Fuzzy Logic Model to Estimate Seasonal Pseudo Steady State Chlorophyll-A Concentrations in Reservoirs

A fuzzy logic model is developed to estimate pseudo steady state chlorophyll-a concentrations in a very large and deep dam reservoir, namely Keban Dam Reservoir, which is also highly spatial and temporal variable. The estimation power of the developed fuzzy logic model was tested by comparing its performance with that from the classical multiple regression model. The data include chlorophyll-a concentrations in Keban lake as a response variable, as well as several water quality variables such as PO₄ phosphorus, NO₃ nitrogen, alkalinity, suspended solids concentration, pH, water temperature, electrical conductivity, dissolved oxygen concentration and Secchi depth as independent environmental variables. Because of the complex nature of the studied water body, as well as non-significant functional relationships among the water quality variables to the chlorophyll-a concentration, an initial analysis is conducted to select the most important variables that can be used in estimating the chlorophyll-a concentrations within the studied water body. Following the outcomes from this initial analysis, the fuzzy logic model is developed to estimate the chlorophyll-a concentrations and the advantages of this new model is demonstrated in model fitting over the traditional multiple regression method.     

A Spatial Model to Estimate Habitat Fragmentation and Its Consequences on Long-Term Persistence of Animal Populations

The increasing use of the landscape by humans has led to important diminutions of natural surfaces. The remaining patches of wild habitat are small and isolated from each other among a matrix of inhospitable land-uses. This habitat fragmentation, by disabling population movements and stopping their spread to new habitats, is a major threat to the survival of numerous plant and animal species. We developed a general model, adaptable for specific species, capable of identifying suitable habitat patches within fragmented landscapes and investigating the capacity of populations to move between these patches. This approach combines GIS analysis of a landscape, with spatial dynamic modeling. Suitable habitat is identified using a threshold area to perimeter ratio. Potential movement pathways of species between habitat patches are modeled using a cellular automaton. Habitat connectivity is estimated by overlaying habitat patches with movement pathways. The maximum potential population is calculated within and between connected habitat patches and potential risk of inbreeding within meta-populations is considered. The model was tested on a sample map and applied to scenario maps of predicted land-use change in the Peoria Tri-county region (IL). It (1) showed area of natural area alone was insufficient to estimate the consequences on animal populations; (2) underscored the necessity to use approaches investigating the effect of land-use change spatially through the landscape and the importance of considering species-specific life history characteristics; and (3) highlighted the model's potential utility as an indicator of species likelihood to be affected negatively by land-use scenarios and therefore requiring detailed investigation.     

Development of an Ozone Forecasting Model for Non-Attainment Areas in the State of Ohio

Ground level ozone is responsible for the formation ofsmog, and for a variety of adverse effects on bothhuman and plant life. High concentrations of groundlevel ozone occur during the summer months. This paperdescribes the development of a model to forecast themaximum daily concentration of ozone as a function ofthe maximum surface temperature, for ozonenon-attainment regions in Ohio. The model wasdeveloped by statistical analysis of existing data.Site-specific models were developed initially. Theverification and evaluation of the performancecriteria of the model at each site were explored bycomparing the model with an independent datasetcollected from that site. A generalized statewidemodel was developed from the site-specific models. Theperformance criteria of this model were verified andevaluated by employing the same independent datasetsemployed for the site-specific models. An exceedencemodel to predict the occurrence of ozone exceedencesover 100 ppb has also been presented.     

Field Study of Wind and Traffic to Test a Street Canyon Pollution Model

In the U.K., local authorities have new duties to review and assess air quality. Dispersion models are important tools in this process. The performance of a street canyon model, AEOLIUS, in calculating carbon monoxide (CO) concentrations in urban areas is discussed. A field experiment was conducted in a busy street canyon in Leek, Staffordshire. Wind speed and direction were measured at three heights adjacent to the street. The canyon's CO concentrations and traffic counts were recorded. Predicted concentrations of CO, calculated using AEOLIUS, were compared with the observed values. The concept of a roof-top wind is discussed, as are the consequences of using wind measurements from outside the town. Choice of wind measurement location and height of the anemometer above the canyon had a pronounced effect on calculating the roof-top wind. Two methods of deriving a street level wind speed from a roof-top wind speed gave results that differ by up to a factor of two. AEOLIUS had variable skill at predicting CO concentrations depending on the roof-top wind direction: possible reasons for this variability are explored. A sensitivity study of the model showed that vehicle emissions have the greatest impact on predicted concentrations. Implications for local air quality management are discussed.     

Model Assessment of Air-Pollution in Prague

Results of relatively simple gaussian dispersion model are presented. This model, developed in the beginning of this decade, is suitable mainly for determination of spatial distributions of annual mean concentrations of such kinds of air-pollution as sulphur dioxide (SO₂), mixture of nitrogen oxides (NO_x) or suspended particulate matter (SPM) from all types of emission sources located within the city - point sources, line sources and area sources. Model has been used in years 1994, 1996 and 1998 to assess the air-pollution distributions of the above mentioned kinds in the Prague area and the development of the air quality state. It contributed to the decision making process when possible impact of some changes in traffic system or in system of domestic heating, for example, has been investigated. In this contribution, behaviour of sulphur dioxide (SO₂) and mixture of nitrogen oxides (NO_x) ground concentration distributions are analyzed with respect to changing emission situation in Prague in recent years. Results show that SO₂ ground concentration level decreases mainly due to changes in local heating methods and type of fuel used. Different trend can be seen in NO_x ground concentrations thanks to rapid increase in the traffic density.     

Development and Evaluation of a Regulatory Model for Pesticides in Flooded Applications

The pesticides in flooded applications model (PFAM) is a regulatory model for government agencies and others interested in estimating water concentrations of pesticides used in flooded agriculture applications such as rice paddies and cranberries bogs. PFAM was designed around the specific parameters that are typically available for a pesticide risk assessment, thereby simplifying the model and allowing the user to concentrate on only the most relevant model inputs. The model considers the fate properties of pesticides and allows for the specifications of typical flooded agriculture management practices such as scheduled water releases and refills. It also allows for natural water-level fluctuations resulting from precipitation and evapotranspiration. Model quality assurance requirements for regulatory models aimed at protecting the public are that the models err on the high side of measured data and at the same time should not cause undue burden to stakeholders by being overly conservative. For the studies herein, PFAM did tend to err on the high side of the data yet provided more realistic estimates than the currently used methods, which thereby reduced stakeholder burden. As is also important for a regulatory model, PFAM is nonproprietary and freely available.     

Development of a Model for Simulation of Solute Transport in a Stream–Aquifer System

A model for simulation of solute transport in a dynamic stream–aquifer system is developed by integrating four existing sub-models. Interface packages are created to link the sub-models. The developed model is successfully used to simulate chloride transport in the stream–aquifer system of the Arkansas River and the Equus Beds Aquifer in Kansas and demonstrates that chloride concentration in the aquifer decreases in the vicinity of the simulated channel over time.     

A Budget Model to Scale Nutrient Biogeochemical Cycles in Two Semienclosed Gulfs

The nutrient dynamics of the Strymonikos and Ierissos Gulfs, two semienclosed coastal water bodies, are studied using a simple steady-state budget model, according to the Land–Ocean Interaction in the Coastal Zone modeling guidelines. Strymon river plume dynamics prevailed in the area of the Inner and Outer Srymonikos Gulfs, comprising two layers, while the Ierissos Gulf was defined as a one-box system. Seasonal and mean annual model input data for river discharge, precipitation, evaporation, and concentrations of salt, phosphorus, and nitrogen were obtained during four field campaigns. Results from the nitrogen and phosphorus cycling revealed the importance of river discharge in the horizontal and vertical transport of these substances within the system. Furthermore, it occurred that the major biogeochemical transformation of nitrogen and phosphorus takes place in the immediate nearshore zone (Inner Strymonikos Gulf), while the outer system sustains its nutrient dependence on oceanic exchanges. Therefore, under the summer low flow conditions, the river-influenced inner system acts as a net source of nitrogen and phosphorus, while under increased Strymon River discharge, phosphorus is transferred to the biological material (and the sediments), and the system moves to an autotrophic state. The outer system showed an opposite behavior being autotrophic throughout the year and heterotrophic in February. The Ierissos Gulf, a system not directly influenced by significant river discharge, experienced a seasonally independent behavior with net heterotrophic and denitrification processes prevailing. Model scenarios demonstrated that phosphate concentration increases, even under low river flow conditions and stimulates primary production in excess of respiration, resulting in nitrogen fixation prevalence in the Inner Strymonikos Gulf.     

Development and Parameterization of a Rain- and Fire-driven Model for Exploring Elephant Effects in African Savannas

We describe the development and parameterization of a grid-based model of African savanna vegetation processes. The model was developed with the objective of exploring elephant effects on the diversity of savanna species and structure, and in this formulation concentrates on the relative cover of grass and woody plants, the vertical structure of the woody plant community, and the distribution of these over space. Grid cells are linked by seed dispersal and fire, and environmental variability is included in the form of stochastic rainfall and fire events. The model was parameterized from an extensive review of the African savanna literature; when available, parameter values varied widely. The most plausible set of parameters produced long-term coexistence between woody plants and grass, with the tree–grass balance being more sensitive to changes in parameters influencing demographic processes and drought incidence and response, while less sensitive to fire regime. There was considerable diversity in the woody structure of savanna systems within the range of uncertainty in tree growth rate parameters. Thus, given the paucity of height growth data regarding woody plant species in southern African savannas, managers of natural areas should be cognizant of different tree species growth and damage response attributes when considering whether to act on perceived elephant threats to vegetation.     

灰色系统模型在总悬浮物预测中的应用

以１９８６－１９９４年东北某城市总悬浮物统计资料为依据，应用灰色系统理论ＧＭ（１，１）模型对总量浮物数值进行预测分析。     

Assessing the effects of land use changes on soil sensitivity to erosion in a highland ecosystem of semi-arid Turkey

There has been increasing concern in highlands of semiarid Turkey that conversion of these systems results in excessive soil erosion, ecosystem degradation, and loss of sustainable resources. An increasing rate of land use/cover changes especially in semiarid mountainous areas has resulted in important effects on physical and ecological processes, causing many regions to undergo accelerated environmental degradation in terms of soil erosion, mass movement and reservoir sedimentation. This paper, therefore, explores the impact of land use changes on land degradation in a linkage to the soil erodibility, RUSLE-K, in Cankiri–Indagi Mountain Pass, Turkey. The characterization of soil erodibility in this ecosystem is important from the standpoint of conserving fragile ecosystems and planning management practices. Five adjacent land uses (cropland, grassland, woodland, plantation, and recreational land) were selected for this research. Analysis of variance showed that soil properties and RUSLE-K statistically changed with land use changes and soils of the recreational land and cropland were more sensitive to water erosion than those of the woodland, grassland, and plantation. This was mainly due to the significant decreases in soil organic matter (SOM) and hydraulic conductivity (HC) in those lands. Additionally, soil samples randomly collected from the depths of 0–10 cm (D ₁) and 10–20 cm (D ₂) with irregular intervals in an area of 1,200 by 4,200 m sufficiently characterized not only the spatial distribution of soil organic matter (SOM), hydraulic conductivity (HC), clay (C), silt (Si), sand (S) and silt plus very fine sand (Si + VFS) but also the spatial distribution of RUSLE-K as an algebraically estimate of these parameters together with field assessment of soil structure to assess the dynamic relationships between soil properties and land use types. In this study, in order to perform the spatial analyses, the mean sampling intervals were 43, 50, 64, 78, 85 m for woodland, plantation, grassland, recreation, and cropland with the sample numbers of 56, 79, 72, 13, and 69, respectively, resulting in an average interval of 64 m for whole study area. Although nugget effect and nugget effect–sill ratio gave an idea about the sampling design adequacy, the better results are undoubtedly likely by both equi-probable spatial sampling and random sampling representative of all land uses.     

Development of a calibration system to evaluate VOC losses in a branch enclosure

Considerable uncertainties are associated with the experimental estimates of emission rates of different volatile organic compound (VOC) species from the biosphere to the atmosphere. Some of this uncertainty derives from the sampling and analytical procedures used in emission rate measurements. A calibration system was developed in order to evaluate possible errors in the measurements of biogenic emission rates using a branch enclosure system. Two types of calibration procedures were tested, a standard additions technique and an internal standard procedure. Both techniques were used to evaluate possible losses while sampling isoprene and monoterpenes, which are the most abundant VOCs of biogenic origin. The losses to Teflon lines and the empty sampling system were tested and losses to the branch enclosure system installed on two VOC emitting plant species were evaluated. A considerable loss of isoprene (approximately 18% of inflow concentration 65 ng l(-1)) to the empty enclosure system and to the system installed on the plant was measured, but no losses of monoterpenes were observed.     

Modelling of Motor Vehicle Fuel Consumption and Emissions Using a Power-Based Model

The performance of a power based fuel consumption and exhaust emissions model for spark ignition vehicles has been evaluated using a large Australian database derived from testing a wide range of in-use cars on a chassis dynamometer. It was also applied to results of on-road fuel consumption measurement using a "floating" car which was driven back and forth on hilly roadways in Sydney with a length of 8.6 km. The model is found to predict the fuel consumption well over the standard drive cycles and also for the floating car. Average exhaust emissions were also well predicted, but, as would be expected, vehicle-to-vehicle correlation is impossible due to the well-known high variability of emissions between nominally identical vehicles.     

Development of a Standardised Approach to River Habitat Assessment in Australia

Despite the demonstrated utility of the Australian River Assessment Scheme (AUSRIVAS) to provide national-scale information on the biological condition of rivers, there is no commensurate scheme that can provide standardised information on physical habitat. Existing habitat assessment methods are not suitable for implementation on a national scale, so we present a new habitat assessment protocol that incorporates favorable elements of existing methods. Habitat Predictive Modelling forms the basis for the protocol because it can predict the occurrence of local-scale features from large-scale data, uses the reference condition concept, can be modified to incorporate a range of biologically and geomorphologically relevant variables, and employs a rapid survey approach. However, the protocol has been augmented with geomorphological variables and incorporates principles of hierarchy and geomorphological river zonation. There are four sequential components to the implementation of the protocol: reference site selection, data collection, predictive model construction and assessment of test sites using the predictive models. Once implemented, the habitat assessment protocol will provide a standardised tool for the assessment of river habitat condition at a variety of governance levels.     

Modelling vegetation greenness responses to climate variability in a Mediterranean terrestrial ecosystem

Accurate knowledge of the quality and environmental impact of the highway runoff in Pear River Delta, South China is required to assess this important non-point pollution source. This paper presents the quality characterization and environmental impact assessment of rainfall runoff from highways in urban and rural area of Guangzhou, the largest city of Pear River Delta over 1 year’s investigation. Multiple regression and Pearson correlation analysis were used to determine influence of the rainfall characteristics on water quality and correlations among the constituents in highway runoff. The results and analysis indicates that the runoff water is nearly neutral with low biodegradability. Oil and grease (O&G), suspended solids (SS) and heavy metals are the dominant pollutants in contrast to the low level of nutrient constituents in runoff. Quality of highway runoff at rural site is better than that of at urban site for most constituents. Depth and antecedent dry period are the main rainfall factors influencing quality of highway runoff. The correlation patterns among constituents in highway runoff at urban site are consistent with their dominant phases in water. Strong correlations (r ≥ 0.80) are found among chemical oxygen demand (COD), total phosphorus, Cu and Zn as well as conductivity, nitrate nitrogen and total nitrogen. O&G, COD, SS and Pb in highway runoff at urban site substantially exceed their concentrations in receiving water of Pear River. The soil directly discharged by highway runoff at rural site has contaminated seriously by heavy metals in surface layer accompanying with pH conversion from original acidic to alkaline at present.     

环境预测中灰色模型的EXCEL解法

提出了利用EXCEL应用软件建立GM（1,N）预测模型的建模方法,并结合实例介绍了建立河流高锰酸盐指数GM（1,3）模型的操作过程。     

Dynamic Modeling of the Ratio Volatile Fatty Acids/Bicarbonate Alkalinity in a UASB Reactor for Potato Processing Wastewater Treatment

In this work, dynamic mathematical model for the prediction of the operational parameter volatile fatty acids/bicarbonate alkalinity (VFA/ALK) in a UASB reactor was developed. The dynamic modeling technique was applied successfully to a two-year data record from an industrial wastewater treatment plant of a potato processing industry. The technique used included regression analysis by residuals. Seventeen parameters were examined including the following: wastewater's flow rate, reactor's temperature and pH, total and soluble influent COD, wastewater's temperature and pH, total and soluble effluent COD, volatile fatty acids, alkalinity, biogas production rate and each parameter with a time lag of up to 10 days. Finally, after all parameters and all time lag trials the best fitted model was developed. The model's adequacy was checked by χ² test for a data record of the same UASB reactor but at a different time period and proved to be satisfactory. Additionally, the model's ability to predict and to control the plant's operation via VFA/ALK was examined. Through this model, in contrary to steady state models, various aspects of the process can be enlighten, such as the fact that the hydrolysis of starch requires at least a resident time of seven days.     

Soil contamination of heavy metals in the Katedan Industrial Development Area, Hyderabad, India

Studies on quantitative soil contamination due to heavy metals were carried out in Katedan Industrial Development Area (KIDA), south of Hyderabad, Andhra Pradesh, India under the Indo-Norwegian Institutional Cooperation Programme. The study area falls under a semi-arid type of climate and consists of granites and pegmatite of igneous origin belonging to the Archaean age. There are about 300 industries dealing with dyeing, edible oil production, battery manufacturing, metal plating, chemicals, etc. Most of the industries discharge their untreated effluents either on open land or into ditches. Solid waste from industries is randomly dumped along roads and open grounds. Soil samples were collected throughout the industrial area and from downstream residential areas and were analysed by X-ray Fluorescence Spectrometer for fourteen trace metals and ten major oxides. The analytical data shows very high concentrations of lead, chromium, nickel, zinc, arsenic and cadmium through out the industrial area. The random dumping of hazardous waste in the industrial area could be the main cause of the soil contamination spreading by rainwater and wind. In the residential areas the local dumping is expected to be the main source as it is difficult to foresee that rain and wind can transport the contaminants from the industrial area. If emission to air by the smokestacks is significant, this may contribute to considerable spreading of contaminants like As, Cd and Pb throughout the area. A comparison of the results with the Canadian Soil Quality Guidelines (SQGL) show that most of the industrial area is heavily contaminated by As, Pb and Zn and local areas by Cr, Cu and Ni. The residential area is also contaminated by As and some small areas by Cr, Cu, Pb and Zn. The Cd contamination is detected over large area but it is not exceeding the SQGL value. Natural background values of As and Cr exceed the SQGL values and contribute significantly to the contamination in the residential area. However, the availability is considerably less than anthropogenic contaminants and must therefore be assessed differently. The pre- and post-monsoon sampling over two hydrological cycles in 2002 and 2003 indicate that the As, Cd and Pb contaminants are more mobile and may expect to reach the groundwater. The other contaminants seem to be much more stable. The contamination is especially serious in the industrial area as it is housing a large permanent residing population. The study not only aims at determining the natural background levels of trace elements as a guide for future pollution monitoring but also focuses on the pollution vulnerability of the watershed. A plan of action for remediation is recommended.     

Development of Dissolved Oxygen Model for a Highly Variable Flow River: A Case Study of Ravi River in Pakistan

A framework for dissolved oxygen (DO) modeling of the Ravi River has been developed based on a combination of laboratory measurements and field and monitoring data. Both the classical Streeter-Phelps (CSP) and the modified Streeter-Phelps (MSP) models are used for DO simulations. The MSP model considers the carbonaceous biochemical oxygen demand (CBOD) and nitrogenous biochemical oxygen demand (NBOD) separately, whereas the CSP model is evaluated considering only the CBOD and NBOD is incorporated in the overall BOD utilization rate. CBOD, NBOD and BOD rates have been determined through long-term BOD analysis of five main wastewater outfalls and two surface drains discharging into the Ravi River over a 98 km stretch. Analysis by Thomas Method manifests strong coefficient of determination “R²” between 0.72 and 0.98 for all the three types of BOD rates. Sensitivity analyses have also been carried out to find out a suitable reaeration rate formula for highly variable flows in the Ravi River. The CSP model results based on classical approach of considering only CBOD show significant difference between the model predictions and field measurements suggesting that NBOD needs to be incorporated for the model development. The dissolved oxygen values calculated using the MSP model and the CSP model based on overall BOD rate are in close agreement with field measurements and are thus suitable to model DO levels in the Ravi River.