The world's first nuclear bomb was a developed in 1954 at a site near the town of Los Alamos, New Mexico. Designated as the Los Alamos National Laboratory (LANL) in 1981, the 40-square-mile site is today operated by Log Alamos National Security LLC under contract to the National Nuclear Security Administration (NNSA) of the U.S. Department of Energy (DOE). Like other sites in the nation's nuclear weapons complex, the LANL site harbors a legacy of radioactive waste and environmental contamination. Radioactive materials and chemical contaminants have been detected in some portions of the groundwater beneath the site. Under authority of the U.S. Environmental Protection Agency, the State of New Mexico regulates protection of its water resources through the New Mexico Environment Department (NMED). In 1995 NMED found LANL's groundwater monitoring program to be inadequate. Consequently LANL conducted a detailed workplan to characterize the site's hydrogeology in order to develop an effective monitoring program. The study described in Plans and Practices for Groundwater Protection at the Los Alamos National Laboratory: Final Report was initially requested by NNSA, which turned to the National Academies for technical advice and recommendations regarding several aspects of LANL's groundwater protection program. The DOE Office of Environmental Management funded the study. The study came approximately at the juncture between completion of LANL's hydrogeologic workplan and initial development of a sitewide monitoring plan.

This study attempts to re-frame the current thinking on groundwater development and the implications for food security. Groundwater is important in agriculture as it provides a reliable fallback when rainfeeding fails. It is therefore instrumental in managing risk and optimizing food production. However accessing groundwater has become habit and turned to dependency. Resources limits on many key aquifers have been exceeded and competition for groundwater has become intense. This study highlights the role of adaptive strategies in dealing with aquifer management and indicates directions of research and management.

Based on the graduate course in Earthquake Hydrology at Berkeley University, this text introduces the basic materials, provides a comprehensive overview of the field to interested readers and beginning researchers, and acts as a convenient reference point.

The book intends to cover various problematic aspects of emerging smart computing and self-adapting technologies comprising of machine learning, artificial intelligence, deep learning, robotics, cloud computing, fog computing, data mining algorithms, including emerging intelligent and smart applications related to these research areas. Further coverage includes implementation of self-adaptation architecture for smart devices, self-adaptive models for smart cities and self-driven cars, decentralized self-adaptive computing at the edge networks, energy-aware AI-based systems, M2M networks, sensors, data analytics, algorithms and tools for engineering self-adaptive systems, and so forth. Acts as guide to Self-healing and Self-adaptation based fully automatic future technologies Discusses about Smart Computational abilities and self-adaptive systems Illustrates tools and techniques for data management and explains the need to apply, and data integration for improving efficiency of big data Exclusive chapter on the future of self-stabilizing and self-adaptive systems of systems Covers fields such as automation, robotics, medical sciences, biomedical and agricultural sciences, healthcare and so forth This book is aimed researchers and graduate students in machine learning, information technology, and artificial intelligence.