Modeling Abundance Index Data from Anuran Calling Surveys

Abstract:  Evaluation of anuran populations is commonly based on calling surveys that report categorical abundance index data. I present a statistical model for abundance index data that are observations representing ordered abundance classes (e.g., none, some, many). The proposed model provides a formal treatment of detection probability, factors that affect detection, and variation in abundance. The model can be viewed as a generalization of that proposed by MacKenzie et al. (2002) for estimating site-occupancy rates in that it allows for more than two abundance classes. Because the abundance distribution is characterized by multiple abundance classes, it may be more sensitive to subtle changes in the underlying abundance that may go undetected with simple occupancy estimates under which sites are characterized merely as occupied or not. The method is most immediately applicable to surveys of anurans in which index data related to the intensity of calling activity are collected. I applied the proposed method to calling index data from the green frog (  Rana clamitans ) collected as part of the North American Amphibian Monitoring Program. The best model indicated considerable variation in detectability over time and in response to temperature. The resulting adjusted (for detectability) abundance-state distribution demonstrates the negative bias in abundance state obtained from simplistic summaries of calling index data that disregard these sources of variation in detectability.     

HYDRODYNAMIC MODELS OF HUMAN STABILITY IN A FLOOD1

ABSTRACT: Major loss of life can occur in a flood when people are toppled by floodwater currents. Three approximate mechanical models and two empirical models of the hydrodynamics of toppling are presented and calibrated to align with available experimental observations to assist the analysis of the risk of life loss. The mechanical models consider circular cylindrical, square cylindrical and cylindrical composite, heavy bodies assembled to represent a human immersed in a flow field and subject to drag and buoyancy forces. The models can account for the height and weight of the exposed persons, and the velocity and depth of the flow. The models are in good mutual agreement and, when calibrated, yield failure functions that can be used to calculate the probability of loss of stability.     

MODELING DRINKING WATER QUALITY VIOLATIONS WITH BAYESIAN NETWORKS1

ABSTRACT: Compliance violations at community water systems are rare but represent significant human health risks. These risks are mediated by the decision schema of human operators at water treatment facilities. However, causal uncertainty among physical and human factors involved in water quality problems complicates assessment of their probability and severity. This study uses a probabilistic Bayesian network modeling approach to explore the causes of compliance violations in a sample of water treatment systems in Pennsylvania. The model presented here is one of several created by treatment system operators during an expert elicitation process. The expert model alone predicts violations poorly, suggesting that experts make inaccurate quantitative estimates. However, Bayesian networks are capable of combining the subjective expertise of treatment system operators with the objective compliance histories of the facilities they manage, and the expert model accurately predicts violations when trained with historical compliance data. Analysis of the trained network reveals those components of the treatment process, including environmental and system characteristics as well as operator decisions, that play the greatest role in determining the likelihood of major violation types. Among operator decisions, coagulant dosing and filter backwash frequency are the most important determinants of violation likelihood.     

TARGETING NONPOINT SOURCE POLLUTION CONTROL: PHOSPHORUS IN THE MINNESOTA RIVER BASIN1

ABSTRACT: The state of Minnesota seeks to reduce phosphorus loading to the Minnesota River by 40 percent from current levels. Looking at one major watershed in the river basin, we examined the cost effectiveness of targeting versus not targeting specific practices or regions within a watershed for controlling nonpoint phosphorus pollution from agriculture. Integrating biophysical simulation results from current and alternative farming systems with production cost and return estimates enabled us to analyze this policy. Our results indicated it is more cost effective to reduce nonpoint pollution by targeting particular regions or practices in a watershed compared to not targeting. Specifically, producers farming on cropland susceptible to erosion in close proximity to water will appreciably reduce phosphorus nonpoint pollution loading potential by switching from conventional tillage to conservation tillage and by reducing phosphorus fertilization levels to those recommended by the state extension service. Efforts to target those producers in the Minnesota River Basin could reduce potential transaction costs and compensation from “takings” by approximately $50 million (74 percent) over not targeting.     

国外泥石流机理模型综述

综述了国外与机理有关的几个主要泥石流运动模型。建议近期泥石流运动机理研究宜着重厘定各类模型的适用范围和比较它们的应用结果，并进一步简化现有的机理模型，为泥石流防治工程提供具有一定理论基础和科学依据的流速、流量和冲击力等关键设计参数。与泥石流机理密切相关的预测预报，宜着重于泥石流的中长期预测和预警报，重点突破泥石流规模和发生频率相互关系的问题。     

COMPARISON OF 1-D AND 2-D MODELING OF OVERLAND RUNOFF AND SEDIMENT TRANSPORT1

ABSTRACT: One-dimensional and two-dimensional modeling approaches were compared for their abilities in predicting overland runoff and sediment transport. Both 1-D and 2-D models were developed to test the hypothesis that the 2-D modeling approach could improve the model predictions over the 1-P approach, based on the same mathematical representations of physical processes for runoff and sediment transport. The models developed in this study were applied to overland areas with cross slopes. A hypothetical case and an experimental study reported by Storm (1991) were used. Based on the simulation results from the selected hypothetical case and experimental study, the 2-D model provided better representation of spatial distribution of flow depths and sediment concentrations than the 1-D model. However, no significant differences in predictions of total runoff volume and sediment yield at the outlet area were found between the 1-D and 2-D models.     

优化大气监测布点方法的探讨

选择有代表性的监测点，是决定监测数据能否对该区域的状况进行描述的前提。炼厂排放源为不规则的无组织排放的面源，数据在该区域具有代表性的点上测出。将整个被测区域按不同的功能特点和生产工艺，划分成若干个小的功能区，在每个功能区中布有限个点，并同时在一个功能区的有限个点采样分析，运用数理统计的手段，探讨某一局部小区域中最优监测点的选择方法。该方法简单、实用，并在实际监测工作中得到应用。     

DEVELOPING AND IMPLEMENTING DECISION SUPPORT SYSTEMS: A CRITIQUE AND A CHALLENGE1

ABSTRACT: Computer-based models together with their interactive interfaces are typically called decision support systems. DSSs are interactive computer-based information providers. The common objective of all DSSs, regardless of the frameworks, methodologies, or techniques used, is to provide timely information that supports human decision makers - at whatever level of decision making. The informational needs of the decision making process are the key considerations that motivate the development of DSSs. The growth of DSS development and use has been substantial. In spite of this impressive growth, computer-aided decision support systems can still be improved and made more useful to those they are intended to support. Researchers and practitioners, and indeed the computer industry, continue to identify ways of doing this. This paper reviews some of these needs and opportunities by focusing on the process of successful DDS development and implementation. The paper outlines an approach and some guidelines for developing DSSs. The approach emphasizes and requires considerable interaction between the DSS developers (analysts) and the DSS users (decision makers). This interaction and feedback is required throughout the entire DSS building, testing and evaluation (debugging), and implementation processes. The paper concludes by identifying some research needs and opportunities affecting DSS development and effective use.     

APPLICATIONS OF A GIS FOR MODELING THE SENSITIVITY OF WATER RESOURCES TO ALTERATIONS IN CLIMATE IN THE GUNNISON RIVER BASIN,COLORADO1

ABSTRACT: The Gunnison River drains a mountainous basin in western Colorado, and is a large contributor of water to the Colorado River. As part of a study to assess water resource sensitivity to alterations in climate in the Gunnison River basin, climatic and hydrologic processes are being modeled. A geographic information system (GIS) is being used in this study as a link between data and modelers - serving as a common data base for project personnel with differing specialties, providing a means to investigate the effects of scale on model results, and providing a framework for the transfer of parameter values among models. Specific applications presented include: (1) developing elevation grids for a precipitation model from digital elevation model (DEM) point-elevation values, and visualizing the effects of grid resolution on model results; (2) using a GIS to facilitate the definition and parameterization of a distributed-parameters, watershed model in multiple basins; and (3) nesting atmospheric and hydrologic models to produce possible scenarios of climate change.     

A COMPARISON OF MODELS PREDICTING GROUND WATER LEVELS ON HILLSIDE SLOPES1

ABSTRACT: A comparative study of ground water level predictions on hillside slopes using two models is presented. The models are a simplified mass balance model that has components for evapotran-spiration, recharge, and drainage; and a two-dimensional finite difference model that employs kriging to estimate soil parameters and accounts for non-uniform thickness of the soil layer. These models are representative of a wide range of modeling capabilities and are used to illustrate the sensitivity of ground water level predictions to the sophistication of the modeling techniques. The drainage and recharge components of the two models are evaluated and the importance of unsaturated flow in recharge computations is underscored. Piezometric observations in a small drainage depression on the slope of Kennel Creek Valley in Tongass National Forest, Alaska, were used to evaluate the two models. The results show that, although the predictions differ from the field observations, the simple physically-based mass balance model predicts the ground water levels as well as the two-dimensional model. It is suggested that caution should be exercised in using complex models to validate simpler models.