Implications of Conceptual Channel Representation on SWAT Streamflow and Sediment Modeling

Hydrologic modeling outputs are influenced by how a watershed system is represented. Channel routing is a typical example of the mathematical conceptualization of watershed landscape and processes in hydrologic modeling. We investigated the sensitivity of accuracy, equifinality, and uncertainty of Soil and Water Assessment Tool (SWAT) modeling to channel dimensions to demonstrate how a conceptual representation of a watershed system affects streamflow and sediment modeling. Results showed the amount of uncertainty and equifinality strongly responded to channel dimensions. On the other hand, the model performance did not significantly vary with the changes in the channel representation due to the degree of freedom allowed by the conceptual nature of hydrologic modeling in the parameter calibration. Such findings demonstrated good modeling performance statistics do not necessarily mean small output uncertainty, and partial improvements in the watershed representation may neither increase modeling accuracy nor reduce uncertainty. We also showed the equifinality and uncertainty of hydrologic modeling are case‐dependent rather than specific to models or regions, suggesting great caution should be used when attempting to transfer uncertainty analysis results to other modeling studies, especially for ungauged watersheds. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

非饱和土壤渗透系数空间不确定性对溶质运移的影响

包气带渗透系数的不确定性是影响非饱和带溶质运移的主要因素。应用贝叶斯方法对非饱和土壤渗透系数进行前处理,使用Monte-Carlo方法模拟其空间不确定性,并通过HYDRUS-1D模型对溶质运移进行数值模拟,研究包气带渗透系数的空间不确定性对溶质运移的影响。结果表明,由于包气带渗透性的不确定性使得溶质浓度分布呈现明显的不确定性,包气带内不同点的浓度值相差很大。与忽略包气带土性参数空间不确定性的模拟结果相对比,考虑包气带渗透系数不确定性的模拟结果与实际情况更加接近,更具合理性和科学性。同时,根据模拟结果,对实际工作中进行地下水数值模拟时溶质初始浓度输入值的确定提出相应建议。     

Estimation of sampling uncertainty for determination of pesticide residues in plant commodities

In order to provide residue data for refining the estimated sampling uncertainty, a coordinated research program was initiated for performing field studies on residues in individual items of leafy vegetables, small and large crops. The trials were carried out in 13 countries with 3 small fruits, 5 large crops, 2 medium/large crops and 3 leafy vegetables. The 25 pesticide active ingredients applied represented the dicarboximide (3), organophosphorus (8), synthetic pyrethroids (5), phthalimides (2), organochlorine (1) and other types of pesticides (6). In addition, 11 supervised field trials were performed in grapes and lettuce by the pesticide manufacturers, and their results were provided for evaluation. The studies represented actual agriculture practice around the world, and provide reliable data for estimation of sampling uncertainty. Based on the 12346 residue data, the best estimate for the relative sampling uncertainty for composite samples, assuming sample size of 10 for small crops and leafy vegetables and 5 for large crops, with 95% confidence limits in brackets are: small commodities: 0.25 (0.20–0.29); Brassica leafy vegetables: 0.20 (0.16–0.24); large commodities: 0.33 (0.29–0.38).     

System Dynamics to Sustainable Water Resources Management in the Eastern Snake Plain Aquifer Under Water Supply Uncertainty1

Abstract: Water supply uncertainty continues to threaten the reliability of regional water resources in the western United States. Climate variability and water dispute potentials induce water managers to develop proactive adaptive management strategies to mitigate future hydroclimate impacts. The Eastern Snake Plain Aquifer in the state of Idaho is also facing these challenges in the sense that population growth and economic development strongly depend on reliable water resources from underground storage. Drought and subsequent water conflict often drive scientific research and political agendas because water resources availability and aquifer management for a sustainable rural economy are of great interest. In this study, a system dynamics approach is applied to address dynamically complex problems with management of the aquifer and associated surface‐water and groundwater interactions. Recharge and discharge dynamics within the aquifer system are coded in an environmental modeling framework to identify long‐term behavior of aquifer responses to uncertain future hydrological variability. The research shows that the system dynamics approach is a promising modeling tool to develop sustainable water resources planning and management in a collaborative decision‐making framework and also to provide useful insights and alternative opportunities for operational management, policy support, and participatory strategic planning to mitigate future hydroclimate impacts in human dimensions.     

Effects of input uncertainty and variability on the modelled environmental fate of organic pollutants under global climate change scenarios

Global climate change (GCC) is expected to influence the fate, exposure and risks of organic pollutants to wildlife and humans. Multimedia chemical fate models have been previously applied to estimate how GCC affects pollutant concentrations in the environment and biota, but previous studies have not addressed how uncertainty and variability of model inputs affect model predictions. Here, we assess the influence of climate variability and chemical property uncertainty on future projections of environmental fate of six polychlorinated biphenyl congeners under different GCC scenarios using a spreadsheet version of the ChemCAN model and the Crystal Ball® software. Regardless of emission mode, results demonstrate: (i) uncertainty in degradation half-lives dominates the variance of modelled absolute levels of PCB congeners under GCC scenarios; (ii) when the ratios of predictions under GCC to predictions under present day climate are modelled, climate variability dominates the variance of modelled ratios; and (iii) the ratios also indicate a maximum of about a factor of 2 change in the long-term average environmental concentrations due to GCC that is forecasted between present conditions and the period between 2080 and 2099. We conclude that chemical property uncertainty does not preclude assessing relative changes in a GCC scenario compared to a present-day scenario if variance in model outputs due to chemical properties and degradation half-lives can be assumed to cancel out in the two scenarios.     

基于层次分析法的未确知测度理论泥石流危险性评价

将未确知测度理论与层次分析方法相结合用于评价泥石流危险性。根据泥石流危险性的影响因素和等级划分标准,选取泥石流规模、泥石流发生频率、流域面积、主沟长度、最大相对高差、流域切割密度、主沟床弯曲系数、泥砂补给长度比、24小时最大降雨量、人口密度等10个指标作为泥石流危险评价因子,利用未确知测度理论建立泥石流危险性评价指标的未确知测度函数,通过层次分析方法确定各评价指标的权重,依据置信度识别准则对泥石流危险性进行评价,并结合实例进行了对比分析。研究结果表明,基于层次分析方法的未确知测度理论的评价方法评价过程合理、置信度高、结果可靠,为泥石流危险性评价提供了一种新的方法     

土地利用规划中不确定性的识别和处理研究

首先概述不确定性概念及其产生、相关理论和研究进展,深刻地揭示由于在我国土地和用规划中长期以来忽视开展不确定性研究,导致规划指标偏离现实需求,频繁修改规划方案和违法用地现象不断发生,在此基础上,引入不确定性规划理念,重新审视不确定性在土地利用规划中的地位和作用,全面系统地阐述土地利用规划中不确定性的类型及其特性,具体表现及其识别和处理方法.研究结果表明,由于人们的知识所限,客观世界中普遍存在不确定性.不确定性孕育着规划的产生,规划是对未来不确定性的缓解和抵消.土地利用规划中长期以来忽视业已存在的不确定性,直接影响土地利用规划的科学性和可操作性.土地利用规划中最基本的不确定性是预测未来和为了适应未来而对现在进行调整的失误.对未来的无知所引发的不确定性,只能求助于不确定性科学,增强对未来的预测能力和控制能力,使不确定性的负面影响最小化.     

Testing the feasibility of a hypothetical whaling‐conservation permit market in Norway

A cap‐and‐trade system for managing whale harvests represents a potentially useful approach to resolve the current gridlock in international whale management. The establishment of whale permit markets, open to both whalers and conservationists, could reveal the strength of conservation demand, about which little is known. This lack of knowledge makes it difficult to predict the outcome of a hypothetical whale permit market. We developed a bioeconomic model to evaluate the influence of economic uncertainty about demand for whale conservation or harvest. We used simulations over a wide range of parameterizations of whaling and conservation demands to examine the potential ecological consequences of the establishment of a whale permit market in Norwegian waters under bounded (but substantial) economic uncertainty. Uncertainty variables were slope of whaling and conservation demand, participation level of conservationists and their willingness to pay for whale conservation, and functional forms of demand, including linear, quadratic, and log‐linear forms. A whale‐conservation market had the potential to yield a wide range of conservation and harvest outcomes, the most likely outcomes were those in which conservationists bought all whale permits.     

气候试验箱内部条件不确定度计算(下)

提供了对温度和湿度气候试验箱内部环境条件进行不确定度分析的方法。首先介绍了测量的不确定度概念,然后讨论容差的意义。考虑到湿度和温度测量是采用确定和合成不确定度。结合校准空载试验箱和有负载试验箱的条件测量的案例。最后,逐条整理成为范本用于分析结果以给出规范的不确定度评估依据。     

Assessing and testing prediction uncertainty for single tree-based models: A case study applied to northern hardwood stands in southern Québec, Canada

Estimating prediction uncertainty for a single tree-based model is hindered by the complex structure of these models. In this paper, we addressed this issue with a case study applied to northern hardwood stands in Québec, Canada. SaMARE is a stochastic single tree-based model that was designed for these types of stands. Using a Monte Carlo approach, the model can provide a mean predicted value and its confidence limits for some plot-level attributes.The mean predicted values were compared to observed values in terms of bias and accuracy. In addition to these common statistics, we compared nominal coverage of Monte Carlo-simulated confidence intervals with real (observed) coverage to verify the adequacy of the simulated uncertainty. A comparison was made using several plot-level attributes, which exhibited an increasing discriminative complexity. This complexity ranges from coarse attributes, such as all-species basal area, up to more complex ones, such as basal area for stems of a particular species and with sawlog potential.The results showed that in terms of absolute value, biases were small, but could be relatively high with respect to the average observed value when the discriminative complexity of the attribute increased. The comparison between nominal and real coverage of confidence intervals gave satisfactory results for all-species plot-level attributes. However, for some species-specific attributes, the Monte Carlo-simulated confidence intervals overestimated the real coverage.