Trend Analysis of Rainfall Pattern in Arunachal Pradesh (India)
Rainfall variability is a key element in water resource management. There has been significant variability in rainfall in Arunachal Pradesh, with the state being in the highest rainfall zone in India. The present study attempts to investigate the annual rainfall trend along with the change points in...
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| Veröffentlicht in: | Environmental modeling & assessment 2023-12, Vol.28 (6), p.1093-1125 |
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| description | Rainfall variability is a key element in water resource management. There has been significant variability in rainfall in Arunachal Pradesh, with the state being in the highest rainfall zone in India. The present study attempts to investigate the annual rainfall trend along with the change points in the rainfall time series, considering more than a hundred years of data (1901–2002) in eleven districts of Arunachal Pradesh. First, a serial correlation test was conducted on the entire time-series data for the three districts to detect the serially independent time series, followed by the non-parametric Mann–Kendall test and Spearman’s rank correlation test to ascertain the presence of a statistically significant trend in hydrological climate variables. Sen’s slope method was applied to estimate the magnitude of the trend. Pre-whitening, trend free pre-whitening Mann–Kendall, and bias corrected pre-whitening, along with two variance correction approaches, are applied to the serially correlated data. All the districts under consideration show a decreasing trend in rainfall in the investigation over the years. A comparative study of the trend test method was also carried out. Further, to identify the trend change points in the time series, a sequential Mann–Kendall test is conducted. Assessing 100 years of time series data for the region makes the study unique of its kind and is likely to play a vital role in environmental policymaking. Furthermore, it will be helpful for water resource management, land use, land cover management, sustainable agricultural planning, and the overall socio-economic development of the region. |
| doi_str_mv | 10.1007/s10666-023-09903-3 |
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There has been significant variability in rainfall in Arunachal Pradesh, with the state being in the highest rainfall zone in India. The present study attempts to investigate the annual rainfall trend along with the change points in the rainfall time series, considering more than a hundred years of data (1901–2002) in eleven districts of Arunachal Pradesh. First, a serial correlation test was conducted on the entire time-series data for the three districts to detect the serially independent time series, followed by the non-parametric Mann–Kendall test and Spearman’s rank correlation test to ascertain the presence of a statistically significant trend in hydrological climate variables. Sen’s slope method was applied to estimate the magnitude of the trend. Pre-whitening, trend free pre-whitening Mann–Kendall, and bias corrected pre-whitening, along with two variance correction approaches, are applied to the serially correlated data. All the districts under consideration show a decreasing trend in rainfall in the investigation over the years. A comparative study of the trend test method was also carried out. Further, to identify the trend change points in the time series, a sequential Mann–Kendall test is conducted. Assessing 100 years of time series data for the region makes the study unique of its kind and is likely to play a vital role in environmental policymaking. 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Appl. in Environmental Science ; Mathematical Modeling and Industrial Mathematics ; Operations Research/Decision Theory ; Pattern analysis ; Precipitation variability ; rain ; Rain and rainfall ; Rainfall ; Resource management ; socioeconomic development ; Statistical analysis ; Sustainable agriculture ; Time series ; time series analysis ; Trend analysis ; Variability ; variance ; Water ; water management ; Water resources management</subject><ispartof>Environmental modeling & assessment, 2023-12, Vol.28 (6), p.1093-1125</ispartof><rights>The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. 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There has been significant variability in rainfall in Arunachal Pradesh, with the state being in the highest rainfall zone in India. The present study attempts to investigate the annual rainfall trend along with the change points in the rainfall time series, considering more than a hundred years of data (1901–2002) in eleven districts of Arunachal Pradesh. First, a serial correlation test was conducted on the entire time-series data for the three districts to detect the serially independent time series, followed by the non-parametric Mann–Kendall test and Spearman’s rank correlation test to ascertain the presence of a statistically significant trend in hydrological climate variables. Sen’s slope method was applied to estimate the magnitude of the trend. Pre-whitening, trend free pre-whitening Mann–Kendall, and bias corrected pre-whitening, along with two variance correction approaches, are applied to the serially correlated data. All the districts under consideration show a decreasing trend in rainfall in the investigation over the years. A comparative study of the trend test method was also carried out. Further, to identify the trend change points in the time series, a sequential Mann–Kendall test is conducted. Assessing 100 years of time series data for the region makes the study unique of its kind and is likely to play a vital role in environmental policymaking. Furthermore, it will be helpful for water resource management, land use, land cover management, sustainable agricultural planning, and the overall socio-economic development of the region.</description><subject>Analysis</subject><subject>Annual rainfall</subject><subject>Applications of Mathematics</subject><subject>autocorrelation</subject><subject>climate</subject><subject>Climate change</subject><subject>Comparative studies</subject><subject>comparative study</subject><subject>Correlation</subject><subject>Earth and Environmental Science</subject><subject>Economic development</subject><subject>Environment</subject><subject>hydrology</subject><subject>India</subject><subject>Land cover</subject><subject>Land use</subject><subject>Land use management</subject><subject>Management</subject><subject>Math. Appl. in Environmental Science</subject><subject>Mathematical Modeling and Industrial Mathematics</subject><subject>Operations Research/Decision Theory</subject><subject>Pattern analysis</subject><subject>Precipitation variability</subject><subject>rain</subject><subject>Rain and rainfall</subject><subject>Rainfall</subject><subject>Resource management</subject><subject>socioeconomic development</subject><subject>Statistical analysis</subject><subject>Sustainable agriculture</subject><subject>Time series</subject><subject>time series analysis</subject><subject>Trend analysis</subject><subject>Variability</subject><subject>variance</subject><subject>Water</subject><subject>water management</subject><subject>Water resources management</subject><issn>1420-2026</issn><issn>1573-2967</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp9kU1LAzEQhoMoWKt_wNOCl3rYmu_snmQpfhQKitRzSLPZNmWbrcn20H_v6AqCB5nDOwzPO8zwInRN8JRgrO4SwVLKHFOW47LELGcnaESEYjktpTqFnlOcU0zlObpIaYsx8FiM0P0yulBnVTDtMfmUdU32ZnxoTNtmr6bvXQyZD1kVD8HYjYFhNLVLm2wyD7U3t5foDNjkrn50jN4fH5az53zx8jSfVYvcspL0OZO8IKIGWSmHmVKNk6VcSSpoowzjyhTGCGk5t1ypckV4jWnBsQQljXBsjCbD3n3sPg4u9Xrnk3Vta4LrDkkzIphQnJcFoDd_0G13iPBg0rQoCyIF4Qqo6UCtTes0fNz10Vio2u287YJrPMwrpQSsZYUEAx0MNnYpRdfoffQ7E4-aYP0Vgh5C0BCC_g5BMzCxwZQADmsXf2_5x_UJTXCF8w</recordid><startdate>20231201</startdate><enddate>20231201</enddate><creator>Goswami, Ghritartha</creator><creator>Prasad, Ram Kailash</creator><general>Springer International Publishing</general><general>Springer</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7ST</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88I</scope><scope>8AL</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>KR7</scope><scope>L.-</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0C</scope><scope>M0N</scope><scope>M2P</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PATMY</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>SOI</scope><scope>7S9</scope><scope>L.6</scope></search><sort><creationdate>20231201</creationdate><title>Trend Analysis of Rainfall Pattern in Arunachal Pradesh (India)</title><author>Goswami, Ghritartha ; Prasad, Ram Kailash</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c391t-364815d364b7e0377fe696b6252f7a347a8aa56c44c4779b14d0284064d01f5e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Analysis</topic><topic>Annual rainfall</topic><topic>Applications of Mathematics</topic><topic>autocorrelation</topic><topic>climate</topic><topic>Climate change</topic><topic>Comparative studies</topic><topic>comparative study</topic><topic>Correlation</topic><topic>Earth and Environmental Science</topic><topic>Economic development</topic><topic>Environment</topic><topic>hydrology</topic><topic>India</topic><topic>Land cover</topic><topic>Land use</topic><topic>Land use management</topic><topic>Management</topic><topic>Math. 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| subjects | Analysis Annual rainfall Applications of Mathematics autocorrelation climate Climate change Comparative studies comparative study Correlation Earth and Environmental Science Economic development Environment hydrology India Land cover Land use Land use management Management Math. Appl. in Environmental Science Mathematical Modeling and Industrial Mathematics Operations Research/Decision Theory Pattern analysis Precipitation variability rain Rain and rainfall Rainfall Resource management socioeconomic development Statistical analysis Sustainable agriculture Time series time series analysis Trend analysis Variability variance Water water management Water resources management |
| title | Trend Analysis of Rainfall Pattern in Arunachal Pradesh (India) |
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