Effect of slope position on the spatial distribution of soil preferential flow paths based on point pattern analysis
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The mechanisms of soil preferential flow occurrence and development are influenced by topographic and geomorphological factors. However, the complex distribution patterns of soil preferential flow paths on different slopes remain unclear. Therefore, taking the subtropical evergreen broad-leaved forest area of Simian Mountain as the study area, this study conducted a quantitative analysis of the spatial distribution characteristics and spatial association of soil preferential flow at different slope positions (slope shoulder (SS), mid-slope (SM) and slope foot (SF)) using field staining tracer tests and spatial point pattern analysis. Results showed that the maximum infiltration depth, the depth of matrix flow, average dye coverage, preferential flow fraction and length index of the SM plot were all greater than those of the SS and SF plots. The number of preferential flow paths in different slope positions decreases with soil depth, with most preferential flow paths measuring 2.5–5.0 mm in each soil layer. The total number of preferential flow paths in SM plot was approximately twice that of the SS and SF plots, and the preferential flow paths in SM plot, regardless of pore size, were all in an aggregated distribution. These findings indicated that differences in soil physical properties and vegetation coverage at different slope positions lead to variations in the spatial distribution and association of soil preferential flow paths. Accordingly, strategies must be modified for the distribution, storage and utilisation of soil water resources. This study provides a theoretical basis for the effective management and protection of water resources in the Simian Mountain area and a scientific basis for exploring the mechanisms of the occurrence and development of the water cycle in forested watersheds.Keywords:
Infiltration (HVAC)
Soil horizon
Point pattern analysis
The hydraulic properties of three unsaturated purple soils were determined by a simple horizontal infiltration method in one-dimensional horizontal infiltration experiment.While the study accurately estimates soil water retention curve,its estimates of soil water diffusion and conductivity are not very accurate.Estimated soil water diffusion and conductivity of the three purple soils by the simple infiltration method are 1～2 order of magnitude lower than that of the measured values.However,the model-estimated and measured variation tendencies of soil water diffusion and conductivity are similar.Under high soil water conditions,the estimated soil water diffusion and conductivity by the horizontal infiltration method are lower than that of the measured values.However,under low soil water conditions,the estimated soil water diffusion and conductivity by the horizontal infiltration method are higher than that of the measured values.This suggests that the model slowly responds to soil water change.
Infiltration (HVAC)
Pedotransfer function
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The purpose of this study is to obtain an understanding of the spatial distribution pattern of Picea crassifolia population,deduce the key parameters for a quantitative remote sensing inversion of largescaled P.crassifolia population and provide a basis for the protection of P.crassifolia populations and sustainable management of the forest for conservation of water supply in the Qilian Mountains,northwestern China.Based on the inventory data of a 1 hm2 sample plot in Dayekou of Gansu Province,we studied the spatial distribution patterns of a P.crassifolia population using an analytical point pattern method and investigated the spatial patterns of trees at different age classes under different spatial scales.First,a Weibull function was used to analyze the distribution of DBH (diameter at breast height).Then,the methods of point pattern analysis and aggregation indices were employed to study the spatial distribution patterns of trees at different age classes under different spatial scales.Finally,a Neymans type A distribution was used to simulate the spatial distribution pattern of P.crassifolia population.The results show that: 1) the DBH distribution of P.crassifolia conforms to the Weibull function;2) the distribution of the population is dense and follows an aggregation pattern;3 ) the spatial distribution patterns of young,small,middle and big trees all obey the aggregation distribution under different scales;4) the aggregation intensity decreases with the growth of P.crassifolia population and 5) the spatial distribution pattern of P.crassifolia conforms to the Neyman s type A distribution.The aggregation distribution of the population could result from natural and human disturbance,environmental conditions and biological characteristics of P.crassifolia.
Point pattern analysis
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<p><span>Tarsius lariang (T. lariang) is an endemic species in Lore Lindu National Park (LLNP). Available information regarding T. lariang is limited to only morphological, anatomical, cytogenetic, and voices issues. Knowledge for its geospatial characteristics such as spatial preferences and spatial distribution is rare. The main objective of this study is to identify the spatial distribution pattern of T. lariang in LLNP. An additional objective is to identify the environmental factors affecting its spatial distribution patterns. Field observation for distribution pattern was done at the observation plot that were using systematic sampling with random start. Furthermore, the density estimation in each point was calculated using Triangle Count and Concentration Count method, while insect abundance was estimated using light traps sample data. Finally, spatial pattern was estimated using nearest neighbor index, while the environmental affecting factors were identified by using spatial analysis and correlation analyses. From 45 observation points, the T. lariang distribution pattern was clumped. It is also recognized that the significant factors affecting the spatial distribution were insect abundance, proximity from the commercially utilized land, and land surface temperature.</span></p><p> </p>
Point pattern analysis
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Soil‐dependent β and γ shape parameters of the Haverkamp infiltration model for 3D infiltration flow
Abstract Estimating of soil sorptivity () and saturated hydraulic conductivity () parameters by field infiltration tests are widespread due to the ease of the experimental protocol and data treatment. The analytical equation proposed by Haverkamp et al. (1994) allows the modelling of the cumulative infiltration process, from which the hydraulic parameters can be estimated. This model depends on both initial and final values of the soil hydraulic conductivity, initial soil sorptivity, the volumetric water content increase () and two infiltration constants, the so‐called and parameters. However, to reduce the number of unknown variables when inverting experimental data, constant parameters such as and are usually prefixed to 0.6 and 0.75, respectively. In this study, the values of these constants are investigated using numerical infiltration curves for different soil types and initial soil water contents for the van Genuchten‐Mualem (vGM) soil hydraulic model. Our new approach considers the long‐time expansions of the Haverkamp model, the exact soil properties such as , and initial soil moisture to derive the value of the and parameters for each specific case. We then generated numerically cumulative infiltration curves using Hydrus‐3D software and fitted the long‐time expansions to derive the value of the and parameters. The results show that these parameters are influenced by the initial soil water content and the soil type. However, for initially dry soil conditions, some prefixed values can be proposed instead of the currently used values. If an accurate estimate of and is the case, then for coarse‐textured soils such as sand and loamy sand, we propose the use of 0.9 for both constants. For the remaining soils, the value of 0.75 can be retained for . For constant, 0.75 and 1.5 values can be considered for, intermediate permeable soils (sandy loam and loam) and low permeable soils (silty loam and silt), respectively. We clarify that the results are based on using the vGM model to describe the hydraulic functions of the soil and that the results may differ, and the assumptions may change for other models.
Sorptivity
Infiltration (HVAC)
Pedotransfer function
Water retention curve
Richards equation
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Infiltration (HVAC)
Electrical Resistivity Tomography
Ground-Penetrating Radar
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Point pattern analysis
Spatial relationship
Lead (geology)
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Mollisol
Soil horizon
Soil carbon
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According to the field investigation results from 2 Populus bolleana sample plots with the area of 20 m × 20 m in Ningxia Mu Us Sandy Land,and point pattern analysis was used to study the spatial distribution patterns and spatial association of Populus bolleana population in Mu Us Sandy Land.The results indicated that in smaller spatial scale(0-3 m),the spatial distribution of Populus bolleana population presented significant nonrandom distribution;when spatial scale was greater than critical value(9 m),the spatial distribution of Populus bolleana population presented random distribution trend;different size classes of Populus bolleana population in spatial association showed negative correlation.
Point pattern analysis
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Spatial distribution plays an important role in hotel group development. Based on the analysis of industrial characteristics of hotel groups' spatial distribution,the paper not only puts forward the rational spatial structure of hotel groups,but also sums up three spatial distribution modes for hotel groups. Furthermore,the paper makes a case study of Huatian Hotel Group,analysing its status quo of spatial expansion and revealing its problems in spatial distribution. The case study demonstrates that the development of Huatian Hotel Group only occurs in confined regions,which is far from the characteristics and requirements of hotel groups' spatial distribution. In order to optimize its spatial distribution,the paper suggests that Huatian Hotel Group should take the following strategies: focus on the development of Beijing-Guangzhou axis to improve its spatial structure of point-axis,actively explore the market in western China to expand its coverage,and choose the right time to enter the market in eastern China to build a national network of distribution.
Point pattern analysis
Spatial organization
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Characterizing soil infiltration parameters using field/laboratory measured and remotely-sensed data
Characterizing soil infiltration parameters is time consuming and costly. We carried out the current research to predict different parameters of soil infiltration using field/laboratory measured and remotely-sensed data. The investigated parameters included infiltration rates at different time intervals and the parameters of the three well-known infiltration models. We employed soil sampling and field measurements on late spring 2012 and acquired ETM+ data for the correspondent dates. We measured several soil properties as well as infiltration. Then, we developed several pedo-transfer functions (PTFs) from the collected field/laboratory measured and remotely sensed data to predict the intended infiltration parameters. Results showed that field/laboratory measured data were able to predict soil infiltration rates and parameters of the investigated models with reasonably high accuracies (E value up to 0.961). The results also revealed that, although there was no significant and robust relationship between soil surface reflectance and the investigated parameters, the developed PTFs had reasonable accuracies (E value up to 0.634) in estimating the intended infiltration parameters using soil characteristics (moisture content, soil separates, and organic carbon) which are predictable from remotely sensed data.
Infiltration (HVAC)
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