فهرست مطالب سیدمحمدجعفر ناظم سادات

Land cover and soil moisture changes have a significant impact on land surface temperature (LST). Therefore, LST can be used to study land cover and desertification changes. Arsanjan County, which is located in the northeast of Fars province, has a relatively good forest and rangeland. Unfortunately, excessive harvesting of the groundwater resources and also reduced precipitation in this area caused to decrease water levels and dried up many wells in this area during recent years. So the area of the farmland and Bakhtegan Lake has decreased in this region during the last decades. However, so far, the condition of the LST and its relationship with land cover changes has not been assessed in Arsanjan County. In this study, spatial-temporal changes of LST and its relationship with vegetation and the water area of Bakhtegan Lake have been studied.

The eleven images related to Level-1 data of Landsat satellite was taken from 2003 to 2018. Since the vegetation situation in the study area is in the best vegetation and water area condition in April and May, so the images related to these months were selected to check the fluctuation of vegetation cover and water level of Bakhtegan Lake. The data pre-processing was performed in three sections: geometric, radiometric and atmospheric correction by ENVI software. The FLAASH algorithm, which is one of the best methods of atmospheric correction, was applied for atmospheric correction. In this study, NDVI was used to estimate the amount of vegetation. The Planck algorithm method was applied to calculate the LST. The change detection process was done using the index differencing method. To classify the LST map and the temporal-spatial changes, the LST difference map was normalized. Then, the normalized image was categorized using the standard deviation parameter in five temperature classes.

In the present study, 11 Landsat images were examined to investigate the spatial-temporal changes in land coverage and LST and the relationship between these two parameters from 2003 to 2018. The NDVI mean value was 0.25 in 2003, which decreased to 0.18 in 2018. On the other hand, the LST mean value had an upward trend as it increased from 29℃ in 2003 to 41.7℃ in 2018. The NDVI mean value was 0.66 in the farmland in 2003, however, its value reached to 0.33 in 2018. In contrast, LST mean value increased in the farmland from 20.9℃ in 2003 to 39.5.5℃ in 2018. Also, the LST mean value in the lake area increased from 20.1℃ in 2003 to 36.5 in 2018. Based on the results, the NDVI mean value in the rangeland and farmland decreased by 0.07 and 0.33, respectively, in 2018. However, due to the positive relationship between NDVI and LST in water-covered areas, the NDVI mean value increased by 0.39 in Bakhtegan Lake area in 2018. In contrast, the LST mean value in the rangeland, farmland and Bakhtegan Lake increased by 12.7℃, 18.6℃ and 16.4℃, respectively, in 2018 compared to 2003. The results indicated a negative relationship between NDVI and LST (R2= 0.862). The LST value decreases by increasing NDVI value in the vegetated area. In contrast, there was a positive correlation between NDVI and LST in salt-marshes and barren areas. According to the results, the highest negative correlation was obtained for the farmland, which was  -0.94. The reason for this high correlation can be related to the high density of vegetation cover in agricultural areas. The low negative correlation between NDVI and LST in the rangeland indicates the low vegetation density in rangeland and forest area. In order to study the area of decrease or increase of LST in the farmland, rangeland and water classes, the LST difference map was classified to five categories including very low temperature, low temperature, medium temperature, high temperature and very high temperature. According to the result of LST classification, the highest area was related to the moderate temperature class in all land covers, so that the highest area of this temperature class was associated with the rangeland by 86733 hectares. Since the vegetation density, especially in the farmland, had a significant decrease in 2018 compared to 2003, the area of high and very high-temperature classes increased in 2018, so that their area reached to 4625 ha and 7192 ha, respectively, in the farmland. Also, since the water area of the lake decreased in 2018 compared to 2003, the area of high and very high-temperature classes in these classes reached to 1824 ha and 3919 ha, respectively.

According to the results, the NDVI mean value in 2018 decreased in the farmland and rangeland and increased in the Bakhtegan Lake area. In contrast, the LST increased in the mentioned areas. The results of the LST classification showed that the highest amount of LST change is related to the moderate temperature class. Since the vegetation density, especially in the agricultural area, had a significant decrease in 2018 compared to 2003, the results showed that the area of high and very high temperatures had a higher increase than low and very low temperatures. Also, since the lake's water level decreased in 2018 compared to 2003, the area of high and very high temperatures in these classes increased. The findings show that there is a negative correlation between vegetation and land surface temperatures.

In recent years, due to excessive consumption and unbalance between water consumption and water resources, Iran has led to a severe shortage of renewable water sources. Therefore, in this situation, analyzing the status and presenting appropriate strategies is the main priority for policymakers. For this purpose, by designing a dynamic stochastic general equilibrium model, status of consumption of water resources has been studied in the household, agriculture and industry sectors. The existence and definite status of the stable situation, both parametric and numerically, has been investigated according to estimated values for Iran's economic parameters. According to the results of the research, it should be noted that at present, per capita water consumption is 1000 cubic meters per year. In other words, with current domestic consumption per capita, water per capita is less than that on the optimal Path. It is expected to achieve sustainable equilibrium in a long-term horizons by reforming consumption and providing policy solutions. Also, based on the simulation, from different policies, Establishing a 8-year limit on agricultural products with high water consumption is the most important policy for achieving the above equilibrium.

The Madden-Julian Oscillation (MJO) and El Niño Southern Oscillation (ENSO) are known as the primary modes of large-scale climate variability in the equatorial parts of the Indian and Pacific Oceans, respectively. The present study has made an effort to analyze interactions of these two oscillations during boreal autumn and the feedback of these interactions on the occurrence of dry or wet periods in Fars province. Cold and warm phases of ENSO (La Niña and El Niño, respectively) are then classified according to the size of the SOI. Then positive and negative phases of the MJO were defined according to the algebraic sign of the real-time multivariate MJO series 1 (RMM1). Daily values of October-December precipitation data of 9 synoptic stations of Fars province were obtained for the 1974-2013 period.
Precipitation amount and the occurrence probability of precipitation were investigated for La Niña, El Niño MJO positive phase, MJO negative phase and other four combinations of these phases. Since the impacts of ENSO or MJO phases on precipitation variability had been studied previously, the present study mainly motivated to investigate precipitation characteristics for the episodes that El Nino or La Nina events were concurrent with the MJO positive phase (El-P or La-P, respectively) or MJO negative phase (El-N and La-N, respectively). The characteristics of atmospheric circulation and vapor transport over the ocean waters and the Middle East are then investigated to justify the obtained results.
Some parameters including precipitation, intensity and occurrence probability of a rainy day were computed for all phases, separately. The ratio between these parameters during opposite phases was computed and spatially mapped to evaluate the effects of the interactions.
The results indicated that the frequency of the positive and negative MJO phases is significantly associated with the ENSO condition. Differences between the frequency of the positive and negative MJO phases during the El Niño events were found to be insignificant. Contrariwise, during the El Niño events, the frequency and occurrence probability of the positive MJO phase are about twice than corresponding statistics during the MJO negative phase. It was found that ENSO and MJO have a significant influence on autumnal precipitation in Fars province. During El Niño or negative MJO phase, the mean occurrence probability and intensity of precipitation were significantly greater than the corresponding values during La Nina or positive MJO in Fars. For almost entire parts and for the periods of El Nino, precipitation has significantly enhanced or suppressed during the negative and positive MJO phase, respectively. On the other hand, such differences are not significant when the opposite phases of the MJO have concurred with the La Nina events. Compare to El-P, mean precipitation during El-N has increased by about 300% in the southeast and about 70% in the eastern districts. When the El-N phase has prevailed, the autumnal precipitation intensity has increased about 40-110% and 4-40% over the southern and northern area of Fars, respectively

The ultimate goal of this study is using remote sensing technology and using MODIS data to calculate the amount of dust in the Persian Gulf and evaluation of linear correlation model with ground measurements of atmospheric dust. The method of this research was that initially deposition mask and clouds mask and atmospheric correction was applied to images. In the following, extract of dust values in the form of AOD parameter was performed by using cod of MATLAB software. Finally, evaluation of results was performed by using the AERONET station data and statistical indicators RMSE and RMSD. Initial results of algorithm was reflects the model ability to simulation of dust particles. The results showed that existing algorithms simulate the spectral reflectance data in the effective radius different for dust concentration in the LUT tables. Amount of correlation calculated form the 13 September 2009 in the band of 1.243 is 0.94 and for the band of 1.643 is 0.97 respectively. RMSE and RMSD indexes were calculated in these day for bands of 1.243 equal to 0.02 and 0.02, and day for bands of 1.643 equal to 0.1 and 0.01 respectively. The evaluation results showed that AOD values obtained from satellite images is significantly correlated with AOD measured in AERONET stations.

Dust prediction such as prediction of wind and rain needs to synoptic information to the earth's surface, upper layers of the atmosphere, the prediction maps of land surface and upper levels as well as using radar and satellites. The purpose of this study, use of remote sensing technology and MODIS images to estimate dust optical depth on the Persian Gulf surface and estimating the linear correlation relationship between the dust measurements in ground and atmospheric. The dust optical depth calculated using the code developed in MATLAB software. Evaluation of extracted data conducted using Pearson correlation coefficient, RMSE and RMSD index. In this study, optical depth obtained from image processing compared with the optical depths obtained from AERONET network. The evaluation results showed a high and significant correlation between the obtained optical depth and optical depths obtained from AERONET network (R2=0.99). The best and most suitable mode demonstrated for 1.243 and 1.643 bonds. At all stations, AOD value obtained from satellite image is bigger than AOD amount corresponding to the AERONET station and the algorithm used has overestimated. The cause of this more estimate can be use of limited particle's effective radius, because the scope of this effective radius is limited at the distribution of particle size in log-normal. Error resources at the retrieving particulate matter was defined such as sensor calibration error, pollution on the radiation angle, or poor predictor of water reflection.

Coastal environments are considered the most sensitive system environments. In terms of environmental Coastal areas because of the sensitive and productive ecosystems have high importance and value. Having knowledge of the coastline’s behavior can help of the coastal better management. The aim of this study is to assessing the application of the OIF utility index factor in the assessment of coastline changes in Dayyer city, Using Landsat satellite images sensor TM and OLI 1991 and 2014 and the software are 2013®MATLAB and ArcGis 9.3. For the separation of land and water, OIF index value for all different band combinations in the application MATLAB® 2013 was calculated and then high-pass Sobel filter with 3 × 3 masks was applied to the images. Then digitization process during different periods in application environments ArcGis 9.3 was done manually and with high precision. The results of the survey the coastline from 1991 to 2014 show moving the coastline to the sea side (sedimentation) and landward (erosion), Which totals 33/784 square kilometers sedimentation and 9/132 square kilometers erosion shows from 1991 to 2014, in Dayyer city occurred because of the construction of piers, installations manmade and natural factors.

The aim of this study evaluates the use of satellite images to change detection in coastlines and evaluate the use of optimum index and the modified normalized difference water index (MNDWI) in examining changes coastline in Dayyer city. As well as for the evaluation of coastline change in the study area, 8 points were taken on April 24th, 2015 along the coastline city of Dayyer with regard to access to the beach, coinciding with the passage of the Landsat satellite, OIF index with a standard deviation and correlation, the correlation between bands is determined. MNDWI index, a combination of green and mid-infrared bands is to determine the boundaries between land and water is suitable. The results show, given that coastal study area and satellite imagery, the highest of OIF for OLI sensor is obtained RGB 156 composition. Also, the algorithm MNDWI is ideal for discriminating between land and water. The average distance from the baseline to the border extracted from the optimum index is 340 meters and the average distance from the baseline to the border extracted from the MNDWI index is 64.28 m is obtained. The results showed to check coastline changes in Dayyer city, MNDWI index is more accurate than the optimal index.

Land surface temperature (LST) is a key parameter in estimating energy balance that has determinate role in climate change studies. Various scientists have studied monitoring of LST in recent decades. The land surface temperature, which is measured by means of thermometers for certain points, for large scale basin is not cost effective. Using of satellite images for estimating LST make the estimates easier and more economical than ground measurement. In this study, MODIS land surface temperature (LST) was evaluated. In addition, due to use of correction factors which may not always be available for Iran, land surface temperature estimated by Landsat 5 image,which its spatial resolution is much higher than MODIS, was also evaluated.
For this study, two groups of data were used: satellite data and in-situ data. Ground measurements were collected from 261 points of a wheat farm in Marvdasht plain located in Fars province. Temperature was measured in four height of wheat including: canopy cover, middle, 10 centimeter from floor and soil surface. After statistical tests, acceptable data were selected for the comparison. In this study, twenty eight satellite images were implemented; including 26 MODIS images (MOD02 & MOD11 product) and 2 level-1G Landsat 5 images. Land surface temperature was estimated from thermal band’s of Landsat 5 images by applying the necessary corrections. After providing land surface temperature (LST) maps, land surface temperature was extracted from LST map (Landsat5 & MODIS) based on the measurement points. Afterward, the equation between the observed data and estimated surface temperatures from Landsat 5 (MODIS images) were obtained. Relationship between estimated and in-situ data was analyzed on four different heights of the wheat. Land surface temperatures were also estimated by three different split–window algorithms from Becker and Li (1990), Price (1984) and Ultivertal (1994) and the coefficients were calibrated. Finally, Fisher test was used to determine significant differences between the observed and the estimated data.
It was found that the estimated temperature by satellite has the best correlations with the plant canopy temperature. Estimated data were evaluated against the in-situ data. Results showed that Landsat and MODIS images overestimated the LST by RMSE of 4.4 oC and 7.1 oC respectively. Error of Estimating LST with split–window algorithms was within the range of 3.5–3.7 degree centigrade. Among the three studied algorithms, Becker and Li (1990) approach showed the best performance (the least error). The significant differences between in-situ data and the satellite estimates were examined by Fisher Test. No significant differences were observed in any of the pairs of data.
For meso-scale and large-scale studies, using satellite images is efficient and economic than the point surface measurements. The choice of satellite images (Landsat or MODIS) is depend on the accuracy which is expected from the study.

Atmospheric aerosol plays a significant role in the Earth's radiation budget through radiative forcing and chemical perturbations. Aerosols are intricately linked to the climate system and the hydrologic cycle. The net effect of aerosols is to cool the climate system by reflecting sunlight. Quantifying the net effect requires accurate information on the global distribution of aerosol properties that have to be estimated from satellite observations. Estimating aerosol properties is also one of the first steps in generating high-level land surface products from satellite observations. Effective aerosol retrieval information is also essential to satellite imagery atmospheric correction. Satellite remote sensing has been employed to supplement the prediction of ground-level dust concentration. Satellites are able to cover vast spaces at a relatively low cost. For aerosol studies, the launch of the Moderate Resolution Imaging Spectro-radiometer (MODIS) has enabled the retrieval of aerosol optical depth (AOD) data globally from the satellite's spectral observation. MODIS AOD is a measure of light transmittal by aerosols in an atmospheric column during the satellite overpass. With the evolution of the retrieval algorithm, MODIS AOD has become increasingly important in the role of producing more accurate estimation for the aerosol. Estimation of aerosol loadings is of great importance to the studies on global climate changes. Meteorological numerical models and ground stations are not able to tracking and detection of dust storms and in many cases have significant errors. This issue show necessitates use of reconstruction ways dust according to remote sensing techniques. The purpose of this study, use of remote sensing technology and MODIS images to estimate dust concentration on the Persian Gulf surface and estimating the linear correlation relationship between the dust measurements in ground and atmospheric. In this study, we develop a new algorithm for estimating the aerosol optical depths using MODIS data over Persian Gulf surfaces. This algorithm is validated using AERONET measurements.
In the current study we analyze atmospheric aerosol optical properties over Persian Gulf. Annually, Dust storms are imported into Persian Gulf from the West and North West and South West. Data corresponding to the station was extracted for channels of 0.644, 0.855, 0.466, 0.553, 1.243 and 1.643 µm of satellite image. The ocean algorithm was designed to retrieve only over Dark Ocean, (i.e. away from glint). There is a special case when we retrieve over glint, and that is described below. The algorithm calculates the glint angle, which denotes the angle of reflection, compared with the specular reflection angle. The glint angle is defined as:Θ_glint=〖cos〗^(-1) ((cosθ_s cosθ_v )(sinθ_s sinθ_v cosϕ)) (1)
Where θ_s, θ_v and ϕ are the solar zenith, the satellite zenith and the relative azimuth angles (between the sun and satellite), respectively. The retrieval requires a single fine mode and a single coarse mode. The trick, however, is to determine which of the (4 x 5) twenty combinations of fine and coarse modes and their relative optical contributions that best mimics the MODIS-observed spectral reflectance. The reflectance from each mode is combined using η as the weighting parameter:ρ_λ^LUT (τ_0.55^tot )=ηρ_λ^f (τ_0.55^tot )(1-η)ρ_λ^c (τ_0.55^tot) (2)
Where ρ_λ^LUT(τ_0.55^tot) is a weighted average reflectance of an atmosphere with a pure fine mode 'f' and optical thickness τ_0.55^tot and the reflectance of an atmosphere with a pure coarse mode 'c' also with the same τ_0.55^tot. Before the final results are output, additional consistency checks are employed. Our primary means of true ‘validation’ is comparison with ocean-based sunphotometer measurements, specifically, those of AERONET. The AERONET measured AOD is easily interpolated to the exact MODIS wavelengths (for example 0.55 µm) by quadratic interpolation in log reflectance/log AOD space. The AERONET ‘sun-measured’ definition of FW differs from either of the MODIS (land or ocean) definitions, but should be correlated with either. AOD images were compared with values obtained in AERONET stations, in finally AOD values were evaluated using statistical indexes of Average, standard deviation, correlation, Mean Squared Error (RMSE) and Mean Difference Square Error (RMSD). In the following validation, we use AERONET Level 1.5 data of the Dalma, Bahrain, Abu Al Bukhoosh, Sir Bu Nuair, Umm Al Quwain, MAARCO and Mussafa station when available.
Discussion of Results & The evaluation results showed that good correlation exists between the AOD simulation and AERONET data, with the correlation coefficient exceeding 0.90. The best and most suitable mode demonstrated for 1.243 and 1.643 bonds with the correlation coefficient equal to 0.94 and 0.99 and RMSE and RMSD index equal to 0. 2 and 0.02 for band of 1.243 and 0.1 and 0.01 for band of 1.643, respectively. We conclude that significant limitations exist for aerosol retrieval using marine AERONET stations. The number of matching points between the two datasets may become sufficient toattempt the reduction of the current uncertainties. Given the identified uncertainties, the results of this study do not contradict these previous validation efforts. Future research may reduce these uncertainties and require modifications to the retrieval algorithm. We used AOT data from a comprehensive set of Persian Gulf AERONET stations to evaluate the dust retrieval algorithm. Data evaluation was performed by using the Pearson correlation coefficient, root mean square error index (RMSE) and root mean square deviation index(RMSD). The evaluation results showed that good correlation exists between the AOD simulation and AERONET data, with the correlation coefficient exceeding 0.90. The regression analysis of AOD data revealed similar limitations. We found that the AOD simulation are on average 5%–25% more than the corresponding AERONET values, depending on the regression weighting assumptions for the comparison dataset. To further evaluate the performance of the algorithm in comparison with the AERONET measurements, we used the RGB image from MODIS. Overall, the comparison with the AERONET data has revealed similar performance of the two satellite datasets with a tendency of the simulation AOTs to underestimate and the MODIS over-ocean AOTs to overestimate the AERONET values. The range of these discrepancies is comparable to the uncertainties associated with the limited number of ocean stations and natural aerosol variability. The comparison of AOTs in the Persian Gulf AERONET stations showed that AOD values in AERONET stations are, on average, 5%–25% lower than the corresponding simulation ones. While the biases in ocean retrieval algorithms and cloud screening procedures may not be excluded, these results indicate that aerosol loading in marine locations may differ significantly from that in adjacent land areas, thereby limiting the achievable validation accuracy. We conclude that significant limitations exist for aerosol retrieval using marine AERONET stations. These limitations can be linked to the extreme sparsity of the marine AERONET data, uncertainties associatedwith local conditions at the marine stations, and regression accuracy limits imposed by natural aerosol variability. The number of matching points between the two datasets may become sufficient toattempt the reduction of the current uncertainties. Given the identified uncertainties, the results of this study do not contradict these previous validation efforts. Future research may reduce these uncertainties and require modifications to the retrieval algorithm.

Analyzing temperature profile of the Earth''s atmosphere is an essential work for understanding the dynamic¡ radiative and chemical processes occur within the atmosphere and its boundary layers. Such analysis is also critical for the detection and modeling of climate change. Several studies is made on different temporal and spatial scales of the vertical structure of the atmosphere. Expanding knowledge and technology of remote sensing is also helpful to identify the vertical profile of the atmosphere. For better understanding the characteristics of vertical temperature profile in southern parts of Iran¡ daily records of radiosonde data at Shiraz station (Latitude 29.6N and Longitude 52.5E) were collected for the period 2005-2010. The dataset consisted of pressure¡ temperature and relative humidity data gathered from surface up to 30 Km above sea level at 0:0 Greenwich Mean Time GMT (3:30 am local time). Daily data were firstly transformed to monthly and seasonal time-series using arithmetic averaging procedure. There was no significant changes in pattern of vertical profiles of temperature fluctuations in the years studied. The study has found a temperature inversion layer¡ mostly having vertical length from 100 to 300 meters above surface level for all months of the year. The layer length was shorter when the relative humidity was greater. Temperature gradient changes to negative at the height of 1760-1580 meters above sea level. A lapse rate with the measure of 4Co/ Km during cold months and 6Co/Km during warm months was detected between the top of inversion layer and tropopause level. Maximum and minimum heights of tropopause were occurred during March and December 2009 (16494 and 19006 meters)¡ respectively. Result showed that according to global warming¡ variation in tropopause elevation trend in Shiraz station not only increase but also decrease. Tropopouse height changes from month to month and from year to year and we could not find any rule for it. Maybe these conflicts are because of short period of investigation. Tropopouse minimum temperature occurs in Jun and July and it is about -74 to -77.5 degrees Celsius .Maximum temperature occurs in December and January and it is closed to -68 degrees Celsius. Average annual value of tropopause temperature was estimated as (-71.6 Co). The coldest and warmest tropopause data were associated to the warm and cold months of the year¡ respectively. In seasonal scale¡ while the highest tropopause height occurred during winter (18138 meters)¡ the lowest elevation was associated to autumn (17158 meters). According to global regularity tropopause height increase in the warm months¡ but in this study it was proven otherwise because the maximum height of tropopause see in winter and it is due to the characteristics of a tropical latitude30 °and being in Subtropical Jet Stream path. Some discrepancies were found between our results and the findings of Australian investigator who analyzed Australian data (Khandu et al.¡ 2011). Discussion was made to justify these differences..Temperature gradient was found positive over the lower parts of stratosphere (up to 30 Km level). The highest or lowest increasing gradient was 1 or 2 oC per Kilometer¡ which happened during cold or warm months of the year¡ respectively.

The Madden–Julian oscillation (MJO) is a large-scale coupling between atmospheric circulation and tropical deep convection explaining a large part of the intra-seasonal (30–90 day) variability in the tropical and extra-tropical atmospheres. Rather than being a standing pattern like the El Niño–Southern Oscillation (ENSO), the MJO is an oceanic–atmospheric moving pattern that propagates eastward at approximately 4 to 8 ms−1, through the atmosphere above the warm parts of the Indian and Pacific oceans. Due to its quasi-cyclic pattern, the MJO is known as the 30–60 day oscillation, 30–60 day wave, or intra-seasonal oscillation. The oscillation is characterized by an eastward progression of large regions of both enhanced and suppressed tropical precipitation, observed mainly over equatorial parts of the Indian and Pacific Oceans. The anomalous convective precipitation is firstly triggered over the western Indian Ocean, and persists as it propagates over the warm ocean waters of the western and central tropical Pacific. Wheeler and Hendon (2004) categorized the whole cycle of the MJO into 8 phases namely phase 1 to 8. Phase 1 of the MJO that is the theme of this study, signifies the spells for which the convective activity is mainly centered over the western parts of the Indian Ocean equator. It has been previously reported that the occurrence of the MJO phase 1 improves the probability of precipitation event in southwestern Iran (Nazemosadat and Ghaedamini, 2010). In spite of these findings, the reasons of frequent clear sky and shiny days during this phase were not yet resolved. The aim of this study was to compare the oceanic and atmospheric features of the phase 1 for the spells that the incidence of this phase is concurrence with or without precipitation in the southwest of Iran. This analysis is beneficial for improving the MJO-based precipitation and climate forecast over this area. To accomplish this task, the MJO amplitudes during phase 1 were extracted for all days during the 1975–2012 period. Among the selected dates, those days with amplitudes greater than 1 were assigned as the strong MJO events. These MJO events were then divided into two different parts comprising the events with and without pervasive precipitation in southwestern Iran. According to the adopted definition, the pervasive precipitation occurred when at least five out of nine considered stations over the study area received more than 1.0 mm precipitation. For the pervasive precipitating dates, the MJO-precipitation composites were constructed for each individual station. Similar composites were also constructed for precipitation, vector wind, outgoing long-wave radiation (OLR) and vapor flux over the Middle Eastern region and tropical parts of the Indian and Pacific Oceans using the ESRL–NOAA composite facilities. Similar compositing procedure was also performed for the no-precipitating dates to investigate atmospheric condition during such spells.From about 8% to 15% of the November–April precipitation in the southwest of Iran was found to be associated with the periods that the MJO was centered in its phase1. It was concluded that, for improving the MJO-based precipitation forecast in southwest of Iran, not only the phase number and amplitude size of the MJO index, but the position and intensity of convective activities as well as the atmospheric circulations over the Indian and the Pacific Oceans should also be analyzed. In phase 1, precipitation event in southwest of Iran is usually associated with the state of convective activities and their relevant airflows over some areas extended from equatorial parts of east Africa up to the equatorial areas of the Indian Ocean around 90o E. In general, precipitation occurs over the study area if the core center of these activities locate around 60o E. For such situation precipitation anomaly over this area is greater than 1.5 mm/day and the OLR anomalies are less than −20Wm−2or lower. Coincidence with the Indian Ocean equatorial area, precipitation event over the study area in Iran is harmonized with the enhancement of convective activities over tropical parts of the Pacific Ocean for the areas between 160o W to 140o W and 10o S to 20o S. Compared to non-precipitating periods of phase 1, easterly or southerly wind enhances by about four times over the eastern parts of the Indian Ocean, tropical parts of North Africa and the Arabian Peninsula during the precipitating spells. The Persian Gulf was found to play an influential role for re-moisturizing the southerly airflows crossing this water body during the precipitating dates.

This research was aimed to investigate indigenous and modern management styles and their roots of success and stability in Arsenjan county, Fars province. Case study approach and observation, interview, and archival research techniques were used for data gathering. Priority rights of Ayesheh, Bonab and Katake Qanats of Arsenjan city were compared with the application of new cooperation models. The results of the study showed that methods of the priority rights of the Arsenjan qanats were compatible with many recent new cooperation ideas and models, indeed in some respects the local methods have priorities. It is also shown that with new technologies of withdrawal of ground water e. g., digging new deep and semi - deep wells, qanats very soon are being to be in danger of dryness, therefore, new methods of qanats management are highly proposed. Although some recommendations for better management of the qanats, monitoring, definition and consideration of the limiting zone, harvesting of aquatic organisms and protecting the qanats water from impact of environmental pollution are presented.

Local information about tillage intensity and ground residue coverage is useful for policies in agricultural extension، tillage implement design and upgrading management methods. The current methods for assessing crop residue coverage and tillage intensity such as residue weighing methods، line-transect and photo comparison methods are tedious and time-consuming. The present study was devoted to investigate accurate methods for monitoring residue management and tillage practices. The satellite imagery technique was used as a rapid and spatially explicit method for delineating crop residue coverage and as an estimator of conservation tillage adoption and intensity. The potential of multispectral high-spatial resolution WorldView-2 local data was evaluated using the total of eleven satellite spectral indices and Linear Spectral Unmixing Analysis (LSUA). The total of ninety locations was selected for this study and for each location the residue coverage was measured by the image processing method and recorded as ground control. The output of indices and LSUA method were individually correlated to the control and the relevant R2 was calculated. Results indicated that crop residue cover was related to IPVI، RVI1، RVI2 and GNDVI spectral indices and satisfactory correlations were established (0. 74 - 0. 81). The crop residue coverage estimated from the LSUA approach was found to be correlated with the ground residue data (0. 75). Two effective indices named as Infrared Percentage Vegetation Index (IPVI) and Ratio Vegetation Index (RVI) with maximum R2 were considered for classification of tillage intensity. Results indicated that the classification accuracy with IPVI and RVI indices in different conditions varied from 78-100 percent and therefore in good agreement with ground measurement، observations and field records.

Investigating the trend and fluctuations of the sea surface temperature (SST) data arecritically important for understanding the interactions between the oceans, the atmosphere and the land in various spatial and temporal timescales. Such analysis of the SST timeseries is also essential for the detection and modeling of climate change. The increase in the global SST is one of the primary physical impacts of climate change. Some recent investigations have shown that the fluctuations in SST data over the Persian Gulf and the western parts of the Indian Ocean regulates Iran's precipitation particularly over the southern districts. The present study was, therefore, motivated to analyze the trends in the SST data over the northwestern parts of the Indian Ocean waters containing 30 nodes of 2by 2 (longitude and latitude) grids for the period 1950-2009. These grids were spread over various parts of the Persian Gulf and Arabian Sea, the water bodied between 18 to 30 North and between 45 to 72 East. The monthly SST data was gratefully extracted from the database of the physical sciences division of the National Oceanic and Atmospheric Administration (NOAA). According to their geographical positions, these 30 grids were classified into three groups, namely, the Persian Gulf, coastal areas (i.e., the grids off the coasts by 2) and the Arabian Sea regions. Since the SST time-series generally have a normal distribution, a linear regression analysis was applied to detect the trend in the constructed time series for the classified regions in annual and seasonal timescales. The analysis was conducted by each grid individually as well as by averaging the SST data over each of the three mentioned zones. The seasonal time series were constructed by averaging monthly data so that winter, spring, summer and autumn consisted of the months Jan-March, April-June, July-Sep and Oct-Dec, respectively. The 60 years of the study period were also divided into three consecutive 20 years to assess the consistency in trend-line slope over time. The parametric statistical tests were used to investigate whether the detected trends are significant The study revealed that during the 60 years of the study period, the SST of these 30 grids has inclusively increased by about 0.61°C. It is in general agreement with Deser et al. (2010) that reported the magnitude of the global SST trend during the 1900-2008 period as approximately 0.4–1.0°C per century in the tropics and subtropics and 1.2– 1.6°C per century at higher latitudes. The amount of such increase for the Persian Gulf, coastal areas and the Arabian Sea was 0.5°C, 0.65°C and 0.63°C, respectively. Comparing with other seasons, for the large regions of the three classified zones the increasing trend was the greatest and the least for autumn and winter, respectively. While the spring and summer’s SST were increased by about 0.5°C during the last six decades, the corresponding increases for winter and autumn were found to be 0.60°C and 0.85°C, respectively. The autumnal upward trend was significantly greater than other seasons for the Persian Gulf and the coastal regions. However, the upward trend is statistically identical during autumn and winter over the Arabian Sea areas. With the exception of the spring, the slopes of the trend-lines were different between the Persian Gulf, coastal areas and the Arabian Sea during the other seasons.When the considered 60 year period was divided into three consecutive 20 yearperiods, the trend exhibited a variety of differences between these new shorter data sets. While the spring and wintertime SSTs did not exhibit any significant trend during either 1950-1969 or 1970-1989 periods, the upward trend was significant for the period 1990- 2009. In contrast to winter and spring, most of the considered SST time series (excluding the Persian Gulf data) were significantly warmed up during 1950-1969. No significant trend was observed for the period 1970-1989 on a seasonal scale. In spite of the fact that the Persian Gulf SSTs did not exhibit any significant positive trend during the summers or autumns for either 1950-1969 or 1970-1989 periods, the trend abruptly increased during the 1990-2009 period for these two seasons.

The El Niño-Southern Oscillation (ENSO) is strongly connected to the inter-annual tointer-seasonal variations of Sea Surface Temperature (SST) over the Pacific Oceanequators. On the other hand, the Decadal Pacific Oscillation (PDO) is related to neardecadal fluctuations of the Pacific SSTs in the northeastern parts of the ocean. Theinfluence of these oscillations on the global climate is generally more obvious when theENSO or PDO is in its extreme condition. For such circumstances, the SST anomaliesover a per-defined Ocean waters are highly positive or negative (positive or negativephase, respectively).The present study has made an effort to analyze the individual and the coupled effectsof the ENSO or PDO on the occurrence of the autumnal dry or wet periods in southernparts of Iran for the period 1951-2005. Regional maps of precipitation and vector windwere also produced to extend the outcome of the present study for the Middle Easteregion. Total precipitation during the October-December period was collected for 30 raingauge stations spread in various parts of southern Iran. In addition to precipitation,monthly values of the October-December SST anomalies over the Niño 3.4 region werealso extracted from the webpage of the National Oceanic and AtmosphericAdministration (NOAA). These monthly data were then averaged to three monthly(seasonal) records that were used as the ENSO indicator. Years related to the rank 1 to 18 and 37 to 55 (18 years each) were registered as the ENSO negative (El Niño) and positive (La Niña) phases, respectively. A similar procedure was also used to detect 18 years of the negative or positive phase of the PDO. The events that El Niño or La Niña years were coincided with the positive or negative phase of the PDO were then investigated. It was found that out of 18 years of La Nina, for 10 or 7 years, the PDO was in its negative (La- LPDO) or positive phase (La-HPDO), respectively. Similarly, out of 18 years of El Niño, the PDO was in its positive (El-HPDO) or negative (El-LPDO) phase for 8 and 5 years.For each individual station, mean precipitation for the El Niño, La Niña events as well asfor the opposite phases of the PDO were examined. Furthermore, the autumnalprecipitation was also investigated and compared for the La-LPDO, La-HPDO, El-LPDO,El-HPDO events.In addition to the rain-gauge data, the regional maps of precipitation and 850 hPa vectorwind anomalies were also produced using the http://www.esrl.noaa.gov/psd/cgibin/data/composites/printpage.pl webpage. These maps were generated for the oppositephases of ENSO, PDO and for the La-LPDO and El-LPDO periods. The GrADS softwarewas then used to overlay the produced maps of precipitation and the 850-hPa vector wind.The interpretation of these overlaid maps was found to be an efficient approach forunderstanding the impact of the considered tele-connections on the atmosphericcirculation and rain-bearing airflows.The results indicated that, for the southwestern parts of the country, precipitation hasbeen significantly suppressed or enhanced during the La Niña or El Niño event,respectively. This suppression or enhancement, however, was not significant for thesoutheastern districts. Although the above or below normal precipitation in the southernparts of Iran was generally coincided with the PDO positive or negative phase, the effectsof this oscillation on the precipitation variability were found to be significant forsoutheastern rather than southwestern parts of the country. In other words, while theprecipitation variability in the southwestern parts of the country is more sensitive to theENSO status, the PDO is more influential on the precipitation characteristics insoutheastern districts. The more dry or wet event was recognized as the periods that LaNiña or El Niño is, respectively, coincided with the negative or positive phase of the PDO(La-LPDO and El-HiPDO, respectively). For the La-LPDO events, the precipitationdeficiency was estimated as 68% to 100% for the southwestern and 37% to 67% for thesoutheastern districts. On the other hand, the occurrence of the El-HiPDO has enhancedthe autumnal precipitation by about 50% to 90% in the southwest and 30% to 50% in thesoutheast parts of Iran.According to the given results, ocurrence of the El Niño event intensifies the westerlyor southwesterly airflows which carry the Red Sea, Mediterranean Sea and Persian Gulfsmoistures to most parts of the Middle Eastern regions including most parts of Iran, Iraq,eastern coasts of the Mediterranean Sea, the Arabian Peninsula and Afghanistan.Furthermore, intensification of the near-surface easterly, southeasterly or southwesterlycirculation over northwestern parts of the Indian Ocean also pushes substantial amountsof water vapor to the Arabian Peninsula and southern parts of Iran for such spells. Thecharacteristics of atmospheric circulation during the PDO positive phase are mostlysimilar to that of the El Nino, though the latter is more vigorous than the former. Themost/least strengths of these moisture-laden circulations are associated with the El-HiPDO/La-LPDO epochs.

Canopy temperature is an important factor for irrigation scheduling. This is because canopy temperature is depend plant water status. This research evaluated usefulness of Modis sensor for estimating wheat canopy temperature. Relationship between temperature and values of digital satellite images were determined on different levels of plant height and then models were evaluated. Based on the results, the best correlation between the temperature of the green cover were with band 34&25, band 3 and band 2 in the special resolution of 1000 m, 500m and 250m respectively, and RMSE was equal to 3.6, 3.6 and 5.3 in the special resolution of 1000 m, 500m and 250m respectively. Lowest error was observed at the top of canopy and maximum error was at the bottom of plant. Result showed that measuring canopy temperature by using remote sensing is possible but magnitude of error showed that models need some modification.

This study aimed the analyses of the simultaneous effects of two phenomena MJO and ENSO on the occurrence of dry and wet spells in Iran. The study showed that the concurrence of El Niño with the MJO negative phase (El-N) and La Niña with the positive phase of the MJO (La-P) have the highest frequencies. Precipitation amounts and the incidence of dry and wet spells were, therefore, compared for these two distinct alternatives. The results indicated that, in February, November, and December, a nationwide dry condition is expected when La Niña is coincided with the MJO positive phase. On the other hand, the pervasive wet spell is anticipated if the El Niño events have concurred with the MJO negative phase. Although rainfall amount in dry zones of the southern Iran is less than corresponding values in the northern half of the country, the simultaneous impact of the considered Oscillations on the occurrence of dry or wet episodes are more significant for the southern half. For instance, Iranshahr station, in southeastern part of the country, has experienced 96 percent reduction or 90 percent increase in precipitation compared to the longterm mean values as the (La-P) or (El-N) was prevailed. Furthermore, for some stations located in very dry zone of the country including (Birjand, Torbatheidarieh, Tabas, and Yazd) the occurrence of dry or wet periods in April was significantly associated to the (La-P) or (El-N) episodes. For these stations about 105 percent increase or 51 percent decrease compared to the longterm mean precipitation values is anticipated as (El-N) or (La-P) events was prevailed, respectively.

Principal components and cluster analysis were used for grouping the monthly precipitation over Iran into somehomogeneous regions. Such grouping is considered as an essential and primary step for pre-process in downscaling of the general circulation models outputs. The monthly precipitation data of 42 stations for the period of 1967-2003 (37 years) forming a 42×444 matrix was used as input file of the principal components analysis. Using PCA, this matrix was reduced into a 42×33 matrix that accounted for about 96% of total variance in the observational time series. The reduced matrix was used as the input file of the Cluster analysis. The results regionalized the country into six different regions.

Rising concentration of greenhouse gases will affect both the amount and characteristics of agricultural products. Decreasing the crop's growing period, increasing the evapo-transpirations and variation in nutritional characteristics of plants are the outcomes of global warming. Currently, the general circulation models (GCMs), are widely used to anticipate future fluctuation and trend in temperature and precipitation. Since these models are in coarse scale, they may not represent the precise features of local characteristics and therefore, needed to be downscaled to be compatible with local attributes and reality. The present study was motivated to evaluate temperature and precipitation conditions in Fars province for the period 2011-2040. For achieving this goal, two distinct statistical downscaling approaches were used to downscale the outputs of the ECHAM5 model. For two scenarios of this model including 20C3M and 1PTO2X, the outputs were downscaled for the period 1951-2005. As a reasonable relationship between observed data and the simulated time series derived for this period, the obtained regression models were applied to downscale the data for the period of 2011-2040. According to the given results by 20C3M scenario, Fars province fasces 0.55OC increase in temperature by 2040. This increase was estimated to be around 2.35 OC using 1PTO2X scenario. Also precipitation in 20C3M and 1PTO2X scenarios, respectively, will decrease around 14 percent and increase about 19 percent for next 30-year

Increasing atmospheric CO2 concentration affects plant activities directly. In order to investigate the effect of CO2 concentration, an experiment was conducted at Research Greenhouse of College of Agriculture, Shiraz University, Shiraz, Iran. In this research, the effects of increasing CO2 concentration from 350 to 750 mg/L were studied on growth and yield of red bean (Phaseolus vulgaris, cv. Naz) at four irrigation levels (1.2 FC, FC, 0.8 FC and 0.6 FC). In order to control CO2 concentration, at the onset of the 4-leaf stage, pots were moved to wooden chambers covered with plastic. The results showed an average 15% decrease in evapotranspiration due to increasing the CO2 concentration. Also the results indicated an increasing effect of CO2 concentration on growth and yield of bean plants. Reducing the irrigation level to 0.6 FC caused the elevated CO2 concentration not to have any significant effect (P<0.05) on growth and yield of the red bean. By increasing the CO2 concentration, number of seeds/plant at FC and 0.8 FC irrigation treatments increased by 13 and 11%, respectively. Moreover, increasing CO2 concentration caused 20% increase in total seed yield. Total dry matter increased about 15% at higher CO2 level. The conclusion of this research was that increasing CO2 concentration has significant effect on yield and reduction of evapotranspiration of red bean.

The Madden Julian oscillation (MJO) is known as the primary mode of large-scale inter-seasonal variability in tropical regions, affectimg equatorial and sub-tropical climates. This study investigated the effects of the MJO on the occurrence of wet and dry spells in Fars province, central southern part of Iran, during November-April. Monthly precipitation data of nine stations spread over various parts of the province was analyzed during 1979-2005. Using two well-known MJO indices: MK and WH, the positive and negative phases of the MJO phases (enhanced and suppressed convective activity over the equatorial Indonesian region, respectively) were identified for monthly and seasonal scales. Precipitation-MJO composites were then constructed for the opposite phases. It was shown that for all the considered stations, seasonal precipitation during negative MJO phase was significantly greater (from about 2.5 to 6.0 folds) than the corresponding values during the positive phase. Moreover, the applied statistical tests proved that the frequency of wet or dry events was related to the prevalence of negative or positive MJO phase, respectively. As the positive MJO phase was engulfed, the probability of dry events varied from 60% to 84%. On the other hand, the probability of wet events was found to vary from 60% to 76% during the MJO negative phase.

Article abstract:Qanats of Arsenjan City, 130 km northeast of Shiraz, I.R. Iran, are the most important source of supplying water for its vast irrigated farm fields. Of these, the Katak Qanat, with the base flow of 20 l/s, situated 7.5 km west of the city, was singled out for our study. The physical characteristics of this qanat, namely its geology, discharge, bed slope, water surface slope, the length of wet (tareh–kar in Farsi) and dry (khoshkeh–kar in Farsi) galleries were measured using the field survey techniques. The collected data were analyzed to assess the possibility of damming its base flow during the off season when it is wasted. The preliminary results confirm our hypothesis that this is a practicable technique in water resources management in a large expanse of Iran where water is the country’s economic mainsta