Multimedia on the Mountaintop: Using public snow images to improve water systems operation

This paper merges multimedia and environmental research to verify the utility of public web images for improving water management in periods of water scarcity, an increasingly critical event due to climate change. A multimedia processing pipeline fetches mountain images from multiple sources and extracts virtual snow indexes correlated to the amount of water accumulated in the snow pack. Such indexes are used to predict water availability and design the operating policy of Lake Como, Italy. The performance of this informed policy is contrasted, via simulation, with the current operation, which depends only on lake water level and day of the year, and with a policy that exploits official Snow Water Equivalent (SWE) estimated from ground stations data and satellite imagery. Virtual snow indexes allow improving the system performance by 11.6% w.r.t. The baseline operation, and yield further improvement when coupled with official SWE information, showing that the two data sources are complementary. The proposed approach exemplifies the opportunities and challenges of applying multimedia content analysis methods to complex environmental problems

Developing a stochastic simulation model for the generation of residential water end-use demand time series

: Smart metering technologies allow for gathering high resolution water demand data in the residential sector, opening up new opportunities for the development of models describing water consumers’ behaviors. Yet, gathering such accurate water demand data at the end-use level is limited by metering intrusiveness, costs, and privacy issues. In this paper, we contribute a stochastic simulation model for synthetically generating high-resolution time series of water use at the end-use level. Each water end-use fixture in our model is characterized by its signature (i.e., its typical single-use pattern), as well as frequency distributions of its number of uses per day, single use duration, time of use during the day, and contribution to the total household water demand. The model relies on statistical data from a real-world metering campaign across 9 cities in the US. Showcasing our model outputs, we demonstrate the potential usability of this model for characterizing the water end-use demands of different communities, as well as for analyzing the major components of peak demand and performing scenario analysis

Modelling residential water consumers’ behaviors by feature selection and feature weighting

Identifying the most relevant determinants of water consuming or saving behaviors at the household level is key to building mathematical models that predict urban water demand variability in space and time and to explore the effects of different Water Demand Management Strategies for the residential sector. This work contributes a novel approach based on feature selection and feature weighting to model the single-user consumption behavior at the household level. A two-step procedure consisting of the extraction of the most relevant determinants of users’ consumption and the identification of a predictive model of water consumers’ profile is proposed and tested on a real case study. Results show the effectiveness of the proposed method in capturing the influence of candidate determinants on residential water consumption, as well as in attaining sufficiently accurate predictions of users’ consumption profiles, which constitutes essential information to support residential water demand management

Trading off natural resources and rural livelihoods. A framework for sustainability assessment of small-scale food production in water-limited regions

Enhancing local production is key to promoting food security, especially in rural households of low-income countries, but may conflict with limited natural resources and ecosystems preservation. We propose a framework integrating the water-food nexus and a sustainable livelihoods perspective to assess small-scale food production in water-poor regions. We demonstrate it by assessing alternative production scenarios in the Gaza Strip at different spatial scales. At the scale of a single farm, there is a clear conflict among objectives: while cash crops ensure good incomes but contribute scarcely to domestic protein supply, crops performing well from the nutritional and environmental viewpoint are among the worst from the economic one. At the regional scale, domestic production might cover an important fraction of nutritional needs while contributing to household income, but water scarcity impairs the satisfaction of food demand by domestic production alone. Pursuing food security under multiple constraints thus requires a holistic perspective: we discuss how a multidimensional approach can promote the engagement of different stakeholders and allow the exploration of trade-offs between food security, sustainable exploitation of natural resources and economic viability

A coupled human-natural systems analysis of irrigated agriculture under changing climate

Exponentially growing water demands and increasingly uncertain hydrologic regimes due to changes in climate and land use are challenging the sustainability of agricultural water systems. Farmers must adapt their management strategies in order to secure food production and avoid crop failures. Investigating the potential for adaptation policies in agricultural systems requires accounting for their natural and human components, along with their reciprocal interactions. Yet this feedback is generally overlooked in the water resources systems literature. In this work, we contribute a novel modeling approach to study the coevolution of irrigated agriculture under changing climate, advancing the representation of the human component within agricultural systems by using normative meta-models to describe the behaviors of groups of farmers or institutional decisions. These behavioral models, validated against observational data, are then integrated into a coupled human-natural system simulation model to better represent both systems and their coevolution under future changing climate conditions, assuming the adoption of different policy adaptation options, such as cultivating less water demanding crops. The application to the pilot study of the Adda River basin in northern Italy shows that the dynamic coadaptation of water supply and demand allows farmers to avoid estimated potential losses of more than 10 M€/yr under projected climate changes, while unilateral adaptation of either the water supply or the demand are both demonstrated to be less effective. Results also show that the impact of the different policy options varies as function of drought intensity, with water demand adaptation outperforming water supply adaptation when drought conditions become more severe