Understanding the hydrological valley landscape: A multi-scenario adaptive framework for delineating valley floors

IF 5.4 1区 农林科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY
Wenjie Sun , Yang Chen , Xingyu Zhou , Xin Yang , Junfei Ma , Sijin Li , Guoan Tang
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引用次数: 0

Abstract

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.
理解水文流域景观:描绘河谷底的多情景自适应框架
作为水文过程形成的河流地貌的关键地带,河谷底在山地和地下水体之间的物质交换和循环中起着至关重要的作用。准确圈定河谷底面对了解河流形态、分析河谷底面沉积物空间分布、维护河流生态系统具有重要意义。然而,现有的圈定方法往往严重依赖人工解译,区域适用性有限,且需要主观选择参数。这强调需要一种结合自适应阈值的方法,并确保在不同地区的广泛适用性。为了应对这一挑战,我们开发了一个多场景自适应框架来描绘谷底。该框架设计了几个用于检测地形横截面和纵向特征的指标,通过自适应阈值法可以准确、自动地提取谷底边界。该框架包括以下几个部分:(1)基于灰度共生矩阵(GLCM)获得的地貌纹理特征,通过设置排水阈值提取初始排水网络;(2)通过计算平均河流坡度并设置自适应参数对上一步生成的水系网进行过滤,去除位于陡峭山谷的水系网;(3)提出坡度累积及其变化等地形因子,自适应提取谷底范围。实验结果表明,该方法适用于各种景观类型的谷底提取,具有较高的提取精度。本研究还探讨了谷底、地质沉积和地表水文过程之间的相关性,发现泥沙分布与谷底范围之间存在显著的一致性。这些发现为谷底演变、河流恢复和可持续水资源管理提供了有价值的视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Catena
Catena 环境科学-地球科学综合
CiteScore
10.50
自引率
9.70%
发文量
816
审稿时长
54 days
期刊介绍: Catena publishes papers describing original field and laboratory investigations and reviews on geoecology and landscape evolution with emphasis on interdisciplinary aspects of soil science, hydrology and geomorphology. It aims to disseminate new knowledge and foster better understanding of the physical environment, of evolutionary sequences that have resulted in past and current landscapes, and of the natural processes that are likely to determine the fate of our terrestrial environment. Papers within any one of the above topics are welcome provided they are of sufficiently wide interest and relevance.
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