Soil Moisture Variability in India: Relationship of Land Surface–Atmosphere Fields Using Maximum Covariance Analysis
This study investigates the spatial and temporal variability of the soil moisture in India using Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) gridded datasets from June 2002 to April 2017. Significant relationships between soil moisture and different land surface⁻...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-02-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/11/3/335 |
| _version_ | 1818320901954863104 |
|---|---|
| author | Kishore Pangaluru Isabella Velicogna Geruo A Yara Mohajerani Enrico Ciracì Sravani Charakola Ghouse Basha S. Vijaya Bhaskara Rao |
| author_facet | Kishore Pangaluru Isabella Velicogna Geruo A Yara Mohajerani Enrico Ciracì Sravani Charakola Ghouse Basha S. Vijaya Bhaskara Rao |
| author_sort | Kishore Pangaluru |
| collection | DOAJ |
| description | This study investigates the spatial and temporal variability of the soil moisture in India using Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) gridded datasets from June 2002 to April 2017. Significant relationships between soil moisture and different land surface⁻atmosphere fields (Precipitation, surface air temperature, total cloud cover, and total water storage) were studied, using maximum covariance analysis (MCA) to extract dominant interactions that maximize the covariance between two fields. The first leading mode of MCA explained 56%, 87%, 81%, and 79% of the squared covariance function (SCF) between soil moisture with precipitation (PR), surface air temperature (TEM), total cloud count (TCC), and total water storage (TWS), respectively, with correlation coefficients of 0.65, −0.72, 0.71, and 0.62. Furthermore, the covariance analysis of total water storage showed contrasting patterns with soil moisture, especially over northwest, northeast, and west coast regions. In addition, the spatial distribution of seasonal and annual trends of soil moisture in India was estimated using a robust regression technique for the very first time. For most regions in India, significant positive trends were noticed in all seasons. Meanwhile, a small negative trend was observed over southern India. The monthly mean value of AMSR soil moisture trend revealed a significant positive trend, at about 0.0158 cm<sup>3</sup>/cm<sup>3</sup> per decade during the period ranging from 2002 to 2017. |
| first_indexed | 2024-12-13T10:32:23Z |
| format | Article |
| id | doaj.art-3041358a1050400a9c456c48ad3a322c |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-13T10:32:23Z |
| publishDate | 2019-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-3041358a1050400a9c456c48ad3a322c2022-12-21T23:50:50ZengMDPI AGRemote Sensing2072-42922019-02-0111333510.3390/rs11030335rs11030335Soil Moisture Variability in India: Relationship of Land Surface–Atmosphere Fields Using Maximum Covariance AnalysisKishore Pangaluru0Isabella Velicogna1Geruo A2Yara Mohajerani3Enrico Ciracì4Sravani Charakola5Ghouse Basha6S. Vijaya Bhaskara Rao7Department of Earth System Science, University of California, Irvine, CA 92697, USADepartment of Earth System Science, University of California, Irvine, CA 92697, USADepartment of Earth System Science, University of California, Irvine, CA 92697, USADepartment of Earth System Science, University of California, Irvine, CA 92697, USADepartment of Earth System Science, University of California, Irvine, CA 92697, USADepartment of Physics, Sri Venkateswara University, Tirupati 517502, IndiaNational Atmospheric Research Laboratory, Gadanki 517112, IndiaDepartment of Physics, Sri Venkateswara University, Tirupati 517502, IndiaThis study investigates the spatial and temporal variability of the soil moisture in India using Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) gridded datasets from June 2002 to April 2017. Significant relationships between soil moisture and different land surface⁻atmosphere fields (Precipitation, surface air temperature, total cloud cover, and total water storage) were studied, using maximum covariance analysis (MCA) to extract dominant interactions that maximize the covariance between two fields. The first leading mode of MCA explained 56%, 87%, 81%, and 79% of the squared covariance function (SCF) between soil moisture with precipitation (PR), surface air temperature (TEM), total cloud count (TCC), and total water storage (TWS), respectively, with correlation coefficients of 0.65, −0.72, 0.71, and 0.62. Furthermore, the covariance analysis of total water storage showed contrasting patterns with soil moisture, especially over northwest, northeast, and west coast regions. In addition, the spatial distribution of seasonal and annual trends of soil moisture in India was estimated using a robust regression technique for the very first time. For most regions in India, significant positive trends were noticed in all seasons. Meanwhile, a small negative trend was observed over southern India. The monthly mean value of AMSR soil moisture trend revealed a significant positive trend, at about 0.0158 cm<sup>3</sup>/cm<sup>3</sup> per decade during the period ranging from 2002 to 2017.https://www.mdpi.com/2072-4292/11/3/335soil moistureprecipitationtemperaturetotal cloud coverGRACEtotal water storageMCA analysis |
| spellingShingle | Kishore Pangaluru Isabella Velicogna Geruo A Yara Mohajerani Enrico Ciracì Sravani Charakola Ghouse Basha S. Vijaya Bhaskara Rao Soil Moisture Variability in India: Relationship of Land Surface–Atmosphere Fields Using Maximum Covariance Analysis Remote Sensing soil moisture precipitation temperature total cloud cover GRACE total water storage MCA analysis |
| title | Soil Moisture Variability in India: Relationship of Land Surface–Atmosphere Fields Using Maximum Covariance Analysis |
| title_full | Soil Moisture Variability in India: Relationship of Land Surface–Atmosphere Fields Using Maximum Covariance Analysis |
| title_fullStr | Soil Moisture Variability in India: Relationship of Land Surface–Atmosphere Fields Using Maximum Covariance Analysis |
| title_full_unstemmed | Soil Moisture Variability in India: Relationship of Land Surface–Atmosphere Fields Using Maximum Covariance Analysis |
| title_short | Soil Moisture Variability in India: Relationship of Land Surface–Atmosphere Fields Using Maximum Covariance Analysis |
| title_sort | soil moisture variability in india relationship of land surface atmosphere fields using maximum covariance analysis |
| topic | soil moisture precipitation temperature total cloud cover GRACE total water storage MCA analysis |
| url | https://www.mdpi.com/2072-4292/11/3/335 |
| work_keys_str_mv | AT kishorepangaluru soilmoisturevariabilityinindiarelationshipoflandsurfaceatmospherefieldsusingmaximumcovarianceanalysis AT isabellavelicogna soilmoisturevariabilityinindiarelationshipoflandsurfaceatmospherefieldsusingmaximumcovarianceanalysis AT geruoa soilmoisturevariabilityinindiarelationshipoflandsurfaceatmospherefieldsusingmaximumcovarianceanalysis AT yaramohajerani soilmoisturevariabilityinindiarelationshipoflandsurfaceatmospherefieldsusingmaximumcovarianceanalysis AT enricociraci soilmoisturevariabilityinindiarelationshipoflandsurfaceatmospherefieldsusingmaximumcovarianceanalysis AT sravanicharakola soilmoisturevariabilityinindiarelationshipoflandsurfaceatmospherefieldsusingmaximumcovarianceanalysis AT ghousebasha soilmoisturevariabilityinindiarelationshipoflandsurfaceatmospherefieldsusingmaximumcovarianceanalysis AT svijayabhaskararao soilmoisturevariabilityinindiarelationshipoflandsurfaceatmospherefieldsusingmaximumcovarianceanalysis |