فهرست مطالب seyed amir shamsnia

Water is the most important component for the sustainable production of agricultural products. Droughts and the increase in plants' water requirement show the necessity of proper and accurate plant irrigation planning. Lack of water is one of the important economic and social factors in most developing countries, especially countries located in arid and semi-arid regions of the world. One of the most important agricultural products in the world is wheat. This product is always a part of macro-agricultural policies, and the analysis of the productivity situation and related challenges plays an important role in agricultural planning. Considering the high cultivated area of this plant and in order for irrigated cultivation to be a sustainable cultivation, it is necessary that its management, modification and methods of water consumption in agricultural lands should be given more attention by agricultural experts and managers. In order to be able to generalize the parameters measured at a point to the regional scale and to determine the water requirement at the regional scale, methods that, in addition to the quantity of data, also measure the location should be used. Therefore, this information should be converted from a point mode to a regional mode and establish the spatial integrity of the point data.

In the current research, the indicators of irrigation planning in wheat production (water requirement, irrigation depth and irrigation interval) in Darab Plain lands in Fars Province have been investigated.In order to create an optimal management, an irrigation database including soil, climate and plant information layers was formed in the GIS, and this information and data was obtained from the Agricultural Jahad Organization. The desired spatial variables are the water requirement of the wheat crop and the net depth of irrigation water. The weather data used to determine the water requirement, such as air temperature and soil parameters, are spatial data and are dependent on spatial characteristics. Then, based on the information provided in the GIS, the location map of the farms was prepared in the first stage. According to the size of the area, after the field visit and information about the condition of the farms, 30 farms that had a pressurized irrigation plan were selected. Due to considering proper dispersion and non-overlapping of information, a number of points were removed, and due to the fact that in order to use the kriging model, it is necessary for the points to have proper distribution, so finally 15 points (farms) were selected. The whole plain is scattered. Based on the selected points, the condition of the soil type was determined. The required information on water requirement, net and gross depth of water irrigation and soil texture were formed in the Geographic Information Systems. So that in the points without data, an estimate of the desired data was made and the required maps were prepared. In order to estimate the irrigation interval in each of the studied lands, using spatial analysis in the GIS and irrigation water depth maps and wheat water requirements, the irrigation interval map was prepared separately for each month.The purpose of the research is spatial analysis and the studied data is of the spatial data type, and geostatistics models were used to prepare spatial distribution maps of water requirement and net depth of water irrigation, and interpolation of data were done using Kriging method.

First, the condition of the soil texture in the study area was investigated. Based on the soil texture in the selected areas and with the help of the Thyssen method, the soil texture map of the study area was prepared. The texture of the soil in the northeast, east, southwest and west is loamy and in the northwest, center, south and southeast it is clay loam. The north of the studied area is sandy loam. The growing season of wheat cultivation in the study area is from December to June. The maps prepared for water requirement and irrigation depth showed that in most months, the highest amount of water requirement is related to the north and northeast parts and the lowest amount is related to the northwest and west parts. Also, the water requirement maps showed that during the wheat growth period in the study area (November to June), the month of May has the highest monthly water requirement with an average of 86.45 mm/month. The irrigation depth maps also showed that the irrigation depth in the center of the plain has the highest value and the northern parts of the plain have the lowest value. Also, the irrigation depth maps showed that the irrigation depth in the whole area varies from 8.6 cm to 13.8 cm. According to the water requirement maps, since the changes of water requirement in the study area are large and also the net irrigation depth map shows a high depth, as a result, the irrigation interval is affected by both. The lowest of wheat irrigation interval in the study area (1 day) is in the months of April and May for lands in the north, northeast and southeast, which increases from the east to the center, and in the northwest and southwest, the maximum irrigation interval is 3 days. Considering that the minimum water requirement of wheat in the growth period is in January and the range of its changes in different parts of the study area is between 6.6 and 18.05 mm/month. Therefore, the longest irrigation interval (5 to 18 days) is related to this month. According to the obtained results, the estimation of water requirement, net irrigation depth and irrigation interval based on regional changes and spatial analysis is a suitable method in irrigation planning. The use of spatial analysis and advanced geostatistics models can be effective in estimating irrigation parameters and productivity indicators and help different land managements and determine the amount of water requirement and the appropriate irrigation interval.

Locating and building small water projects in hot and dry areas of the country that are facing water shortage is of great importance. These projects are more popular among farmers than other water supply and storage projects due to simple construction technology, low study and implementation costs, public participation, simple operation and maintenance, and environmental effects. The use of new sciences, especially Remote Sensing techniques (RS) and Geographic Information System (GIS) helps planners to locate water supply and storage projects. Various studies have been conducted in the world in relation to location, analysis of factors affecting the location of water storage and supply plans using different criteria and using RS and GIS techniques. The aim of the present study is to identify and introduce water areas with the potential to create small water supply projects in the southeast of Bushehr province.

This research was conducted in Dayyer City in the southeast of Bushehr Province with an area of ​​2306 Km2 and a mean rainfall of 215 mm. In order to achieve the goal, first, nine flood-producing criteria including the slope, aspect of slope, river density, height, rainfall, runoff, distance from the river, land use and geological formations were considered. Then, using AHP method and weighting and prioritization of effective parameters and taking into account other environmental conditions and the overlap of maps, the final flood map of the city was prepared and classified. After calculating and estimating the degrees of importance, ArcGIS was used as a decision support system for future calculations. Also, Google earth and Arc Scene software have been used for better analysis and better understanding of the results in preparing the 3D space of the study area. After preparing the maps of the distribution and location of the wells and waterways network, the opinions of the relevant experts were also used. Also, other factors such as downstream land use, topography and access roads, drinking water consumption, livestock drinking consumption, the widest points in terms of the storage resource level and the ease of implementation of the structure were also considered as quality and management criteria.

The results showed that the region can be divided into five regions with very low, low, medium, high and very high in terms of flood vulnerability risk. Also, the results of flood zoning showed that the extension of the northern and northeastern elevations to the east of Dayyer City and the middle elevations of the city and its center have high flood potential. According to the area of the study area, 25.2% are in the high vulnerability class and 11.5% in the very high vulnerability class. In addition, the results showed that 25 places in the region are suitable for creating small water supply projects, which, if implemented, can be effective in collecting and supplying water and increasing the profitability of the region in addition to controlling seasonal floods.

Based on the results of this research, it is concluded that more than one third of the region (36.7%) has a high to very high risk of flooding, so these areas should be the focus of urban management planning. Also, 25 places in the region were suitable for creating small water supply projects, which need to be considered by regional managers and planners to reduce the effects of water shortage of the region. In addition, this research showed the good performance of GIS and AHP method in flood risk zoning and locating of small water supply projects in Dayyer City. Another noticeable point is that there are about 4217 hectares of land under dry wheat cultivation in the 23 proposed points of downstream, and currently the harvest of rainfed wheat is 1.3 tons per hectare on average. If appropriate water supply plans are implemented, the total harvest amount can reach about 16,000 tons per year. Therefore, making suitable water supply plans can result in an increase in production.

Soil moisture is one of the most important factors that are affected by drought. Soil Moisture Deficit Index (SMDI) is one of the most important indicators that monitors drought based on soil moisture. But due to lack of direct measurement of soil moisture in weather stations and lack of information, it has been used to a limited extent. In this research, the meteorological data of Zarghan synoptic station was used during the statistical period of 30 years (1992 to 2022) and with the help of ET0 and AquaCrop models, the amount of soil moisture was estimated at the depths of 5, 15, 45 and 95 cm. Then the percentage of soil moisture deficiency and SMDI index were calculated to monitor drought. Also, the results of this index were compared and analyzed with two common indices SPI and RDI which are based on precipitation and evapotranspiration data.The highest value of this index occurred in 1996 after a period of heavy rain in 1994 and 1995, and the lowest value occurred in 2011 after the dry years of 2008 to 2010. Considering that the highest and lowest amount of rainfall is in 2004 and 2021, SPI and RDI drought indices have shown the most severe drought in the mentioned years. Severe droughts occurred in 2010, 2011, 2016 and 2021, and all three indicators had similar results. In examining the relationship between meteorological parameters and indices, the results showed that the SMDI index has the lowest coefficient of explanation with evapotranspiration (0.25), RDI index (0.4) and then SPI and precipitation index (0.45). Also, the results showed that there is a strong correlation between SPI and RDI. Regarding moderate and very severe droughts, where the amount of precipitation is greatly reduced and evapotranspiration increases, the RDI index is more accurate and shows the severity of the drought with higher accuracy, and its sensitivity to weather conditions is higher than the SPI index. Therefore, in arid and semi-arid regions where the severity of drought reaches the severe and very severe threshold, it is recommended to use indicators that take into account other factors in addition to precipitation.

Stochastic models will be used as a method, to study changes in time series data in the future. The purpose of this study is to analyzing the groundwater level of piezometer wells in Shiraz, simulating and short-term forecasting of its status in the future using stochastic methods. for modeling In this research, water level statistics of 14 piezometer wells that had more complete statistics from 1993 to 2019 were used and based on ARIMA model and partial autocorrelation and autocorrelation method and with evaluation of parameters and types of models and all possible patterns in terms of being static, suitable model for predicting groundwater level in each well was obtained separately. After validation and evaluation of the model, the groundwater level was predicted in the future years 2020 to 2026. The results of groundwater level forecasting in wells in Shiraz using time series models show that with assuming the consumption pattern remains constant and no noticeable change in the groundwater recharge process, during the next 7 years, on average, we will face a decrease of about 3.5 meters in the groundwater level compared to the current situation. Therefore, due to the significant drop in groundwater level in the future and the limited resources of drinking water supply in Shiraz and the need for more water in the future, appropriate decision-making for supply management and consumption management in this city, seems necessary.It is necessary to study the consumption and demand management, in order to save water and prevent its loss in the city as a basic solution.

Flood-prone areas are of great importance in order to control the resulting damages, store runoff and increase underground water reserves. In this regard, it is possible to use advanced spatial methods to identify flood-prone areas and use its results in urban management planning. The purpose of the present study is to identify flood prone areas and flood potential zoning of dayyer County in Bushehr province using hierarchical analysis in GIS environment. For this purpose, based on the most important effective factors in creating floods and their weighting, the Analytical Hierarchy (AHP) method was used. After preparing the weighted maps and analyzing the criteria, by overlapping the layers, a flood zoning map was prepared and presented in dayyer County. Based on the results, the extension of the northern and northeastern elevations to the east of dayyer County and the middle elevations of the city and its center have a high flood potential. The results showed that out of the total area of 2306 square kilometers of the studied area, 204 square kilometers are in the very low vulnerability category (8.8%), 563 square kilometers are in the low vulnerability category (24%), and 694 square kilometers are in the medium vulnerability category (5.5). 30 percent), 583 square kilometers are in the high vulnerability class (25.2 percent) and 262 square kilometers are in the very high vulnerability class (11.5 percent). Considering that more than 50% of the area of the region has a medium to high risk of flood potential and the areas with a very high risk also constitute a significant area of the region, Therefore, it is necessary that flood-prone areas be the focus of urban management planning.

Assess the quality of rainfall and stream flow information have an important role in improving the efficiency and correct their deficiencies. For an optimal monitoring network design, they should be reviewed periodically based on the information needs and future water resources development plans. In this study evaluates regional values of rain-gauges and stream-gauges in Jarrahi- Zohre basin using the discrete entropy. To determine the regional value of each station within a region, several information parameters, were calculated to identify essential rain gauge and critical area. Based on the obtained results, 39.7% of the area of the area does not have a rain-gauge station, while nearly 53% of the area of the area is in the class of lack, severe lack and lack of information exchange, and 40% of the area of the area is in the middle class. Therefore, the density of the 42 selected stations of the rain gauge network in Jarrahi - Zohre basin is not acceptable and it is necessary to seriously reconsider the distribution and layout of the rain-gauge stations in the area. Also, 21.16% of the area of the area does not have a water measuring station. While more than 5.7% of the district area is in the class of deficiency, severe deficiency and lack of information exchange, and more than 73% of the area of the district is in the middle, upper middle and surplus class. Therefore, the density of the 16 selected stations of the water measurement network is optimal and other active water measurement stations can be removed from the monitoring network of the area.

Contamination in sewage systems and dumping them in the environment is amongst the biggest concerns for the World Community for which some solutions have been proposed. In this paper, a greywater treatment system in a Shiraz residential building using the aerobic method was evaluated and 10 intake and exhaust samples were acquired under normal lab conditions. Sampling was done in approximately four-month period in 5-day intervals. The results revealed that output values for pH, Turbidity, COD, BOD5, Nitrate, Total Coliform, and Fecal Coliform were 6.88, 26.5, 111.6, 29.7, 5.65, 184.9 and 670.2 respectively. All the amounts are within the legal limits of Ministry of Health and Medical Education’s Article 5 of Code of Water Pollution. This technology is able to purify turbidity up to 99.11 percent, COD up to 93.92 percent, BOD5 up to 96.23 percent and nitrate up to 99.96 percent. Therefore, scientific and principled treatment of greywater can reduce more than 90% of pollutants in wastewater and set the level of pollution to the standard of use in agriculture and irrigation. The use of this valuable water source can be useful in the development of urban green space and the promotion of the urban ecosystem.

Soil temperature is one of the important parameters in meteorological agriculture and affects many soil biological processes. Unfortunately, due to the lack of soil temperature data in many regions of the country, this issue has always been discussed in agricultural projects. In the present study, practical equations were created to estimate the monthly soil temperature using the correlations between different meteorological parameters and soil temperature in five agricultural stations in different cities of Fars province (Shiraz, Abadeh, Darab, Zarghan, and Jahrom) at depths of 5, 10, 20, 30, 50, and 100 cm. In this regard, multivariate linear regression equations have been used. According to the results, the following parameters affected soil temperature: in Abadeh, meteorological variables of wind speed, rainfall, and maximum temperature; in Darab, relative humidity, wind speed, air pressure, rainfall, maximum temperature, and minimum temperature; in Jahrom, variables of wind speed, air pressure, maximum temperature, and minimum temperature; in Shiraz, the variables of sunshine hours, wind speed, air pressure, rainfall, maximum temperature, and minimum temperature and in Zarghan city, the variables of sunshine hours, wind speed, air pressure, rainfall, maximum temperature, and minimum temperature. In general, fewer parameters are needed in all stations to estimate soil temperature at depths of 5 and 10 cm, and the importance of meteorological parameters and their effective role in estimating soil temperature increases with increasing depth. Also, the effect of meteorological variables on soil temperature is not the same in different climates. According to the coefficients related to the equations, the highest and the lowest effect on soil temperature at different depths, are the maximum temperature and sunshine hours. With increasing depth, regression coefficients decrease as well. In all stations, regression coefficient at depths of 5 and 10 cm has been calculated between 0.98-0.99, and at depth of 100 cm has been calculated between 0.87-0.92, shows decreased about 10% of this coefficient with increasing the depth. According to the results and equations obtained for each station and different climates in Fars Province, this equation can be used to estimate soil temperature in areas without data.

Drought is one of the most important natural disasters that due to the frequency of occurrence needs to be assessed and monitored, especially in the field of agriculture. In the present study, the Reconnaissance Drought Index (RDI) was used to monitor drought and spatially assess its severity in central and southern regions of Fars province. The relationship between the severity and duration of drought during different years of the statistical period (1990-1991 to 2012-2013) was investigated. Kriging model was used in the geographic information system (GIS) environment for spatial evaluation. Based on the comparison between the different semivariogram of the kriging model, the most suitable model was selected. Based on the results of drought severity, its continuity and trend were determined during the statistical period. The results showed that severe droughts occurred in Darab and Neyriz stations during 2000-2002 and 2008-2010. In Fasa and Jahrom stations, in most of the years, climate fluctuations have led to drought with low to high intensities. At Larestan station, the results also showed several droughts have occurred, especially during the years 2000 to 2010. In spatial evaluation of drought using the Kriging model, the results showed that the best semivariogram is the spherical model. The evaluation of drought vulnerability in the studied areas also showed that the northern areas of Nayriz, Estahban, Fasa, Darab and Larestan have suffered more damage. Therefore, the use of drought indices, drought intensity monitoring and mapping methods are essential for better management and planning for advance planning and it is recommended for water resources management decisions.

Drought is one of the most common natural events that has a great negative impact on agriculture and water resources. Using the indices is necessary in order to monitor, evaluate and statistically analyze drought in each area. Recently, a powerful drought index, the Reconnaissance Drought Index (RDI), is gaining wide acceptance mainly in the arid and semiarid climatic regions. Since RDI is based both on precipitation and potential evapotranspiration (PET), it is interesting to assess the effect of the PET calculation methods on the drought severity characterization obtained by the RDI. This paper compares the results of the RDI for various reference periods using some popular empirical PET methods with minimum data requirements. The selected methods are: Hargreaves-Samani, Thornthwaite, Blaney-Criddle, Jensen-Haise and FAO Penman-Monteith. The FAO Penman-Monteith method is used as reference method. The data used are from meteorological stations in thr Tehran Province representing different climatic conditions. No significant influence on RDI was detected by using the selected PET methods. However, the Blaney-Criddle method performed relatively better. This supports the conclusion that the RDI is a robust drought index not dependent upon the PET calculation methods.

Deficit irrigation is a technique for optimizing crop production under drought stress conditions. The superabsorbent hydrogel is a hydrophilic polymer being able to absorb and retain a large amount of water. This study was conducted to evaluate the effect of different rates of Super AB A 200 superabsorbent hydrogel on yield and yield components of corn cv SC704 under drought stress. The experiment carried out in split plot based on a randomized block design in Hamidieh region, Khuzestan province, Iran. In this study, three different depths of irrigation were considered as the main plot including 100, 75 and 50% of water requirement of plants respectively and different levels of superabsorbent were used as sub-plot including 0 (control), 15, 30 and 45 g/m2, respectively. Increasing drought stress led to significant loss of yield, yield components and decrement in water use efficiency of corn The effect of drought stress was determined by decreasing leaf surface area index, disruption of nutrients uptake and transfer, which ultimately led to a decrease in the supply of nutrients, yield and yield components. Finally, it was concluded that superabsorbent hydrogel is effective in retaining water and nutrients and releasing them under drought stress conditions and significantly prevents the decline of yield and yield components. It is recommended to use 75% of plant water requirement and 45 g/m2 superabsorbent for corn cultivation under Khuzestan province climate conditions.

Temperature is one of the most important climate parameters affecting yield production. In the present study, the critical threshold of heat stress for wheat cultivation in Fars Province was evaluated and the equations for each critical threshold is presented. For this purpose, 14 active stations of Fars Province were selected. According to the climatic conditions of the region, three thresholds of temperature of 30, 35 and 40 degrees Celsius were selected and the days when the maximum daily temperature was higher than these thresholds were studied. Also, due to the importance of heat stress at night, the number of days when the air temperature was at least 20 degrees Celsius was also determined. Finally, according to the results, the mapping of thermal stresses in Fars Province was presented .The evaluation results showed that the southern part of Fars Province consists mainly Larestan, Mohr and Khonj and northwestern parts including Kazeroon and Mamasani are more susceptible to heat stress and larestan and mamasani more than other areas suffer from stress. In most cases, periods of heat stress coincide during germination and flowering of wheat culture in Fars Province. Maps provided by climatological analysis helps to agriculture managers to estimate probability of favorable or unfavorable atmospheric events in later stages of crop development with high accuracy.