可视化灾害数字仿真重构理论及实证研究(Ⅱ)--理论框架与概念化范式

可视化灾害数字仿真重构理论研究,不仅可以实现对灾害空间数据进行有效的集成管理和时空分析,而且为灾害的防治、应急管理和工程论证等提供可靠的依据,是解决灾害实验的危险性和不可重复性的最佳途径.本文提出可视化灾害数字仿真重构理论的概念、研究对象和方法,综述该理论所需要涉及多种跨学科的技术支持,提出灾害数字仿真重构理论的实施流程,按照致灾因子孕育、发生以及作用于承灾体形成灾害的过程为线索,建立灾害数字仿真模型的概念化范式.上述工作共同构成灾害数字仿真重构的完整理论体系.     

IMPLICATIONS OF ON‐GROUND NITROGEN LOADING AND SOIL TRANSFORMATIONS ON GROUND WATER QUALITY MANAGEMENT1

ABSTRACT: This paper presents a modeling approach based on a geographic information system (GIS) to estimate the variability of on‐ground nitrogen loading and the corresponding nitrate leaching to ground water. The methodology integrates all point and nonpoint sources of nitrogen, the national land cover database, soil nitrogen transformations, and the uncertainty of key soil and land use‐related parameters to predict the nitrate mass leaching to ground water. The analysis considered 21 different land use classes with information derived from nitrogen sources such as fertilizer and dairy manure applications, dairy lagoons, septic systems, and dry and wet depositions. Simulations were performed at a temporal resolution of one month to capture seasonal trends. The model was applied to a large aquifer of 376 square miles in Washington State that serves more than 100,000 residents with drinking water. The results showed that dairy manure is the main source of nitrogen in the area followed by fertilizers. It was also seen that nitrate leaching is controlled by the recharge rate, and there can be a substantial buildup of soil nitrogen over long periods of time. Uncertainty analysis showed that denitrification rate is the most influential parameter on nitrate leaching. The results showed that combining management alternatives is a successful strategy, especially with the use of nitrification inhibitors. Also, change in the land use pattern has a noticeable impact on nitrate leaching.     

EFFECTS OF WATERSHED REPRESENTATION ON RUNOFF AND SEDIMENT YIELD MODELING1

ABSTRACT: This paper evaluates the effects of watershed geometric representation (i.e., plane and channel representation) on runoff and sediment yield simulations in a semiarid rangeland watershed. A process based, spatially distributed runoff erosion model (KINEROS2) was used to explore four spatial representations of a 4.4 ha experimental watershed. The most complex representation included all 96 channel elements identifiable in the field. The least complex representation contained only five channel elements. It was concluded that oversimplified watershed representations greatly influence runoff and sediment yield simulations by inducing excessive infiltration on hillslopes and distorting runoff patterns and sediment fluxes. Runoff and sediment yield decrease systematically with decreasing complexity in watershed representation. However, less complex representations had less impact on runoff and sediment‐yield simulations for small rainfall events. This study concludes that the selection of the appropriate level of watershed representation can have important theoretical and practical implications on runoff and sediment yield modeling in semiarid environments.     

SIMULATING THE IMPACT OF DRAINAGE DESIGN IN A COLD CLIMATE WITH ADAPT1

ABSTRACT: Surface and subsurface drainage make crop production economically viable in much of southern Minnesota because drainage allows timely field operations and protects field crops from extended periods of flooded soil conditions. However, subsurface drainage has been shown to increase nitrate/nitrogen losses to receiving waters. When engaging in drainage activities, farmers are increasingly being asked to consider, apart from the economic profit, the environmental impact of drainage. The Agricultural Drainage and Pesticide Transport model (ADAPT) was used in this study to evaluate the impact of subsurface drainage design on the soil water balance over a two‐year period during which observed drainage discharge data were available. Twelve modeling scenarios incorporated four drainage coefficients (DC), 0.64 cm/d, 0.95 cm/d, 1.27 cm/d, and 1.91 cm/d, and three drain depths, 0.84 m, 1.15 m, and 1.45 m. The baseline condition corresponded to the drainage system specifications at the field site: a drain depth and spacing of 1.45 m and 28 m, respectively (DC of 0.64 cm/d). The results of the two‐year simulation suggested that for a given drainage coefficient, soils with the shallower drains (but equal DC) generally have less subsurface drainage and can produce more runoff (but reduced total discharge) and evapotranspiration. The results also suggested that it may be possible to design for both water/nitrate/nitrogen reduction and crop water needs.     

ENHANCING FECAL COLIFORM TOTAL MAXIMUM DAILY LOAD MODELS THROUGH BACTERIAL SOURCE TRACKING1

ABSTRACT: Surface water impairment by fecal coliform bacteria is a water quality issue of national scope and importance. In Virginia, more than 400 stream and river segments are on the Commonwealth's 2002 303(d) list because of fecal coliform impairment. Total maximum daily loads (TMDLs) will be developed for most of these listed streams and rivers. Information regarding the major fecal coliform sources that impair surface water quality would enhance the development of effective watershed models and improve TMDLs. Bacterial source tracking (BST) is a recently developed technology for identifying the sources of fecal coliform bacteria and it may be helpful in generating improved TMDLs. Bacterial source tracking was performed, watershed models were developed, and TMDLs were prepared for three streams (Accotink Creek, Christians Creek, and Blacks Run) on Virginia's 303(d) list of impaired waters. Quality assurance of the BST work suggests that these data adequately describe the bacteria sources that are impairing these streams. Initial comparison of simulated bacterial sources with the observed BST data indicated that the fecal coliform sources were represented inaccurately in the initial model simulation. Revised model simulations (based on BST data) appeared to provide a better representation of the sources of fecal coliform bacteria in these three streams. The coupled approach of incorporating BST data into the fecal coliform transport model appears to reduce model uncertainty and should result in an improved TMDL.     

MODELING THE IMPACTS OF WATER LEVEL CHANGES ON A GREAT LAKES COMMUNITY1

ABSTRACT: Recent research that couples climate change scenarios based on general circulation models (GCM) with Great Lakes hydrologic models has indicated that average water levels are projected to decline in the future. This paper outlines a methodology to assess the potential impact of declining water levels on Great Lakes waterfront communities, using the Lake Huron shoreline at Goderich, Ontario, as an example. The methodology utilizes a geographic information system (GIS) to combine topographic and bathymetric datasets. A digital elevation surface is used to model projected shoreline change for 2050 using water level scenarios. An arbitrary scenario, based on a 1 m decline from February 2001 lake levels, is also modeled. By creating a series of shoreline scenarios, a range of impact and cost scenarios are generated for the Goderich Harbor and adjacent marinas. Additional harbor and marina dredging could cost as much as CDN $7.6 million. Lake freighters may experience a 30 percent loss in vessel capacity. The methodology is used to provide initial estimates of the potential impacts of climate change that can be readily updated as more robust climate change scenarios become available and is adaptable for use in other Great Lakes coastal communities.     

锂离子电池安全性特点及热模型研究

锂离子电池的安全问题越来越受到重视.本文从锂离子电池热安全性特点着手,分析了锂离子电池的着火、爆炸和电解液泄漏等安全事故特点.简单介绍了锂离子电池主要材料的产热特性、相互反应产热特性.讨论了锂离子电池热模型建立的两种途径,即量热仪途径和化学反应途径,通过这些热模型的建立,来指导锂离子电池的安全设计和管理.     

DRY AND WET WEATHER FLOW NUTRIENT LOADS FROM A LOS ANGELES WATERSHED1

Effective watershed management requires an accurate assessment of the pollutant loads from the associated point and nonpoint sources. The importance of wet weather flow (WWF) pollutant loads is well known, but in semi‐arid regions where urbanization is significant the pollutant load in dry weather flow (DWF) may also be important. This research compares the relative contributions of potential contaminants discharged in DWF and WWF from the Ballona Creek Watershed in Los Angeles, California. Models to predict DWF and WWF loads of total suspended solids, biochemical oxygen demand, nitrate‐nitrogen, nitrite‐nitrogen, ammonia‐nitrogen, total Kjeldahl nitrogen, and total phosphorus from the Ballona Creek Watershed for six water years dating from 1991 to 1996 were developed. The contaminants studied were selected based on data availability and their potential importance in the degradation of Ballona Creek and Santa Monica Bay beneficial uses. Wet weather flow was found to contribute approximately 75 percent to 90 percent of the total annual flow volume discharged by the Ballona Creek Watershed. Pollutant loads are also predominantly due to WWF, but during the dry season, DWF is a more significant contributor. Wet weather flow accounts for 67 to 98 percent of the annual load of the constituents studied. During the dry season, however, the portion attributable to DWF increases to greater than 40 percent for all constituents except biochemical oxygen demand and total suspended solids. When individual catchments within the watershed are considered, the DWF pollutant load from the largest catchment is similar to the WWF pollutant load in two other major catchments. This research indicates WWF is the most significant source of nonpoint source pollution load on an annual basis, but management of the effects of the nonpoint source pollutant load should consider the seasonal importance of DWF.     

MODELING LIGHT ATTENUATION,SECCHI DISK,AND EFFECTS OF TRIPTON IN SENACA RIVER,NEW YORK,USA1

The development, testing, and application of a probabilistic model framework for the light attenuation coefficient for downwelling irradiance (K_d) and Secchi disc transparency (SD) that resolves the effects of several light attenuating constituents, including phytoplankton and nonliving particles (tripton), is documented. The model is consistent with optical theory, partitioning the magnitudes of the light attenuating processes of absorption and scattering according to the contributions of attenuating constituents as simple summations. The probabilistic framework accommodates variations in the character and concentrations of these constituents and ambient conditions during measurements, and recognizes a linear relationship between the magnitudes of absorption and scattering by tripton. The model is tested and applied for a 21 km reach of the Seneca River, New York, that features optical gradients caused by an intervening hypereutrophic lake and dam, and a severe infestation of the exotic zebra mussel. The model is applied to resolve the roles of phytoplankton and tripton in regulating measured longitudinal patterns of SD along the study reach of the river and increases in SD since the zebra mussel invasion, and to predict decreases in K_d since the invasion.     

MODELING THE DISTRIBUTION OF DIFFUSE NITROGEN SOURCES AND SINKS IN THE NEUSE RIVER BASIN OF NORTH CAROLINA,USA1

This study quantified nonpoint source nitrogen (NPS‐N) sources and sinks across the 14,582 km² Neuse River Basin (NRB) located in North Carolina, to provide tabular data summaries and graphic overlay products to support the development of management approaches to best achieve established N reduction goals. First, a remote sensor derived, land cover classification was performed to support modeling needs. Modeling efforts included the development of a mass balance model to quantify potential N sources and sinks, followed by a precipitation event driven hydrologic model to effectively transport excess N across the landscape to individual stream reaches to support subsequent labeling of transported N values corresponding to source origin. Results indicated that agricultural land contributed 55 percent of the total annual NPS‐N loadings, followed by forested land at 23 percent (background), and urban areas at 21 percent. Average annual N source contributions were quantified for agricultural (1.4 kg/ha), urban (1.2 kg/ha), and forested cover types (0.5 kg/ha). Nonpoint source‐N contributions were greatest during the winter (40 percent), followed by spring (32 percent), summer (28 percent), and fall (0.3 percent). Seasonal total N loadings shifted from urban dominated and forest dominated sources during the winter, to agricultural sources in the spring and summer. A quantitative assessment of the significant NRB land use activities indicated that high (greater than 70 percent impervious) and medium (greater than 35 percent impervious) density urban development were the greatest contributors of NPS‐N on a unit area basis (1.9 and 1.6 kg/ha/yr, respectively), followed by row crops and pasture/hay cover types (1.4 kg/ha/yr).