Geochemical and Hydrothermal Alteration Patterns of the Abrisham-Rud Porphyry Copper District, Semnan Province, Iran

In this study, the zonality method has been used to separate geochemical anomalies and to calculate erosional levels in the regional scale for porphyry-Cu deposit, Abrisham-Rud (Semnan province, East of Iran). In geochemical maps of multiplicative haloes, the co-existence of both the supra-ore elements and sub-ore elements local maxima implied blind mineralization in the northwest of the study area. Moreover, considering the calculated zonality indices and two previously presented geochemical models, E and NW of the study have been introduced as ZDM and BM, respectively. For comparison, the geological layer has been created by combining rock units, faults, and alterations utilizing the K-nearest neighbor (KNN) algorithm. The rock units and faults have been identified from the geological map; moreover, alterations have been detected by using remote sensing and ASTER images. In the geological layer map related to E of the study area, many parts have been detected as high potential areas; in addition, both geochemical and geological layer maps only confirmed each other at the south of this area and suggested this part as high potential mineralization. Therefore, high potential areas in the geological layer map could be related to the mineralization or not. Due to the incapability of the geological layer in identifying erosional levels, mineralogy investigation could be used to recognize this level; however, because of the high cost, mineralogy is not recommended for application on a regional scale. The findings demonstrated that the zonality method has successfully distinguished geochemical anomalies including BM and ZDM without dependent on alteration and was able to predict erosional levels. Therefore, this method is more powerful than the geological layer.

Numerical simulation of groundwater in an unconfined aquifer with a novel hybrid model (case study: Birjand Aquifer, Iran)

In recent decades, due to the population growth and low precipitation, the overexploitation of ground water resources has become an important issue. To ensure a sustainable scheme for these resources, understanding the behavior of the aquifers is a key step. This study takes a numerical modeling approach to investigate the behavior of an unconfined aquifer in an arid area located in the east of Iran. A novel hybrid model is proposed that couples the numerical modeling to a data assimilation model to remove the uncertainty in the hydrodynamic parameters of the aquifer including the hydraulic conductivity coefficients and specific yields. The uncertainty that exists in these parameters results in unreliability of the head values acquired from the models. Meshless local Petrov-Galerkin (MLPG) is used as the numerical model, and particle filter (PF) is our data assimilation model. These models are implemented in the MATLAB software. We have calibrated and validated our PF-MLPG model by the observation head data from the piezometers. The RMSE in head values for our model and other commonly used numerical models in the literature including the finite difference method and MPLG are calculated as 0.166, 1.197 and 0.757 m, respectively. This fact shows the necessity of using this method in each aquifer.

Water resources availability under different climate change scenarios in South East of Iran

The comprehensive large-scale assessment of future available water resources is crucial for food security in countries dealing with water shortages like Iran. Kerman province, located in the south east of Iran, is an agricultural hub and has vital importance for food security. This study attempts to project the impact of climate change on available water resources of this province and then, by defining different scenarios, to determine the amount of necessary reduction in cultivation areas to achieve water balance over the province. The GFDL-ESM2M climate change model, RCP scenarios, and the CCT (Climate Change Toolkit) were used to project changes in climatic variables, and the Soil and Water Assessment Tool (SWAT) was used for hydrological simulation. The future period for which forecasts are made is 2020–2050. Based on the coefficient of determination (R2) and Nash–Sutcliffe coefficient, the CCT demonstrates good performance in data downscaling. The results show that under all climate change scenarios, most parts of the province are likely to experience an increase in precipitation yet to achieve water balance a 10% decrease in the cultivation area is necessary under the RCP8.5 scenario. The results of the SWAT model show that green water storage in central and western parts of the province is higher than that in other parts.

Nutrition assessment and geriatric associated conditions among free living elderly people in Birjand, East of Iran: a cross-sectional study

Background Few data are available on the nutritional status of Iranian geriatric population. The present study aimed to determine the nutritional status of older adults’ population in Birjand, East of Iran. Methods The community-based cohort study was performed on older adults population (60 years and older) living in urban and rural areas of Birjand. The mini nutritional assessment (MNA) questionnaire was used to assess nutritional status. Anthropometric and biochemical evaluation were also performed for all of the participants. Results A total of 1417 geriatric person were enrolled in this study, which, most of them were female (51.9 %). According to MNA tool, most of the participants (73.3 %) had normal nutrition (MNA score ≥ 24). Malnourished (MNA score < 17) and at high risk of malnutrition (MNA score: 17- 23.5) were constituted 0.9 % and 25.8 % of the participants, respectively. Marital status, occupation, period of education and family member were associated with nutritional status. Multiple logistic regression showed that with increase of body mass index (BMI) (OR = 0.96), education years (OR = 0.95), hemoglobin (OR = 0.86) and lymphocyte (OR = 0.98), the odds of malnutrition decreased, but with increase of age the odds (1.03) of malnutrition is also elevated. Conclusions MNA could successfully forecast the risk of malnutrition and malnourished people. Sociodemographic factors are associated with the nutritional status.