Uncertainty in watershed response predictions induced by spatial variability of precipitation

Negligence to consider the spatial variability of rainfall could result in serious errors in model outputs. The objective of this study was to examine the uncertainty of both runoff and pollutant transport predictions due to the input errors of rainfall. This study used synthetic data to represent the “true” rainfall pattern, instead of interpolated precipitation. It was conducted on a synthetic case area having a total area of 20 km² with ten subbasins. Each subbasin has one rainfall gauge with synthetic precipitation records. Six rainfall storms with varied spatial distribution were generated. The average rainfall was obtained from all of the ten gauges by the arithmetic average method. The input errors of rainfall were induced by the difference between the actual rainfall pattern and estimated average rainfall. The results show that spatial variability of rainfall can cause uncertainty in modeling outputs of hydrologic, which would be transport to pollutant export predictions, when uniformity of rainfall is assumed. Since rainfall is essential information for predicting watershed responses, it is important to consider the properties of rainfall, particularly spatial rainfall variability, in the application of hydrologic and water quality models.     

Mapping nitrate leaching to upper groundwater in the sandy regions of The Netherlands, using conceptual knowledge

The European Community asks its Member States to provide a comprehensive and coherent overview of their groundwater chemical status. It is stated that simple conceptual models are necessary to allow assessments of the risks of failing to meet quality objectives. In The Netherlands two monitoring networks (one for agriculture and one for nature) are operational, providing results which can be used for an overview. Two regression models, based upon simple conceptual models, link measured nitrate concentrations to data from remote sensing images of land use, national forest inventory, national cattle inventory, fertiliser use statistics, atmospheric N deposition, soil maps and weather monitoring. The models are used to draw a nitrate leaching map and to estimate the size of the area exceeding the EU limit value in the early 1990s. The 95% confidence interval for the fraction nature and agricultural areas where the EU limit value for nitrate (50 mg/l) was exceeded amounted to 0.77–0.85 while the lower 97.5% confidence limit for the fraction agricultural area where the EU limit value was exceeded amounted to 0.94. Although the two conceptual models can be regarded as simple, the use of the models to give an overview was experienced as complex.     

Exploring the Relationship Between Hydrologic Parameters and Nutrient Loads Using Digital Elevation Model and GIS – A Case Study from Sugarcreek Headwaters, Ohio, U.S.A.

Ohio is typical among the Midwestern and Eastern United States with high levels of water pollutants, the main sources being from agriculture. In this study, we used a digital elevation model in conjunction with hydrological indices to determine the role of landscape complexity affecting the spatial and temporal variation in pollutant levels, in one of the most impaired headwater streams in Ohio. More than eighty five percent of the study area is dominated by agriculture. Spatial distribution of slope (S), altitude and wetness index along with other watershed parameters such as flow direction, flow accumulation, stream networks, flow stream orders and erosion index were used within a Geographic Information Systems framework to quantify variation in nitrate and phosphate loads to headwater streams. Stream monitoring data for nutrient loads were used to correlate the observed spatial and temporal patterns with hydrological parameters using multiple linear regressions. Results from the wetness index calculated from a digital elevation model suggested a range of 0.10–16.39, with more than 35% having values less than 4.0. A Revised Universal Soil Loss Equation (RUSLE) predicted soil loss in the range of 0.01–4.0 t/ha/yr. Nitrate nitrogen levels in the study area paralleled precipitation patterns over time, with higher nitrate levels corresponding to high precipitation. Atmospheric deposition through precipitation could explain approximately 35% of total nitrate levels observed in streams. Among the different topographic variables and hydrological indices, results from the step-wise multiple regression suggested the following best predictors, (1) elevation range and upstream flow length for nitrate, (2) flow direction and upstream flow length for ammonia-nitrogen and slope, and (3) elevation range for phosphate levels. Differences in the landscape models observed for nitrate, phosphate and ammonia-nitrogen in the surface waters were attributed partly to differences in the chemical activity and source strengths of the different forms of these nutrients through agricultural management practices. The results identify geomorphologic and landscape characteristics that influence pollutant levels in the study area.     

Numerical Modeling on the Effect of Dissolved Oxygen on Nitrogen Transformation and Transport in Unsaturated Porous System

Nitrogen pollution in groundwater resulting from wastewater application to land is a common problem, and it causes a major threat to groundwater-based drinking water supplies. In this study, a numerical model is developed to study the nitrogen species transport and transformation in unsaturated porous media. Further, a new mass transfer module for dissolved oxygen (DO) is incorporated in the one-dimensional numerical model for nitrogen species transport to describe the fate and transport of nitrogen species, dissolved oxygen, dissolved organic carbon (DOC), and biomass. The spatial and temporal variation of dissolved oxygen is incorporated in the model through the mass transfer from gaseous phase to water phase in an unsaturated porous system. The numerical results of the water flow model and single species and multispecies transport model in an unsaturated zone developed for this purpose have been validated with the available analytical/numerical solution. The developed model is applied in clay loam, silt, and sand soils to analyze the transport behavior of nitrogen species under unsaturated condition. The numerical results suggest that the high rate of oxygen mass transfer from the air phase to the water phase positively increases the dissolved oxygen in the applied wastewater and enhances the nitrification process. Because of this high oxygen mass transfer, the nitrate nitrogen concentration significantly increases in the unsaturated zone and the same is transported to a larger depth at higher simulation period. On the other hand, the low rate of oxygen mass transfer implicitly enhances the denitrification process and finally reduces the nitrate nitrogen concentration in the unsaturated zone. The numerical results also show that the nitrate nitrogen transport is rapid in sandy soil when compared with clay loam and silty soils under high oxygen mass transfer rate. In essence, the high oxygen mass transfer rate significantly increases the nitrate nitrogen in the unsaturated zone, especially at a greater depth at larger time levels and eventually affects the groundwater quality.     

Modeling of nitrate concentration in groundwater using artificial intelligence approach—a case study of Gaza coastal aquifer

Nitrate concentration in groundwater is influenced by complex and interrelated variables, leading to great difficulty during the modeling process. The objectives of this study are (1) to evaluate the performance of two artificial intelligence (AI) techniques, namely artificial neural networks and support vector machine, in modeling groundwater nitrate concentration using scant input data, as well as (2) to assess the effect of data clustering as a pre-modeling technique on the developed models' performance. The AI models were developed using data from 22 municipal wells of the Gaza coastal aquifer in Palestine from 2000 to 2010. Results indicated high simulation performance, with the correlation coefficient and the mean average percentage error of the best model reaching 0.996 and 7 %, respectively. The variables that strongly influenced groundwater nitrate concentration were previous nitrate concentration, groundwater recharge, and on-ground nitrogen load of each land use land cover category in the well's vicinity. The results also demonstrated the merit of performing clustering of input data prior to the application of AI models. With their high performance and simplicity, the developed AI models can be effectively utilized to assess the effects of future management scenarios on groundwater nitrate concentration, leading to more reasonable groundwater resources management and decision-making     

STUMOD—a Tool for Predicting Fate and Transport of Nitrogen in Soil Treatment Units

A typical onsite wastewater treatment system consists of a septic tank and a soil treatment unit to treat wastewater before it is discharged through the vadose zone to an aquifer. A tool was developed for the purpose of predicting the fate and transport of nitrogen in soil treatment units (STUMOD or Soil Treatment Unit Model). STUMOD calculates nitrogen species concentrations and the fraction of total nitrogen reaching the aquifer or a specified soil depth. Input data include parameters for hydraulics and nutrient transport and transformation. An analytical solution is used to calculate the profile of pressure based on Darcy’s equation and the relationships between suction head, unsaturated hydraulic conductivity, and soil moisture. Chemical transport is based on simplification of the advection–dispersion equation. STUMOD is relatively simple to use but accounts for important processes such as ammonium sorption, nitrification, and denitrification. STUMOD accounts for the effect of soil moisture content (a surrogate for redox conditions) on nitrification and denitrification reactions. The model has provisions to handle the influence of temperature and organic carbon content on nitrogen transformation. Model outputs, generated based on input parameters obtained from extensive literature review, were compared to a numerical model and data from laboratory tests and field sites. Both measured data and STUMOD outputs show a relatively higher removal in clayey soils compared to sandy soils. Consistent with literature data for most soils, STUMOD predicted ammonium conversion to nitrate within the first foot below the trench infiltrative surface.     

Are Nitrogen-Fertilized Forest Soils Sinks or Sources of Carbon?

We developed a simple conceptual model that tracks nitrogen and carbon jointly through an N fertilized forest ecosystem. The stimulation of growth increases the litterfall and imports substrate for soil microorganisms. Microbial biomass forms according to the supply of C and N. The formation of microbial biomass is accompanied by respiratory C losses. The quantity of CO₂ efflux depends on the C use efficiency of microbes. When excess N is available, the microbial activity is accelerated and the demand for substrate is high. Litterfall supplies an insufficient amount of C to the soil. In such a case, labile soil C is mineralized and the net effect of N fertilization is a loss of soil C. A strong N fertilization effect on the aboveground biomass can offset the soil C loss. In the case of a low N dosage or high N losses due to leaching or emission of nitrogen oxides, the soil C loss is small. The conceptual model was applied to a case study. The field data, collected over a time span of several decades, could not support sound conclusions on the temporal trend of soil C because the spatial and temporal variability of the chemical data was high. The conceptual model allowed to give an evaluation of the fertilization effect on soil C based on reproducible principles.     

Evaluation of ground water denitrification at a biosolids disposal site

A study was conducted at a sanitary sewage sludge(biosolids) disposal site in Springfield, Illinois, U.S.A. todetermine if biological denitrification played a significantfactor in attenuation of ground water nitrate values. The siteselected for this study is a 23 ha (57 acre) dedicatedbiosolids disposal facility located adjacent to a 75.7 millionliter per day (20 million gallons per day) municipal treatmentplant that uses anaerobic solids stabilization for treatment ofgenerated biosolids material. Biosolids have been disposed of byfixed-point spray applicators at the site since 1976, which hascaused ground water nitrate levels to increase significantlyabove background levels. A method was developed using aconservative chemical tracer to simulate the biosolidsapplication process and monitor the ground water directly beneaththe simulated disposal site. Results demonstrated a net declineof nitrates that could not be attributed to dilution alone.While the monitoring methodology developed for this study didnot directly estimate the denitrification rate, a rate foroverall nitrate reduction was calculated that could be consideredto take into account all transport and reduction mechanisms suchas denitrification, advection, dispersion and dilution.     

Temporal and spatial change detecting (1998–2003) and predicting of land use and land cover in Core corridor of Pearl River Delta (China) by using TM and ETM+ images

Land use/land cover (LULC) has a profound impact on economy, society and environment, especially in rapid developing areas. Rapid and prompt monitoring and predicting of LULC’s change are crucial and significant. Currently, integration of Geographical Information System (GIS) and Remote Sensing (RS) methods is one of the most important methods for detecting LULC’s change, which includes image processing (such as geometrical-rectifying, supervised-classification, etc.), change detection (post-classification), GIS-based spatial analysis, Markov chain and a Cellular Automata (CA) models, etc. The core corridor of Pearl River Delta was selected for studying LULC’s change in this paper by using the above methods for the reason that the area contributed 78.31% (1998)–81.4% (2003) of Gross Domestic Product (GDP) to the whole Pearl River Delta (PRD). The temporal and spatial LULC’s changes from 1998 to 2003 were detected by RS data. At the same time, urban expansion levels in the next 5 and 10 years were predicted temporally and spatially by using Markov chain and a simple Cellular Automata model respectively. Finally, urban expansion and farmland loss were discussed against the background of China’s urban expansion and cropland loss during 1990–2000. The result showed: (1) the rate of urban expansion was up to 8.91% during 1998–2003 from 169,078.32 to 184,146.48 ha; (2) the rate of farmland loss was 5.94% from 312,069.06 to 293,539.95 ha; (3) a lot of farmland converted to urban or development area, and more forest and grass field converted to farmland accordingly; (4) the spatial predicting result of urban expansion showed that urban area was enlarged ulteriorly compared with the previous results, and the directions of expansion is along the existing urban area and transportation lines.     

The use of simple kinetic models to help design environmental monitoring systems

This paper describes the application of simple linear models to help design environmental monitoring systems. This process involves five steps: (1) The derivation of a schematic of the identified pollutant's transport and fate. (2) The derivation of the equation in the schematic. (3) Estimation of input data and numerical solution. (4) Comparison with initial field data. (5) Design of a monitoring system.Two examples of how this system was applied under field conditions are given. Advantages of this approach are: (1) It forces a consideration of the system as a whole rather than a series of distinct environmental components. (2) It forces a consideration of the physical-chemical and biological factors effecting pollutant transport in the system. (3) It sets up an analytical procedure for data analysis at the time the monitoring system is designed. (4) It helps show the functional relationship between pollutant levels in different environmental media. (5) It identifies points where sampling design could be changed to provide for a more efficient monitoring system. (6) It identifies gaps in our knowledge base.     

Modelling of spatial contaminant probabilities of occurrence of chlorinated hydrocarbons in an urban aquifer

In this study, a 3D urban groundwater model is presented which serves for calculation of multispecies contaminant transport in the subsurface on the regional scale. The total model consists of two submodels, the groundwater flow and reactive transport model, and is validated against field data. The model equations are solved applying finite element method. A sensitivity analysis is carried out to perform parameter identification of flow, transport and reaction processes. Coming from the latter, stochastic variation of flow, transport, and reaction input parameters and Monte Carlo simulation are used in calculating probabilities of pollutant occurrence in the domain. These probabilities could be part of determining future spots of contamination and their measure of damages. Application and validation is exemplarily shown for a contaminated site in Braunschweig (Germany), where a vast plume of chlorinated ethenes pollutes the groundwater. With respect to field application, the methods used for modelling reveal feasible and helpful tools to assess natural attenuation (MNA) and the risk that might be reduced by remediation actions.     

全球及区域碳模拟与源汇同化反演研究进展

近年来,全球和区域碳模拟与同化反演系统(简称“碳同化系统”)快速发展,并被广泛应用于不同时空尺度的碳通量和碳汇估算、碳排放量校核研究中,为支撑全球碳盘点提供了关键技术手段。文章回顾了国内外主要碳同化系统的发展历程和应用案例,总结了当前常见的全球和区域碳同化系统的结构和特点,包括使用的大气传输模式、同化方法、空间分辨率等内容;探讨了当前常见模型系统应用中的关键问题、不足与发展方向,以期为碳同化系统应用于我国环境管理和气候变化工作提供参考。     

Heavy metals fractionation in surface sediments of Gowatr bay-Iran

Establishing the effectiveness of habitat features to act as surrogate measures of diversity and abundance of juvenile reef fish provides information that is critical to coral reef management. When accurately set on a broader spatial context, microhabitat information becomes more meaningful and its management application becomes more explicit. The goal of the study is to identify coral reef areas potentially important to juvenile fishes in Ngederrak Reef, Republic of Palau, across different spatial scales. To achieve this, the study requires the accomplishment of the following tasks: (1) structurally differentiate the general microhabitat types using acoustics; (2) quantify microhabitat association with juvenile reef fish community structure; and (3) conduct spatial analysis of the reef-wide data and locate areas optimal for juvenile reef fish settlement. The results strongly suggest the importance of branching structures in determining species count and abundance of juvenile reef fish at the outer reef slope of Ngederrak Reef. In the acoustic map, the accurate delineation of these features allowed us to identify reef areas with the highest potential to harbor a rich aggregation of juvenile reef fish. Using a developed spatial analysis tool that ranks pixel groups based on user-defined parameters, the reef area near the Western channel of Ngederrak is predicted to have the most robust aggregation of juvenile reef fish. The results have important implications not only in management, but also in modeling the impacts of habitat loss on reef fish community. At least for Ngederrak Reef, the results advanced the utility of acoustic systems in predicting spatial distribution of juvenile fish.     

An Approach to Multi-criteria Environmental Evaluation with Multiple Weight Assignment

In the domain of environmental protection, multi-criteria evaluation is used in cases where multiple alternatives, on the bases of multiple parameters, need to be evaluated. Depending on the particular goal of investigation, various approaches have been developed and applied. This various multi-criteria approaches differ in parameter weighting method, in data normalization method as well as in the method for assessment of alternatives. According to the applied multi-criteria methodology, the result, i.e., the rank of alternatives may differ to some extent. In this context, parameter weighting bears special significance in multi-criteria evaluation, while the choice of method is crucial for final result. The specificity of parameter weighting process in environment protection is directly related to pronounced interdisciplinary character of this area, as well as the large number of influential parameters. With this in mind, this paper presents an approach to multi-criteria evaluation which—through integration of three specific methods for parameter weighting—allows more flexible and multi-purpose application. Based on the established concept, a software application was developed. Besides automated parameter weighting, it also provides graphical interpretation of results. The developed approach and software have been verified on the case study related to evaluation of environmental loadings at six locations in the city of Novi Sad.     

Distributed process modeling for regional assessment of coastal vulnerability to sea-level rise

Sea-level rise involves increases in the coastal processes of inundation and erosion which are affected by a complex interplay of physical environmental parameters at the coast. Many assessments of coastal vulnerability to sea-level rise have been detailed and localised in extent. There is a need for regional assessment techniques which identify areas vulnerable to sea-level rise. Four physical environmental parameters – elevation, exposure, aspect and slope, are modeled on a regional scale for the Northern Spencer Gulf (NSG) study area using commonly available low-resolution elevation data of 10 m contour interval and GIS-based spatial modeling techniques. For comparison, the same parameters are modeled on a fine-scale for the False Bay area within the NSG using high-resolution elevation data. Physical environmental parameters on the two scales are statistically compared to coastal vulnerability classes as identified by Harvey et al. [1] using the Spearman rank-correlation test and stepwise linear regression. Coastal vulnerability is strongly correlated with elevation and exposure at both scales and this relationship is only slightly stronger for the high resolution False Bay data. The results of this study suggest that regional scale distributed coastal process modeling may be suitable as a first cut in assessing coastal vulnerability to sea-level rise in tide-dominated, sedimentary coastal regions. Distributed coastal process modeling provides a suitable basis for the assessment of coastal vulnerability to sea-level rise of sufficient accuracy for on-ground management and priority-setting on a regional scale.     

Temporal moments analysis of preferential solute transport in soils

Temporal moments analysis of solute breakthrough curves is used to investigate the preferential leaching of chloride, nitrate and phosphate through an Australian soil. Recent studies have shown that current models and methods do not adequately describe the leaching of nutrients through soil, often underestimating the risk of groundwater contamination by surface-applied chemicals, and overestimating the concentration of resident solutes. This inaccuracy results primarily from ignoring soil structure and non-equilibrium between soil constituents, water and solutes. Therefore simple models are required to accurately characterise solute transport in natural and agricultural soils under non-equilibrium conditions. A multiple sample percolation system, consisting of 25 individual collection wells was constructed to study the effects of localised soil heterogeneities on the transport of nutrients (NO₃ ^–, Cl^–, PO₄ ^{3 –}) in the vadose zone of an agricultural soil predominantly dominated by clay. Using data collected from the multiple sample percolation experiments, this paper compares and contrasts the performance of temporal moments analysis with two mathematical models for predicting solute transport, the advective-dispersion model with a reaction term (ADR) and a two-region preferential flow model (TRM) suitable for modelling preferential transport. The values for solute transport parameters predicted by temporal moments analysis were in excellent agreement with experimental data and results from ADR and TRM. It is concluded that temporal moments analysis when applied with other physical models such as the ADR and TRM, provide an excellent means of obtaining values for important solute transport parameters and gaining insight of preferential flow. These results have significant ramifications for modelling solute transport and predicting nutrient loadings.     

Selection and Calibration of Numerical Modeling in Flow and Water Quality

Numerical modeling is frequently used in coastal engineering research and application. One possible issue associated with using this method however, is that initial outcomes might differ from expectation. Modeling manipulation addresses this issue by changing the initial parameters which in turn affects the final output results.The advancement of modeling techniques in recent years has seen a gradual but steady accruement of knowledge regarding the relationship between input parameters and possible outputs, which has resulted in improved accuracy and efficiency methods. The advancements within this field have predominantly occurred on an individual basis and as such lack standardisation. An expert numerical modeler may use this knowledge subconsciously, yet may not know how to convey it to the model users. This paper has been written to introduce a systematic intelligent coding schema designed to organise current coastal engineering modeling manipulation knowledge into a standardised format. This system is relevant to the development of appropriate strategies for improved accuracy and efficiency as well as model modification to simulate specific real phenomena in prototype application cases.     

Modelling the Competitive Sorption Process of Multiple Solutes During their Transport in Porous Media

A general mathematical model to solve the advection–dispersion transport equation for multiple solutes was developed, where the dual porosity mobile–immobile mass transfer, the two-site non-equilibrium model and first-order transformation reactions were included. The two-site model was expressed with an equilibrium sorption term and a kinetic term. One of three kinetic models could be used: the non-linear, the bilinear and the pore diffusion model. The traditional Freundlich or Langmuir isotherms were employed to simulate no-interaction between the solutes, but with the extended Freundlich or extended Langmuir isotherms, a competitive sorption could be simulated. The transport equation was solved with the Moving Concentration Slope method. The mathematical model was tested and further simplified by using real data from soil column experiments, with 1,2-cis-dichloroethene and trichloroethene as model contaminants and silica gel and real soil samples as porous medium.