采煤塌陷地积水对土壤氮素矿化过程的影响

煤炭开采导致大面积的土地塌陷,使大量耕地出现常年积水或季节性积水,对塌陷地土壤氮素矿化过程产生一定影响。采集了某矿采煤塌陷地土壤样品,进行好气和淹水培养条件下间歇淋洗培养实验,研究了塌陷地积水对土壤氮素矿化过程的影响。经过62d的培养,40d左右氮素的矿化过程趋于稳定,淹水培养条件下土壤氮素最终累积矿化量为68.99mg/kg,约为好气培养条件的10倍,且淹水培养条件下土壤氮素矿化势可达69.472mg/kg,均矿化速率为5.210mg/(kg·d),说明淹水对土壤氮素矿化过程有显著的促进作用。将实验所得累积矿化量分别代入简单指数模型及双因子指数模型进行拟合,发现简单指数模型能有效模拟好气和淹水培养条件下土壤氮素矿化过程,并获得了2种培养条件下土壤氮素矿化过程的模型参数。     

Assisting Australian indigenous resource management and sustainable utilization of species through the use of GIS and environmental modeling techniques

Information on distribution and relative abundance of species is integral to sustainable management, especially if they are to be harvested for subsistence or commerce. In northern Australia, natural landscapes are vast, centers of population few, access is difficult, and Aboriginal resource centers and communities have limited funds and infrastructure. Consequently defining distribution and relative abundance by comprehensive ground survey is difficult and expensive. This highlights the need for simple, cheap, automated methodologies to predict the distribution of species in use, or having potential for use, in commercial enterprise. The technique applied here uses a Geographic Information System (GIS) to make predictions of probability of occurrence using an inductive modeling technique based on Bayes' theorem. The study area is in the Maningrida region, central Arnhem Land, in the Northern Territory, Australia. The species examined, Cycas arnhemica and Brachychiton diversifolius, are currently being 'wild harvested' in commercial trials, involving sale of decorative plants and use as carving wood, respectively. This study involved limited and relatively simple ground surveys requiring approximately 7 days of effort for each species. The overall model performance was evaluated using Cohen's kappa statistics. The predictive ability of the model for C. arnhemica was classified as moderate and for B. diversifolius as fair. The difference in model performance can be attributed to the pattern of distribution of these species. C. arnhemica tends to occur in a clumped distribution due to relatively short distance dispersal of its large seeds and vegetative growth from long-lived rhizomes, while B. diversifolius seeds are smaller and more widely dispersed across the landscape. The output from analysis predicts trends in species distribution that are consistent with independent on-site sampling for each species and therefore should prove useful in gauging the extent of resource availability. However, some caution needs to be applied as the models tend to over predict presence which is a function of distribution patterns and of other variables operating in the landscape such as fire histories which were not included in the model due to limited availability of data.     

Comparison of models of simazine transport and fate in the subsurface environment in a citrus farm

Contamination of groundwater by agrochemicals is now widely recognized as an extremely important environmental problem. Modern agricultural practices involve the combined use of irrigation with the application of large amounts of agrochemicals to maximize crop yield. Due to flood irrigation and natural runoff, agricultural activities might generate soil, surface water and groundwater contamination problems and leaching of pesticides. Modeling of the transport and fate of pesticides, such as simazine, may help understand the long-term potential risk to the subsurface environment. This paper illustrates a comparative study via the use of three different pesticide transport simulation models and the applicability of those models in determining the groundwater vulnerability to pesticides contamination in a citrus orchard located at the Lower Rio Grande Valley (LRGV). The three models used in the study are the pesticide root zone model-3 (PRZM-3), the pesticide analytical model (PESTAN) and integrated pesticide transport modeling (IPTM). The concentration values obtained from all three models are in agreement, and they show a decreasing trend from the surface through the vadose zone. The problem is how to use this information and, specifically, how to combine the testimony of a number of experts into a single useful judgment. With the aid of the fuzzy multiattribute decision making method, PRZM-3 is deemed as the most promising one for such precision farming applications.     

Estimating Forest Ecosystem Evapotranspiration at Multiple Temporal Scales With a Dimension Analysis Approach1

Abstract:  It is critical that evapotranspiration (ET) be quantified accurately so that scientists can evaluate the effects of land management and global change on water availability, streamflow, nutrient and sediment loading, and ecosystem productivity in watersheds. The objective of this study was to derive a new semi‐empirical ET modeled using a dimension analysis method that could be used to estimate forest ET effectively at multiple temporal scales. The model developed describes ET as a function of water availability for evaporation and transpiration, potential ET demand, air humidity, and land surface characteristics. The model was tested with long‐term hydrometeorological data from five research sites with distinct forest hydrology in the United States and China. Averaged simulation error for daily ET was within 0.5 mm/day. The annual ET at each of the five study sites were within 7% of measured values. Results suggest that the model can accurately capture the temporal dynamics of ET in forest ecosystems at daily, monthly, and annual scales. The model is climate‐driven and is sensitive to topography and vegetation characteristics and thus has potential to be used to examine the compounding hydrologic responses to land cover and climate changes at multiple temporal scales.     

Integrated Modular Modeling of Water and Nutrients From Point and Nonpoint Sources in the Patuxent River Watershed1

Abstract: We present a simple modular landscape simulation model that is based on a watershed modeling framework in which different sets of processes occurring in a watershed can be simulated separately with different models. The model consists of three loosely coupled submodels: a rainfall‐runoff model (TOPMODEL) for runoff generation in a subwatershed, a nutrient model for estimation of nutrients from nonpoint sources in a subwatershed, and a stream network model for integration of point and nonpoint sources in the routing process. The model performance was evaluated using monitoring data in the watershed of the Patuxent River, a tributary to the Chesapeake Bay in Maryland, from July 1997 through August 1999. Despite its simplicity, the landscape model predictions of streamflow, and sediment and nutrient loads were as good as or better than those of the Hydrological Simulation Program‐Fortran model, one of the most widely used comprehensive watershed models. The landscape model was applied to predict discharges of water, sediment, silicate, organic carbon, nitrate, ammonium, organic nitrogen, total nitrogen, organic phosphorus, phosphate, and total phosphorus from the Patuxent watershed to its estuary. The predicted annual water discharge to the estuary was very close to the measured annual total in terms of percent errors for both years of the study period (≤2%). The model predictions for loads of nutrients were also good (20‐30%) or very good (<20%) with exceptions of sediment (40%), phosphate (36%), and organic carbon (53%) for Year 1.     

Identification of key parameters controlling dissolved oxygen migration and attenuation in fractured crystalline rocks

In the crystalline rocks of the Canadian Shield, geochemical conditions are currently reducing at depths of 500-1000 m. However, during future glacial periods, altered hydrologic conditions could potentially result in enhanced recharge of glacial melt water containing a relatively high concentration of dissolved oxygen (O2). It is therefore of interest to investigate the physical and geochemical processes, including naturally-occurring redox reactions, that may control O2 ingress. In this study, the reactive transport code MIN3P is used in combination with 2k factorial analyses to identify the most important parameters controlling oxygen migration and attenuation in fractured crystalline rocks. Scenarios considered are based on simplified conceptual models that include a single vertical fracture, or a fracture zone, contained within a rock matrix that extends from the ground surface to a depth of 500 m. Consistent with field observations, Fe(II)-bearing minerals are present in the fractures (i.e. chlorite) and the rock matrix (biotite and small quantities of pyrite). For the parameter ranges investigated, results indicate that for the single fracture case, the most influential factors controlling dissolved O2 ingress are flow velocity in the fracture, fracture aperture, and the biotite reaction rate in the rock matrix. The most important parameters for the fracture zone simulations are flow velocity in the individual fractures, pO2 in the recharge water, biotite reaction rate, and to a lesser degree the abundance and reactivity of chlorite in the fracture zone, and the fracture zone width. These parameters should therefore receive increased consideration during site characterization, and in the formulation of site-specific models intended to predict O2 behavior in crystalline rocks.     

基于灰建模的瓦斯含量多变量预测模型研究

研究了GM(1,N)、GM(0,N)瓦斯含量预测模型的数学原理,收集郑煤集团告成矿地质勘探期间及生产期间的瓦斯含量实测资料,获得16个可靠点,选取基岩厚度、新生界厚度、煤层厚度、煤层水分、煤层灰分、50m顶板含砂率6个因素作灰色建模预测的指标,分别建立了GM(1,6)和GM(0,6)瓦斯含量多变量预测模型。根据计算和评价结果,GM(1,6)和GM(0,6)瓦斯含量预测模型精度均能够满足工程精度的要求,说明利用灰色模型来预测瓦斯含量是可行的。由于前者精度略高于后者,故建议告成矿采用GM(1,6)模型来进行未知地区煤层瓦斯含量的预测。需要注意,由于模型没有考虑构造的影响,在实际预测时,还应根据构造对待预测区的影响关系和影响程度对模型的预测结果进行修正。     

Leaching behavior of heavy metals from municipal solid waste incineration bottom ash and its geochemical modeling

With the increase in the number of municipal solid waste incineration (MSWI) plants constructed in China recently, great attention has been paid to the heavy metal leaching toxicity of MSWI residues. In this study, the effects of various parameters, including extractant, leaching time, liquid-to-solid ratio, leachate pH, and heavy metal content, on the release properties of Cd, Cr, Cu, Ni, Pb, and Zn from MSWI bottom ash were investigated. Partial least-squares analysis was employed to highlight the interrelationships between the factors and response variables. Both experimental research and geochemical modeling using Visual MINTEQ software were conducted to study the pH-dependent leaching behavior of these metals in fresh and weathered bottom ash, considering precipitation/dissolution and surface complexation reactions (adsorption by hydrous ferric oxide and amorphous aluminum oxide/hydroxide). The results showed that leachate pH was the predominant factor influencing heavy metal leachability. The leaching of Cu, Pb, and Zn was mainly controlled by precipitation/dissolution reactions, whereas surface complexation had some effect on the leaching of Cr, Cd, and Ni for certain pH ranges. The modeling results aggreed well with the experimental results. Part of this work was presented at the Fourth International Conference on Combustion, Incineration/Pyrolysis and Emission Control (i-CIPEC)     

Comparison of Microscopic and Macroscopic Modeling Approaches for Subsurface Contaminant Transport

The practice of contaminant transport and remediation has shown significant progress in recent years. However, despite the significant progress made, remediation efforts are often delayed by extremely long breakthrough curve tails that render efforts to bring the level of contaminants below the regulatory standards inefficient. One hypothesis is that these long tails are due to the reservoir-like slow diffusive processes in soil micropore zones. This study compares the effects of micropores at macroscopic and microscopic levels and establishes a link between these approaches for validation and calibration purposes. The link between macroscopic and microscopic levels is established through comparisons and testing of the two models while incorporating appropriate scale and boundary effects. Despite the differences in conceptual approaches and simulation time, the two approaches rendered meaningful results. The link helps forecast the effects of micropore zone transport processes in the subsurface efficiently and thus allows development of numerical tools that could contribute towards more efficient remediation design.     

IFTCIP: An Integrated Optimization Model for Environmental Management under Uncertainty

In this study, an interval-fuzzy two-stage chance-constrained integer programming (IFTCIP) method is developed for supporting environmental management under uncertainty. The IFTCIP improves upon the existing interval, fuzzy, and two-stage programming approaches by allowing uncertainties expressed as probability distributions, fuzzy sets, and discrete intervals to be directly incorporated within a general mixed integer linear programming framework. It has advantages in uncertainty reflection, policy investigation, risk assessment, and capacity-expansion analysis in comparison to the other optimization methods. Moreover, it can help examine the risk of violating system constraints and the associated consequences. The developed method is applied to the planning for facility expansion and waste-flow allocation within a municipal solid waste management system. Violations of capacity constraints are allowed under a range of significance levels, which reflects tradeoffs between the system cost and the constraint-violation risk. The results indicate that reasonable solutions for both binary and continuous variables have been generated under different risk levels. They are useful for generating desired decision alternatives with minimized system cost and constraint-violation risk under various environmental, economic, and system-reliability conditions. Generally, willingness to take a higher risk of constraint violation will guarantee a lower system cost; a strong desire to acquire a lower risk will run into a higher system cost.