Holistic water management approaches are essential under future climate and socio-economic changes, especially while trying to achieve inter-disciplinary societal goals such as the Sustainable Development Goals (SDGs) of clean water, hunger eradication, clean energy and life on land. Assessing water resources within a water-food-energy-environment nexus approach enables the relationships between water-related sectors to be untangled while incorporating impacts of societal changes. We use a systems modelling approach to explore global change impacts on the nexus in the mid-21st century in a complex western Himalayan water resource system in India, considering a range of climate change and alternative socio-economic development scenarios. Results show that future socio-economic changes will have a much stronger impact on the nexus compared to climate change. Hydropower generation and environmental protection represent the major opportunities and limitations for adaptation in the studied system and should, thereby, be the focus for actions and systemic transformations in pursue of the SDGs. The emergence of scenario-specific synergies and trade-offs between nexus component indicators demonstrates the benefits that water resource systems models can make to designing better responses to the complex nexus challenges associated with future global change.

The analysis and use of hydrological data for decision making in water resources planning and management can only be meaningful if the data possess the appropriate characteristics. In general, it is customary that data being analysed are consistent, free of trend and constituting a stochastic process whose random component is described by an appropriate probability distribution hypothesis. This paper describes, using hypothetical numerical examples where possible, some of the commonly used tests for establishing the presence or otherwise of these attributes in hydrological data series. The tests were then applied to actual streamflow data records from seven sites, in Iran and England, which formed the basis of an extensive water resources planning study carried out recently. In general, the data from all seven sites possessed the right attributes, which made their use in the wider water resources planning study straightforward.

Although it is a well-researched topic, the complexity, time for process stabilization, and economic factors related to anaerobic digestion call for simulation of the process offline with the help of computer models. Nature-inspired techniques are a recently developed branch of artificial intelligence wherein knowledge is transferred from natural systems to engineered systems. For soft computing applications, nature-inspired techniques have several advantages, including scope for parallel computing, dynamic behavior, and self-organization. This paper presents a comprehensive review of such techniques and their application in anaerobic digestion modeling. We compiled and synthetized the literature on the applications of nature-inspired techniques applied to anaerobic digestion. These techniques provide a balance between diversity and speed of arrival at the optimal solution, which has stimulated their use in anaerobic digestion modeling.