Catena最新文献

{"title":"Differential response of soil characteristics and extracellular enzyme activities along an altitude gradient in a subtropical forest ecosystem, eastern China","authors":"Ziqing Xu ,&nbsp;Xuefeng Xie ,&nbsp;Qi Shao ,&nbsp;Lijie Pu ,&nbsp;Michael Meadows ,&nbsp;Zhenyi Jia ,&nbsp;Xiaoyi Shi ,&nbsp;Zhenzhen Zhang ,&nbsp;Tao Wu ,&nbsp;Fei Xu","doi":"10.1016/j.catena.2025.109132","DOIUrl":"10.1016/j.catena.2025.109132","url":null,"abstract":"<div><div>Variations in altitude profoundly affect soil characteristics and extracellular enzyme activities (EEAs) due to the distinct vertical zonation of mountains. However, understanding the nature and strength of the interactive linkages among soil characteristics, C:N:P stoichiometry, and EEAs along altitudinal gradients in subtropical forest ecosystems remains elusive. Here, we designed an altitude gradient that covered five altitude levels on Tianmu Mountain, located in the transition zone between the central and northern subtropics, eastern China. This study explores how the soil characteristics and EEAs vary with altitude and aims to clarify the nature and strength of the interactive linkages among soil characteristics, C:N:P stoichiometry, and EEAs along an altitude gradient. Soil sand ratio, soil water content (SWC), electrical conductivity (EC), soil organic carbon (SOC), total nitrogen (TN), protease (PRO), urease (URE), and acid phosphatase (ACP) activities exhibited fluctuating upward trends with increasing altitude, peaking at the 1500 m asl. Conversely, silt ratio and pH levels demonstrated a downward trajectory, reaching their nadir at the same altitude. Meanwhile, the clay ratio, ammonium, and nutrient stoichiometric ratio initially increase but then decline with their highest value at 800 m or 1000 m. On the contrary, soil nitrate and total phosphorus (TP), first decrease and then increase again with increasing altitude, reaching their lowest value at 1000 m and 800 m, respectively. Soil catalase (CAT) and invertase (INV) activity exhibited a pronounced upward surge followed by a stabilization as altitude increased. Moreover, the altitude-dependent differences in the soil EEAs were primarily affected by SOC, SWC, TN, sand, silt, and pH, with explained variation higher than 30 % (<em>P</em> &lt; 0.01). Overall, this study demonstrates a clear altitude effect on soil characteristics and EEAs, and the alterations in soil characteristics across altitudes are essential in shaping the soil EEAs in subtropical forest ecosystems.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"256 ","pages":"Article 109132"},"PeriodicalIF":5.4,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143916466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Different response patterns of vegetation to environmental changes during the mid-to-late Holocene: Pollen evidence from an alpine lake in Western Sichuan Province, southwestern China","authors":"Changting Chi ,&nbsp;Xiayun Xiao ,&nbsp;Baoyan Jia ,&nbsp;Yanling Li ,&nbsp;Hua Zhang ,&nbsp;Xiangdong Yang","doi":"10.1016/j.catena.2025.109117","DOIUrl":"10.1016/j.catena.2025.109117","url":null,"abstract":"<div><div>Understanding long-term vegetation responses to environmental change is essential for predicting ecosystem resilience under future climate scenarios. We used high-resolution mid-to-late Holocene pollen records from an alpine lake in southwestern China to reconstruct vegetation dynamics over the past ∼ 5000 years, revealing distinct response patterns between alpine shrub–herb communities and forests. Results showed that alpine shrub–herb vegetation, highly sensitive to climate fluctuations, exhibited increasing turnover rates after 4410 cal. yr BP, whereas tree vegetation gradually stabilized before ∼ 3000 cal. yr BP. After 500 cal. yr BP, turnover rates accelerated in both shrub–herb communities and forests, with intensified variability in forests and declining coverage in shrub–herb communities, likely driven by climate cooling and intensified human activity. Principal Component Analysis (PCA) results indicated that temperature primarily controlled coverage of shrub–herb communities, while precipitation mediated tree abundance variations. Structural Equation Modeling (SEM) identified CO₂ and precipitation as the dominant drivers of shrub and herb community turnover rates, whereas forest turnover rates responded mainly to temperature. Crucially, shrub–herb communities, with higher turnover rates and a stronger contribution to species richness, responded more rapidly to climatic shifts, whereas forests influencing species evenness provided long-term ecosystem stability. These findings offer novel insights into vegetation change mechanisms and enhance understanding of mountain ecosystem resilience under environmental change.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"256 ","pages":"Article 109117"},"PeriodicalIF":5.4,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143921759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of land use and landscape pattern on legacy nitrogen pollution in a typical watershed in eastern China","authors":"Yucang Wang ,&nbsp;Hao Wu ,&nbsp;Zheqi Pan ,&nbsp;Longdan Ma ,&nbsp;Yu Zhang ,&nbsp;Jia Zhou ,&nbsp;Minpeng Hu ,&nbsp;Zhihan Cheng ,&nbsp;Xin Zheng ,&nbsp;Dingjiang Chen","doi":"10.1016/j.catena.2025.109129","DOIUrl":"10.1016/j.catena.2025.109129","url":null,"abstract":"<div><div>Legacy effects from nonpoint source nutrient pollution reduce the effectiveness of nitrogen remediation strategies in watersheds, yet spatial landscape variations and their influence on the legacy effects remain unclear. This study addressed spatial differences in legacy nitrogen pollution within the Yongan watershed in eastern China using detrended fluctuation analysis (where H &gt; 0.5 indicates a legacy effect). Results revealed strong legacy effects for total nitrogen (TN) and nitrate nitrogen (NO₃^–-N) at the watershed outlet, with H values of 0.70 and 0.87, respectively, primarily influenced by soil nitrogen contributions (40 ± 8 %), as revealed by isotopic source apportionment. Significant spatial variation in the legacy effect was observed across different catchments, with H-index ranging from 0.42 to 0.85 for TN and from 0.58 to 0.91 for NO₃^–-N. Land use explained 90 % of this variation, predominantly driven by<!--> <!-->grasslands (48 %), impervious surfaces (16 %), and orchards (14 %). Grasslands were found to reduce legacy effects by reducing nitrogen inputs from soil and groundwater, whereas impervious surfaces reduced the legacy effect by increasing domestic wastewater contributions. Conversely, agricultural lands (orchards, paddy fields and drylands) exacerbated the legacy effect through elevated soil nitrogen contributions. Threshold values for key landscape metrics were identified that effectively mitigated the legacy effect: increasing grassland edge density (ED) to 0.16 km/km², orchard connectivity (CONNECT) to 32 %, and impervious surface aggregation (AI) to 91 %. The integration of stable isotopes and landscape data provides a robust framework for identifying dominant nitrogen sources and uncovering the spatial mechanisms underlying legacy pollution. These findings can guide landscape management strategies and support targeted interventions for nonpoint source nitrogen control at the watershed scale.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"256 ","pages":"Article 109129"},"PeriodicalIF":5.4,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143916464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An enhanced soil salinity estimation method for arid regions using multisource remote sensing data and advanced feature selection","authors":"Aihepa Aihaiti ,&nbsp;Ilyas Nurmemet ,&nbsp;Xinru Yu ,&nbsp;Yilizhati Aili ,&nbsp;Shiqin Li ,&nbsp;Xiaobo Lv ,&nbsp;Yu Qin","doi":"10.1016/j.catena.2025.109116","DOIUrl":"10.1016/j.catena.2025.109116","url":null,"abstract":"<div><div>Accurate soil salinity monitoring is crucial for sustainable soil use and management. While most existing studies rely on optical remote sensing for salinity estimation, the potential of polarimetric synthetic aperture radar (PolSAR) data, particularly its polarimetric decomposition characteristics, remains underexplored. This study focuses on the Yutian Oasis in southern Xinjiang, China, to investigate the potential of PolSAR data for estimating soil salinity in arid regions through the integration of multi-source remote sensing data (including RADARSAT-2 C-band SAR, Sentinel-2, and topographic data). From the multi-source dataset, 121 features were extracted, and correlation analysis identified 52 variables significantly correlated (<em>P</em> &lt; 0.05) with soil electrical conductivity (EC). These variables were then further screened using three feature selection algorithms: Recursive Feature Elimination (RFE), Boruta, and Variable Importance in Projection (VIP), to mitigate high-dimensionality and collinearity. Subsequently, three machine learning models—Multi-Layer Perceptron (MLP), Random Forest (RF), and Extreme Gradient Boosting (XGBoost)—were employed to construct soil salinity inversion models. The results revealed that the Boruta-MLP model outperformed other strategies in both the calibration and validation phases, demonstrating strong generalization capabilities. For validation, the Boruta-MLP model achieved an R² of 0.819, with RMSE and MAE values of 5.767 and 3.800, respectively. Variable sensitivity analysis indicated that key SAR features—including the backscatter cross-polarization ratio (σ⁰_VV/σ⁰_VH), radar vegetation index (RVI_σ⁰), and volume scattering index (VSI_σ⁰)—along with SAR polarimetric decomposition components (Alpha, Entropy, MF4CF_theta_FP) and texture features (Contrast_σ⁰_VH, Dissimilarity_σ⁰_VH, and Homogeneity_σ⁰_VH), play crucial roles in soil salinity estimation. This research underscores the critical role of SAR data and advanced feature selection in soil salinity estimation, offering a robust framework for arid region salinity mapping through multi-source data integration and machine learning optimization.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"256 ","pages":"Article 109116"},"PeriodicalIF":5.4,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143916465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A framework for fusing transfer learning and meta-learning for enhanced soil thickness prediction in unsampled areas","authors":"Zhenghai Xue ,&nbsp;Xiaoyu Yi ,&nbsp;Wenkai Feng ,&nbsp;Linghao Kong ,&nbsp;Shuangquan Li ,&nbsp;Jiachen Zhao ,&nbsp;Xuefeng Tang","doi":"10.1016/j.catena.2025.109125","DOIUrl":"10.1016/j.catena.2025.109125","url":null,"abstract":"<div><div>Soil thickness is a crucial parameter that affects surface processes and environmental evolution. Its spatial distribution characteristics hold significant guiding importance in various fields. However, existing soil thickness prediction methods have significant limitations in cross-regional applicability, restricting their widespread use. To address this challenge, this study introduces a model framework based on the combination of feature transfer and <em>meta</em>-learning (MTL) to predict soil thickness in unsampled areas. We select two geologically similar regions in the southeastern hills of China as the study areas. After verifying the linear independence of the environmental covariates between the source and target domains, transfer component analysis (TCA) is applied to align their covariate distributions. A prediction model is then constructed by integrating the model-agnostic <em>meta</em>-learning (MAML) algorithm to predict the spatial distribution of soil thickness in the target domain. Comparative analysis reveals that the MTL model outperforms traditional multiple layer perceptron (MLP), transfer learning (TL), and <em>meta</em>-learning (ML) models, achieving a root mean square error (RMSE) of 14.06 cm and a coefficient of determination (R²) of 0.725. Additionally, the predicted spatial distribution of soil thickness aligns more closely with actual conditions. The transfer learning and <em>meta</em>-learning fusion framework proposed in this study provides a valuable reference for soil thickness prediction in unsampled areas.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"256 ","pages":"Article 109125"},"PeriodicalIF":5.4,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143911461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Meta-analysis shows global water availability thresholds for the contents of soil organic carbon and its fractions are only partly affected by nitrogen addition","authors":"Yifei Peng ,&nbsp;Jianghuan Qin ,&nbsp;Weixue Luo ,&nbsp;Lu Yang ,&nbsp;Mathias Mayer","doi":"10.1016/j.catena.2025.109130","DOIUrl":"10.1016/j.catena.2025.109130","url":null,"abstract":"<div><div>Soils are the largest terrestrial reservoir of organic carbon, with water availability creating a global threshold for soil organic carbon (SOC) sequestration. Nitrogen (N) deposition is known to affect SOC, but its potential to shift global water availability thresholds for the contents of SOC and its particulate, mineral-associated and microbial fractions remain unclear. Here, we synthesized 2529 paired observations from 339 global N addition studies conducted in surface soil (0–20 cm) to investigate these effects under different water availability conditions, defined by the ratio of precipitation to potential evapotranspiration. Our results show that although nitrogen addition does not alter the water availability threshold for SOC, it significantly increases SOC content, particularly below the threshold, with an increase of 4.62 % below and 2.66 % above the threshold. Similarly, nitrogen does not affect the water availability thresholds for mineral-associated organic carbon and microbial biomass and necromass carbon. Nitrogen addition also increases microbial necromass carbon by 18.2 %, particularly bacterial necromass carbon, while having no significant effect on fungal necromass carbon. In contrast, nitrogen addition lowers the threshold for particulate organic carbon and increases its content by a total of 19.2 %. This differential response likely reflects a closer coupling of particulate organic carbon with plant litter inputs whereas mineral-associated organic carbon is more closely linked to microbial processing and transformation of organic matter. Overall, most SOC fractions showed a water availability threshold around 0.5, indicating that abrupt changes in SOC content may occur when precipitation drops below 50 % of an ecosystem’s evapotranspiration demand. Our results highlight how water availability and N addition interact to shape SOC fractions, offering key insights into SOC responses to global environmental change. Understanding these mechanisms is essential for predicting future SOC stocks and climate feedbacks under increasing N deposition and shifting precipitation patterns.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"256 ","pages":"Article 109130"},"PeriodicalIF":5.4,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143916613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding the hydrological valley landscape: A multi-scenario adaptive framework for delineating valley floors","authors":"Wenjie Sun ,&nbsp;Yang Chen ,&nbsp;Xingyu Zhou ,&nbsp;Xin Yang ,&nbsp;Junfei Ma ,&nbsp;Sijin Li ,&nbsp;Guoan Tang","doi":"10.1016/j.catena.2025.109111","DOIUrl":"10.1016/j.catena.2025.109111","url":null,"abstract":"<div><div>As critical zones in fluvial geomorphology shaped by hydrological processes, valley floors play an essential role in material exchange and circulation between upland and groundwater bodies. Accurate delineation of valley floors is crucial for understanding river morphology, analyzing the spatial distribution of valley floor sediments, and maintaining the riverine ecosystem. However, existing delineation methods often rely heavily on manual interpretation, are limited in regional applicability, and require subjective parameter selection. This underscores the need for a method that incorporates adaptive thresholding and ensures broad applicability across diverse regions. In response to this challenge, we develop a multi-scenario adaptive framework for delineating valley floors. This framework designs several indicators for detecting topographical cross-sectional and longitudinal features, which enables the accurate and automated extraction of valley floor boundaries through adaptive thresholding. The framework includes the following components: (1) The initial drainage network was extracted by setting drainage thresholds based on geomorphological texture features obtained using the gray-level co-occurrence matrix (GLCM); (2) The drainage network generated in the previous step was filtered by calculating the average river gradient and setting adaptive parameters, removing drainage networks located in steep valleys; (3) The valley floor extent was adaptively extracted by proposing terrain factors such as slope accumulation and its variation. The experimental results demonstrate<!--> <!-->that this method applies<!--> <!-->to the extraction of valley floors in various landscape types, exhibiting<!--> <!-->remarkable precision. This study also explored the correlation between valley floor, geological sedimentation, and surface hydrological processes, finding a significant consistency between sediment distribution and valley floor<!--> <!-->extent. These findings offer valuable perspectives on valley floor evolution, river restoration, and sustainable water resource management.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"256 ","pages":"Article 109111"},"PeriodicalIF":5.4,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143911462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Climate dynamics during the last 3000 years forced environmental and sedimentation changes in southern Spain: The Laguna Grande de Archidona record","authors":"Gonzalo Jiménez-Moreno ,&nbsp;Antonio García-Alix ,&nbsp;Fernando Gázquez ,&nbsp;Aurora Castillo-Baquera ,&nbsp;Lucía Martegani ,&nbsp;Miguel Rodríguez-Rodríguez ,&nbsp;Marta Rodrigo-Gámiz ,&nbsp;Francisco J. Jiménez-Espejo","doi":"10.1016/j.catena.2025.109123","DOIUrl":"10.1016/j.catena.2025.109123","url":null,"abstract":"<div><div>A geochemical, mineralogical, and sedimentological analysis of the sedimentary record from Laguna Grande de Archidona (LGA), a lake in southern Spain, produced a high-resolution climate and human activity record for the southwestern Mediterranean over the past three millennia. Lake level changes, organic matter, and gypsum intervals were primarily driven by precipitation and hydrological shifts. From 3300 to 2600 cal yr BP, dry conditions prevailed, particularly from 3050 to 2600 cal yr BP, coinciding with a regional drought tied to a positive North Atlantic Oscillation (NAO). The wettest period, from 2600 to 1400 cal yr BP during the Iberian Roman Humid Period (IRHP), was marked by increased groundwater and lake stratification due to negative NAO, which generated the precipitation of gypsum and manganese oxides. However, this relatively wetter period was interrupted by two arid events between 2300–2200 and 2150–2050 cal yr BP. A dry phase spanned the Dark Ages through the Medieval Climate Anomaly (MCA; 1400–700 cal yr BP), while the Little Ice Age (LIA) showed varied but generally wetter conditions, followed by an arid period from ∼1600–1850 CE. The Industrial Epoch (1850–1957 CE) also saw dryness, with late 20th-century changes attributed to modern climate impacts and irrigation practices.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"256 ","pages":"Article 109123"},"PeriodicalIF":5.4,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143911460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Late Holocene linkages between soil erosion, phosphate bioavailability and lake productivity in Central Africa","authors":"Alexandrine N’nanga ,&nbsp;Germain Bayon ,&nbsp;Mathilde Levacher ,&nbsp;Anne Trinquier ,&nbsp;Flavio S. Anselmetti","doi":"10.1016/j.catena.2025.109126","DOIUrl":"10.1016/j.catena.2025.109126","url":null,"abstract":"<div><div>Major vegetation shifts and large-scale erosion events occurred in Central Africa during the late Holocene in response to hydroclimate change and enhanced land use related to the Bantu expansion. On the Adamawa Plateau, a highland in Central Cameroon that experienced abrupt forest collapse about 3000 years ago, recent works showed that lake primary productivity markedly increased during the same period. Yet, the causes of increased productivity in Adamawa plateau lakes and its link to the Central African rainforest crisis still remain unclear. To address this issue, we investigated lake sediment records from this region, using radiogenic isotope proxies for sediment provenance and chemical weathering to complement previously published mineralogical and organic geochemistry data. Our results indicate that increased biological productivity in Adamawa Plateau lakes was linked to enhanced erosion of highly weathered lateritic soils. An examination into possible causes leads us to propose that phosphate desorption following erosion of kaolinite, iron (goethite) and aluminium (gibbsite) oxide-bearing soils may have played a key role in stimulating lake productivity at that time, together with degradation of terrestrial organic matter. These findings emphasize the importance of deforestation and land use on soil-P cycling and lake ecosystems in tropical regions during the Holocene.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"256 ","pages":"Article 109126"},"PeriodicalIF":5.4,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143911704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combination of statistical and conceptual approaches for debris-flow susceptibility modelling at a regional scale, British Columbia, Canada","authors":"Txomin Bornaetxea ,&nbsp;Andrée Blais-Stevens ,&nbsp;Brendan Miller ,&nbsp;Ivan Marchesini","doi":"10.1016/j.catena.2025.109044","DOIUrl":"10.1016/j.catena.2025.109044","url":null,"abstract":"<div><div>This paper describes the data and methodological approaches used to assess the initiation and runout susceptibility of debris-flows in the Valemount area, east-central British Columbia, Canada. Debris-flows are frequent in this area and have impacted the roads and dwellings. The study area covers about 1200 km². A landslide inventory for this area delineates past debris-flows, including their source areas and deposits. This inventory includes hillslope and channelized debris-flows, enabling the development of separate models for each type of event. For hillslope debris-flows, a supervised multivariate regression technique was used to identify possible initiation zones. Subsequently, a conceptual model was trained and applied to simulate runout and classify areas according to runout susceptibility.</div><div>Modeled hillslope debris-flow deposits reaching the main valley channels were considered as a proxy for potential source areas for channelized debris-flows, even though source sediments may also result from other processes, including gradual erosion or mass movements from adjacent slopes. Conceptual modelling was then applied to this second type as well. The results of the two models were combined to classify the area according to its predisposition to debris-flow runout. Debris-flow datasets other than those used to train the models, were used to optimize and validate the models. Results indicate that, considering both debris-flow types, there is a 75 % of agreement between the modeled susceptible areas and the validation debris-flow fans. This suggests that the models can effectively distinguish between potential debris-flow fan areas and non-debris-flow areas.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"256 ","pages":"Article 109044"},"PeriodicalIF":5.4,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143911703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}