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Keywords = rocky hillslope

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21 pages, 23853 KiB  
Article
Remote Sensing-Informed Zonation for Understanding Snow, Plant and Soil Moisture Dynamics within a Mountain Ecosystem
by Jashvina Devadoss, Nicola Falco, Baptiste Dafflon, Yuxin Wu, Maya Franklin, Anna Hermes, Eve-Lyn S. Hinckley and Haruko Wainwright
Remote Sens. 2020, 12(17), 2733; https://doi.org/10.3390/rs12172733 - 24 Aug 2020
Cited by 20 | Viewed by 4638
Abstract
In the headwater catchments of the Rocky Mountains, plant productivity and its dynamics are largely dependent upon water availability, which is influenced by changing snowmelt dynamics associated with climate change. Understanding and quantifying the interactions between snow, plants and soil moisture is challenging, [...] Read more.
In the headwater catchments of the Rocky Mountains, plant productivity and its dynamics are largely dependent upon water availability, which is influenced by changing snowmelt dynamics associated with climate change. Understanding and quantifying the interactions between snow, plants and soil moisture is challenging, since these interactions are highly heterogeneous in mountainous terrain, particularly as they are influenced by microtopography within a hillslope. Recent advances in satellite remote sensing have created an opportunity for monitoring snow and plant dynamics at high spatiotemporal resolutions that can capture microtopographic effects. In this study, we investigate the relationships among topography, snowmelt, soil moisture and plant dynamics in the East River watershed, Crested Butte, Colorado, based on a time series of 3-meter resolution PlanetScope normalized difference vegetation index (NDVI) images. To make use of a large volume of high-resolution time-lapse images (17 images total), we use unsupervised machine learning methods to reduce the dimensionality of the time lapse images by identifying spatial zones that have characteristic NDVI time series. We hypothesize that each zone represents a set of similar snowmelt and plant dynamics that differ from other identified zones and that these zones are associated with key topographic features, plant species and soil moisture. We compare different distance measures (Ward and complete linkage) to understand the effects of their influence on the zonation map. Results show that the identified zones are associated with particular microtopographic features; highly productive zones are associated with low slopes and high topographic wetness index, in contrast with zones of low productivity, which are associated with high slopes and low topographic wetness index. The zones also correspond to particular plant species distributions; higher forb coverage is associated with zones characterized by higher peak productivity combined with rapid senescence in low moisture conditions, while higher sagebrush coverage is associated with low productivity and similar senescence patterns between high and low moisture conditions. In addition, soil moisture probe and sensor data confirm that each zone has a unique soil moisture distribution. This cluster-based analysis can tractably analyze high-resolution time-lapse images to examine plant-soil-snow interactions, guide sampling and sensor placements and identify areas likely vulnerable to ecological change in the future. Full article
(This article belongs to the Special Issue Ecohydrological Remote Sensing)
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25 pages, 25318 KiB  
Article
Spatial Variability of Preferential Flow and Infiltration Redistribution along a Rocky-Mountain Hillslope, Northern China
by Si-yuan Zhao, Yang-wen Jia, Jia-guo Gong, Cun-wen Niu, Hui-dong Su, Yong-de Gan and Huan Liu
Water 2020, 12(4), 1102; https://doi.org/10.3390/w12041102 - 13 Apr 2020
Cited by 11 | Viewed by 3823
Abstract
Rock fragments in soil strongly increase the complexity of hydrological processes. Spatial variability of preferential flow and infiltration characteristics, especially along a rocky-mountain hillslope are poorly understood. In this study, five rainfall–dye tracer experiments were performed in the rocky Taihang Mountains, northern China, [...] Read more.
Rock fragments in soil strongly increase the complexity of hydrological processes. Spatial variability of preferential flow and infiltration characteristics, especially along a rocky-mountain hillslope are poorly understood. In this study, five rainfall–dye tracer experiments were performed in the rocky Taihang Mountains, northern China, to investigate the spatial variability of preferential flow and infiltration redistribution on different hillslope positions. Tracers were used to distinguish macropore flow and actual water flow patterns, and preferential flow indices and spatial non–uniformity of the infiltration redistribution were calculated using image analysis. Results showed increasing trends in the dye coverage, maximum infiltration depth, and steady infiltration rate with increased hillslope position, with a preferential flow fraction of 0.10, 0.11, 0.15, 0.29, and 0.26 for the bottom–, down–, mid–, upper–, and top–slope positions, respectively. With increased hillslope position, the spatial non–uniformity of the infiltration redistribution gradually increased in orthogonal and parallel directions to the stained section, and was supported by the fractal dimensions. Positive (gravel mass ratio, saturated water content, altitude, hydraulic conductivity and roots) and negative (bulk density and clay content) impacts on preferential flow and infiltration redistribution were quantitatively emphasized. The characteristic and mechanism of infiltration process were further identified along a rocky-mountain hillslope. Full article
(This article belongs to the Section Hydrology)
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