Abstract: Guideline values are prescribed for drinking water to ensure long term protection of the public against anticipated potential adverse effects. There is a great public and regulatory agencies interest in the guideline values of uranium due to its complex behavior in natural aquatic system and divergent guideline values across the countries. Wide variability in guideline values of uranium in drinking water may be attributed to toxicity reference point, variation in threshold values, uncertainty within intraspecies and interspecies, resource availability, socio-economic condition, variation in ingestion rate, etc. Although guideline values vary to a great extent, reasonable scientific basis and technical judgments are essential before it could be implemented. Globally guideline values are derived considering its radiological or chemical toxicity. Minimal or no adverse effect criterions are normally chosen as the basis for deriving the guideline values of uranium. In India, the drinking water limit of 60 µg/L has been estimated on the premise of its radiological concern. A guideline concentration of 2 µg/L is recommended in Japan while 1700 µg/L in Russia. The relative merit of different experimental assumption, scientific approach and its methodology adopted for derivation of guideline value of uranium in drinking water in India and other countries is discussed in the paper.

Abstract: This article aims to show that virtual water has historically been an adaptation strategy that enabled some arid regions to develop a prosperous economy without putting pressure on their scarce water resources. Virtual water is referred to as the total amount of water that is consumed to produce goods and services. As an example, in arid central Iran, the deficiency in agricultural revenues was offset by more investment in local industries that enjoyed a perennial capacity to employ more workers. The revenues of local industries weaned the population from irrigated agriculture, since most of their raw materials and also food stuff were imported from other regions, bringing a remarkable amount of virtual water. This virtual water not only sustained the region’s inhabitants, but also set the stage for a powerful polity in the face of a rapid population growth between the 13th and 15th centuries AD. The resultant surplus products entailed a vast and safe network of roads, provided by both entrepreneurs and government. Therefore, it became possible to import more feedstock such as cocoons from water-abundant regions and then export silk textiles with considerable value-added. This article concludes that a similar model of virtual water can remedy the ongoing water crisis in central Iran, where groundwater reserves are overexploited, and many rural and urban centers are teetering on the edge of socio-ecological collapse. History holds an urgent lesson on sustainability for our today’s policy that stubbornly peruses agriculture and other high-water-demand sectors in an arid region whose development has always been dependent on virtual water.

Abstract: The crucial role which groundwater resource plays in our environment and the overall well-being of all living things can not be underestimated. Nonetheless, mismanagement of resources, over-exploitation, inadequate supply of surface water and pollution have led to severe drought and an overall drop in groundwater resources’ levels over the past decades. To address this, a groundwater flow model and several mathematical data-driven models have been developed for forecasting groundwater levels. However, there is a problem of unavailability and scarcity of the on-site input data needed by the data-driven models to forecast the groundwater level. Furthermore, as a result of the dynamics and stochastic characteristics of groundwater, there is a need for an appropriate, accurate and reliable forecasting model to solve these challenges. Over the years, the broad application of Machine Learning (ML) and Artificial Intelligence (AI) models are gaining attraction as an alternative solution for forecasting groundwater levels. Against this background, this article provides an overview of forecasting methods for predicting groundwater levels. Also, this article uses ML models such as Regressions Models, Deep Auto-Regressive models, and Nonlinear Autoregressive Neural Networks with External Input (NARX) to forecast groundwater levels using the groundwater region 10 at Karst belt in South Africa as a case study. This was done using Python Mx. Version 1.9.1., and MATLAB R2022a machine learning toolboxes. Moreover, the Coefficient of Determination (R2);, Root Mean Square Error (RMSE), Mutual Information gain, Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), Mean Absolute Error (MAE), and the Mean Absolute Scaled Error (MASE)) models were the forecasting statistical performance metrics used to assess the predictive performance of these models. The results obtained showed that NARX and Support Vector Machine (SVM) have higher performance metrics and accuracy compared to other models used in this study.

Abstract: Groundwater is both an invaluable and a vulnerable resource. Aquifer resources management, aiming at the responsible exploitation and adequate protection of the groundwater resources, is therefore of key importance and has to be based on sound hydrological, environmental, economic and social principles. Aquifer-wide groundwater projects are carried out to collect the required area-specific information, to understand ongoing processes, to identify the management issues to be addressed and to develop an adequate management strategy and action plan. The quality of the project results depends to a large extent on the science and methodologies adopted in the design and used during the implementation of the projects. In this context, a project was carried out recently to analyse the scientific aspects of—among others—the transboundary aquifer projects within the IW: Portfolio of the Global Environmental Facility (GEF) and to make recommendations for scientific strengthening and innovation. This paper presents the main outcomes of this analysis. In order to accomplish groundwater resources management goals in the case of transboundary aquifers, a balanced joint strategy is needed. Analysis of documentation on completed and on-going transboundary aquifer projects has shown a wide range of scientific activities that contribute positively to the development of such strategies. This analysis has also identified options for increasing the positive impacts of science on strategy development; some of these options have been pioneered already and deserve wider application other ones are relatively new. Important options are: integrating transboundary aquifer resource management in a wider environmental–socio-economical context (holistic approach); exploring causal chains to better understand the processes of change of groundwater resources; using this improved understanding for optimising groundwater assessment and monitoring programmes; and adaptive management. In addition, to obtain maximum benefit of the scientific results there is a general need to promote effective communication at all levels, between the scientific community and policy-/decision makers, as well as with the local community who have a major role to play in the use and conservation of the resources. All of this should be accompanied by the harmonisation of the legal instruments and co-operation agreements between countries and the communities involved. Two case studies, one in South America and one in Southern Africa, are added as examples of the setting and approach of the analysed transboundary aquifer projects.

Abstract: Whether a nuclear installation has radiological impact and, in that case, its extension, are the questions behind any environmental analysis of the installation along its operational life. This analysis is based on the detailed establishment of the radiological background of the area. Accordingly, the dismantling and decommissioning process (D&D) of a nuclear power plant starts with a radiological monitoring plan, which includes the radiological characterization of the area and of its surroundings. At the completion of the D&D, unrestricted use for the site will be permitted strictly in accordance with results of the radiological survey within the limits established by the local authorities. Groundwater quality is typically included in any radiological analysis since, among other reasons, a significant part of it is highly likely to end up being extracted for domestic use and hence, human consumption. While there is no regulation containing maximum activity concentration or radionuclide guidance values for water that may be destined for uses other than public consumption, if groundwater is considered a “part” of the land, dose criteria for site release can be applied. Therefore, together with the guidance levels to be established for the different radionuclides expected in the groundwater, the detection limits to be employed when performing routine radio analytical characterization procedures in the laboratory should also be provided. In this paper, we first propose a relation of the potential radionuclides to be analyzed in groundwater, together with their detection limits to be achieved when the determinations are performed in a laboratory, and subsequently, we discuss the most suitable analytical methodologies and resources that would be necessary to undertake radiological characterization plans from a practical point of view.