ECOPERSIA
Volume:6 Issue: 2, Spring 2018

Aims: Groundwater, especially in comparison with surface water, is one of the most critical sources of water supplies in different parts of the world. Due to the increasing demand in various parts of agriculture, household, industry, etc., and also decreasing groundwater level in recent years in Hamadan province, it is necessary to estimate the carrying capacity of groundwater resources.
In this article, seven factors, having greater impacts on the carrying capacity of the region, were selected based on experts’ views during the 2001–2011 period. Furthermore, fuzzy comprehensive evaluation method using different membership functions (MF) was used to estimate the carrying capacity of groundwater resources.
Findings: By considering different numbers of MF, the results of this study pointed out that groundwater carrying capacity decreased throughout the 2001–2011 period. Moreover, by considering the rate of decline of water level, it is obvious that by the use of five member functions in comparison with other methods, the reduction level of groundwater resources is better observed. Hence, the process of recognition of reduction groundwater resources carrying capacity in Hamadan Province can be immediately done.
As a consequence, governments can make some proper and quick decisions and effective strategies to compensate the reduction and save implementation cost and time.

Aims: Nowadays, dangerous chemical pollutants by a numerous of natural and synthetic sources are produced and released to the environment. These pollutants have short-term and long-term effects on human health. The purpose of this paper is to examine the impact of climate parameters and instability indices on air pollution in Tehran-Iran.
To evaluate the impact of meteorological parameters and indices of stability and instability on sensitivity analysis in Tehran-Iran, the Sharif University monitoring station was selected for air sampling and analysis. Sampling was performed from March 2011 to July 2012 in Tehran.
Findings: Results of sensitivity analysis showed that average daily change of the concentration of pollutants throughout the year was very different and intensively influenced by meteorological parameters. Results showed that wind direction (WD) (82%) and relative humidity (32%) and temperature (20%) have the most influence on the concentration values of pollutants carbon monoxide (CO), particulate matter (PM10), and air quality index (AQI). The highest concentrations of CO occurred in summer and lowest in winter, and maximum concentration of PM10 was in autumn, and its lowest concentration was in spring. Results revealed that the lowest average of AQI occurred in the spring, while in autumn, winter, and summer have almost equal values, but in winter AQI has slightly higher values.
According to the results of this research in Sharif station Tehran, the WD has the highest impact percentage (82%) on the concentration of pollutants. The highest concentrations of CO occurred in summer, and maximum concentration of PM10 was in autumn.

Aims: The contamination of soils and groundwater by toxic, hazardous organic pollutants is a widespread environmental problem. The use of vegetation for the treatment of contaminated soils is an attractive and cost-effective alternative, especially for petroleum-contaminated soils.
Three species including Calotropis procera L., Stipagrostis plumosa, and Medicago sativa were selected.
To evaluate the abilities of S. plumosa, M. sativa, and C. procera in the degradation of petroleum hydrocarbons, a greenhouse study was conducted with two trial factors: (1) Urban waste compost and (2) biochar (each 0, 1, and 2%). At the end of the experiment, aerial and underground parts of the plants were collected, and some important soil properties and plant morphological characteristics were measured. The total amount of hydrocarbons was measured by gas chromatography, Flame Ionization type, Agilent 7890A model.
Findings: The results showed that the strongest hydrocarbon reduction by C. procera, S. plumosa, and M. sativa was 62.5%, 57.3%, and 53.5%, respectively. The results also demonstrated that control/biochar 2% had the highest/lowest (21922/14511 mg/kg) hydrocarbon level left in the soil. Therefore, biochar 1% or 2% is the best treatment for the remediation of petroleum-contaminated soils. C. procera L. is a good potential candidate to be cultivated for the phytoremediation of petroleum-contaminated soils.
Overall, using the amendment seedbed including biochar and urban waste compost treatments is suitable to promote phytoremediation of petroleum hydrocarbons. Biochar and urban waste compost provide optimal conditions for plant growth and at least help to promote the process phytoremediation. Regarding plant species diversity in Iran and petroleum contamination, application of phytoremediation may apply with effective and applied solution in soils contaminated.

Aims: Drought has become a main concern in Iran. The drought is posing a serious threat to life in Sistan and Baluchestan Province. This study aimed to evaluate the severity and extent of drought in Sistan and Baluchestan Province, Southeastern Iran.
Standardized precipitation index (SPI) and reconnaissance drought index (RDI) were used to determine the severity, duration, and extent of drought in Sistan and Baluchestan Province. Seven synoptic stations located across the province with data period of 2001–2012 were used in monthly timescale. DrinC software was used to calculate SPI and RDI indices. Drought zoning maps were generated using ArcGIS software.
Findings: Iranshahr and Saravan stations showed the most severe drought in 2003–2004 water year and Nikshahr station had the lowest drought severity in the same water year. The drought zoning maps indicated that the lowland areas and plains, especially in the southwestern part of the province and Iranshahr and Nikshahr stations, were vulnerable at the time of drought occurrence.
Both drought indices behaved similarly, but the RDI index was more sensitive in a specific climate condition due to using potential evapotranspiration of reference crop. It can be recommended that the RDI index can be used as an appropriate indicator for drought monitoring in Sistan and Baluchestan Province.

Aims: Greenhouse gas (GHG) emission estimates were made from agriculture sector in Jammu and Kashmir to assess the 2015 situation and future trends in emission which would help in formulating a policy for mitigation.
The Intergovernmental Panel on Climate Change (IPCC) tier-II methodology (IPCC, 1997) has been adopted for estimating methane (CH4) emissions from enteric fermentation in livestock and Tier-I methodology for other sectors of agriculture for GHG emission.
Findings: Agriculture in J and K accounted for a total GHG emission of 5.411 Tg of carbon dioxide (CO2)e in the year 2015. Source-wise, enteric fermentation was responsible for emittance of 160.233 Gg of CH4 and 1.399 Gg of nitrous oxide (N2O), manure management for 8.25 Gg of CH4 and 0.276 Gg of N2O, rice cultivation for 28.75 Gg of CH4, cultivated soils for 1.988 Gg of N2O, and residue burning for 0.405 Gg of CH4, 0.029 Gg of N2O, and 118.01 Gg of CO2.
Higher GHG emission from enteric fermentation was mainly due to higher population of livestock in the state. The most effective methods for reducing GHG emissions in the state would be to adjust the part of animal feed to decrease digestion time, using feed additives to reduce metabolic activity of rumen bacteria that produce CH4, and increase nitrogen-use efficiency by applying nitrogenous fertilizer or manure to crops as per crop needs and time of need.

Aims: In this study, variation in annual and seasonal rainfalls in Southeastern Anatolian Project (GAP) area was analyzed using the non-parametric and parametric approaches.
According to the aim of the study, the data sets of the seasonal and annual timescales, based on monthly rainfalls in the GAP area, including 9 rain gauges operated by Turkish State Meteorological Service, were considered in the study. Mann–Kendall (MK) and unit root test to detect the direction of an available monotonic trend in any given data were used while obtaining the magnitude of the variation with Theil–Sen slope estimator.
Findings: Based on the MK test, decreasing trend in four of the seven different time scales was observed, whereas there was an upward trend in the only two (P-III and P-IV) of the all time scales while none of the stations in the P-II period showed a monotonic trend. However, the parametric unit root test detected the existence of variation in the period III for Sanliurfa station and the period V for Sirnak station.
The percentage change calculated by considering the MK varied between 19 and 57%.

Aims: The information on species richness (SR) can be used to help establish conservation strategies or to predict future patterns of biodiversity under global change. The aim of the present study was the prediction of spatial distribution of plant species richness in the Valdarreh Rangelands, Mazandaran, Iran by Macroecological Modelling (MEM) and Stacked Species Distribution Models (S-SDM).
This experimental study was carried out in the Valdarreh rangelands. In the present study compared the direct, macroecological approach for modeling species richness with the more recent approach of stacking predictions from individual species distributions. Both approaches performed in reproducing observed patterns of species richness along an elevation gradient were evaluated. MEM was implemented by relating the species counts to environmental predictors with statistical models, assuming a Poisson distribution. S-SDM was implemented by modelling each species distribution individually, assuming a binomial distribution.
Findings: The direct MEM approach yielded nearly unbiased predictions centered around the observed mean values, but with a lower correlation between predictions and observations, than that achieved by The S-SDM approaches. This method also cannot provide any information on species identity and, thus community composition. Predicted SR by S-SDM was correlated by a Spearman p of 0.76 with the observed SR. The MEM-predicted SR achieved a Spearman rank correlation of 0.32 with S-SDM. The species richness along the elevational gradient for MEM and S-SDM were 0.21 and 0.82, respectively.
MEM and S-SDM have complementary strengths and both can be used in combination to obtain better species richness predictions.