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1.
This study reassesses the application of the geochemical model MAGIC in the prediction of long-term changes of water quality in response to changes in atmospheric deposition. It does so within the Monte Carlo based GLUE methodology in which it is possible to evaluate the performance of sets of model parameters in predicting the available observations as a means of constraining the uncertainty in current and future predictions. This work was prompted by previous work which showed that, for a typical upland site in Wales, MAGIC predictions were dominated by the depositional scenario used. Uncertainties in the depositional scenario are taken into account by using estimates of uncertainty for the different depositional sources including European anthropogenic sources as produced by the HARM model. The results show almost no change in predictive uncertainty bounds, in the form of 5th and 95th percentiles of the likelihood-weighted distributions, owing to tight observational data constraints. The implications of this lack of change with respect to predictive capability and possible over-constraint by observed data are discussed. 相似文献
2.
Anisotropic models are often used in spatial statistics to analyze spatially referenced data. Within a Bayesian framework we develop default priors for the anisotropic Gaussian random field model with and without including a nugget parameter accounting for the effects of microscale variations and measurement errors. We present Jeffreys priors and a reference prior and study their posterior propriety. Moreover, we obtain that the predictive distributions at ungauged locations have finite variance. We also show that the seemingly uninformative uniform prior for the anisotropy parameters, ratio and angle, yields an improper posterior. Finally, we find that the proposed priors have good frequentist properties and we illustrate our approach by analyzing two data sets for which we discuss model choice as well as predictions and uncertainty estimates. 相似文献
3.
This study investigates the uncertainty associated with the modelled response of a catchment to historic and predicted future acidic deposition for the period 1851–2041. The MAGICmodel is applied within a GLUE framework to the 3.88 km2 Afon Gwy catchment at Plynlimon, Wales. Nine million Monte Carlo simulations resulted in 5700 being accepted as behaviouralas defined by a fuzzy measure comparing observed to simulated variables. Model output and parameter sensitivity analysis indicate that, for this example where weathering rates are low,model dynamics are limited compared to control exerted by modelinitial conditions and by the specified acidic deposition boundary conditions. The results show that despite the small number of behavioural simulations, they are widely spread acrossthe ranges for most of the parameters varied. The GLUE methodology allows simulated prediction ranges for important variables to be presented as quantitative likelihood weighteduncertainty estimates rather than a single prediction for eachvariable over time. 相似文献
4.
生态系统模型一般参数较多,且在应用时存在时空尺度问题,易产生不确定性。通过模型不确定性分析,可以加深对模型结构的理解,提高模型预报的可靠性。植被界面过程模型(VIP)是一个综合考虑了陆地生态系统能量收支、水文循环和碳氮等生命元素吸收转化等过程的生态/水文动力学模型。本文采用GLUE(General-ized Likelihood Uncertainty Estimation)方法,以拟合度系数作为似然判据,利用华北平原冬小麦生长季内的田间观测数据分析VIP模型中的作物生长、土壤水分运动以及光合速率模块中8个参数以及模型预报的不确定性。研究表明,最大光合速率Vmax、饱和含水量wcsat、田间持水量wcfield参数为敏感性参数,其对似然判据的影响大,其余参数是相对不敏感参数。在置信度为95%水平下,发现观测值大都接近或者包含在置信预报区域内,说明可以通过参数校准得到很好的模型模拟效果。 相似文献
5.
The PROFILE model is a steady state soil chemistry model which is used to calculate soil weathering rate. The model has also been used to calculate critical loads of acidity and N to forest soils, using the ratio of Ca+Mg+K to total inorganic aluminium in the soil solution as criterion, and to surface waters, using the ANC leached from the soil column as criterion. An uncertainty analysis of the PROFILE model was performed by Monte Carlo analysis, varying input parameter errors individually and simultaneously in ranges of ±10–100%, depending on parameter. The uncretainty in calculation of weathering rate, ANC leaching and ratio of Ca+Mg+K to inorganic Al in the soil solution was studied for three Nordic sites. Furthermore, the effect of uncertainty in estimates of critical load for forest soils was assessed. The analysis shows that the weathering rate can be calculated with high precision, provided that the errors of input parameter are within the range that has been reported in the literature. The model tend to be less sensitive to errors in input parameters for the range of conditions where forest damage is most likely to occur. Critical loads of acid deposition for one site calculated on the basis of the model varies within a largest range of ±40%. A study of one geographical grid included in the Swedish critical loads assessment shows that with the number of calculation points in the grid, the distribution of critical loads will stay stable independently of stochastic errors. 相似文献
6.
The Ca l?Isard catchment (1.32 km2), a sub-basin of the Vallcebre experimental catchments, yields large amounts of sediments (about 580 Mg km− 2 year− 1) that are produced in relatively small but very active eroded areas (badlands). Several lines of evidence suggest that there is a delay between sediment production, caused by intense summer rainstorms, and sediment transport, occasioned by the main floods produced by large precipitation events following wet antecedent conditions. First, a calibration–validation exercise was carried out with sediment yield data obtained using containers provided with slot divisors in a badlands micro-catchment (1240 m2). Then, the model was applied to the main badlands areas in the Ca l?Isard sub-catchment for a 4-year period and the simulated sediment yields were compared with the records at the gauging station. The test was performed with the Generalized Likelihood Uncertainty Estimation (GLUE) approach for assessing the uncertainty associated with model predictions, which assumes that many parameter sets can give acceptable simulations. The results demonstrated the capacity of KINEROS2 to simulate badland erosion, although it showed limited robustness. A clear temporal mismatch between erosion and sediment transport and the relevance of sediment stores in the catchment were confirmed, while the total weights of sediment were generally under-predicted. The limited suitability of the area used for calibration or the role of sediment sources not simulated in the approach may account for this shortcoming. 相似文献
7.
This paper reports an uncertainty analysis of critical loads for acid deposition for a site in southern England, using the Steady State Mass Balance Model. The uncertainty bounds, distribution type and correlation structure for each of the 18 input parameters was considered explicitly, and overall uncertainty estimated by Monte Carlo methods. Estimates of deposition uncertainty were made from measured data and an atmospheric dispersion model, and hence the uncertainty in exceedance could also be calculated. The uncertainties of the calculated critical loads were generally much lower than those of the input parameters due to a “compensation of errors” mechanism – coefficients of variation ranged from 13% for CLmaxN to 37% for CL(A). With 1990 deposition, the probability that the critical load was exceeded was > 0.99; to reduce this probability to 0.50, a 63% reduction in deposition is required; to 0.05, an 82% reduction. With 1997 deposition, which was lower than that in 1990, exceedance probabilities declined and uncertainties in exceedance narrowed as deposition uncertainty had less effect. The parameters contributing most to the uncertainty in critical loads were weathering rates, base cation uptake rates, and choice of critical chemical value, indicating possible research priorities. However, the different critical load parameters were to some extent sensitive to different input parameters. The application of such probabilistic results to environmental regulation is discussed. 相似文献
8.
Distributed erosion models are potentially good tools for locating soil sediment sources and guiding efficient Soil and Water Conservation (SWC) planning, but the uncertainty of model predictions may be high. In this study, the distribution of erosion within a catchment was predicted with a semi-empirical erosion model that combined a semi-distributed hydrological model with the Morgan, Morgan and Finney (MMF) empirical erosion model. The model was tested in a small catchment of the West Usambara Mountains (Kwalei catchment, Tanzania). Soil detachability rates measured in splash cups (0.48–1.16 g J− 1) were close to model simulations (0.30–0.35 g J− 1). Net erosion rates measured in Gerlach troughs (0.01–1.05 kg m− 2 per event) were used to calibrate the sediment transport capacity of overland flow. Uncertainties of model simulations due to parameterisation of overland flow sediment transport capacity were assessed with the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. The quality of the spatial predictions was assessed by comparing the simulated erosion pattern with the field-observed erosion pattern, measuring the agreement with the weighted Kappa coefficient of the contingency table. Behavioural parameter sets (weighted Kappa > 0.50) were those with short reinfiltration length (< 1.5 m) and ratio of overland flow power α to local topography power γ close to 0.5. In the dynamic Hortonian hydrologic regime and the dissected terrain of Kwalei catchment, topography controlled the distribution of erosion more than overland flow. Simulated erosion rates varied from − 4 to + 2 kg m− 2 per season. The model simulated correctly around 75% of erosion pattern. The uncertainty of model predictions due to sediment transport capacity was high; around 10% of the fields were attributed to either slight or severe erosion. The difficult characterisation of catchment-scale effective sediment transport capacity parameters poses a major limit to distributed erosion modelling predicting capabilities. 相似文献
9.
Soil heat and moisture processes are interconnected, especially during low temperatures. To examine the interaction between soil temperature and moisture under freeze‐thaw cycles, a physical process‐based model (CoupModel) coupled with uncertainty analysis was applied to 3‐year measurements under seasonal frost conditions from a site in the black soil belt of northeast China. The uncertainty in parameters and measurements was described by general likelihood uncertainty estimation (GLUE). To identify the degree of linkage between soil temperature and moisture, three criteria were applied to them separately or together. The most sensitive parameters among 26 site‐specific parameters were closely related to soil heat, soil evaporation and freeze‐thaw processes. Soil temperature was simulated with less uncertainty than soil moisture. Soil temperature measurements had the potential to improve model performance for soil water content, whereas soil moisture measurements demonstrated a trade‐off effect when finding a model with good performance for both temperature and moisture. During winter conditions the uncertainty ranges of soil temperature were most pronounced, probably because of the greater complexity of soil properties during the freeze‐thaw process and the uncertainty caused by snow properties. The largest uncertainty ranges of both soil water content and soil water storage were found mainly in the deep soil layers. The simulated surface heat fluxes are an important output of the model and it is of great value to compare them with the results from regional climate models and micrometeorological measurements. 相似文献
10.
Purpose
Spatial prediction of near-surface soil moisture content (NSSMC) is necessary for both hydrologic modeling and land use planning. However, uncertainties associated with the prediction are always neglected and lack of quantitative analysis. The objective of this study was to investigate the influences of different sources of uncertainty on NSSMC estimation at two typical hillslopes (i.e., tea garden and forest).Materials and methods
In this study, stepwise multiple regression models with terrain indices and soil texture were built to spatially estimate NSSMC on two typical land use hillslopes (tea garden and forest) at different dates. The uncertainties due to limited sample sizes used for developing regression models (uncertainty of model parameter), digital elevation model resolutions of 1, 2, 3, 4, and 5 m (uncertainty of terrain indices) and spatial interpolations of soil texture by kriging or cokriging with electromagnetic induction (uncertainty of soil texture), were investigated using bootstrap, resampling, and Latin hypercube sampling techniques, respectively.Results and discussion
The accuracies of NSSMC predictions were acceptable for both tea garden (the Nash-Sutcliffe efficiency or NSE?=?0.34) and forest hillslopes (NSE?=?0.57). The model parameter uncertainty was more important on tea garden hillslope than on forest hillslope. A significant negative correlation (P?<?0.05) was observed between the model parameter uncertainty and the mean NSSMC of the hillslopes, indicating that the model parameter uncertainty was small when the hillslope was wet. The resolution uncertainty from digital elevation model had a minor effect on NSSMC predictions on both hillslopes. The texture uncertainty was weak on NSSMC estimations on tea garden hillslope. However, it was more important than the model parameter uncertainty on the forest hillslope.Conclusions
Improving the regression model structure and the hillslope soil texture mapping are critical in the accurate spatial prediction of NSSMC on tea garden and forest hillslopes, respectively. This study presents techniques for analyzing three different uncertainties that can be used to identify the main sources of uncertainties in soil mapping.11.
R. A. Skeffington 《Water, air, and soil pollution》2006,169(1-4):3-24
Critical loads are the basis for policies controlling emissions of acidic substances in Europe. The implementation of these policies involves large expenditures, and it is reasonable for policymakers to ask what degree of certainty can be attached to the underlying critical load and exceedance estimates. This paper is a literature review of studies which attempt to estimate the uncertainty attached to critical loads. Critical load models and uncertainty analysis are briefly outlined. Most studies have used Monte Carlo analysis of some form to investigate the propagation of uncertainties in the definition of the input parameters through to uncertainties in critical loads. Though the input parameters are often poorly known, the critical load uncertainties are typically surprisingly small because of a “compensation of errors” mechanism. These results depend on the quality of the uncertainty estimates of the input parameters, and a “pedigree” classification for these is proposed. Sensitivity analysis shows that some input parameters are more important in influencing critical load uncertainty than others, but there have not been enough studies to form a general picture. Methods used for dealing with spatial variation are briefly discussed. Application of alternative models to the same site or modifications of existing models can lead to widely differing critical loads, indicating that research into the underlying science needs to continue. 相似文献
12.
延河流域典型物种分布预测模型比较研究 总被引：3，自引：0，他引：3
物种分布预测一直以来都是生态学研究的重要内容之一.应用生态学的发展为物种分布预测提供了众多强有力的模型,在推进物种分布预测进展的同时,也增加了合适模型选择的难度.评价和比较不同模型的预测效果,对于模型的选择和应用具有非常重要的意义.以黄土丘陵区延河流域为研究区,采用R语言和BIOMOD程序包为平台,选择人工神经网络(artificial neural networks,ANN)等9个较常用的物种分布模型,比较它们在物种分布预测精度上的差异,为物种分布预测模型的选择提供依据,也为进一步预测未来气候变化情景下物种空间分布的变化奠定基础.研究结果表明,不同模型对不同物种的模拟精度差异明显.根据Kappa,TSS和Roc评价方法,9个模型对百里香(Thymus mongolicus)分布的预测精度最高;对铁杆蒿(Artemisia gmelinii)分布的模拟精度最差;而对其余物种分布的模拟精度均比较理想,其中以随机树RF模型最好. 相似文献
13.
Uncertainty in parameter estimates from sampling variation or expert judgment can introduce substantial uncertainty into ecological predictions based on those estimates. However, in standard population viability analyses, one of the most widely used tools for managing plant, fish and wildlife populations, parametric uncertainty is often ignored in or discarded from model projections. We present a method for explicitly incorporating this source of uncertainty into population models to fully account for risk in management and decision contexts. Our method involves a two-step simulation process where parametric uncertainty is incorporated into the replication loop of the model and temporal variance is incorporated into the loop for time steps in the model. Using the piping plover, a federally threatened shorebird in the USA and Canada, as an example, we compare abundance projections and extinction probabilities from simulations that exclude and include parametric uncertainty. Although final abundance was very low for all sets of simulations, estimated extinction risk was much greater for the simulation that incorporated parametric uncertainty in the replication loop. Decisions about species conservation (e.g., listing, delisting, and jeopardy) might differ greatly depending on the treatment of parametric uncertainty in population models. 相似文献
14.
We present a Bayesian mark-recapture method for explicitly communicating uncertainty about the size of a closed population
where capture probabilities vary across both individuals and sampling occasions. Heterogeneity is modeled hierarchically using
a continuous logistic-Normal model to specify the capture probabilities for both individuals that are captured on at least
one occasion and individuals that are never captured and so remain undetected. Inference about how many undetected individuals
to include in the model is accomplished through a Bayesian model selection procedure using MCMC, applied to a product space
of possible models for different numbers of undetected individuals. Setting the estimation problem in a fixed dimensional
parameter space enables the model selection procedure to be performed using the freely available WinBUGS software. The outcome
of inference is a full “posterior” probability distribution for the population size parameter. We demonstrate this method
through an example involving real mark-recapture data. 相似文献
15.
The critical loads approach to quantifying areas at risk of damage requires deposition and critical loads data at the same spatial scale to calculate exceedance. While maps of critical loads for soil acidification are available at a 1 km scale no monitoring networks in Europe measure wet and dry inputs at this scale and, further, the models currently used to estimate deposition incorporate a number of assumptions which are not valid at the 1 km scale. Simulations of 1 km deposition from 20 km data show that the uncertainty introduced by using 20 km scale estimates of deposition is small, except in mountain areas where it can give misleading results, but a major problem is the uncertainty in estimates of deposition at the 20 km scale produced by the current models. 相似文献
16.
Yung-Chieh Wang Yu-Pin Lin Chun-Wei Huang Li-Chi Chiang Hone-Jay Chu Wen-Sheng Ou 《Water, air, and soil pollution》2012,223(5):2719-2742
This work develops a system dynamic simulation model for free-water surface constructed wetlands, as well as provides appropriate values for the parameters of constructed wetland management. The system dynamic model is calibrated and validated by using data from a 1-year study of a constructed wetland in Tainan of southern Taiwan. Additionally, the major parameters that affect the simulation output are obtained via sensitivity analysis by using generalized likelihood uncertainty estimation (GLUE). A high R 2 and Nash?CSutcliffe coefficient of efficiency between the simulated and measured outflow values indicate that in addition to reproducing the changing trends of dissolved oxygen (DO), 5-day biological oxygen demand (BOD5), total nitrogen (TN), total suspended sediment (TSS), and total phosphorous (TP) concentrations, the model can simulate the variations of DO, BOD5, and TSS. Taken into account the interactions among parameters, the GLUE method successfully obtained the model sensitive parameters from the Monte Carlo parameter sets. Sensitivity analysis results indicate that the parameters of microorganisms are sensitive factors that affect DO, BOD5, and TN, while sediment diameter largely influences TP and TSS. Further elucidating environmental microorganisms would increase the model accuracy and provide a valuable reference for constructed wetland management and design. 相似文献
17.
Richard D. Wilkinson Michail Vrettas Dan Cornford Jeremy E. Oakley 《Journal of Agricultural, Biological & Environmental Statistics》2011,16(4):554-570
When making predictions with complex simulators it can be important to quantify the various sources of uncertainty. Errors
in the structural specification of the simulator, for example due to missing processes or incorrect mathematical specification,
can be a major source of uncertainty, but are often ignored. We introduce a methodology for inferring the discrepancy between
the simulator and the system in discrete-time dynamical simulators. We assume a structural form for the discrepancy function,
and show how to infer the maximum-likelihood parameter estimates using a particle filter embedded within a Monte Carlo expectation
maximization (MCEM) algorithm. We illustrate the method on a conceptual rainfall-runoff simulator (logSPM) used to model the
Abercrombie catchment in Australia. We assess the simulator and discrepancy model on the basis of their predictive performance
using proper scoring rules. This article has supplementary material online. 相似文献
18.
A sensitivity analysis was performed testingweathering rates, critical loads andexceedances for Swedish forest soils using Monte Carlosimulations of the PROFILE model. Different subsetsof input data were investigated with respect to theirpotential to reduce data uncertainty at site level butalso for modified estimates of the 5%-ile critical load andthe 95%-ile exceedance on 150×150 kmresolution. Physical soil properties were of dominantimportance for all sites and yield up to 62%reduction of the output standard deviation in weathering rate.The study showed that the critical ratio ofbase cations to inorganic aluminium (Bc/Al ratio) in the soilsolution was of major importance for reducingdata uncertainty in critical loads and exceedance estimates.The critical Bc/Al ratio was found to beimportant for reducing data uncertainties in modifiedestimates of the 5%-ile critical load and the95%-ile exceedance, in particular in the northern part ofSweden. Atmospheric deposition, uptake andlitterfall were more important for reducing data uncertaintyin the southern part. Physical soil propertiesand especially mineral content were found to be less importantfor reducing data uncertainties in criticalloads and exceedance estimates. The greatest scope forreducing data uncertainties in an applied perspectiveis to improve estimates of atmospheric deposition of anionsand cations as well as uptake and litterfall ofbase cations and nitrogen. 相似文献
19.
Jagadeesh B. Yeluripati Marcel van Oijen A. Neftel W.J. Parton 《Soil biology & biochemistry》2009,41(12):2579-321
The most widely applied soil carbon models partition the soil organic carbon into two or more kinetically defined conceptual pools. The initial distribution of soil organic matter between these pools influences the simulations. Like many other soil organic carbon models, the DAYCENT model is initialised by assuming equilibrium at the beginning of the simulation. However, as we show here, the initial distribution of soil organic matter between the different pools has an appreciable influence on simulations, and the appropriate distribution is dependent on the climate and management at the site before the onset of a simulated experiment. If the soil is not in equilibrium, the only way to initialise the model is to simulate the pre-experimental period of the site. Most often, the site history, in terms of land use and land management is often poorly defined at site level, and entirely unknown at regional level. Our objective was to identify a method that can be applied to initialise a model when the soil is not in equilibrium and historic data are not available, and which quantifies the uncertainty associated with initial soil carbon distribution. We demonstrate a method that uses Bayesian calibration by means of the Accept-Reject algorithm, and use this method to calibrate the initial distribution of soil organic carbon pools against observed soil respiration measurements. It was shown that, even in short-term simulations, model initialisation can have a major influence on the simulated results. The Bayesian calibration method quantified and reduced the uncertainties in initial carbon distribution. 相似文献
20.
J. N. Quinton J. Freer C. J. A. Macleod G. S. Bilotta R. E. Brazier J. M. B. Hawkins P. M. Haygarth 《European Journal of Soil Science》2012,63(2):211-223
Soils are important sources of sediment and phosphorus in rural catchments, necessitating the development of mathematical models for impact assessment. In this paper, multiple empirical models are tested on an event basis at four nested locations in an intensively managed grassland headwater catchment while accounting for parameter and data uncertainties using extended Generalized Likelihood Uncertainty Estimation (GLUE). The study provides the first template of model comparison under data uncertainty in soil erosion and phosphorus transfer modelling as well as hypotheses of soil and water processes in the study catchment. A fodder field, yielding large sediment and phosphorus concentrations in runoff, is characterized by inter‐event variation in sediment‐discharge relationship, mild intra‐event hysteretic behaviour and seemingly random erosion incidents. Sediment‐discharge variation is partly formalized by parameter variation as a function of antecedent soil moisture, indicative of a gradual shift from transport‐ to source‐limited behaviour, decreasing soil erodibility and/or decreasing initial flow erosivity and transport capacity with increasing antecedent wetness. The catchment outlet appears to be source‐limited while converging flows with different sediment concentrations, variable erosion processes and/or sporadic entrainment of near‐ or in‐stream sediments gain importance. Phosphorus dynamics are strongly linked to those of sediment. Non‐linearities can be explained by preferential transfer of phosphorus‐rich organic matter at small flows while there is no significant evidence of preferential transfer of phosphorus‐rich mineral fines. Iterating between collecting data, constraining uncertainties and rejecting and improving models is suggested as a consistent framework for understanding soil erosion and phosphorus movement. 相似文献