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In this study, the aridity index (AI) based on gridded climate data was validated for defining aridity and classifying aridity zones in Iraq through comparison with the results obtained by the station-based aridity index. Gauge-based gridded climate data taken from Climatic Research Unit Timeseries (CRU TS) were used to determine the annual value of four aridity indices (Lang, De Martonne, Ernic and UNEP AI) over the period 1998-2011. The results showed that the aridity distribution maps derived using grid-based aridity indices were reasonably close to those found using station-based ones. The four aridity indices properly identified similar aridity (dryness) classifications in both the station-based and grid-based aridity maps. The area percentage of each aridity class predicted by grid-based AIs was also compared with that obtained by the station-based AIs. The results showed that the variances between the area percentages predicted by grid-based AIs and those estimated using station-based AIs are fairly slight. The Lang AI exhibited the least variance (0.4%) while the De Martonne AI had the biggest variance (-4.8%). Despite these minor variances, it is however possible to conclude that the grid-based aridity index classified the aridity zones of Iraq as properly as the station-based aridity index did. [ABSTRACT FROM AUTHOR]

High spatial and temporal resolution remote sensing data are becoming readily available. This has made the use of remote sensing to monitor and quantify spatiotemporal changes in surface waters feasible and efficient. In this paper, remote sensing techniques based on spectral indices were used to assess the changes in submerged areas and water storage in the Hawizeh marsh (south of Iraq) during the 2019 flood. Two water indices, the Normalized Difference Water Index (NDWI) and Normalized Difference Moisture Index (NDMI), were used for this purpose. Water indices have been frequently utilized to detect water bodies because of their particular spectral properties in the visible and infrared spectrum. Non-measured flood-related flows into the marsh have also been estimated by applying the water balance approach. The accuracy assessment of the water areas extracted by the remote sensing indices showed an acceptable degree of reliability, which reflected positively on the water inflow calculations. As the Hawizeh is a transboundary marsh shared by Iraq and Iran, remote sensing techniques allowed for the estimation of difficult-to-measure inflows from the Iranian side. The results of the water balance revealed that the inflows from the Iranian side to the marsh during the 5 months of the flood made up approximately 41.2% of the total water volume entering the marsh. The study demonstrated the feasibility of using uncomplicated water extraction methods that depend on remote sensing data to monitor hydrological changes in the Hawizeh wetland that lack sufficient data. [ABSTRACT FROM AUTHOR]

Type 1 diabetes mellitus (T1DM) is one of the most common endocrine diseases of childhood. Its incidence is rising world-wide, with reported increases of 2-5 percent per year in the Middle East. The incidence and clinical presentation of T1DM markedly varies among countries, and major efforts are ongoing to extensively characterize the epidemiology of the disease. This study describes the demographics and clinical pattern of Type 1 diabetes among children referred to ALHasan specialized Diabetes center in Karbala city, Iraq. A retrospective study of medical records of children with diabetes type 1 (T1DM), who were referred to ALHasan specialized tertiary center for diabetes and endocrine disorders in Imam Hussein medical city, Karbala. The study included a total of 405 medical records, registered from 2014 to 2018. The study included 405 medical records of which 52.8% were females and 47.2% were males. Hence, Female to male ratio was 2:1.95. The mean age of incidence was 12.69 (ST±4) Family history was positive in (39%) of the cases. Most of the patients (69.9%) were from urban areas, while those from rural areas constitute (30.1 %). The seasonal variation peak onset was in the spring (32.1%) and Autumn (26.17). Classical symptoms represent (73.3%) of the cases while 26.7% of the patients were diabetic ketoacidosis as a clinical onset. Classical clinical presentation is the most common pattern of T1DM in Karbala city with slight female predominance and spring peak of onset. The data produced by this study provide a baseline for future studies to describe the changes in the epidemiology of T1DM in Karbala city using better method electronic medical records that gives attention to other variables like socioeconomic status, BMI and providing a vitamin D level measure in the center lab as routine. [ABSTRACT FROM AUTHOR]