DETECTING EMERGING DROUGHT PATTERNS THROUGH LONG-TERM RAINFALL VARIABILITY ANALYSIS

Abstract

Long-term rainfall records are crucial for drought detection to understand temporal variability and to detect emerging hydroclimatic risks. In this study, multi-decadal duration of meteorological data obtained from 50 stations across the state of Sinaloa, Mexico, was analyzed to capture the rainfall variability, drought events, and longer-term trends in rainfall occurring across the state. Precipitation records for the annual and monthly cycles were analyzed through descriptive statistics, standardized precipitation anomalies, comparisons for the periods and Mann–Kendall trend analysis. The average annual precipitation was 707.64 mm and was very variable from year to year. A total of 13 large drought periods were identified, one from 1987 with significant drought and another from 2024, indicating a recent significant dry event. The regional rainfall showed no significant monotonic change (p=0.869) but station level analysis indicated significant decreasing trends at some stations, showing spatial heterogeneity. The frequency of droughts did not continuously increase over time. Emerging drought conditions were dominated overall by recurring rainfall deficits, pockets of rainfall decreases, and significant rainfall variability over time, rather than regional drying. The results are useful for local drought monitoring and adaptive management of water resources.