Changing controls of soil moisture spatial organization in the Shale Hills Catchment

Takagi, Ken; Lin, Henry

doi:10.1016/j.geoderma.2011.11.003

Cited by 67 publications

(56 citation statements)

References 58 publications

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“…Takagi and Lin (2012) found clear seasonal changes in soil moisture in near-surface layers during rainy seasons. However, de Souza et al (2011) found an increase in the temporal stability of soil moisture in deeper soil layers as compared with upper layers.…”

Section: The Effect Of Vegetation Restoration On Vertical Soil Moistumentioning

confidence: 92%

Response of temporal variation of soil moisture to vegetation restoration in semi-arid Loess Plateau, China

Yang¹,

Wei²,

Chen³

et al. 2014

CATENA

207

109

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Soil moisture is fundamental to ecosystem sustainability in semi-arid regions, and characterizing the response of temporal soil moisture variation to different vegetation types is important for assessing the sustainability of vegetation restoration. In this study, the soil moisture among eight typical types of vegetation is investigated and compared during three rainy seasons. The temporal variations of soil moisture in the near-surface (0-0.4 m), sub-surface (0.4-1.0 m), and deep layers (1.0-2.0 m) are explored to evaluate the ecohydrological effect of vegetation restoration in the semi-arid Loess Plateau of China. The results show that soil moisture content decreases drastically after vegetation restoration, with no significant difference in near-surface soil moisture among the vegetation types but significant differences in the sub-surface and deep soil layers. Introduced vegetation is the main factor affecting the soil moisture deficit below near-surface layers. Secondly, soil moisture is temporally stable in the sub-surface and deep layers, especially in introduced vegetation. This indicates that introduced vegetation consumes excessive amount of soil moisture and induces temporally stable soil desiccation. Soil desiccation with temporal stability cannot provide enough available soil moisture for plants and will inevitably threaten the sustainability of vegetation restoration and the associated ecosystem services. Lastly, high planting density is the main cause of severe soil moisture deficit on a long-term temporal scale. Our study results suggest that the current planting density of introduced vegetation is too high in specific cases and should be optimized with local soil moisture conditions in semi-arid regions.

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Section: The Effect Of Vegetation Restoration On Vertical Soil Moistumentioning

confidence: 92%

Response of temporal variation of soil moisture to vegetation restoration in semi-arid Loess Plateau, China

Yang¹,

Wei²,

Chen³

et al. 2014

CATENA

207

109

View full text Add to dashboard Cite

show abstract

“…(1) Geology (2) Soil information (types, regime) (3) DEM (topography, slope, curvature) (4) Land cover/land use (5) Vegetation cover (6) DEM (topography, slope, curvature) (7) Geomorphology (8) Climate data (rainfall, temperature, evapotranspiration) (9) Remote sensing information (NDMI and land surface temperature) (10) Landform According to the above GIS layers, we should specify that the soil types and the soil regime data contain different information (Table 1). Landform was derived based on topography, and the land was classified into terrain types on the basis of two morphometric indices: slope and curvature [8,30,32].…”

Section: Derivation Of the Lua Mapmentioning

confidence: 99%

Soil Moisture Mapping in an Arid Area Using a Land Unit Area (LUA) Sampling Approach and Geostatistical Interpolation Techniques

Gharechelou

Tateishi

Sharma

et al. 2016

IJGI

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Soil moisture (SM) plays a key role in many environmental processes and has a high spatial and temporal variability. Collecting sample SM data through field surveys (e.g., for validation of remote sensing-derived products) can be very expensive and time consuming if a study area is large, and producing accurate SM maps from the sample point data is a difficult task as well. In this study, geospatial processing techniques are used to combine several geo-environmental layers relevant to SM (soil, geology, rainfall, land cover, etc.) into a land unit area (LUA) map, which delineates regions with relatively homogeneous geological/geomorphological, land use/land cover, and climate characteristics. This LUA map is used to guide the collection of sample SM data in the field, and the field data is finally spatially interpolated to create a wall-to-wall map of SM in the study area (Garmsar, Iran). The main goal of this research is to create a SM map in an arid area, using a land unit area (LUA) approach to obtain the most appropriate sample locations for collecting SM field data. Several environmental GIS layers, which have an impact on SM, were combined to generate a LUA map, and then field surveying was done in each class of the LUA map. A SM map was produced based on LUA, remote sensing data indexes, and spatial interpolation of the field survey sample data. The several interpolation methods (inverse distance weighting, kriging, and co-kriging) were evaluated for generating SM maps from the sample data. The produced maps were compared to each other and validated using ground truth data. The results show that the LUA approach is a reasonable method to create the homogenous field to introduce a representative sample for field soil surveying. The geostatistical SM map achieved adequate accuracy; however, trend analysis and distribution of the soil sample point locations within the LUA types should be further investigated to achieve even better results. Co-kriging produced the most accurate SM map of the study area.

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“…This limitation is problematic for making hydrologic assessments, as numerous studies have shown the importance of soil input data on modeling rainfall runoff processes (Becker and Braun, 1999;Romanowicz et al, 2005;Diek et al, 2014). For hydrological modeling purposes, a number of soil characteristics are needed (i.e., texture, hydraulic properties, and profile depth) which have a major impact on the hydrological cycle, as they are typically directly correlated with soil moisture variability (Geroy et al, 2011;Vachaud et al, 1985;Takagi and Lin, 2012). Diek et al (2014) show that spatial variations in effective soil depth and hydraulic properties play an important role in the variability of both net bottom out flux and transpiration rates.…”

Section: Introductionmentioning

confidence: 99%

Combining digital soil mapping and hydrological modeling in a data scarce watershed in north-central Portugal

et al. 2016

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Changing controls of soil moisture spatial organization in the Shale Hills Catchment

Cited by 67 publications

References 58 publications

Response of temporal variation of soil moisture to vegetation restoration in semi-arid Loess Plateau, China

Response of temporal variation of soil moisture to vegetation restoration in semi-arid Loess Plateau, China

Soil Moisture Mapping in an Arid Area Using a Land Unit Area (LUA) Sampling Approach and Geostatistical Interpolation Techniques

Combining digital soil mapping and hydrological modeling in a data scarce watershed in north-central Portugal

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