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This study analysed spatio-temporal fluctuations in rainfall to assess drought and wet spells in Khyber Pakhtunkhwa, Pakistan. Temporal changes in rainfall were assessed using a linear regression method, while aridity conditions at each meteorological station were measured using the United Nations Environment Programme climate aridity index. In this study, drought and wet spell patterns were identified using the Standardized Precipitation Evapotranspiration Index (SPEI). The Spearman’s Rho (SR) test was applied to find trends in the temporal 1-month and 12-month SPEI data. Balakot, Dir, Kakul, Kalam, Malam Jabba, Parachinar, Patan and Saidu were humid whereas Cherat and Timergara were sub-humid meteorological stations while Bannu, Chitral, Drosh and Peshawar were semi-arid and D.I. Khan was found to be the only arid meteorological station in the study area. The regression results revealed that the amount of rainfall is decreasing at Balakot, Kakul and Dir, while in the southern part of the province the amount of rainfall is increasing, such as in Parachinar and Cherat. The SPEI results revealed distinct drought spells in 1971–1974, 1984–1989, 1998–2004 and recently in 2017–2018, in almost all met-stations results. The SR results indicated a significant wet trend at met-station Parachinar, located in the west, while a significant drying trend has been noted at Balakot in the north-eastern part of the study area. Detailed knowledge about rainfall variability can provide a foundation for the planning and use of water resources.

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Abstract. This study assessing the landslide susceptibility using Weight of Evidence (WoE) and Frequency Ratio (FR) model in Shahpur valley, situated in the eastern Hindu Kush. Here, landslide is a recurrent phenomenon that disrupts natural environment and cause huge property damages as well as incurs human losses every year. These damages are expected to increase due to high rate of deforestation in the region, population growth, agricultural expansion and infrastructural development on the fragile slopes. Initially, landslide inventory map was prepared from SPOT5 satellite image and were verified from frequent visits in the field. Seven landslide contributing factors including surface geology, fault lines, slope aspect and gradient, land use, proximity to roads and stream were selected. To analyze the relationship of landslide occurrence with these causative factors, WoE and FR models were used. Based on WoE and FR model landslide susceptibility zonation maps were prepared and were reclassified into very low to very high landslide susceptible zones. Finally, the resultant maps of landslide susceptibility were authenticated using success rate curve and prediction rate curve approach to validate the models.