森林植被影响径流形成机制研究进展

径流形成机制研究在水文学领域中具有十分重要的意义,且受到越来越广泛的重视。水文环境以及水文通量的空间异质性和时间变化性导致了水文过程的尺度依赖性和非线性特征,没有对水文过程较为清晰的认识,就不能将某一地区某一流域森林植被变化水文生态效应的研究结果简单地外推到其他地区和其他流域。开发基于物理过程分布式参数水文模型可以为认识森林植被变化的生态学后效和客观评价森林植被水文生态效益提供可行的工具。但是要实现这一目标,研究森林植被影响径流形成机制是问题的核心所在。另一方面,认识森林影响径流形成机制有助于研究水文学中的尺度问题。研究森林植被影响径流形成机制的主要方法包括水文测验、同位素示踪和动力水文学计算等,研究的空间尺度则为坡面与流域相接合。从已有的研究成果来看,森林植被影响径流形成机制可以概括为:①森林流域径流形成为变动源区产流机制;②森林流域径流形成主要受饱和地表径流、亚表层径流和地下径流的控制;③森林流域径流形成机制是相互作用和相互转化的;④优先流在森林流域径流形成中起到了至关重要的作用。     

An air quality forecasting system in Beijing - Application to the study of dust storm events in China in May 2008

An air pollution forecast system, ARIA Regional, was implemented in 2007-2008 at the Beijing Municipality Environmental Monitoring Center, providing daily forecast of main pollutant concentrations. The chemistry-transport model CHIMERE was coupled with the dust emission model MB95 for restituting dust storm events in springtime so as to improve forecast results. Dust storm events were sporadic but could be extremely intense and then control air quality indexes close to the source areas but also far in the Beijing area. A dust episode having occurred at the end of May 2008 was analyzed in this article, and its impact of particulate matter on the Chinese air pollution index (API) was evaluated. Following our estimation, about 23 Tg of dust were emitted from source areas in Mongolia and in the Inner Mongolia of China, transporting towards southeast. This episode of dust storm influenced a large part of North China and East China, and also South Korea. The model result was then evaluated using satellite observations and in situ data. The simulated daily concentrations of total suspended particulate at 6:00 UTC had a similar spatial pattern with respect to OMI satellite aerosol index. Temporal evolution of dust plume was evaluated by comparing dust aerosol optical depth (AOD) calculated from the simulations with AOD derived from MODIS satellite products. Finally, the comparison of reported Chinese API in Beijing with API calculated from the simulation including dust emissions had showed the significant improvement of the model results taking into account mineral dust correctly.     

Quantitative analysis of microbial biomass yield in aerobic bioreactor

We have studied the integrated model of reaction rate equations with thermal energy balance in aerobic bioreactor for food waste decomposition and showed that the integrated model has the capability both of monitoring microbial activity in real time and of analyzing biodegradation kinetics and thermal-hydrodynamic properties. On the other hand, concerning microbial metabolism, it was known that balancing catabolic reactions with anabolic reactions in terms of energy and electron flow provides stoichiometric metabolic reactions and enables the estimation of microbial biomass yield (stoichiometric reaction model). We have studied a method for estimating real-time microbial biomass yield in the bioreactor during food waste decomposition by combining the integrated model with the stoichiometric reaction model. As a result, it was found that the time course of microbial biomass yield in the bioreactor during decomposition can be evaluated using the operational data of the bioreactor (weight of input food waste and bed temperature) by the combined model. The combined model can be applied to manage a food waste decomposition not only for controlling system operation to keep microbial activity stable, but also for producing value–added products such as compost on optimum condition.     

Simulating a natural fire regime on an Atlantic coast barrier island complex in Florida, USA

The HFire fire regime model was used to simulate the natural fire regime (prior to European settlement) on Kennedy Space Center, Merritt Island National Wildlife Refuge, Canaveral National Seashore, and Cape Canaveral Air Force Station, Florida. Model simulations were run for 500 years and the model was parameterized using information generated from previously published empirical studies on these properties (e.g., lightning fire ignition frequencies and ignition seasonality). A mosaic pattern of frequent small fires dominated this fire regime with rare but extremely large fires occurring during dry La Niña periods. This simulated fire size distribution very closely matched the previously published fire size distribution for lightning ignitions on these properties. A sensitivity analysis was performed to establish which parameters were most influential and the range of variation surrounding empirically parameterized model output. Dead fuel moisture and wind speed had the largest influence on model outcome. A wide range of variance was observed surrounding the composite simulation with the least being 6% in total burn frequency and the greatest being 49% in total area burned. Because simulation modeling is the best option for fire regime reconstruction in many rapidly growing shrub dominated systems, these results will be of interest to scientists and fire managers for delineating the natural fire regime on these properties, the southeastern United States and other fire adapted shrub systems worldwide.     

Improving inverse model fitting in trees—Anisotropy,multiplicative effects,and Bayes estimation

Model fitting for individual-based effects in forests has some problems. Because samples measuring the separate influence of each individual are rarely available, the measured value in the sample represents the influence of all surrounding individual trees. Therefore, it is helpful to build inverse models that use the spatial pattern of the variable as well as that of the source trees. For example, since seed dispersal is influenced by wind effects, a model is discussed describing anisotropic effects to ensure an unbiased estimate of the total fruit number. Further, we present a model describing the absorption of radiation by trees. In this case a multiplicative combination of individual effects yields the total effect. Our approach uses logarithmic transformations of the original data to model multiplicative combinations as sum of transformed single effects. For fitting model parameters we propose an approach based on Bayesian statistics, to ensure ecologically interpretable parameters.     

Characterizing sources of nitrate leaching from an irrigated dairy farm in Merced County, California

Dairy farms comprise a complex landscape of groundwater pollution sources. The objective of our work is to develop a method to quantify nitrate leaching to shallow groundwater from different management units at dairy farms. Total nitrate loads are determined by the sequential calibration of a sub-regional scale and a farm-scale three-dimensional groundwater flow and transport model using observations at different spatial scales. These observations include local measurements of groundwater heads and nitrate concentrations in an extensive monitoring well network, providing data at a scale of a few meters and measurements of discharge rates and nitrate concentrations in a tile-drain network, providing data integrated across multiple farms. The various measurement scales are different from the spatial scales of the calibration parameters, which are the recharge and nitrogen leaching rates from individual management units. The calibration procedure offers a conceptual framework for using field measurements at different spatial scales to estimate recharge N concentrations at the management unit scale. It provides a map of spatially varying dairy farming impact on groundwater nitrogen. The method is applied to a dairy farm located in a relatively vulnerable hydrogeologic region in California. Potential sources within the dairy farm are divided into three categories, representing different manure management units: animal exercise yards and feeding areas (corrals), liquid manure holding ponds, and manure irrigated forage fields. Estimated average nitrogen leaching is 872 kg/ha/year, 807 kg/ha/year and 486 kg/ha/year for corrals, ponds and fields respectively. Results are applied to evaluate the accuracy of nitrogen mass balances often used by regulatory agencies to assess groundwater impacts. Calibrated leaching rates compare favorably to field and farm scale nitrogen mass balances. These data and interpretations provide a basis for developing improved management strategies.     

Integrated assessment: Missing link in the acid rain debate?

The United States is finding it difficult to develop a coherent policy on acid rain. Despite more than a decade of scientific research and policy initiatives, no clear course of action has been identified. This article argues that what is missing is an integrated assessment of the scientific knowledge that will guide the political process. The role of the integrated assessment is described, and a conceptual framework presented that would accomplish the desired goal. Currently available acid rain assessment models are compared against this framework and found to be less than satisfactory. The article concludes by stressing the opportunity now available to the National Acid Precipitation Assessment Program to perform such an assessment and break the logjam.     

EXPOSURE ASSESSMENT OF POPULATIONS USING ENVIRONMENTAL MODELING,DEMOGRAPHIC ANALYSIS,AND GIS1

ABSTRACT: Simulation of ground-water flow and fate of contaminants in the subsurface environment constitutes a major phase of most environmental assessment and site remediation studies. These simulation studies yield information on spatial and temporal distributions of contaminants in the subsurface media. An important use of this information is to conduct exposure assessment studies. Spatial and temporal distributions of both chemical concentrations and exposed populations render this integrated exposure analysis task rather difficult. Geographic Information Systems (GIS), on the other hand, provide a platform in which layered, spatially distributed databases can be manipulated with ease, thereby simplifying exposure analysis tasks significantly. In this paper, we describe procedures that combine the simulation models and demographic databases under a GIS platform to automate the exposure assessment phase of a typical health assessment study. Procedures developed herein significantly simplify the post-processing phase of the analysis, and render the overall task more ‘user friendly.’ A site-specific application is included as a demonstration of the proposed process.     

BASIN WATER MONITORING: HYDROLOGIC IMPACT OR LEGAL COMPLIANCE1

ABSTRACT: The Surface Mining Control and Reclamation Act of 1977 (PL 95–87) requires data collection prior to mining which will allow a determination to be made of the probable hydrologic consequences. Modeling strategies exist which allow for such determination, but selection of a specific model form will dictate the length of data record needed. The absence of a sound management strategy by the regulatory authority in‘Maryland does not result in valid data collection and suggests that the agency is concerned more with legal compliance than with integrated resource management.