Long-term Monitoring Network Research Articles

Emulator-assisted reduced-rank ecological data assimilation for nonlinear multivariate dynamical spatio-temporal processes

As ecological data sets increase in spatial and temporal extent with the advent of new remote sensing platforms and long-term monitoring networks, there is increasing interest in forecasting ecological processes. Such forecasts require realistic initial conditions over complete spatial domains. Typically, data sources are incomplete in space, and the processes include complicated dynamical interactions across physical and biological variables. This suggests that data assimilation, whereby observations are fused with mechanistic models, is the most appropriate means of generating complete initial conditions. Often, the mechanistic models used for these procedures are very expensive computationally. We demonstrate a rank-reduced approach for ecological data assimilation whereby the mechanistic model is based on a statistical emulator. Critically, the rank-reduction and emulator construction are linked and, by utilizing a hierarchical framework, uncertainty associated with the dynamical emulator can be accounted for. This provides a so-called “weak-constraint” data assimilation procedure. This approach is demonstrated on a high-dimensional multivariate coupled biogeochemical ocean process.

Assessment of regional change in nitrate concentrations in groundwater in the Central Valley, California, USA, 1950s–2000s

A regional assessment of multi-decadal changes in nitrate concentrations was done using historical data and a spatially stratified non-biased approach. Data were stratified into physiographic subregions on the basis of geomorphology and soils data to represent zones of historical recharge and discharge patterns in the basin. Data were also stratified by depth to represent a shallow zone generally representing domestic drinking-water supplies and a deep zone generally representing public drinking-water supplies. These stratifications were designed to characterize the regional extent of groundwater with common redox and age characteristics, two factors expected to influence changes in nitrate concentrations over time. Overall, increasing trends in nitrate concentrations and the proportion of nitrate concentrations above 5 mg/L were observed in the east fans subregion of the Central Valley. Whereas the west fans subregion has elevated nitrate concentrations, temporal trends were not detected, likely due to the heterogeneous nature of the water quality in this area and geologic sources of nitrate, combined with sparse and uneven data coverage. Generally low nitrate concentrations in the basin subregion are consistent with reduced geochemical conditions resulting from low permeability soils and higher organic content, reflecting the distal portions of alluvial fans and historical groundwater discharge areas. Very small increases in the shallow aquifer in the basin subregion may reflect downgradient movement of high nitrate groundwater from adjacent areas or overlying intensive agricultural inputs. Because of the general lack of regionally extensive long-term monitoring networks, the results from this study highlight the importance of placing studies of trends in water quality into regional context. Earlier work concluded that nitrate concentrations were steadily increasing over time in the eastern San Joaquin Valley, but clearly those trends do not apply to other physiographic subregions within the Central Valley, even where land use and climate are similar.

Enhanced warming over the global subtropical western boundary currents

Subtropical western boundary currents are warm, fast-flowing currents that form on the western side of ocean basins. They carry warm tropical water to the mid-latitudes and vent large amounts of heat and moisture to the atmosphere along their paths, affecting atmospheric jet streams and mid-latitude storms, as well as ocean carbon uptake1, 2, 3, 4. The possibility that these highly energetic currents might change under greenhouse-gas forcing has raised significant concerns5, 6, 7, but detecting such changes is challenging owing to limited observations. Here, using reconstructed sea surface temperature datasets and century-long ocean and atmosphere reanalysis products, we find that the post-1900 surface ocean warming rate over the path of these currents is two to three times faster than the global mean surface ocean warming rate. The accelerated warming is associated with a synchronous poleward shift and/or intensification of global subtropical western boundary currents in conjunction with a systematic change in winds over both hemispheres. This enhanced warming may reduce the ability of the oceans to absorb anthropogenic carbon dioxide over these regions. However, uncertainties in detection and attribution of these warming trends remain, pointing to a need for a long-term monitoring network of the global western boundary currents and their extensions.

Save now, pay later? Multi-period many-objective groundwater monitoring design given systematic model errors and uncertainty

This study demonstrates how many-objective long-term groundwater monitoring (LTGM) network design tradeoffs evolve across multiple management periods given systematic models errors (i.e., predictive bias), groundwater flow-and-transport forecasting uncertainties, and contaminant observation uncertainties. Our analysis utilizes the Adaptive Strategies for Sampling in Space and Time (ASSIST) framework, which is composed of three primary components: (1) bias-aware Ensemble Kalman Filtering, (2) many-objective hierarchical Bayesian optimization, and (3) interactive visual analytics for understanding spatiotemporal network design tradeoffs. A physical aquifer experiment is utilized to develop a severely challenging multi-period observation system simulation experiment (OSSE) that reflects the challenges and decisions faced in monitoring contaminated groundwater systems. The experimental aquifer OSSE shows both the influence and consequences of plume dynamics as well as alternative cost-savings strategies in shaping how LTGM many-objective tradeoffs evolve. Our findings highlight the need to move beyond least cost purely statistical monitoring frameworks to consider many-objective evaluations of LTGM tradeoffs. The ASSIST framework provides a highly flexible approach for measuring the value of observables that simultaneously improves how the data are used to inform decisions.

Quantification of PM<sub>2.5</sub> organic carbon sampling artifacts in US networks

Abstract. Field blanks (bQF) and backup filters (quartz-fiber behind quartz-fiber filter; QBQ) have been adopted by US long-term air quality monitoring networks to estimate PM2.5 organic carbon (OC) sampling artifacts. This study documents bQF and QBQ carbon levels for the: 1) Interagency Monitoring of Protected Visual Environments (IMPROVE); 2) Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]); and 3) Southeastern Aerosol Research and Characterization (SEARCH) networks and examines the similarities/differences associated with network-specific sampling protocols. A higher IMPROVE sample volume and smaller filter deposit area results in PM2.5 areal density (μg/cm2 on filter) 3–11 times those of STN/CSN and SEARCH samples for the same ambient PM2.5 concentrations, thus reducing the relative contribution of sampling artifacts from passive OC adsorption. A relatively short (1–15 min) passive exposure period of STN/CSN and SEARCH bQF OC (0.8–1 μg/cm2) underestimates positive and negative OC artifacts resulting from passive adsorption or evaporation of semi-volatile organic compounds on quartz-fiber filters. This is supported by low STN/CSN and SEARCH bQF levels and lack of temporal or spatial variability among the sites within the networks. With a much longer period, ~7 days of ambient passive exposure, average IMPROVE bQF and QBQ OC are comparable (2.4±0.5 and 3.1±0.8 μg/cm2, respectively) and more than twice levels found in the STN/CSN and SEARCH networks. Sampling artifacts in STN/CSN were estimated from collocated IMPROVE samples based on linear regression. At six of the eight collocated sites in this study, STN/CSN bQFs underestimated OC artifacts by 11–34%. Using a preceding organic denuder in the SEARCH network minimized passive adsorption on QBQ, but OC on QBQ may not be attributed entirely to the negative sampling artifact (e.g., evaporated or volatilized OC from the front filter deposits after sample collection).

Rapid Prototyping for Wildlife and Ecological Monitoring

Wildlife tracking and ecological monitoring are important for scientific monitoring, wildlife rehabilitation, disease control, and sustainable ecological development. Yet technologies for both of them are expensive and not scalable. Also it is important to tune the monitoring system parameters for different species to adapt their behavior and gain the best result of monitoring. In this paper, we propose using wireless sensor networks to build both short term and long term wildlife and ecological monitoring systems. For the short term system, everything used is off-the-shelf and can be easily purchased from the market. We suggest that before establishing a large scale wildlife/ecological monitoring network, it is worthwhile to first spend a short period of time constructing a rapid prototype of the targeted network. Through verifying the correctness of the prototype network, ecologists can find potential problems, avoid total system failure, and use the best-tuned parameters for the long-term monitoring network.

A large atomic chlorine source inferred from mid-continental reactive nitrogen chemistry

Halogen atoms and oxides are highly reactive and can profoundly affect atmospheric composition. Chlorine atoms can decrease the lifetimes of gaseous elemental mercury and hydrocarbons such as the greenhouse gas methane. Chlorine atoms also influence cycles that catalytically destroy or produce tropospheric ozone, a greenhouse gas potentially toxic to plant and animal life. Conversion of inorganic chloride into gaseous chlorine atom precursors within the troposphere is generally considered a coastal or marine air phenomenon. Here we report mid-continental observations of the chlorine atom precursor nitryl chloride at a distance of 1,400 km from the nearest coastline. We observe persistent and significant nitryl chloride production relative to the consumption of its nitrogen oxide precursors. Comparison of these findings to model predictions based on aerosol and precipitation composition data from long-term monitoring networks suggests nitryl chloride production in the contiguous USA alone is at a level similar to previous global estimates for coastal and marine regions. We also suggest that a significant fraction of tropospheric chlorine atoms may arise directly from anthropogenic pollutants.

The design of long-term air quality monitoring networks in urban areas using a spatiotemporal approach

The implementation and maintenance of an air pollution monitoring program can be expensive and time consuming, especially when the aim is for long-term monitoring over a significant area. Consequently, it is essential that sites are optimized to provide the best representative cover while minimizing costs. In the past, there has been a tendency to locate sampling stations at pollution hot-spots. While this is acceptable for determining a maximum potential exposure or identifying the extent of a risk, there are limitations to this approach when assessing the potential impact of any future abatement strategies or determining the level of exposure outside the vicinity. This paper presents an approach in which representative air quality assessments can be undertaken for an urban area using the minimum number of measurement sites. A novel methodology is described that involves site selection to capture the maximum variance in measured pollutants, while minimizing spatiotemporal autocorrelation between the selected sites. A case study is presented for Yazd, Iran. Overall, the results show that the proposed methodology can be effective and enable the long-term monitoring of air pollution to be undertaken on a cost-effective basis in urban areas. In addition, there is the potential for the methodology to be utilized for other forms of pollution (e.g., water, soil, and noise).

The future of soils and land use in the UK: Soil systems for the provision of land-based ecosystem services

Historically, soils have always underpinned civilisation. Their role is fundamental to the provision of food and water, along with a wide range of ecosystem goods and services. Soils are arguably the most complex systems on Earth, and are intimately linked to human security and the integrity of the wider environment. In this paper we propose 18 ecosystem services that are critical for soils and land use in the UK. Soils are extremely heterogeneous and not all soils can fulfil the full spectrum of services required for the future of the UK, so there is a need to protect their multifunctional attributes in order to preserve national and international natural capital. There are concerns that anthropogenically induced changes in land use or management will result in soils not being utilised to provide the functions to which they are best suited. For example, soils primarily suited for food supply may be given over to provide a platform for construction. This is an all-pervading and recurring concern and highlights the importance of critical decisions, thresholds and potential ‘tipping points’. Once critical soil functions are lost they are irrecoverable, potentially for millennia, representing a loss of resource that is fundamental to the UK's national livelihood and well-being. Pressures from changes in climate and to the Earth system will bring about complex and systematic change to soils and their abilities to provide essential functions. We therefore recommend national needs for ensuring the sustainability for soils and future land use in the UK. They are to maintain the long-term base for soil science through education and intellectual investment, including communication of the value of soils and land as natural capital; to manage soil resources so that multi-functionality prevails and critical tipping points are avoided; to audit the national soil resource through soil mapping; preparation of appropriate databases and provision of long-term monitoring networks and observatories; and to synthesise adaptable predictive frameworks for soil system science through integrated modelling.

Stream Discharge and Riparian Land Use Influence In-Stream Concentrations and Loads of Phosphorus from Central Plains Watersheds

Total annual nutrient loads are a function of both watershed characteristics and the magnitude of nutrient mobilizing events. We investigated linkages among land cover, discharge and total phosphorus (TP) concentrations, and loads in 25 Kansas streams. Stream monitoring locations were selected from the Kansas Department of Health and Environment stream chemistry long-term monitoring network sites at or near U.S. Geological Survey stream gauges. We linked each sample with concurrent discharge data to improve our ability to estimate TP concentrations and loads across the full range of possible flow conditions. Median TP concentration was strongly linked (R (2) = 76%) to the presence of cropland in the riparian zones of the mostly perennial streams. At baseflow, discharge data did not improve prediction of TP, but at high flows discharge was strongly linked to concentration (a threshold response occurred). Our data suggest that on average 88% of the total load occurred during the 10% of the time with the greatest discharge. Modeled reductions in peak discharges, representing increased hydrologic retention, predicted greater decreases in total annual loads than reductions of ambient concentrations because high discharge and elevated phosphorus concentrations had multiplicative effects. No measure of land use provided significant predictive power for concentrations when discharge was elevated or for concentration rise rates under increasing discharge. These results suggest that reductions of baseflow concentrations of TP in streams without wastewater dischargers may be managed by reductions of cropland uses in the riparian corridor. Additional measures may be needed to manage TP annual loads, due to the large percentage of the TP load occurring during a few high-flow events each year.

Fault tree analysis for data-loss in long-term monitoring networks

Prevention of data-loss is an important aspect in the design as well as the operational phase of monitoring networks since data-loss can seriously limit intended information yield. In the literature limited attention has been paid to the origin of unreliable or doubtful data from monitoring networks. Better understanding of causes of data-loss points out effective solutions to increase data yield. This paper introduces FTA as a diagnostic tool to systematically deduce causes of data-loss in long-term monitoring networks in urban drainage systems. In order to illustrate the effectiveness of FTA, a fault tree is developed for a monitoring network and FTA is applied to analyze the data yield of a UV/VIS submersible spectrophotometer. Although some of the causes of data-loss cannot be recovered because the historical database of metadata has been updated infrequently, the example points out that FTA still is a powerful tool to analyze the causes of data-loss and provides useful information on effective data-loss prevention.

Assessment of frozen-ground conditions for engineering geology along the Qinghai–Tibet highway and railway, China

The Qinghai–Tibet Highway and Railway (the Corridor) across the Qinghai–Tibet Plateau traverses 670 km of permafrost and seasonally frozen-ground in the interior of the Plateau, which is sensitive to climatic and anthropogenic environmental changes. The frozen-ground conditions for engineering geology along the Corridor is complicated by the variability in the near-surface lithology, and the mosaic presence of warm permafrost and talik in a periglacial environment. Differential settlement is the major frost-effect problem encountered over permafrost areas. The traditional classification of frozen ground based on the areal distribution of permafrost is too generalized for engineering purposes and a more refined classification is necessary for engineering design and construction. A proposed classification of 51 zones, sub-zones, and sections of frozen ground has been widely adopted for the design and construction of foundations in the portion of the Corridor studied. The mean annual ground temperature (MAGT), near-surface soil types and moisture content, and active faults and topography are most commonly the primary controlling factors in this classification. However, other factors, such as local microreliefs, drainage conditions, and snow and vegetation covers also exert important influences on the features of frozen ground. About 60% of the total length of the Corridor studied possesses reasonably good frozen-ground conditions, which do not need special mitigative measures for frost hazards. However, other sections, such as warm and ice-rich or -saturated permafrost, particularly in the sections in wetlands, ground improvement measures such as elevated land bridges and passive or proactive cooling techniques need to be applied to ensure the long-term stability of thermally unstable, thick permafrost subsoils, and/or refill with non-frost-susceptible soils. Due to the long-history of the construction and management of the Corridor by various government departments, adverse impacts of construction and operation on the permafrost environment have been resulted. It is recommended that an integrated, executable plan for the routing of major construction projects within this transportation corridor be established and long-term monitoring networks installed for evaluating and mitigating the impact from anthropogenic and climatic changes in frozen-ground conditions.

Tratamento estatístico dos parâmetros da qualidade das águas da bacia do alto curso do Rio das Velhas

Water quality was monitored at the upper course of the Rio das Velhas, a major tributary of the Sao Francisco basin located in the state of Minas Gerais, over an extension of 108 km from its source up to the limits with the Sabara district. Monitoring was done at 37 different sites over a period of 2 years (2003-2004) for 39 parameters. Multivariate statistical techniques were applied to interpret the large water-quality data set and to establish an optimal long-term monitoring network. Cluster analysis separated the sampling sites into groups of similarity, and also indicated the stations investigated for correlation and recommended to be removed from the monitoring network. Principal component analysis identified four components, which are responsible for the data structure explaining 80% of the total variance of the data. The principal parameters are characterized as due to mining activities and domestic sewage. Significant data reduction was achieved.

Optimal groundwater monitoring design using an ant colony optimization paradigm

Groundwater long-term monitoring (LTM) is required to assess the performance of groundwater remediation and human being health risk at post-closure sites where groundwater contaminants are still present. The large number of sampling locations can make the LTM costly, especially since LTM may be required over several decades. An optimization algorithm based on the ant colony optimization (ACO) paradigm is developed to minimize the overall data loss due to fewer sampling locations for a given number of monitoring wells. The ACO method is inspired by the ability of an ant colony to identify the shortest route between their nest and a food source. The developed ACO-LTM algorithm is applied to a field site with an existing 30-well LTM network. When compared to the results identified through complete enumeration, the ACO-LTM solutions are globally optimal for the cases with 21 to 27 remaining wells. Results from the developed ACO-LTM algorithm provide a proof-of-concept for the application of the general ACO analogy to the groundwater LTM sampling location optimization problem. A major contribution of this work is the successful development of an efficient and effective stochastic search algorithm for solving the LTM optimization problem based on the ACO paradigm.

Multicriteria Relocation Analysis of an Off-site Radioactive Monitoring Network for a Nuclear Power Plant

Due to increasing environmental consciousness in most countries, every utility that owns a commercial nuclear power plant has been required to have both an on-site and off-site emergency response plan since the 1980s. A radiation monitoring network, viewed as part of the emergency response plan, can provide information regarding the radiation dosage emitted from a nuclear power plant in a regular operational period and/or abnormal measurements in an emergency event. Such monitoring information might help field operators and decision-makers to provide accurate responses or make decisions to protect the public health and safety. This study aims to conduct an integrated simulation and optimization analysis looking for the relocation strategy of a long-term regular off-site monitoring network at a nuclear power plant. The planning goal is to downsize the current monitoring network but maintain its monitoring capacity as much as possible. The monitoring sensors considered in this study include the thermoluminescence dosimetry (TLD) and air sampling system (AP) simultaneously. It is designed for detecting the radionuclide accumulative concentration, the frequency of violation, and the possible population affected by a long-term impact in the surrounding area regularly while it can also be used in an accidental release event. With the aid of the calibrated Industrial Source Complex-Plume Rise Model Enhancements (ISC-PRIME) simulation model to track down the possible radionuclide diffusion, dispersion, transport, and transformation process in the atmospheric environment, a multiobjective evaluation process can be applied to achieve the screening of monitoring stations for the nuclear power plant located at Hengchun Peninsula, South Taiwan. To account for multiple objectives, this study calculated preference weights to linearly combine objective functions leading to decision-making with exposure assessment in an optimization context. Final suggestions should be useful for narrowing the set of scenarios that decision-makers need to consider in this relocation process.

Developing a Long‐Term Monitoring Network Under Uncertain Flowpaths

A long-term monitoring well network is developed using complementary and simple approaches in conjunction with a stochastic ground water flow and transport model. The development is illustrated for a case study of a U.S. nuclear testing site (Shoal) that is undergoing environmental restoration. The network design builds on three different, yet complementary, tools for locating the monitoring wells with a main objective of detection monitoring. The first tool is applied to select potential siting horizons where monitoring wells could be located. The second tool is used to place monitoring wells in locations with high success probability. The success here is defined as the detection of migrating stochastic plumes before a certain mass percentage reaches a compliance boundary. The third tool is used to analyze detection efficiency of multiple combinations of three wells. Seventy-six different three-well networks are selected from 20 candidate locations and are evaluated for detection efficiency. From the 76 networks analyzed, 28 attain detection efficiency close to or above 70%. The results of the different analyses provide multiple alternatives for the locations of the three wells, which will become part of the long-term monitoring network at Shoal. A number of combinations are equally good, and the final choice will depend on practical considerations and future agreements between model sponsor and regulators.

Optimizing groundwater long‐term monitoring networks using Delaunay triangulation spatial analysis techniques

AbstractGroundwater long‐term monitoring (LTM) is a costly activity required at most subsurface remediation sites. Many existing LTM networks need to be optimized to reflect changes in site conditions and to increase their effectiveness in defining the plume. A spatial analysis method using Delaunay triangulation techniques was developed to eliminate redundant monitoring points and to locate new wells where additional data are needed. This method uses Delaunay triangulation of the monitoring network for site discretization and assesses the concentration estimation error at each monitoring location to judge its relative contribution to the spatial plume characterization. Locations where the concentration estimation error is small are considered redundant and become candidates for elimination. New monitoring locations are identified where the projected concentration estimation errors are high. Tests comparing the Delaunay method to a fate and transport analytical model illustrated the attributes and effectiveness of the method. Application to a benzene plume site demonstrated that results from Delaunay triangulation agree well with geostatistical approaches. Although the method is relatively less accurate, and lacks the resolution obtained with the geostatistical approach, it is computationally efficient and simple to implement by non‐statisticians. Copyright © 2005 John Wiley & Sons, Ltd.

Historical Overview of Permafrost Studies in China

Although soil freeze/thaw phenomena were reported centuries ago in the historical Chinese literature, systematic study of permafrost in China started in the 1950s. Permafrost research in China has been related to the exploration for and economic development of natural resources. Intensive investigations for several decades culminated in 2000 in the publication of a detailed map of geocryological regionalization and classification. From this map, it is estimated that permafrost covers approximately 23% of the country. About 80% of China's permafrost is mountain permafrost. China contains about 74.5% of the mountain permafrost area of the northern hemisphere. Since the early 1960s, researchers in China have conducted numerous field campaigns to determine permafrost and ground-ice distribution. A comprehensive ground-based and long-term monitoring network has been established on the Tibetan Plateau and in northeastern China. The State Key Laboratory of Frozen Soil Engineering (SKLFSE) was established in 1991 and is open to national and international engineers and scientists to conduct related studies and experiments. Numerous field and laboratory experiments, as well as numerical modeling, have been conducted to meet the requirements for industrial design, construction, and operation in permafrost regions. Rescuing, archiving, and distributing historical permafrost data would greatly aid the ability of scientists to assess long-term changes in permafrost and its potential influence on the natural and engineered environment. Chinese geocryologists and engineers are facing new challenges with the construction and future operation of the Qinghai-Xizang railroad that will cross 550 km of permafrost on the Tibetan Plateau.

Reducing Spatial Sampling in Long-Term Groundwater Monitoring Networks Using Ant Colony Optimization

Groundwater long-term monitoring (LTM) is required to assess human health and environmental risk of residual contaminants after active groundwater remediation activities are completed. However, LTM can be costly because of the large number of sampling locations that exist at a site from previous site characterization and remediation activities. The cost of LTM may be reduced by identifying redundant sampling locations. However, care must be taken so that the elimination of specific individual wells from the monitoring network does not result in unacceptable levels of data loss and errors. An ant colony optimization (ACO) algorithm is proposed to identify optimal sampling networks that minimize the number of monitoring locations while maintaining the overall data loss below a given threshold. ACO is inspired by the ability of an ant colony to identify the shortest route between its nest and a food source through indirect communication and positive feedback. Metrics for quantifying well redundancy and overall data loss after optimization are quantified and used in the ACO heuristics. To demonstrate its effectiveness, the ACO developed for LTM optimization is applied to a case study with 30 existing monitoring wells. The LTM optimization problem was solved using different data loss thresholds to identify solutions with 27 to 21 wells remaining in the LTM network. Contour mapping of the contaminant plume using the remaining wells show that the ACO solutions are effective and practical. These results demonstrated that ACO is a promising method for solving LTM optimization problems.

Reducing Spatial Sampling in Long-Term Groundwater Monitoring Networks Using Ant Colony Optimization

Reducing Spatial Sampling in Long-Term Groundwater Monitoring Networks Using Ant Colony Optimization