Academic literature on the topic 'Geo-HMS'

The spatial patterns, ecological risks, and sources of heavy metals (HMs), including Pb, Zn, Mn, Cu, Cd, Hg, and As in river sediments, were identified around a lead-zinc mine of Danzhai, Guizhou, China. The concentrations of selected HMs and their coefficient variations indicated that the river sediments around this typical lead-zinc mine were obviously contaminated with HMs. Anthropogenic activities had further enhanced the accumulation of HMs. The higher contents of the most common selected HMs were mainly distributed in the area close to the lead-zinc mine. Based on the combined evaluations of the single factor pollution index, geo-accumulation index, and potential ecological risk index, it indicated that the ecological risks of Hg, Cd, Zn, and Pb were high or extremely high, and of Mn, Cu, and As were slight or none in the sediments around this lead-zinc mine. It was found that lead-zinc mining and smelting activities, coal mining activities, and agricultural activities (livestock and poultry breeding) are the primary sources of selected HMs, based on the results of correlation analysis together with principal component analysis (PCA) and positive matrix factorization (PMF) model. The pollution of HMs in the river sediments around a lead-zinc mine was predominantly caused by lead-zinc mining and smelting activities. Therefore, for environmental persistence, lead-zinc mining and smelting activities should be given careful consideration and under close surveillance.

Understanding the environmental risks of soil heavy metals (HMs) and identifying their main sources are the essential prerequisites for the prevention and management of soil pollution. Based on a detailed survey of soil HMs (Cu, Cr, Ni, Zn, Pb, Cd, As and Hg) from different land use types (including agricultural land, construction land, wetland, and forest land) in an estuary alluvial island, the environmental risk and source apportionment of soil HMs were investigated. Altogether, 117 soil samples were taken in the study area to appraise the soil HMs environmental risk by using the geo-accumulation index (Igeo), potential ecological risk index (RI), and human health risk assessment (HRA) and to identify its main sources by using positive matrix factorization (PMF) model. The average concentrations of soil HMs (except As) surpassed their reference background values in China. There were no significant differenced in the mean concentrations of HMs in different land use types, except that the Hg concentration in the construction land was significantly higher than that in others. The results of Igeo showed that Cd pollution was unpolluted to moderately polluted, and that the others were unpolluted. The potential ecological risk level for Cd and Hg was “moderated potential risk”, while for Cu, Cr, Ni, Zn, Pb and As was “low potential risk”. Higher contamination was distributed at the west-central area. The results of the HRA indicated that the non-carcinogenic risk and the carcinogenic risk that human beings suffered from HMs in different land uses were insignificant. To more accurately identify the sources of soil HMs, the PMF model coupled with the GIS-spatial analysis was applied. The results showed that agricultural activities, natural source, industrial discharge and river transportation, and atmosphere deposition were the main determining factors for the accumulation of soil HMs in the study area, with the contribution rate of 24.25%, 23.79%, 23.84%, and 28.12%, respectively. The study provides an underlying insight needed to control of the soil HM pollutions for an estuary alluvial island.

The paper presents the results of a study of heavy metals (HMs) concentrations in six retention reservoirs located in the lowland area of western Poland. The objectives of this study were to analyze the Cd, Cr, Cu, Ni, Pb and Zn concentrations, assess contamination and ecological risk, analyze the spatial variability of HM concentrations and identify potential sources and factors determining the concentration and spatial distribution. The bottom sediment pollution by HMs was assessed on the basis of the index of geo-accumulation (Igeo), enrichment factor (EF), pollution load index (PLI) and metal pollution index (MPI). To assess the ecological risk associated with multiple HMs, the mean probable effect concentration (PEC) quotient (Qm-PEC) and the toxic risk index (TRI) were used. In order to determine the similarities and differences between sampling sites in regard to the HM concentration, cluster analysis (CA) was applied. Principal component analysis (PCA) was performed to assess the impact of grain size, total organic matter (TOM) content and sampling site location on HM spatial distribution. Additionally, PCA was used to assess the impact of catchment, reservoir characteristics and hydrological conditions. The values of Igeo, EF, MPI and PLI show that Cd, Cr, Cu, Ni and Pb mainly originate from geogenic sources. In contrast, Zn concentrations come from point sources related to agriculture. The mean PEC quotient (Qm-PEC) and TRI value show that the greatest ecological risk occurred at the inlet to the reservoir and near the dam. The analysis showed that the HMs concentration depends on silt and sand content. However, the Pb, Cu, Cd and Zn concentrations are associated with TOM as well. The relationship between individual HMs and silt was stronger than with TOM. The PCA results indicate that HMs with the exception of Zn originate from geogenic sources—weathering of rock material. However, the Ni concentration may additionally depend on road traffic. The results show that a reservoir with more frequent water exchange has higher HMs concentrations, whereas the Zn concentration in bottom sediments is associated with agricultural point sources.

This study aimed to determine the levels and possible sources of heavy metals (HMs) in the sediments of Chalan beel (a large lake-like aquatic ecosystem) area located in the northwestern part of Bangladesh. The mean concentrations (mg kg−1) of two HMs, Cd (6.22) and Pb (51.39) exceeded the world normal averages (WNA), whereas the mean concentrations (mg kg−1) of Ni (60.46), Zn (10.75), Mn (8.64) and Cu (4.71) were below the WNA. The sediments showed significant enrichment with Cd, Pb and Ni in the studied area. The geo-accumulation index values of Cd (3.72) and Pb (0.76) were significantly higher in the sediments. The contamination factor and potential ecological risk index values of Cd and Pb revealed that Chalan beel was extremely and moderately contaminated by these heavy metals, respectively. Analysis of dye complexes used in handlooms around the Chalan beel areas revealed that mean concentrations of Cd and Pb exceeded the WNA. Furthermore, analyses of principal component, cluster and correlation matrix indicated that the presence of the higher levels of Cd and Pb in the sediments might be linked to various anthropogenic activities like discharged dyes into the beel water from the nearby handloom dyeing factories.

Recent availability of various spatial data, especially for gridded rainfall amounts, provide a great opportunity in hydrological modeling of spatially distributed rainfall–runoff analysis. In order to support this advantage using gridded precipitation in hydrological application, (1) two main Python script programs for the following three steps of radar-based rainfall data processing were developed for Next Generation Weather Radar (NEXRAD) Stage III products: conversion of the XMRG format (binary to ASCII) files, geo-referencing (re-projection) with ASCII file in ArcGIS, and DSS file generation using HEC-GridUtil (existing program); (2) eight Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) models of ModClark and SCS Unit Hydrograph transform methods for rainfall–runoff flow simulations using both spatially distributed radar-based and basin-averaged lumped gauged rainfall were respectively developed; and (3) three storm event simulations including a model performance test, calibration, and validation were conducted. For the results, both models have relatively high statistical evaluation values (Nash–Sutcliffe efficiency—ENS 0.55–0.98 for ModClark and 0.65–0.93 for SCS UH), but it was found that the spatially distributed rainfall data-based model (ModClark) gives a better fit regarding observed streamflow for the two study basins (Cedar Creek and South Fork) in the USA, showing less requirements to calibrate the model with initial parameter values. Thus, the programs and methods developed in this research possibly reduce the difficulties of radar-based rainfall data processing (not only NEXRAD but also other gridded precipitation datasets—i.e., satellite-based data, etc.) and provide efficiency for HEC-HMS hydrologic process application in spatially distributed rainfall–runoff simulations.

Heavy metal poisoning has caused serious and widespread human tragedies via the food chain. To alleviate heavy metal pollution, particular attention should be paid to low accumulating vegetables and crops. In this study, the concentrations of five hazardous heavy metals (HMs), including copper (Cu), chromium (Cr), lead (Pb), cadmium (Cd), and arsenic (As) were determined from soils, vegetables, and crops near four typical mining and smelting zones. Nemerow’s synthetical pollution index (Pn), Potential ecological risk index (RI), and Geo-accumulation index (Igeo) were used to characterize the pollution degrees. The results showed that soils near mining and metal smelting zones were heavily polluted by Cu, Cd, As, and Pb. The total excessive rate followed a decreasing order of Cd (80.00%) > Cu (61.11%) > As (45.56%) > Pb (32.22%) > Cr (0.00%). Moreover, sources identification indicated that Cu, Pb, Cd, and As may originate from anthropogenic activities, while Cr may originate from parent materials. The exceeding rates of Cu, Cr, Pb, Cd, and As were 6.7%, 6.7%, 66.7%, 80.0%, and 26.7% among the vegetable and crop species, respectively. Particularly, vegetables like tomatoes, bell peppers, white radishes, and asparagus, revealed low accumulation characteristics. In addition, the hazard index (HI) for vegetables and crops of four zones was greater than 1, revealing a higher risk to the health of local children near the mine and smelter. However, the solanaceous fruit has a low-risk index (HI), indicating that it is a potentially safe vegetable type.

The current study aimed at measuring the impact of the change in land-use morphology on the increase of flood risk through its application to the case of the Riyadh–Dammam train track in Saudi Arabia. The track was exposed to drift on 18 February 2017, over a length of 10 km, in the district of Dhahran in the capital of Dammam. Flooding caused the train to drift off its track and resulted in damage to lives, property, and infrastructure. This resulted from human interventions in the preplanning land uses and changing the morphology of the land by encroaching on the valleys, which resulted in the loss of the environmental and ecological balance in the study area. In order to achieve these goals, land-use changes in the study area were monitored by analyzing successive images from the GEO-I-1 satellite with a resolution of 60 cm for the years 2011 and 2017, before and after the train drift, using the maximum likelihood classification process provided in ERDAS IMAGINE 2016. GIS was used in the processing of 1 m digital elevation models to extract the morphological changes of the wadies between 2011 and 2017. A hydrological model (HEC–HMS) was used in calculating the (flood) hydrograph curve of the wadies basins and estimating the calculation of flood water quantities and its flow rates based on the Soil Conservation Services (SCS) Unit Hydrograph Method. Rain depth was analyzed and estimated for different return periods. The HEC–RAS hydraulic modeling program was employed in developing a 2D model to calculate the velocity, depth, and spread of the flood in order to apply the risk matrix method.

Heavy metals (HMs) in soil are some of the most serious pollutants due to their toxicity and nonbiodegradability. Especially across large-scale areas affected by industry, the complexity of pollution sources has attracted extensive attention. In this study, an approach based on zoning to analyze the sources of heavy metals in soil was proposed. Qualitative identification of pollution sources and quantification of their contributions to heavy metals in soil are key approaches in the prevention and control of heavy metal pollution. The concentrations of five HMs (Cd, Hg, As, Pb and Cr) in the surface soil of the Chenzhou industrial impact area were the research objects. Multiple methods were used for source identification, including positive matrix factorization (PMF) analysis combined with multiple other analyses, including random forest modeling, the geo-accumulation index method and hot spot analysis. The results showed that the average concentrations of the five heavy metals were 9.46, 2.36, 2.22, 3.27 and 1.05 times the background values in Hunan soil, respectively. Cd was associated with moderately to strongly polluted conditions, Hg, As and Pb were associated with unpolluted to moderately polluted conditions and Cr was associated with practically unpolluted conditions. The mining industry was the most significant anthropogenic factor affecting the content of Cd, Pb and As in the whole area, with contribution rates of 87.7%, 88.5% and 62.5%, respectively, and the main influence area was within 5 km from the mining site. In addition, we conducted hot spot analysis on key polluting enterprises and identified hot spots, cold spots, and areas insignificantly affected by enterprises, used this information as the basis for zoning treatment and discussed the sources of heavy metals in the three subregions. The results showed that Cd originated mainly from agricultural activities, with a contribution rate of 63.6%, in zone 3. As originated mainly from sewage irrigation, with a contribution rate of 65.0%, in zone 2, and the main influence area was within 800 m from the river. This element originated mainly from soil parent materials, with a contribution rate of 69.7%, in zone 3. Pb mainly originated from traffic emissions, with a contribution rate of 72.8%, in zone 3, and the main influence area was within 500 m from the traffic trunk line. Hg was mainly derived from soil parent materials with a contribution rate of 92.1% in zone 1, from agricultural activities with a contribution rate of 77.5% in zone 2, and from a mixture of natural and agricultural sources with a contribution rate of 74.2% in zone 3. Cr was mainly derived from the soil parent materials in the whole area, with a contribution rate of 90.7%. The study showed that in large-scale industrial influence areas, the results of heavy metal source analysis can become more accurate and detailed by incorporating regional treatment, and more reasonable suggestions can be provided for regional enterprise management and soil pollution control decision making.

Heavy metals (HMs) in soil are some of the most serious pollutants due to their toxicity and nonbiodegradability. Especially across large-scale areas affected by industry, the complexity of pollution sources has attracted extensive attention. In this study, an approach based on zoning to analyze the sources of heavy metals in soil was proposed. Qualitative identification of pollution sources and quantification of their contributions to heavy metals in soil are key approaches in the prevention and control of heavy metal pollution. The concentrations of five HMs (Cd, Hg, As, Pb and Cr) in the surface soil of the Chenzhou industrial impact area were the research objects. Multiple methods were used for source identification, including positive matrix factorization (PMF) analysis combined with multiple other analyses, including random forest modeling, the geo-accumulation index method and hot spot analysis. The results showed that the average concentrations of the five heavy metals were 9.46, 2.36, 2.22, 3.27 and 1.05 times the background values in Hunan soil, respectively. Cd was associated with moderately to strongly polluted conditions, Hg, As and Pb were associated with unpolluted to moderately polluted conditions and Cr was associated with practically unpolluted conditions. The mining industry was the most significant anthropogenic factor affecting the content of Cd, Pb and As in the whole area, with contribution rates of 87.7%, 88.5% and 62.5%, respectively, and the main influence area was within 5 km from the mining site. In addition, we conducted hot spot analysis on key polluting enterprises and identified hot spots, cold spots, and areas insignificantly affected by enterprises, used this information as the basis for zoning treatment and discussed the sources of heavy metals in the three subregions. The results showed that Cd originated mainly from agricultural activities, with a contribution rate of 63.6%, in zone 3. As originated mainly from sewage irrigation, with a contribution rate of 65.0%, in zone 2, and the main influence area was within 800 m from the river. This element originated mainly from soil parent materials, with a contribution rate of 69.7%, in zone 3. Pb mainly originated from traffic emissions, with a contribution rate of 72.8%, in zone 3, and the main influence area was within 500 m from the traffic trunk line. Hg was mainly derived from soil parent materials with a contribution rate of 92.1% in zone 1, from agricultural activities with a contribution rate of 77.5% in zone 2, and from a mixture of natural and agricultural sources with a contribution rate of 74.2% in zone 3. Cr was mainly derived from the soil parent materials in the whole area, with a contribution rate of 90.7%. The study showed that in large-scale industrial influence areas, the results of heavy metal source analysis can become more accurate and detailed by incorporating regional treatment, and more reasonable suggestions can be provided for regional enterprise management and soil pollution control decision making.

A presente pesquisa concentra-se no estudo hidrológico utilizando o potencial das geotecnologias na modelagem do escoamento na bacia do rio Bengalas, cujo rio principal de mesmo nome, corta o município de Nova Friburgo, RJ, no sentido Sul-Norte. Esse município, um dos mais importantes da região serrana, sofre frequentemente com inundações e deslizamentos, onde, dados históricos e acontecimentos recentes mostram que a ocupação inadequada de encostas e calhas dos rios são as áreas destacada e negativamente afetadas. A metodologia tem suporte no uso de um SIG, extraindo informações, que por sua vez, serão entrada de dados na fase de modelagem, e reforçando a apresentação dos resultados das simulações através de mapas. Ela está divida basicamente em três etapas: "SIG", "Modelagem" e "Suporte à Tomada de Decisão/Simulação". Esse primeiro estudo permitiu compor um banco de dados geográfico com as características fisiográficas da bacia; a seleção criteriosa de uma modelagem matemática e encadeamento de seus parâmetros com os componentes do ciclo hidrológico; realizar a calibração do modelo de transformação chuva-vazão, Soil Conservation Service (CN); e simular a passagem dos volumes gerados pela precipitação efetiva na calha do rio Bengalas, com o objetivo de identificar e analisar as áreas suscetíveis a inundações na porção central da cidade de Nova Friburgo. Modelagem dessa natureza vem sendo empregada, principalmente, no gerenciamento de recursos hídricos, onde a tomada de decisões embasada nos resultados de simulações computacionais, contribuem para evitar prejuízos materiais e financeiros, e ainda, perdas de vidas humanas em áreas de risco, neste caso, aquelas suscetíveis a inundações. Analisando os resultados encontrados temos que a área suscetível à inundação para uma chuva com tempo de recorrência de 50 anos, o mais crítico estudado, seja de aproximadamente 1,0 km, distribuídos nos seus 8,5km na região central de Nova Friburgo-RJ, sendo está, ora delimitada, prioritariamente edificada.
This research focuses on the hydrological study using the potential of geotechnology into runoff modeling of the Bengalas Basin, whose main river, with same name, crosses the city of Nova Friburgo - RJ, in a south-north orientation. This city, one of the most important in "Região Serrana", suffers often with floods and landslides, which, historical data and recent events show that the inappropriate occupation of hillsides and margins of rivers are the highlighted and negatively affected areas. The methodology has basis in a GIS application, extracting information, which in turn, are input in the modeling phase, and enhancing the presentation of simulation results through maps. It is basically divided into three stages: "SIG", "Modelagem" and "Suporte à Tomada de Decisão/Simulação." This first study allowed to compose a geographic database with the physiographic features of the basin; the careful selection of a chain of mathematical modeling and its parameters with the hydrological cycle components, perform the calibration of the rainfall-runoff transformation model, Soil Conservation Service (CN) and simulate the transition of volumes generated by an effective precipitation in the Bengalas river, in order to identify and analyze the susceptible flooding areas in the central part of Nova Friburgo. A kind of this modeling has been used, mainly, in the water resource management, in which decision-making are based on results of computer simulations, helps to avoid a range of losses, such as material, financial and, especially, humans, that in this case, people who lives in areas susceptible to flooding. Analyzing the results, it was found that an area susceptible to flooding by a rainfall with a recurrence time of 50 years, the most critical studied, results in approximately 1.0 km, distributed in its 8.5km (central part of Nova Friburgo - RJ) which this bounded area has a great part with buildings.