The new generation of weather observatory satellites, namely Global Precipitation Measurement (GPM) constellation satellites, is the lead observatory of the 10 highly advanced earth orbiting weather research satellites. Indeed, GPM is the first satellite that has been designed to measure light rain and snowfall, in addition to heavy tropical rainfall. This work compares the final run of the Integrated Multi-satellitE Retrievals for GPM (IMERG) product, the post real time of TRMM and Multi-satellite Precipitation Analysis (TMPA-3B42) and the Era-Interim product from the European Centre for Medium Range Weather Forecasts (ECMWF) against the Iran Meteorological Organization (IMO) daily precipitation measured by the synoptic rain-gauges over four regions with different topography and climate conditions in Iran. Assessment is implemented for a one-year period from March 2014 to February 2015. Overall, in daily scale the results reveal that all three products lead to underestimation but IMERG performs better than other products and underestimates precipitation slightly in all four regions. Based on monthly and seasonal scale, in Guilan all products, in Bushehr and Kermanshah ERA-Interim and in Tehran IMERG and ERA-Interim tend to underestimate. The correlation coefficient between IMERG and the rain-gauge data in daily scale is far superior to that of Era-Interim and TMPA-3B42. On the basis of daily timescale of bias in comparison with the ground data, the IMERG product far outperforms ERA-Interim and 3B42 products. According to the categorical verification technique in this study, IMERG yields better results for detection of precipitation events on the basis of Probability of Detection (POD), Critical Success Index (CSI) and False Alarm Ratio (FAR) in those areas with stratiform and orographic precipitation, such as Tehran and Kermanshah, compared with other satellite/model data sets. In particular, for heavy precipitation (>15 mm/day), IMERG is superior to the other products in all study areas and could be used in future for meteorological and hydrological models, etc.

This paper presents the first groundwater‒energy‒food (GEF) nexus study of Iran’s agronomic crops based on national and provincial datasets and firsthand estimates of agricultural groundwater withdrawal. We use agronomic crop production, water withdrawal, and energy consumption data to estimate groundwater withdrawal from electric-powered irrigation wells and examine agronomic productivity in Iran’s 31 provinces through the lens of GEF nexus. The ex-post GEF analysis sheds light on some of the root causes of the nation’s worsening water shortage problems. Access to highly subsidized water (surface water and groundwater) and energy has been the backbone of agricultural expansion policies in Iran, supporting employment in agrarian communities. Consequently, water use for agronomic crop production has greatly overshot the renewable water supply capacity of the country, making water bankruptcy a serious national security threat. Significant groundwater table decline across the country and increasing energy consumption underscore dysfunctional feedback relations between agricultural water and energy price and groundwater withdrawal in an inefficient agronomic sector. Thus, it is essential to implement holistic policy reforms aimed at reducing agricultural water consumption to alleviate the looming water bankruptcy threats, which can lead to the loss of numerous agricultural jobs in the years to come.