جستجوی مقالات مرتبط با کلیدواژه « مدیریت منابع » در نشریات گروه « آب و خاک »

Although the exploitation of mineral resources is very useful for the country, it has a negative impact on human and plant life with its destructive effects. These destructive effects appear as pollution in the soil, which can lead to the imbalance of ecosystems and ultimately endanger human health. In addition, economic development and the expansion of industrial areas, especially coal mining mines, cause heavy metal contamination of the soil to become more severe and cause the destruction of soil resources and the deterioration of ecosystems in different regions of the world. The present study was conducted to investigate the contamination of the two elements Pb and Zn in the surface soil of the Komarzd mining area in Mazandaran province (Iran) due to coal mining.

Komarzd mines in Mazandaran province are one of the largest and oldest coal-producing areas in the central Alborz coal field. Komarzd mines are located 48 km from the southern district of Qaemshahr and 25 km from Alasht. Four indices, including CF, mCF, RI, and Igeo were calculated for 110 samples from surface soil prepared at a depth of 5-15 cm. After separating the rubble, the collected soils were kept in closed plastic bags with a unique code, and a GPS device recorded their location. The samples prepared in a dry environment were transferred to the laboratory. The ICP-MS method at 75 microns was used to analyze and measure the concentration of heavy elements in the collected samples. According to the presence of different elements measured in the region's soil and the compounds in it, two metals Zn and Pb were selected for evaluation and analysis. Sampling was randomly selected based on saved points and drilling tunnels. PCA statistical test is a type of multivariate analysis widely used in sediment, water, and soil pollution studies. Varimax Rotation is one of the most common types of PCA tests to interpret the results and contamination components of the method. This statistical method can be calculated using R and SPSS softwares.

The results showed that the ordinary kriging model is the most suitable model to show the region's concentration distribution of the two metals, PB and Zn. Also, the statistical status of the elements showed that the lowest amount of Zn for the Igeo index is equal to -0.53 and the highest value for the CF index is equal to 0.72. The amount of Pb concentration measured based on Igeo, CF, mCF, and RI indices equals 0.08, 1.03, and 213 mg/kg, respectively (RI<CF<Igeo). The results of the CF and mCF showed that the region has a low or moderate pollution status in terms of the concentration of the two determining elements; in other words, the value of this factor for Zn is less than 1 (CF<1) and the amount for Pb is (3 > CF> 1). The Igeo index showed that Zn with a concentration lower than zero is not polluted, but Pb with a value (0< Igo <1) has a non-polluted to slightly polluted state. The RI also showed that the concentration of the two elements is less than 150 mg/kg, so this index is also in the low-risk category of contamination (RI ≤ 150). By evaluating the graphs obtained from the PCA analysis, it was found that the two elements Zn and Pb in the correlation analysis graph have a good correlation and distribution, and the changes in the two axes show 47.9% and 24%, respectively, for the Igeo. This indicates the presence of environmental factors in the distribution of this element in the environment. The CF also showed that their distribution in region three negatively correlated with environmental factors. Its value for the two axes is 32.5 and 21.9 %, respectively. The correlation of the Zn element is less than -0.5, but the Pb element is more than -0.5. In general, the value of this variable is 8 and 20, respectively, based on the diagram of two minimum and maximum values. The mCF and RI indices showed that environmental factors influence the distribution of the two elements PB and Zn, and among the two elements, the distribution of the Pb element in the mCF and RI, results of 32.8 and 34.4 has the most influence from the distribution of the drilling tunnel and had environmental factors and has a lower correlation than Zn. The effect percentage of these two elements is 32.8 and 23.2%, respectively, and the two elements Zn and Pb have a good correlation and distribution with environmental changes and human factors.

According to the measurements and the results of four indices, the area is uncontaminated or has low contamination in terms of the concentration of two elements, PB and Zn. Therefore, mineral tailings and coal exploitation do not significantly affect the distribution of the mentioned elements. To improve the research results, other indices can be used to determine the role of environmental factors. Also, considering the agricultural lands and water resources of Talar River, it is better to use other elements that directly affect human health and analyze the region's conditions in terms of environmental pollution to achieve better results and accuracy. One of the main disadvantages of measuring the sources of pollution is the many problems in laboratory work and the preparation of laboratory materials. Still, with this research, it is possible to determine the existing doubts in the field of soil pollution for residents and show the impact of mining on the spread of pollutants. A suggestion to improve this research is to consider elements other than Pb and Zn in different environments such as water sources; In general, for a more detailed investigation, other elements that play a role in human health should be investigated.

The study of changes in precipitation and temperature components provides the basic information needed to assess the frequency and severity of climatic and hydrological processes. Therefore, the present study investigates the temporal changes of precipitation and temperature at different time scales in Karkheh Watershed. The present results are applicable in regional planning and decision makings.

Karkheh Watershed with an area of 51337 Km2 located in the west and southwest of Iran includes Kermanshah, Hamedan, Kurdistan, Ilam, Lorestan and Khuzestan provinces. The average annual rainfall in Karkheh Watershed varies from 150 mm in the southern regions to more than 1000 mm in the eastern regions. To do this study, daily minimum and maximum precipitation, temperature and sunny hours of six synoptic stations of Ahvaz, Dezful, Hamedan, Khorramabad, Kermanshah and Sanandaj in Karkheh Watershed with the statistical period 1980-2010 were used. The trend of changes in time series of precipitation and temperature was evaluated using Mann-Kendall statistical test and age estimator.

The results show that in the case of precipitation, the changes in most stations are decreasing and without a significant trend, and in a limited number of stations it has a significant decreasing trend, which is generally related to the cold months of the year (-0.09 and -0.07 at the station). Khorramabad and Sanandaj in February). The most changes in precipitation trend were observed in annual time series (-0.02 in Sanandaj Station). Thus, in most stations, a significant decrease in precipitation is observed. In all time series, the minimum and maximum temperatures in most stations have an increasing trend. The rate of this increasing trend is higher at minimum temperature (slope of changes 2.77 and 2.75 in Sanandaj and Ahvaz stations, respectively).

Analysis of daily, monthly, seasonal and annual trends of precipitation and minimum and maximum temperatures in the period 1980-2010 are very important due to their high impact on the hydrological response of watersheds as well as environmental issues. Also, the role of climate change and its effects on the trend of marginal phenomena in different regions can have many consequences. The present study was conducted to investigate the trend of precipitation and temperature in different time series. The results of the analysis of the monthly rainfall trend in the study period showed a decreasing and insignificant trend in most stations and in most months. Also, in most of the study stations, the monthly minimum temperature, with the exception of January, November and December, has an increasing trend and indicates that the monthly minimum temperature in the Karkheh Watershed has been increasing in recent years.

Today, watersheds are severely affected by natural and man-made stresses, and their ability to recover and adapt to altered conditions depends on the resilience of watersheds. Therefore, due to the importance of this issue and the necessity to explain  management models in  order to promote resilience in the country's watersheds, the present paper aims to analyze the concept, application, and methods of hydrological resilience assessment as one of the resilience dimensions in comprehensive watershed management. Studies in this field are very limited worldwide but have an upward trend. Accordingly, the methods used to evaluate hydrological resilience have so far been limited to the use of simple compilation methods such as determining the arithmetic mean of some important hydrological indicators, using the Budyko curve and the Convex model. Budyko's curve analysis was mostly based on rainfall, evapotranspiration, and runoff production. But the convex model is used by considering the failure thresholds of hydrological indicators and establishing a relation between the process of long-term changes and the failure thresholds of indicators. The indicators used are multitude and have different applications depending on the hydrological conditions of each watershed. Among the most important of them can be the ratio of drought index to runoff, temporal trend and frequency of low and high water flow, change in annual water yield, groundwater level, surface runoff intensity, river enrichment from nutrients, and heavy metals, forest degradation percentage, soil erosion, sediment yield, and saline water levels are all the result of the interaction of other influential environmental factors, such as climatic, ecological, economic, biophysical and social.

The yield of rainfed crops depends on climatic parameters, plant genetic characteristics, soil type and agricultural operations (Hosaini et al., 2007). Among these factors, climatic variables have a stochastic nature. Therefore, it is important to investigate the effect of the mentioned parameters on the variability of the crop plants yield. The correct identification of the climatic conditions will help farmers to timely sow and supply plant requirement during the growing season (Azizi and Yarahmadi, 2003). Also, predicting the yield of strategic plants (such as wheat) will be possible via identify and quantify the effects of the important climatic variables on crop production in each region (Bazgeer and Kamali, 2008). Kordestan is one of the most important rainfed agricultural regions in Iran. Bijar, with a production about 123,000 tons of rainfed wheat per year, is one of the most important regions to product rainfed wheat in Kurdistan. The maximum and minimum yield of rainfed wheat in Bijar during a 25-year period has been between 1380 and 213 (kg/ha), respectively (Anonymous, 2015). This large range of yield changes has had a significant impact on the region's economy. The present research was carried out with the aim of identifying important climatic factors in Bijar region and developing a model for estimating rainfed wheat yield based on these factors. The results of this research can be useful in developing quantitative and qualitative agricultural products and sustainable use of resources.

This study shows how multiobjective programming, compromise programming and filtering techniques could be used to manage scarce resources. Data were collected from a sample of 109 Rafsanjan pistachio producers. The aim of the program was to make a compromise between the objectives of profit maximization, the maximization of the area under pistachio gardens and also maximization of the groundwater use. The multiobjective programming approach and filtering techniques were used to find the efficient set among these objectives. A compromise between the objectives was established by the compromise programming method. Although none of the above three objectives achieved completely in the compromise solution, it became nearer to the ideal point on the assumption that the importance of three objectives was the same. By omitting this assumption and considering the objective weights based on decision maker preferences, the compromise solution might become nearer to the ideal point.