Pub Date : 2019-06-01DOI: 10.22059/JDESERT.2019.72445
A. Karbassi, Mohsen Maghrebi, R. Lak, R. Noori, M. Sadrinasab
Long marine sedimentary cores can be effective in paleo-climate reconstruction. The present research aims at analyzing the temporal variation of temperature as an important climate parameter and also variations in metal concentrations (As, Ba, Cd, Li, Mo, Mg, Mn, Na, Pb, Sr, Zn, Fe, Ca, Al) of two long sedimentary cores at the Persian Gulf back to the Holocene. The obtained results revealed that the average elemental concentrations, apart from Ni, Sr, Ca and Na, are less than the shale value in both sedimentary cores. Moreover, the amount of varies from -1.31 versus 1.02 in Bushehr, to -1.69 versus 1.56 in Bandar Abbas sedimentary cores, respectively. In addition, change from -3.63 Vs -2.02 in Bushehr to -3.79 Vs -1.36 in Bandar Abbas sedimentary cores, respectively. Abrupt change in and can be seen in both sedimentary cores at two different periods (3000 to 5000 and 8000 to 9000 years ago). The maximum increase in temperature in sedimentary cores was at 0.4°C per 100 years in Bushehr and 0.01°C per 100 years in Bandar Abbas. The minimum temperature reached to -0.8°C per 100 years in Bushehr to -0.02°C per 100 years in Bandar Abbas sedimentary cores. Compared to the previously obtained temperatures in this research, there has been temperature changes in the last 40 years in the Persian Gulf, which indicates that the recent rate change in sea water temperature has been unprecedented.
{"title":"Application of sediment cores in reconstruction of long-term temperature and metal contents at the northern region of the Persian Gulf","authors":"A. Karbassi, Mohsen Maghrebi, R. Lak, R. Noori, M. Sadrinasab","doi":"10.22059/JDESERT.2019.72445","DOIUrl":"https://doi.org/10.22059/JDESERT.2019.72445","url":null,"abstract":"Long marine sedimentary cores can be effective in paleo-climate reconstruction. The present research aims at analyzing the temporal variation of temperature as an important climate parameter and also variations in metal concentrations (As, Ba, Cd, Li, Mo, Mg, Mn, Na, Pb, Sr, Zn, Fe, Ca, Al) of two long sedimentary cores at the Persian Gulf back to the Holocene. The obtained results revealed that the average elemental concentrations, apart from Ni, Sr, Ca and Na, are less than the shale value in both sedimentary cores. Moreover, the amount of varies from -1.31 versus 1.02 in Bushehr, to -1.69 versus 1.56 in Bandar Abbas sedimentary cores, respectively. In addition, change from -3.63 Vs -2.02 in Bushehr to -3.79 Vs -1.36 in Bandar Abbas sedimentary cores, respectively. Abrupt change in and can be seen in both sedimentary cores at two different periods (3000 to 5000 and 8000 to 9000 years ago). The maximum increase in temperature in sedimentary cores was at 0.4°C per 100 years in Bushehr and 0.01°C per 100 years in Bandar Abbas. The minimum temperature reached to -0.8°C per 100 years in Bushehr to -0.02°C per 100 years in Bandar Abbas sedimentary cores. Compared to the previously obtained temperatures in this research, there has been temperature changes in the last 40 years in the Persian Gulf, which indicates that the recent rate change in sea water temperature has been unprecedented.","PeriodicalId":11118,"journal":{"name":"Desert","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42412029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-01DOI: 10.22059/JDESERT.2019.72441
Hesam Ahmady-Birgani, J. Engelbrecht, Masoud Bazgir
A major question is whether different source regions across the Middle East account for changes in aerosol and dust particle characteristics, which impact Western Iran. Therefore, over a period of sampling from April 2017 to April 2018, dust particles were collected in Western Iran from different cities including Urmia, Sanandaj, Sare-Pole-Zahab, Dehloran and Abadan. The research aim is to compare the chemical compositions of dust and aerosol samples collected during the dust events from the different regions. Results of the analysis of components indicate that during dust events, the concentrations of major and trace elements change. The variability of chemical species during dust events, noted by tracking the dust plumes in satellite images, was also assessed and the results related to the different source areas, namely the dry lands of North-Western Iraq and the desert areas of South-Eastern Syria, some parts of Kuwait and KSA (around the Persian Gulf). Generally, the results show, different source regions across the Middle East have individual chemical compositions with different abundances.
{"title":"How different source regions across the Middle East change aerosol and dust particle characteristics","authors":"Hesam Ahmady-Birgani, J. Engelbrecht, Masoud Bazgir","doi":"10.22059/JDESERT.2019.72441","DOIUrl":"https://doi.org/10.22059/JDESERT.2019.72441","url":null,"abstract":"A major question is whether different source regions across the Middle East account for changes in aerosol and dust particle characteristics, which impact Western Iran. Therefore, over a period of sampling from April 2017 to April 2018, dust particles were collected in Western Iran from different cities including Urmia, Sanandaj, Sare-Pole-Zahab, Dehloran and Abadan. The research aim is to compare the chemical compositions of dust and aerosol samples collected during the dust events from the different regions. Results of the analysis of components indicate that during dust events, the concentrations of major and trace elements change. The variability of chemical species during dust events, noted by tracking the dust plumes in satellite images, was also assessed and the results related to the different source areas, namely the dry lands of North-Western Iraq and the desert areas of South-Eastern Syria, some parts of Kuwait and KSA (around the Persian Gulf). Generally, the results show, different source regions across the Middle East have individual chemical compositions with different abundances.","PeriodicalId":11118,"journal":{"name":"Desert","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48443803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-01DOI: 10.22059/JDESERT.2019.72442
Abdolrahman Ghazi, A. Karimi, G. Haghnia, S. Hojati
The objectives of this study were to determine the nature (aeolian vs. alluvial) and origin of sandy sediments in southwestern Iran (Khuzestan province) were collected in two transects across (NW-SE directions) and perpendicular to the Karkheh River, by using grain sized distribution characteristics, and the mineralogy and micro-texture of quartz grains of forty-five surface samples (0-30cm) at interval distances of ~1.5km. Standard sieves (0.5phi-intervals) were used for determining sand fractions. Silt and clay fractions were measured using the pipette method. Mineralogical composition and surface micro-texture of quartz grains of the selected samples were examined using a polarizing microscope and a scanning electron microscope, respectively. Mz (mean grain size) varied between 1.82 to 4.56f. The variations of Mz indicated the directional particle size fining the NW-SE transect. Sorting (dI) was 0.46 to 2f and with an average of 0.97f was poorly to well sorted. [FE1] The mean value of skewness (SKI) was 0.12 which ranged from -0.24 to 0.46 and skewed to fine particles. Kurtosis with mean values of 1.21 varied between 0.85 to 2.25, which indicated a slight leptokurtic. Grain size characteristics showed a disturbance near the river due to the fluvial processes. Quartz grains were rounded and evidences of both aeolian and fluvial processes were observed on the grains’ micro-texture. The mineralogy of sediments were similar to those in Saudi Arabia. This mineralogical similarity, as well as prevailing wind direction and grain size variations, indicates the possibility of the sediments to have likely originated from the Arabian plate.
{"title":"Grain size and mineralogical studies of sandy sediments in southwestern Iran","authors":"Abdolrahman Ghazi, A. Karimi, G. Haghnia, S. Hojati","doi":"10.22059/JDESERT.2019.72442","DOIUrl":"https://doi.org/10.22059/JDESERT.2019.72442","url":null,"abstract":"The objectives of this study were to determine the nature (aeolian vs. alluvial) and origin of sandy sediments in southwestern Iran (Khuzestan province) were collected in two transects across (NW-SE directions) and perpendicular to the Karkheh River, by using grain sized distribution characteristics, and the mineralogy and micro-texture of quartz grains of forty-five surface samples (0-30cm) at interval distances of ~1.5km. Standard sieves (0.5phi-intervals) were used for determining sand fractions. Silt and clay fractions were measured using the pipette method. Mineralogical composition and surface micro-texture of quartz grains of the selected samples were examined using a polarizing microscope and a scanning electron microscope, respectively. Mz (mean grain size) varied between 1.82 to 4.56f. The variations of Mz indicated the directional particle size fining the NW-SE transect. Sorting (dI) was 0.46 to 2f and with an average of 0.97f was poorly to well sorted. [FE1] The mean value of skewness (SKI) was 0.12 which ranged from -0.24 to 0.46 and skewed to fine particles. Kurtosis with mean values of 1.21 varied between 0.85 to 2.25, which indicated a slight leptokurtic. Grain size characteristics showed a disturbance near the river due to the fluvial processes. Quartz grains were rounded and evidences of both aeolian and fluvial processes were observed on the grains’ micro-texture. The mineralogy of sediments were similar to those in Saudi Arabia. This mineralogical similarity, as well as prevailing wind direction and grain size variations, indicates the possibility of the sediments to have likely originated from the Arabian plate.","PeriodicalId":11118,"journal":{"name":"Desert","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49157587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-01DOI: 10.22059/JDESERT.2019.72446
Z. Rafieemajoomard, M. Rahimi, S. Nikoo, H. Memarian, S. Kaboli
In this research, two techniques of pixel-based and object-based image analysis were investigated and compared for providing land use map in arid basin of Mokhtaran, Birjand. Using Landsat satellite imagery in 2015, the classification of land use was performed with three object-based algorithms of supervised fuzzy-maximum likelihood, maximum likelihood, and K-nearest neighbor. Nine combinations were examined in terms of scale level (SL10, SL30, and SL50) and the nearest neighborhood (NN3, NN5, and NN7) in an object-based classification. Ultimately, the validity was evaluated through the usage of two disagreement components including allocation disagreement and quantity disagreement. Results of maximum likelihood classification showed higher overall inaccuracycompared to images categorized based on fuzzy-maximum likelihood and object-based nearest neighbor algorithms. The SL30-NN3 object-based classifier decreased the quantity disagreement by 290% compared to the maximum likelihood and 265% compared to fuzzy-maximum likelihood classifiers. For allocation disagreement, these values were equal to 36% and 19%, respectively. Thus, object-based classification had a better performance in land-use classification of Mokhtaran basin.
{"title":"Comparing pixel-based and object-based algorithms for classifying land use of arid basins (Case study: Mokhtaran Basin, Iran)","authors":"Z. Rafieemajoomard, M. Rahimi, S. Nikoo, H. Memarian, S. Kaboli","doi":"10.22059/JDESERT.2019.72446","DOIUrl":"https://doi.org/10.22059/JDESERT.2019.72446","url":null,"abstract":"In this research, two techniques of pixel-based and object-based image analysis were investigated and compared for providing land use map in arid basin of Mokhtaran, Birjand. Using Landsat satellite imagery in 2015, the classification of land use was performed with three object-based algorithms of supervised fuzzy-maximum likelihood, maximum likelihood, and K-nearest neighbor. Nine combinations were examined in terms of scale level (SL10, SL30, and SL50) and the nearest neighborhood (NN3, NN5, and NN7) in an object-based classification. Ultimately, the validity was evaluated through the usage of two disagreement components including allocation disagreement and quantity disagreement. Results of maximum likelihood classification showed higher overall inaccuracycompared to images categorized based on fuzzy-maximum likelihood and object-based nearest neighbor algorithms. The SL30-NN3 object-based classifier decreased the quantity disagreement by 290% compared to the maximum likelihood and 265% compared to fuzzy-maximum likelihood classifiers. For allocation disagreement, these values were equal to 36% and 19%, respectively. Thus, object-based classification had a better performance in land-use classification of Mokhtaran basin.","PeriodicalId":11118,"journal":{"name":"Desert","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46427063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-01DOI: 10.22059/JDESERT.2019.72448
Z. Feizi, A. Keshtkar, A. Afzali
The main portion of water demands of arid regions like Kashan Plain, Iran supply by groundwater wells. This research was conducted to assess the groundwater quality as well as modelling and mapping groundwater quality in the study area using geosatistics and deterministic techniques. Five water quality parameters, including Electrical Conductivity, Sodium Adsorption Ratio, Total Hardness, Total Dissolved Solids and pH, were applied to determine the irrigation and drinking water quality index using the Wilcox diagram and WHO standards. The final map indicated that the groundwater quality increased from north to south of the study area. The areas located in the centre, south and eastern south of the study area had the optimum quality for irrigation and drinking purposes. Furthermore, based on the results of zoning using the Wilcox diagram determined that ground water quality of the study area 22%, 42% and 36% were good, medium and non-suitable, respectively
{"title":"Using geostatistical and deterministic modelling to identify spatial variability of groundwater quality","authors":"Z. Feizi, A. Keshtkar, A. Afzali","doi":"10.22059/JDESERT.2019.72448","DOIUrl":"https://doi.org/10.22059/JDESERT.2019.72448","url":null,"abstract":"The main portion of water demands of arid regions like Kashan Plain, Iran supply by groundwater wells. This research was conducted to assess the groundwater quality as well as modelling and mapping groundwater quality in the study area using geosatistics and deterministic techniques. Five water quality parameters, including Electrical Conductivity, Sodium Adsorption Ratio, Total Hardness, Total Dissolved Solids and pH, were applied to determine the irrigation and drinking water quality index using the Wilcox diagram and WHO standards. The final map indicated that the groundwater quality increased from north to south of the study area. The areas located in the centre, south and eastern south of the study area had the optimum quality for irrigation and drinking purposes. Furthermore, based on the results of zoning using the Wilcox diagram determined that ground water quality of the study area 22%, 42% and 36% were good, medium and non-suitable, respectively","PeriodicalId":11118,"journal":{"name":"Desert","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46547836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-01DOI: 10.22059/JDESERT.2019.72432
S. Ahmadi, H. Azarnivand, H. Khosravi, P. Dehghana, M. B. Manesh
Drought is a disaster phenomenon especially in arid and semi-arid areas. Vegetation and its production play a main role in the social and economic issues in every country. In this study, Standardized Precipitation Index (SPI) and Normalized Difference Vegetation Index (NDVI) data have been used to monitor drought and the vegetation condition in Sonqor Abad in, Kermanshah province. Meteorological station data in the study area was used to study the SPI as a drought index. The maps of NDVI and also land use changes were provided using Landsat-TM images for 2001, 2008 and Landsat 8 images for 2015 in ENVI software environment. The obtained results showed that the land uses of cultivation and fallow have decreased and rangeland, urban and rock mass have increased. On the other hand, the dense of rainfall in the vegetation density has increased in this area during 2001 until 2015. Due to population growth and expansion of urban areas, the farm and garden lands have decreased around the city during this period. The correlation was found between vegetation density in mid-spring and the annual SPI of last year. Therefore, it can be concluded that there is a direct relationship between rainfall and the density of vegetation. By increasing the amount of rainfall and SPI, the vegetation density is increased. Based on the results, it is recommended that in addition to using meteorological data, satellite images should be used for monitoring the drought.
{"title":"Assessment the effect of drought and land use change on vegetation using Landsat data","authors":"S. Ahmadi, H. Azarnivand, H. Khosravi, P. Dehghana, M. B. Manesh","doi":"10.22059/JDESERT.2019.72432","DOIUrl":"https://doi.org/10.22059/JDESERT.2019.72432","url":null,"abstract":"Drought is a disaster phenomenon especially in arid and semi-arid areas. Vegetation and its production play a main role in the social and economic issues in every country. In this study, Standardized Precipitation Index (SPI) and Normalized Difference Vegetation Index (NDVI) data have been used to monitor drought and the vegetation condition in Sonqor Abad in, Kermanshah province. Meteorological station data in the study area was used to study the SPI as a drought index. The maps of NDVI and also land use changes were provided using Landsat-TM images for 2001, 2008 and Landsat 8 images for 2015 in ENVI software environment. The obtained results showed that the land uses of cultivation and fallow have decreased and rangeland, urban and rock mass have increased. On the other hand, the dense of rainfall in the vegetation density has increased in this area during 2001 until 2015. Due to population growth and expansion of urban areas, the farm and garden lands have decreased around the city during this period. The correlation was found between vegetation density in mid-spring and the annual SPI of last year. Therefore, it can be concluded that there is a direct relationship between rainfall and the density of vegetation. By increasing the amount of rainfall and SPI, the vegetation density is increased. Based on the results, it is recommended that in addition to using meteorological data, satellite images should be used for monitoring the drought.","PeriodicalId":11118,"journal":{"name":"Desert","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44577241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-01DOI: 10.22059/JDESERT.2019.72443
F. Abdi, S. S. Moosavi, M. Abdollahi, S. Enferadi, M. Maleki
Triticum boeoticum wild wheat is a remarkable gene pool to environmental stress resistance. It is one of the most valuable species of the Triticeae tribe for improving wheat cultivars to moisture-stress. This research was carried out to assess the changes and responses of different traits of 10 accessions of Triticum boeoticum under non-stress and imposed moisture stress conditions in 2015 and 2016. Most traits were significantly affected by accession (A), water treatments (WT), and A×WT interactions. The accessions showed a high-level of genetic diversity for all traits, except peduncle weight. The accessions Tb5 and TB3 with the highest amount of economic yield per plant (EYPP) and water use efficiency (WUE), were less affected by the imposed moisture stress, while accession Tb6 with the maximum amount of water use (WU), main root length (MRL) and some phenological traits, were the most affected. The traits of WUE and main stem weight (MSTW) showed the highest and the traits of excised leaf water retention (ELWR), MRL and WU showed the lowest alignment with EYPP, respectively. The ability of producing assimilates (by increasing biological yield per plant and MSTW) and the ability of faster assimilates-remobilization into grains (by increasing harvest index and WUE), has been a neglected aspect of breeding wheat program under drought stress. In other words, the ability of a genotype to produce more assimilates and allocate it to grains (by increased BYPP and WUE, respectively) instead of belowground-traits, will result to increase EYPP. For example, the Tb6 ecotype, due to the allocation of more assimilates to underground parts, had little grain yield. While the traits of WUE, BYPP, seed number per main spike, seed weight per main spike (SWPMS) and main spike weight (MSPW) showed a positive and significant (P<0.01) correlation to EYPP, the traits of ELWR, MRL, day to heading and day to anthesis, had a negative and significant (P<0.05) correlation with yield. Generally, a high amount of WUE, MSTW, SWPMS, MSPW and peduncle weight; with a low amount of ELWR, phenological traits (except grain filling period), MRL, WU, and root to shoot dry weight ratio (RDWSDW) were suggested for the improvement of grain yield. SWPMS and MSPW were two main-components of grain yield in the favorite accessions (Tb5 and Tb3). Tb5 and Tb3 may have value for breeding wheat better adapted to moisture stress conditions in future.
{"title":"Responses of above and below ground traits of 10 accessions of Triticum boeoticum to non-stress and imposed moisture stress conditions","authors":"F. Abdi, S. S. Moosavi, M. Abdollahi, S. Enferadi, M. Maleki","doi":"10.22059/JDESERT.2019.72443","DOIUrl":"https://doi.org/10.22059/JDESERT.2019.72443","url":null,"abstract":"Triticum boeoticum wild wheat is a remarkable gene pool to environmental stress resistance. It is one of the most valuable species of the Triticeae tribe for improving wheat cultivars to moisture-stress. This research was carried out to assess the changes and responses of different traits of 10 accessions of Triticum boeoticum under non-stress and imposed moisture stress conditions in 2015 and 2016. Most traits were significantly affected by accession (A), water treatments (WT), and A×WT interactions. The accessions showed a high-level of genetic diversity for all traits, except peduncle weight. The accessions Tb5 and TB3 with the highest amount of economic yield per plant (EYPP) and water use efficiency (WUE), were less affected by the imposed moisture stress, while accession Tb6 with the maximum amount of water use (WU), main root length (MRL) and some phenological traits, were the most affected. The traits of WUE and main stem weight (MSTW) showed the highest and the traits of excised leaf water retention (ELWR), MRL and WU showed the lowest alignment with EYPP, respectively. The ability of producing assimilates (by increasing biological yield per plant and MSTW) and the ability of faster assimilates-remobilization into grains (by increasing harvest index and WUE), has been a neglected aspect of breeding wheat program under drought stress. In other words, the ability of a genotype to produce more assimilates and allocate it to grains (by increased BYPP and WUE, respectively) instead of belowground-traits, will result to increase EYPP. For example, the Tb6 ecotype, due to the allocation of more assimilates to underground parts, had little grain yield. While the traits of WUE, BYPP, seed number per main spike, seed weight per main spike (SWPMS) and main spike weight (MSPW) showed a positive and significant (P<0.01) correlation to EYPP, the traits of ELWR, MRL, day to heading and day to anthesis, had a negative and significant (P<0.05) correlation with yield. Generally, a high amount of WUE, MSTW, SWPMS, MSPW and peduncle weight; with a low amount of ELWR, phenological traits (except grain filling period), MRL, WU, and root to shoot dry weight ratio (RDWSDW) were suggested for the improvement of grain yield. SWPMS and MSPW were two main-components of grain yield in the favorite accessions (Tb5 and Tb3). Tb5 and Tb3 may have value for breeding wheat better adapted to moisture stress conditions in future.","PeriodicalId":11118,"journal":{"name":"Desert","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45124249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-01DOI: 10.22059/JDESERT.2019.72431
Z. Rasaei, R. Mohajer
Although fertility capability classification (FCC) has high performance in land evaluation and soil maps interpretation, so far it has been less attended in land evaluation studies. Therefore, qualitative (FCC method) and quantitative (Riquer index) land fertility capability evaluation for Wheat and Rice cultivation and comparison of Soil Taxonomy and WRB classification with FCC were chosen as this study objective. After field and laboratory studies, the soil map was prepared with the scale of 1: 50,000. Then, FCC and Riquer methods were used to determine the land fertility capability for Wheat and Rice cultivation for each of the soil map unites. Investigations showed that the FCC and Riquer methods have presented similar results and well interpreted and classified soils. The results of Riquer method indicated that the fertility capability of these lands is good except in gravelly and shallow parts, thus Wheat and Rice can be cultivated in these soils. A comparison of the current soil classification systems and the FCC results showed that the problems and inherent characteristics of studied soils were pointed well by the FCC system, whereas they have been expressed differently in Soil Taxonomy and WRB classifications. Gleyic condition, dryness and subsoil gravel are the most limitative factors to Wheat and Rice cultivation in this area.
{"title":"Comparision of fertility capability and taxonomic classification systems to classify the soil map units in some parts of Chaharmahal-va-Bakhtiari province","authors":"Z. Rasaei, R. Mohajer","doi":"10.22059/JDESERT.2019.72431","DOIUrl":"https://doi.org/10.22059/JDESERT.2019.72431","url":null,"abstract":"Although fertility capability classification (FCC) has high performance in land evaluation and soil maps interpretation, so far it has been less attended in land evaluation studies. Therefore, qualitative (FCC method) and quantitative (Riquer index) land fertility capability evaluation for Wheat and Rice cultivation and comparison of Soil Taxonomy and WRB classification with FCC were chosen as this study objective. After field and laboratory studies, the soil map was prepared with the scale of 1: 50,000. Then, FCC and Riquer methods were used to determine the land fertility capability for Wheat and Rice cultivation for each of the soil map unites. Investigations showed that the FCC and Riquer methods have presented similar results and well interpreted and classified soils. The results of Riquer method indicated that the fertility capability of these lands is good except in gravelly and shallow parts, thus Wheat and Rice can be cultivated in these soils. A comparison of the current soil classification systems and the FCC results showed that the problems and inherent characteristics of studied soils were pointed well by the FCC system, whereas they have been expressed differently in Soil Taxonomy and WRB classifications. Gleyic condition, dryness and subsoil gravel are the most limitative factors to Wheat and Rice cultivation in this area.","PeriodicalId":11118,"journal":{"name":"Desert","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42059052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.22059/JDESERT.2018.69120
M. Samiee, R. Ghazavi, M. Pakparvar, A. Vali
Saline lakes can increase the soil and water salinity of the coastal areas. The main aim of this study is to distinguish the characteristics of the spectral reflectance of saline soil, analyze the statistical relationship between soil EC and characteristics of the spectral reflectance of saline soil, and to map soil salinity east of the Maharloo Lake. The correlation between field measurements of electrical conductivity and remote sensing spectral indices was evaluated using multiple regression analysis. In this study, Kriging, CoKriging, and multiple regressions were applied for soil salinity mapping and classification using 100 soil samples. After radiometric, geometric, and atmospheric corrections of Landsat OLI images, the statistical correlation between the electrical conductivity of field measurements and spectral reflectance was investigated. According to obtained results, the modified salinity index (MSI) with the highest correlation (R2=0.78) was used as an auxiliary variable for the coKriging method. Kriging with a spherical model was selected for soil salinity mapping (RMSE = 50.5 and R2 = 0.18). The RMSE and R2 values for CoKriging were (43.2 and 0.42), respectively. Because of their acceptable R2 (=0.65) and low standard deviation (33.8) for salinity analysis, MSI and difference vegetation index (DVI) were used to estimate and zonate soil salinity in the study area. The results showed that soil salinity could be estimated via spectral indices with acceptable accuracy, R2 and RMSE. Overall, this method leads to a decrease in the costs involved in the soil mapping of saline soil areas.
{"title":"Mapping spatial variability of soil salinity in a coastal area located in an arid environment using geostatistical and correlation methods based on the satellite data","authors":"M. Samiee, R. Ghazavi, M. Pakparvar, A. Vali","doi":"10.22059/JDESERT.2018.69120","DOIUrl":"https://doi.org/10.22059/JDESERT.2018.69120","url":null,"abstract":"Saline lakes can increase the soil and water salinity of the coastal areas. The main aim of this study is to distinguish the characteristics of the spectral reflectance of saline soil, analyze the statistical relationship between soil EC and characteristics of the spectral reflectance of saline soil, and to map soil salinity east of the Maharloo Lake. The correlation between field measurements of electrical conductivity and remote sensing spectral indices was evaluated using multiple regression analysis. In this study, Kriging, CoKriging, and multiple regressions were applied for soil salinity mapping and classification using 100 soil samples. After radiometric, geometric, and atmospheric corrections of Landsat OLI images, the statistical correlation between the electrical conductivity of field measurements and spectral reflectance was investigated. According to obtained results, the modified salinity index (MSI) with the highest correlation (R2=0.78) was used as an auxiliary variable for the coKriging method. Kriging with a spherical model was selected for soil salinity mapping (RMSE = 50.5 and R2 = 0.18). The RMSE and R2 values for CoKriging were (43.2 and 0.42), respectively. Because of their acceptable R2 (=0.65) and low standard deviation (33.8) for salinity analysis, MSI and difference vegetation index (DVI) were used to estimate and zonate soil salinity in the study area. The results showed that soil salinity could be estimated via spectral indices with acceptable accuracy, R2 and RMSE. Overall, this method leads to a decrease in the costs involved in the soil mapping of saline soil areas.","PeriodicalId":11118,"journal":{"name":"Desert","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41961449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-20DOI: 10.22059/JDESERT.2018.66355
A. Z. Meymand, M. B. Bodaghabadi, A. Moghimi, M. Navidi, F. E. Meymand, M. A. pour
This study was conducted to rate the land characteristics of corn in hot areas based on artificial neural networks and regression models. For this purpose, 63 corn fields were selected in southern Iran. In each farm, a pedon was excavated, described and sampled. A questionnaire was completed for each farm. A stepwise regression model was used to study the relationship between land characteristics and corn yield. A characteristic-function curve was used to rate the land characteristics. Finally, crop requirements were prepared by artificial neural network and regression models and verified by comparing the actual and predicted performance levels. The results of regression analysis showed that soil salinity, exchangeable sodium percentage, sand, clay, phosphorous, gypsum and potassium recorded the highest effect on yield and according to the artificial neural network, the exchangeable sodium percentage, soil salinity, soil texture and cation exchange capacity are the most important. Based on regression and artificial neural network methods, the threshold limit and break even production for soil salinity were 4, 2.5, 12, and 10 dS m-1, respectively, but for exchangeable sodium percentage the values were 18, 14, 35, and 30, respectively. The coefficient of determination (R2) between the actual and predicted yield based on the regression model was 0.88, but it was 0.945 (training data) and 0.837 (testing data) for the artificial neural network. Also, the results of the verification of the prepared crop requirements tables showed that the correlation of determination between the land index and the yield in the regression method was 0.78 but it was 0.81 for the artificial neural network, these results are acceptable in both methods.
{"title":"Modeling of yield and rating of land characteristics for corn based on artificial neural network and regression models in southern Iran","authors":"A. Z. Meymand, M. B. Bodaghabadi, A. Moghimi, M. Navidi, F. E. Meymand, M. A. pour","doi":"10.22059/JDESERT.2018.66355","DOIUrl":"https://doi.org/10.22059/JDESERT.2018.66355","url":null,"abstract":"This study was conducted to rate the land characteristics of corn in hot areas based on artificial neural networks and regression models. For this purpose, 63 corn fields were selected in southern Iran. In each farm, a pedon was excavated, described and sampled. A questionnaire was completed for each farm. A stepwise regression model was used to study the relationship between land characteristics and corn yield. A characteristic-function curve was used to rate the land characteristics. Finally, crop requirements were prepared by artificial neural network and regression models and verified by comparing the actual and predicted performance levels. The results of regression analysis showed that soil salinity, exchangeable sodium percentage, sand, clay, phosphorous, gypsum and potassium recorded the highest effect on yield and according to the artificial neural network, the exchangeable sodium percentage, soil salinity, soil texture and cation exchange capacity are the most important. Based on regression and artificial neural network methods, the threshold limit and break even production for soil salinity were 4, 2.5, 12, and 10 dS m-1, respectively, but for exchangeable sodium percentage the values were 18, 14, 35, and 30, respectively. The coefficient of determination (R2) between the actual and predicted yield based on the regression model was 0.88, but it was 0.945 (training data) and 0.837 (testing data) for the artificial neural network. Also, the results of the verification of the prepared crop requirements tables showed that the correlation of determination between the land index and the yield in the regression method was 0.78 but it was 0.81 for the artificial neural network, these results are acceptable in both methods.","PeriodicalId":11118,"journal":{"name":"Desert","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44035229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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