Spatiotemporal snow cover characterization and its linkage with climate change over the Chenab river basin, western Himalayas
Monitoring of snow cover variability is crucial because it is closely linked with mountain water resources, ecosystems, and climate change. For this, moderate-resolution imaging spectroradiometer (MODIS) daily snow cover products (SCPs, version 6) were used over the Chenab river basin (CRB) during 2...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2020-10-01
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| Series: | GIScience & Remote Sensing |
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| Online Access: | http://dx.doi.org/10.1080/15481603.2020.1821150 |
| _version_ | 1797679107140485120 |
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| author | Jaydeo K. Dharpure Akansha Patel Ajanta Goswami Anil V. Kulkarni Snehmani |
| author_facet | Jaydeo K. Dharpure Akansha Patel Ajanta Goswami Anil V. Kulkarni Snehmani |
| author_sort | Jaydeo K. Dharpure |
| collection | DOAJ |
| description | Monitoring of snow cover variability is crucial because it is closely linked with mountain water resources, ecosystems, and climate change. For this, moderate-resolution imaging spectroradiometer (MODIS) daily snow cover products (SCPs, version 6) were used over the Chenab river basin (CRB) during 2001–2017. In these data, cloud cover is a significant problem that produces a discontinuity in spatial and temporal scale for long-term snow cover monitoring. Therefore, a sequential non-spectral composite methodology (with five successive steps) was applied to reduce cloud obscuration. Further, the cloud gap-filled SCPs were validated with the indirect method as well as high-resolution satellite data (Landsat-8). Results indicate that the cloud-removed SCPs show an overall efficiency of 92.8 $$ \pm $$ 1.6% with an indirect approach, while an overestimation (9.3%) was observed between Landsat and MODIS snow cover area (SCA) along with higher correlation (R = 0.99, p < 0.001). The result shows an increasing trend (0.25% $${\rm{y}}{{\rm{r}}{ - 1}}$$) of mean annual SCA during 2001–2017, while it is slightly decreasing since 2009 and was statistically insignificant. Moreover, the Snow Cover Day and nine indexes (from snow depletion curves) were derived for snow cover characterization, indicating that a shift or change in the snow accumulation period in terms of the seasonal snow cover in the recent decade. Furthermore, the linear relationships between SCA and climatic variables were established to identify the influence of snow cover distribution and its related snowmelt onset. The analysis demonstrated that the precipitation and net shortwave radiation (SWN) were increasing in the north-eastern region of the basin. However, the air temperature ($${{\rm{T}}_{\rm{a}}}$$) and wind speed showed a declining trend. Furthermore, associated uncertainty and sensitivity analyzes were performed, suggesting that the SCA is more sensitive to $${{\rm{T}}_{\rm{a}}}$$. However, it may be less susceptible to precipitation during the melt season. Overall, this finding indicates the potential importance of climatic variables on the snow cover distribution that is essential for proper management of the hydrological system. |
| first_indexed | 2024-03-11T23:08:34Z |
| format | Article |
| id | doaj.art-951277af02b84ea4b49f373c62990592 |
| institution | Directory Open Access Journal |
| issn | 1548-1603 1943-7226 |
| language | English |
| last_indexed | 2024-03-11T23:08:34Z |
| publishDate | 2020-10-01 |
| publisher | Taylor & Francis Group |
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| series | GIScience & Remote Sensing |
| spelling | doaj.art-951277af02b84ea4b49f373c629905922023-09-21T12:34:16ZengTaylor & Francis GroupGIScience & Remote Sensing1548-16031943-72262020-10-0157788290610.1080/15481603.2020.18211501821150Spatiotemporal snow cover characterization and its linkage with climate change over the Chenab river basin, western HimalayasJaydeo K. Dharpure0Akansha Patel1Ajanta Goswami2Anil V. Kulkarni3Snehmani4Indian Institute of TechnologyIndian Institute of TechnologyIndian Institute of TechnologyIndian Institute of Science (IISc)Defence Research & Development Organisation (DRDO), Ministry of DefenceMonitoring of snow cover variability is crucial because it is closely linked with mountain water resources, ecosystems, and climate change. For this, moderate-resolution imaging spectroradiometer (MODIS) daily snow cover products (SCPs, version 6) were used over the Chenab river basin (CRB) during 2001–2017. In these data, cloud cover is a significant problem that produces a discontinuity in spatial and temporal scale for long-term snow cover monitoring. Therefore, a sequential non-spectral composite methodology (with five successive steps) was applied to reduce cloud obscuration. Further, the cloud gap-filled SCPs were validated with the indirect method as well as high-resolution satellite data (Landsat-8). Results indicate that the cloud-removed SCPs show an overall efficiency of 92.8 $$ \pm $$ 1.6% with an indirect approach, while an overestimation (9.3%) was observed between Landsat and MODIS snow cover area (SCA) along with higher correlation (R = 0.99, p < 0.001). The result shows an increasing trend (0.25% $${\rm{y}}{{\rm{r}}{ - 1}}$$) of mean annual SCA during 2001–2017, while it is slightly decreasing since 2009 and was statistically insignificant. Moreover, the Snow Cover Day and nine indexes (from snow depletion curves) were derived for snow cover characterization, indicating that a shift or change in the snow accumulation period in terms of the seasonal snow cover in the recent decade. Furthermore, the linear relationships between SCA and climatic variables were established to identify the influence of snow cover distribution and its related snowmelt onset. The analysis demonstrated that the precipitation and net shortwave radiation (SWN) were increasing in the north-eastern region of the basin. However, the air temperature ($${{\rm{T}}_{\rm{a}}}$$) and wind speed showed a declining trend. Furthermore, associated uncertainty and sensitivity analyzes were performed, suggesting that the SCA is more sensitive to $${{\rm{T}}_{\rm{a}}}$$. However, it may be less susceptible to precipitation during the melt season. Overall, this finding indicates the potential importance of climatic variables on the snow cover distribution that is essential for proper management of the hydrological system.http://dx.doi.org/10.1080/15481603.2020.1821150climatic variabilitycloud gap-filling algorithmmodis snow cover productssnow cover variabilitytrend analysis |
| spellingShingle | Jaydeo K. Dharpure Akansha Patel Ajanta Goswami Anil V. Kulkarni Snehmani Spatiotemporal snow cover characterization and its linkage with climate change over the Chenab river basin, western Himalayas GIScience & Remote Sensing climatic variability cloud gap-filling algorithm modis snow cover products snow cover variability trend analysis |
| title | Spatiotemporal snow cover characterization and its linkage with climate change over the Chenab river basin, western Himalayas |
| title_full | Spatiotemporal snow cover characterization and its linkage with climate change over the Chenab river basin, western Himalayas |
| title_fullStr | Spatiotemporal snow cover characterization and its linkage with climate change over the Chenab river basin, western Himalayas |
| title_full_unstemmed | Spatiotemporal snow cover characterization and its linkage with climate change over the Chenab river basin, western Himalayas |
| title_short | Spatiotemporal snow cover characterization and its linkage with climate change over the Chenab river basin, western Himalayas |
| title_sort | spatiotemporal snow cover characterization and its linkage with climate change over the chenab river basin western himalayas |
| topic | climatic variability cloud gap-filling algorithm modis snow cover products snow cover variability trend analysis |
| url | http://dx.doi.org/10.1080/15481603.2020.1821150 |
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