A new operational approach for understanding water-related interactions to achieve water sustainability in growing cities

About 56 percent of the world’s population currently lives in cities. Anthropogenic activities have both directly and indirectly modified their environment. Therefore, management actions at the urban level determine whether or not cities are heading toward sustainability. Consequently, water management is in need of a clear insight of the social and ecological water-related interactions. Thus, a new operational approach is proposed for a better understanding of the interactions between the water cycle, cities and the society. In our approach, eleven key issues and their interactions emerge from an analysis of 371 documents published between 2012 and 2018. The interactions between different key issues were examined through four main foci of analysis: water resources, urban throughput, water equity, and water governance and financing. Those main foci help to comprehend water as a holistic element intertwined in urban areas. In addition, our approach provides six challenges to guide the stakeholders in decision-making processes: how to recognize, integrate, and/or restore water-related ecosystem services, how to maintain and improve the supporting green and blue spaces, how to guarantee the quality and quantity of water resources and the water supplied and used, how to ensure public and social health and well-being of the citizens, how to prevent and manage water-related conflicts, and how to make informed and equitable decisions on water management at urban level?

Well Integrity Leak Diagnostic Using Fiber-Optic Distributed Temperature Sensing and Production Logging

Fiber optics has many applications in the oil and gas industry. In recent years, fiber optics has found usefulness in leak detection. The leaks can be efficiently identified using fiber-optic distributed temperature sensing measurement, thereby mitigating the health, safety, and environmental (HSE) risk associated with well integrity. Further, a production log can be used to gain more insight and finalize a way ahead to resolve well integrity issues. An innovative solution-driven approach was defined, with fiber-optic distributed measurement playing a key role. Multiple leaks were suspected in the well completion, and a fiber-optic cable was run to identify possible areas of the leak path. After the fiber-optic data acquisition, a production log was recorded across selective depths to provide an insight on leak paths. After identifying leak depths, a definitive decision between tubular patching and production system overhaul was decided based on combined outputs of the fiber-optic acquisition and production log. Results are presented for a well where multiple leaks were successfully identified using the novel operational approach. Further, operational time was reduced from 3 days (conventional slickline memory or e-line logging performed during daylight operation) to 1 day (a combination of fiber-optic distributed temperature sensing and production log in a single run). The diagnosis of production system issues was completed in one shut-in and one flowing condition, thereby reducing the risk of HSE exposure with multiple flowing conditions (to simulate the leak while the conventional production logging tool is moved to different depths in the well). Additional insight on leak quantification was confirmed from the production log data, where one leak was noted at the tubing collar while the other leak was noted a few meters above the tubing collar. This observation was substantial in deciding whether to proceed with tubing patch or replace the entire production tubing. The novel operational approach affirms fiber-optic distributed temperature measurement's versatility in solving critical issues of operation time and reducing HSE exposure while delivering decisive information on production system issues. The paper serves as a staging area for other applications of similar nature to unlock even wider horizons for distributed temperature sensing measurement.

DECISION MAKING PRINCIPLES IN LAND DEVELOPMENT APPROVAL

The inconsistency of legal coordination is one of the contributing factors in land use conflict. This scenario implicates various objections to the court due to the dissatisfaction of the landowners and developers with the decision of land development approval. In Malaysia, studies about land use conflict in land development conducted by previous researchers only cater on conflict factors and not in the perspective of its operational approach by the stakeholder. Therefore, this paper aims to identify the decision-making principles for decision-makers in grant land development approval. This paper adopts qualitative methods that consist of two types of data collection. The first method used was desk study analysis of ten (10) file cases of development application and the second method involved is an in-depth interview with selected respondents. The result from the analysis of ten (10) file cases determined the decision-making trends that were then cross-tabulated with the five principles of decision-making by using an indepth interview with the selected respondents. The result from the analysis indicates five principles of decision-making which is intuition, rational, power, factual, and experience. The findings of this paper contribute towards the aspects of strategic decision-making, decision-maker practices, and further research. A comprehensive decision-making principle will then minimise the risk of fallacy in decision-making.

Analysis-Ready Data from Hyperspectral Sensors—The Design of the EnMAP CARD4L-SR Data Product

Today, the ground segments of the Landsat and Sentinel missions provide a wealth of well-calibrated, characterized datasets which are already orthorectified and corrected for atmospheric effects. Initiatives such as the CEOS Analysis Ready Data (ARD) propose and ensure guidelines and requirements so that such datasets can readily be used, and interoperability within and between missions is a given. With the increasing availability of data from operational and research-oriented spaceborne hyperspectral sensors such as EnMAP, DESIS and PRISMA, and in preparation for the upcoming global mapping missions CHIME and SBG, the provision of analysis ready hyperspectral data will also be of increasing interest. Within this article, the design of the EnMAP Level 2A Land product is illustrated, highlighting the necessary processing steps for CEOS Analysis Ready Data for Land (CARD4L) compliant data products. This includes an overview of the design of the metadata, quality layers and archiving workflows, the necessary processing chain (system correction, orthorectification and atmospheric correction), as well as the resulting challenges of this procedure. Thanks to this operational approach, the end user will be provided with ARD products including rich metadata and quality information, which can readily be integrated in analysis workflows, and combined with data from other sensors.

Short-Term Deterministic Solar Irradiance Forecasting Considering a Heuristics-Based, Operational Approach

Solar energy is an economic and clean power source subject to natural variability, while energy storage might attenuate it, ultimately, effective and operationally feasible forecasting techniques for energy management are needed for better grid integration. This work presents a novel deterministic forecast method considering: irradiance pattern classification, Markov chains, fuzzy logic and an operational approach. The method developed was applied in a rolling manner for six years to a target location with no prior data to assess performance and its changes as new local data becomes available. Clearness index, diffuse fraction and irradiance hourly forecasts are analyzed on a yearly basis but also for 20 day types, and compared against smart persistence. Results show the proposed method outperforms smart persistence by ~10% for clearness index and diffuse fraction on the base case, but there are significant differences across the 20 day types analyzed, reaching up to +60% for clear days. Forecast lead time has the greatest impact in forecasting performance, which is important for any practical implementation. Seasonality in data gaps or rejected data can have a definite effect in performance assessment. A novel, comprehensive and detailed analysis framework was shown to present a better assessment of forecasters’ performance.

Operational applications of the diamond norm and related measures in quantifying the non-physicality of quantum maps

Although quantum channels underlie the dynamics of quantum states, maps which are not physical channels — that is, not completely positive — can often be encountered in settings such as entanglement detection, non-Markovian quantum dynamics, or error mitigation. We introduce an operational approach to the quantitative study of the non-physicality of linear maps based on different ways to approximate a given linear map with quantum channels. Our first measure directly quantifies the cost of simulating a given map using physically implementable quantum channels, shifting the difficulty in simulating unphysical dynamics onto the task of simulating linear combinations of quantum states. Our second measure benchmarks the quantitative advantages that a non-completely-positive map can provide in discrimination-based quantum games. Notably, we show that for any trace-preserving map, the quantities both reduce to a fundamental distance measure: the diamond norm, thus endowing this norm with new operational meanings in the characterisation of linear maps. We discuss applications of our results to structural physical approximations of positive maps, quantification of non-Markovianity, and bounding the cost of error mitigation.