Search

The construction of carbon market is one of the important means for China to reach the goal of carbon peaking and carbon neutrality, and the allocation of initial carbon emission right quota is the key link in carbon market transaction. At present, the historical method is the commonly used allocation method of initial carbon emission rights in China, and the use of this method is unfair and inefficient. Therefore, this paper proposes an allocation optimization model, selects a number of indicators, and optimizes the allocation of initial carbon emission rights based on the hierarchical analysis method and entropy weight method. Example analysis shows that the allocation optimization model helps to share the carbon emission responsibility and improve the allocation efficiency, realizes the optimal allocation of initial carbon emission rights among industrial sectors, and provides support for the emission reduction of industrial sectors.

The particle size distribution (PSD) is a crucial parameter used to characterize the material composition of debris-flow deposits which determines their hydraulic permeability, affecting the mobility of debris flows and, hence, the sustainable development of debris-flow fans. Three types of graded bedding structures—normal, reverse, and mixed graded bedding structures—are characterized by discontinuous gradation within a specific deposit thickness. A series of permeability tests were conducted to study the effects of bed sediment composition, particularly coarse grain sizes and fine particle contents, on the permeability and migration of fine particles in discontinuous debris-flow deposits. An increase in fine particles within the discontinuously graded bed sediment led to a power-law decrease in the average permeability coefficient. With fine particle contents of 10% and 15% in the bed sediments, the final permeability coefficient consistently exceeded the initial value. However, this trend reversed when the fine particle contents were increased to 20%, 25%, and 30%. Lower fine particle contents indicated enhanced permeability efficiency due to more interconnected voids within the coarse particle skeleton. Conversely, an increase in fine particle content reduced the permeability efficiency, as fine particles tended to aggregate at the lower section of the seepage channel. An increase in coarse particle size decreased the formation of flow channels at the coarse–fine particle interface, causing fine particles to move slowly along adjacent or clustered slow flow channels formed by fine particles, resulting in decreased permeability efficiency. Three formulae are proposed to calculate the permeability coefficients of discontinuously graded bed sediments, which may aid in understanding the initiation mechanism of channel deposits. Based on experimental studies and field investigations, it is proposed that achieving sustainable development of debris-flow fans requires a practical approach that integrates three key components: spatial land-use planning, in situ monitoring of debris flows and the environment, and land-use adjustment and management. This comprehensive and integrated approach is essential for effectively managing and mitigating the risks associated with debris flows, ensuring sustainable development in vulnerable areas. [ABSTRACT FROM AUTHOR]

In mountainous areas, damage caused by debris flows is often aggravated by subsequent dam-burst floods within the main river confluence zone. On 30 August 2020, a catastrophic disaster chain occurred at the confluence of the Heixiluo Gully and Niri River in Ganluo County, southwest China, consisting of a debris flow, the formation of a barrier lake, and subsequent dam break that flooded the community. This study presents a comprehensive analysis of the characteristics of the two hazards and the resulting damage to buildings from the cascading hazards. The peak discharge of the debris flow in the gully mouth reached 1871 m3s-1. Following the dam break, the flood with a peak discharge of 2737 m3s-1 significantly altered the main river channel, causing a 4-fold increase in flood inundation compared to an ordinary flood. Three hazard zones were established based on the building damage patterns: (I) primary debris flow burial, (II) secondary dam-burst flood inundation, and (III) sequential debris flow burial and dam-burst inundation. Vulnerability curves were developed for Zone (II) and Zone (III) using impact pressures and inundation depths, and a vulnerability assessment chart is presented that contains the three damage categories. This research addresses a gap in the vulnerability assessments of debris flow hazard cascades and can support future disaster mitigation within confluence areas. [ABSTRACT FROM AUTHOR]

An increasing amount of landslides leading to significant human and economic consequences is a primary concern for the government of Tajikistan and local authorities. Based on the Committee on Emergency Situations data, from 1996 to 2018, there were 3460 emergencies and more than 1000 fatalities because of earthquake-triggered and rainfall-induced landslides in the region. In addition, landslides caused severe damage to houses and infrastructure facilities due to the population’s lack of landslide hazard knowledge. Therefore, current research focuses on developing a regional-scale landslide inventory map in the Hissar–Allay region, central Tajikistan, where the population density is much higher than at other mountainous territories. In recent decades, the enhancements in geographic information systems, the open access to high-resolution remote sensing data, and an extensive field survey allowed us to identify 922 landslides possible along the highway corridor in the Hissar–Allay region. Based on Varnes’s system, these landslides are classified into four categories: debris flows, rockfalls, shallow landslides, and complex (deep-seated) landslides, considering landslides morphology, geology, deformation of slopes, degree and aspect of slopes, and weathered and disintegrated zones on slopes in the study area. The results show that 8.24% of the total study area is affected by landslides. Along the highway corridor in the Hissar–Allay region there are 96 bodies of deep-seated landslides and 216 rockfall catchments, 273 debris flow catchments, and 313 shallow landslides. Thus, shallow landslides are the most frequent type of movement. In addition, landslide frequency-area distribution analysis shows that shallow landslides are frequent with an area of 1.88E+04 m2; most frequent debris flow channels have a place of 5.58E+05 m2; rockfalls, for its part, are rife with an area of 1.50E+05 m2, and frequent complex landslides have an area of 4.70E+06 m2. Furthermore, it was found out that slopes consist of Silurian formation comprise shales, pebbles, sands, loams, and limestones, metamorphic clays are exposed to landslides more than other geological formations because of the layered structure and their broad spatial distribution in the study area. As the first applied research to compile a landslide inventory map in the Hissar–Allay region on the regional scale, our study provides a sound basis for future explorations of landslide susceptibility, hazard, and risk assessment for this region.

Debris flows, as a special kind of landslides, often block rivers to form barrier dams and trigger a series of disasters such as upstream aggradation and outburst floods. The understanding of debris-flow barrier dams (DFBDs) is poor, mostly due to existing researches focusing on individual events and a lack of summarization of multiple DFBD events. The existing global or regional datasets of landslide barrier dams (LDs) contain only a few cases of DFBDs, and ignore the differences between DFBDs and other landslide barrier dams (LDs), such as the dams of rock slide, debris avalanche, or earth slide. To fill this gap, we reviewed 2519 literatures and media reports with high quality. Focusing on identified debris-flow damming events, a rigorous data review and validation process was conducted using Google Earth. A systematic approach was employed to prioritize conflicting information from various data sources. Consequently, a global dataset was compiled, encompassing 555 historical DFBDs from 1800 to 2023. This pioneering global dataset includes five categories and 36 attributes, detailing DFBDs. It captures basic information (location, the date of formation, etc.), dam characteristics (height, length, volume, etc.), lake characteristics (area, capacity, length), debris flow characteristics (velocity, discharge, volume, etc.), and failure characteristics (peak discharge, loss of life, etc.). Our dataset elucidates that DFBDs exhibit key features of instability, complete blockage, and overtopping failure. The number of such dams has notably increased, especially in China. 15 % of channels showed recurrent debris flows, resulting in DFBDs that make up 35 % of all DFBDs. Further analysis recommends the Ls (AHV) model is recommended for priority use, followed by the DBI model, for the stability assessment of DFBDs. Compared to other barrier dam datasets, our dataset is more targeted, lays a greater emphasis on the review of raw data, and stresses the unification of terminology and concepts (such as blockage modes and stability), ensuring the consistency and accuracy of the data. The dataset and results in this work may help to deepen the understanding of DFBD formation, distribution, and evolution. The DFBD dataset can be accessed through this link: https://doi.org/10.5281/zenodo.13382846 (Cheng et al., 2024). [ABSTRACT FROM AUTHOR]

In hydrology, accurate predictions and monitoring of river discharge are critical for river engineering, flood mitigation, water resource management and agricultural purposes. The Brahmaputra-Jamuna in Bangladesh, one of the highest discharge rivers in South Asia, is fundamental to the region’s socio-economic structure and a major driver of flooding. Hence, predicting discharge in this river is crucial for managing water resources, protecting infrastructures and minimizing flood risks. In this study, four machine learning models, namely, Random Forest (RF), Support Vector Machine (SVM), Gradient Boosting Regression Tree (GBRT), eXtreme Gradient Boosting (XGB) and their ensemble model were employed for weekly river discharge (Qt) prediction at Bahadurabad Transit. Weekly observed discharge and ERA5 reanalysis rainfall data with lag times from 1976 to 2022 were used for model calibration and validation. Various graphical and statistical evaluation metrics were employed to assess the model’s performance. The findings indicate Rt, Rt-1, Qt-1 is the most effective inputs in predicting discharge (r = 0.92). Individual and ensemble models have a very good performance (R2, NSE: 0.85 to 0.92), and the ensemble model outperforms RF by 4.55%, SVM by 8.24%, GBRT by 3.37% and XGB by 2.22%. For peak discharge simulation, the ensemble model shows the best performance (R2 = 0.94, NSE = 0.94, RMSE = 4013.11 m3/s and MAE = 2843.60 m3/s). The reliability analysis verified the ensemble’s superiority. The models in this study were efficient, adaptable and applicable for river discharge prediction in the Brahmaputra-Jamuna and other river gauge stations. [ABSTRACT FROM AUTHOR]

A larger antecedent effective precipitation (AEP) indicates a higher probability of a debris flow (Pdf) being triggered by subsequent rainfall. Scientific topics surrounding this qualitative conclusion that can be raised include what kinds of variation rules they follow and whether there is a boundary limit. To answer these questions, Jiangjia Gully in Dongchuan, Yunnan Province, China, is chosen as the study area, and numerical calculation, a rainfall scenario simulation, and the Monte Carlo integration method have been used to calculate the occurrence probability of debris flow under different AEP conditions and derive the functional relationship between Pdf and AEP. The relationship between Pdf and AEP can be quantified by a piecewise function. Pdf is equal to 15.88 %, even when AEP reaches 85 mm, indicating that debris flow by nature has an extremely small probability compared to the rainfall frequency. Data from 1094 rainfall events and 37 historical debris flow events are collected to verify the reasonability of the functional relationship. The results indicate that the piecewise functions are highly correlated with the observation results. Our study confirms the correctness of the qualitative description of the relationship between AEP and Pdf , clarifies that debris flow is a small-probability event compared to rainfall frequency, and quantitatively reveals the evolution law of debris flow occurrence probability with AEP. All the above discoveries can provide a clear reference for the early warning of debris flows. [ABSTRACT FROM AUTHOR]