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Showing 3 results for Aquifer
Mohammadreza Jafari, Shamsullah Asgari,
Volume 8, Issue 2 (9-2021)
Volume 8, Issue 2 (9-2021)
Abstract
One of the causes of environmental hazards is the change in the pattern of surface water flow in floodplains following the construction of flood Spreading networks. The purpose of this study is to prepare a zoning map of vulnerable areas of the flood Spreading station of Musian plain in Ilam province after the implementation of the aquifer project in this plain. To prepare this map, five factors influencing the change in flow pattern including elevation, slope, flow direction, geological formations, and landuse change were examined. Then, in the GIS environment, each class of the mentioned factors was given a score of zero to 10 based on the range and the corresponding weight layers were created. Then, by combining the created weight layers, the vulnerability zoning map of the area was created based on 5 classes: very low, low, medium, high and very high. The results showed that the most important threat and danger factor is the concentration of waterways behind erosion-sensitive embankments. Also, the study area in terms of vulnerability includes three classes with medium risk, high and very high and covers 16, 62 and 22% of the area, respectively. Flood and upland Spreading areas, risk areas and lowland lands are the most vulnerable parts of the basin in terms of floods and sedimentary deposits.
Mis Vajihe Gholizade, Dr Amir Saffari, Dr Ali Ahmadabadi, Dr Amir Karam,
Volume 8, Issue 4 (1-2021)
Volume 8, Issue 4 (1-2021)
Abstract
Introduction: Assessing the vulnerability and pollution of the aquifer is necessary for the management, development and allocation of land use, quality monitoring, prevention and protection of groundwater pollution. The purpose of this research is to identify and analyze the qualitative vulnerability of the Mashhad plain aquifer in order to monitor and manage underground water resources and prevent its future pollution.
Methodology: Mashhad plain is located in the northeast of Iran between Binaloud and Hezarmasjed mountains and in the watershed of the Kasfroud river, and its area is 2527 square kilometers. In this research, the vulnerability of the Mashhad Plain aquifer was evaluated with DRASTIC and SI models, and ArcGIS was used to analyze the parameters and prepare the vulnerability map. DRASTIC model is one of the overlap and index methods. In this method, the seven measurable parameters for the hydrogeological system include the depth of the groundwater level(D), net recharge(R), aquifer environment(A), soil environment(S), topography(T), Impact of the unsaturated Zone(I) and hydraulic conductivity(C) is used. The ratings for the sub-layers of each criterion vary from one to ten depending on their impact on the vulnerability potential. In SI method, five parameters of groundwater depth(D), net recharge (R), aquifer lithology(A), topography(T) and landuse(LU) are used for aquifer vulnerability. After preparing the SI model layers and weighting each of the layer classes using the functions available in the ArcGIS, the sensitivity index is obtained from the weighted sum of the mentioned parameters.
Conclusion: Study area is divided into four zones with very low vulnerability(21.85%), low(32.09%), medium to low(31.05%) and medium to high vulnerability(14.59%). Also, based on the results of the SI model, the study area is divided into five areas with very low vulnerability(0.4%), low(24.63%), medium to low(23.98%), medium to high(18.71%) and high vulnerability(32.25%). In general, the vulnerability of the aquifer increases from the southeast to the northwest.For verification, statistical method and calculation of correlation coefficient between vulnerability maps and TDS layer was used in TerrSet software and the results showed that both DRASTIC and SI models have high accuracy in zoning the vulnerability of Mashhad plain aquifer, so that the correlation coefficient of vulnerability maps with index The quality of TDS in Drastic model is (0.996) and in SI model (0.995); Therefore, the results of the following research can be used in environmental assessments and analysis of various pollutions and can be used as a basis for management decisions.
Fateme Emadoddin, Dr Amir Safari,
Volume 9, Issue 4 (3-2023)
Volume 9, Issue 4 (3-2023)
Abstract
Vulnerability assessment of karst aquifer using COP and PI model (Case study: Bisotun and Paraw aquifers)
Introduction
Drinking karst water resources, especially in arid and semi-arid regions, like Iran, are considered as valuable and strategic water resources. A sharp decrease in rainfall reduces the quality and quantity of karst water sources (Christensen et al., 2007). On the other hand, urban and industrial development, which is accompanied by the increase in population growth, increases the risk of underground water pollution caused by the dumping of chemicals, waste and change of use (McDonald et al., 2011). Protection of karst aquifer is one of the most important measures in the management of karst water resources due to its vulnerability and high sensitivity to pollution (Khoshakhlagh et al., 2014, Afrasiabian, 2007). Therefore, With the advancement of geographic information system technology, rapid progress was made in the ability to identify and model groundwater pollution, as well as the vulnerability of water sources from these pollutants (Babiker et al., 2004, Rahman, 2008). The pollution potential decreases from the center to the periphery (Saffari et al., 2021).
Materials and methods
In this study to evaluate the vulnerability of Bisotun and Paraw aquifer which is karstically developed and has, crack and fissure and various landforms; COP and PI vulnerability models have been used to identify areas at risk of contamination. The COP model includes three main factors including concentration of flow (C), overlaying layers (O) and precipitation (P). Factor C, which indicates surface features (Sf), slope and vegetation (Sv). It was obtained between 0.8-0.0 in 5 classes. From the overlap of the subfactores soil, layer index and lithology, the O factor map was prepared in three classes, including class 2 with low protection value, 2-4 with medium protection value and 4-8 with high protection value. The P factor, which is the temporal distribution of precipitation along with the intensity and duration of precipitation, can show the ability of precipitation to transfer pollutants from the surface to the underground water. P factor was 0.8 in 2 layers in the northwest of the study area and 0.8-0.9 with low protection value. Furthermore, top Soil, precipitation, net recharge, fracture density, bedrock and lithology maps were used for the protective cover factor (P) in the PI model. The zoning of the P factor showed 2 classes such as very low and low most of the study area is in the low class. The infiltration condition factor (I) using the characteristics of the soil, the slope layer, and the land use in four layers showed high, aamedium, low, very low, which due to the high slope of the area of the high layer has the highest dispersion, which causes the reduction of the protective cover.
Results and discussion
Consequently, COP vulnerability map in 5 classes with very high vulnerability (0-0.5) equal to 38774.74 hectares (41.4%) and very low vulnerability (4-9-4) with 57.86 hectares (0.06%) of the largest and smallest area respectively. Also, the PI vulnerability map of the combination of these two factors showed very high vulnerability with the largest area of about 68,783 hectares and 72.9% scattered throughout the study area and the high vulnerability class with an area of about 25,526 hectares and 27%.
Conclusion
The results of this research showed that the simulation performance of each COP and PI vulnerability model is closely related to the amount of pollution in the environment. It seems that the COP vulnerability model can better and more accurately showed the level of vulnerability in the karst aquifers of Bisotun and Paraw.
Keywords: karst aquifer, Bisotun and Paraw, COP model, PI model, vulnerability.
Introduction
Drinking karst water resources, especially in arid and semi-arid regions, like Iran, are considered as valuable and strategic water resources. A sharp decrease in rainfall reduces the quality and quantity of karst water sources (Christensen et al., 2007). On the other hand, urban and industrial development, which is accompanied by the increase in population growth, increases the risk of underground water pollution caused by the dumping of chemicals, waste and change of use (McDonald et al., 2011). Protection of karst aquifer is one of the most important measures in the management of karst water resources due to its vulnerability and high sensitivity to pollution (Khoshakhlagh et al., 2014, Afrasiabian, 2007). Therefore, With the advancement of geographic information system technology, rapid progress was made in the ability to identify and model groundwater pollution, as well as the vulnerability of water sources from these pollutants (Babiker et al., 2004, Rahman, 2008). The pollution potential decreases from the center to the periphery (Saffari et al., 2021).
Materials and methods
In this study to evaluate the vulnerability of Bisotun and Paraw aquifer which is karstically developed and has, crack and fissure and various landforms; COP and PI vulnerability models have been used to identify areas at risk of contamination. The COP model includes three main factors including concentration of flow (C), overlaying layers (O) and precipitation (P). Factor C, which indicates surface features (Sf), slope and vegetation (Sv). It was obtained between 0.8-0.0 in 5 classes. From the overlap of the subfactores soil, layer index and lithology, the O factor map was prepared in three classes, including class 2 with low protection value, 2-4 with medium protection value and 4-8 with high protection value. The P factor, which is the temporal distribution of precipitation along with the intensity and duration of precipitation, can show the ability of precipitation to transfer pollutants from the surface to the underground water. P factor was 0.8 in 2 layers in the northwest of the study area and 0.8-0.9 with low protection value. Furthermore, top Soil, precipitation, net recharge, fracture density, bedrock and lithology maps were used for the protective cover factor (P) in the PI model. The zoning of the P factor showed 2 classes such as very low and low most of the study area is in the low class. The infiltration condition factor (I) using the characteristics of the soil, the slope layer, and the land use in four layers showed high, aamedium, low, very low, which due to the high slope of the area of the high layer has the highest dispersion, which causes the reduction of the protective cover.
Results and discussion
Consequently, COP vulnerability map in 5 classes with very high vulnerability (0-0.5) equal to 38774.74 hectares (41.4%) and very low vulnerability (4-9-4) with 57.86 hectares (0.06%) of the largest and smallest area respectively. Also, the PI vulnerability map of the combination of these two factors showed very high vulnerability with the largest area of about 68,783 hectares and 72.9% scattered throughout the study area and the high vulnerability class with an area of about 25,526 hectares and 27%.
Conclusion
The results of this research showed that the simulation performance of each COP and PI vulnerability model is closely related to the amount of pollution in the environment. It seems that the COP vulnerability model can better and more accurately showed the level of vulnerability in the karst aquifers of Bisotun and Paraw.
Keywords: karst aquifer, Bisotun and Paraw, COP model, PI model, vulnerability.
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