Effectiveness of a market-based instrument for the allocation of water in a tropical river environment

The seasonal nature of Australia’s tropical rivers means that connected groundwater aquifers are an important source of both consumptive and non-consumptive water, particularly during the dry season. The management of these common pool groundwater resources is one of the predominant water issues facing northern Australia. A national program of water reform stipulates the expansion of water trading as a key instrument for water allocation. The effectiveness of new institutional arrangements such as water markets will be determined mostly by how well they coordinate with local environmental requirements, local institutions and local norms. This paper describes a novel application of combined field work, institutional analysis, experimental economics and agent-based modeling to the analysis of a potential water market in the Katherine region of the Northern Territory, Australia. The effectiveness of different versions of the policy instrument is assessed in light of local conditions. Instruments that enable personal relationships and local institutions and norms to play a role in water management are found to be more effective in terms of both farming income and environmental impact.     

Triggering factors,behavior, and social impact of the January 2021 hail-debris flows at the Central Valley of Chile

Landslides - An extreme precipitation event produced catastrophic debris flows in central Chile during 29–31 January 2021 (austral summer). Our study focuses on the triggering factors and...     

Use of LIDAR in landslide investigations: a review

This paper presents a short history of the appraisal of laser scanner technologies in geosciences used for imaging relief by high-resolution digital elevation models (HRDEMs) or 3D models. A general overview of light detection and ranging (LIDAR) techniques applied to landslides is given, followed by a review of different applications of LIDAR for landslide, rockfall and debris-flow. These applications are classified as: (1) Detection and characterization of mass movements; (2) Hazard assessment and susceptibility mapping; (3) Modelling; (4) Monitoring. This review emphasizes how LIDAR-derived HRDEMs can be used to investigate any type of landslides. It is clear that such HRDEMs are not yet a common tool for landslides investigations, but this technique has opened new domains of applications that still have to be developed.     

Urban Seismic Risk Evaluation: A Holistic Approach

Risk has been defined, for management purposes, as the potential economic, social and environmental consequences of hazardous events that may occur in a specified period of time. However, in the past, the concept of risk has been defined in a fragmentary way in many cases, according to each scientific discipline involved in its appraisal. From the perspective of this article, risk requires a multidisciplinary evaluation that takes into account not only the expected physical damage, the number and type of casualties or economic losses, but also the conditions related to social fragility and lack of resilience conditions, which favour the second order effects (indirect effects) when a hazard event strikes an urban centre. The proposed general method of urban risk evaluation is multi hazard and holistic, that is, an integrated and comprehensive approach to guide decision-making. The evaluation of the potential physical damage (hard approach) as the result of the convolution of hazard and physical vulnerability of buildings and infrastructure is the first step of this method. Subsequently, a set of social context conditions that aggravate the physical effects are also considered (soft approach). In the method here proposed, the holistic risk evaluation is based on urban risk indicators. According to this procedure, a physical risk index is obtained, for each unit of analysis, from existing loss scenarios, whereas the total risk index is obtained by factoring the former index by an impact factor or aggravating coefficient, based on variables associated with the socio-economic conditions of each unit of analysis. Finally, the proposed method is applied in its single hazard form to the holistic seismic risk evaluation for the cities of Bogota (Colombia) and Barcelona (Spain).     

Sources of spread in simulations of Arctic sea ice loss over the twenty-first century

We show that intermodel variations in the anthropogenically-forced evolution of September sea ice extent (SSIE) in the Arctic stem mainly from two factors: the baseline climatological sea ice thickness (SIT) distribution, and the local climate feedback parameter. The roles of these two factors evolve over the course of the twenty-first century. The SIT distribution is the most important factor in current trends and those of coming decades, accounting for roughly half the intermodel variations in SSIE trends. Then, its role progressively decreases, so that around the middle of the twenty-first century the local climate feedback parameter becomes the dominant factor. Through this analysis, we identify the investments in improved simulation of Arctic climate necessary to reduce uncertainties both in projections of sea ice loss over the coming decades and in the ultimate fate of the ice pack.     

Intercomparison of multiple statistical downscaling methods: multi-criteria model selection for South Korea

A number of statistical downscaling methodologies have been introduced to bridge the gap in scale between outputs of climate models and climate information needed to assess potential impacts at local and regional scales. Four statistical downscaling methods [bias-correction/spatial disaggregation (BCSD), bias-correction/constructed analogue (BCCA), multivariate adaptive constructed analogs (MACA), and bias-correction/climate imprint (BCCI)] are applied to downscale the latest climate forecast system reanalysis (CFSR) data to stations for precipitation, maximum temperature, and minimum temperature over South Korea. All methods are calibrated with observational station data for 19 years from 1973 to 1991 and validated for the more recent 19-year period from 1992 to 2010. We construct a comprehensive suite of performance metrics to inter-compare methods, which is comprised of five criteria related to time-series, distribution, multi-day persistence, extremes, and spatial structure. Based on the performance metrics, we employ technique for order of preference by similarity to ideal solution (TOPSIS) and apply 10,000 different weighting combinations to the criteria of performance metrics to identify a robust statistical downscaling method and important criteria. The results show that MACA and BCSD have comparable skill in the time-series related criterion and BCSD outperforms other methods in distribution and extremes related criteria. In addition, MACA and BCCA, which incorporate spatial patterns, show higher skill in the multi-day persistence criterion for temperature, while BCSD shows the highest skill for precipitation. For the spatial structure related criterion, BCCA and MACA outperformed BCSD and BCCI. From the TOPSIS analysis, we found that MACA is the most robust method for all variables in South Korea, and BCCA and BCSD are the second for temperature and precipitation, respectively. We also found that the contribution of the multi-day persistence and spatial structure related criteria are crucial to ranking the skill of statistical downscaling methods.