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This paper uses the Budyko method to investigate mean annual streamflow changes, due to climate variation and human influence, in the important Karkheh River Basin in western Iran. To validate the results, hydrological modelling (HBV model) and Landsat 5 Thematic Mapper (TM) images were used for the study period between 1980 and 2012. The recently developed DBEST (Detecting Breakpoints and Estimating Segments in Trend) method identified an abrupt negative change in the streamflow trend in 1994-5. The results show that the observed streamflow decrease in the Karkheh River is associated with both climate variation and human influence. The combination of increased irrigated area (from 9 to 19 % of the total basin area), reduction of forests (from 11 to 3 %), and decreasing annual precipitation has significantly reduced streamflow in the basin. Moreover, the results show that the streamflow reduction in the Karkheh Basin is more sensitive to the change in precipitation than temperature. [ABSTRACT FROM AUTHOR]

Accurate estimation of precipitation is crucial for fundamental input to various hydrometeorological applications. Ground-based precipitation data suffer limitations associated with spatial resolution and coverage; hence, satellite precipitation products can be used to complement traditional rain gauge systems. However, the satellite precipitation data need to be validated before extensive use in the applications. Hence, we conducted a thorough validation of the Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals (IMERG) product for all of Iran. The study focused on investigating the performance of daily and monthly GPM IMERG (early, late, final, and monthly) products by comparing them with ground-based precipitation data at synoptic stations throughout the country (2014–2017). The spatial and temporal performance of the GPM IMERG was evaluated using eight statistical criteria considering the rainfall index at the country level. The rainfall detection ability index (POD) showed that the best IMERG product's performance is for the spring season while the false alarm ratio (FAR) index indicated the inferior performance of the IMERG products for the summer season. The performance of the products generally increased from IMERG-Early to –Final according to the relative bias (rBIAS) results while, based on the quantile-quantile (Q-Q) plots, the IMERG-Final could not be suggested for the applications relying on extreme rainfall estimates compared to IMERG-Early and -Late. The results in this paper improve the understanding of IMERG product's performance and open a door to future studies regarding hydrometeorological applications of these products in Iran. [ABSTRACT FROM AUTHOR]