Abstract
Drought monitoring is a complicated issue as it requires multiple meteorological variables to monitor and anticipate drought accurately. Therefore, developing a method that enables researchers, data scientists, and planners to comprehend drought mitigation policies more accurately is essential. In this research, based on the concepts behind the calculation of the Standardized Precipitation Evapotranspiration Index (SPEI), a new drought index is proposed for regional drought monitoring: the Modified Standardized Precipitation Evapotranspiration Index (MSPEI). The potential of the proposed index is based on the estimation of Reference Evapotranspiration (ET
o
). Therefore, the Modified Hargreaves-Samani (MHS) equation based on fuzzy logic calibration is used to estimate ET
o
. The proposed index is validated on ten meteorological stations in Pakistan at a one-month time scale. Afterward, based on the Pearson correlation, the performance of the proposed index is compared with the commonly used drought index (SPEI). Results showed a significant correlation (r > 0.7) between the quantitative values of MSPEI and SPEI for all ten stations. Moreover, a modified Tjostheims coefficient is used to estimate and test the spatial correlation between SPEI and MSPEI for different drought classes. According to our findings, the association between the SW, ND, ED, EW, MW, and SD patterns of MSPEI and SPI is 0.74, 0.834, 0.673, 0.592, 0.393, and 0.434, respectively. Meanwhile, considering the significance of future drought trend detection, this research is further extended to detect the future trend of MSPEI by using the Hurst index. In accordance with the results, Bahawalnagar, Sialkot, Lahore, Kotli, and Gilgit all have HI values greater than 0.5 (0.63, 0.58, 0.56, 0.55, and 0.53, respectively). In contrast, Muzaffarabad, Skardu, and Jhelum have HI values 0.47, 0.45 and 0.38, respectively; however, HI values of 0.5 are observed at Dera Ismail Khan (DIK) and Islamabad. Therefore, this research provides a basis for developing and enhancing drought hazard characterization, encouraging researchers and policymakers to monitor and forecast regional droughts using a more accurate drought index.