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This is the final version. Available from MDPI via the DOI in this record. ; Multiple criteria decision analysis (MCDA) methods have shown advantages in supporting decision-making with problems that confront conflicting objectives. However, current applications to complex environmental problems featuring the dynamic social sphere, particularly problems involving cultural heritage and nature, have yet to substantially reflect this. The dynamic social sphere reflects the demand for scenario forecasting in decision-making support. This knowledge gap has not been addressed sufficiently in MCDA research. A participatory MCDA method is hence proposed as a merger with Contingent Valuation Method (CVM) as the scenario forecasting. The MCDA is then carried out to tackle a complex environmental problem caused by traditional food production in a historic town, Daxi in Taiwan. The result reveals a remarkable willingness to support this issue of a historically significant industry causing detriment to environment (with WTP estimate of 128,700,000 USD from the public) and suggests a plan that applies multiple policy instruments rather than following a potentially adverse polluter-pays principle. This manifests the authors' argument that recognition of heritage significance has dramatically affected selection of policy instruments and provides a critical recommendation to the local government which has struggled to find solutions. The proposed MCDA also highlights its participatory aspect for addressing issues involving cultural heritage, supported by several key steps, in particular the intervention-impact value tree building, the scenario forecasting and the sensitivity analysis. ; Newton-Mosharafa Fund ; UK Department of Business, Energy and Industrial Strategy (BEIS) ; Egypt Science and Technology Development Fund (STDF)

AbstractThis paper describes some of the latest developments in real‐time fluvial flood‐forecasting systems which utilise quantitative weather radar information. Rain‐gauge, flow‐measuring stations, weather radar and other sources of information are fully integrated by the real‐time flood‐forecasting system and provide flood warnings for civil protection. The systems have been commissioned in various regions within the UK and are undergoing continuous development in conjunction with the UK water industry and through close involvement with various European partners via the auspices of the European Union.

This paper introduces a run-and-tumble model with self-reinforcing directionality and rests. We derive a single governing hyperbolic partial differential equation for the probability density of random-walk position, from which we obtain the second moment in the long-time limit. We find the criteria for the transition between superdiffusion and diffusion caused by the addition of a rest state. The emergence of superdiffusion depends on both the parameter representing the strength of self-reinforcement and the ratio between mean running and resting times. The mean running time must be at least 2/3 of the mean resting time for superdiffusion to be possible. Monte Carlo simulations validate this theoretical result. This work demonstrates the possibility of extending the telegrapher's (or Cattaneo) equation by adding self-reinforcing directionality so that superdiffusion occurs even when rests are introduced. © 2022 American Physical Society. ; S.F. is thankful for the support and hospitality of the Ural Mathematical Center at the Ural Federal University, Ekaterinburg. S.F. also acknowledges financial support from RSF Project No. 20-61-46013. D.H. acknowledges the support from Wellcome Trust Grant No. 215189/Z/19/Z, the Medical Research Council, as part of United Kingdom Research and Innovation (also known as UK Research and Innovation) [MC/UP/1201/21] and Churchill College, University of Cambridge. A.O.I. acknowledges financial support from the Ministry of Science and Higher Education of the Russian Federation (Ural Mathematical Center Project No. 075-02-2021-1387). D.H. and M.A.A.S acknowledge financial support from FAPESP/SPRINT Grant No. 18/15308-4. M.A.A.S acknowledges the Brazilian government's research funding agency CNPq (process no. 312667/2018-3).

Abstract. The Kosi River is an important tributary of the Ganges River, which passes through China, Nepal and India. With a basin area of 71 500 km2, the Kosi River has the largest elevation drop in the world (from 8848 m of Mt Everest to 60 m of the Ganges Plain) and covers a broad spectrum of climate, soil, vegetation and socioeconomic zones. The basin suffers from multiple water related hazards including glacial lake outburst, debris flow, landslides, flooding, drought, soil erosion and sedimentation. This paper describes the characteristics of water hazards in the basin, based on the literature review and site investigation covering hydrology, meteorology, geology, geomorphology and socio-economics. Glacial lake outbursts are a huge threat to the local population in the region and they usually further trigger landslides and debris flows. Floods are usually a result of interaction between man-made hydraulic structures and the natural environment. Debris flows are widespread and occur in clusters. Droughts tend to last over long periods and affect vast areas. Rapid population increase, the decline of ecosystems and climate change could further exacerbate various hazards in the region. The paper has proposed a set of mitigating strategies and measures. It is an arduous challenge to implement them in practice. More investigations are needed to fill in the knowledge gaps.