Yunqiang Wang

Regional spatial pattern of deep soil water content and its influencing factors

Abstract Plant root systems can utilize soil water to depths of 10 m or more. Spatial pattern data of deep soil water content (SWC) at the regional scale are scarce due to the labour and time constraints of field measurements. We measured gravimetric deep SWC (DSWC) at depths of 200, 300, 400, 500, 600, 800 and 1000 cm at 382 sites across the Loess Plateau, China. The coefficient of variation was high for soil water content (SWC) in the horizontal direction (48%), but was relatively small for SWC in the vertical direction (9%). Semivariogram ranges for DSWC at different depths were between 198 and 609 km. Kriged distribution maps indicated that deep soil layers became moister along northwest to southeast transects. Multiple statistical analyses related DSWC to plant characteristics (e.g. plant age explained >21% of the variability), geographical location and altitude (8–13%), soil texture and infiltrability, evaporation zone and eco-hydrological processes (P < 0.05). Regional land management decisions can be based on our DSWC distribution data to determine land uses and plant species appropriate for the soil type and location that would maintain a stable soil water balance. Maintaining infiltrability is of great importance in this and other water-scarce regions of the world. Editor D. Koutsoyiannis; Associate editor J. Simunek Citation Wang, Y.Q., Shao, M.A., Liu, Z.P. and Warrington, D.N., 2012. Regional spatial pattern of deep soil water content and its influencing factors. Hydrological Sciences Journal, 57 (2), 265–281.

Characteristics of Dried Soil Layers Under Apple Orchards of Different Ages and Their Applications in Soil Water Managements on the Loess Plateau of China

Negative soil water balance (i.e., water input 0.88), whereas the QWD and mean SWC in DSLs were found to have no correlation with them. The optimal age of apple orchards for avoiding/controlling the formation of DSLs was about 9 years. This information provided pertinent references for the management of deep water resources by controlling the growth age of plants.

Estimating Soil Organic Carbon Across a Large-Scale Region: A State-Space Modeling Approach

Abstract Soil organic carbon (SOC) plays a dynamic role in the global carbon cycle and is important in sustaining soil fertility and ecosystem productivity. Information about the spatial distribution of SOC across large-scale areas and its relationships with pertinent environmental factors is limited although required. In our study, a total of 283 sampling sites were investigated to estimate the spatial variation of SOC across the entire Loess Plateau (620,000 km2) of China. Two strategies, state-space modeling and classical linear regression, were used to quantify the relationships between SOC and selected soil properties (bulk density, soil pH, and clay and silt contents) and climatic (precipitation and temperature) and topographic (elevation) variables. The best state-space models explained more than 80% of the variation of SOC, whereas the best linear regression model explained less than 45% of the variation of SOC. The results showed that all state-space models described spatial variation of SOC much better than the equivalent linear-regression models. Soil-based properties were more important than climatic and topographic variables in identifying localized variation of SOC; the best bivariate and multivariate state-space models included bulk density, silt content, and soil pH. The state-space models performed even better when only 50% of the SOC data were used. However, when using only 25% of the data, the state-space models marginally yielded good estimates of SOC. State-space modeling is recommended as a useful tool for quantifying the spatial relationships between SOC and other environmental factors in large-scale regions.

Pedotransfer Functions for Predicting Soil Hydraulic Properties of the Chinese Loess Plateau

Abstract Soil hydraulic properties play an important role in modelingwater and solute movement within the vadose zone of soils. Direct measurement of hydraulic parameters at a wide range of scales involves considerable time, labor, and money. Pedotransfer functions (PTF) may provide an alternative way of estimating these parameters indirectly from easy-to-measure soil properties. The Loess Plateau of China lacks large databases of hydraulic parameters and also the PTF that could determine them accurately enough for scientists and policy makers to address many of the region’s related problems, such as severe soil erosion. In this study, new PTF for saturated hydraulic conductivity (Ks), field capacity, and saturated soil-water content were developed. Multiple linear regression was used to analyze 252 data sets of the hydraulic and basic soil properties, as well as altitude, to derive the PTF. A further 130 data sets were used for validation. The predictive capabilities of the PTF were the best for saturated soil-water content (Radj2 = 0.78) and least for log Ks (Radj2 = 0.36). Bulk density, soil organic carbon, and soil particle composition were identified as significant input variables for the PTF. The inclusion of a topographic factor (altitude) significantly improved the predictive capability of the PTF for log Ks. Compared with established PTF, the PTF developed in this study predicted the hydraulic parameters more accurately as indicated by higher R2 and lower RMSE values when predicted, and measured parameter values were compared, and the greatest improvement was obtained for log Ks. The new PTF are the first set of PTF based on data from the Loess Plateau. Their better performance makes them applicable for a variety of purposes in the Plateau region and possibly in other loess regions around the world.

Effect of long-term cultivation on soil organic carbon fractions and metal distribution in humic and fulvic acid in black soil, Northeast China

Cultivation affects soil organic matter and its fractions. Fulvic acid (FA) and humic acid (HA) make up an important part of soil organic matter, and their binding capacity influences heavy metal behaviour in soil. This research studied changes in soil organic components and the distribution of copper (Cu), lead (Pb), and zinc (Zn) in HA and FA affected by long-term cultivation in black soils. Uncultivated sites and their adjacent cultivated sites (18, 50, and >200 years) were selected. Alkaline sodium hydroxide/pyrophosphate extraction of humic substances and precipitation of HA by acidification were used to separate the HA and FA fractions. Concentrations of Cu, Pb, and Zn in HA and FA were determined. The content of soil organic carbon (C) had decreased by 30% after 200 years of cultivation. Cultivation led to a moderate decrease (38%) in HA and a minor decrease (7%) in FA. The CHA/CFA ratio, which is a humification parameter, decreased from 2.05 in the uncultivated soil to 1.38 in the soil cultivated for 200 years, indicating a lower degree of humification of organic matter in cultivated soils. Of the Na4P2O7 + NaOH-extracted Pb and Zn, 47–60% and 63–76%, respectively, was associated with FA, showing that FA has a high affinity for Pb and Zn. Of the Na4P2O7 + NaOH-extracted Cu, 55% was in the HA fraction. The share of Cu and Zn in the HA fraction decreased with cultivation time, but cultivation did not bring about a systematic change in Pb distribution in humic substances. The results show that cultivation can decrease the humified C content and metals bound to the HA fraction, and suggest that cultivation may potentially increase the mobility of heavy metals.

Estimating regional losses of soil water due to the conversion of agricultural land to forest in China's Loess Plateau

Afforestation on the Chinese Loess Plateau (CLP) has been extensively implemented by the central government over the past decades to control soil erosion. The conversion of agricultural land to forest, however, has led to decreases in soil-water storage (SWS), which may in turn limit tree growth and threaten the health of ecosystems in the region. This study estimated the regional patterns of losses of soil water (∆SWS) following conversions across the CLP. Soil-water content at 0-5.0 m was measured in 169 forests on the plateau, and the initial pre-afforestation SWS at each sample site was then estimated using stepwise regression. The mean ∆SWS in the 1.0-5.0 m profile across the study area was 203.7 mm, with an estimated annual average ∆SWS rate of 16.2 mm y-1. ∆SWS and its main contributing factors varied amongst three rainfall zones. ∆SWS generally increased with mean annual precipitation (MAP). ∆SWS depended primarily on tree age in the > 550 mm MAP zone and on slope gradient and initial SWS in the < 450 mm MAP zone. This result suggested that the vegetation might be more important than soil or topographic properties for estimating ∆SWS following the conversion of farmland in the wettest area of the CLP. Our study also suggests that MAP, tree age, slope gradient, and initial SWS have important effects on ∆SWS which vary with rainfall. Understanding the regional hydrological effects of afforestation is necessary for the efficient management of soil-water resources on the CLP and in other water-limited regions.

Infiltration characteristics of non-aqueous phase liquids in undisturbed loessal soil cores.

The widespread contamination of soils and aquifers by non-aqueous phase liquids (NAPL), such as crude oil, poses serious environmental and health hazards globally. Understanding the infiltration characteristics of NAPL in soil is crucial in mitigating or remediating soil contamination. The infiltration characteristics of crude and diesel oils into undisturbed loessal soil cores, collected in polymethyl methacrylate cylindrical columns, were investigated under a constant fluid head (3 cm) of either crude oil or diesel oil. The infiltration rate of both crude and diesel oils decreased exponentially as wetting depth increased with time. Soil core size and bulk density both had significant effects on NAPL infiltration through the undisturbed soil cores; a smaller core size or a greater bulk density could reduce oil penetration to depth. Compacting soil in areas susceptible to oil spills may be an effective stratage to reduce contamination. The infiltration of NAPL into soil cores was spatially anisotropic and heterogeneous, thus recording the data at four points on the soil core is a good stratage to improve the accuracy of experimental results. Our results revealed that crude and diesel oils, rather than their components, have a practical value for remediation of contaminated loessal soils.

A micromachined square extensional mode resonant magnetometer with directly voltage output

In this paper, a novel resonant magnetometer is demonstrated based on MEMS Technology. The proposed sensor consists of a square extensional mode resonator with a planar induction coil placed on top of the resonant plate. The sensor employs capacitive driving and electromagnetic induction to detect external magnetic field through the electromotive force in the induction coil. The operation principle, fabrication process as well as the measurement of the magnetic field sensor is demonstrated. Experimental result shows that the device offers a sensitivity of 3 μV/mT at its resonant frequency of f0 = 4.33 MHz in atmosphere pressure.

Scale-dependent correlations between soil properties and environmental factors across the Loess Plateau of China

Traditional statistical analysis of the correlations between spatially distributed variables takes no account of their regionalised nature. Factorial kriging analysis (FKA) was developed and widely used to overcome this problem. In our study, we applied FKA to investigate scale-dependent correlations between selected soil properties and environmental factors across the Loess Plateau of China. Surface soil samples were collected from 382 sampling sites throughout the region, and soil organic carbon (SOC), soil total nitrogen (STN), soil total phosphorus (STP), soil total potassium (STK), soil pH, bulk density (BD), and clay and silt contents were determined. Five environmental factors (elevation, precipitation, temperature, land-use type, and soil type) were also included in the FKA to identify influential processes. A linear model of co-regionalisation, including a nugget effect and two spherical structures (effective ranges of 200 and 400 km), was fitted to the experimental auto- and cross-variograms of the variables. Scale-dependent correlations were calculated for nugget-effect scale (<30-50 km), short-range scale with a range of 200 km, and long-range scale with a range of 400 km. Principal component analysis was conducted to clearly illustrate the correlations at each spatial scale. The scale-dependent correlations were different from the general correlations and varied at different scales. Generally, SOC and STN were strongly correlated at the nugget-effect scale and the long-range scale, but not at the short-range scale. Precipitation and clay content showed close correlations with STP at the nugget-effect scale and long-range scale. The STK was weakly correlated with the other variables at each spatial scale, and closely correlated with soil type at the long-range scale. Soil pH was closely correlated with BD, soil type, and elevation at the nugget-effect, short, and long spatial scales, respectively. Close correlations were found between BD and land-use type at each spatial scale. Land use and soil type were considered to be the important factors controlling spatial variation of soil properties at the short-range scale, while at the long-range scale the likely factors were identified as precipitation, temperature, and elevation. Our study provided an insight into the spatial-dependent correlations between soil properties and environmental factors from a regional perspective.

Estimating soil water content from surface digital image gray level measurements under visible spectrum

Zhu, Y., Wang, Y., Shao, M. and Horton, R. 2011. Estimating soil water content from surface digital image gray level measurements under visible spectrum. Can. J. Soil Sci. 91: 69-76. Determining soil water content (SWC) is fundamental for soil science, ecology and hydrology. Many methods are put forward to measure SWC, such as drying soil samples, neutron probes, time domain reflectrometry (TDR) and remote sensing. Sampling and drying soil is time-consuming. A neutron probe cannot determine SWC of surface soil accurately because neutrons escape when they are emitted near soil surface and TDR is, to some extent, influenced by soil salinity and temperature. Remote sensing can obtain SWC over a large area across a range of temporal and spatial scales. Complicated terrain and atmospheric conditions often make remote sensing data unreliable. Determining SWC from surface gray level (GL) measurements in the visible spectrum may have advantages over other remote sensing techniques, because surface soil images can be easily acquired by digital cameras, even with complicated landforms and meteorological conditions. However, few studies use this method, and further work is required to develop the ability of visible spectrum digital images to accurately estimate SWC. In this study, 42 soil samples were collected to investigate the relationship between surface GL and SWC using computer processing of soil surface images acquired by a digital camera. After establishing an equation to describe this relationship, a simple calibrated model was developed. The calibrated model was validated by an independent set of 48 soil samples. The results indicate that surface GL was sensitive to SWC. There was a negative linear relationship between surface GL and the square of SWC for the 42 calibration soil samples (correlation coefficients >0.91). Based on this negative relationship, a model was established to estimate SWC from surface GL. The results of model validation showed the estimated SWCs by surface GL were very close to the measured SWCs (correlation coefficient=0.99 at a significant level of 0.01). Generally, SWC could be estimated from surface GL for a given soil, and the model could be used to quickly and accurately determineg SWC from surface GL measurements.