Application of ESACCI SM product-assimilated to a statistical model to assess the drought propagation for different Agro-Climatic zones of India using copula
Meteorological drought precedes the agricultural drought and studying the propagation time from meteorological to agricultural drought can substantially reduce agricultural losses. To find this propagation time between the meteorological and agricultural drought, this study analyzed the copula-based...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-03-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843224000554 |
| _version_ | 1797303366346342400 |
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| author | Hussain Palagiri N Sudardeva Manali Pal |
| author_facet | Hussain Palagiri N Sudardeva Manali Pal |
| author_sort | Hussain Palagiri |
| collection | DOAJ |
| description | Meteorological drought precedes the agricultural drought and studying the propagation time from meteorological to agricultural drought can substantially reduce agricultural losses. To find this propagation time between the meteorological and agricultural drought, this study analyzed the copula-based conditional probability between the Standardized Precipitation Index at 12 timescales (SPI-1 to12, meteorological drought) and Standardized Soil Moisture Index at 1 month timescale (SSI-1, agricultural drought), over the fifteen Agro-Climatic Zones (ACZs) of India. SSI is computed using a total column Soil Moisture (SM) derived from ESACCI SM using the Statistical Soil Moisture Profile (SSMP) model. The SSMP-based ESACCI SM is positively correlated (Correlation Coefficient of 0.871) with ERA5 Land SM. To compute the conditional probability, three copulas namely Frank, Clayton, and Gumbel copulas are fitted between SPI-1 to 12 and SSI-1. The Goodness of Fit analysis showed the dominance of the Gumbel copula among the Clayton, Frank, and Gumbel copulas. Gumbel copula completely dominated the SPI timescales of 1–3 and 11–12 whereas Clayton copula was relatively favored for SPI timescales of 4–10. The propagation time results revealed that the monsoon season (JAS) consistently exhibits the highest propagation time, averaging around 10 months followed by summer (AMJ, 7 months), spring (JFM, 4 months), and winter (OND, 2–3 months) seasons. The Mann-Kendall trend test revealed that the same season can have different trends in different ACZs and vice versa, underlining the localized and season-specific strategies for drought management, considering each ACZ's unique environmental, agricultural, and socio-economic conditions in each zone. Overall, this study showcases the capability of remote sensing and copula-based statistical models, in understanding meteorological to agricultural drought propagation. It also highlights the efficiency of statistical models in deriving total column SM from surface SM. |
| first_indexed | 2024-03-07T23:51:42Z |
| format | Article |
| id | doaj.art-15b267a8cde840daa379f9ae787c39f4 |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-03-07T23:51:42Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-15b267a8cde840daa379f9ae787c39f42024-02-19T04:13:19ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322024-03-01127103701Application of ESACCI SM product-assimilated to a statistical model to assess the drought propagation for different Agro-Climatic zones of India using copulaHussain Palagiri0N Sudardeva1Manali Pal2Department of Civil Engineering, NIT Warangal, Telangana 506004, IndiaDepartment of Civil Engineering, NIT Warangal, Telangana 506004, IndiaCorresponding author.; Department of Civil Engineering, NIT Warangal, Telangana 506004, IndiaMeteorological drought precedes the agricultural drought and studying the propagation time from meteorological to agricultural drought can substantially reduce agricultural losses. To find this propagation time between the meteorological and agricultural drought, this study analyzed the copula-based conditional probability between the Standardized Precipitation Index at 12 timescales (SPI-1 to12, meteorological drought) and Standardized Soil Moisture Index at 1 month timescale (SSI-1, agricultural drought), over the fifteen Agro-Climatic Zones (ACZs) of India. SSI is computed using a total column Soil Moisture (SM) derived from ESACCI SM using the Statistical Soil Moisture Profile (SSMP) model. The SSMP-based ESACCI SM is positively correlated (Correlation Coefficient of 0.871) with ERA5 Land SM. To compute the conditional probability, three copulas namely Frank, Clayton, and Gumbel copulas are fitted between SPI-1 to 12 and SSI-1. The Goodness of Fit analysis showed the dominance of the Gumbel copula among the Clayton, Frank, and Gumbel copulas. Gumbel copula completely dominated the SPI timescales of 1–3 and 11–12 whereas Clayton copula was relatively favored for SPI timescales of 4–10. The propagation time results revealed that the monsoon season (JAS) consistently exhibits the highest propagation time, averaging around 10 months followed by summer (AMJ, 7 months), spring (JFM, 4 months), and winter (OND, 2–3 months) seasons. The Mann-Kendall trend test revealed that the same season can have different trends in different ACZs and vice versa, underlining the localized and season-specific strategies for drought management, considering each ACZ's unique environmental, agricultural, and socio-economic conditions in each zone. Overall, this study showcases the capability of remote sensing and copula-based statistical models, in understanding meteorological to agricultural drought propagation. It also highlights the efficiency of statistical models in deriving total column SM from surface SM.http://www.sciencedirect.com/science/article/pii/S1569843224000554Microwave Remote SensingSoil Moisture (SM)ESACCI SMStatistical ModelsCopulasDrought Propagation |
| spellingShingle | Hussain Palagiri N Sudardeva Manali Pal Application of ESACCI SM product-assimilated to a statistical model to assess the drought propagation for different Agro-Climatic zones of India using copula International Journal of Applied Earth Observations and Geoinformation Microwave Remote Sensing Soil Moisture (SM) ESACCI SM Statistical Models Copulas Drought Propagation |
| title | Application of ESACCI SM product-assimilated to a statistical model to assess the drought propagation for different Agro-Climatic zones of India using copula |
| title_full | Application of ESACCI SM product-assimilated to a statistical model to assess the drought propagation for different Agro-Climatic zones of India using copula |
| title_fullStr | Application of ESACCI SM product-assimilated to a statistical model to assess the drought propagation for different Agro-Climatic zones of India using copula |
| title_full_unstemmed | Application of ESACCI SM product-assimilated to a statistical model to assess the drought propagation for different Agro-Climatic zones of India using copula |
| title_short | Application of ESACCI SM product-assimilated to a statistical model to assess the drought propagation for different Agro-Climatic zones of India using copula |
| title_sort | application of esacci sm product assimilated to a statistical model to assess the drought propagation for different agro climatic zones of india using copula |
| topic | Microwave Remote Sensing Soil Moisture (SM) ESACCI SM Statistical Models Copulas Drought Propagation |
| url | http://www.sciencedirect.com/science/article/pii/S1569843224000554 |
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