Application of SMR to Modeling Watersheds in the Catskill Mountains

Very few hydrological models commonly used in watershed management are appropriate for simulating the saturation excess runoff. The Soil Moisture Routing model (SMR) was developed specifically to predict saturation excess runoff from variable source areas, especially for areas where shallow interflow controls saturation. A recent version of SMR was applied to two rural catchments in the Catskill Mountains to evaluate its ability to simulate the hydrology of these systems. Only readily available meteorological, topographical, and landuse information from published literature and governmental agencies was used. Measured and predicted streamflows showed relatively good agreement; the average Nash–Sutcliffe efficiency for the two watersheds were R ²=72% and R ²=63%. Distributed soil moisture contents and the locations of hydrologically sensitive areas were also predicted well.     

Statistical Modelling of Extreme Rainfall Indices using Multivariate Extreme Value Distributions

Environmental Modeling & Assessment - Multivariate extreme value models are used to investigate the combined behaviour of several weather variables. To investigate joint dependence of extreme...     

Support Vector Machine Modeling Using Particle Swarm Optimization Approach for the Retrieval of Atmospheric Ammonia Concentrations

This study was performed in order to improve the estimation accuracy of atmospheric ammonia (NH₃) concentration levels in the Greater Houston area during extended sampling periods. The approach is based on selecting the appropriate penalty coefficient C and kernel parameter σ ². These parameters directly influence the regression accuracy of the support vector machine (SVM) model. In this paper, two artificial intelligence techniques, particle swarm optimization (PSO) and a genetic algorithm (GA), were used to optimize the SVM model parameters. Data regarding meteorological variables (e.g., ambient temperature and wind direction) and the NH₃ concentration levels were employed to develop our two models. The simulation results indicate that both PSO-SVM and GA-SVM methods are effective tools to model the NH₃ concentration levels and can yield good prediction performance based on statistical evaluation criteria. PSO-SVM provides higher retrieval accuracy and faster running speed than GA-SVM. In addition, we used the PSO-SVM technique to estimate 17 drop-off NH₃ concentration values. We obtained forecasting results with good fitting characteristics to a measured curve. This proved that PSO-SVM is an effective method for estimating unavailable NH₃ concentration data at 3, 4, 5, and 6 parts per billion (ppb), respectively. A 4-ppb NH₃ concentration had the optimum prediction performance of the simulation results. These results showed that the selection of the set-point values is a significant factor in compensating for the atmospheric NH₃ dropout data with the PSO-SVM method. This modeling approach will be useful in the continuous assessment of NH₃ sensor discrete data sources.     

Inverse Modeling for Aquatic Source and Transport Parameters Identification and its Application to Fukushima Nuclear Accident

Inverse modeling technique based on nonlinear least square regression method (LSRM) is developed for the identification of aquatic source and transport parameters. Instantaneous line source release model in two-dimensional domain and continuous point source release model in three-dimensional domain are used for the purpose. Case studies have been carried out for both types of releases to illustrate their application. Error analysis has been carried out to identify the maximum error that can be tolerated in the input concentration data used in the inverse model and to specify the minimum number of sampling points to generate such input data. The LSRM is compared with the well-established correlation coefficient optimization method for instantaneous line source release model, and good comparison is observed between them. The LSRM is used to quantitatively estimate the releases of different radionuclides into the Pacific Ocean which has resulted due to the discharge of highly radioactive liquid effluent from the affected Daiichi Nuclear Power Station at Fukushima in Japan. The measured concentrations of these radionuclides in seawater samples collected from two sampling points near Fukushima are used for the estimation. The average release works out to be 1.09?×?10¹⁶ for ¹³¹I, 3.4?×?10¹⁵ Bq for ¹³⁴Cs, and 3.57?×?10¹⁵ Bq for ¹³⁷Cs. Very good agreement is observed between the releases estimated in this study and those estimated by other different agencies.     

Stationary and Non-stationary Extreme Value Approaches for Modelling Extreme Temperature: the Case of Riyadh City,Saudi Arabia

Climate change is one of the most fiercely debated scientific issues in recent decades, and the changes in climate extremes are estimated to have greater negative impacts on human society and the natural environment than the changes in mean climate. Extreme value theory is a well-known tool that attempts to best estimate the probability of adversarial risk events. In this paper, the focus is on the statistical behaviour of extreme maximum values of temperature. Under the framework of this theory, the methods of block maxima and threshold exceedances are employed. Due to the non-stationary characteristic of the series of temperature values, the generalized extreme value distribution and the generalized Pareto distribution were extended to the non-stationary processes by including covariates in the parameters of the models. For the purpose of obtaining an approximately independent threshold excesses, a declustering method was performed and then the de-clustered peaks were fitted to the generalized Pareto distribution. The stationary Gumbel distribution was found a reasonable model for the annual block maxima; however, a non-stationary generalized extreme value distribution with quadratic trend in the location was recommended for the half-yearly period. The findings also show that there is an improvement in modelling daily maxima temperature when it is applied to the declustered series and the given model outperforms the non-stationary generalized Pareto distribution models. Furthermore, the retained generalized Pareto distribution model proved better than the generalized extreme value distribution. Estimates of the return levels obtained from both extreme value models show that new records on maximum temperature event could appear within the next 20, 50 and 100 years.     

Extreme Nitrogen Oxide and Ozone Concentrations in Athens Atmosphere in Relation to Meteorological Conditions

In the present study, we investigate the variation of NO _x (NO + NO₂) and O₃ concentrations and the relation between the extreme events (episodes) of NO _x and O₃ concentrations and the relevant meteorological conditions in the urban atmosphere of the Athens basin. Hourly data of NO, NO₂ and O₃ concentrations from 10 representative monitoring sites located in the Athens basin were used, covering the 10-year time period from 1994 to 2003. The results of our analysis show that the concentrations of air pollutants differ significantly from one monitoring site to another, due to the location and proximity of each station to the emission sources. For each site, there are also significant differences in NO _x and O₃ concentrations from day to day, as well as from month to month and/or from season to season. The annual and seasonal variations show higher NO values in winter and lower in summer. On the contrary, NO₂ and O₃ values are higher in summer (photochemical production of O₃) and lower in winter. These differences are attributed, to a large extent, to the prevailing synoptic and meteorological conditions, the most important between them being the wind direction and speed as well as the atmospheric pressure. Our analysis of the identified 179 extreme NO _x air pollution events shows that most of them took place under anticyclonic conditions, associated with calm or weak winds (speed <2.5 ms⁻¹) of mostly southern to southwestern directions, as well as with low air temperatures and intense stable surface atmospheric conditions. There exists a significant decreasing tendency in NO _x air pollution episodic events over the 10-year study period, resulting in very few to none events in the period from 2000 to 2003. As far as it concerns the extreme O₃ concentrations, 34 air pollution events were identified, occurring under high air temperatures, variable weak winds and intense solar irradiation. The trends of O₃ concentrations are stronger in suburban sites than in urban ones.     

The Application of Water Quality Monitoring Data in a Reservoir Watershed Using AMOS Confirmatory Factor Analyses

This study investigates six water quality monitoring stations in the watershed of the Feitsui Reservoir. It uses nine parameters of water quality collected in an interval of two and half years for factor analyses, which was first conducted to determine four types of factors, respectively, those for organic pollution, eutrophication, seasonal influence, and sediment pollution. The analysis results effectively help to determine water quality in the watershed of the reservoir. The authors reutilize analysis of moment structures (AMOS) to acquire further results in order to confirm the goodness of fit of the previous factor analysis model. During the confirmation, we examine the hypothesized orthogonal results as well as utilize oblique rotation to explore the goodness of fit of the reflective indicators of the orthogonal rotation. As shown in the algorithm results, as long as the covariance curve is included in the four factors, no related issues are detected in the goodness of fit of reflective indicators and interior and external quality is reported with excellence. The orthogonal model, thus, stands. Additionally, when the analysis of structural equation modeling (SEM) is conducted, sample data mismatches the hypotheses of multivariate normality. Therefore, this study adopts the generalized least square (GLS) for an algorithm. Research results of this study have been submitted to the reservoir management authorities in Taiwan for the improvement of statistical application and strategic evaluation of water quality monitoring data in order to strengthen the managerial effectiveness of water quality in watersheds.     

Bivariate Extreme Value Analysis of Rainfall and Temperature in Nigeria

Environmental Modeling & Assessment - The rising cases of floods and the onset of drought in different parts of Nigeria require urgent attention particularly because Nigeria accommodates the...     

Multimedia Integrated Modeling for Environmental Protection: Introduction to a Collaborative Framework

The EPA's Office of Research and Development is embarking on a long term project to develop a Multimedia Integrated Modeling System (MIMS). The system will have capabilities to represent the transport and fate of nutrients and chemical stressors over multiple spatial and temporal scales. MIMS will be designed to improve the environmental management community's ability to evaluate the impact of air and water quality and watershed management practices on stream and estuarine conditions. The system will provide a computer-based problem-solving environment for testing understanding of multimedia (atmosphere, land, water) environmental problems, such as the movement of chemicals through the hydrologic cycle, and the response of aquatic ecological systems to land-use change, with initial emphasis on the fish health endpoint. The design will attempt to combine the state-of-the-art in computer science, system design, and numerical analysis (i.e., object-oriented design, parallel processing, advanced numerical libraries including analytic elements) with the latest advancements in process level science (hydrology, atmospheric sciences, chemistry, ecology). The purpose of this paper is to introduce a vision for a MIMS and anticipate the challenges to its development.     

An Approach to Reaeration Coefficient Modeling in Local Surface Water Quality Monitoring

Reaeration coefficient (k ₂) for River Atuwara, Ogun State, Nigeria was calculated from dissolved oxygen and biochemical oxygen demand data collected over period of 3 months covering the two prevailing climatic seasons in the country. Both the Akaike and Bayesian information criteria were used in the selection and analysis of ten models to identify the most suitable reaeration coefficient (k ₂) model for Atuwara River. Models that passed the confidence limit were subjected to model evaluation using measures of agreement between observed and predicted data such as percent bias, Nash–Sutcliffe efficiency, and root mean square observation standard deviation ratio. The used approach yield better results than empirical models developed for local conditions while it is also useful in conserving scarce resources.     

ICP在环境分析中的应用

对近年来ICP—AES和ICP—MS在环境分析中的应用情况进行了综述,并对其在环境分析中的发展前景作了评估。     

Follow-up to environmental impact assessment: Learning from the Canadian Government experience

The environmental impact assessment procedure for Canadian federal government projects is briefly described. In the non-legislated Canadian system, follow-up to assessments is one of the major means of encouraging and improving the implementation of environmental impact assessment and the quality of environmental work done around development projects. The results of a study on the status of follow-up in the Canadian Government are presented. Factors that limit and that are conducive to follow-up are discussed. The effectiveness of follow-up depends as much on the circumstances surrounding a project and the concerned parties as on the follow-up techniques used; both of these aspects can be addressed in the planning and management of follow-up and of environmental impact assessment overall. Areas for improving the management of follow-up are identified and discussed: planning of follow-up activities, coordination of concerned parties, generation of clear understandings, information management, resource allocation, and maintenance of credibility. A method for planning follow-up activities for specific projects is presented.     

Seasonal variations of dissolved inorganic nutrients transported to the Linjiang Bay of the Three Gorges Reservoir, China

Field surveys were carried out from January 2007 to December 2008 to investigate seasonal variations of dissolved inorganic nitrogen (DIN) and phosphorus (DIP) transported to the Linjiang Bay of the Three Gorges Reservoir, China. The results revealed that both DIN and DIP exhibited large seasonal variability. DIN (dominated by NH₄?CN) concentrations were drastically higher in the dry season than those in the rainy season, and the same seasonal patterns of DIP concentrations and DIN and DIP fluxes were observed but inverse to that of DIN concentrations. The interannual variation in DIN fluxes descended by 28.2% from 2007 to 2008, while DIP fluxes increased by 40.9%, which were closely constant with interannual changes in DIN and DIP concentrations, respectively. The study indicated that nutrient fluxes (DIN and DIP) were strongly correlated with both nutrient concentrations and river discharge, and the Linjiang Bay received approximately 3,416 × 10³ kg DIN and 324 × 10³ kg DIP every year. In addition, DIN mainly originated from point sources, but DIP originated from non-point sources. It is shown that to control point source pollution is the most effective step for water quality improvement and reducing nutrient loading inputs in the Linjiang Bay.     

Aggregated Versus Individual Land-Use Models: Modeling Spatial Autocorrelation to Increase Predictive Accuracy

The objective of this paper is to compare the predictive accuracy of individual and aggregated econometric models of land-use choices. We argue that modeling spatial autocorrelation is a comparative advantage of aggregated models due to the smaller number of observation and the linearity of the outcome. The question is whether modeling spatial autocorrelation in aggregated models is able to provide better predictions than individual ones. We consider a complete partition of space with four land-use classes: arable, pasture, forest, and urban. We estimate and compare the predictive accuracies of individual models at the plot level (514,074 observations) and of aggregated models at a regular 12 × 12 km grid level (3,767 observations). Our results show that modeling spatial autocorrelation allows to obtain more accurate predictions at the aggregated level when the appropriate predictors are used.     

Sizing an Off-stream Reservoir with Respect to Water Availability,Water Quality,and Biological Integrity

Sizing a new reservoir is a challenging task, which normally requires simultaneously a cost-effective, risk-informed, and forward-looking decision analysis with respect to basin-wide hydrological features, environmental quality, and biological integrity. Such a sustainable planning approach takes into account the global trend to balance the needs of economic growth, ecological conservation, and environmental protection. To achieve the goal of sustainability, emphasis in this paper was placed upon the correlation of three physical, chemical, and biological indices, including the dissolved oxygen (DO), the 5-day biochemical oxygen demand (BOD₅), and the index of biotic integrity (IBI), for the optimal planning of a reservoir in a river basin. This new methodological paradigm has been employed for sizing an off-stream reservoir in the Hou-Lung River Basin, central Taiwan. The internal linkage between the water quality parameters (DO and BOD₅) and the IBI levels further enables us to formulate a special biotic integrity constraint which reflects fish community attributes to suit a relatively low-density and unspecialized freshwater fish fauna in response to the changing water quality conditions in the river basin. The tradeoffs among economic, environmental, and ecological aspects for reservoir sizing can then be based on the river flow patterns, the water demand, the water quality standards, and the anticipated biological integrity in some critical river reaches. Findings in a preliminary case study suggest that an optimal pumping scheme may be smoothly maintained on a yearly basis within a combined multicriteria and multiobjective decision-making process.     

Modeling Runoff Response to Land Cover and Rainfall Spatial Variability in Semi-Arid Watersheds

Hydrologic response is an integrated indicator of watershed condition, and significant changes in land cover may affect the overall health and function of a watershed. This paper describes a procedure for evaluating the effects of land cover change and rainfall spatial variability on watershed response. Two hydrologic models were applied on a small semi-arid watershed; one model is event-based with a one-minute time step (KINEROS), and the second is a continuous model with a daily time step (SWAT). The inputs to the models were derived from Geographic Information System (GIS) theme layers of USGS digital elevation models, the State Soil Geographic Database (STATSGO) and the Landsat-based North American Landscape Characterization classification (NALC) in conjunction with available literature and look up tables. Rainfall data from a network of 10 raingauges and historical stream flow data were used to calibrate runoff depth using the continuous hydrologic model from 1966 to 1974. No calibration was carried out for the event-based model, in which six storms from the same period were used in the calculation of runoff depth and peak runoff. The assumption on which much of this study is based is that land cover change and rainfall spatial variability affect the rainfall-runoff relationships on the watershed. To validate this assumption, simulations were carried out wherein the entire watershed was transformed from the 1972 NALC land cover, which consisted of a mixture of desertscrub and grassland, to a single uniform land cover type such as riparian, forest, oak woodland, mesquite woodland, desertscrub, grassland, urban, agriculture, and barren. This study demonstrates the feasibility of using widely available data sets for parameterizing hydrologic simulation models. The simulation results show that both models were able to characterize the runoff response of the watershed due to changes of land cover.     

丹江口水库总氮较高原因初步分析

通过对丹江口水库库区、河南省辖入库河流及其它水体含氮类指标的对比,对水库总氮偏高的原因加以分析,指出总氮标准与硝酸盐、氨氮标准有差异,提出合理评价总氮指标及水库水质、加强水质保护措施的建议。