Trend Detection and GEV-Based Frequency Analysis of Extreme Rainfall Events in Nagaland, India
Abstract
In this study, the extreme rainfall events at daily and monthly time scales were analyzed across all the major districts of Nagaland State located in the northeastern part of India by jointly using observed station data from Soil and Water Conservation Department, Government of Nagaland and India Meteorological Department’s gridded rainfall data (0.25° × 0.25°) for a period of 1995-2024. The extreme rainfall was analyzed for presence of homogeneity and trend, computing descriptive statistics, average monthly rainfall, annual and short-duration extreme rainfall indices, i.e., annual maximum 1-day (Rx1day), maximum consecutive 3-day (Rx3day), 5-day (Rx5day) and 10-day (Rx10day) rainfall, and the simple daily intensity index (SDII). Trends were identified using Mann-Kendall test and the trend magnitude was quantified using Sen’s slope estimation test. In addition, generalized extreme value (GEV)-based frequency analysis of the extreme rainfall was carried out. The results revealed no significant long-term rainfall trends in most of the districts; however, Tuensang district demonstrated statistically significant increasing trends in Rx3day, and Mon station showed a significant increasing trend in Rx1day. The GEV analysis revealed pronounced spatial variability, with Mokokchung and Wokha districts showing the highest 50-year and 100-year return periods in the observed rainfall dataset, and Mon, Dimapur and Longleng districts showing the highest return periods in the gridded dataset, implying higher hydrometeorological risk. The negative values of GEV shape parameters dominated the gridded dataset for most of the districts, signalling high risk for unprecedented future rainfall extremes. The integration of observed and gridded datasets strengthened the reliability of the extreme rainfall characterization, providing valuable insights for climate-resilient infrastructure planning, flood and landslide risk assessment, and water resource management in Nagaland’s complex terrain.