Characterization of permeability and porosity from nanosensor observations

In this paper, we investigate the information content in “nanosensors” with limited functionality that might be injected into a reservoir or an aquifer to provide information on the spatial distribution of properties. The two types of sensors that we consider are sensors that can potentially measure pressure at various times during transport, and sensors can be located in space by perturbations in electrical, magnetic, or acoustic properties. The intent of the study is to determine the resolution of estimates of properties that can be obtained from various combinations of sensors, various frequencies of observations, and various specifications on sensor precision.Our goal is to investigate the resolution of model estimates for various types of measurements. For this, we compute linearized estimates of the sensitivity of the observations to the porosity and permeability assuming gaussian errors in the pressure and location observations. Because the flow is one-dimensional and incompressible, observations of location are sensitive to the porosity between the injection location and the sensor location, while the location of particles is sensitive to the effective permeability over the entire interval from injector to producer. When only the pressure is measured but the location of the sensor is unknown, as might be the situation for a threshold sensor, the pressure is sensitive to both permeability and porosity only in the region between the injector and sensor.In addition to the linearized sensitivity and resolution analyses, Markov chain Monte Carlo sampling is used to estimate the posterior pdf for model variables for realistic (non-Gaussian) likelihood models. For a Markov chain of length one million samples approximately 200-500 independent samples are generated for uncertainty and resolution assessment. Results from the MCMC analysis are not in conflict with the linearized analysis.     

深圳市龙岗中心城岩溶塌陷光纤传感监测研究

岩溶塌陷具有的突发性、隐蔽性、不确定性,使其监测、预警预报问题一直未解决。通过多年的研发,光纤传感器监测技术已成为当今最为先进的岩土变形现场监测技术,特别是BOTDR技术,它的分布式、长距离、远程实时监控以及光纤耐久性好的特点正好弥补了传统监测技术的不足。目前光纤传感技术在岩溶塌陷（沉陷）灾害的监测上开展工作较少,本次工作主要目的为利用光纤传感技术实时监测岩溶塌陷。     

Short-term variability of suspended sediment and phytoplankton in Tampa Bay,Florida: Observations from a coastal oceanographic tower and ocean color satellites

We examined short-term phytoplankton and sediment dynamics in Tampa Bay with data collected between 8 December 2004 and 17 January 2005 from optical, oceanographic, and meteorological sensors mounted on a coastal oceanographic tower and from satellite remote sensing. Baseline phytoplankton (chlorophyll-a, Chl) and sediment concentrations (particle backscattering coefficient at 532 nm, bbp(532)) were of the order of 3.7 mg m⁻³ and 0.07 m⁻¹, respectively, during the study period. Both showed large fluctuations dominated by semidiurnal and diurnal frequencies associated with tidal forcing. Three strong wind events (hourly averaged wind speed >8.0 m s⁻¹) generated critical bottom shear stress of >0.2 Pa and suspended bottom sediments that were clearly observed in concurrent MODIS satellite imagery. In addition, strong tidal current or swells could also suspend sediments in the lower Bay. Sediments remained suspended in the water column for 2–3 days after the wind events. Moderate Chl increases were observed after sediment resuspension with a lag time of ˜1–2 days, probably due to release of bottom nutrients and optimal light conditions associated with sediment resuspension and settling. Two large increases in Chl with one Chl > 12.0 mg m⁻³ over ˜2 days, were observed at neap tides. For the study site and period, because of the high temporal variability in phytoplankton and sediment concentrations, a monthly snapshot can be different by −50% to 200% from the monthly “mean” chlorophyll and sediment conditions. The combination of high-frequency observations from automated sensors and synoptic satellite imagery, when available, is an excellent complement to limited field surveys to study and monitor water quality parameters in estuarine environments.     

Soil moisture dynamics at high temporal resolution in a semiarid Mediterranean watershed with scattered tree cover

Subsurface water flows play a key role in the distribution of water and solutes and thereby in the water availability for plants. However, the characterization of different flow processes (i.e. matrix and preferential flow), the frequency and factors that cause them, is relatively rare. This characterization enables a better understanding of spatio‐temporal variability of water resources and allows for the design of models to be improved. Using a method based on the time derivative of soil moisture variation known as maximum wetting slope, types of soil wetting processes were classified and quantified. For this, capacitance sensors, which registered the volumetric water content at high temporal resolution (30 min) for more than two hydrological years, were installed at different depths and placed in soil moisture stations with different vegetation covers, lithology and topographic position. Results indicated that there is a general behaviour or pattern of soil moisture dynamics in the catchment with a dominant occurrence of slower soil wetting processes (>50%), caused by matrix flows, and a low occurrence of those faster processes (<30%), originated by preferential flows. Nevertheless, when the total volume of water is considered, preferential flow becomes the dominant process, so that the ecological role of both flow types becomes prominent in water‐limited environments. Statistical multivariate analyses based on data‐mining techniques proved that although both flow types depend on variables associated with precipitation and antecedent soil moisture conditions, faster soil wetting processes are mainly related to variables such as rainfall intensity and topography, while slower soil wetting processes are related to flow velocity, soils or vegetation. Copyright © 2015 John Wiley & Sons, Ltd.     

Continuous field estimation of dissolved organic carbon concentration and biochemical oxygen demand using dual‐wavelength fluorescence,turbidity and temperature

Dissolved organic matter (DOM) quality and quantity is not measured routinely in‐situ limiting our ability to quantify DOM process dynamics. This is problematic given legislative obligations to determine event based variability; however, recent advances in field deployable optical sensing technology provide the opportunity to address this problem. In this paper, we outline a new approach for in‐situ quantification of DOM quantity (Dissolved Organic Carbon: DOC) and a component of quality (Biochemical Oxygen Demand: BOD) using a multi‐wavelength, through‐flow fluorescence sensor. The sensor measured tryptophan‐like (Peak T) and humic‐like (Peak C) fluorescence, alongside water temperature and turbidity. Laboratory derived coefficients were developed to compensate for thermal quenching and turbidity interference (i.e., light attenuation and scattering). Field tests were undertaken on an urban river with ageing wastewater and stormwater infrastructure (Bourn Brook; Birmingham, UK). Sensor output was validated against laboratory determinations of DOC and BOD collected by discrete grab sampling during baseflow and stormflow conditions. Data driven regression models were then compared to laboratory correction methods. A combination of temperature and turbidity compensated Peak T and Peak C was found to be a good predictor of DOC concentration (R² = 0.92). Conversely, using temperature and turbidity correction coefficients provided low predictive power for BOD (R² = 0.46 and R² = 0.51, for Peak C and T, respectively). For this study system, turbidity appeared to be a reasonable proxy for BOD, R² = 0.86. However, a linear mixed effect model with temperature compensated Peak T and turbidity provided a robust BOD prediction (R² = 0.95). These findings indicate that with careful initial calibration, multi‐wavelength fluorescence, coupled with turbidity, and temperature provides a feasible proxy for continuous, in‐situ measurement of DOC concentration and BOD. This approach represents a cost effective monitoring solution, particularly when compared to UV – absorbance sensors and DOC analysers, and could be readily adopted for research and industrial applications.     

热液喷口探测化学传感器的研制及应用*

海底热液喷口周围的水体具有显著的浊度和化学组分异常, 是寻找热液喷口的重要标志。文章提出了一种海底热液喷口的探测技术方法, 设计了低功耗化学传感器。该化学传感器可搭载在相关平台, 实时探测水体的Eh、H₂S、pH及CO₃^2-等电位值, 结合浊度异常, 可以推断热液喷口的位置。在西南印度洋中脊海试结果表明, 该化学传感器可有效探测由热液活动产生的水体异常, 是一种探测海底热液喷口的有效技术。     

Advances in active fire detection using a multi-temporal method for next-generation geostationary satellite data

ABSTRACT

A vital component of fire detection from remote sensors is the accurate estimation of the background temperature of an area in fire's absence, assisting in identification and attribution of fire activity. New geostationary sensors increase the data available to describe background temperature in the temporal domain. Broad area methods to extract the expected diurnal cycle of a pixel using this temporally rich data have shown potential for use in fire detection. This paper describes an application of a method for priming diurnal temperature fitting of imagery from the Advanced Himawari Imager. The BAT method is used to provide training data for temperature fitting of target pixels, to which thresholds are applied to detect thermal anomalies in 4?μm imagery over part of Australia. Results show the method detects positive thermal anomalies with respect to the diurnal model in up to 99% of cases where fires are also detected by Low Earth Orbiting (LEO) satellite active fire products. In absence of LEO active fire detection, but where a burned area product recorded fire-induced change, this method also detected anomalous activity in up to 75% of cases. Potential improvements in detection time of up to 6?h over LEO products are also demonstrated.     

A methodology for the performance evaluation of low-cost accelerometer and magnetometer sensors in geomatics applications

This paper presents a methodology and its software implementation for the performance evaluation of low-cost accelerometer and magnetometer sensors for use in geomatics applications. A known mathematical calibration model has been adopted. The method was completed with statistical methodologies for adjusting observations and has been extended to calculate accuracies for the attitude, heading, and tilt angles estimation that are of interest to geomatics applications. The evaluation method consists of two stages. First, the evaluation method reviews the total magnitude of acceleration or the strength of the magnetic field. Second, the evaluation is more detailed and concerns the determination of mathematical parameters that describe both accelerometer and magnetometer working model. A software tool that implements the evaluation model has been developed and is applied both in accelerometer and magnetometer measurement data-sets acquired from a low-cost sensor system.     

多传感器数据融合与航迹预测

本文是用滤波估计的方法对多传感器数据进行融合.在误差处理方面应用多元方差分析方法来消除各雷达测量数据的偏差,最终预测信号在短期内的轨迹.该方法简单、精度高、可信度强.