Search published articles
Showing 2 results for Aghayari Hir
Mohsen Aghayari Hir , Mohammad Zahheri, Hossein Karimzadeh, Ali Majnuni Tutakhaneh,
Volume 10, Issue 36 (summer 2021 2021)
Volume 10, Issue 36 (summer 2021 2021)
Abstract
Introduction
Due to its geographical location and climatic conditions, Iran is facing water shortages. A large part of the country is in arid and semi-arid climates. In addition to the dry weather of the country, mismanagement, short knowledge of farmers, outdated infrastructure, low level of technology have led to low water productivity in rural areas. The Qaleh chai watershed is one of the catchments located around Lake Urmia, which is facing water shortage due to drought conditions. This area with 36 villages is known as one of the hubs of agricultural and livestock production. According to the obtained data, the water efficiency level in the basin is less than 50%. Lack of water resources has led to the need to pay attention to ways to improve water efficiency. It seems that several factors play a role in the quantity and quality of water use, in other words, in the level of its productivity in The Qaleh Chai, and the most important ones include geographical conditions such as slope, location of villages, amount of products produced. Literacy level, number of rural households, water resources, amount of water available. By identifying and analyzing the factors affecting the promotion of water productivity in the basin, the amount of water productivity can be improved. Therefore, the main purpose of this study is to investigate and find a scientific answer to the question of what is the spatial distribution of factors affecting water productivity in villages located in The Qale chai? And to what extent can the studied variables explain the changes related to water productivity?
Methodology
The research method is descriptive-analytical and inferential, which has based on documentary studies, libraries, and field studies. Local Moran correlation tests and geographic weight regression (GWR) tests were used to analyze the data. The variables used in this study included 19 environmental components affecting water productivity: Number and spatial distribution of springs, number and spatial distribution of wells, river water volume, water abstraction from wells, water abstraction from rivers, water abstraction from springs, length of concrete irrigation canals of all canals, the total volume of water in Consumption, number of households, unemployment rate, the employment rate in agriculture, literacy rate, rial value of tree products, rial value of rainfed products, rial value of summer crops, rial value of light livestock products, rial value of heavy livestock products, agricultural and medium irrigated land area Slope of villages to percent.
Water productivity has been used to calculate the rial value of livestock products, agricultural products, and human variables. The study area of this research is the Qaleh chai which has 36 villages located in it. The region of this basin is equal to 249.63 square kilometers, which has located in East Azerbaijan province and the southeast of Lake Urmia.
Discussion and conclusion
Research Findings show that the number of spring water resources is higher in mountainous villages and, the number of wells is higher in plain rural. The results of Moran showed that the variables of the Iranian Rial value of livestock production and the total amount of available water lack spatial autocorrelation. Also, the variable of the Iranian Rial value of all agricultural products has no spatial autocorrelation, but the total number of water resources has a spatial correlation. There is also an intense spatial correlation in the average slope of the villages, but the results of this test on the final water productivity lack spatial correlation. According to the results, the literacy variable of spatial autocorrelation is cluster type. The variables of household size and employment have no spatial correlation. Results The GWR regarding the causal role of the variable related to the final value of agricultural products and livestock products with water productivity showed that the last value of products with a correlation of R2 = 229 can explain water productivity. Based on the results of the geographical weight regression test, the value of R2 for social variables was equal to R2 = 0.129, which is lower than the final value variables of livestock and agricultural products.
Findings of this study show that factors such as the number of agricultural products produced, water resources, the volume of water available from water resources, land slope, number of water pumps and Iranian Rial value of livestock and agricultural products, literacy rate, employment rate, population have a significant relationship with water productivity. According to the research findings, it is clear that to achieve an efficient solution to improve water productivity in the villages located in the Qalah Chai watershed, it must have all the operative factors, including natural elements. Human factors, management factors, and physical characteristics are based on accurate, reliable data and planning occurrence.
Due to its geographical location and climatic conditions, Iran is facing water shortages. A large part of the country is in arid and semi-arid climates. In addition to the dry weather of the country, mismanagement, short knowledge of farmers, outdated infrastructure, low level of technology have led to low water productivity in rural areas. The Qaleh chai watershed is one of the catchments located around Lake Urmia, which is facing water shortage due to drought conditions. This area with 36 villages is known as one of the hubs of agricultural and livestock production. According to the obtained data, the water efficiency level in the basin is less than 50%. Lack of water resources has led to the need to pay attention to ways to improve water efficiency. It seems that several factors play a role in the quantity and quality of water use, in other words, in the level of its productivity in The Qaleh Chai, and the most important ones include geographical conditions such as slope, location of villages, amount of products produced. Literacy level, number of rural households, water resources, amount of water available. By identifying and analyzing the factors affecting the promotion of water productivity in the basin, the amount of water productivity can be improved. Therefore, the main purpose of this study is to investigate and find a scientific answer to the question of what is the spatial distribution of factors affecting water productivity in villages located in The Qale chai? And to what extent can the studied variables explain the changes related to water productivity?
Methodology
The research method is descriptive-analytical and inferential, which has based on documentary studies, libraries, and field studies. Local Moran correlation tests and geographic weight regression (GWR) tests were used to analyze the data. The variables used in this study included 19 environmental components affecting water productivity: Number and spatial distribution of springs, number and spatial distribution of wells, river water volume, water abstraction from wells, water abstraction from rivers, water abstraction from springs, length of concrete irrigation canals of all canals, the total volume of water in Consumption, number of households, unemployment rate, the employment rate in agriculture, literacy rate, rial value of tree products, rial value of rainfed products, rial value of summer crops, rial value of light livestock products, rial value of heavy livestock products, agricultural and medium irrigated land area Slope of villages to percent.
Water productivity has been used to calculate the rial value of livestock products, agricultural products, and human variables. The study area of this research is the Qaleh chai which has 36 villages located in it. The region of this basin is equal to 249.63 square kilometers, which has located in East Azerbaijan province and the southeast of Lake Urmia.
Discussion and conclusion
Research Findings show that the number of spring water resources is higher in mountainous villages and, the number of wells is higher in plain rural. The results of Moran showed that the variables of the Iranian Rial value of livestock production and the total amount of available water lack spatial autocorrelation. Also, the variable of the Iranian Rial value of all agricultural products has no spatial autocorrelation, but the total number of water resources has a spatial correlation. There is also an intense spatial correlation in the average slope of the villages, but the results of this test on the final water productivity lack spatial correlation. According to the results, the literacy variable of spatial autocorrelation is cluster type. The variables of household size and employment have no spatial correlation. Results The GWR regarding the causal role of the variable related to the final value of agricultural products and livestock products with water productivity showed that the last value of products with a correlation of R2 = 229 can explain water productivity. Based on the results of the geographical weight regression test, the value of R2 for social variables was equal to R2 = 0.129, which is lower than the final value variables of livestock and agricultural products.
Findings of this study show that factors such as the number of agricultural products produced, water resources, the volume of water available from water resources, land slope, number of water pumps and Iranian Rial value of livestock and agricultural products, literacy rate, employment rate, population have a significant relationship with water productivity. According to the research findings, it is clear that to achieve an efficient solution to improve water productivity in the villages located in the Qalah Chai watershed, it must have all the operative factors, including natural elements. Human factors, management factors, and physical characteristics are based on accurate, reliable data and planning occurrence.
Dr. Mohsen Aghayari Hir, Dr. Hossein Asgharpur, Dr. Soheyla Bakhtar,
Volume 13, Issue 1 (6-2024)
Volume 13, Issue 1 (6-2024)
Abstract
Objective: The present research was conducted with the aim of identifying and analyzing economic factors affecting the acceptance of organic agriculture in Tabriz County.
Methods: The population of this study consists of producers and consumers of Tabriz County. The community of producers in the County is composed of 28 person. Due to their limited number, they were studied in full. In the consumer community, the sample size was estimated to be 384 person, but to achieve better results, 391 questionnaires were completed. In order to analyze the data, structural equation modeling was used in Smart PLS software and one-sample t-tests and Friedman in SPSS software.
Results: The results of the measurement model indicate that the loads of the observed agents with their hidden variables have significant values, and the observed agents have measured their hidden variables well. Also, there is a significant structural relationship between price perception, providing support facilities, product distribution, product preparation method, product price, product features, product quality, and willingness to pay. The obtained values of T, the average and the upper and lower limits of the factors affecting the acceptance of organic agriculture from the producers' point of view, had higher values than the standard set. The results of Friedman's test showed that the price of the product has the highest importance and the provision of support facilities has the lowest importance.
Conclusions: Comparing and examining the views of two producer and consumer groups shows that the economic dimension has had a major effect on the adoption of organic agriculture. Also, factors such as having high prices for products, costs and prices offered for a specific brand, an appropriate marketing system, etc. are among the factors that have affected the economic aspect of adopting organic agriculture.
| Page 1 from 1 |
Related Websites
Site Keywords
نشریه, Academic Journal, Scientific Article, کلمه شماره یک, کلمه شماره یک, کلمه شماره یک, کلمه شماره یک, کلمه شماره دو, کلمه شماره یک, کلمه دوVote
Designed & Developed by : Yektaweb