Environmental modelling of Omerli catchment area in Istanbul, Turkey using remote sensing and GIS techniques

Omerli Reservoir is one of the major drinking water reservoirs of Greater Metropolis Istanbul, providing 40% of the overall water demand. Istanbul where is one of the greatest metropolitan areas of the world with a population over 10 million and a rate of population increase about twice that of Turkey. As a result of population growth and industrial development, Omerli watershed is highly affected by the wastewater discharges from the residential areas and industrial plants. The main objective of this study is to investigate the temporal assessment of the land-use/cover of the Omerli Watershed and the water quality changes in the Reservoir. It is not possible to adequately control urbanization and other pollution sources affecting the water quality. Responses of these detrimental effects are due to rapidly increasing population, unplanned and illegal housing, and irrelevant industries at the protection zones of the watershed, together with insufficient infrastructure. The study is focused on the assessment of urbanization in relation to land use and water quality using Remote Sensing (RS) and Geographic Information Systems (GIS) techniques for all the four protection zones of the Reservoir and a time variant analyzing model is obtained. IRS-1C LISS and IRS-1C PAN, LANDSAT-5 TM satellite data of 1997, 1998, 2000, 2001 and 2006 are analyzed by confirmation through the ground truth data. RS data have been transferred into UTM coordinate system and image enhancement and classification techniques were used. Raster data were converted to vector data that belongs to study area to analyze in GIS for the purpose of planning and decision-making on protected watersheds.     

Impact of Fly Ash from Coal-Fired Power Stations in Delhi, with Particular Reference to Metal Contamination

Indraprastha Power Station (IPP Stn) and Rajghat Power House (RPH), owned by Delhi Electric Supply Undertaking, are both coal-fired power stations located on Ring Road in New Delhi. Ash content of the coal used ranges between 38–47%. The ash is collected in electrostatic precipitators which have an efficiency of 99.3% (IPP station), and 99.7% (RPH). There are instances of major dust pollution around the power stations from fly ash dispersal. The main method of disposal of fly ash from the power stations is by mixing with water, the resultant slurry is pumped through pipes to ash disposal ponds. The supernatant from these ponds is discharged into River Yamuna. Field studies have revealed large quantities of fly ash being deposited into the river. Local populations of Eichhornia crassipes have reduced dramatically between 1987–1995, with a marked reduction in the year 1994–1995. Field studies, conducted in January, 1995 have investigated the impact of fly ash dispersal in the Delhi region with particular reference to metal contamination. Elemental concentrations for a range of elements are determined by ICP-AES in fly ash and top soils along four transects from the power stations up to a distance of 8 km. The effects of fly ash leachates from the ash settling ponds on the river are determined by analyzing river overbank soils and vegetation for their elemental contents. It is concluded that fly ash dispersal from the stacks are a source of alkali, alkaline-earth and to some extent heavy metals in soils in the vicinity of the power stations, and enrichment of elements in river overbank soils are a result of discharge of fly ash leachates from ash disposal ponds. However, the impact from both these sources of metal contamination is not large enough to give cause for concern. Marked reduction in populations of Eichhornia crassipes downstream of the river where it receives leachates from the ash disposal ponds are attributed to turbidity of the ash pond leachates and metal toxicity. Elemental enrichment in the floodplain soils, as a result of fly ash particle deposition during monsoons, may enhance the horticultural value of these soils as is shown by a healthy cultivated crop of Brassica juncea.     

内陆河流域重要生态功能区生态安全评价研究——以黑河流域为例

以遥感与GIS技术为依托,根据PSR模型框架建立黑河流域生态安全评价指标体系,通过三期生态安全评价数据,综合分析了黑河流域20年来生态安全变化情况,结果表明其生态安全状况总体呈现波动变化,2000年较1986年呈恶化趋势,2007年较2000年有所好转。     

Land cover change of watersheds in Southern Guam from 1973 to 2001

Land cover change can be caused by human-induced activities and natural forces. Land cover change in watershed level has been a main concern for a long time in the world since watersheds play an important role in our life and environment. This paper is focused on how to apply Landsat Multi-Spectral Scanner (MSS) satellite image of 1973 and Landsat Thematic Mapper (TM) satellite image of 2001 to determine the land cover changes of coastal watersheds from 1973 to 2001. GIS and remote sensing are integrated to derive land cover information from Landsat satellite images of 1973 and 2001. The land cover classification is based on supervised classification method in remote sensing software ERDAS IMAGINE. Historical GIS data is used to replace the areas covered by clouds or shadows in the image of 1973 to improve classification accuracy. Then, temporal land cover is utilized to determine land cover change of coastal watersheds in southern Guam. The overall classification accuracies for Landsat MSS image of 1973 and Landsat TM image of 2001 are 82.74% and 90.42%, respectively. The overall classification of Landsat MSS image is particularly satisfactory considering its coarse spatial resolution and relatively bad data quality because of lots of clouds and shadows in the image. Watershed land cover change in southern Guam is affected greatly by anthropogenic activities. However, natural forces also affect land cover in space and time. Land cover information and change in watersheds can be applied for watershed management and planning, and environmental modeling and assessment. Based on spatio-temporal land cover information, the interaction behavior between human and environment may be evaluated. The findings in this research will be useful to similar research in other tropical islands.     

Monitoring urban growth and detecting land-cover changes on the Istanbul metropolitan area

Istanbul is the most populated city of Turkey with a population of around 10.58 M (2000) living on around 5,750 km². In 1980, the population was only 4.7 M and then it has been more than doubled in only two decades. The population has been increasing as a result of mass immigration. An urbanization process continues and it causes serious increases in urban areas while decreasing the amount of green areas. This rapid, uncontrolled, and illegal urbanization accompanied by insufficient infrastructure has caused degradation of forest and barren lands in the metropolitan area, especially through the last two decades. The watershed basins inside the metropolitan area and the transportation network have accelerated the land-cover changes, which have negative impacts on water quality of the basins. Monitoring urban growth and land cover change will enable better management of this complex urban area by the Greater Istanbul Metropolitan Municipality (GIMM). A temporal assessment of land-cover changes of Istanbul has been documented in this study. The study mainly focuses on the acquisition and analysis of Landsat TM and Landsat GeoCover LC satellite images reflecting the significant land-cover changes between the years of 1990 and 2005. Raster data were converted to vector data and used in Geographic Information Systems (GIS). A database was created for Istanbul metropolitan area to plan, manage, and utilize statistical attribute data covering population, water, forest, industry, and topographic position. Consequently an overlay analysis was carried out and land use/cover changes through years have been detected for the case study area. The capability of Landsat images in determining the alterations in the macro form of the city are also discussed.     

Mathematical Modeling of Leachates from Ash Ponds of Thermal Power Plants

The present study describes the development of empirical models for the prediction of various trace metals i.e., Mn, Cu, Fe, Zn and Pb found in the leachates generated from the ash ponds of various thermal power plants. The dispersion phenomenon of these trace metals followed first order reaction rate kinetics. The empirical models for individual trace metals derived from the lab scale models data correlate well with the real field data with regression coefficients varying from 0.93 to 0.98. The predicted concentrations of the trace metals varied within ±3% of the observed values in the leachates generated from the ash ponds of four thermal power plants with standard deviation varying from 0.001 to 0.032. The empirical models derived from the study can be applied for prediction of trace metals in leachates generated from similar thermal power plants.     

Application of integrated GIS and multimedia modeling on NPS pollution evaluation

In Taiwan, nonpoint source (NPS) pollution is one of the major causes of the impairment of surface waters. I-Liao Creek, located in southern Taiwan, flows approximately 90 km and drains toward the Kaoping River. Field investigation results indicate that NPS pollution from agricultural activities is one of the main water pollution sources in the I-Liao Creek Basin. Assessing the potential of NPS pollution to assist in the planning of best management practice (BMP) is significant for improving pollution prevention and control in the I-Liao Creek Basin. In this study, land use identification in the I-Liao Creek Basin was performed by properly integrating the skills of geographic information system (GIS) and global positioning system (GPS). In this analysis, 35 types of land use patterns in the watershed area of the basin are classified with the aid of Erdas Imagine process system and ArcView GIS system. Results indicate that betel palm farms, orchard farms, and tea gardens dominate the farmland areas in the basin, and are scattered around on both sides of the river corridor. An integrated watershed management model (IWMM) was applied for simulating the water quality and evaluating NPS pollutant loads to the I-Liao Creek. The model was calibrated and verified with collected water quality and soil data, and was used to investigate potential NPS pollution management plans. Simulated results indicate that NPS pollution has significant contributions to the nutrient loads to the I-Liao Creek during the wet season. Results also reveal that NPS pollution plays an important role in the deterioration of downstream water quality and caused significant increase in nutrient loads into the basin's water bodies. Simulated results show that source control, land use management, and grassy buffer strip are applicable and feasible BMPs for NPS nutrient loads reduction. GIS system is an important method for land use identification and waste load estimation in the basin. Linking the information of land utilization with the NPS pollution simulation model may further provide essential information of potential NPS pollution for all subregions in the river basin. Results and experience obtained from this study will be helpful in designing the watershed management and NPS pollution control strategies for other similar river basins.     

红壤丘陵区典型流域地表水水环境特征研究——以浏阳河流域为例

选取浏阳河流域为例,根据近十年河流断面监测数据,采用改进的综合污染指数法来评价水质污染程度,研究了该红壤丘陵区典型河流水质的时空变化特征,并结合土地利用和土壤特征等分析地表水质变化原因。结果表明,改进的综合污染指数法有较好的适用性;从时间特征上看,由于面源污染加剧,使得浏阳河近十年的水质污染呈增长趋势;从空间特征上看,浏阳河从上游到下游,河流污染呈增长趋势,上游水质较好,中游表现为重金属铅和汞的污染较大,而下游则是氨氮污染加剧。     

连续纵向水质监测方法在温瑞塘河的应用

水质监测结果是水质评价与水污染防治的重要依据。针对常规定点水质监测方法无法完整再现水质指标的时空连续分布特征的问题,将船只搭载的水质实时监测设备与GPS同步形成基于GIS数据支撑的连续纵向水质监测方法。重点对水质监测仪及GPS空间数据集成问题进行了分析讨论,并在温瑞塘河流域进行了实验论证。结果表明,连续性纵向水质监测不但能进行连续时空水质监测,还能与GPS、GIS结合进行连续性时空分布特征的分析。     

Monitoring the impacts of urbanization and industrialization on the agricultural land and environment of the Torbali, Izmir region, Turkey

The aim of this research is to determine agricultural land loss and environmental pollution caused by industrialization and urban sprawl using the Geographical Information System (GIS) and Remote Sensing technique (RS). Remotely sensed data is the most powerful tool for monitoring land use changes and GIS is the best way to store and reproduce various kinds of integrated data. Considering the rapid increase of population the loss of fertile agricultural soils is a very dangerous situation for the future of the country. Thus, people are living in the cities in (with adverse) conditions of insufficient drinking water, infrastructure problems, inadequate landscape and many unsolved (extreme) environmental problems. During the last 36 years, unplanned urbanization and industrialization have led to the use of agricultural areas for non-agricultural purposes in the Torbali (Izmir) region, which has the most fertile soils of the Aegean Region. Within this study, a database was created on the parameters of land loss and environmental pollution by means of field observation, interpretation of satellite images (ASTER), aerial photos(1/25.000 scale), topographic map ,soil map, and 1/5.000 scale cadastral map. Results of previous researches and the archives of Torbali municipality were used as ancillary data. In the research, urbanization and industrialization of the town was studied by (using) GIS and RS between 1965 and 2001. Since 1965, 4.742.357 m² agricultural land, mostly of first and second land use capability classes, has been lost due to unplanned urban and industrial developments. Urbanization and industrialization involved an area of which 58% was being used as irrigated lands, 25 % rain feed (rain fed lands)and 17 % for olive growing.     

Derivation of unit and flood hydrographs using a gis

A geographic information system (GIS) supporting a flood hydrograph prediction software package is described. The hydrograph prediction method is based on the convolution of excess rainfall with a synthetic unit hydrograph, derived by the Soil Conservation Service runoff curve number and a regional dimensionless unit hydrograph method, respectively. The GIS uses a raster method to store the following data: land use and land cover, soil type, rainfall intensity-frequency-duration statistics, runoff curve numbers (CN), regional dimensionless unit hydrograph, and regional lag-time relationship. The GIS has also the capability of computing a number of watershed and hydrologic parameters required for predictions, such as a watershed average rainfall and CN value, area, centroid, stream length etc. Most of the data for such computations are input from a digitizer. Substantial time and cost savings are possible once the data base has been created. Application of the system is illustrated by an example predicting flood frequency curves for selected watersheds in Alberta's Rocky Mountain foothills, Canada.     

Factors influencing the sinuosity of Pannagon River, Kottayam, Kerala, India: An assessment using remote sensing and GIS

The present study was carried out to identify the factors influencing the sinuosity of the Pannagon river, using the IRS P6 LISS III data and Geographical Information System (GIS) on 1:50,000 scale. The river follows meandering course and exhibits a narrow, highly sinuous and incised channel. Several lines of evidence including satellite and topographic data, geological maps and field investigations and the generated themes on lithology, structure, geomorphology, slope, riparian vegetation and hydrology have analyzed to understand the controls on the channel morphology of the Pannagon river. The average of sinuosity index of the selected reaches in the river on 1967 was 1.6 and of 2004 was 1.8. The sinuous patches are more in the lower reaches of the river and most of the area comes under floodplain with thick column of alluvial deposits. The analysis shown that the style and degree of sinuosity of the Pannagon river depends on a number of geological factors, including tectonics and the riparian vegetation also plays a major role.     

Nonpoint Source Pollution Assessment of Wujiang RiverWatershed in Guizhou Province,SW China

The amount of pollution from nonpoint sources flowing in the streams of the Wujiang River watershed in Guizhou Province, SW China, is estimated by a geographic information system (GIS)-based method using rainfall, surface runoff and land use data. A grid of cells of 100 m in size is laid over the landscape. For each cell, mean annual surface runoff is estimated from rainfall and percent land use, and expected pollutant concentration is estimated from land use. The product of surface runoff and concentration gives expected pollutant loading from that cell. These loadings are accumulated going downstream to give the expected annual pollutant loadings in streams and rivers. By dividing these accumulated loadings by the similarly accumulated mean annual surface runoff, the expected pollutant concentration from nonpoint sources is determined for each location in a stream or river. Observed pollutant concentrations in the watershed are averaged at each sample point and compared to the expected concentrations at the same locations determined from the grid cell model. In general, annual nonpoint source nutrient loadings in the Wujiang River watershed are seen to be predominantly from the agricultural and meadow areas. The total annual loadings through the outlet of the watershed are 40,309 and 2,607 tons for total nitrogen (TN) and total phosphorus (TP), respectively.     

Morphometry and land cover based multi-criteria analysis for assessing the soil erosion susceptibility of the western Himalayan watershed

Complex mountainous environments such as Himalayas are highly susceptibility to natural hazards particular those that are triggered by the action of water such as floods, soil erosion, mass movements and siltation of the hydro-electric power dams. Among all the natural hazards, soil erosion is the most implicit and the devastating hazard affecting the life and property of the millions of people living in these regions. Hence to review and devise strategies to reduce the adverse impacts of soil erosion is of utmost importance to the planners of watershed management programs in these regions. This paper demonstrates the use of satellite based remote sensing data coupled with the observational field data in a multi-criteria analytical (MCA) framework to estimate the soil erosion susceptibility of the sub-watersheds of the Rembiara basin falling in the western Himalaya, using geographical information system (GIS). In this paper, watershed morphometry and land cover are used as an inputs to the MCA framework to prioritize the sub-watersheds of this basin on the basis of their different susceptibilities to soil erosion. Methodology included the derivation of a set of drainage and land cover parameters that act as the indicators of erosion susceptibility. Further the output from the MCA resulted in the categorization of the sub-watersheds into low, medium, high and very high erosion susceptibility classes. A detailed prioritization map for the susceptible sub-watersheds based on the combined role of land cover and morphometry is finally presented. Besides, maps identifying the susceptible sub-watersheds based on morphometry and land cover only are also presented. The results of this study are part of the watershed management program in the study area and are directed to instigate appropriate measures to alleviate the soil erosion in the study area.     

Water Quality Assessment of an Untreated Effluent Impacted Urban Stream: The Bharalu Tributary of the Brahmaputra River, India

Guwahati, the lone city on the bank of the entire midstream of the Brahmaputra River, is facing acute civic problem due to severe depletion of water quality of its natural water bodies. This work is an attempt towards water quality assessment of a relatively small tributary of the Brahmaputra called the Bharalu River flowing through the city that has been transformed today into a city drainage channel. By analyzing the key physical, chemical and biological parameters for samples drawn from different locations, an assessment of the dissolved load and pollution levels at different segments in the river was made. Locations where the contaminants exceeded the permissible limits during different seasons were identified by examining spatial and temporal variations. A GIS developed for the watershed with four layers of data was used for evaluating the influence of catchment land use characteristics. BOD, DO and total phosphorus were found to be the sensitive parameters that adversely affected the water quality of Bharalu. Relationship among different parameters revealed that the causes and sources of water quality degradation in the study area were due to catchments input, anthropogenic activities and poor waste management. Elevated levels of total phosphorus, BOD and depleted DO level in the downstream were used to develop an ANN model by taking total phosphorus and BOD as inputs and dissolved oxygen as output, which indicated that an ANN based predictive tool can be utilized for monitoring water quality in the future.     

基于GIS的页岩气开发生态环境数据管理系统设计

分析了数据管理系统在生态环境领域的应用现状,以及页岩气开发生态环境数据的特性和管理需求,提出了基于地理信息系统和关系型数据库有效集成的数据管理系统框架,实现对页岩气开发区域水环境、土壤环境、环境空气及污染源负荷在时间和空间尺度的分析与评价,指出大数据、物联网技术的运用是系统发展的重要方向.     

Water quality in Lis river, Portugal

In the past 30?years, the Lis river basin has been subjected to constant ecological disasters mainly due to piggery untreated wastewater discharges. The aim of this study was to evaluate the effect of existing domestic, agricultural, and industrial activities on the water quality, and to propose a watershed plan to protect and manage surface water resources within the Lis river basin. For this purpose, 16 monitoring stations have been strategically selected along the Lis river stretch and its main tributaries to evaluate the water quality in six different sampling periods (2003–2006). All samples were characterized in terms of organic material, nutrients, chlorophyll, and pathogenic bacteria. Generally, the Lis river presents poor water quality, according to environmental quality standards for surface water, principally in terms of dissolved oxygen, biochemical oxygen demand, total nitrogen, and fecal coliform, which can be associated mainly with the contamination source from pig-breeding farms.     

Monitoring Air Quality in Mountains: Designing an Effective Network

A quantitatively robust yet parsimonious air-quality monitoring network in mountainous regions requires special attention to relevant spatial and temporal scales of measurement and inference. The design of monitoring networks should focus on the objectives required by public agencies, namely: 1) determine if some threshold has been exceeded (e.g., for regulatory purposes), and 2) identify spatial patterns and temporal trends (e.g., to protect natural resources). A short-term, multi-scale assessment to quantify spatial variability in air quality is a valuable asset in designing a network, in conjunction with an evaluation of existing data and simulation-model output. A recent assessment in Washington state (USA) quantified spatial variability in tropospheric ozone distribution ranging from a single watershed to the western third of the state. Spatial and temporal coherence in ozone exposure modified by predictable elevational relationships ( 1.3 ppbv ozone per 100 m elevation gain) extends from urban areas to the crest of the Cascade Range. This suggests that a sparse network of permanent analyzers is sufficient at all spatial scales, with the option of periodic intensive measurements to validate network design. It is imperative that agencies cooperate in the design of monitoring networks in mountainous regions to optimize data collection and financial efficiencies.     

Integrating geospatial and ground geophysical information as guidelines for groundwater potential zones in hard rock terrains of south India

The increasing demand of water has brought tremendous pressure on groundwater resources in the regions were groundwater is prime source of water. The objective of this study was to explore groundwater potential zones in Maheshwaram watershed of Andhra Pradesh, India with semi-arid climatic condition and hard rock granitic terrain. GIS-based modelling was used to integrate remote sensing and geophysical data to delineate groundwater potential zones. In the present study, Indian Remote Sensing RESOURCESAT-1, Linear Imaging Self-Scanner (LISS-4) digital data, ASTER digital elevation model and vertical electrical sounding data along with other data sets were analysed to generate various thematic maps, viz., geomorphology, land use/land cover, geology, lineament density, soil, drainage density, slope, aquifer resistivity and aquifer thickness. Based on this integrated approach, the groundwater availability in the watershed was classified into four categories, viz. very good, good, moderate and poor. The results reveal that the modelling assessment method proposed in this study is an effective tool for deciphering groundwater potential zones for proper planning and management of groundwater resources in diverse hydrogeological terrains.