Geostatiscal analysis of groundwater quality index (Case study: Marvdasht-Kharameh aquifer, Fars)

One method of groundwater quality assessment is applying Groundwater quality index (GWQI), which is a combinational method of different quality parameters of groundwater. The aim of this study was to estimate the Marvdasht-Kharameh Plain groundwater quality for drinking by employing GWQI along with applying geostatistics technology in GIS environment. For this purpose, the norm of five years quality data of 49 wells were used. GWQI was estimated by applying inverse distance weighting method to quality parameters. Kriging geostatistics pattern was used for assessing spatial changes and mapping the quality parameters and GWQI. Spherical variogram pattern had the best fitting on quality parameters and GWQI. The results illustrated that spherical variogram pattern with 19200 m effective range is appropriate for GWQI. Based on sensitivity analysis, EC, TDS, and Mg had the most and pH, sulphate and TA had the least influence on GWQI. The GWQI range was variable from 47 to 1000. Upon to GWQI map, the north-western parts of Marvdasht-Kharameh Plain aquifer had suitable quality for drinking while it was not suitable to use in southern parts of aquifer

Land use optimization using the fuzzy mathematical-spatial approach: a case study of Chelgerd watershed, Iran

In recent years, inappropriate land use, urban and industrial development along with different pollutions emanating from it gives rise to loss of natural resources and further leads to destructive floods, soil erosion, sedimentation and other various environmental, economic and social damages. Thus, management and planning are essential for the proper utilization, protection and revival of these resources. This study aimed to develop a mathematical-spatial optimum utilization model using FGP – MOLA in watershed including environmental and economic objectives while considering social issues. The results showed that the proposed model can lead to economic growth to 37% and decreasing the environmental damages to 2.4%. Under optimized condition, the area allocated to dry farming lands will decrease about 12% and gardens will increase about 423% and the other land uses remain unchanged too. In addition to, the results demonstrated the usefulness and efficiency of the proposed fuzzy model due to its flexibility and capability to simultaneously provide both optimum values and location of production resources

Qualitative Assessment and Mapping of Corrosion and Sedimentation Potential of Marvdasht Groundwater

Determination of corrosion and scaling potential is one of the most important quality aspects of groundwater resources in different uses. Therefore, the aim of this research work was to determine the corrosion and scaling potential of Marvdasht Plain groundwater using Langelier saturation and Ryznar stability indices and their mapping through GIS. For this purpose, 49 agricultural wells were sampled for five years and total hardness (TH), total dissolved solids (TDS), total alkalinity (TA) and pH were measured. The ordinary kriging geostatistical method was applied for mapping the Langelier saturation and Ryznar stability indices and their components. The results showed that the spherical model was most fitted for these indices. The eefective domin varied from 15752 to 32711 m for the components and the spatial correlation class changed from good to fair. The mean Langelier index was 0.58 showing low to fair scaling potential. The mean Ryznar index was 6.2 indicating low corrosion potential of Marvdasht Plain Aquifer. Based on the zoning maps, the northern parts of the area showed the highest TH and TDS components followed by Langelier index, showing fair scaling potential. In this part, the effect of carbonate formations was evaluated as the probable contributor of the increasing the Langelier index. In general, the Marvdasht groundwater has fair quality in terms of corrosion and scaling potential

Regional Frequency Analysis of Low Flow in Parts of the Northern Karun River Basin in Chaharmahal and Bakhtiari Province

Hydrological droughts reduce groundwater and surface water, lakes and rivers. The purpose of the present study was to analyze the minimum regional flow frequency in parts of the northern Karun basin in Chaharmahal and Bakhtiari province. For this purpose, 11 hydrometric stations were used. For the minimum flow estimation, 15 different physiographic, climatic and hydrological features of the basin were used in. At first, hydrometric stations were divided into two homogeneous groups using cluster analysis method. Then, using principal component analysis (PCA), the most important features were selected for each region among the 15 physiographic, climatic and hydrological characteristics. Finally, the models for estimating the minimum flow of each region were developed using stepwise regression method in return periods of 2, 10, 25 and 50 years. The results showed that the characteristics of the basin area with a weight of 0.347, elongation coefficient with a weight of 0.389, a length of the basin with a weight of 0.326 and a coefficient of roundness with a weight of 0.326 were the most important features in the estimation of minimum flow. In general, all regression-logarithmic models in the two regions for all rounds of returns with a coefficient of greater than 0.96 were considered to have a good performance for minimum flow estimation

GIS and multi-criteria decision-making analysis assessment of land suitability for rapeseed farming in calcareous soils of semi-arid regions

To reverse the negative environmental properties effect on fertile lands for agriculture, land suitability evaluation is the first step in the designing the most sustainable land use and management systems. The aim of the present study was to develop and evaluate a land suitability model for rapeseed farming using topography factors, soil data and remote sensing data in calcareous soils of semi-arid regions northwestern Iran. For this purpose, stratified random sampling was used to select a set of 92 soil samples of agricultural land use from 0 to 30 cm depth. For land suitability assessment, the opinions of 19 local experts were used to make a decision for the weight of topography, soil data and remote sensing data factors by an analytic hierarchy process (AHP) from multi-criteria analysis. The input data including climate, topography, soil and remote sensing data were included that are related to rapeseed production. The results indicate the highest specific weight belongs to the soil texture (0.341), calcium carbonate equivalent (0.171) and elevation (0.114), respectively. Land suitability evaluation based on the United Nations Food and Agriculture Organization classification system indicated that 0.81% (420.8 ha) of the studied area was for high suitable (S1), 42.33% (21940.2 ha) was for moderately suitable (S2) and 11.78% (6104 ha) was for marginally suitable (S3) class. The 39.72% (20586.4) and 0.95% (492.1 ha) of studied area were located as currently not-suitable and permanently not-suitable for rapeseed productions, respectively

Numerical modelling of flow patterns in meandering river channels

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Fractal Features of Soil Particles as an Indicator of Land Degradation under Different Types of Land Use at the Watershed Scale in Southern Iran

Soil particle-size distribution (PSD) is an important soil feature that is associated with soil erosion, soil fertility, and soil physical and chemical properties. However, very few studies have been carried out to investigate soil degradation using the fractal dimension (D) of the PSD of soils from different land-use types in the calcareous soil of Iran. For this study, 120 soil samples (0–20 cm) were collected from different land-use types in the Fars Province, and various basic soil properties such as soil organic matter (SOM), soil texture fractions, calcium carbonate (CaCO3), pH, and cation-exchange capacity (CEC) were measured. The PSD of the soil samples was determined using the international classification system for soil size fraction, and the D of the PSD was calculated for all soils. The results of this study show that D is significantly correlated with clay content (r = 0.93) followed by sand content (r = −0.54) and CEC (r = 0.51). The mean D values of the forest areas (D = 2.931), with a SOM content of 2.1%, are significantly higher than those of the agricultural land (D = 2.905 and SOM = 1.6%) and pastures (D = 2.910 and SOM = 1.6%), indicating that fine soil particles, particularly clay, have been preserved in forest soils but lost in agricultural and pasture soils. We conclude that agricultural land has experienced significantly higher levels of soil erosion than forest areas

GIS-Based assessment of groundwater quality for drinking purpose in northern part of Fars province, Marvdasht

With increasing population and freshwater shortages worldwide, it is necessary to protect vital groundwater resources using innovative methods. The main objective of this study is to use a GIS-based approach with the Groundwater Quality Index (GWQI) to analyze groundwater quality in Marvdasht located in the semi-arid region of Iran. For this purpose, we used groundwater quality data that were collected in a five-year period (2010–2015). The most influential water quality parameters were determined by performing map removal sensitivity analysis. Mean maps of the groundwater parameters showed that total dissolved solid (TDS), electrical conductivity (EC) and total hardness (TH) were the most important parameters that exceed the maximum permissible limits for drinking water. The groundwater quality of the study area is generally desirable for drinking (GWQI = 71). The GWQI map indicated that groundwater was higher quality in northern regions of the study area. The GWQI also revealed that only 2% of the study area (11 km2) was below the low quality class. According to map removal sensitivity analysis, Mg2+, TH and Na+ were identified as the most sensitive water quality parameters. Therefore, these parameters need to be monitored regularly and with increased precision

Fractal Features of Soil Particles as an Indicator of Land Degradation under Different Types of Land Use at the Watershed Scale in Southern Iran

Soil particle-size distribution (PSD) is an important soil feature that is associated with soil erosion, soil fertility, and soil physical and chemical properties. However, very few studies have been carried out to investigate soil degradation using the fractal dimension (D) of the PSD of soils from different land-use types in the calcareous soil of Iran. For this study, 120 soil samples (0–20 cm) were collected from different land-use types in the Fars Province, and various basic soil properties such as soil organic matter (SOM), soil texture fractions, calcium carbonate (CaCO3), pH, and cation-exchange capacity (CEC) were measured. The PSD of the soil samples was determined using the international classification system for soil size fraction, and the D of the PSD was calculated for all soils. The results of this study show that D is significantly correlated with clay content (r = 0.93) followed by sand content (r = −0.54) and CEC (r = 0.51). The mean D values of the forest areas (D = 2.931), with a SOM content of 2.1%, are significantly higher than those of the agricultural land (D = 2.905 and SOM = 1.6%) and pastures (D = 2.910 and SOM = 1.6%), indicating that fine soil particles, particularly clay, have been preserved in forest soils but lost in agricultural and pasture soils. We conclude that agricultural land has experienced significantly higher levels of soil erosion than forest areas