Participatory Model Calibration for Improving Resource Management Systems: Case Study of Rainwater Harvesting in an Indian Village

While planning resource management systems in rural areas, it is important to consider criteria that are specific to the local social conditions. Such criteria might change from one region to another and are hence best identified using a participatory approach. In this work, we propose a participatory framework to identify such criteria and derive their weights. These identified criteria and their weights are used as parameters to develop a quantitative model for evaluating efficiency of each system. Such a model can serve as a support tool for stakeholders to simulate and analyze “what‐if” scenarios, evaluate alternatives, and select one which best satisfies their requirements. We use existing systems to test the model by comparing efficiencies evaluated by the model to efficiencies perceived by the stakeholders. The model is calibrated by repeating the process until statistically significant correlation is achieved between evaluated and perceived efficiencies. The novelty of the proposed framework lies in treating efficiencies perceived by the stakeholders as the ground truth since they know these systems well and are their ultimate users. The framework is successfully demonstrated using case study of rainwater harvesting (RWH) systems in an Indian village. The resulting calibrated model can be used to plan new RWH systems in this region and similar regions elsewhere. The framework can be used to plan other resource management systems in various regions.     

Methane and nitrous oxide emissions from a subtropical coastal embayment (Moreton Bay,Australia)

Surface water methane (CH₄) and nitrous oxide (N₂O) concentrations and fluxes were investigated in two subtropical coastal embayments (Bramble Bay and Deception Bay, which are part of the greater Moreton Bay, Australia). Measurements were done at 23 stations in seven campaigns covering different seasons during 2010–2012. Water–air fluxes were estimated using the Thin Boundary Layer approach with a combination of wind and currents-based models for the estimation of the gas transfer velocities. The two bays were strong sources of both CH₄ and N₂O with no significant differences in the degree of saturation of both gases between them during all measurement campaigns. Both CH₄ and N₂O concentrations had strong temporal but minimal spatial variability in both bays. During the seven seasons, CH₄ varied between 500% and 4000% saturation while N₂O varied between 128 and 255% in the two bays. Average seasonal CH₄ fluxes for the two bays varied between 0.5 ± 0.2 and 6.0 ± 1.5 mg CH₄/(m²·day) while N₂O varied between 0.4 ± 0.1 and 1.6 ± 0.6 mg N₂O/(m²·day). Weighted emissions (t CO₂-e) were 63%–90% N₂O dominated implying that a reduction in N₂O inputs and/or nitrogen availability in the bays may significantly reduce the bays' greenhouse gas (GHG) budget. Emissions data for tropical and subtropical systems is still scarce. This work found subtropical bays to be significant aquatic sources of both CH₄ and N₂O and puts the estimated fluxes into the global context with measurements done from other climatic regions.     

Learning,participation, and adaptation: exploring agri-environmental programmes

This paper explores the perceptions of policy makers and rural agricultural producers in respect of policy framing and adaptation to climate change, social learning and stakeholder input (participation) surrounding two successful agri-environmental programmes in Saskatchewan, Canada. Given the record of success of these two programmes in reducing vulnerability to climate change, this study provides an opportunity to explore certain attributes of adaptive management, including: what attributes make policy and programmes responsive; how government can frame programmes facilitating adaptation to climate change; what types of mechanisms can or should be used to engage with producers; and perhaps most importantly, what producers expect of government, government policies and programmes in relation to adaptation to climate change.     

Optimal Design Methods for Hybrid Renewable Energy Systems

Renewable and hybrid energy systems (HESs) are expanding due to environmental concerns of climate change, air pollution, and depleting fossil fuels. Moreover, HESs can be cost effective in comparison with conventional power plants. This article reviews current methods for designing optimal HESs. The survey shows these systems are often developed on a medium scale in remote areas and stand-alone, but there is a global growing interest for larger scale deployments that are grid connected. Examples of HESs are PV–wind–battery and PV–diesel–battery. PV and wind energy sources are the most widely adopted. Diesel and batteries are often used but hydrogen is increasing as a clean energy carrier. The design of an efficient HES is challenging because HES models are nonlinear, non-convex, and composed of mixed-type variables that cannot be solved by traditional optimization methods. Alternatively, two types of approaches are typically used for designing optimal HESs: simulation-based optimization and metaheuristic optimization methods. Simulation-based optimization methods are limited in view of human intervention that makes them tedious, time consuming, and error prone. Metaheuristics are more efficient because they can handle automatically a range of complexities. In particular, multi-objective optimization (MOO) metaheuristics are the most appropriate for optimal HES because HES models involve multiple objectives at the same time such as cost, performance, supply/demand management, grid limitations, and so forth. This article shows that the energy research community has not fully utilized state-of-the-art MOO metaheuristics. More recent MOO metaheuristics could be used such as robust optimization and interactive optimization.     

A油气田公司安全文化评价指标体系初探

深入研究了国内外学者安全文化与安全文化评价指标体系相关成果,结合油气田企业的安全生产实际,从定量、定性分析两个方面构建了适合A油气田公司安全文化评价体系.同时采用层次分析法确定安全文化评价体系各指标的权重,结合专家定性评价、员工问卷调查、安全生产定量指标多种赋分方式,客观和全面的评价了油气田公司安全文化建设现状.评价结果对指导油气田企业安全文化建设和提升企业安全文化水平具有现实意义.     

Reconnecting crop and cattle farming to reduce nitrogen losses to river water of an intensive agricultural catchment (Seine basin,France): past,present and future

Nitrate and pesticide contamination of surface and groundwater has become a major problem in intensive farming regions in Europe, with nitrate concentrations reaching values above the standard defined in 2000 by the European Water Framework Directive. In the Seine basin, a major issue is the closure and abandonment of drinking-water wells, which force water managers and drinking-water producers to explore solutions for water resource protection. Organic farming has appeared as a credible alternative to conventional farming, and this study explores the potential of organic farming to reconcile agricultural production and water quality. On the basis of agricultural statistics, survey questionnaires and experimental data, the nitrogen soil surface balance (N-SSB) has been established at the scale of a small 104-km² catchment (The Orgeval sub-basin), representative of the intensive cash crop farming in the Seine basin. The N-surplus for arable land in specialized organic cash crop systems has been found to be half that of current conventional systems (15 kg N ha⁻¹ yr⁻¹ versus 30 kg N ha⁻¹ yr⁻¹, respectively). The N-yield in organic systems is 21% lower than in conventional systems, but total fertilization (mostly symbiotic N fixation) is also 26% lower. Whereas 2–3 years of forage legume (e.g., alfalfa) as a starter crop of the typical 7- to 10-year diversified rotation builds up N soil fertility and helps prevent weeds without pesticides, the existence of an outlet for this fodder production is a limiting factor for the economic sustainability and the environmental benefits of these farming systems. Therefore, we explored the possibility of a reconnection of livestock and crop farming systems in the Orgeval catchment, a traditional dairy farming and Brie cheese production region. We calculated the N-SSB for this type of a reconnected livestock and cropping system and found a value very close to the specialized organic cash crop system with full utilization of fodder production, leading to profitable animal production, essentially as milk in this farm design. This reconnected system is compared with the estimated situation in 1955 before separation of plant and livestock production. Furthermore, the N-SSB values were converted into infiltrating sub-root concentrations and used as a boundary condition to a biogeochemical model. Organic cropping and organic reconnected livestock cropping systems result in a 50% reduction of surface water nitrate concentrations, a surface water quality 20% better than that reconstructed for 1955, with an overall higher protein production.     

Chemical self-organization in self-assembling biomimetic systems

Far-from-equillibrium oscillating chemical reactions are among the simplest systems showing complex behaviors and emergent properties. This class of reactions is often employed to mimic and understand the mechanisms of a great variety of biological processes. In this context, pattern formation due to the coupling between reaction and transport phenomena represent an active and promising research area. In this paper, we present results coming from experiments where we tried to blend the structural properties of self-assembled matrixes (sodium dodecyl sulphate micelles and phospholipid bilayers) together with the evolutive peculiarities of the Belousov–Zhabotinsky reaction. A series of interesting dynamical behaviors, like spatio-temporal chaos, stationary patterns and segmented waves, were found in reaction–diffusion and reaction–diffusion–convection experiments.     

Fuzzy modelling to identify key drivers of ecological water quality to support decision and policy making

Water quality modelling is an effective tool to investigate, describe and predict the ecological state of an aquatic ecosystem. Various environmental variables may simultaneously affect water quality. Appropriate selection of a limited number of key-variables facilitates cost-effective management of water resources. This paper aims to determine (and analyse the effect of) the major environmental variables predicting ecological water quality through the application of fuzzy models. In this study, a fuzzy logic methodology, previously applied to predict species distributions, was extended to model environmental effects on a whole community. In a second step, the developed models were applied in a more general water management context to support decision and policy making. A hill-climbing optimisation algorithm was applied to relate ecological water quality and environmental variables to the community indicator. The optimal model was selected based on the predictive performance (Cohen’s Kappa), ecological relevance and model’s interpretability. Moreover, a sensitivity analysis was performed as an extra element to analyse and evaluate the optimal model. The optimal model included the variables land use, chlorophyll and flow velocity. The variable selection method and sensitivity analysis indicated that land use influences ecological water quality the most and that it affects the effect of other variables on water quality to a high extent. The model outcome can support spatial planning related to land use in river basins and policy making related to flows and water quality standards. Fuzzy models are transparent to a wide range of users and therefore may stimulate communication between modellers, river managers, policy makers and stakeholders.     

Panarchy and community resilience: Sustainability science and policy implications

How does the resilience concept of nested relationships (panarchy) contribute to sustainability science and policy? Resilience at a particular level of organization, the community level in our case, is influenced by internal processes at that level. But it is also impacted by actions at lower levels of organization (individuals, households), and by drivers of change originating at higher levels (national level policies, globalized market forces). We focus on community level social-ecological systems, looking upwards and downwards from there. Our objective is to explore the connections of the community to other levels, the ways in which community resilience is impacted, and the implications of this for sustainability. Conventional disciplines specialize at different levels, a barrier to investigating multi-level interactions. Use of the panarchy concept helps contribute to the interdisciplinary understanding of resilience at the community (and other levels) by drawing attention to cross-scale relationships. From the effect of individual leadership to the implication of pandemics that move swiftly across levels, examples illustrate a diversity of ways in which community resilience is shaped in a multi-level world.     

Exploring coffee farmers’ awareness about climate change and water needs: Smallholders’ perceptions of adaptive capacity

Nicaragua is one of the four countries most affected by climate change, and coffee production is expected to vastly shrink in some critical areas. This can have considerable effects on social structure since nearly a third of its working population depend on coffee for a living. Social perceptions of climate change and water pressures are a key issue in the public's acceptance of adaptation measures. Furthermore, the existing risk for crop production is not necessarily correlated with the farmers’ awareness of that threat. This paper focuses on coffee producers’ perception of risk and adaptive capacity for coffee crops in Nicaragua in response to climate change and water availability. We aim to analyze how dependent the producers are on water resources, and if this reliance affects their perception of risk and their expectations with regard to public and private support for dealing with adaptation. A survey of 212 representative farmers of the national population of farms in the country's two most important production areas was conducted for this purpose. We consider socio-economic and biophysical variables to explain the farmers’ perceptions. Our findings show that experience and technical capacity are relevant to the adaptive capacity although smallholders do not always show high concern and their expectations with regard to external support are very low. The paper can be useful to prioritize the measures necessary for a greater level of involvement from stakeholders.