نشریه انسان و محیط زیست
سال پانزدهم شماره 3 (پیاپی 42، پاییز 1396)

Given the importance of ground water for drinking and agriculture sector, simulation and forecasting changes its quality is an increasing human needs. In this study, the modeling of water quality parameters TDS and EC based on other chemical components of the major anions and cations, SAR and pH have been carried out. In addition to modeling the sodium adsorption ratio as the dependent variable parameters latitude, electrical conductivity, total dissolved elements and pH values were used as independent variables. The neural network to predict Marquardt Levenberg- groundwater quality parameters were selected. Results showed that high performance neural network to predict the groundwater quality parameters. High levels of correlation coefficient obtained between the values of parameters modeled closely reflects anticipated the measured data and the ability and accuracy of the relationships between input variables with output. Coefficient of determination of all three elements were modeled in three phases: training, validation and testing is over 90 percent Which indicate acceptable accuracy and good learning neural network and efficient network using the learning algorithm and data provided to the network. The results of great importance for the planning and integrated management of water resources and conservation and better utilization of it is important in the study area.

Performance evaluation is a process by which employees are studied and assessed officially at determined intervals. Identifying distinguished employees and giving them awards and thus creating incentives for them to improve their performance is among the main reasons for evaluating performance. This research intended to identify dimensions and attributes on evaluating employees of Environmental Offices using the BSC approach on performance evaluation, weighting them by the fuzzy analytic network process (FANP), and then ranking Offices employing a fuzzy TOPSIS technique. The statistical community was made up of 500 senior specialists and managers of Environmental Offices in Alborz, Tehran, and Esfahan Provinces. Using Cochran’s sample size formula, 217 employees constituted the sample volume. The attributes used on employee performance were first identified for the employees and managers of Environmental Offices in the financial, customer, internal business process, and learning and growth dimensions from the literature on the subject and from the views of the experts. The analytic network process technique was then employed for determining the dimensions, weighting the attributes, and measuring the degree of importance of each one. Following that, the TOPSIS technique was used to study three Offices with respect to the performance of the specialists and the managers. Results of weighting dimensions of performance evaluation of the employees in the Environmental Offices employing the analytic network process technique showed that the customer dimension ranked first in importance with the financial, internal business process, and learning and growth dimensions ranking second to fourth, respectively. Finally, considering the performance of each Office determined by using the fuzzy TOPSIS technique, suggestions were made to improve performance of Environmental Offices.

Water resource evaluation is considered as one of the fundamental steps in water resource management. DPSIR framework assists water resource decision makers with evaluating main reasons led to current conditions to fundamentally address related problems.The DPSIR analytical framework is not new but developed from the pioneering work by the Organization for Economic Cooperation and Development (OECD) in the 1980s, and was published in the early 1990s. In this study, based on DPSIR framework, a conceptual model for evaluating current water resource condition in Latiyan dam catchment is proposed to integrate environmental and social-economic indexes. Finally, after assessing the Latiyan dam catchment’s water resource condition, appropriate responses are suggested to tackle water resource condition in the region. These responses will remove or reduce the undesirable effects of natural and human reasons on water resources. The results show that increasing in Tehran’s annual average of daily temperature by 1.50c during past 50 years as well as Tehran’s population growth of more than 11 times in the same period results in falling Tehran’s groundwater surface elevation that according to changes’ trend in climate change and water quality parameters, the groundwater surface decline is more of human driving force

Water pollution is chemical, biological, microbic pollution, and pollution by waste materials in lakes, rivers, oceans and underground waters. Pollutants that cause water pollution include a wide range of chemical materials, pathogens, sensory and physical changes like increase in temperature and changes in color. Water pollution, whether biological, that is due to the existence of pathogenic microbes, or chemical, that is due to the existence of polluting chemical materials, causes many illnesses and several disorders to individual or public health. Therefore, the main purpose of this article investigation is the impact of water pollution on death rate and Health Expenditure as indicators of health economics in a the selected European countries. This article is an applied research, causal and inferential research by methodology.
The results of the estimation models using Fixed Effect shows that water pollution has a significant and positive effect on death rate and Health Expenditure as indicators of health economics in the selected countries. The scarcity of water resources and their pollution is an alarm call indicating the shortage of healthy water resources in the future. To counter this crisis, water consumption management is the best option

Due to limitations and potential of land ecosystems, ecological integrity and interactions between the various components of land show vulnerable because of the escalation of irrational human activities. So, it is essential that different environmental aspects such as landscape aesthetic quality be considered in landscape management and planning in order to preserve integrity and balance of ecosystems as well as to achieve sustainable development. Also, it seems necessary to identify and study the important elements affecting quality and aesthetic aspects of landscape in visual quality assessment process. In this study, considering the review and identification of important elements in visual quality assessment of landscape, aesthetic criteria and characteristics were examined based on scientific studies and existing documents. After that, the important and effective elements identified about the various ecological, socio-economic and aesthetic aspects in the visual quality assessment of urban, forest, agriculture, coastal, desert and mountain landscapes. The qualitative analysis was performed in relation to each of the landscapes according to the identified elements and components.
This study showed that understanding and awareness of the effective environmental and visual elements and their properties can be helpful in visual quality assessment of different landscape types and it will facilitate its process

One of the most important issues of urban and regional development throughout the world is land use and planning for its sustainability. Nowadays, organization of land use and understanding of land cover situation is a great importance due to the increasing development of cities and imbalance in the spatial distribution of users. Remote sensing techniques are the best application to extract the land use map. So in this study, for preparing the map of land use a Supervised Classification Technique and the Maximum Likelihood Classification Algorithm were used. The study area is located in the Roudbar-e Qasran region of Shemiranat county and in this research the Landsat-8 satellite images (June) of the OLI sensor in 2015 was used. The results showed that the barren lands, rangelands, man-made and farms comprise the largest area of use, respectively. To evaluate the accuracy of the classifications carried out, the total accuracy and Kappa coefficient were determined by 97.74% and 0.92%, respectively, representing the high resolution of Landsat images to map the land use.

Parks and urban green spaces are a part of the city that has natural or artificial vegetation. These areas have various functions, including conservation of biodiversity, improvement of air quality, leisure and recreation and also aesthetic effects. Birds are the dominant animal groups of green spaces that an effective communication can be seen between them. Parks and urban green spaces are an important factor in attracting various species of birds. Management of parks and green spaces and recreational sites is an aspect of biodiversity management in urban habitats. The present study investigates the human use of these areas for recreation and leisure and the effects of these activities on its biodiversity and then present management solutions for this problems. Two important approaches of the study to birds in parks and urban green spaces are investigation of the indices of bird species richness and the shape and size of parks and green spaces in relation to these indicators. The results of studies pointed to the vital importance of the protection of these areas and also the effect of birds in attracting visitors. In fact, the problems in the field of protection of birds in urban green spaces requires management approaches for increasing the richness of bird species and visitors’ satisfaction. These approaches include development of bird watching stations, preparing and distributing posters and leaflets, organizing workshops on the birds and urban green spaces for children and students.

The growing trend of forest fires necessitates presentation of a solution to predict and control them. Fire occurrence modeling with attention to all effective factors, is a proper solution to predict the fire occurrence in the forests because many factors affect on forest fire occurrence. This study has been done to investigate the different methods of fire modeling and fire risk assessment in forests of the world and Iran. Investigation of the researches implemented in Iran shows that the studies about fire risk potential evaluation in Iran have been limited and AHP has been used to weigh the effective factors in forest fire in most of these studies. Conclusion of researches implemented in the world shows that vegetation type, slope, aspect, distance from roads, topography and land use, have been the most effective factors in modeling of fire occurrence and integration of digital layers has often been based on a hierarchy and a risk coefficient in fire occurrence. The past actual fires map has been compared with the fire risk map to assess the accuracy of models used in provision of fire risk potential map. Logistic regression and decision-making tree algorithm have been used to select the effective variables in fire and to model the fire risk in some new studies. Integration of fuzzy inference system and neural network, neural intelligence and support vector machine has been used to predict the future fires in some advanced methods. Multi-criteria analysis is a subject used in the new studies and organization of the criteria in a spatial model using GIS has had the good results.

Vegetation is an important element in the forest. Study and understanding of the vegetation of the most urgent issues and research in the area of natural resources and the environment. Due to the proximity to urban parks and impress their quality of life is important. Park Forest regeneration is important, In this study, in order to maintain and develop forest regeneration has been. This study aimed to evaluate regeneration in relation to the slope, aspect and elevation has been made. Tsavfy systematic sampling was done using 35 plots of national park area of determination and characteristics to be measured in the plots. Initially, descriptive statistics indicators measured by use of the expression and then using parametric and nonparametric and ultimately affect the characteristics of the land on growth trees and predict growth trees with each other using Version SPSS 21 software was evaluated. The results of this study showed that the slope of the growth characteristics had no significant effect, But Ash slope height, diameter Ktlpa breast, breast diameter ash, the average diameter of the chest, the canopy of acacia, ash canopy, canopy and canopy average overall plot was significantly affected. The number of trees per plot on reproduction, and other characteristics as well as significant growth. Acacia at its height had a negative relationship between happiness