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Tellus A: Dynamic Meteorology and Oceanography Volume 72, 2020 - Issue 1
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Research Article

Regional drought assessment using improved precipitation records under auxiliary information

He Jiang1 School of Statistics, Jiangxi University of Finance and Economics, Nanchang, People’s Republic ChinaView further author information
,
Muhammad Asif Khan1 School of Statistics, Jiangxi University of Finance and Economics, Nanchang, People’s Republic China;2 Department of Statistics, Islamia College University, Peshawar, Pakistan;3 Department of Pharmacy, Sarhad University of Science & Information Technology, Peshawar, PakistanCorrespondence[email protected]
View further author information
,
Zhilong Li1 School of Statistics, Jiangxi University of Finance and Economics, Nanchang, People’s Republic ChinaView further author information
,
Zulfiqar Ali4 Department of Statistics, Quaid-i-Azam University, Islamabad, PakistanORCID Iconhttps://orcid.org/0000-0001-9291-8342View further author information
ORCID Icon,
Farman Ali5 School of Mathematics and Statistics, Beijing Institute of Technology, Beijing, People’s Republic of ChinaView further author information
&
Sajid Gul6 School of Mathematics and Statistics, Zhengzhou University, Zhengzhou, People’s Republic of ChinaView further author information
Pages 1-26 | Received 08 Oct 2019, Accepted 18 May 2020, Published online: 15 Jul 2020

Figures & data

Fig. 1. Map of the selected regions.

Fig. 1. Map of the selected regions.

Table 1. Statistics of the selected stations.

Fig. 2. Flow chart. Precipitation (P), Average Temperature (AT), Correlation coefficient (r), Product Estimator (PE), Regression Estimator (RE), Improved Precipitation (IP), Probability Distributions (PDs).

Fig. 2. Flow chart. Precipitation (P), Average Temperature (AT), Correlation coefficient (r), Product Estimator (PE), Regression Estimator (RE), Improved Precipitation (IP), Probability Distributions (PDs).

Table 2. Categories of SPI and RIWSDI.

Fig. 3. Comparison of precipitation records.

Fig. 3. Comparison of precipitation records.

Table 3. Statistics of the selected clusters (Regions).

Table 4. Top-notch distributions with their parameters for Region-1.

Table 5. Top-notch distributions with their parameters for Region-3.

Table 6. Top-notch distributions with their parameters for Region-6.

Table 7. Top-notch distributions with their parameters for Region-7.

Fig. 4. Comparison of RIWSDI-3 and SPI-3.

Fig. 4. Comparison of RIWSDI-3 and SPI-3.

Fig. 5. Comparison of RIWSDI-12 and SPI-12.

Fig. 5. Comparison of RIWSDI-12 and SPI-12.

Fig. 6. Correlations of RIWSDI-3 and SPI-3.

Fig. 6. Correlations of RIWSDI-3 and SPI-3.

Fig. 7. Correlations of RIWSDI-12 and SPI-12.

Fig. 7. Correlations of RIWSDI-12 and SPI-12.

Fig. 8. Observed probability distribution functions for RIWSDI-3 and SPI-3 (Regions 1-4).

Fig. 8. Observed probability distribution functions for RIWSDI-3 and SPI-3 (Regions 1-4).

Fig. 9. Observed probability distribution functions for RIWSDI-3 and SPI-3 (Regions 5-7).

Fig. 9. Observed probability distribution functions for RIWSDI-3 and SPI-3 (Regions 5-7).

Fig. 10. Observed probability distribution functions for RIWSDI-12 and SPI-12 (Regions 1-4).

Fig. 10. Observed probability distribution functions for RIWSDI-12 and SPI-12 (Regions 1-4).

Fig. 11. Observed probability distribution functions for RIWSDI-12 and SPI-12 (Regions 5-7).

Fig. 11. Observed probability distribution functions for RIWSDI-12 and SPI-12 (Regions 5-7).

Table 8. Probability plotting position techniques.

Table 9. Non-parametric determination: correlation of RIWSDI-12 and SPI-12.

Table 10. Shapiro–Wilk test for Region (1–5).

Table 11. Shapiro–Wilk test for Region (6–7).

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