Active and online prediction of BOD5 in river systems using reduced-order support vector machine

Due to the limitations of hardware sensors for online measurement of the water quality parameters such as 5-day biochemical oxygen demand (BOD₅), the recent research efforts have focused on the software sensors for the rapid prediction of such parameters. The main objective in this research is to develop a reduced-order support vector machine (ROSVM) model based on the proper orthogonal decomposition to solve the time-consuming problem of the BOD₅ measurements. The performance of the newly developed methodology is tested on the Sefidrood River Basin, Iran. Subsequently, the predicted values of BOD₅, resulted from the selected developed ROSVM model, are compared with the results of support vector machine (SVM) model. According to the obtained results, selected ROSVM model seems to be more accurate, showing Person correlation coefficient (R) and root mean square error (RMSE) equal to 0.97 and 6.94, respectively. Further, the investigations based on developed discrepancy ratio (DDR) statistic for selection of the optimum model between the best accurate ROSVM and SVM models are carried out. Results of DDR statistic indicated superior performance of the selected ROSVM model comparing to the SVM technique for online prediction of BOD₅ in the Sefidrood River.     

Improving WRF-Hydro runoff simulations of heavy floods through the sea surface temperature fields with higher spatio-temporal resolution

This study investigates the impact of the spatio-temporal accuracy of four different sea surface temperature (SST) datasets on the accuracy of the Weather Research and Forecasting (WRF)-Hydro system to simulate hydrological response during two catastrophic flood events over the Eastern Black Sea (EBS) and the Mediterranean (MED) regions of Turkey. Three time-variant and high spatial resolution external SST products (GHRSST, Medspiration and NCEP-SST) and one coarse-resolution and time-invariant SST product (ERA5- and GFS-SST for EBS and MED regions, respectively) already embedded in the initial and the boundary conditions datasets of WRF model are used in deriving near-surface atmospheric variables through WRF. After the proper event-based calibration is performed to the WRF-Hydro system using hourly and daily streamflow data in both regions, uncoupled model simulations for independent SST events are conducted to assess the impact of SST-triggered precipitation on simulated extreme runoff. Some localized and temporal differences in the occurrence of the flood events with respect to observations depending on the SST representation are noticeable. SST products represented with higher cross-correlations (GHRSST and Medspiration) revealed significant improvement in flood hydrographs for both regions. The GHRSST dataset shows a substantial improvement in NSE (~70%), RMSE reduction up to 20%, and an increase in correlation from 0.3 to 0.8 with respect to the invariable SST (ERA5) in simulated runoffs over the EBS region. The use of both GHRSST and Medspiration SST data characterized with high spatio-temporal correlation resulted in runoff simulations exactly matching the observed runoff peak of 300 m³/s by reducing the overestimation seen in invariable SST (GFS) in the MED region. Improved precipitation simulation skills of the WRF model with the detailed SST representation show that the hydrographs of GHRSST and Medspiration simulations show better performance compared to the simulated hydrographs by observed precipitation.     

Total Hg concentrations in stream and lake sediments: Discerning geospatial patterns and controls across Canada

This article presents an analysis of Geological Survey of Canada (GSC) open-file data for total Hg concentrations (THg) in stream and lake sediments at 142,028 sampling locations. This analysis was done for select survey zones across Canada, with emphasis on discerning THg-relevant geographic, geological, atmospheric and topographic controls. THg was generally highest in areas affected by mining and smelting, followed by areas with high metallogenic source locations. Background levels for THg were elevated in the more populated areas along the south, but dropped toward the remote and coldest locations in the east, north and west. This trend was correlated (R² = 0.74; P < 0.0001) with the 2005 GRAHM projections (Global/Regional Atmospheric Heavy Metals Model) for atmospheric Hg deposition (zones and locations with major geogenic sources and mining activities removed). Mean THg was higher for upland lakes (100.9 ± 0.5 SE, ppb) and streams (71.7 ± 0.6 SE, ppb) than for lowland lakes (94.4 ± 0.86 SE, ppb) and streams (64.2 ± 1.26 SE, ppb). The east-central portion of the Yukon Territory (Selwyn Basin) was analyzed in further detail. Here, THg within the sediments increased with increasing loss-on-ignition and increasing trace-element concentrations, and decreased with an increasing wet-area component per catchment above the sediment sampling locations. The characterization and quantification of these Hg trends is important for modeling and mapping health risks to ecosystems and communities across Canada and elsewhere.     

2013年3月19日江西省冰雹天气成因分析

利用常规观测资料和卫星、雷达、自动站等非常规观测资料以及NCEP再分析资料,对2013年3月19日江西省大范围冰雹天气过程形成原因进行分析。结果表明,该过程是在有利的环境条件下发生的：对流层中低层强热力不稳定和强动力不稳定为冰雹生成和增长提供了不稳定机制;暖湿边界层偏南风急流和低层西南急流以及中层“干”西南急流对热力不稳定和动力不稳定机制发展有重要贡献;适宜的0℃层和-20℃层高度有利于冰雹增长。江西北部冰雹天气是在边界层有锋面逆温的条件下发生的,为“高架雷暴”类对流,南部冰雹天气是在边界层有较强暖平流的条件下发生的,为非“高架雷暴”类对流,两类对流的边界层温度层结分布差异明显。与历史同类个例比较发现,假相当位温垂直变化不仅能表征条件不稳定发展程度,对雷雨大风类强对流天气的判断也有一定参考意义。     

2007年夏季两次强雷电过程的气象卫星资料分析

利用FY2一C、FY2一D高时空分辨率可见光云图和FY2一C云顶亮温资料,选取了2007年6月24—25日和7月10一11日2次强雷电过程,对雷电时空分布与强雷暴云团（MCS）演变特征的相关性进行了分析。结果表明：（1）对于不同MCS来说,落雷次数和落雷密度都与MCS的强度密切相关,即MCS强度越大,对流越强,落雷次数越多,落雷密度越大。（2）落雷集中的时段主要都出现在MCS成熟之前、水平尺度为中口尺度的时段内。（3）对于同一MCS来说,在MCS成熟之前,当前以及未来1h的落雷密集区都不是位于当前大范围较低亮温区所覆盖的区域,而是位于MCS移动方向前方和最低云顶亮温中心前方TBB梯度最大的区域内,未来1h的落雷密集区比当前的落雷密集区偏东30—50km。在MCS成熟之后,落雷密集区位于MCS主体外新生的尺度小、生命史短的雷暴云团附近TBB的密集区内。     

Contamination and ecological risk assessment of heavy metals in street dust of Tehran,Iran

Heavy metals are introduced in human tissue through breathing air, food chain and human skin. They can cause damage to the nervous system and internal organs. In the present study, sixty street dust samples were collected from the central area of Tehran and were digested in the laboratory to determine the content of Zn, Ni, Cd, Cr, Cu and Pb, using inductively coupled plasma optical emission spectrometry (ICP-OES). The level of contamination with the analyzed metals was determined according to the following indices: geo-accumulation index (I _geo), enrichment factor (EF), pollution index (PI), integrated pollution index (IPI) and potential ecological risk index (RI). The average concentration of heavy metals found was in the order of Zn > Cu > Pb > Ni > Cr > Cd. The average I _geo values for Cd, Cr, Cu, Ni, Pb and Zn were 1.53, ?1.88, 2.68, ?0.67, 1.62 and 2.70, respectively. Among the investigated heavy metals, zinc and copper had the maximum average EF values and were placed into the “very severe enrichment” class. Potential ecological risk factor (E _r) also indicated that Cd had the highest risk, and it was classified as of considerable potential ecological risk. Therefore, it is necessary to pay more attention to the appearance of Cd in the human environment. The calculated potential ecological risk index values also illustrated that the street dust samples presented a “moderate ecological risk.” The calculated IPI values showed that the pollution levels of the street dust samples ranged from high to extremely high.     

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.     

Calibration of Valiantzas’ reference evapotranspiration equations for the Pilbara region,Western Australia

Theoretical and Applied Climatology - Reference evapotranspiration (ET0) is a critical component of water resources management and planning. Different methods have been developed to estimate ET0...     

Evaluation of Carcinogenic Risk Due to Accidental Ingestion of PAHs in Contaminated Soils

Polycyclic aromatic hydrocarbons (PAHs) are types of hazardous contaminants, which their ingestion could cause severe consequences on human health. Leakages from storage tanks, underground pipelines, and evaporation ponds are the main sources of soil and groundwater contaminations at the Tehran Oil Refinery area (TOR site), located in south of Tehran, Iran. In this study, soil samples were collected from different locations at and adjacent to a polluted stream in the south of the refinery. The samples were analyzed for two hazardous PAH compounds, namely benzo[a]anthracene and acenaphthene. The clean up levels due to the accidental ingestion of contaminated soils at the site were also investigated in accordance to the U.S.EPA guidelines. Comparing the soil analysis results indicated that the benzo[a]anthracene concentrations in the samples varied from 53 to 299 mg/kg, which were higher than the clean up level of 1.17 mg/kg. Thus, soil remediation is required for this contaminant. The acenaphthene analysis results denoted that the average concentration of this contaminant was below the clean up level of 116.67 mg/kg, indicating that no treatment for this contaminant is necessary at the TOR site. Also, because the slope of the ground extends to the south of the stream, which stimulates the migration of the contaminants in this direction due to advection and dispersion mechanisms, the average of benzo[a]anthracene concentrations in south samples was higher than north samples (i.e., C_avg(S) = 160 ppm, C_avg(N) = 113 ppm). Various treatment techniques such as thermal desorption, soil vapor extraction (SVE), and solidification/stabilization (S/S) were investigated for this site. Due to moderate to high plasticity and relatively low permeability of the soil and low volatility of benzo[a]anthracene, however S/S method is recommended as a practical approach for the remediation of the soil at the site.