Smart Water Management in Agriculture: a Proposal for an Optimal Scheduling Formulation of a Gravity Water Distribution System

Agriculture represents one of the most water demanding sectors and its role is central on defining water saving policies. In this work, we propose an improved approach to the irrigation scheduling problem, reducing water wastage while satisfying farmers\u2019 demands and crops\u2019 water needs.For water distribution system managed with on-demand distribution approach, the efficiency of irrigation relies on the ability of the network manager (i.e., gatekeeper) to guarantee a proper service, consisting in: the irrigation scheduling, the definition of the volume of water passing through the channels at a given time, and the operations on gates and sluices to make the water reach the farms. Consequently, the irrigation scheduling inefficiencies might be limited by: i) reducing the water wastage, ii) minimizing the gatekeeper work and iii) maximizing the satisfaction of the farmers\u2019 requirements.We propose an improved mixed-integer linear optimization formulation that adds the possibility to store water in the channels and takes seepage into account. This new formulation is able to better represent the physical behavior of the water flow in the channels network, also avoiding the presence of flooding. The proposed optimization solution is embedded within a wider monitoring framework with the intent to fully exploit the availability of a complex network of models, repositories and sensors installed in the field.The resulting problem is solved by one of the most used optimization solvers (IBM ILOG Cplex) and tested on a synthetic benchmark. Furthermore, we validate the results on a digital copy of the network that performs a hydraulic simulation of the irrigation system. The scheduling is accepted if the water introduced in the system can satisfy farmers\u2019 requests with the considered timing and does not produce flooding

Cooling history and emplacement of a pyroxenitic lava as proxy for understanding Martian lava flows

Terrestrial analogues are often investigated to get insights into the geological processes occurring on other planetary bodies. Due to its thickness and petrological similarities, the pyroxenitic layer of the 120m-thick magmatic pile Theo’s Flow (Archean Abitibi greenstone belt Ontario, Canada), has always been regarded as the terrestrial analogue for Martian nakhlites. However, its origin and cooling history and, as a consequence those of nakhlites, have always been a matter of vigorous debate. Did this lava flow originate from a single magmatic event similar to those supposed to occur on Mars or do the different units derive from multiple eruptions? We demonstrate, by a combination of geothermometric constraints on augite single crystals and numerical simulations, that Theo’s Flow has been formed by multiple magma emplacements that occurred at different times. This discovery supports the idea that the enormous lava flows with similar compositions observed on Mars could be the result of a process where low viscosity lavas are emplaced during multiple eruptions. This has profound implications for understanding the multiscale mechanisms of lava flow emplacement on Earth and other planetary bodies

Bayesian Data-Driven approach enhances synthetic flood loss models

Flood loss estimation models are developed using synthetic or empirical approaches. The synthetic approach consists of what-if scenarios developed by experts. The empirical models are based on statistical analysis of empirical loss data. In this study, we propose a novel Bayesian Data-Driven approach to enhance established synthetic models using available empirical data from recorded events. For five case studies in Western Europe, the resulting Bayesian Data-Driven Synthetic (BDDS) model enhances synthetic model predictions by reducing the prediction errors and quantifying the uncertainty and reliability of loss predictions for post-event scenarios and future events. The performance of the BDDS model for a potential future event is improved by integration of empirical data once a new flood event affects the region. The BDDS model, therefore, has high potential for combining established synthetic models with local empirical loss data to provide accurate and reliable flood loss predictions for quantifying future risk

Evolutionary leap in large-scale flood risk assessment needed

Current approaches for assessing large-scale flood risks contravene the fundamental principles of the flood risk system functioning because they largely ignore basic interactions and feedbacks between atmosphere, catchments, river-floodplain systems and socio-economic processes. As a consequence, risk analyses are uncertain and might be biased. However, reliable risk estimates are required for prioritizing national investments in flood risk mitigation or for appraisal and management of insurance portfolios. We review several examples of process interactions and highlight their importance in shaping spatio-temporal risk patterns. We call for a fundamental redesign of the approaches used for large-scale flood risk assessment. They need to be capable to form a basis for large-scale flood risk management and insurance policies worldwide facing the challenge of increasing risks due to climate and global change. In particular, implementation of the European Flood Directive needs to be adjusted for the next round of flood risk mapping and development of flood risk management plans focussing on methods accounting for more process interactions in flood risk systems

A Conceptual Framework for Vulnerability and Risk Assessment in the Context of Nature-Based Solutions to Hydro-Meteorological Risks

Various frameworks for vulnerability and risk assessment of social-ecological systems (SES) to natural hazards have been developed addressing different contexts. However, none were specifically developed in the context of implementing nature-based solutions (NBS) to hydro-meteorological risks. Since the basic concepts and principles of NBS are mainly focused on ensuring balance between ecological and social benefits, the entire vulnerability and risk assessment process should focus equally on various social and ecological components of a location where an NBS would be implemented. As a part of the OPEn-air laboRAtories for Nature baseD solUtions to Manage hydro-meteo risks (OPERANDUM) project, this research proposes a conceptual framework for vulnerability and risk assessment in the context of NBS to hydro-meteorological risks. This conceptual framework is developed mainly considering the major components of the existing Delta-SES risk assessment framework (Sebesvari et al. 2016) and other similar frameworks proposed in recent studies, as well as the proposed principles for NBS endorsed by International Union for Conservation of Nature (IUCN). The major components of the framework include: (i) the exposure of SES to multiple hydro-meteorological hazards (e.g., flood, drought); (ii) vulnerability of SES that consists of ecosystem susceptibility, social susceptibility, ecosystem robustness, and coping and adaptive capacity of the social system; (iii) risks in the NBS project site determined by the combination of hazard exposure and vulnerability; and (iv) the impacts of hydro-meteorological hazards on the SES surrounding or within the NBS project site. While the basic space of risk assessment would be the NBS project site (usually at the local level within sub-catchments) with specific SES characteristics, this framework also reflects the interrelationships between ecosystem and social system as well as the effects of multiple hazards and risks at local up to the global scales. The framework also considers the changes over time that would capture the maturation time lag of the ecological components of an NBS, as well as the sustainability of the system with the intervention of NBS and other risk reduction measures. An indicator-based risk assessment approach can be used to operationalize the framework. To facilitate that, an indicator library has been developed comprising of indicators for different exposure and vulnerability components of the framework. The proposed framework can be applicable to any geographical conditions where an NBS project is to be implemented to reduce hydro-meteorological risks. The framework can also be tailored for other natural hazards (e.g. geological hazards like earthquake) and anthropogenic hazards (e.g. pollution). We will explain the conceptualisation process of the framework and of the indicator library and how these will be tested within the OPERANDUM project in the context of NBS implementation