Global Sensitivity Analysis of environmental models: Convergence and validation

We address two critical choices in Global Sensitivity Analysis (GSA): the choice of the sample size and of the threshold for the identification of insensitive input factors. Guidance to assist users with those two choices is still insufficient. We aim at filling this gap. Firstly, we define criteria to quantify the convergence of sensitivity indices, of ranking and of screening, based on a bootstrap approach. Secondly, we investigate the screening threshold with a quantitative validation procedure for screening results. We apply the proposed methodologies to three hydrological models with varying complexity utilizing three widely-used GSA methods (RSA, Morris, Sobol’). We demonstrate that convergence of screening and ranking can be reached before sensitivity estimates stabilize. Convergence dynamics appear to be case-dependent, which suggests that “fit-for-all” rules for sample sizes should not be used. Other modellers can easily adopt our criteria and procedures for a wide range of GSA methods and cases.     

基于支持向量机的地表水环境质量分类模型

建立了一种基于支持向量机的地表水环境质量分类模型,并将其用于浙江省主要市界交界面的地表水环境质量分类。该模型采用径向基核函数,以一对多方式实现多分类。分别以网格搜索、粒子群优化和遗传算法三种优化方法对支持向量机的控制参数进行寻优。实验表明,采用网格搜索法确定支持向量机控制参数可以得到最好的水质分类结果,分类准确率可达到82%,由此证明以支持向量机对水质进行分类是可行的。     

Mitigating the effects of soil and residue water contents on remotely sensed estimates of crop residue cover

Crop residues on the soil surface decrease soil erosion and increase soil organic carbon and the management of crop residues is an integral part of many conservation tillage systems. Current methods of measuring residue cover are inadequate for characterizing the spatial variability of residue cover over large fields. The objectives of this research were to determine the effects of water content on the remotely sensed estimates of crop residue cover and to propose a method to mitigate the effects of water content on remotely sensed estimates of crop residue cover. Reflectance spectra of crop residues and soils were measured in the lab over the 400-2400 nm wavelength region. Reflectance of scenes with various residue cover fractions and water contents was simulated using a linear mixture model. Additional spectra of scenes with mixtures of crop residues and soil were also acquired in corn, soybean, and wheat fields with different tillage treatments and different water content conditions. Crop residue cover was linearly related to the cellulose absorption index (CAI), which was defined as the relative intensity of an absorption feature near 2100 nm. Water in the crop residue significantly attenuated CAI and changed the slope of the residue cover vs. CAI relationship. Without an appropriate correction, crop residue covers were underestimated as scene water content increased. Spectral vegetation water indices were poorly related to changes in the water contents of crop residues and soils. A new reflectance ratio water index that used the two bands located on the shoulders of the cellulose absorption feature to estimate scene water conditions was proposed and tested with data from corn, soybean, and wheat fields. The ratio water index was used to describe the changes in the slope of crop residue cover vs. CAI and improve the predictions of crop residue cover. These results indicate that spatial and temporal adjustments in the spectral estimates of crop residue cover are possible. Current mutispectral imaging systems will not provide reliable estimates of crop residue cover when scene water content varies. Hyperspectral data are not required, because the three narrow bands that are used for both CAI and the scene moisture correction could be incorporated in advanced multispectral sensors. Thus, regional surveys of soil conservation practices that affect soil carbon dynamics may be feasible using either advanced multispectral or hyperspectral imaging systems.     

Use of environmental sensors and sensor networks to develop water and salinity budgets for seasonal wetland real-time water quality management

Management of river salt loads in a complex and highly regulated river basin such as the San Joaquin River Basin of California presents significant challenges for current Information Technology. Computer-based numerical models are used as a means of simulating hydrologic processes and water quality within the basin and can be useful tools for organizing Basin data in a structured and readily accessible manner. These models can also be used to extend information derived from environmental sensors within existing monitoring networks to areas outside these systems based on similarity factors – since it would be cost prohibitive to collect data for every channel or pollutant source within the Basin. A common feature of all hydrologic and water quality models is the ability to perform mass balances. This paper describes the use of a number of state-of-the-art sensor technologies that have been deployed to obtain water and salinity mass balances for a 60,000 ha tract of seasonally managed wetlands in the San Joaquin River Basin of California. These sensor technologies are being combined with more traditional environmental monitoring techniques to support real-time salinity management (RTSM) in the River Basin. Two of these new technology applications: YSI-Econet (which supports continuous flow and salinity monitoring of surface water deliveries and seasonal wetland drainage); and electromagnetic salinity mapping (a remote sensing technology for mapping soil salinity in the surface soils) – have not previously been reported in the literature. Continuous sensor deployments that experience more widespread use include: weather station sensor arrays – used to estimate wetland pond evaporation and moist soil plant evapotranspiration; high resolution multi-spectral imagery – used to discriminate between and estimate the area of wetland moist soil plant vegetation; and groundwater level sensors – used primarily to estimate seepage losses beneath a wetland pond during flood-up. Important issues associated with quality assurance of continuous data are discussed and the application of a state-of-the-art software product AQUARIUS, which streamlines the process of data error correction and dissemination, is described as an essential element of ensuring successful RTSM implementation in the San Joaquin River Basin.     

Analysis of the quality factor of AlN-actuated micro-resonators in air and liquid

The quality factor (Q) of different modes of self-actuated aluminium nitride beams operated in air and liquid media is analyzed applying different techniques. In air, both optical and electrical techniques are used. In the case of the optical approach, characterization is done with a laser Doppler vibrometer. The values for the Q factors are deduced straight forward from both the frequency spectrum and the transient response, while electrical impedance measurements need a more careful evaluation with two different fitting methods to obtain the Q factor of the vibration modes. In water, only optical measurements, more sensitive than the electrical measurements, could be used to determine the Q factor of selected modes. In addition, the results of finite element model analysis were compared to the experimental data, showing an excellent agreement regarding the modal shape and the resonance frequency of the microresonators.     

Comparing the effects of classification techniques on landscape-level assessments: pixel-based versus object-based classification

Landscape-level assessments, particularly the quantification of forest fragmentation, often involve calculating landscape metrics from classified remotely sensed images. The utility of these derived metrics is often assumed to be dependent on the quality of the classified images. We compared conventional, pixel-based classification and a newer method of object-based classification to determine the effects of these two methods on fragmentation analysis of Cockpit Country, Jamaica, West Indies. Both methods showed similar trends in fragmentation metrics; however, there were significant differences between the methods for the metrics that quantified landscape configuration. The object-based classification allowed for the easy inclusion of roads into the analysis, which produced more accurate maps that showed a significant difference in the size of the largest forest patch. The object-based method also allowed classification of forests to show the location and extent of core forest areas; we were therefore able to identify an area of core forest that had remained consistent over the study period as a significant area for conservation focus. We recommend that the object-based method be the method chosen for landscape analyses, particularly forest-fragmentation studies.     

Protocol for developing ANN models and its application to the assessment of the quality of the ANN model development process in drinking water quality modelling

The application of Artificial Neural Networks (ANNs) in the field of environmental and water resources modelling has become increasingly popular since early 1990s. Despite the recognition of the need for a consistent approach to the development of ANN models and the importance of providing adequate details of the model development process, there is no systematic protocol for the development and documentation of ANN models. In order to address this shortcoming, such a protocol is introduced in this paper. In addition, the protocol is used to critically review the quality of the ANN model development and reporting processes employed in 81 journal papers since 2000 in which ANNs have been used for drinking water quality modelling. The results show that model architecture selection is the best implemented step, while greater focus should be given to input selection considering input independence and model validation considering replicative and structural validity.     

A detailed statistical study on selection of optimum IRS LISS pixel configuration for development of water quality models

Whenever remote sensing data are used in conjunction with in situ measurements for modelling a physical phenomenon, the major problem is in the selection of digital data which are representative of the ground points under consideration. This problem can be solved in most cases, including the present study on water quality modelling, by placing dependence not on a single pixel number of the estimated point in question. The study reports the analyses of different size pixel arrays for date of 11 April 1993 in the form of CCT obtained from NRSA, Hyderabad. In order to select the best pixel array configuration to represent the sample station point on the multi-band image, nested arrays of pixels for 4 bands with 7 different sizes are sampled at 52 different sampling stations in the Gautami-Godavari river estuary where water quality variables had been measured. These seven array sizes, namely three symmetric arrays of sizes: 5 by 5, 3 by 3 and 1 by 1 and 4 non-symmetrical arrays of 2 by 2 with the centre pixel located at different corners of each 2 by 2 arrays are analysed using Analysis of Variance [ANOVA] and t -test. The data bank of 52 by 7 by 4 average pixel values was available for ANOVA and t -test. The results of ANOVA highlight the importance of considering all four IRS bands and each band contains different information regarding physical conditions of the study points, sensor characteristics and water and atmospheric responses. The pixel data are also significantly different at 99 per cent confidence level among sample locations. This indicated that all the four bands have to be considered in developing water quality models. The results of t -test proved that the 5 by 5 and 3 by 3 array sizes are the best among the 7 configurations, but no significant difference is indicated between the two array types. The 3 by 3 window is selected for water quality modelling because it is smaller and involves less computational work.     

Analysis of interpolation algorithms for the missing values in IoT time series: a case of air quality in Taiwan

The Journal of Supercomputing - Missing values are common in the Internet of Things (IoT) environment for various reasons, including regular maintenance or malfunction. In time-series prediction in...     

An open source massively parallel solver for Richards equation: Mechanistic modelling of water fluxes at the watershed scale

In this paper we present a massively parallel open source solver for Richards equation, named the RichardsFOAM solver. This solver has been developed in the framework of the open source generalist computational fluid dynamics tool box OpenFOAM^®  and is capable to deal with large scale problems in both space and time. The source code for RichardsFOAM may be downloaded from the CPC program library website.     

The patchwork problem: effects of sub-pixel scale non-uniformity on the spatially-averaged sensible heat flux

Previous experimental and theoretical studies have examined the possible use of thermal-infrared measurements of surface temperature to estimate sensible heat flux from homogeneous surfaces. In extending the methodology suggested by Lagouarde and McAneney to larger scales, it is necessary to consider the effect of spatial variability. Over a heterogeneous mixture of surfaces, statistical errors are possible due to spatially-correlated changes in windspeed, surface roughness and surface temperature. Errors due to the latter two variables are investigated here at the 1 km² scale of the NOAA AVHRR using two specific case studies. Errors due to correlated variations in windspeed and surface roughness, and windspeed and surface temperature, are also estimated. The results suggest that all these errors are generally negligible if application is restricted to surfaces having a maximum crop height of around I m. Given this qualification,estimates of regional scale sensible heat fluxes seem feasible using spatially-averaged measurements of surface temperature along with ancillary estimates of averaged maximum air temperatures, windspeed and surface roughness.     

Development of quality bounds for time and frequency domain models: application to the Shell distillation column

Statistical confidence bounds are developed for frequency response and step response models estimated from process input-output data using the frequency sampling filter model structure. The frequency domain bound is an extension of earlier work by the authors (Arifin et al., Journal of Process Control, 1995, 5, 71–76) and the time domain bound is a new result. These bounds provide the engineer with a measure of the quality of the estimated model, and therefore an indication of which aspects of the model are reliable and which aspects require further improvement. The Shell distillation column benchmark problem introduced by Cott (Journal of Process Control, 1995, 5, 60–70) is used for illustrative purposes.     

Ex-Stream: A MATLAB program for calculating fluid flux through sediment–water interfaces based on steady and transient temperature profiles

Temperature is a useful environmental tracer for quantifying movement and exchange of water and heat through and near sediment–water interfaces (SWI). Heat tracing involves analyzing temperature time series or profiles from temperature probes deployed in sediments. Ex-Stream is a MATLAB program that brings together two transient and two steady one-dimensional coupled heat and fluid flux analytical models. The program includes a graphical user interface, a detailed user manual, and postprocessing capabilities that enable users to extract fluid fluxes from time-series temperature observations. Program output is written to comma-separated values files, displayed within the MATLAB command window, and may be optionally plotted. The models that are integrated into Ex-Stream can be run collectively, allowing for direct comparison, or individually.     

Improving quality and quantity of contributions: Two models for promoting knowledge exchange with shared databases

Shared databases are used for knowledge exchange in groups. Whether a person is willing to contribute knowledge to a shared database presents a social dilemma: Each group member saves time and energy by not contributing any information to the database and by using the database only to retrieve information which was contributed by others. But if all people use this strategy, then the database will be empty and, hence, useless for every group member. Based on theoretical approaches, two models for fostering the information-sharing behavior of database users are presented. One for enhancing the quality of database contents, and one for enhancing the quantity of those contents. The models take into account the following factors: the kinds of rewards the participants obtain for contributing information, the individual costs associated with this contribution, the prospective metaknowledge about the importance of one’s own information to the others, and the retrospective metaknowledge about how much others contributed to and retrieved from the database. These factors enhance the quantity of database contents as well as their quality.     

A generic database and spatial interface for the application of hydrological and water resource models

The paper discusses a software package that has been designed to enhance the efficiency of applying a range of hydrological and water resource simulation models. The SPATSIM (SPatial and Time Series Information Modeling) system has been developed in Delphi using MapObjects and incorporates a spatial data interface for access to the different types of information commonly associated with water resource analyses. All of the information is stored within database tables (Paradox by default) with generic structures. The structure and components of the system are briefly described and some example applications provided. The discussion identifies some of the criticisms that have been leveled at the software, the approach of the developers to user support and some possible future developments. The conclusions suggest that the development can be considered successful in that it has substantially improved the efficiency of the Institute for Water Research to undertake one of its core functions of hydrological model development and application.     

Pervasive and standalone computing: the perceptual effects of variable multimedia quality

The introduction of multimedia on pervasive and mobile communication devices raises a number of perceptual quality issues; however, limited work has been done examining the three-way interaction between use of equipment, quality of perception and quality of service. Our work measures levels of informational transfer (objective) and user satisfaction (subjective) when users are presented with multimedia video clips at three different frame rates, using four different display devices, simulating variation in participant mobility. Our results will show that variation in frame rate does not impact a user's level of information assimilation, however, does impact a users’ perception of multimedia video ‘quality’. Additionally, increased visual immersion can be used to increase transfer of video information, but can negatively affect the users’ perception of ‘quality’. Finally, we illustrate the significant affect of clip-content on the transfer of video, audio and textual information, placing into doubt the use of purely objective quality definitions when considering multimedia presentations.     

The psychological effects on man of air movement and the colour of his surroundings

The psychological microclimate is a term which is used to describe the specific psychological effects of some environmental agents as well as the psychological effects of other factors of the physical environment (e g, colour of surroundings, etc). This paper considers air motion and colour schemes of space, defines their stress and strain factors, describes the psychological effects - post-strain, and the methodology of their investigation. It further suggests the criteria and limiting and optimum values of the dynamic effect of air (permissible air velocities in interior and exterior environments) and the colour scheme of space (in accordance with the Tektronix standard). In conclusion the paper sums up the possibilities of optimisation of the 'psychological microclimate'.