Background and Objectives: Meteorological drought, a critical challenge in semi-arid regions, profoundly impacts agriculture, water resources, and ecosystems in Semnan Province, Iran. The Damghan region, a vital agricultural area, is highly vulnerable to climatic fluctuations due to its arid climate and reliance on seasonal precipitation. Understanding temporal and spatial drought patterns is essential for effective water management and enhancing agricultural resilience. This study aims to analyze meteorological drought in the Damghan region using Standardized Precipitation Index (SPI) over a 30-year period. Selected for its simplicity and flexibility across the time scales, SPI enables assessment of drought severity and frequency. Monthly precipitation data from three meteorological stations, representing distinct regions (rain-fed agriculture, transitional, and ecologically sensitive arid zones), were analyzed to evaluate drought patterns at short-term (1- and 3-month), medium-term (6- and 12-month), and long-term (24- and 48-month) scales, providing a framework for drought monitoring and sustainable water policy.
Materials and Methods: Monthly precipitation data from three meteorological stations in the Damghan region, which reflect diverse land uses and microclimates, were collected from 1990 to 2020. Data quality was ensured through statistical tests, including normality (Shapiro-Wilk), homogeneity (Pettitt), and outlier detection (IQR method), with anomalies corrected via interpolation. The SPI was calculated at 1-, 3-, 6-, 12-, and 24-month scales using a gamma distribution fitted via maximum likelihood estimation, followed by transformation to a standard normal distribution to identify dry (SPI < -1) and wet (SPI > 1) periods. Analyses were conducted using R software to ensure computational accuracy. Spatial variability was assessed by comparing station results based on regional characteristics (topography, land use).
Results : SPI analysis revealed significant variability in drought patterns across the three stations, driven by microclimatic and land-use differences. The Damghan station, in a rain-fed agricultural area, exhibited frequent short-term droughts in late winter and spring, coinciding with critical planting phases for crops like wheat and barley, likely reducing yields and disrupting farming schedules. The Fooladmahale station, in a transitional zone, recorded autumn and winter droughts, decreasing soil moisture for cereals and pulses, and increasing irrigation needs. The Chahardeh-Damghan station, in a drier, ecologically fragile area, experienced spring and early summer droughts, leading to reduced vegetation cover, increased soil erosion, and land degradation. At medium-term scales (6 and 12 months), all stations showed persistent dry periods, straining surface and groundwater resources and challenging irrigated agriculture and rural water supply. Long-term (24-month) droughts, though less frequent, were severe, threatening groundwater-dependent ecosystems. The limited number of stations reduced spatial resolution, while the focus on precipitation excluded factors like temperature and evapotranspiration, limiting comprehensive drought analysis. Future studies should incorporate satellite data (e.g., TRMM, GPM), complementary indices like SPEI, and hydrological models (e.g., SWAT, CMIP6). Practical measures, such as farmer training, drip irrigation, and rainwater harvesting, are recommended.
Conclusion: Multi-scale SPI analysis confirmed Damghan's high vulnerability to meteorological droughts, with distinct impacts on agricultural, transitional, and arid zones, underscoring the need for region-specific water management. Advanced monitoring, integrated modeling, and climate adaptation strategies are crucial for sustaining water resources and agriculture. This study offers a framework for local policy-making.