anis heydari; AliAkbar Nazari Samani; Mohsen Farzin; sadat feiznia
Abstract
1-IntroductionSubmarine Groundwater Discharge (SGD), any flow or all water flows on the continental banks of the sea bed, is defined regardless of the liquid composition and the driving force of its agent (Barnett et al., 2003). This occurs in a calm and continuous flow of SGD wherever its table has ...
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1-IntroductionSubmarine Groundwater Discharge (SGD), any flow or all water flows on the continental banks of the sea bed, is defined regardless of the liquid composition and the driving force of its agent (Barnett et al., 2003). This occurs in a calm and continuous flow of SGD wherever its table has a positive relative hydraulic gradient with the sea level, which is attached to the surface runoff. The outflow of the flow into the sea will cause a temperature anomaly on the surface. The depletion of the underground submarine currents plays a remarkable role in the water cycle, which can be considered as an important part of water balance. Therefore, it is important to identify the range of anomalies caused by the probable depletion of SGD into the sea.2-MethodologyRemote sensing systems are used to determine the site of SGD depletion into the sea or lake, including aerial images with high resolution (Lewandowski et al., 2013). The aerial manual infrared imaging (Duarte et al., 2006) or ground thermal imaging (Schuetz and Weiler, 2011) are highly expensive and are certainly not suitable to assess the regional scale or continuous monitoring of SGD depletion in large blue bodies (Wilson and Rocha, 2016). Hence, free data and images of the Landset 8 satellite for 2017 and 2018 were used to determine sea surface temperature maps. For this purpose, corrections were first applied to thermal bands in the ENVI 5.3 software environment. Then, to investigate the existence of geometrical and non-geometrical errors, the quality of the data was examined on satellite images. Analyses and extraction of sea surface temperature maps were carried out using GIS 10.3.1 software. After preparing a suitable temperature map, the least surface roughness level was determined by applying different classifications in the GIS environment. Then, the distribution of each anomaly was finally prepared to prepare the distribution map of thermal anomalies. In this study, a digital elevation model (DEM) was used in GIS software to provide geomorphometryindices and maps related to environmental variables (slope, Topographic Position Index, profile curvature, general curvature, plan curvature, and height) and statistical modeling. Finally, the layers were prepared and the required adjustments were made in the software settings. Maxent Version 3.3.3 software was then used to perform statistical modeling.3-Results and discussionSome anomalies were observed by examining the rainfall of existing pluviometry stations (n = 14) in the study area and investigating the rainfall amount (the same month, the month before, six months before, the same year, and the preceding year). The regression relationship between levels of anomalies and rainfall values determined at different times revealed a strong relationship between the anomaly levels and the amount of rainfall in the previous month. Finally, the seasons studied in 2017 and 2018, the results obtained from the study of SST, STA, and the least common level defined, along with rainfall investigations, all indicated that that the highest temperature anomalies with iterations in two different histories belonged to January 2017 and 2018, which were used for subsequent analyses. The depth studies in the range of anomalies included in January 2017 and 2018, as well as the common level of anomalies from the two dates, show that anomalies obtained in the deep-sea regions are not located and the depth of these anomalies is low within the range, which increases the probable presence of the underground spring. It can be stated that the results obtained are related to the depth of temperature anomalies because they are in the shallow depth of the sea and less than 30 meters, which is the reason to increase the likelihood of the presence of the submarine springs in these areas. According to McBride and Pfannkuch et al. (1975), Shaban et al. (2005), Thomas et al. (2002), Lewandowski et al. (2013), Wilson and Rocha (2016), and Farzin et al. (2017), SGD presence rate decreases with the distance from the shore, and the presence of submarine springs would be expected at a water level close to the shore in the disorders created at the surface of the sea, which corresponds to our results. All temperature anomalies, particularly the repeated anomalies in January 2017 and 2018 are located 3 km away from the coast, which increases the probable presence of SGD. According to the results of the jackknife test, the most important indices are in the presence of temperature anomalies and the presence of SGD (depth) and slope, which indicates that the presence of SGD spring is up to a depth of 4 meters and the appropriate slope for the presence of SGD depletion region is 5%. Figure (1): The classification map of the presence of SGD based on temperature level anomalies and environmental variables Figure (2): The Jackknife test for model sensitivity analysis4-ConclusionThe environmental factors play a role in the creation of temporal and spatial changes of SST and STA. Based on the results obtained from geomorphometrystudies and inequalities, as well as those of maxent modeling based on the common level of temperature anomalies in January 2017 and 2018, it can be concluded that anomalies occurred in the Bandar Magham, Bandar Nakhiloo, and coasts of Bandar Divan, Bandar Shenas, Bandar lengeh, and Bandar kong indicate that these areas have a very high probability of underground aquifers. These submarine currents seem to have a substantial amount of evacuation that could have significant effects on the coastal ecosystem and the regional water balance. If the quality of the evacuated water is not intrinsically salty and is desirable to be used, it can be utilized as a water supply source in the area.
Maryam Azarakhshi; Majid Aboutalebi; Ali Akbar Nazari Samani; Bahram Mohhamadi Golrang
Volume 5, Issue 17 , March 2019, , Pages 125-144
Abstract
Introduction
In arid and semi-arid areas, due to the lack of proper management of renewable natural resources, not only the proper utilization of water and soil resources is not done, but also water becomes a natural disaster, and every year, floods cause many human and financial losses. One ...
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Introduction
In arid and semi-arid areas, due to the lack of proper management of renewable natural resources, not only the proper utilization of water and soil resources is not done, but also water becomes a natural disaster, and every year, floods cause many human and financial losses. One of the integrated methods of flood control operations is flood spreading. This method improves the status of utilization of water and soil resources, plant cover, and artificial recharge of groundwater. Sediments that are carried with the flood, deposit in flood spreading region and may change the physical and chemical properties of soil over time. The most serious danger which threatens the flood spreading networks and artificial recharge schemes is the reduction of the infiltration of soil due to sedimentation. The most important factor affecting the performance of flood spreading systems is the amount of input sediment into the spreading canals, its depositing on the surface and accumulation in the depth of soil, which can change the physical and chemical properties of the soil. In this regard, current research was conducted to investigate the role of input sediments into flood spreading field, determine the penetration depth of sediments and the spatial pattern of physical and chemical changes in soil.
Materials and Methods
Kashmar flood spreading station is located in 17 km east of Kashmar, in the longitude of 58° 38' to 58° 40' of the east and latitude of 35° 15' to 35° 39' of the north. This research was conducted in the first Phase of Kashmar flood spreading. In this research, the first five channels of dewatering were divided into three study networks (outset, middle, and end), and the upstream of the spreading flood arena was considered as the control sample. In each grid, three points were selected as repeat tests and soil profiles were drilled with a depth of 1 m. In each soil profile, the soil samples from 0-50 and 50-100 cm depths were provided. At the test site, soil infiltration was determined using double rings. After transferring soil samples to the lab, the soil texture (clay, silt and sand percentages) was determined by the hydrometer method. In the laboratory, the value of the chemical parameters of the soil, including soil acidity (PH), electrical conductivity (EC), bicarbonate (HCO3ˉ), sulfate (SO4-2), chlorine (Cl), potassium (K+), and sodium (Na+) were measured. The effects of flood spreading on the physical and chemical properties of soil in spreading filed were investigated with the factorial experiment in a completely randomized block design.
Results
The results of the analysis of variance showed that there was a significant difference between the soil infiltration in channels 1 to 5 and the control arena at the probability level of 1%. However, there was no significant difference (p=%5) in soil infiltration in the start, middle, and end sections of the channels. In channels 1 to 5 and in the control arena, there was no significant difference (p=%5) in the amount of sand, silt, and clay. Flood spreading increased the amount of the clay in the depths of the channels compared to the control area. The Analysis of the variance showed all chemical properties of the soil. Except potassium, there was a significant difference (p=%1) between the dewatering channel and the control field. The amount of the variables did not change in the second depth compared to the control arena. The interaction effect between the depth and channel was not significant at 5% probability level. Thus, flood spreading did not change the chemical characteristics of soil in depth.
Discussion and Conclusion
The rate of the soil infiltration in spreading channel reduced 4.3 times of soil infiltration in the control arena. The least infiltration was observed in channels 1 and 2 due to the proximity of these channels to the source of flood and deposition of more suspended load on the surface of the soil. Because the suspended load of floods increased the clay particles and reduced the macro porosity, it decreased the soil infiltration. Flood spreading caused an increase of 1.5% in the soil acidity of the channels compared to the control arena. A 30% reduction in electrical conductivity was observed in the first two and third channels, compared to the control arena. The amount of HCO3-, Cl-, SO4-2, and Na+ reduced in the first, second, and third channels but increased in the fourth and fifth channels. The amount of potassium in all channels decreased compared to the control samples but this decrease was not significant. In general, flood spreading in Kashmar site caused the diminution of soil infiltration, which had a negative effect on flood spreading system. Therefore, it is recommended that water spreading channels are plowed every year to increase soil permeability.
