A new dynamic wetness index (DWI) predicts soil moisture persistence and correlates with key indicators of surface soil geochemistry

Li, Ming; Foster, Erika J.; Le, Phuong Thu; Yan, Qina; Stumpf, Andrew J.; Hou, Ting; Papanicolaou, A. N.; Wacha, K.; Wilson, Christopher G.; Wang, Jingkuan; Filley, Timothy R.

doi:10.1016/j.geoderma.2020.114239

Cited by 11 publications

(10 citation statements)

References 94 publications

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“…We introduce the Morris one-step-at-a-time (OAT) method for a sensitivity analysis of parameters used in the hybrid model. Given the uncertainty of the input parameters (Table 1), we applied the Morris OAT method to quantify parameter sensitivity (Campolongo et al 2007;Morris, 1991). The Morris method provides global sensitivity indices over the parameter space at a relatively limited computational cost (Wainwright et al, 2014).…”

Section: Sensitivity Analysis Of the Model Parametersmentioning

confidence: 99%

“…More-over, soils hold the largest reservoir of organic carbon in the terrestrial ecosystem and function as a reservoir of other elements' accumulation, sequestration, and biogeochemical reactions (Grant and Dietrich, 2017;Tokunaga et al, 2019). Therefore, an accurate soil thickness map can improve the estimation of water, carbon, nitrogen, and other elements dynamics for hydrologic and biogeochemical modeling (Carvalhais et al, 2014;Fan et al, 2019;Li et al, 2020;Patton et al, 2019;Pelletier et al, 2016). However, mapping soil thickness remains one of the key uncertainties in land sur-Q.…”

Section: Introductionmentioning

confidence: 99%

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A hybrid data–model approach to map soil thickness in mountain hillslopes

et al. 2021

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Abstract. Soil thickness plays a central role in the interactions between vegetation, soils, and topography, where it controls the retention and release of water, carbon, nitrogen, and metals. However, mapping soil thickness, here defined as the mobile regolith layer, at high spatial resolution remains challenging. Here, we develop a hybrid model that combines a process-based model and empirical relationships to estimate the spatial heterogeneity of soil thickness with fine spatial resolution (0.5 m). We apply this model to two aspects of hillslopes (southwest- and northeast-facing, respectively) in the East River watershed in Colorado. Two independent measurement methods – auger and cone penetrometer – are used to sample soil thickness at 78 locations to calibrate the local value of unconstrained parameters within the hybrid model. Sensitivity analysis using the hybrid model reveals that the diffusion coefficient used in hillslope diffusion modeling has the largest sensitivity among all input parameters. In addition, our results from both sampling and modeling show that, in general, the northeast-facing hillslope has a deeper soil layer than the southwest-facing hillslope. By comparing the soil thickness estimated between a machine-learning approach and this hybrid model, the hybrid model provides higher accuracy and requires less sampling data. Modeling results further reveal that the southwest-facing hillslope has a slightly faster surface soil erosion rate and soil production rate than the northeast-facing hillslope, which suggests that the relatively less dense vegetation cover and drier surface soils on the southwest-facing slopes influence soil properties. With seven parameters in total for calibration, this hybrid model can provide a realistic soil thickness map with a relatively small amount of sampling dataset comparing to machine-learning approach. Integrating process-based modeling and statistical analysis not only provides a thorough understanding of the fundamental mechanisms for soil thickness prediction but also integrates the strengths of both statistical approaches and process-based modeling approaches.

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Section: Sensitivity Analysis Of the Model Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A hybrid data–model approach to map soil thickness in mountain hillslopes

et al. 2021

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“…The integration of CO 2 flux, as well as the TWI, has been used in different empirical studies aimed at conservation, planning and landscape design with a view to ecological integrity in the Federal District. Thus, these are seen as validated indices in different landscape contexts (Rahman et al, 2001;Xu et al, 2008;Zhu et al, 2014;Silva and Baptista, 2015;Santos, 2017;Radula et al, 2018;Li et al, 2020;Correia Filho et al, 2021;Kopecky et al, 2021), as a way of measuring important landscape characteristics to be identified in ecological recovery actions: photosynthetic efficacy of vegetation, carbon flux, capacity of biomass production (Bonam, 2008;Costanza et al, 2017;Baptista, 2019), moisture, fertility, presence of organic matter, soil texture and thickness (Xu et al, 2008;He et al, 2016;Raduła et al, 2018).…”

Section: Methodsmentioning

confidence: 99%

“…In this way, the quantification and qualification of carbon becomes relevant so that future intervention decisions can be supported with occupations that allow for such functions, providing a territorial planning decision-making integrated with nature. These relationships are subject to several explorations through remote sensing, whose spatial and temporal analysis can simplify and improve merely quantitative assessments (Amaral et al, 2020;Li et al, 2020;Correia Filho et al, 2021;Kopecky et al, 2021).…”

Section: Ecological Restoration Based On Carbon Fluxesmentioning

confidence: 99%

Landscape planning and design by identifying areas for ecological restoration based on carbon fluxes

Amaral

Bezerra

Baptista

2022

IJBPA

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PurposeHuman actions on natural ecosystems have not only jeopardized human well-being but also threatened the existence of other species. On the other hand, the benefits resulting from a greater integration between the logic of nature and human occupations have been seen as motivating factors for the prevention and mitigation of environmental impacts in landscape planning, since it provides human well-being through the grant of resources, regulation of the environment and socio-cultural services called ecosystem services. This article highlights the relevance of using ecosystem integrity indicators related to the functioning of ecological support processes for landscape planning.Design/methodology/approachThe research used the photosynthetic performance of vegetation through carbon fluxes in the landscape, defining areas where different approaches to green infrastructure can be applied, gaining over the majority of work in this area, in which low degrees of objectivity on measurement and consequent ecological recovery still prevail. Thus, using the conceptual support of restoration ecology and remote sensing, the work identified different vegetation performances in relation to the supporting ecological processes using the multispectral CO2flux index, linked to the carbon flux to identify the photosynthetic effectiveness of the vegetation and the Topographic Wetness Index (TWI).FindingsWith a study in the Distrito Federal (DF), the results of the different performances of vegetation for ecological support, through electromagnetic signatures and associated vegetation formations, allowed for the identification of hotspots of greater integrity that indicate multifunctional areas to be preserved and critical areas that deserve planning actions using green infrastructure techniques for their restoration and integration into the landscape.Originality/valueThis approach could be the initial step towards establishing clear and assertive criteria for selecting areas with greater potential for the development of supporting ecological processes in the territorial mosaic.

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“…For instance, urban expansion leads to increased population density and a greater demand for water resources, while increased impervious surfaces and industrial practices lead to increased flows and contaminant transport to downstream areas (Carpio and Fath 2011; Wang et al 2018). Additionally, agricultural modernization and expansion impacts water quality due to increased erosion, application of pesticides and fertilizers, (Canfield, Glazer, and Falkowski 2010; Lu and Tian 2017; Li et al 2020) and changing water availability (Stark, Guillén, and Brady 2012). Globally, land use change has caused drastic alterations of soil fertility (Khaledian et al 2017) and stability (Diringer et al 2020; Lacroix, Dehecq, and Taipe 2020), hydrology (Ochoa‐Tocachi et al 2016), loss of ecosystem services (Castello and Macedo 2016; Peng et al 2017), and susceptibility to natural disasters such as flooding (Rogger et al 2017) and drought (Bagley et al 2014).…”

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confidence: 99%

Using Remote Sensing to Discover Historic Context of Human‐Environmental Water Resource Dynamics

Brecheisen

Hamp-Adams

Tomasek

et al. 2020

Contemporary Water Research

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Analysis of historic and contemporary high‐resolution imagery can help to fill knowledge gaps in land cover and management history in locations where documentation is non‐existent or records are difficult to access. Historic imagery dating back to the 1960s can be used to structure quantitative investigation and mapping of land use and land cover change across space and time to enhance earth science, policy, and social science research. Imagery can further inform municipal planning and implementation in areas of natural resource allocation, infrastructure, and hazard mitigation. For management and public education, historic imagery can help people to understand environmental processes and the impacts of human activity in the local environment. Here we emphasize the value of high‐resolution historic satellite imagery from the Corona and Keyhole satellite programs to inform environmental research, public education, and environmental management. Within the Region of Arequipa in southern Peru we highlight examples of urban development, agricultural expansion, river channelization, and glacial retreat via comparison of historic and modern satellite imagery. By incorporating these types of historic imagery data in formats accessible to non‐professionals, public engagement as well as research into human‐environmental investigations will be greatly enhanced.

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A new dynamic wetness index (DWI) predicts soil moisture persistence and correlates with key indicators of surface soil geochemistry

Cited by 11 publications

References 94 publications

A hybrid data–model approach to map soil thickness in mountain hillslopes

A hybrid data–model approach to map soil thickness in mountain hillslopes

Landscape planning and design by identifying areas for ecological restoration based on carbon fluxes

Using Remote Sensing to Discover Historic Context of Human‐Environmental Water Resource Dynamics

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