to approach this problem.  In 1958, the oil geologist Parke Dickey said: “We usually find oil in a new place with old ideas. Sometimes, we find oil in an old place with a new idea, but we seldom find much oil in an old place with an old idea.” The same can be said now for water (our most critical resource as we run out of old places to look, and as old ideas are no longer sufficient).

This Special Issue aims to create a platform for novel cross-disciplinary advances in groundwater delineation, exploration, extraction, and use. We are especially keen on manuscripts presenting new insights and better models derived from subsurface, aerial, and satellite data generation (whether from relatively new sensors or satellite missions, or new applications of previously deployed sensors or satellites), especially when combined with innovative ground-based observations.  Creativity, innovation, and sustainability are central tenants of this Special Issue.

The aim of this Special Issue is to gather recent innovations into a single volume. We are seeking novel research and applications aimed at solving the above problem, focusing on the future of sustainable groundwater exploration and extraction.  Reviews or work previously published elsewhere, supplemented with new data, interpretations, and insights, also are encouraged.

Suggested topics include (but are not limited to) combining data from separate missions (e.g., GRACE and/or GRACE-FO, SAR and InSAR, LiDAR, LANDSAT, MODIS, Sentinel-1 and -2, IRS-LISS 3, SRTM, TRMM, GPM, GOES, POES, EOS, CALIPSO, CloudSat, SMOS, AMSR, ASCAT) with geophysical, GIS, geochemical, ground-based hydrogeological data.

Prof. Dr. Timothy D. Bechtel
Prof. Dr. Robert C. Walter
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. Remote Sensing 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 2700 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
  • sensors
  • satellites
  • field geology and hydrogeology
  • innovation
  • novel approaches

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Published Papers (3 papers)

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Research

28 pages, 4254 KiB  
Article
Remote Sensing-Based Estimates of Changes in Stored Groundwater at Local Scales: Case Study for Two Groundwater Subbasins in California’s Central Valley
by Aakash Ahamed, Rosemary Knight, Sarfaraz Alam, Michael Morphew and Tea Susskind
Remote Sens. 2023, 15(8), 2100; https://doi.org/10.3390/rs15082100 - 16 Apr 2023
Cited by 1 | Viewed by 2322
Abstract
Sustainable groundwater management requires high-quality and low-latency estimates of changes in groundwater storage (∆Sgw). However, estimates of ∆Sgw produced using traditional methods, including groundwater models and well-based measurements, typically lag years behind the present because collecting the required on-the-ground [...] Read more.
Sustainable groundwater management requires high-quality and low-latency estimates of changes in groundwater storage (∆Sgw). However, estimates of ∆Sgw produced using traditional methods, including groundwater models and well-based measurements, typically lag years behind the present because collecting the required on-the-ground data is a time consuming, expensive, and labor-intensive task. Satellite remote sensing measurements provide potential pathways to overcome these limitations by quantifying ∆Sgw through closing the water balance. However, the range of spatial scales over which ∆Sgw can be accurately estimated using remote sensing products remains unclear. To bridge this knowledge gap, this study quantified ∆Sgw for the period of 2002 through to 2021 using the water balance method and multiple remote sensing products in two subbasins (~2700 km2–3500 km2) within California’s Central Valley: (1) the Kaweah–Tule Subbasin, a region where the pumping of groundwater to support agriculture has resulted in decades of decline in head levels, resulting in land subsidence, damage to infrastructure, and contamination of drinking water and (2) the Butte Subbasin, which receives considerably more rainfall and surface water and has not experienced precipitous drops in groundwater. The remote sensing datasets which we utilized included multiple sources for key hydrologic components in the study area: precipitation, evapotranspiration, and soil moisture. To assess the fidelity of the remote sensing-based model, we compared estimates of ∆Sgw to alternative estimates of ∆Sgw derived from independent sources of data: groundwater wells as well as a widely used groundwater flow model. The results showed strong agreement in the Kaweah–Tule Subbasin in long-term ∆Sgw trends and shorter-term trends during droughts, and modest agreement in the Butte Subbasin with remote sensing datasets suggesting more seasonal variability than validation datasets. Importantly, our analysis shows that the timely availability of remote sensing data can potentially enable ∆Sgw estimates at sub-annual latencies, which is timelier than estimates derived through alternate methods, and thus can support adaptive management and decision making. The models developed herein can aid in assessing aquifer dynamics, and can guide the development of sustainable groundwater management practices at spatial scales relevant for management and decision making. Full article
(This article belongs to the Special Issue Remote Sensing in Hydrogeology; New Sensors, Applications, and Combined Methods)
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22 pages, 17021 KiB  
Article
Downscaling Simulation of Groundwater Storage in the Beijing, Tianjin, and Hebei Regions of China Based on GRACE Data
by Jianchong Sun, Litang Hu, Fei Chen, Kangning Sun, Lili Yu and Xin Liu
Remote Sens. 2023, 15(6), 1490; https://doi.org/10.3390/rs15061490 - 8 Mar 2023
Cited by 8 | Viewed by 2267
Abstract
Gravity Recovery and Climate Experiment (GRACE)-derived groundwater storage anomalies (GWSA) have been used to highlight groundwater depletion in regional aquifer systems worldwide. However, the use of GRACE products in smaller areas is limited owing to the coarse spatial resolution of the data product. [...] Read more.
Gravity Recovery and Climate Experiment (GRACE)-derived groundwater storage anomalies (GWSA) have been used to highlight groundwater depletion in regional aquifer systems worldwide. However, the use of GRACE products in smaller areas is limited owing to the coarse spatial resolution of the data product. This study utilized a dynamic downscaling method to improve the GWSA resolution from 1° to 0.05° by constructing a groundwater storage numerical model in the Beijing, Tianjin, and Hebei regions of China (BTH). The results indicate that: (1) the GRACE-derived and calculated GWSA had a good match with an average root mean squared error (RMSE) of 2.61 cm equivalent water height (EWH) and an average Nash–Sutcliffe efficiency coefficient (NSE) of 0.84 for the calibration period. (2) The hydraulic gradient coefficient and specific yield had the highest sensitivity, and transmissivity had the lowest sensitivity; however, different forcing data had no obvious influence on the GWSA. (3) The downscaled results not only exhibited time series variations that were consistent with those of the GRACE-derived solutions but also revealed a finer spatial heterogeneity of the GWSA along with increasing correlation coefficients between the GRACE-derived GWSA and the in situ measurements of groundwater levels by 0.06 and reducing the RMSE by 8.85%. (4) The downscaled results reflected the spatiotemporal change characteristics of groundwater storage in different hydrogeological units and administrative regions well. This study demonstrates the potential applications of the proposed downscaling method for both regional and local groundwater resource management. Full article
(This article belongs to the Special Issue Remote Sensing in Hydrogeology; New Sensors, Applications, and Combined Methods)
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22 pages, 7048 KiB  
Article
Evaluating the Applicability of PERSIANN-CDR Products in Drought Monitoring: A Case Study of Long-Term Droughts over Huaihe River Basin, China
by Na Yang, Hang Yu, Ying Lu, Yehui Zhang and Yunchuan Zheng
Remote Sens. 2022, 14(18), 4460; https://doi.org/10.3390/rs14184460 - 7 Sep 2022
Cited by 6 | Viewed by 1895
Abstract
In this study, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) was evaluated for the assessment of long-term drought monitoring in Huaihe River Basin using daily gauge observation data for the period from 1983 to 2017. The evaluation [...] Read more.
In this study, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) was evaluated for the assessment of long-term drought monitoring in Huaihe River Basin using daily gauge observation data for the period from 1983 to 2017. The evaluation results show that the PERSIANN-CDR algorithm has a good detection ability for small precipitation events over the whole basin, but a poor ability for extreme precipitation events (>50 mm/day). Daily PERSIANN-CDR estimates perform relatively better in areas with abundant precipitation, while the monthly and yearly PERSIANN-CDR estimates are highly consistent with gauge observations both in magnitude and space. The Standardized Precipitation Index (SPI) at various time scales (3, 6, and 12 months) was calculated based on PERSIANN-CDR and gauge observation, respectively. Grid-based values of statistics derived from those SPI values demonstrate that PERSIANN-CDR has a good ability to capture drought events of each time scale across the basin. However, caution should be applied when using PERSIANN-CDR estimates for basin-scale drought trend analysis. Furthermore, three drought events with long duration and large extent were selected to test the applicability of PERSIANN-CDR in drought monitoring. The results show that it has a good ability to capture when and where droughts occur and how far they spread. Due to the overestimation of small precipitation events, PERSIANN-CDR tends to overestimate the number of extreme droughts and their extents. This needs to be considered in future algorithm improvement. Full article
(This article belongs to the Special Issue Remote Sensing in Hydrogeology; New Sensors, Applications, and Combined Methods)
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