The great success of the Tropical Rainfall Measuring Mission (TRMM) and its successor Global Precipitation Measurement (GPM) has accelerated the development of global high-resolution satellite-based precipitation products (SPP). However, the quantitative accuracy of SPPs has to be evaluated before using these datasets in water resource applications. This study evaluates the following GPM-era and TRMM-era SPPs based on two years (2014–2015) of reference daily precipitation data from rain gauge networks in ten mountainous regions: Integrated Multi-SatellitE Retrievals for GPM (IMERG, version 05B and version 06B), National Oceanic and Atmospheric Administration (NOAA)/Climate Prediction Center Morphing Method (CMORPH), Global Satellite Mapping of Precipitation (GSMaP), and Multi-Source Weighted-Ensemble Precipitation (MSWEP), which represents a global precipitation data-blending product. The evaluation is performed at daily and annual temporal scales, and at 0.1 deg grid resolution. It is shown that GSMaPV07 surpass the performance of IMERGV06B Final for almost all regions in terms of systematic and random error metrics. The new orographic rainfall classification in the GSMaPV07 algorithm is able to improve the detection of orographic rainfall, the rainfall amounts, and error metrics. Moreover, IMERGV05B showed significantly better performance, capturing the lighter and heavier precipitation values compared to IMERGV06B for almost all regions due to changes conducted to the morphing, where motion vectors are derived using total column water vapor for IMERGV06B.

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Smart, green, and resilient city paradigms have been mainly promoted through top-down and technocratic approaches. However, based on the notion to return to "the right to the city", emerging community-driven initiatives are providing self-managed infrastructures contributing to urban sustainability transitions. This paper explores the relevance of the behavioral aspects of people-centered approaches in dealing with two different facets of urban metabolism: physical infrastructure (involvement with the management of decentralized infrastructures) and consumption patterns (involvement in proactive reduction of resources used). In the first case we assessed community perceptions about the roles, benefits, and willingness to proactively engage in the management of decentralized green infrastructures in Bogotá City, Colombia. For the second facet, we measured the effectiveness of change agents in re-shaping energy consumption decisions within urban social networks in South Africa and Saudi Arabia. This paper's results show that pre-determined and standardized strategies do not guarantee positive, nor homogeneous, results in terms of meeting sustainability targets, or promoting community involvement. Hence, a better integration of people-centered and top-down approaches is needed through context-dependent policies, for enhancing both users' appreciation of and commitment to urban metabolism participative management.

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The planning and scheduling of maintenance operations of large conventional sewer systems generate a complex decision-making environment due to the difficulty in the collection and analysis of the spatiotemporal information about the operational and structural condition of their components (e.g. pipes, gully pots and manholes). As such, water utilities generally carry out these operations following a corrective approach. This paper studies the impact of the spatiotemporal correlation between these failure events using Log-Gaussian Cox Process (LGCP) models. In addition, the association of failure events to physical and environmental covariates was assessed. The proposed methods were applied to analyze sediment-related blockages in the sewer system of an operative zone in Bogotá (Colombia). The results of this research allowed the identification of significant covariates that were further used to model spatiotemporal clusters with high sediment-related failure risk in sewer systems. The LGCP model proved to be more accurate in comparison to those models that build upon a fundamental assumption that a failure is equally likely to occur at any time regardless of the state of the system and the system's history of failures (i.e. a homogeneous Poisson process model).