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Mingan Shao - One of the best experts on this subject based on the ideXlab platform.

  • effects of activities of ants camponotus japonicus on soil moisture cannot be neglected in the northern loess plateau
    Agriculture Ecosystems & Environment, 2017
    Co-Authors: Mingan Shao, Yuhua Jia
    Abstract:

    Abstract Ants can create abundant and continuous soil macropores by burrowing their nests. The hydrological processes in ant nests for different soil types and the effects of ant activities on soil water evaporation are unclear. In this study, we assessed the effects of ant (Camponotus japonicus) nests on preferential flow in the loam and sand soils and on soil water evaporation. First, 12 plots in the sand and loam soils with and without ants were selected for the preferential flow measurements in the field. Second, 200 worker ants and the queen ant were introduced to abandoned cropland plots, and the comprehensive effects of ants on soil moisture down to 340 cm were measured using Neutron Probes. Third, at the Shenmu Erosion and Environment Research Station, 18 iron buckets (20 cm in diameter, 20 cm high) were filled with disturbed loam soil, and a different number of ants was used to assess the effects of ant activities on soil evaporation. The infiltration rate in areas with a nest was approximately 20 times higher than that in no-nest areas. Moreover, the dyeing depths in loam and sand soil with a nest were 47 ± 4.6 and 34 ± 1.5 cm, which were significantly greater than those without a nest (13 ± 2.7 and 23 ± 2.3 cm). Ant nests reached a depth of 60 cm in the field. The effects of a nest on soil moisture existed between 0 and 120 cm deep. Moreover, by moving a high number of “homemade soil aggregates” (1.6 ± 0.18 mm in diameter) onto the soil surface, ants reduced soil evaporation. Ant activities improved soil moisture around the nest by increasing rainfall infiltration and reducing soil water evaporation, which increased the variation in soil water distribution in the soil profile and may benefit the general restoration of vegetation on the Loess Plateau.

  • estimation of soil water storage using temporal stability in four land uses over 10 years on the loess plateau china
    Journal of Hydrology, 2014
    Co-Authors: Bingxia Liu, Mingan Shao
    Abstract:

    Summary An understanding of the temporal stability of soil water storage (SWS) in deep soil profiles is critical to optimize monitoring strategies and to predict the status of soil water on the Loess Plateau. This study tested and validated the feasibility of estimating mean SWS over multiple years by the SWSs at selected locations. The SWSs in 0–1, 1–2, 2–3, and 3–4 m layers were collected using Neutron Probes at 11 sites in each of four land-use types: cropland (CL), grassland (GL), fallow land (FL), and shrubland (SL). The most time-stable locations (MTSLs) for the various layers and the location at mid-slope for each land use were selected on 20 sampling occasions during a calibration period from July 2004 to December 2005. A validation data sets from January 2006 to October 2013 was used to test the length of time the estimates of mean SWS remained valid. The SWSs in SL and GL decreased with plant growth, and the temporal variations were larger in SL and GL than in FL and CL. The temporal stability of the SWSs was high for all soil layers in four land uses, with the rank correlations over the threshold of significance ( α  = 0.05) over 10 years. The degree of temporal stability of SWSs was ranked as CL > FL > GL > SL, and the temporal stability of SWSs in SL and GL decreased with increasing lengths of observation period, as indicated by lower mean Spearman’s correlations for all soil layers. The MTSLs selected from the calibration period could accurately estimate mean SWSs for diverse layers under four land uses with estimation errors less than 10% over eight years. The study verified that a single location at mid-slope of each land use could be sampled in order to reduce the required number of samples and save time and labor while maintaining a high accuracy of prediction over multiple years.

  • hillslope scale temporal stability of soil water storage in diverse soil layers
    Journal of Hydrology, 2013
    Co-Authors: Xiaoxu Jia, Yunqiang Wang, Mingan Shao, Xiao Rong Wei
    Abstract:

    Knowledge of the soil water storage (SWS) of soil profiles on the scale of a hillslope is important for the optimal management of soil water and revegetation on sloping land in semi-arid areas. This study aimed to investigate the temporal stability of SWS profiles (0–1.0, 1.0–2.0, and 2.0–3.0 m) and to identify representative sites for reliably estimating the mean SWS on two adjacent hillslopes of the Loess Plateau in China. We used two indices: the standard deviation of relative difference (SDRD) and the mean absolute bias error (MABE). We also endeavored to identify any correlations between temporal stability and soil, topography, or properties of the vegetation. The SWS of the soil layers was measured using Neutron Probes on 15 occasions at 59 locations arranged on two hillslopes (31 and 28 locations for hillslope A (HA) and hillslope B (HB), respectively) from 2009 to 2011. The time-averaged mean SWS for the three layers differed significantly (P < 0.05) between HA and HB and was greatly affected by topography and vegetation. Temporal–spatial analyses showed that the temporal variation of SWS decreased with increasing soil depth, while the spatial variation increased on both hillslopes. Comparisons of the values for SDRD and MABE and the number of time-stable locations with SDRD and MABE < 5% among various depths indicated that temporal stability increased with an increase in soil depth. The representative sites identified for each hillslope (two on HA and one on HB) accurately estimated the mean SWS for the three soil layers (R2 ⩾ 0.95, P < 0.001). SWS on the scale of a hillslope was strongly time stable, and the temporal–spatial patterns of SWS were highly dependent on sampling depth. The temporal stability of SWS patterns was controlled by soil texture, organic carbon content, elevation, and properties of the vegetation in the study area, which was characterised by diverse or complex terrains and plant cover. Such effects, however, might vary across hillslopes due to different conditions of wetness and patterns of land use. This study provides useful information on the profiles of mean SWS on the scale of a hillslope, which is necessary for improving the management of soil water on sloping land on the Loess Plateau.

  • estimating soil water content from surface digital image gray level measurements under visible spectrum
    Canadian Journal of Soil Science, 2011
    Co-Authors: Yunqiang Wang, Mingan Shao, Yuanjun Zhu, Robert Horton
    Abstract:

    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.

  • time stability of soil water storage measured by Neutron probe and the effects of calibration procedures in a small watershed
    Catena, 2009
    Co-Authors: Mingan Shao, Quanjiu Wang, Klaus Reichardt
    Abstract:

    The knowledge of soil water storage (SWS) of soil profiles is crucial for the adoption of vegetation restoration practices. With the aim of identifying representative sites to obtain the mean SWS of a watershed, a time stability analysis of Neutron probe evaluations of SWS was performed by the means of relative differences and Spearman rank correlation coefficients. At the same time, the effects of different Neutron probe calibration procedures were explored on time stability analysis. mean SWS estimation. and preservation of the spatial variability of SWS. The selected watershed, with deep gullies and undulating slopes which cover an area of 20 ha, is characterized by an Ust-Sandiic Entisol and an Aeolian sandy soil. The dominant vegetation species are bunge needlegrass (Stipa bungeana Trim) and korshinsk peashrub (Carugano Korshinskii kom.). From June 11, 2007 to July 23,2008, SWS of the top1 m soil layer was evaluated for 20 dates, based on Neutron probe data of 12 sampling sites. Three calibration procedures were employed: type 1, most complete, with each site having its own linear calibration equation (TrE); type II. with TrE equations extended over the whole field: and type III, with one single linear calibration curve for the whole field (UnE) and also correcting its intercept based on site specific relative difference analysis (RdE) and on linear fitting of data (RcE), both maintaining the same slope. A strong time stability of SWS estimated by TrE equations was identified. Soil particle size and soil organic matter content were recognized as the influencing factors for spatial variability of SWS. Land use influenced neither the spatial variability nor the time stability of SWS. Time stability analysis identified one site to represent the mean SWS of the whole watershed with mean absolute percentage errors of less than 10%, therefore. this site can be used as a predictor for the mean SWS of the watershed. Some equations of type II were found to be unsatisfactory to yield reliable mean SWS values or in preserving the associated soil spatial variability. Hence, it is recommended to be cautious in extending calibration equations to other sites since they might not consider the field variability. For the equations with corrected intercept (type III), which consider the spatial variability of calibration in a different way in relation to TrE, it was found that they can yield satisfactory means and standard deviation of SWS, except for the RdE equations, which largely leveled off the SWS values in the watershed. Correlation analysis showed that the Neutron probe calibration was linked to soil bulk density and to organic matter content. Therefore, spatial variability of soil properties should be taken into account during the process of Neutron probe calibration. This study provides useful information on the mean SWS observation with a time stable site and on distinct Neutron probe calibration procedures, and it should be extended to soil water management studies with Neutron Probes, e.g., the process of vegetation restoration in wider area and soil types of the Loess Plateau in China. (C) 2009 Elsevier B.V. All rights reserved.

Yunqiang Wang - One of the best experts on this subject based on the ideXlab platform.

  • hillslope scale temporal stability of soil water storage in diverse soil layers
    Journal of Hydrology, 2013
    Co-Authors: Xiaoxu Jia, Yunqiang Wang, Mingan Shao, Xiao Rong Wei
    Abstract:

    Knowledge of the soil water storage (SWS) of soil profiles on the scale of a hillslope is important for the optimal management of soil water and revegetation on sloping land in semi-arid areas. This study aimed to investigate the temporal stability of SWS profiles (0–1.0, 1.0–2.0, and 2.0–3.0 m) and to identify representative sites for reliably estimating the mean SWS on two adjacent hillslopes of the Loess Plateau in China. We used two indices: the standard deviation of relative difference (SDRD) and the mean absolute bias error (MABE). We also endeavored to identify any correlations between temporal stability and soil, topography, or properties of the vegetation. The SWS of the soil layers was measured using Neutron Probes on 15 occasions at 59 locations arranged on two hillslopes (31 and 28 locations for hillslope A (HA) and hillslope B (HB), respectively) from 2009 to 2011. The time-averaged mean SWS for the three layers differed significantly (P < 0.05) between HA and HB and was greatly affected by topography and vegetation. Temporal–spatial analyses showed that the temporal variation of SWS decreased with increasing soil depth, while the spatial variation increased on both hillslopes. Comparisons of the values for SDRD and MABE and the number of time-stable locations with SDRD and MABE < 5% among various depths indicated that temporal stability increased with an increase in soil depth. The representative sites identified for each hillslope (two on HA and one on HB) accurately estimated the mean SWS for the three soil layers (R2 ⩾ 0.95, P < 0.001). SWS on the scale of a hillslope was strongly time stable, and the temporal–spatial patterns of SWS were highly dependent on sampling depth. The temporal stability of SWS patterns was controlled by soil texture, organic carbon content, elevation, and properties of the vegetation in the study area, which was characterised by diverse or complex terrains and plant cover. Such effects, however, might vary across hillslopes due to different conditions of wetness and patterns of land use. This study provides useful information on the profiles of mean SWS on the scale of a hillslope, which is necessary for improving the management of soil water on sloping land on the Loess Plateau.

  • estimating soil water content from surface digital image gray level measurements under visible spectrum
    Canadian Journal of Soil Science, 2011
    Co-Authors: Yunqiang Wang, Mingan Shao, Yuanjun Zhu, Robert Horton
    Abstract:

    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.

Yuhua Jia - One of the best experts on this subject based on the ideXlab platform.

  • effects of activities of ants camponotus japonicus on soil moisture cannot be neglected in the northern loess plateau
    Agriculture Ecosystems & Environment, 2017
    Co-Authors: Mingan Shao, Yuhua Jia
    Abstract:

    Abstract Ants can create abundant and continuous soil macropores by burrowing their nests. The hydrological processes in ant nests for different soil types and the effects of ant activities on soil water evaporation are unclear. In this study, we assessed the effects of ant (Camponotus japonicus) nests on preferential flow in the loam and sand soils and on soil water evaporation. First, 12 plots in the sand and loam soils with and without ants were selected for the preferential flow measurements in the field. Second, 200 worker ants and the queen ant were introduced to abandoned cropland plots, and the comprehensive effects of ants on soil moisture down to 340 cm were measured using Neutron Probes. Third, at the Shenmu Erosion and Environment Research Station, 18 iron buckets (20 cm in diameter, 20 cm high) were filled with disturbed loam soil, and a different number of ants was used to assess the effects of ant activities on soil evaporation. The infiltration rate in areas with a nest was approximately 20 times higher than that in no-nest areas. Moreover, the dyeing depths in loam and sand soil with a nest were 47 ± 4.6 and 34 ± 1.5 cm, which were significantly greater than those without a nest (13 ± 2.7 and 23 ± 2.3 cm). Ant nests reached a depth of 60 cm in the field. The effects of a nest on soil moisture existed between 0 and 120 cm deep. Moreover, by moving a high number of “homemade soil aggregates” (1.6 ± 0.18 mm in diameter) onto the soil surface, ants reduced soil evaporation. Ant activities improved soil moisture around the nest by increasing rainfall infiltration and reducing soil water evaporation, which increased the variation in soil water distribution in the soil profile and may benefit the general restoration of vegetation on the Loess Plateau.

Trenton E Franz - One of the best experts on this subject based on the ideXlab platform.

  • assessment of irrigation physics in a land surface modeling framework using non traditional and human practice datasets
    Hydrology and Earth System Sciences, 2017
    Co-Authors: Joseph A Santanello, Patricia M Lawston, Trenton E Franz, M Rodell
    Abstract:

    : Irrigation increases soil moisture, which in turn controls water and energy fluxes from the land surface to the planetary boundary layer and determines plant stress and productivity. Therefore, developing a realistic representation of irrigation is critical to understanding land-atmosphere interactions in agricultural areas. Irrigation parameterizations are becoming more common in land surface models and are growing in sophistication, but there is difficulty in assessing the realism of these schemes, due to limited observations (e.g., soil moisture, evapotranspiration) and scant reporting of irrigation timing and quantity. This study uses the Noah land surface model run at high resolution within NASA's Land Information System to assess the physics of a sprinkler irrigation simulation scheme and model sensitivity to choice of irrigation intensity and greenness fraction datasets over a small, high resolution domain in Nebraska. Differences between experiments are small at the interannual scale but become more apparent at seasonal and daily time scales. In addition, this study uses point and gridded soil moisture observations from fixed and roving Cosmic Ray Neutron Probes and co-located human practice data to evaluate the realism of irrigation amounts and soil moisture impacts simulated by the model. Results show that field-scale heterogeneity resulting from the individual actions of farmers is not captured by the model and the amount of irrigation applied by the model exceeds that applied at the two irrigated fields. However, the seasonal timing of irrigation and soil moisture contrasts between irrigated and non-irrigated areas are simulated well by the model. Overall, the results underscore the necessity of both high-quality meteorological forcing data and proper representation of irrigation for accurate simulation of water and energy states and fluxes over cropland.

  • Incorporation of globally available datasets into the roving cosmic-ray Neutron probe method for estimating field-scale soil water content
    Hydrology and Earth System Sciences, 2016
    Co-Authors: William Alexander Avery, Trenton E Franz, C. E. Finkenbiner, Tiejun Wang, Anthony L. Nguy-robertson, Andrew E. Suyker, Timothy J. Arkebauer, Francisco Munoz-arriola
    Abstract:

    Abstract. The need for accurate, real-time, reliable, and multi-scale soil water content (SWC) monitoring is critical for a multitude of scientific disciplines trying to understand and predict the Earth's terrestrial energy, water, and nutrient cycles. One promising technique to help meet this demand is fixed and roving cosmic-ray Neutron Probes (CRNPs). However, the relationship between observed low-energy Neutrons and SWC is affected by local soil and vegetation calibration parameters. This effect may be accounted for by a calibration equation based on local soil type and the amount of vegetation. However, determining the calibration parameters for this equation is labor- and time-intensive, thus limiting the full potential of the roving CRNP in large surveys and long transects, or its use in novel environments. In this work, our objective is to develop and test the accuracy of globally available datasets (clay weight percent, soil bulk density, and soil organic carbon) to support the operability of the roving CRNP. Here, we develop a 1 km product of soil lattice water over the continental United States (CONUS) using a database of in situ calibration samples and globally available soil taxonomy and soil texture data. We then test the accuracy of the global dataset in the CONUS using comparisons from 61 in situ samples of clay percent (RMSE  =  5.45 wt %, R2  =  0.68), soil bulk density (RMSE  =  0.173 g cm−3, R2  =  0.203), and soil organic carbon (RMSE  =  1.47 wt %, R2  =  0.175). Next, we conduct an uncertainty analysis of the global soil calibration parameters using a Monte Carlo error propagation analysis (maximum RMSE  ∼  0.035 cm3 cm−3 at a SWC  =  0.40 cm3 cm−3). In terms of vegetation, fast-growing crops (i.e., maize and soybeans), grasslands, and forests contribute to the CRNP signal primarily through the water within their biomass and this signal must be accounted for accurate estimation of SWC. We estimated the biomass water signal by using a vegetation index derived from MODIS imagery as a proxy for standing wet biomass (RMSE

  • measurement depth of the cosmic ray soil moisture probe affected by hydrogen from various sources
    Water Resources Research, 2012
    Co-Authors: Trenton E Franz, Marek G Zreda, Ty P A Ferre, Rafael Rosolem, C Zweck, Susan Stillman, Xubin Zeng, W J Shuttleworth
    Abstract:

    [1] We present here a simple and robust framework for quantifying the effective sensor depth of cosmic ray soil moisture Neutron Probes such that reliable water fluxes may be computed from a time series of cosmic ray soil moisture. In particular, we describe how the Neutron signal depends on three near-surface hydrogen sources: surface water, soil moisture, and lattice water (water in minerals present in soil solids) and also their vertical variations. Through a combined modeling study of one-dimensional water flow in soil and Neutron transport in the atmosphere and subsurface, we compare average water content between the simulated soil moisture profiles and the universal calibration equation which is used to estimate water content from Neutron counts. By using a linear sensitivity weighting function, we find that during evaporation and drainage periods the RMSE of the two average water contents is 0.0070 m 3 m � 3 with a maximum deviation of 0.010 m 3 m � 3 for a range of soil types. During infiltration, the RMSE is 0.011 m 3 m � 3 with a maximum deviation of 0.020 m 3 m � 3 , where piston like flow conditions exists for the homogeneous isotropic media. Because piston flow is unlikely during natural conditions at the horizontal scale of hundreds of meters that is measured by the cosmic ray probe, this modeled deviation of 0.020 m 3 m � 3 represents the worst case scenario for cosmic ray sensing of soil moisture. Comparison of cosmic ray soil moisture data and a distributed sensor soil moisture network in Southern Arizona indicates an RMSE of 0.011 m 3 m � 3 over a

J M Abrisqueta - One of the best experts on this subject based on the ideXlab platform.

  • soil water balance trial involving capacitance and Neutron probe measurements
    Agricultural Water Management, 2009
    Co-Authors: Juan Vera, O Mounzer, M C Ruizsanchez, Isabel Abrisqueta, L M Tapia, J M Abrisqueta
    Abstract:

    The objective of this study was to compare soil water measurements made using capacitance and Neutron Probes by means of a water balance experiment in a drainage lysimeter. The experiment was conducted in a 5-year-old drip-irrigated peach orchard (Prunus persica L. Batsch, cv. Flordastar, on GF-677 peach rootstock) planted in a clay loam textured soil located in southern Spain. Four drainage lysimeters (5 m × 5 m × 1.5 m), each containing one tree, were constructed and equipped with one lateral line containing eight drippers per tree, with a discharge rate of 2 L h-1. Three access tubes for the Neutron probe (NP), symmetrically facing three PVC access tubes containing the multi-depth capacitance Probes (MDCP) were located perpendicularly to the drip line (0.2, 0.6 and 1 m). The results demonstrated that both the capacitance and Neutron Probes gave similar soil water content values under steady state hydraulic gradient conditions (0.2 m from the emitter) although some discrepancies were found in heterogeneous soil water distribution conditions (1 m from the emitter), which might be attributed to the smaller soil volume explored by the MDCP compared with the NP. Explanations for the discrepancies between both devised are presented. When water inputs and outputs were fairly constant, the volumetric soil water content could be considered to represent field saturation (?sat = 0.36 m3 m-3). When drainage was zero, there were 2 days when the soil water content was constant and could be considered as field capacity (?fc = 0.31 m3 m-3). The findings suggest that: (i) capacitance Probes can be used for continuous real-time soil water content monitoring unlike the manual measurements obtained with the Neutron probe; (ii) the location of the sensors is critical when used for drip irrigation scheduling and our recommendations for practical agricultural purposes would be to place MDCP sensors in the place representing the highest root density, leading the sensors to become biological sensors rather than mere soil moisture sensors; and (iii) on average, the water balance values determined by lysimeter match those calculated using the data from both Probes. However, due to the smaller soil volume explored by MDCP, more of these sensors must be used to characterize the soil water status in water balance studies