<p>This study explores rainfall regionalization to understand spatial and temporal variations in the Teesta River Basin using 122 years (1901–2022) of monthly precipitation data from the Indian Meteorological Department (IMD) with 23 rain-gauge stations. The seasonality index (SI), the precipitation concentration index (PCI), the innovative trend analysis (ITA), the Mann-Kendall test (MK) family, and the cluster analysis (K-means and fuzzy) were used to the annual precipitation data to compare and visualize temporal patterns. Spatial variability was discovered by trend analysis using the ITA and MK tests. Results indicate spatial variability in trends, with significant positive trends in annual rainfall observed at stations G4, G7, G9, and G13, while stations G6 and G10 show negative trends. According to the MK family test, 8 out of 23 rain gauge sites in the Teesta River Basin displayed a monotonic trend in rainfall. The ITA indicates that at a significance level of 99%, 13 stations exhibit increasing trends in historical annual rainfall, whereas eight stations demonstrate decreasing trends. Additionally, trends in rainfall at two stations are deemed not significant. By employing rainfall regionalization techniques like clustering (fuzzy C-means or K-means), study area stations are grouped into two clusters with similar characteristics. Stations in the upper basin are included in Cluster 1, while stations in the lower basin are covered by Cluster 2. Silhouette width analysis was used to validate the clustering results. Researchers and policymakers can benefit from rainfall regionalisation by better understanding the variability of precipitation within river basins.</p>

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Identification of homogeneous rainfall regions and spatial-temporal variability in the Teesta River Basin

  • Prasanya Sarkar,
  • Shasanka Kumar Gayen

摘要

This study explores rainfall regionalization to understand spatial and temporal variations in the Teesta River Basin using 122 years (1901–2022) of monthly precipitation data from the Indian Meteorological Department (IMD) with 23 rain-gauge stations. The seasonality index (SI), the precipitation concentration index (PCI), the innovative trend analysis (ITA), the Mann-Kendall test (MK) family, and the cluster analysis (K-means and fuzzy) were used to the annual precipitation data to compare and visualize temporal patterns. Spatial variability was discovered by trend analysis using the ITA and MK tests. Results indicate spatial variability in trends, with significant positive trends in annual rainfall observed at stations G4, G7, G9, and G13, while stations G6 and G10 show negative trends. According to the MK family test, 8 out of 23 rain gauge sites in the Teesta River Basin displayed a monotonic trend in rainfall. The ITA indicates that at a significance level of 99%, 13 stations exhibit increasing trends in historical annual rainfall, whereas eight stations demonstrate decreasing trends. Additionally, trends in rainfall at two stations are deemed not significant. By employing rainfall regionalization techniques like clustering (fuzzy C-means or K-means), study area stations are grouped into two clusters with similar characteristics. Stations in the upper basin are included in Cluster 1, while stations in the lower basin are covered by Cluster 2. Silhouette width analysis was used to validate the clustering results. Researchers and policymakers can benefit from rainfall regionalisation by better understanding the variability of precipitation within river basins.