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Climate Change Impact on Water and Soil Using Remote Sensing
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Climate Change Impact on Water and Soil Using Remote Sensing

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Agriculture and Vegetation".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 8694

Special Issue Editors

Dr. Sananda Kundu

E-Mail Website
Guest Editor
Department of Geography, Manipur University, Canchipur, Imphal 795003, Manipur, India
Interests: remote sensing; hydrology; climate change; land use classification and change modeling; evapotranspiration; flood
Special Issues, Collections and Topics in MDPI journals
Dr. Emilio Rodriguez Caballero

E-Mail Website1 Website2
Guest Editor
Departamento de Edafología y Química Agrícola, Universidad de Almería, La Cañada de San Urbano s/n, Almería, Spain
Interests: biological soil crust; soil erosion; runoff generation; remote sensing; micro-topography

Special Issue Information

Dear Colleagues,

Changes in climatic variables are affecting the land, soil, and water resources, which constitute the essential parts of ecosystems. Climate change can affect and modify the rate of change of water and soil characteristics of the earth. Hence, it is essential to understand the changes caused by climatic variables. These include rainfall, temperature, humidity, wind speed, hours of sunshine, and solar radiation, which significantly impact landscapes, recharge and runoff, and responses of various components of the hydrological cycle including soil moisture, baseflow, evapotranspiration, and the shift from snow to rain. Moreover, hydroclimatic extremes like droughts, floods, landslides, and heat waves are indicating an unprecedented intensification in the last few decades, occurrences instigated to a large extent by climate change. Soil erosion caused by wind or water leads to various small- and large-scale effects including salinization, gully erosion, land use/cover change, expansion or abandonment of agriculture, deforestation, drought, etc. Application of various remote sensing data and in-situ sensors have increased the ability to understand and assess the physical processes on the surface of the earth.

This Special Issue is aimed at the collection of the latest novel methodological proposals and modeling contributions utilizing remote sensing data and techniques, with an emphasis on the impacts of climate change on soil and water resources. We look forward to manuscripts within, but not limited to, the following focus areas:

  • trends in climate change, extremes, and hydrology
  • remote sensing and in situ observation, hydrology, land degradation
  • climate change and soil–water balance
  • climate change and evapotranspiration, snow, soil moisture
  • climate change and soil erosion
  • climate change and groundwater
  • climate change, water systems, and agriculture
  • ecosystem, hydrology, climate change, and soil
  • climate change, soil, and water quality
  • climate-hydrology-degradation (modeling, artificial intelligence and machine learning, statistical methods)

Dr. Sananda Kundu
Dr. Emilio Rodriguez Caballero
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

  • climate change
  • hydrological extremes
  • soil erosion
  • land degradation
  • water balance
  • evapotranspiration
  • snow and soil moisture

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Published Papers (3 papers)

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25 pages, 7326 KiB  
Article
Enhancing Streamflow Modeling by Integrating GRACE Data and Shared Socio-Economic Pathways (SSPs) with SWAT in Hongshui River Basin, China
by Muhammad Touseef, Lihua Chen, Hang Chen, Hamza Farooq Gabriel, Wenzhe Yang and Ammara Mubeen
Remote Sens. 2023, 15(10), 2642; https://doi.org/10.3390/rs15102642 - 18 May 2023
Cited by 8 | Viewed by 2407
Abstract
Climatic variability and the quantification of climate change impacts on hydrological parameters are persistently uncertain. Remote sensing aids valuable information to streamflow estimations and hydrological parameter projections. However, few studies have been implemented using remote sensing and CMIP6 data embedded with hydrological modeling. [...] Read more.
Climatic variability and the quantification of climate change impacts on hydrological parameters are persistently uncertain. Remote sensing aids valuable information to streamflow estimations and hydrological parameter projections. However, few studies have been implemented using remote sensing and CMIP6 data embedded with hydrological modeling. This research studied how changing climate influences the hydro-climatic parameters based on the earth system models that participated in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). GRACE evapotranspiration data were forced into the Soil and Water Assessment Tool (SWAT) to project hydrologic responses to future climatic conditions in the Hongshui River basin (HRB) model. A novel approach based on climate elasticity was utilized to determine the extent to which climate variability affects stream flow. CMIP6 SSPs (shared socio-economic pathways) for the second half of the 20th century (1960–2020) and 21st century (2021–2100) projected precipitation (5–16%) for the whole Hongshui River basin (HRB). The ensemble of GCMs projected an increase of 2 °C in mean temperature. The stream flow is projected to increase by 4.2% under SSP-1.26, 6.2% under SSP-2.45, 8.45% under SSP-3.70, and 9.5% under SSP-5.85, based on the average changes throughout the various long-term future scenarios. We used the climate elasticity method and found that climate change contributes 11% to streamflow variability in the Hongshui River basin (HRB). Despite the uncertainty in projected hydrological variables, most members of the modeling ensemble present encouraging findings for future methods of water resource management. Full article
(This article belongs to the Special Issue Climate Change Impact on Water and Soil Using Remote Sensing)
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19 pages, 8800 KiB  
Article
Mapping Soil Erosion Dynamics (1990–2020) in the Pearl River Basin
by Xiaolin Mu, Junliang Qiu, Bowen Cao, Shirong Cai, Kunlong Niu and Xiankun Yang
Remote Sens. 2022, 14(23), 5949; https://doi.org/10.3390/rs14235949 - 24 Nov 2022
Cited by 10 | Viewed by 2281
Abstract
Healthy soil is the key foundation of the world’s agriculture and an essential resource to ensure the world’s food security. Soil erosion is one of the serious forms of soil degradation and a major threat to sustainable terrestrial ecosystems. In this study, we [...] Read more.
Healthy soil is the key foundation of the world’s agriculture and an essential resource to ensure the world’s food security. Soil erosion is one of the serious forms of soil degradation and a major threat to sustainable terrestrial ecosystems. In this study, we utilized a continuous Landsat satellite image dataset to map soil erosion changes (1990–2020) based on the RUSLE model across the Pearl River Basin. The study results indicated that: (1) The multi-year area-specific soil erosion average in the Pearl River Basin is approximately 538.95 t/(km2·a) with an annual soil loss of approximately 353 million tons; (2) The overall soil erosion displayed a decreasing trend over the past 30 years with an annual decreasing rate of −13.44(±1.53) t/(km2·a); (3) Soil erosion, dominated by low- and moderate-level erosion, primarily occurred in the tributary basin of Xijiang River, especially in the areas with slopes > 15°, low vegetation coverage, or poorly managed forests; (4) the NDVI and land cover were the dominant factors regulating soil erosion dynamics versus the insignificant role of precipitation played in the erosion procedure. The study results are valuable for soil erosion management and water conservation in the Pearl River Basin. Full article
(This article belongs to the Special Issue Climate Change Impact on Water and Soil Using Remote Sensing)
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19 pages, 38282 KiB  
Technical Note
Non-Destructive Biomass Estimation in Mediterranean Alpha Steppes: Improving Traditional Methods for Measuring Dry and Green Fractions by Combining Proximal Remote Sensing Tools
by Borja Rodríguez-Lozano, Emilio Rodríguez-Caballero, Lisa Maggioli and Yolanda Cantón
Remote Sens. 2021, 13(15), 2970; https://doi.org/10.3390/rs13152970 - 28 Jul 2021
Cited by 6 | Viewed by 2801
Abstract
The Mediterranean region is experiencing a stronger warming effect than other regions, which has generated a cascade of negative impacts on productivity, biodiversity, and stability of the ecosystem. To monitor ecosystem status and dynamics, aboveground biomass (AGB) is a good indicator, being a [...] Read more.
The Mediterranean region is experiencing a stronger warming effect than other regions, which has generated a cascade of negative impacts on productivity, biodiversity, and stability of the ecosystem. To monitor ecosystem status and dynamics, aboveground biomass (AGB) is a good indicator, being a surrogate of many ecosystem functions and services and one of the main terrestrial carbon pools. Thus, accurate methodologies for AGB estimation are needed. This has been traditionally done by performing direct field measurements. However, field-based methods, such as biomass harvesting, are destructive, expensive, and time consuming and only provide punctual information, not being appropriate for large scale applications. Here, we propose a new non-destructive methodology for monitoring the spatiotemporal dynamics of AGB and green biomass (GB) of M. tenacissima L. plants by combining structural information obtained from terrestrial laser scanner (TLS) point clouds and spectral information. Our results demonstrate that the three volume measurement methods derived from the TLS point clouds tested (3D convex hull, voxel, and raster surface models) improved the results obtained by traditional field-based measurements. (Adjust-R2 = 0.86–0.84 and RMSE = 927.3–960.2 g for AGB in OLS regressions and Adjust-R2 = 0.93 and RMSE = 376.6–385.1 g for AGB in gradient boosting regression). Among the approaches, the voxel model at 5 cm of spatial resolution provided the best results; however, differences with the 3D convex hull and raster surface-based models were very small. We also found that by combining TLS AGB estimations with spectral information, green and dry biomass fraction can be accurately measured (Adjust-R2 = 0.65–0.56 and RMSE = 149.96–166.87 g in OLS regressions and Adjust-R2 = 0.96–0.97 and RMSE = 46.1–49.8 g in gradient boosting regression), which is critical in heterogeneous Mediterranean ecosystems in which AGB largely varies in response to climatic fluctuations. Thus, our results represent important progress for the measurement of M. tenacissima L. biomass and dynamics, providing a promising tool for calibration and validation of further studies aimed at developing new methodologies for AGB estimation at ecosystem regional scales. Full article
(This article belongs to the Special Issue Climate Change Impact on Water and Soil Using Remote Sensing)
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