Assessment of runoff composition and residence time using stable isotopes and hydrochemical characteristics in Urumqi River Basin, northwest China

Journal of Hydrology Regional Studies, Journal Year: 2025, Volume and Issue: 57, P. 102174 - 102174

Published: Jan. 8, 2025

Language: Английский

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Analysis of Hydrochemical Characteristics and Hydraulic Connections in the Middle and Upper Reaches of the Urumqi River, Northwest China

Published: Jan. 1, 2024

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Language: Английский

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Is There Difference in Lsm Based on Explainable Machine Learning from the Perspective of Different Slope Unit Scales?

Published: Jan. 1, 2024

This study endeavors to assess the performance of landslide susceptibility models and differences in factors across various slope unit scales. Initially, we curated a geospatial dataset comprising 3594 historical events 22 initial factors. Subsequently, 30 sets schemes were generated based on different parameter combinations. These datasets trained tested 7:3 ratio using random forest (RF) model, resulting accuracy values ranging from 0.686 0.812 AUC 0.770 0.884. In addition, model optimization was facilitated GridSearchCV (GS), generation mapping (LSM) for three representative scenarios. Lastly, decision-making mechanism at scales elucidated explainable artificial intelligence (XAI). Key findings elucidate: (1) The scale has profound effect efficacy models, with smaller minimum area thresholds improving but cost increased computational time. (2) Overly homogeneous units prove inadequate encapsulating intricacies real-world terrain slopes, thereby precipitating diminished accuracy. (3) optimized scheme may enhance hyperparameter is somewhat more appropriate XAI models. Wise selection optimal cell key training machine learning-based superior performance.

Language: Английский

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Hydrological processes in the Aksu River source region during the intense ablation period based on water chemistry and isotopes

Journal of Geographical Sciences, Journal Year: 2024, Volume and Issue: 34(11), P. 2111 - 2127

Published: Nov. 1, 2024

Language: Английский

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