Dadu River Basin Research Articles

Inventory and Spatial Distribution of Landslides on the Eastern Slope of Gongga Mountain, Southwest China

The eastern slope of Gongga Mountain is located in the mountainous region of Southwestern China, which has strong geologic tectonics that leads to frequent landslide hazards. A large number of such landslides were induced by the 2022 Luding Ms 6.8 earthquake. Therefore, it is necessary to identify the spatial distribution of landslides in the region. In this paper, the Google Earth platform and GF-1 and GF-6 satellite imagery were used to construct new pre-earthquake and co-seismic landslides. Then, we analyzed the relationship between the conditioning factors of the pre-earthquake and co-seismic landslide inventories and the spatial distribution of landslides, as well as the main controlling factors of landslide development. The main conclusions are as follows: (i) Through remote-sensing interpretation and field investigation, 1198 and 4284 landslides were recognized before and after the earthquake, respectively, and the scale was mainly small- and medium-sized. (ii) In two kinds of inventories, landslides are primarily distributed along the banks of the Dadu River basin, within elevations of 1200–1400 m and slopes of 30–50°. (iii) The distribution of pre-earthquake and co-seismic landslides was influenced by engineering geological layer combinations and earthquake intensity, with these two factors being the most significant. This paper plays an important role in hazard prevention and reconstruction planning in the Gongga Mountains.

Enhanced runoff simulation by precise capture of snowmelt variation signals with satellite-based snow products in a high-elevation basin

Hydrological models stand as a pivotal instrument for runoff simulation, while encountering notable uncertainties in output due to intricate terrain conditions and limited ground-based observations, especially in high-elevation basins. Leveraging satellite-based images presents a promising avenue for deciphering the hydrological model’s state variables. In pursuit of refining runoff simulation, this study developed a two-step enhancement strategy, which involved (1) calibrating snow-related parameters in the hydrological model using remotely sensed snow cover area (SCA) and snow water equivalent (SWE) and (2) capturing snowmelt runoff through the hydrological model and image-based products. Coupled with the Variable Infiltration Capacity (VIC) model, we adopted this strategy as a case study in the Dadu River Basin, China. The results indicated (1) the daily Nash-Sutcliffe Efficiency (NSE) of runoff simulation reached 0.84 by the enhancement strategy, markedly surpassing the strategy reliant on soil parameters with a single calibrated reference (daily NSE of 0.66), and exhibited comparability to the strategy incorporating snow parameters but calibrated solely based on observed discharge (daily NSE of 0.83). (2) the enhancement strategy demonstrated hydrological consistency with snowmelt information derived from imagery. Specifically, multi-year average contributions of model’s and image-based snowmelt calculations were 31.8% and 33.4%, respectively. Additionally, simulated dates of snow accumulation and ablation appeared an average deviation of approximately one week compared to the imagery results. This study elucidates a potential methodological approach for offering valuable insights into hydrological processes within analogous high-elevation basins globally.

Exploring the Spatiotemporal Evolution Patterns and Determinants of Construction Land in Mianning County on the Eastern Edge of the Qinghai–Tibet Plateau

Studying the spatiotemporal evolution and driving forces behind construction land amidst the intricate ecological and geological setting on the eastern edge of the Qinghai–Tibet Plateau offers invaluable insights for local sustainable development in a landscape transition zone and ecologically fragile area. Using construction land data from four phases, spanning 1990 to 2020, in Mianning County, this study employs methodologies like the Landscape Expansion Index (LEI) and land use transfer matrix to delineate the spatiotemporal evolution characteristics of construction land. A comprehensive set of 12 influencing factors across five categories—geomorphology, geological activity, climate, river and vegetation environment, and social economy—were examined. The Geographically Weighted Regression (GWR) model was then employed to decipher the spatial distribution pattern of construction land in 1990 and 2020, shedding light on the driving mechanisms behind its changes over the three decades. The research reveals distinct patterns of construction land distribution and evolution in Mianning County, shaped by the ecological and geological landscape. Notably, the Anning River wide valley exhibits a concentrated and contiguous development mode, while the Yalong River deep valley showcases a decentralized development pattern, and the Dadu River basin manifests an aggregation development mode centered around high mountain lakes. Over the study period, all three river basins witnessed varying degrees of construction land expansion, transitioning from quantitative expansion to qualitative enhancement. Edge expansion predominantly characterizes the expansion mode, complemented by leapfrog and infilling modes, accompanied by conversions from cropland and forest land to construction land. An analysis of the spatial pattern and drivers of construction land change highlights human-induced factors dominating the Anning River Basin, contrasting with natural factors prevailing in the Yalong River Basin and the Dadu River Basin. Future efforts should prioritize climate change considerations and environmental capacity, aiming for an ecologically resilient spatial pattern of construction land.

Understanding tectonics from fluvial topography by using the stochastic‐threshold incision model: Theory and application to the Dadu River basin, eastern Tibetan Plateau

AbstractThe flood distribution and bedrock incision threshold exert important influences on the erosion efficiency, which can result into a nonlinear scaling between channel steepness (normalized channel gradients for the downstream increases in drainage area) and erosion rates. Here, we explore the incorporation of both river incision threshold and discharge probability distribution into erosion efficiency to construct a stochastic‐threshold incision model equation to simulate river power incision and the evolution of fluvial topography. Assuming time‐dependent tectonic uplift, we develop a closed‐form analytical solution to the model equation and derive a linear inverse procedure to retrieve relative uplift rate history from river longitudinal profiles. Application of the inverse scheme to the Dadu River basin in the eastern Tibetan Plateau produces a history with three‐phase increases in the uplift/incision rates during the Cenozoic. We use the inversion results to forward the time‐changed river long profile, which indicates the existence of paleo relief before the Oligocene and significant contributions of the late Miocene regional uplift and early Pleistocene river capture on the present topography.

Identification Method of River Blocking by Debris Flow in the Middle Reaches of the Dadu River, Southwest of China

Debris flow is a typical natural disaster in the middle reaches of the Dadu River, which seriously threatens the safety of life and property of local residents. However, there is currently a lack of a comprehensive analysis methods applicable to the blockage of river channels by debris flow in the Dadu River basin, limiting disaster prevention and mitigation in this area. Based on previous large-scale model tests carried out in the middle reaches of the Dadu River, the debris flows are divided into dam-type debris flows and submerged debris flows. The calculation formulas for the maximum travel distance of the two kinds of debris flows entering the river are obtained via theoretical derivation. The formulas for calculating the length and volume of debris flow accumulation are derived, and the relationship between the debris flow loss coefficient and river blocking degree in the middle part of the Dadu River is analyzed. An identification method of river blocking by debris flow is put forward in this study. By calculating the maximum blocking degree, S (the ratio of the maximum driving distance of the debris flow to the width of the river), and the volume of the source materials needed to form a debris flow dam under the conditions that the debris flow does not reach the opposite bank (V1), reaches the opposite bank but does not block the river (V2), and reaches the opposite bank (V3), the form of debris flow blocking the river is distinguished. When S = 1, V > V3, complete blockage occurs; when S = 1, V > V2, the river is mostly blocked; when S < 1, V > V1, the river is half-blocked. This study established an identification method of river blocking by debris flow, providing a basis for early warning for river blocking and disaster prevention in the middle reaches of the Dadu River.

A comprehensive remote sensing identification model for ancient landslides in the Dadu river basin on the eastern margin of tibet plateau

A comprehensive remote sensing identification model for ancient landslides in the Dadu river basin on the eastern margin of tibet plateau

Spatial Morphological Characteristics of Ethnic Villages in the Dadu River Basin, a Sino-Tibetan Area of Sichuan, China

Analysis of spatial patterns and driving factors of different ethnic villages under regional integration is important for the conservation and development of ethnic villages. This article takes seven multi-ethnic villages in the Dadu River Basin of Ganzi Prefecture as an example; we employ a quantitative model of spatial syntax based on the theory of figure–ground relationship to link the tangible and intangible spaces. The results reveal the logical context and formation mechanism among the overall layout, residential architecture, and public space of the villages. The findings of this study are as follows: (1) The site of different ethnic villages reflects commonality. (2) The spatial configurations of the villages are significantly influenced by the surrounding natural environment, with significant differences. Cluster-concentrated villages exhibit the smallest expansion trend, rich spatial levels, and strong ethnic territoriality; strip-intensive villages have the largest scale and the strongest permeability; and radiation-dispersion villages have variable expansion directions and architectural relationships among residents. (3) Both of the participants’ selection behaviors and residential spaces constitute the internal structure for the ethnic culture, which is driven by the humanistic spirit and force of social order, making the spatial morphology a diversified and multi-layered characteristic. (4) The rural space has gradually changed from a single residential unit to a complex unit with multiple functions. The findings extend the scope of research to ethnic villages in watersheds and provide a theoretical and practical basis for the development of other similar rural villages.

Estimation of Shallow Landslide Susceptibility Incorporating the Impacts of Vegetation on Slope Stability

This study aimed to develop a physical-based approach for predicting the spatial likelihood of shallow landslides at the regional scale in a transition zone with extreme topography. Shallow landslide susceptibility study in an area with diverse vegetation types as well as distinctive geographic factors (such as steep terrain, fractured rocks, and joints) that dominate the occurrence of shallow landslides is challenging. This article presents a novel methodology for comprehensively assessing shallow landslide susceptibility, taking into account both the positive and negative impacts of plants. This includes considering the positive effects of vegetation canopy interception and plant root reinforcement, as well as the negative effects of plant gravity loading and preferential flow of root systems. This approach was applied to simulate the regional-scale shallow landslide susceptibility in the Dadu River Basin, a transition zone with rapidly changing terrain, uplifting from the Sichuan Plain to the Qinghai–Tibet Plateau. The research findings suggest that: (1) The proposed methodology is effective and capable of assessing shallow landslide susceptibility in the study area; (2) the proposed model performs better than the traditional pseudo-static analysis method (TPSA) model, with 9.93% higher accuracy and 5.59% higher area under the curve; and (3) when the ratio of vegetation weight loads to unstable soil mass weight is high, an increase in vegetation biomass tends to be advantageous for slope stability. The study also mapped the spatial distribution of shallow landslide susceptibility in the study area, which can be used in disaster prevention, mitigation, and risk management.

A 278-Year Summer Minimum Temperature Reconstruction Based on Tree-Ring Data in the Upper Reaches of Dadu River

In the context of global warming, climate change in river headwater regions and its drivers have attracted increasing attention. In this study, tree-ring width (TRW) chronology was constructed using tree-ring samples of fir (Abies faxoniana) in Dadu River Basin in the central part of the western Sichuan Plateau, China. Correlation analysis with climatic factors implies that the radial growth of trees in the region is mainly limited by temperature and has the highest correlation with the mean minimum temperature in summer (June and July) (R = 0.602, p < 0.001). On this basis, the TRW chronology was adopted to reconstruct variations in the mean minimum temperatures in summer from 1733 to 2010 in the upper reaches of Dadu River. The reconstruction equation was stable and reliable and offered a variance explanation rate of 36.2% in the observed period (1962~2010). In the past 278 years, the region experienced nine warm periods and ten cold periods. The warmest and coldest years occurred in 2010 and 1798, respectively, with values of 13.6 °C and 11.0 °C. The reconstruction was highly spatiotemporally representative and verified by temperatures reconstructed using other tree-ring data in surrounding areas. A significant warming trend was found in the last few decades. Moreover, the multi-taper method (MTM) analysis indicated significant periodic changes in quasi-2-year and 21–35-year periods, for which the El Niño Southern Oscillation (ENSO) and the Pacific decadal oscillation (PDO) could be the key controlling factors.

Landslide Monitoring along the Dadu River in Sichuan Based on Sentinel-1 Multi-Temporal InSAR

The Dadu River travels in the mountainous areas of southwestern China, one of regions with the most hazards that has long suffered from frequent geohazards. The early identification of landslides in this region is urgently needed, especially after the recent Luding earthquake (MS 6.8). While conventional ground-based monitoring techniques are limited by the complex terrain conditions in these alpine valley regions, space interferometric synthetic aperture radar (InSAR) provides an incomparable advantage in obtaining surface deformation with high precision and over a wide area, which is very useful for long-term and slow geohazard monitoring. In this study, more than 500 Sentinel-1 SAR images with four frames acquired during 2017~2022 were collected to detect the hidden landslide regions from the Jinchuan to Ebian Section along the Dadu River, based on joint-scatterer InSAR (JS-InSAR) and small baseline subset (SBAS) techniques. The results showed that our method could be successfully applied for landslide monitoring in complex mountainous regions. Furthermore, 143 potential landslide regions spreading over an 800 km area along the Dadu River were extracted by integrating the deformation measurements and optical images. Our study can provide a reference for large-scale geological hazard surveys in mountainous areas, and the InSAR technique will be encouraged for the local government in future long-term monitoring applications in the Dadu River Basin.

Intelligent operation and management in the Dadu River Basin

AbstractThe top priority of a hydropower enterprise is to secure the safe, scientific, and economic operation of its power stations. The Dadu River Basin, the fifth largest hydropower base in China, is definitely vital to the grid security and stability in southwest China's Sichuan Province. Given the challenges faced by production O&M (operation and management), efforts were made to put forth solutions featuring multielement business quantification, multisource data integration, and multitarget intelligent collaboration, according to which, through the development and application of a number of key technologies for intelligent operation, hard work was done to promote management optimization simultaneously and realize the smart and autonomous operation of the 10‐million‐megawatt power station group in the basin.

Digitalization and hydroinformatics

Digitalization and hydroinformatics

Debris flow susceptibility based on the connectivity of potential material sources in the Dadu River Basin

The Dadu River Basin (DRB) is an important economic corridor on the Chuanxi Plateau. The DRB is located in the highly changeable terrain of the eastern Qinghai-Tibet Plateau and is often threatened by debris flows. To mitigate the damage of debris flow disasters to the construction and operation of large infrastructures such as railways, roads and hydropower stations in the DRB, it is necessary to evaluate debris flow susceptibility. The connectivity of potential material sources (CPMS), which proxies the possibility of potential material transfer from the source to the outlet, was calculated using an improved index of connectivity, excess topography and brittle fracture index to identify and quantify debris flow susceptibility. The results show that the IC and the gully scale have a Logartihmic function in the DRB, in which IC decreases as the catchment area increases. In 3967 gullies of the Dadu River and its tributaries, the total connectivity of potential material sources (TCPMS) could be used to distinguish between debris flow gullies and non-debris flow gullies (AUC = 0.748). The TCPMS and average connectivity of potential material sources (ACPMS) were used to classify the scale and activity intensity of the 2398 debris flow gullies into four levels. The moderate- and high-activity intensity and large- and extra large-scale debris flows are mainly distributed in Danba, Luding and Kangding. The results of this study provide reference and evidence for the identification and evaluation of debris flow susceptibility.

Integrated flood risk assessment of river basins: Application in the Dadu river basin, China

Flood is the most common worldwide natural disaster with enormous impacts on human society and the ecosystem. Consequently, the research of flood risk assessment and zonation is critical. Its research scope is changeable, wherein the basin-scale research has become more and more important due to the increasing boom of cascade hydropower development in the river basin. The study proposed a basin-wide integrated flood risk assessment method combining index-based evaluation, Analytical Hierarchy Process (AHP) and Geographic Information System (GIS) technologies, which was implemented in the Dadu River basin, southwestern China to assess and zoning the basin flood risk. In the constructed risk assessment index system, we use extreme rainfall and dam breach to jointly describe the basin flood disaster-inducing factors and select flood control standard and flood routing coefficient as the sub-indicators of basic and specific coping capacity to characterize the flood intervention capacity of hydropower engineering. The results showed that, for the hazard, vulnerability and risk zonation maps with five classified levels, the southern of midstream and downstream of the basin are prone to frequent floods, while higher vulnerability levels mainly concentrate in the downstream but some parts scatter in the medium vulnerability zone. The high and very high risk zones account for 3% of the basin area and mainly concentrate in the southern basin, while 86% of the basin area is assigned as low and very low risk zones. The results of this work quantitatively express the spatial distribution characteristics of basin-wide flood hazard, vulnerability and risk, and provide a reference for practicing an integrated and efficient flood risk management, and disaster prevention and alleviation strategies.

Simulation of hydraulic power matching–based risk and economic evaluation among cascade hydropower stations in spot transactions

The electricity market is evolving rapidly from pre-bid to spot markets, where the transactions between producers and consumers have become crucial and are vulnerable to safety risks. In addition, the new modes of transaction are also becoming popular and are said to have some risks. To reveal the impact of the new electricity transaction mode—spot market—on the safety risk and generation benefit, this article presents a simulation method connecting the transaction results and operation process. To verify the effectiveness of the proposed method, an actual cascade hydropower station (CHS) in the Dadu River basin, Southwestern China, which comprises eight hydropower stations, is selected. Hydraulic power matching among the CHSs is discriminated from four aspects with multiple indicators combined with the reality of a hydropower-dominated market in Sichuan, China. The dispatching decision-making process of hydropower generators is described with a multi-objective optimization model and then solved with a fast search strategy based on the classical output calculation method in hydrology. The security risks and economic damage hidden in the day-ahead market on a certain day are discovered and analyzed. The technology proposed provides support for bidding decisions in spot transactions and satisfies the reality during the transition period of electricity reform.

Flood hazard zone mapping incorporating geographic information system (GIS) and multi-criteria analysis (MCA) techniques

Flood is one of the most common natural disasters worldwide and has caused serious harm to humans, socio-economy and the environment. Identification and classification of flood hazard areas is therefore essential for flood management and risk decision-making which attempt to combat this challenge. This study selected eleven flood hazard conditioning factors as evaluation criteria, integrated geographic information system (GIS) with three multi-criteria analysis (MCA) techniques, viz. the analytical hierarchy process (AHP), technique ordered preference by similarity to the ideal solution (TOPSIS), and ordered weighted averaging (OWA), to form a GIS-MCA framework for analyzing the spatial distribution of flood-prone areas. Its application in the Dadu River basin, China derived a total of eleven flood hazard maps across the basin, and their analysis and comparison results demonstrated the spatial distributions of flood-prone areas based on various GIS-MCA approaches and their overlap situations, and indicated that hazard class distribution patterns of the AHP, TOPSIS, and OWA (α = 1) maps are similar, and Luding, Yuexi and their nearby areas are the highest hazard zones, where should be concerned on firstly under the condition of limited resources. To validate the three MCA methods, the AHP, TOPSIS, and OWA (α = 1) maps were compared with the historical flood disaster ranges. The verification results exhibited that the largest proportion of historical flood disaster ranges fell into the high and highest hazard levels in the three maps, and shown the resultant flood hazard maps are scientific, rational and consistent with the actual situation. The GIS-MCA approach is a powerful and feasible guidance tool for conducting flood disaster management studies, and a reference for future more efficient flood management and risk decision-making in the basin.

Assessing and mapping human well-being for sustainable development amid drought and flood hazards: Dadu River Basin of China.

Drought and flood are two of the most destructive natural disasters with the most significant impact and greatest losses in the Dadu River basin (DRB). However, their impacts on people's life have not attracted enough attention from scholars. In this study, the Standardized Precipitation Index (SPI) describing the drought/flood situation and the Composite Index of Human Well-being (CIHW) are calculated, and a framework is further constructed to assess the impacts of drought and flood disasters on human well-being in the DRB. The results show that the annual and seasonal SPI in the DRB generally exhibit an increasing trend in fluctuations during 2000-2009, indicating a wetting climate in this basin. Overall, the upper reaches of the DRB have experienced an evolution of flood-drought-flood state transition, where the variation amplitude of the SPI in the western sub-basin is greater than that in the eastern sub-basin. In addition, the lower reaches of the DRB have suffered more dramatic and periodic changes from the drought/flood disasters in terms of the SPI. For human well-being during 2000-2019, Maerkang City in the upper reaches, Kangding City in the middle reaches, and Shimian County in the lower reaches of the DRB are at a relatively higher level, with the CIHW decreasing from administrative centers to the around. Moreover, the CIHW over the whole basin increases gradually from 2000 to 2019. The SPI has significantly negative effects on different capitals, following a descending order of financial, social, physical, human and natural capitals. The counties of the basin are divided into four groups, namely the group with high disaster risks and high human well-being, the group with high disaster risks and low human well-being, the group with low disaster risks and high human well-being, and the group with low disaster risks and low human well-being. The panel regression results suggest that the construction of water conservancy facilities, the financial inputs in agriculture and meteorology, and the educational level have positive impacts on human well-being, but the impacts differ from different groups. The construction of water conservancy facilities has highly significant impacts on human well-being in all groups; the education level has no significant impact on the group with high disaster risk and high human well-being, which has not passed the significance test; while the financial inputs in agriculture and meteorology have relatively higher impacts on the whole basin and on the group with low disaster risk and low human well-being compared with other groups. Therefore, it is suggested that the negative impacts of drought and flood disasters can be mitigated through strengthening infrastructure construction, responding appropriately to climate change, avoiding disasters at the source of major projects and improving the disaster prevention and mitigation systems.

An efficient online outlier recognition method of dam monitoring data based on improved M-robust regression

Common anomaly recognition methods are easy to misjudge and miss outliers for the online monitoring data. This is a bottleneck problem that needs to be overcome in dam safety management moving toward informatization. Based on the data of nine hydropower stations along Dadu River Basin, this paper analyzed existing problems of the common anomaly identification method and an algorithm was proposed based on improved M-robust regression recognition. In this algorithm, the AR factor was introduced to avoid the defect that the traditional model cannot simulate random variables. The extreme value method and robust estimation were utilized to avoid the leverage effect. The model collapse caused by maximum measured value was avoided through improving the residual calculation model of M-robust and optimizing the weight distribution function. The maximum of the three values, residual quartile difference, discrete quartile difference, and measurement accuracy, was used as an anomaly recognition criterion to improve the evaluation criteria. The algorithm compiled was used in the Dadu River Company since 2017. The statistics showed that for the 150,000 measured values per day, the evaluation time could be within 15 min, the missed judgment rate was 0%, and the misjudgment rate was less than 2%. The proposed algorithm achieved a great improvement and can meet the needs of online outlier recognition in dam safety management.

Calculation of dam risk probability of cascade reservoirs considering risk transmission and superposition

Because of the risk transmission and superposition among dams in cascade reservoirs, the analysis and probability calculation of dam risk become more complex compared with a single reservoir. By analyzing the main risk sources and actionmechanisms, the disaster-causing factors, disaster-transmitting body and disaster-bearing body in the cascade reservoirs system were determined. By defining the influence coefficient (IC) to express the transmission and superposition degree of dam risk among cascade reservoirs, dam risk was divided into two parts: own risk (OR) and additional risk (AR). On this basis, the relevant concepts and equations for the calculation of the dam risk probability of cascade reservoirs were proposed. The numerical simulation was carried out to quantify the IC, and a Bayesian network analysis model was constructed to calculate the OR. Finally, taking five cascade reservoir dams in the Dadu River basin as examples, the value of their ORs, ARs and risk probabilities were calculated, and thereafter the weakest cascade, controlling cascade and general cascade in the system were divided. The proposed methodology realizes an effective connection with the dam risk calculation method of a single reservoir, which can provide a reference for the risk assessment and management of cascade reservoirs in the basin.

A self-matching model for online anomaly recognition of safety monitoring data in dams

The online anomaly recognition of real-time dam safety monitoring data, such as deformation and seepage data from the automatic sensing instruments (e.g., the osmometer and the multi-point displacement meter), has the premise of ensuring data reliability, and it is also one of the core functional modules of online dam safety monitoring. To compensate for the limitation of a single method to identify outliers and further improve the reliability and the rapidity of the anomaly recognition of dam safety monitoring data, a self-matching model based on data-types for online anomaly recognition (SMM) was proposed in this paper. Based on a detailed classification of dam safety monitoring data sequences, this article describes a comparison and analysis of the applicability of a statistical regression model based on the least-squares regression (LSR) model and the online robust recognition and early warning (RREW) model for different datatype sequences. For the single-step-type sequences and normal-type sequences with low fitting accuracy, which could not be completely identified by the two models above, an improved cloud model recognition method based on the diurnal variation rate (ICM) was proposed to compensate for the limitations. Finally, the SMM was determined, that is, the LSR model was used for the multi-point-outlier-type and normal-type sequences with high fitting accuracy, the RREW model method was used for the double-step-type and oscillatory-type sequences, and the ICM method was used for the single-step-type sequences and normal-type sequences with low fitting accuracy. The engineering application of the Dadu River Basin showed that this method effectively solved the problems of low calculation efficiency and a 2% misjudgment rate when using the RREW model alone, and this method greatly improved the accuracy and timeliness of the anomaly recognition of dam safety monitoring data, so it had important theoretical significance and engineering application value.