Communicating uncertainty: lessons learned and suggestions for climate change assessment

Assessments of climate change face the task of making information about uncertainty accessible and useful to decision-makers. The literature in behavior economics provides many examples of how people make decisions under conditions of uncertainty relying on inappropriate heuristics, leading to inconsistent and counterproductive choices. Modern risk communication practices recommend a number of methods to overcome these hurdles, which have been recommended for the Intergovernmental Panel on Climate Change (IPCC) assessment reports. This paper evaluates the success of the most recent IPCC approach to uncertainty communication, based on a controlled survey of climate change experts. Evaluating the results from the survey, and from a similar survey recently conducted among university students, the paper suggests that the most recent IPCC approach leaves open the possibility for biased and inconsistent responses to the information. The paper concludes by suggesting ways to improve the approach for future IPCC assessment reports. To cite this article: A. Patt, S. Dessai, C. R. Geoscience 337 (2005).     

Uncertainty Estimate in Resources Assessment: A Geostatistical Contribution

For many decades the mining industry regarded resources/reserves estimation and classification as a mere calculation requiring basic mathematical and geological knowledge. Most methods were based on geometrical procedures and spatial data distribution. Therefore, uncertainty associated with tonnages and grades either were ignored or mishandled, although various mining codes require a measure of confidence in the values reported. Traditional methods fail in reporting the level of confidence in the quantities and grades. Conversely, kriging is known to provide the best estimate and its associated variance. Among kriging methods, Ordinary Kriging (OK) probably is the most widely used one for mineral resource/reserve estimation, mainly because of its robustness and its facility in uncertainty assessment by using the kriging variance. It also is known that OK variance is unable to recognize local data variability, an important issue when heterogeneous mineral deposits with higher and poorer grade zones are being evaluated. Altenatively, stochastic simulation are used to build local or global uncertainty about a geological attribute respecting its statistical moments. This study investigates methods capable of incorporating uncertainty to the estimates of resources and reserves via OK and sequential gaussian and sequential indicator simulation The results showed that for the type of mineralization studied all methods classified the tonnages similarly. The methods are illustrated using an exploration drill hole data sets from a large Brazilian coal deposit.     

On container versus time based inspection policies in invasive species management

We study the problem of precluding biological invasions caused by ships transporting internationally traded goods in containers between different regions of the world. Using the long run expected net cost (LRENC) of inspections as the apposite managerial objective, we address the following important question: given that inspection is a cyclical activity, is the LRENC lower when a port manager’s inspector inspects cargo upon the arrival of a specified number of containers (container policy) or is this LRENC lower when this inspector inspects cargo at fixed points in time (temporal policy)? We construct a queuing theoretic model and show that in an inspection cycle, irrespective of whether the inspection policy choice is made on the basis of an explicit optimization exercise or on the basis of rules of thumb, the container policy is superior to the temporal policy because the container policy results in lower LRENC from inspection activities.     

An application of Ensemble Kalman Filter in integral-balance subsurface modeling

Data assimilation method provides a framework to decrease the uncertainty of hydrological modeling by sequentially incorporating observations into numerical model. Such a process involves estimating statistical moments of different order based on the evolution of conditional probability distribution function. Because of the nonlinearity of many hydrological dynamics, explicit and analytical solutions for moments of state distribution are often impossible. Evensen [J Geophys Res 99(c5): 10143–10162 (1994)] introduced Ensemble Kalman Filtering (EnKF) method to address such problems. We test and evaluate the performance of EnKF in fusing model predictions and observations for a saturated–unsaturated integral-balance subsurface model. We find EnKF improve the model predictions, and also we conclude a good estimate of state variance is essential for the success of EnKF.     

The impact of different spatial land cover data sets on the outputs of a hydrological model - a modelling exercise in the Ucker catchment, North-East Germany

The spatial distribution of forests, meadows, arable land, water bodies and settlements in a catchment influences the spatial and temporal dynamics of evapotranspiration, surface runoff, soil moisture and ground water recharge. Four digital data sets from different sources were available for land cover distribution to be applied in a regional case study in the Ucker catchment with an area of about 2415 km². The first data set was obtained from the German digital topographic data set “Atkis” and the second one from the federal German biotope mapping procedure “Biotoptypenkartierung”. In addition, Corine land cover data and a land cover obtained from a supervised, multitemporal classification of three Landsat-TM5-scenes from the year 2000 were used in our study. These data sets differ in spatial resolution and in information content and this leads to different areal proportions of the main land cover classes forests, meadows, arable land, water bodies and settlements. This has to be considered as an uncertainty in the land cover data. In our case study, we analyzed how and to which extent this uncertainty influences the outputs of a hydrological catchment model such as evapotranspiration and discharge. For the time period 1996-2001, meteorological time series were obtained from four meteorological stations and five additional precipitation stations. Measured daily discharge rates were available from two gauges located in the catchment. In the different land cover data sets, the proportions of arable land ranged from 52.7% to 61.7% of the catchment area and for forests from 19.5% to 24.6%. These different proportions showed only minor impacts with small differences below ±10 mm y⁻¹ on the simulated annual rates of evapotranspiration and ground water recharge. In contrast, the simulated surface runoff rates showed a strong correlation to the amount of the settlement areas in the catchment. The highest proportion of settlements with 4.9% of the catchment area in comparison to the lowest proportion of 2.9% leads to an increase in the simulated surface runoff of 70%.     

Risk minimization in water quality control problems of a river system

Methodologies are presented for minimization of risk in a river water quality management problem. A risk minimization model is developed to minimize the risk of low water quality along a river in the face of conflict among various stake holders. The model consists of three parts: a water quality simulation model, a risk evaluation model with uncertainty analysis and an optimization model. Sensitivity analysis, First Order Reliability Analysis (FORA) and Monte–Carlo simulations are performed to evaluate the fuzzy risk of low water quality. Fuzzy multiobjective programming is used to formulate the multiobjective model. Probabilistic Global Search Laussane (PGSL), a global search algorithm developed recently, is used for solving the resulting non-linear optimization problem. The algorithm is based on the assumption that better sets of points are more likely to be found in the neighborhood of good sets of points, therefore intensifying the search in the regions that contain good solutions. Another model is developed for risk minimization, which deals with only the moments of the generated probability density functions of the water quality indicators. Suitable skewness values of water quality indicators, which lead to low fuzzy risk are identified. Results of the models are compared with the results of a deterministic fuzzy waste load allocation model (FWLAM), when methodologies are applied to the case study of Tunga–Bhadra river system in southern India, with a steady state BOD–DO model. The fractional removal levels resulting from the risk minimization model are slightly higher, but result in a significant reduction in risk of low water quality.     

Calibration framework for a Kalman filter applied to a groundwater model

The paper presents a novel approach to the setup of a Kalman filter by using an automatic calibration framework for estimation of the covariance matrices. The calibration consists of two sequential steps: (1) Automatic calibration of a set of covariance parameters to optimize the performance of the system and (2) adjustment of the model and observation variance to provide an uncertainty analysis relying on the data instead of ad-hoc covariance values. The method is applied to a twin-test experiment with a groundwater model and a colored noise Kalman filter. The filter is implemented in an ensemble framework. It is demonstrated that lattice sampling is preferable to the usual Monte Carlo simulation because its ability to preserve the theoretical mean reduces the size of the ensemble needed. The resulting Kalman filter proves to be efficient in correcting dynamic error and bias over the whole domain studied. The uncertainty analysis provides a reliable estimate of the error in the neighborhood of assimilation points but the simplicity of the covariance models leads to underestimation of the errors far from assimilation points.     

数量化理论在泥石流灾害预测预报中的应用--以吉林和龙市泥石流为例

和龙市地处长白山脉东北部,地质环境质量较差,区内常有泥石流、崩塌、滑坡等地质灾害发生。该市东城区具备形成泥石流的条件,泥石流发生频繁。2002年7月间,该市境内连降暴雨,日最大降雨量达69.8mm,导致多处暴发泥石流,造成较大灾害。文章根据东城区34条泥石流沟的调查资料,采用数量化理论对泥石流易发程度进行统计分析,建立了泥石流易发程度预测模型。计算获得的预测值与实测值相接近。     

中国早寒武世岩相古地理

本文中的中国主要指我国的大陆、海南岛及台湾等地区的陆地部分。本文由中国早寒武世早期及晚期的岩相古地理图2幅及相应的文字论述组成。这两幅岩相古地理图的最大特征是“两槽和三台相间分布”。两槽即天山北山蒙辽吉槽地和昆仑秦岭槽地,三台即准噶尔蒙兴槽地、塔里木柴达木华北台地和西藏华南台地。两个槽地与三个台地之间的界限是根据大地构造、地层、岩石、岩相等资料综合判断而定的,绝大部分是比较确切的,有的地方是推断的。天山北山槽地可分出次级岩相古地理单元,其他槽地的次级岩相古地理单元尚难以划分。在三个台地中,华南、华北和西北地区的研究程度较高,它们的次级岩相古地理单元的划分均有确切的定量资料和图件为依据,是定量的,而且还能把早寒武世早期和晚期的岩相古地理区分开;其他地区的研究程度较低,难以再划分次级古地理单元,其古地理图都只能是定性的。这种研究程度有差异的、定量和定性兼有的、全国范围的岩相古地理图,既反映笔者等的研究成果,也反映我国当前地质工作的研究程度,优缺兼有,实虚共存。敬请读者指教。