Effect of topography on spatiotemporal patterns of soil moisture in a mountainous region of Northwest China

Li, Ling; Wu, Dong-Fang; Wang, Zhihui; Wang, Yunqiang

doi:10.1016/j.geodrs.2021.e00456

Cited by 8 publications

(6 citation statements)

References 47 publications

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“…However, for functional communities with higher successional stages (i.e., G5, G6, and G7), shrubby functional species (PFT3 ~ PFT4) exhibited absolute dominance, followed by tree functional species (PFT1 ~ PFT2), we found species composition of these communities to be closely related to SOC. Vegetation restoration increases SOC stock in the Loess Plateau (Chen et al, 2022; Wang, Li, et al, 2021; Zhu et al, 2021), which is affected by land use and cover (Li, Shi, Zhao, & Wu, 2022; Li, Wu, Liu, et al, 2022; Li, Wu, Wang, & Wang, 2022; Stockmann et al, 2015). Chen et al (2022) found that the coupling interaction between soil organic carbon and soil water storage changed during vegetation restoration.…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, PFT1 has high water and nutrient requirements for growth. AS is one cause of forest ecosystem water and photosynthetic efficiency spatial heterogeneity (Li, Wu, Wang, & Wang, 2022), and many studies have shown that high‐density PFT1 causes excessive soil nutrient consumption (e.g., nitrogen, phosphorus, potassium, and carbon) in the watershed (Wu et al, 2020; Zhang, Yang, et al, 2021). However, PFT2 communities have a longer growing season, and they employ a conservative strategy to compensate for the cost of their long‐lived leaves (Reich et al, 1992; Zhang, Yang, et al, 2021), and may become dominant at a later successional stage (Chi et al, 2015; Condit et al, 1996).…”

Section: Discussionmentioning

confidence: 99%

“…After decades of vegetation restoration in the Loess Plateau, the soil conditions in most areas have allowed many PFT6 and PFT10 communities to enter. Hygrophytic herbs (PFT7) have strict soil moisture requirements, and do not grow well under conditions of drought, water shortage, and large evaporation in the Loess Plateau (Li, Shi, Zhao, & Wu, 2022; Li, Song, Zhao, et al, 2022; Li, Wu, Liu, et al, 2022; Li, Wu, Wang, & Wang, 2022). Therefore, PFT7 is rare within the study area and only exist on riversides and in humid valley areas, which are located in water concentrated areas at lower altitudes.…”

Section: Discussionmentioning

confidence: 99%

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Functional vegetation community responses to soil and topographic factors in the Loess Plateau of China

Zhang

Zha

et al. 2023

Land Degrad Dev

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Given the developmental program outlined in United Nations Sustainable Development Goal 15 (Life on Land) and the to effectively address the challenge of biodiversity decline while mitigating the adverse effects of climate change, particularly drought, on terrestrial forest ecosystems, a fundamental reorientation of global forest restoration paradigms is warranted. It is imperative to move beyond a narrow emphasis on expanding forest area and instead prioritize the enhancement of biodiversity and functional attributes within these ecosystems. However, the differential response mechanisms of forest ecosystem functional communities and main plant functional types (PFTs) to environmental factors, especially soil and topography, remains unclear, especially at plant level. Here, we divided the functional communities of 93 sites in the study area into seven groups through Two‐way indicator species analysis (TWINSPAN), and studied the different functional communities, namely dynamic succession, species richness, and PFT compositional differences. We also analyzed the various PFTs and functional community response mechanisms to soil and topographic factors using canonical correspondence analysis (CCA). The main results were as follows: (1) With the successional stages of PFTs, vegetation diversity across multiple functional communities inceased, tree and shrub proportions and importance increased, while herbs decreased. (2) From the arid and barren areas (i.e., G2), to the humid and fertile areas (i.e., G6 and G7), various compositional PFT differences, and their responses to soil and topographic factors, were found, namely, xerophytic, annual and biennial species gradually changed to mesophytic, hygrophytic, and perennial species (richness increased 6.94 ~ 27.33%, important value (IV) increased 8.73 ~ 29.45%) for shrubs and herbs. (3) Functional communities in various successional stages display distinct sensitivities to soil and topographic factors, as evidenced by a notable increase in the richness and IV of deciduous broad‐leaved tree species, rendering their communities more responsive to SOC and AS, whereas evergreen coniferous trees (e.g., Pinus tabuliformis Carr.) were sensitive to altitude (AL) and exhibited a tendency to transition from plantations to natural secondary forests predominantly at higher altitudes (above 1200 m). Our findings suggest that site conditions influence scenarios, and that different PFT responses and adjustments to soil and topography factors affect whole functional community dynamic succession processes, which can profoundly impact forest ecosystem function predictions based on PFT changes in the Loess Plateau of China.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Functional vegetation community responses to soil and topographic factors in the Loess Plateau of China

Zhang

Zha

et al. 2023

Land Degrad Dev

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“…Soil moisture (SM) is a fundamental constituent of the terrestrial environment and the hydrological cycle (Li et al., 2022). It significantly influences catchment hydrological responses by moderating processes such as runoff generation (Freebairn et al., 2009; Robinson et al., 2008; Singh et al., 2021) and evapotranspiration (Kim et al., 2016).…”

Section: Introductionmentioning

confidence: 99%

Estimation of soil moisture using environmental covariates and machine learning algorithms in Cathedral Peak Catchment, South Africa

Kibirige,

Gokool,

Mkhize

2023

Vadose Zone Journal

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Soil moisture (SM) is a fundamental constituent of the terrestrial environment and the hydrological cycle. Owing to its significant influence on catchment hydrological responses, it can be utilized as an indicator of floods and droughts to aid early warning systems. This study aimed to develop a field‐scale method to estimate SM using parametric and machine learning‐based methods to compare whether advanced artificial intelligence methods can give similar results as traditional methods. Considering this, monthly observed SM data (from the top 10 cm), environmental covariates, and remotely sensed data from March 2019 to July 2021 for the Cathedral Peak Research Catchments VI and IX in South Africa were obtained. From the 241 observations obtained across 12 sites, 160 (∼66%) were used for model training, while the remaining 81 (∼34%) were used for model testing. Employing 10‐fold cross‐validation, the individual machine learning models (viz., support vector machine [SVM], random forest (RF), k‐nearest neighbor, classification and regression trees [Rpart], and generalized linear model) displayed a satisfactory performance (R2 = 0.52–0.79; root mean square error = 3.79–5.80). In the validation phase, the RF model displayed a superior performance, followed by the SVM. Subsequent SM estimation using the hybrid model produced satisfactory results in training (R2 = 0.90) and testing (R2 = 0.45). The results obtained from this study can aid in predicting SM variations in catchments with limited monitoring. Furthermore, this model can be applied in drought monitoring, forecasting, and informing agricultural management practices.

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“…The complex geometric structure of mountains and the unique water and heat characteristics and ecosystem structure caused by topography can result in the observation error of microwave radiometer [4][5][6][7]. It leads to a lower inversion accuracy of mountain surface soil moisture than flat surface [8][9][10]. Research has shown that the error in soil moisture inversion caused by topography can exceed 4% [11].…”

Section: Introductionmentioning

confidence: 99%

An Empirical Model for Correction of Topographic Effect in Microwave Radiation of Mountainous Area

Zhao,

Liu,

Chai

et al. 2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The topographic effect is one of the essential factors affecting microwave radiation in mountainous regions. This effect's correction can improve the inversion accuracy of key surface parameters. Here, a new terrain correction model in microwave pixel scale is proposed by regression. Using the rugosity (RU) measure the relief of land surface, and analyze its correlation with the brightness temperature difference between the undulating surface and flat surface (∆𝑻𝑩 𝝋 𝑹𝒊 ). The topographic effects are simulated by the mountain microwave radiation model. Through the regression analysis of the topographic effects with RU in different regions, we find that: first, RU has a linear relationship with the average ∆𝑻𝑩 𝝋 𝑹𝒊 for different azimuths of the pixel (∆𝑻𝑩 ̅̅̅̅̅̅ ), with the value of R 2 above 0.9 for both polarization; then, the effects of azimuths and ground characteristics on brightness temperature can also be corrected by establishing their regression relationship with brightness temperature. Combined with these analyses, an empirical model is developed to measure the topographic effect according to RU. The verification results show that the ∆𝑻𝑩 𝒎𝒐𝒅𝒆𝒍 calculated by the empirical model is similar to the ∆𝑻𝑩 𝒔𝒊𝒎𝒖𝒍𝒂𝒕𝒆𝒅 of microwave radiation model (r>0.9), which indicates that the empirical model is suitable for mountainous areas with different terrains. Results also provide a theoretical basis for improving the accuracy of passive microwave remote sensing of mountainous areas.

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Effect of topography on spatiotemporal patterns of soil moisture in a mountainous region of Northwest China

Cited by 8 publications

References 47 publications

Functional vegetation community responses to soil and topographic factors in the Loess Plateau of China

Functional vegetation community responses to soil and topographic factors in the Loess Plateau of China

Estimation of soil moisture using environmental covariates and machine learning algorithms in Cathedral Peak Catchment, South Africa

An Empirical Model for Correction of Topographic Effect in Microwave Radiation of Mountainous Area

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