REGIONALIZATION OF LOW-FLOW FREQUENCY ESTIMATES: AN ALABAMA CASE STUI)Y1

ABSTRACT: Low-flow estimates, as determined by probabilistic modeling of observed data sequences, are commonly used to describe certain streamflow characteristics. Unfortunately, however, reliable low-flow estimates can be difficult to come by, particularly for gaging sites with short record lengths. The shortness of records leads to uncertainties not only in the selection of a distribution for modeling purposes but also in the estimates of the parameters of a chosen model. In flood frequency analysis, the common approach to mitigation of some of these problems is through the regionalization of frequency behavior. The same general approach is applied here to the case of low-flow estimation, with the general intent of not only improving low-flow estimates but also illustrating the gains that might be attained in so doing. Data used for this study is that which has been systematically observed at 128 streamflow gaging sites across the State of Alabama. Our conclusions are that the log Pearson Type 3 distribution is a suitable candidate for modeling of Alabama low-flows, and that the shape parameter of that distribution can be estimated on a regional basis. Low-flow estimates based on the regional estimator are compared with estimates based on the use of only at-site estimation techniques.     

Bandwidth determination for kernel density analysis of wildfire events at forest sub-district scale

Forest fire is regarded as one of the most significant factors leading to land degradation. While evaluating fire hazard or producing fire risk zone maps, quantitative analyses using historic fire data is often required, and during all these modeling and multi-criteria analysis processes, the fire event itself is taken as the dependent variable. However, there are two main problematic issues in analyzing historic fire data. The first difficulty arises from the fact that it is in point format, whereas a continuous surface is frequently needed for statistically analyzing the relationship of fire events with other factors, such as anthropogenic, topographic and climatic conditions. Another, and probably the most bothersome challenge is to overcome inaccuracy inherent in historic fire data in point format, since the exact coordinates of ignition points are mostly unknown. In this study, kernel density mapping, a widely used method for converting discrete point data into a continuous raster surface, was used to map the historic fire data in Mumcular Forest Sub-district in Mu?la, Turkey. The historic fire data was transferred onto the digital forest stand map of the study area, where the exact locations of ignition points are unknown; however, the exact number of ignition points in each compartment of the forest stand map is known. Different random distributions of ignition points were produced, and for each random distribution, kernel density maps were produced by applying two distinct kernel functions with several smoothing parameter options. The obtained maps were compared through correlation analysis in order to illustrate the effect of randomness, choice of kernel function and smoothing parameter. The proposed method gives a range of values rather than a single bandwidth value; however, it provides a more reliable way than comparing the maps with different bandwidths subjectively by eye.     

环境归趋模型参数估计方法的比较

大量的研究表明,参数估计方法的可行性和有效性,决定着环境归趋模型的成功与否。在文献检索的基础上,简单介绍了环境归趋模型参数估计方法的类型和最优化原理,分析了各种方法的优点与不足,并初步探讨了环境归趋模型参数估计方法的研究趋势。     

Closed population estimation models and their extensions in Program MARK

Program MARK provides > 65 data types in a common configuration for the estimation of population parameters from mark-encounter data. Encounter information from live captures, live resightings, and dead recoveries can be incorporated to estimate demographic parameters. Available estimates include survival (S or ϕ), rate of population change (λ), transition rates between strata (Ψ), emigration and immigration rates, and population size (N). Although N is the parameter most often desired by biologists, N is one of the most difficult parameters to estimate precisely without bias for a geographically and demographically closed population. The set of closed population estimation models available in Program MARK incorporate time (t) and behavioral (b) variation, and individual heterogeneity (h) in the estimation of capture and recapture probabilities in a likelihood framework. The full range of models from M ₀ (null model with all capture and recapture probabilities equal) to M _tbh are possible, including the ability to include temporal, group, and individual covariates to model capture and recapture probabilities. Both the full likelihood formulation of Otis et al. (1978) and the conditional model formulation of Huggins (1989, 1991) and Alho (1990) are provided in Program MARK, and all of these models are incorporated into the robust design (Kendall et al. 1995, 1997; Kendall and Nichols 1995) and robust-design multistrata (Hestbeck et al. 1991, Brownie et al. 1993) data types. Model selection is performed with AICc (Burnham and Anderson 2002) and model averaging (Burnham and Anderson 2002) is available in Program MARK to provide estimates of N with standard error that reflect model selection uncertainty.     

Improved strategies for coverage estimation by using replicated line-intercept sampling

Coverage, i.e., the area covered by the target attribute in the study region, is a key parameter in many surveys. Coverage estimation is usually performed by adopting a replicated protocol based on line-intercept sampling coupled with a suitable linear homogeneous estimator. Since coverage is a parameter which may be interestingly represented as the integral of a suitable function, improved Monte Carlo strategies for implementing the replicated protocol are introduced in order to achieve estimators with small variance rates. In addition, new specific theoretical results on Monte Carlo integration methods are given to deal with the integrand functions arising in the special coverage estimation setting.

Pilot study for the treatment of sodium and fluoride-contaminated groundwater by using high-pressure membrane systems

High-pressure membrane process is one of the cost-effective technologies for the treatment of groundwater containing excessive dissolved solids. This paper reports a pilot study in treating a typical groundwater in Huaibei Plain containing excessive sodium, sulfate and fluoride ions. Three membrane systems were set up and two brands of reverse osmosis (RO), four low-pressure RO (LPRO) and one tight nanofiltration (NF) membranes were tested under this pilot study. An apparent recovery rate at about 75% was adopted. Cartridge filtration, in combination with dosing antiscalent, was not sufficient to reduce the fouling potential of the raw water. All RO and LPRO systems (except for the two severely affected by membrane fouling) demonstrated similar rejection ratios of the conductivity (~98.5%), sodium (~98.5%) and fluoride (~99%). Membrane fouling substantially reduced the rejection performance of the fouled membranes. The tight NF membrane also had a good rejection on conductivity (95%), sodium (94%) and fluoride (95%). All membranes rejected sulfate ion almost completely (more than 99%). The electricity consumptions for the RO, LPRO and NF systems were 1.74, 1.10 and 0.72 kWh?m^-3 treated water, respectively. The estimated treatment costs by using typical RO, LPRO and tight NF membrane systems were 1.21, 0.98 and 0.96 CNY?m^-3 finished water, respectively. A treatment process consisting of either LPRO or tight NF facilities following multi-media filtration was suggested.     

中国土地生产力变化的情景分析

中国土地生产力变化态势是当前国内外学术界、决策界关注的焦点问题之一.介绍了土地生产力估算系统(ESLP)的原理与功能模块并利用该系统研究了中国土地生产力的变化态势.ESLP是在气温、降水、辐射水平、土壤质地等自然因素控制下,受土地利用方向与强度影响的,考虑土地系统不同的投入水平和管理措施的区域土地生产力估算系统.ESLP关注土地生产力变化的时空动态,能表达出不同投入管理水平下土地生产力的时空变化.文章应用ESLP研究了1988年和2000年中国土地生产力变化及其空间分异特征,将估算结果与1988年和2000年全国分县粮食产量数据的比较与验证表明,基于ESLP估算的各县土地生产力与各县粮食总产量具有很高的相关性,在一定程度上反映一个区域的粮食生产能力.在此基础上,应用ESLP预测了2010与2020年在气候变化情景下土地生产力的变化,预测结果显示,虽然局部地区土地生产力有小幅减少趋势,但从全国来看,土地生产力增长趋势明显.平均来看,2010年比2000年增长4.4%,而到2020年,土地生产力的增长幅度达到10.7%.不过在各个农业生态分区上,不同年份土地生产力变化差异较大,在2010年和2020年长江中下游区土地生产力均呈一定幅度的下降,而甘新区和西藏区只在2010年土地生产力有小幅下降.该研究结论对我国编制土地利用规划与粮食生产方面的决策具有重要的参考价值.     

Comparing model averaging with other model selection strategies for benchmark dose estimation

Model averaging (MA) has been proposed as a method of accommodating model uncertainty when estimating risk. Although the use of MA is inherently appealing, little is known about its performance using general modeling conditions. We investigate the use of MA for estimating excess risk using a Monte Carlo simulation. Dichotomous response data are simulated under various assumed underlying dose–response curves, and nine dose–response models (from the USEPA Benchmark dose model suite) are fit to obtain both model specific and MA risk estimates. The benchmark dose estimates (BMDs) from the MA method, as well as estimates from other commonly selected models, e.g., best fitting model or the model resulting in the smallest BMD, are compared to the true benchmark dose value to better understand both bias and coverage behavior in the estimation procedure. The MA method has a small bias when estimating the BMD that is similar to the bias of BMD estimates derived from the assumed model. Further, when a broader range of models are included in the family of models considered in the MA process, the lower bound estimate provided coverage close to the nominal level, which is superior to the other strategies considered. This approach provides an alternative method for risk managers to estimate risk while incorporating model uncertainty.

武夷山风景名胜区生态系统服务价值评价

参照Costanza等对全球生态系统服务价值的测算方法,初步估算了武夷山风景名胜区的生态服务价值.研究结果表明,该区生态系统服务总价值为12.59×106 USD·a-1,其中生态效益占79.67%.这反映出该区生态系统具有明显的生态功能.该区生态系统服务价值占全国的0.001 444%,调节水分等对全国生态服务功能贡献相对较高.该景区1996-2001年生态服务功能发生了一定程度的变化,2001年提供的生态服务功能价值比1996年减少了1.94×105 USD·a-1.由于存在许多不确定因素以及方法上的不成熟,故所得武夷山风景名胜区生态系统服务价值只是一个保守的、较低的估计值.     

公路隧道火灾风险评价模型及应用

公路隧道火灾风险评价研究是预防和控制公路隧道火灾事故的重要手段。通过火灾案例统计分析,运用安全系统工程方法分析公路隧道火灾事故原因,从设备因素、人员因素、环境因素以及管理因素四个方面构建公路隧道火灾风险评价指标体系。建立了基于模糊层次评价法公路隧道火灾风险评价数学模型;最后对某公路隧道进行应用实例研究,确定了公路隧道的火灾风险等级并提出了相应的改进措施。结果表明公路隧道火灾风险评价指标体系以及评价方法能合理反映公路隧道的火灾风险。