Academic literature on the topic 'Groundwater quality processes and contaminated land assessment'

Abstract In Bantul, Southern Yogyakarta, groundwater is the main source of domestic water needs. Therefore, knowing the hydrogeochemistry of groundwater is crucial in order to manage a sustainable groundwater resource. To characterize the compelling geochemical processes that control the groundwater chemistry, further hydrogeochemical examinations were directed in the area. Thirty groundwater samples were collected from shallow dug wells during the early dry season (April 2021). Sampling procedures and chemical analysis were carried out as per standard methods with secondary data obtained in 2006. The geochemical evaluations were depicted using several graphical plots dependent on the ionic constituents, hydrochemical facies, and controlling factors of groundwater quality. Two major hydrochemical facies were identified: alkaline-earth water with higher alkali; bicarbonate predominated (62%) and alkaline-earth water; bicarbonate predominated (32%). Weathering of silicate minerals occurs in 70% of recent samples and predominantly regulates major ion chemistry such as calcium, magnesium, sodium, and potassium. Chloro-alkaline indices 1,2 values signify that there are two potential rock-water interaction processes in the study region, namely the ion exchange and reverse ion exchange. Concentrations of nitrate, sulfate, and chloride indicate that the water chemistry has not been heavily contaminated by the land use in the area and is still mainly controlled by geogenic processes rather than anthropogenic activities.

Nitrates are one of the most common groundwater contaminants and they come from different sources. The paper presents a study of groundwater quality at Varaždin wellfield in the north part of Croatia. The nitrate concentration at this location has been above the maximum allowed concentration for several decades, which has made the opening of new wellfields costly. Based on the previously developed groundwater flow model, a model that covers the narrow area of the wellfield is developed. The influential zone of the observed wellfield in working conditions is determined. Based on the developed model, the sources of nitrate pollution are located, which can be generally divided into non-point and point sources. Considering the time of groundwater retention in the horizontal flow, it is concluded that the water protection zones are marked following the applicable ordinance. Based on the developed groundwater flow model at the observed wellfield, a simulation of nitrate pollution propagation by advection and dispersion processes is performed. The simulation results point out the location of the poultry landfill as the largest source of nitrate pollution. However, poultry farms, which are located in the influence area of the wellfield, also contribute significantly to the nitrate concentration at the wellfield.

Thriving of the society in Zhengzhou city and development of its economy needs scientific and practical solutions of two main problems; natural water shortage and pollution. It is essential to assess the groundwater quality in order to confirm public safety in Zhengzhou and to reduce contamination in there. Fuzzy Synthetic evaluation was applied to delineate the extent of groundwater contamination in Zhengzhou. Assessment of shallow groundwater results concluded that the first three grades of Chinese water quality standards are 91%, whereas the fourth and fifth grades constitute 9% of it. For the deep water quality, the first two grades are 94% and 6%. It is deduced that part of the shallow groundwater quality is effectively contaminated. Contamination disappears going downward into the deep water. Cluster analysis show exactly same deduction. Fuzzy synthetic evaluation results (using Geographic Information System) were employed to assess the groundwater flow direction around the surveyed wells. It is concluded that infiltration of upstream industrial groundwater is probable into the deep confined groundwater

Abstract. Climate and land use change (global change) impacts on groundwater systems cannot be studied in isolation, as various and complex interactions in the hydrological cycle take part. Land-use and land-cover (LULC) changes have a great impact on the water cycle and contaminant production and transport. Groundwater flow and storage are changing in response not only to climatic changes but also to human impacts on land uses and demands (global change). Changes in future climate and land uses will alter the hydrologic cycles and subsequently impact the quantity and quality of regional water systems. Predicting the behavior of recharge and discharge conditions under future climatic and land use changes is essential for integrated water management and adaptation. In the Mancha Oriental system in Spain, in the last decades the transformation from dry to irrigated lands has led to a significant drop of the groundwater table in one of the largest groundwater bodies in Spain, with the consequent effect on stream-aquifer interaction in the connected Jucar River. Streamflow depletion is compromising the related ecosystems and the supply to the downstream demands, provoking a complex management issue. The intense use of fertilizer in agriculture is also leading to locally high groundwater nitrate concentrations. Understanding the spatial and temporal distribution of water availability and water quality is essential for a proper management of the system. In this paper we analyze the potential impact of climate and land use change in the system by using an integrated modelling framework consisting of the sequentially coupling of a watershed agriculturally-based hydrological model (SWAT) with the ground-water model MODFLOW and mass-transport model MT3D. SWAT model outputs (mainly groundwater recharge and pumping, considering new irrigation needs under changing ET and precipitation) are used as MODFLOW inputs to simulate changes in groundwater flow and storage and impacts on stream-aquifer interaction. SWAT and MODFLOW outputs (nitrate loads from SWAT, groundwater velocity field from MODFLOW) are used as MT3D inputs for assessing the fate and transport of nitrate leached from the topsoil. Results on river discharge, crop yields, groundwater levels and groundwater nitrate concentrations obtained from simulation fit well to the observed values. Three climate change scenarios have been considered, corresponding to 3 different GCMs for emission scenario A1B, covering the control period, and short, medium and long-term future periods. A multi-temporal analysis of LULC change was carried out, helped by the study of historical trends by remote sensing images and key driving forces to explain LULC transitions. Markov chains and European scenarios and projections have been used to quantify trends in the future. The cellular automata technique was applied for stochastic modeling future LULC maps. The results show the sensitivity of groundwater quantity and quality (nitrate pollution) to climate and land use changes, and the need to implement adaptation measures in order to prevent further groundwater level declines and increasing nitrate concentrations. The sequential modelling chain has been proved to be a valuable assessment and management tool for supporting the development of sustainable management strategies.

The aim of this study was to evaluate the quality and hydrochemical characteristics of urban groundwater in Urmia City, northwest of Iran. In order, 59 groundwater samples were collected and analyzed for various anions and cations. Result shows that, mineral weathering, ion exchange and anthropogenic activity are the main hydrochemical processes controlling urban groundwater chemistry. The evaluation of groundwater geochemistry in the flow path beneath the urban area shows that, due to land use changes, the hydrochemical change occurs predominantly in electrical conductivity (EC), Cl− and NO3–. The EC is increased in the direction of groundwater flow and in the last decade in industrial areas. According to the groundwater quality index values, most of the samples fit into the good quality class and samples with poor quality are located in the old residential, parks and agricultural areas of the city. The calculation of the irrigation water quality indices (Na%, sodium adsorption ratio, permeability index, residual sodium carbonate), and industrial water quality indices (Ryznar stability index, Langelier saturation index, Larson–Skold, Puckorius scaling index) indicated that the quality of water for irrigation purposes could be classified in the excellent to permissible categories. However, as for the industrial uses, the results also revealed that most of the samples could be classified in the aggressive and very aggressive categories.

Groundwater quality is substantial for social and economic activities in Greece since the majority of the cultivated land is irrigated by water abstracted from aquifers, via a large number of wells and boreholes. The main sources of groundwater pollution are the fertilizers used in agriculture, and the disposal of untreated wastewater from domestic and industrial use. The plain part of Almopia basin, North Greece, is a rural area with intense agricultural activities (including livestock), without significant industrial activity or urban centers. Mild touristic activity has been developed during the last decades in the area of Loutraki, due to the exploitation of the local geothermal field (Pozar springs) for balneotherapy. The aim of this paper is to evaluate the groundwater quality using conventional statistical methods, as well as to employ multivariate statistical methods (factor analysis, cluster analysis) in order to identify the main hydrogeological processes or human activities that affect and determine the water character. The area was selected because of the extended cultivating activities that take place within its boundaries and the availability of adequate data. According to the results of the implemented research, the groundwater samples are of good quality, whereas the chemical composition is mainly formed by the interaction between the water and the geological formations.

The continuous intake of contaminated drinking water causes serious issues for human health. In order to estimate the suitability of groundwater for drinking and irrigation, and also conduct human risk assessments of various groups of people, a total of 43 sample locations in the semi-arid southern part of India were selected based on population density, and we collected and analyzed groundwater from the locations for major anions and cations. The present study’s novelty is integrating hydrochemical analysis with the entropy water quality index (EWQI), nitrate pollution index (NPI) and human health risk assessment. The results of the EWQI revealed that 44.19% of the sample locations need to be treated before consumption. About 37.20% of the study region has a high concentration of nitrate in the groundwater. NPI revealed that 41.86% of the samples had moderate or significant pollution levels. The non-carcinogenic risk evaluation showed that 6–12-year-old children are at a higher risk than teenagers, adults and elderly people in the study area. The natural sources of nitrate and other contamination of groundwater are rock–water interaction, weathering of rock, dissolution of carbonate minerals and evaporation processes, and the anthropogenic sources are the decomposition of organic substances in dumping yards, uncovered septic tanks and human and animal waste. The results suggest taking mitigation measures to reduce the contamination and improve the sustainable planning of groundwater management.

Landfills are one of the groundwater pollution sources in Rwanda. Physical and chemical analyses of water samples were carried out to assure the magnitude of Nduba Landfill on ground water quality. Laboratory tests were conducted to get the results which helped us to study the assessment of leachate effect and to propose mitigation measures of Nduba landfill. The results showed that most of water were contaminated, where concentration of most physical and chemical parameters were above acceptable standard levels required by local and international standards for potable. The analytical results of leachates samples (Cu: 38.5 mg/L, Mn: 13.075mg/l, Zn:15mg/l, TP:4525mg/l, pH:8.52µS/cm, COD:7100mg/l, BOD:182.1mg/l, TN:5mg/l and Fe: 43.025 mg/L) showed that heavy metals are leached out from the MSW. The analytical results of groundwater from the wells located in the vicinity of Nduba landfill site (Cu: 2 mg/L, Zn:3.5-5.5mg/l, SO42-: 250-275mg/l, NO3-: 55-67.5mg/l,NH4+:1.5-2.25mg/l, COD: 39-53.4mg/l, Fe: 1.75-4.25 mg/L, Turbidity: 4.03-4.32NTU, pH:5.31-5.73µS/cm, Temperature: 21°C and BOD:20.7-21.6mg/l) compared to the World Health Organization standard (Cu:0.1mg/L,Fe:0.3mg/L,Zn:5mg/l,SO42-:200mg/l,NO3-:50mg/l,NH4+:1.5mg/l,Turbidity:<5.0 NTU and pH:6.5-9.2µS/cm) revealed that groundwater from the wells located in the vicinity of Nduba landfill site requires further physical chemical treatment to ensure their suitability for human consumption as the levels of some water quality parameters exceeded the EPA guidelines for drinking water. Designing a sanitary landfill was recommended to avoid effects of leachate on environment.

Natural and anthropogenic causes jointly lead to land degradation and eventually to desertification, which occurs in arid, semiarid, and dry subhumid areas. Furthermore, extended drought periods may cause soil exposure and erosion, land degradation and, finally, desertification. Several climatic, geological, hydrological, physiographic, biological, as well as human factors contribute to desertification. This paper presents a methodological procedure for the quantitative classification of desertification severity over a watershed with degraded groundwater resources. It starts with drought assessment using Standardized Precipitation Index (SPI), based on gridded satellite-based precipitation data (taken from the CHIRPS database), then erosion potential is assessed through modeling. The groundwater levels are estimated with the use of a simulation model and the groundwater quality components of desertification, based on scattered data, are interpolated with the use of geostatistical tools. Finally, the combination of the desertification severity components leads to the final mapping of desertification severity classification.

Despite being a finite resource, both the quality and quantity of groundwater are under tremendous pressure due to rapid global changes, viz. population growth, land-use/land-cover changes (LULC), and climate change. The 6th Sustainable Development Goal (SDG) aims to “Ensure availability and sustainable management of water and sanitation for all”. One of the most significant dimensions of the SDG agenda is the emphasis on data and governance. However, the lack of good governance coupled with good observed data cannot ensure the achievement of SDG6. Therefore, this study strives to evaluate water quality status and hydrochemical processes governing it in the data-scarce Mokopane area of South Africa. Groundwater is the main source of fresh water supply for domestic usage, intensive agriculture, and mining activities in Mokopane. In this study, hydrogeochemical analysis of groundwater samples was employed to calculate the water quality index (WQI) and evaluate factors governing water quality evolution in the study area. Statistical and spatial analysis techniques were carried out to divide sampling sites into clusters and delineate principal factors responsible for determining water quality of the sampled groundwater. Results suggest that most of the physico-chemical parameters are within permissible limits for drinking water set by the World Health Organization (WHO), except for high fluoride in some samples. Na-HCO3 is the most abundant water type followed by Mg-HCO3, which indicates dominance of Na+, Mg2+, and HCO3±. Rock-water interaction is the prime factor responsible for fluoride enrichment in water. The alkaline nature of groundwater favors the release of exchangeable F− from minerals like muscovite. The WQI suggests that 80% of water samples fall into the good and excellent categories. Poor management of untreated domestic sewage and agricultural runoff is a main factor for the bad/very bad categories of water samples. As the area lacks any credible scientific/government work to report water quality and its management aspects, the findings of this study will definitely help both scientific communities and policy makers to do what is needed for sustainable water resource management in a timely manner.

Urban development is becoming increasingly common along landward margins of mangroves and results in increased impervious surfaces which collect and facilitate discharge of storm-water at point locations into the mangrove swamp. In contrast, natural storm-water inputs into mangroves are largely diffuse flows. Along the central Queensland coast Neosarmatium trispinosum and Parasesarma erythrodactyla are the most abundant species of sesarmid crabs occuring within these mangroves. Following a trial that found burrow counts were the most reliable estimate of relative crab abundance, comparisons were made between mangroves receiving storm-water input and control sites that were not affected.

Coal seam gas (CSG) is obtained by pumping water from the saturated coal seam to reduce the pressure allowing the methane gas to desorb. The co-produced water from the gas extraction process has a geochemical signature mainly determined by the moderate levels of salinity, sodicity and dissolved trace elements. Typically, CSG co-produced water requires treatment to be suitable for beneficial re-use, since untreated co-produced water can cause soil infiltration damage and nutritional imbalance for crops and livestock. CSG water from the Bowen Basin (Queensland) was used in this study and has a typical ionic composition of Na+-Cl--HCO3-. In this study, two natural ion exchange materials, zeolite and scoria, were used for the removal of Na+, Sr2+ and Ba2+ from CSG co-produced water. Following XRD analysis, the mineral composition of the zeolite material was found to be consistent of clinoptilolite (41%) and mordenite (29%), while the scoria material presented as diopside (35%), forsterite (33%) and anorthite (29%) characteristic. The real exchange capacity exhibited by the zeolite material was 75 meq/100 g, while the real exchange capacity determined for the scoria was 28 meq/100 g. Adsorption capacity and kinetic rates for Na+ ions were favoured by the use of small fraction sizes of natural forms of the zeolite and scoria material, which increased the accessibility of available adsorption sites on the material for cation interaction, consequently, an optimised fraction size of 0.6 – 0.3 mm was used in all studies. Equilibrium studies used a ratio of 20:1 for solution and material (50 mL : 2.5 g) for 72 h showing that the scoria and zeolite material treated with NH4+ exhibited greater adsorption capacities for Na+, Sr2+ and Ba2+ than the natural form. The maximum Na+ adsorption observed in the scoria and zeolite materials enriched with NH4+ was 17 and 45 meq/100 g, which corresponds to 61% and 60% of the measured real exchange capacity, respectively. The scoria and zeolite materials enriched with NH4+ for Sr2+ adsorption were 4.5 and 8 meq/100 g (44 and 80% removal of the initial Sr2+ concentration). The maximum Ba2+ adsorption achieved using the scoria and zeolite in NH4+ form was 5.8 and 10.6 meq/100 g (40 and 94% removal of the initial Ba2+ concentration). Competitive uptake studies were undertaken to determine selectivity isotherms and coefficients that showed the scoria material’s selectivity series was Ba2+ >Sr2+ >> Ca2+ > K+ > Na+, while, the zeolite material exhibited selectivity for K+ >Ba2+> Sr2+ >> Ca2+ > Na+. Other cations present in CSG water compete with Na+ for adsorption sites, reducing its adsorption capacity to 10 and 38 meq/100 g for scoria and zeolite. The adsorption and desorption of Na+ ions studied in batch mode showed that the ability of scoria and zeolite to adsorb cations decreased with the number of regeneration cycles. The effect of the flow rate on the removal of Na+ by the scoria and the zeolite material in a fixed bed column experiment was relatively small (5% reduction when using flow rates of up 10 BV/h). Columns packed with the scoria and the zeolite material exhibited a larger Na+ dynamic adsorption capacity (breakthrough capacity) when treated with NH4+ as well as larger desorption capacities than the same materials in K+ form. Nonetheless, the adsorption capacity exhibited for both materials was approximately 50% of the real exchange capacity. The maximum bed volumes obtained before the breakpoint (C/C0 = 0.3, output concentration) with a flow rate of 5 BV/h for the scoria material in NH4+ form using CSG water was 1.5 BV, while zeolite in NH4+ form exhibited 4.5 BV. These results showed that in using any natural and pre-treated ion exchange material as a CSG water treatment technology, allow the adsorption of Na+ ions with evident improvement for pre-treated materials. Batch and column type experiments showed that chemical conditioning increased the zeolite and scoria ion selectivity towards cations such as Ba2+, Sr2+ and Na+ present in high concentrations in CSG water. Ion selectivity was found to be correlated to the incoming hydrated cation size and its energy of hydration. The outcomes obtained from the experimentation indicates that natural ion exchangers are suitable for the removal of cations present in CSG water through ion exchange. Nonetheless, limitations to the use of natural and pre-treated ion exchange materials were identified. The high salinity characteristic of CSG water needs to be corrected with other treatment methods or mixed with low salinity water, before the CSG water can be beneficially re-used. The use of natural ion exchange material for the treatment of CSG water may consist of a multi-column arrangement with several trains operating in parallel allowing continuous treatment and facilitate the regeneration of the column without the need to stop the treatment.

Project develops a stochastic dynamic programming technique for the optimal operation of a reservoir, to control salinity in the reservoir and thereby also in releases. These procedures are to meet irrigation and municipal demands.. A stochastic dynamic programming technique for the optimal operation of a reservoir to control salinity in the reservoir and thereby also in the releases, and to meet irrigation and municipal demands is developed. The technique defines the optimal policy for releases to meet salinity and irrigation water supply requirements. The problem for which the approach was specifically developed is characterised by the presence of a strongly stratified, essentially two-layer, condition in a reservoir used to supply irrigation water. The two-layer condtion exists over the winter months when cold and heavy saline flows enter the reservoir and flow to the bottom of the reservoir. The two-layer condition continues until mixing of the reservoir occurs in early summer. While the reservoir is stratified, it is possible to flush the saline water out of the reservoir by low level intakes. This flushing reduces the overall salinity level in the reservoir when mixing occurs at end of winter, and thereby reduces the salinity of reservoir summer. However, removing the saline bottom layer also reduces the volume of water available for irrigation. Hence there are limitations on the amount that can be withdrawn to reduce the salinity. The technique is an approach to optimising the performance of the reservoir to meet irrigation demands, while minimising salt concentration in the irrigation water. Stochastic dynamic programming is used to reflect the uncertainty in the inflows while chance-constraints are reservoir beginning of the irrigation season. Three different probabilistic nature of the salt inflows to the reservoir: 1) salt load is directly related to the volume of inflow, 2) salt load is independent of the volume of the inflow, and 3) salt load is conditioned on the volume of inflow. The model is demonstrated by application to the Wellington Reservoir in Western Australia for the case in which the salt load is conditioned on the inflow. The results of the application of the model for a range of different combinations of maximum allowable saltconcentration and probability of exceeding that are compared to each other and to the release policy generated in an earlier simulation analysis undertaken to manage the salinity question.

Study examines issues associated with the design and operation of water quality monitoring networks where one or more monitoring stations have been discontinued. A methodology has been developed for prediction of these water quality values at discontinued stations in Queensland.. This study examines an issue associated with the design and operation of water quality monitoring networks, namely, the situation, where, because of reductions in the budget allocated to water quality monitoring, or because the budget allocated to water quality monitoring is not increasing at the same rate at which the cost of operation of the network is increasing, or the need for a monitoring station is more acute in another location, one or more existing monitoring stations have to be discontinued. The particular question addressed in relation to this scenario is the development of an improved metho-dology for the prediction of water quality values at the discontinued stations. The methodology proposed for the improved prediction of these water quality is derived from the information theory interpretation of the entropy principle, as formulated in terms of the Principle of Maximum Entropy (POME) and the Minimum Discrimination Information (MDI). The methodology itself is a nonlinear optimisation model in which an entropy function of the form Pi ln Pi where Pi represents the probability of event xi, is maximised subject to a series of constraints on the form and statistics of the probability function from which the Pi values are derived. An important feature of the probability distribution predictions provided by the model is that they are the 'most likely' distributions and therefore are un-biased, being affected only by the information which the user chooses to include in the constraints imposed on the optimisation, and on the historical values of the probability distributions which are incorporated into the non-linear objective function. The approach is demonstrated by application to a series of water quality monitoring networks in Queensland, Australia. The model was evaluated on the basis of these cases in a verification step involving a comparison of the accuracy of the predictions provided by the entropy technique with the accuracy of the predictions available from a traditional regression based approach. The predictions from the entropy based approach were on average more accurate then those obtained from the regression approach 61% of the time. The performance of the approach in terms of the accuracy of its predictions, the unbiased nature of those predictions, and the fact that it requires the same type and amount of data as traditional regression techniques, indicates that the technique represents a significant advance in the prediction of water quality values at dis-continued water quality monitoring stations.

Project investigates a neural network approach to reservoir operations.. The techniques traditionally used to generate optimal or near optimal operating policies for reservoirs fall into two general categories, optimisation and simulation. These techniques have, to date, been unable to satisfactorily address the complete range of issues which must be considered in the development of optimal reservoir operating policies. Neural networks appear to have the potential to address some of the problems associated with the use of optimisation and simulation to define the wide range of issues involved in optimal decision for operations of reservoirs. A neural network approach to reservoir operations is investigated in this thesis. In particular, the sensitivity of the performance of the neural network to variations in the key parameters of; normalisation method, number of training patterns, number of hidden neurons, learning rate, momentum coefficient, number of training iterations, and starting connection weights is examined. The approach utilises historical patterns of inflow, storage, and demand for a reservoir to predict the quantity of water to be released from the reservoir. Based on the analysis in this study, it was determined that relatively few rules exist for selection of the values of the parameters of the neural network. In general, where rules do exist, they tend to be in the form of guidelines or principles rather than explicit rules. Despite this lack of explicit rules, the neural network used in this study was able to perform reasonably well in predicting the quantity of water to be released. Overall, the concept of neural networks appear to have considerable potential to provide an alternative method for use in optimising reservoir performance, compared to the more conventional methods of optimisation or simulation.

On large industrial or nuclear sites there is a requirement to undertake assessments of land quality, from desk studies to detailed field investigations. Data obtained from such investigations provides the baseline from which known or potentially contaminated land can be managed. However, a commonly encountered problem is that this information is often disparate, collected for reasons not related to land quality management, with data from previous ground investigations also exhibiting the following particular problems: • The intent of a previous investigation is often not clear. • There can be much variability in investigation and analytical methods and standards. • The investigation techniques and standards are not documented. • Ground investigation and analytical data does not have adequate quality control in order to make a judgment about its value and applicability. Consequently, a commonly occurring problem is the frequent re-investigation of the same areas of a site for reasons that may not be very different. This is costly and incurs unnecessary risks. In order to resolve this problem, the UK Atomic Energy Authority (UKAEA), in conjunction with ESiT Ltd, has developed and implemented a software application to capture, interrogate and present land quality assessment data for its sites across the UK. The overall assessment of land quality on the sites relies on information that is both varied and disparate in nature. Tools are therefore required to structure and assess this information to enable clear interpretation and management decisions to be made. UKAEA has applied these tools to several areas within its environmental restoration programme including delicensing activities, Safety Cases for contaminated ground, inventories of land liabilities as well as the general monitoring of the environmental conditions on and surrounding the sites. This paper will describe the software application in the context of its function as a land quality management tool. The software application, known as the Information Management and Geographic Evaluation System (IMAGES), has a modular design and facilitates multi-user access. IMAGES interfaces with standard desktop applications to enable straightforward upload or reporting of data. There are also interfaces with industry standard software packages for spatial analysis of data (ArcGIS) and to provide representation of borehole logging data. The modules that make up IMAGES are: • Land & Risk Assessment “Sentencing”; • Document Register; • Photograph/Image register; • Site Investigation; • Excavation & Soil Transfer; • Groundwater Monitoring; • Radiation survey (Health Physics) Monitoring; • Buildings Information; • Geographic Information System (GIS) Data Management. The IMAGES solution is process based, dealing with data acquisition through storage and interpretation to output and has the ability to systematically deal with large volumes of information while ensuring consistency in approach at each stage. It also provides data that is access and revision-controlled and quality assessed. IMAGES also includes a series of standard data capture templates to enable environmental monitoring and site investigation information to be captured directly in the field and automatically logged into the IMAGES relational database structure. Data within the system can be quality assessed and queried using a map-based interface. Information held within IMAGES can also be delivered seamlessly into UKAEA’s Geographic Information System (GIS) for visual assessment and further analysis.

A preliminary assessment of the Sellafield site in Cumbria was undertaken to provide the information for the hazard identification stage in the environmental risk assessment process. This preliminary investigation has been crucial to understanding the site’s history, the zones of potential risk and for the design of a site investigation. The formalised assessment strategy that has subsequently been developed by BNFL for the Sellafield study has drawn upon UK and international guidance to take into account the size of the site and the anticipated complexity of issues. The approach presented represents an advance on existing working practices in contaminated land investigations. The use of a generic list of Features, Events and Processes (FEPs) has been adopted to ensure the systematic and comprehensive appraisal of all relevant uncertainties and sources of risk. Proforma have also been developed to provide a data management and retrieval system that is transparent for quality assurance purposes. This unique approach facilitates the development of conceptual site models as new data become available during the site investigation. It also aids in the development and justification of alternative site conceptualisations and in the early identification of data and interpretative uncertainty.