Abstract: ABSTRACT As a result of population growth, economic development and climate change, feeding the world and providing water security will require important changes in the technologies, institutions, policies and incentives that drive present-day water management, as captured in Goal 6.4 of the Millennium Development Goals. Irrigation is the largest and most inefficient water user, and there is an expectation that even small improvements in agricultural water productivity will improve water security. This paper argues that improvements in irrigation water productivity involves a complex and comprehensive rural transformation that goes beyond mere promotion of water saving technologies. Many of the measures to improve water productivity require significant changes in the production systems of farmers and in the support provided to them. Looking forward, water use and competition over water are expected to further increase. By 2025, about 1.8 billion people will be living in regions or countries with absolute water scarcity. Demand for water will rise exponentially, while supply becomes more erratic and uncertain, prompting the need for significant shifts of inter-sectoral water allocation to support continued economic growth. Advances in the use of remote sensing technologies will make it increasingly possible to cost-effectively and accurately estimate crop evapotranspiration from farmers’ fields.

Abstract: Study region Africa, Latin America, Europe. Study focus Through the extensive study and mapping of the world’s aquifers that lie astride the international boundary lines of sovereign States, ISARM has awakened concerned States to the existence of aquifers stretching beyond their borders, and precipitated cooperation in generating a body of knowledge that facilitated cooperation in governance arrangements for such aquifers. In parallel, ISARM influenced the shape and direction of the United Nations “Draft articles on the law of transboundary aquifers” appended to UN Resolution 63/124 of 2008. Both stimulated cooperation among concerned States, and provided a frame of reference for the legal grounding of such cooperation in aquifer-specific agreements. New hydrological insights Through this synergistic paradigm, ISARM has made an impact on the shape and direction of cooperation in the Guaraní Aquifer in South America, and in the Iullemeden and Taoudeni/Tanezrouft Aquifer Systems (ITAS) in the Sahel region of Africa. It is having an influence on the shape and direction of cooperation being negotiated on the Stampriet Aquifer System in Southern Africa, and on the Ocotepeque-Citalá Aquifer in Central America. The link of ISARM to other international aquifer agreements on record is tenuous, and ISARM’s influence on their generation speculative. The visibility of ISARM has faded since 2012, however its legacy is lasting.

Abstract: The migration process of leached uranium in the in-situ leaching of uranium is considered a typical reactive transport problem. During this process, the lixiviant concentration and injection rate are important in-situ leaching process parameters (ISLPP) to efficiently recover uranium. However, several uncertain factors affect the outcomes of the ISLPP design. In addition, the repeated use of the reactive transport model (RTM) for investigating the acid in-situ leaching of uranium with the application of the Monte Carlo method leads to a substantial computational load. For this reason, a machine learning (ML)–based surrogate model was developed with the backpropagation neural network (BPNN) method to replace the RTM under the condition of uncertain parameters. Moreover, the simulated annealing optimisation model for ISLPP was created based on the proposed surrogate model. The optimal ISLPP was achieved that generated maximum profits from uranium recovery under different lixiviant prices, uranium prices and exploitation times. The optimal design framework of ISLPP based on the proposed ML algorithm was then applied in the Bayan-Uul sandstone-type uranium deposit in Inner Mongolia, China. From our analysis, it was demonstrated that the ML-based surrogate model exhibited great fitness with the RTM. The optimal results of the ISLPP indicated that the lixiviant concentration and injection rate could be adjusted based on the fluctuations in lixiviant price, uranium price and exploitation time. If the prices of sulphuric acid were high, a specific concentration of hydrogen peroxide could be injected into the injection well to promote the oxidation and dissolution of the uranium ore to increase the income from the uranium recovery. The optimisation model can also use the ISLPP scheme to boost the revenues from different lixiviant prices, uranium prices and exploitation times under the uncertainty of porosity, illustrating the applicability of the ML-based optimal design method of ISLPP in ISL mining. A general framework for developing surrogate models, as well as for conducting uncertainty analyses for a wide range of groundwater models was proposed here yielding valuable insights.