OPEN CHANNEL INTERPOLATION OF CROSS SECTIONAL PROPERTIES1

ABSTRACT: This paper confirms the use of interpolated data to refine water surface profiles. Sources of error within these computations are due to truncation error, inaccuracies in geometric data, and improper modeling. Confirmation includes the development of an equation that models the effect of data measurement error on the computed water surface profile. A review of interpolation procedures includes a proposed method based upon geometric properties.     

HYDROLOGIC MODELING WITH REMOTELY SENSED DATABASES1

ABSTRACT: An integrated remotely sensed database was used as the basis for a hydrologic and sediment transport modeling effort for an agricultural area of western Puerto Rico. Classified spectral images of airborne radiance data provided ground cover information and were used in conjunction with topographic and soils data to guide model construction and provide input to the water balance and sediment yield simulations. Runoff and sediment discharge from hydrologically homogeneous regions were routed through the drainage network and combined at the basin outlet. The model was used to simulate four years of observed sediment discharge from the basin. Relative contributions to the total sediment yield of forested and agricultural areas were determined and compared.     

南山铁矿风场及扩散规律风洞模拟研究

以风洞模拟方式研究中性层结条件下南山铁矿凹山采场地域边界层风场特征,并以示踪气体扩散摸拟方法给出该地域大气扩散参数的实验结果。     

新建水库初期磷氮变化的动态模拟研究

本文首先建立磷氮时空分布模型并确定模型参数的率定方法。文章模拟了新建清平水库建库初期磷氮变化情况,得出由不稳定到稳定的过程。水库磷氮时空变化的模拟结果表明,空间分布是从库尾到大坝浓度逐渐递砬,时间分布是一年中Ｐ,Ｎ浓度七月份最高,年初年末最低,其分布央线类似高斯分布。     

Sensitivity of Ozone Production to the Nmhc Composition, Aerosol Back-Scattering and High Chimney Emission

In this paper, three sensitivity studies are designed to analyze the effect of the NMHC (Non-Methane HydroCarbon) composition, the aerosol back-scattering and the high chimney NO_x emission to the photochemical prodution of ozone by using a one-dimensional photochemistry-diffusion model under a favourable meteorological condition. Measurements of the NMHC composition in Taipei indicated that the percentage of iso-butene, cis-2-butene, trans-2-butene and benzene in a unit volume was much higher than of those observed in other major cities. the high ratio of benzene was directly linked to its high percentage in gasoline. As to the unusually high amount of iso-butene, cis-2-butene and trans-2-butene, more researches are needed to identify their source. Concerns are raised as to how productive is NMHC composition is to the photochemical production of the surface ozone. A rough estimate shows that the total reactivity of the Taipei NMHC composition is about 1.21 × 10^-9 cm³ s^-1 which is 1.6 times that of the Los Angeles (LA) NMHC composition, while the simulated noon peak will be different by 28 ppbv, i.e. 18% more than that simulated with a LA composition.

Meanwhile, high aerosol loading is a serious problem in Taipei. the attenuation of the UV radiation by aerosols cannot be ignored. A numerical simulation shows that the noon ozone level will decrease from 178 to 141ppbv, i. e. about 21% reduction, with deterioration of the visual range from 85 to 5 km.

In the southern Taiwan, industry parks are mixed with the populated Kaohsiung city, hence the large emission of NO_x from high chimneys cannot be ignored. in this study, NO_x is assumed to be emitted in the layer between 235-460 m high with an emission rate of 0.05 or 0.145 ppbv/sec. the results show that the NO_x emitted from the elevated stack lead to a considerable reduction of surface ozone. Such conclusion is obtained due to the fact that a one-dimensional model is used in this paper. Whereas, if a three-dimensional regional model was used, then a higher productivity of ozone downstream would be simulated.     

Rough Set Rule Induction for Suitability Assessment

The data that characterize an environmental system are a fundamental part of an environmental decision-support system. However, obtaining complete and consistent data sets for regional studies can be difficult. Data sets are often available only for small study areas within the region, whereas the data themselves contain uncertainty because of system complexity, differences in methodology, or data collection errors. This paper presents rough-set rule induction as one way to deal with data uncertainty while creating predictive if–then rules that generalize data values to the entire region. The approach is illustrated by determining the crop suitability of 14 crops for the agricultural soils of the Willamette River Basin, Oregon, USA. To implement this method, environmental and crop yield data were spatially related to individual soil units, forming the examples needed for the rule induction process. Next, four learning algorithms were defined by using different subsets of environmental attributes. ROSETTA, a software system for rough set analysis, was then used to generate rules using each algorithm. Cross-validation analysis showed that all crops had at least one algorithm with an accuracy rate greater than 68%. After selecting a preferred algorithm, the induced classifier was used to predict the crop suitability of each crop for the unclassified soils. The results suggest that rough set rule induction is a useful method for data generalization and suitability analysis.     

Watershed scale assessment of nitrogen and phosphorus loadings in the Indian River Lagoon basin,Florida

There is a growing evidence that the ecological and biological integrity of the lagoon has declined during the last 50 years, probably due to the decline in water quality. Establishment of a watershed scale seagrass-based nutrient load assessment is the major aim of water quality management in the Indian River Lagoon (IRL). Best estimate loadings incorporate wet and dry deposition, surface water, groundwater, sediment nutrient flux, and point source effluent discharge data. On the average, the IRL is receiving annual external loadings of 832, 645 and 94,476kg of total nitrogen (TN) and total phosphorus (TP), respectively, from stormwater discharges and agricultural runoff. The average internal cycling of TN and TP from sediment deposits in the IRL was about 42,640kg TN and 1050kg TPyr(-1). Indirect evidence suggests that atmospheric deposition has played a role in the ongoing nutrient enrichment in the IRL. The estimated total atmospheric deposition of TN and TP was about 32,940 and 824kgyr(-1), while groundwater contribution was about 84,920 and 24,275kgyr(-1), respectively, to the surface waters of the IRL. The estimated annual contribution of point effluent discharge was about 60,408kg TN and 7248kg TP. In total, the IRL basin is receiving an annual loading of about 1,053,553kg TN and 127,873kg TP. With these results, it is clear that the current rate of nutrient loadings is causing a shift in the primary producers of the IRL from macrophyte to phytoplankton- or algal-based system. The goal is to reverse that shift, to attain and maintain a macrophyte-based estuarine system in the IRL.     

Numerical Prediction of Dispersion Characteristics in an Urban Area Based on Grid Refinement and Various Turbulence Models

A detailed simulation of the Goettinger Strasse pollutantdispersion problem is performed using the CFD code CFX-TASCflow for different wind directions. Two turbulencemodels, the k- and the RSM are adopted on three gridrefinement levels. Besides the typical reference gridimplemented by the TRAPOS group, two different gridresolutions are introduced. The first refinement is in thewhole street canyon region on the x-y level, while thesecond one is local in all three directions. Validation ofall involved computational schemes is performed based onrelative available experimental data. The computed velocityfields and concentration contours imply that the typicalreference grid is a suitable choice for the velocityfields, while local grid refinement in all three directionsin a small region containing the receptor is required toupgrade the pollutant concentration results with modestadditional computational effort. Finally the RSM modelresulted in smaller concentration levels. The k-model compared to the RSM seems a more appropriate choiceto solve this particular problem.     

Using the ECLPSS software environment to build a spatially explicit component-based model of ozone effects on forest ecosystems

We have developed a modeling framework to support grid-based simulation of ecosystems at multiple spatial scales, the Ecological Component Library for Parallel Spatial Simulation (ECLPSS). ECLPSS helps ecologists to build robust spatially explicit simulations of ecological processes by providing a growing library of reusable interchangeable components and automating many modeling tasks. To build a model, a user selects components from the library, and then writes new components as needed. Some of these components represent specific ecological processes, such as how environmental factors influence the growth of individual trees. Other components provide simulation support such as reading and writing files in various formats to allow inter-operability with other software. The framework manages components and variables, the order of operations, and spatial interactions. The framework provides only simulation support; it does not include ecological functions or assumptions. This separation allows biologists to build models without becoming computer scientists, while computer scientists can improve the framework without becoming ecologists. The framework is designed to operate on multiple platforms and be used across networks via a World Wide Web-based user interface. ECLPSS is designed for use with both single processor computers for small models, and multiple processors in order to simulate large regions with complex interactions among many individuals or ecological compartments. To test Version 1.0 of ECLPSS, we created a model to evaluate the effect of tropospheric ozone on forest ecosystem dynamics. This model is a reduced-form version of two existing models: , which represents an individual tree, and , which represents forest stand growth and succession. This model demonstrates key features of ECLPSS, such as the ability to examine the effects of cell size and model structure on model predictions.