Analysis of temporal and spatial variations in groundwater nitrate and development of its pollution plume: a case study in Karaj aquifer

Considering the importance of groundwater resources in water-supply demands in arid and semiarid areas such as Iran, it is essential to investigate the risk of groundwater pollution. Nitrate is one of the main pollutants that penetrate into the groundwater from various sources such as chemical fertilizers, pesticides, and domestic and industrial sewage. Unfortunately currently, nitrate contamination of the aquifers is a serious problem in Iran. The Karaj aquifer is not exempted, and the nitrate pollution zone, with concentrations far beyond the permitted limit (50 mg/L), expands fast. In this paper, the long-term groundwater-quality data (from 2000 to 2013) collected from Alborz Province Water and Wastewater Company were analyzed using ArcGIS10 and statistical software, and the spatial and temporal patterns of nitrate pollution in drinking-water wells in the Karaj plain and effective parameters (such as depth to groundwater level, hydraulic gradient, land use, precipitation, and urban, agricultural and industrial wastewater) were investigated. The authors also investigated the status of nitrate concentration variation using the concepts of geostatistics, based on determinations from 62 to 194 surveyed wells with a suitable distribution across the plain. With respect to the relationship between quality parameters, hydrogeological status of the aquifer and land usage, causes of the increase in the concentration of nitrate in the water and its trend were investigated as well. Results revealed that the nitrate levels in the northern portion of the study area were the highest with maximum concentrations of 181.7 mg/L from 2000 to 2013. Based on nitrate concentration distribution maps, the levels of nitrate increased from 2006 onwards to 26–100 mg/L. Unfortunately from 2008 to 2012, a pollution zone with a nitrate water concentration of 101–150 mg/L has been observed and even a concentration of 180 mg/L has been determined. In 2000, the entire aquifer area has been drinkable but with the increase in nitrate concentration, the area with undrinkable water has expanded to 21% in 2003, 24% in 2005, 33% in 2007, 39% in 2009, 43% in 2011 and 44% in 2013. The results of this study could provide valuable information with on the status of nitrate water concentrations in the Karaj plain which demands proper strategies and qualitative approaches in the future.     

Numerical study on static and seismic stability of breakwaters on soft granular marine deposits against deep failure

Marine structures which cover a wide range of offshore and onshore structures are often subjected to different external and internal forces against which a proper design should be performed. Among many, breakwaters constructed over a relatively loose agglomerate of granular soils are much prone to deep seated failure extended beneath the foundation. This type of failure has been given less attention in conventional design approaches. Stability analysis of such failures is the main subject of this research which includes both the static and the seismic stability of breakwaters over granular marine soils. As the subsoil strata in sea beds often comprise loose sand deposits, it is more convenient to assume a rather small angle of dilation, at least at failure, which certainly reduces the potential to resist geotechnical instabilities. The method of stress characteristics along with slight modifications to handle this issue has been used to assess the overall stability of breakwaters against deep seated failures. Investigations revealed that while even under static condition, there is certain potential of failure, under seismic condition, the risk is quite very high. A series of design charts are also developed presenting the factor of stability as a measure of safety against such failure.     

Functional data clustering using K-means and random projection with applications to climatological data

In this paper, an efficient pattern recognition method for functional data is introduced. The proposed method works based on reproducing kernel Hilbert space (RKHS), random projection and K-means algorithm. First, the infinite dimensional data are projected onto RKHS, then they are projected iteratively onto some spaces with increasing dimension via random projection. K-means algorithm is applied to the projected data, and its solution is used to start K-means on the projected data in the next spaces. We implement the proposed algorithm on some simulated and climatological datasets and compare the obtained results with those achieved by K-means clustering using a single random projection and classical K-means. The proposed algorithm presents better results based on mean square distance (MSD) and Rand index as we have expected. Furthermore, a new kernel based on a wavelet function is used that gives a suitable reconstruction of curves, and the results are satisfactory.     

Impact of seismic excitation characteristics on the efficiency of tuned liquid column dampers

Various types of passive control systems have been used to suppress the seismic response of structures in recent years. Among these systems, Tuned Liquid Column Dampers （TLCDs） dissipate the input earthquake energy by combining the effects of the movement of the liquid mass in the container, the restoring force on the liquid due to the gravity loads and the damping due to the liquid movement through orifices. In this study, the effects of seismic excitation characteristics such as frequency content and soil condition on the seismic performance of TLCDs are investigated using nonlinear time-history analyses. In this regard, among the past earthquake ground motion records of Iran, 16 records with different parameters were selected. In the structural model developed, the attached TLCD is simulated as a Tuned Mass Damper （TMD） having the same vibration period and damping ratio as the original TLCD. The numerical results show that the seismic excitation characteristics have a substantial role on the displacement reduction capability of TLCDs and they should be considered accordingly in the design of TLCDs.     

Experimental investigating on the reflected waves from the caisson-type vertical porous seawalls

The hydrodynamic efficiencies of caisson-type vertical porous seawalls used for protecting coastal areas were calculated in this study. Physical models were developed to compare the wave reflection from vertical plane, semi-porous, and porous seawalls caused by both regular and random waves. Tests were carried out for a wide range of wave heights, wave periods, and different water depths (d=0.165, 0.270 and 0.375 m). The performance regarding the reflected waves from porous and semi-porous seawalls showed improvement when compared with those from the plane seawall. The reflection coefficients of the porous and semi-porous seawalls were calculated as 0.6 and 0.75, respectively, while the coefficient for the fully reflecting plane vertical wall was significantly higher (0.9). It was also observed that the reflection coefficient decreases with increase in wave steepness and relative water depth. In addition, the reduction in the reflection coefficient of porous and semi-porous seawalls, as compared to that of a plane seawall, was observed for both regular and random waves. New equations were also proposed to calculate the reflection coefficient of different types of seawalls with the aid of laboratory experiments. By verifying the developed equations using some other experimental data, it was validated that the equations could be used for practical situations. The results of the present study can be applied to optimize the design of vertical seawalls and for coastal protecting schemes.     

Development of a Land Subsidence Forecasting Model Using Small Baseline Subset—Differential Synthetic Aperture Radar Interferometry and Particle Swarm Optimization—Random Forest (Case Study: Tehran-Karaj-Shahriyar Aquifer,Iran)

Doklady Earth Sciences - Land subsidence, as a dangerous environmental issue, causes serious damages to farms and urban infrastructure. In this regards, this research was conducted with aimed to...     

Spatial variation assessment of groundwater quality using multivariate statistical analysis(Case Study: Fasa Plain,Iran)

Groundwater is considered as one of the most important sources for water supply in Iran. The Fasa Plain in Fars Province, Southern Iran is one of the major areas of wheat production using groundwater for irrigation. A large population also uses local groundwater for drinking purposes. Therefore, in this study, this plain was selected to assess the spatial variability of groundwater quality and also to identify main parameters affecting the water quality using multivariate statistical techniques such as Cluster Analysis (CA), Discriminant Analysis (DA), and Principal Component Analysis (PCA). Water quality data was monitored at 22 different wells, for five years (2009-2014) with 10 water quality parameters. By using cluster analysis, the sampling wells were grouped into two clusters with distinct water qualities at different locations. The Lasso Discriminant Analysis (LDA) technique was used to assess the spatial variability of water quality. Based on the results, all of the variables except sodium absorption ratio (SAR) are effective in the LDA model with all variables affording 92.80% correct assignation to discriminate between the clusters from the primary 10 variables. Principal component (PC) analysis and factor analysis reduced the complex data matrix into two main components, accounting for more than 95.93% of the total variance. The first PC contained the parameters of TH, Ca²⁺, and Mg²⁺. Therefore, the first dominant factor was hardness. In the second PC, Cl^-, SAR, and Na⁺ were the dominant parameters, which may indicate salinity. The originally acquired factors illustrate natural (existence of geological formations) and anthropogenic (improper disposal of domestic and agricultural wastes) factors which affect the groundwater quality.