Background,aim,and scope Soil saturated hydraulic conductivity(K_(s))is a key parameter in the hydrological cycle of soil;however,we have very limited understanding of K_(s) characteristics and the factors that inf lu...Background,aim,and scope Soil saturated hydraulic conductivity(K_(s))is a key parameter in the hydrological cycle of soil;however,we have very limited understanding of K_(s) characteristics and the factors that inf luence this key parameter in the Mu Us sandy land(MUSL).Quantifying the impact of changes in land use in the Mu Us sandy land on K_(s) will provide a key foundation for understanding the regional water cycle,but will also provide a scientific basis for the governance of the MUSL.Materials and methods In this study,we determined K_(s) and the basic physical and chemical properties of soil(i.e.,organic matter,bulk density,and soil particle composition)within the first 100 cm layer of four different land use patterns(farmland,tree,shrub,and grassland)in the MUSL.The vertical variation of K_(s) and the factors that influence this key parameter were analyzed and a transfer function for estimating K_(s) was established based on a multiple stepwise regression model.Results The K_(s) of farmland,tree,and shrub increased gradually with soil depth while that of grassland remained unchanged.The K_(s) of the four patterns of land use were moderately variable;mean K_(s)values were ranked as follows:grassland(1.38 mm·min^(-1))<tree(1.76 mm·min^(-1))<farmland(1.82 mm·min^(-1))<shrub(3.30 mm·min^(-1)).The correlation between K_(s) and organic matter,bulk density,and soil particle composition,varied across different land use patterns.A multiple stepwise regression model showed that silt,coarse sand,bulk density,and organic matter,were key predictive factors for the K_(s) of farmland,tree,shrub,and grassland,in the MUSL.Discussion The vertical distribution trend for K_(s) in farmland is known to be predominantly influenced by cultivation,fertilization,and other factors.The general aim is to improve the water-holding capacity of shallow soil on farmland(0-30 cm in depth)to conserve water and nutrients;research has shown that the K_(s) of farmland increases with soil depth.The root growth of tree and shrub in sandy land exerts mechanical force on the soil due to biophysical processes involving rhizospheres,thus leading to a significant change in K_(s).We found that shallow high-density fine roots increased the volume of soil pores and eliminated large pores,thus resulting in a reduction in shallow K_(s).Therefore,the K_(s) of tree and shrub increased with soil depth.Analysis also showed that the K_(s) of grassland did not change significantly and exhibited the lowest mean value when compared to other land use patterns.This finding was predominantly due to the shallow root system of grasslands and because this land use pattern is not subject to human activities such as cultivation and fertilization;consequently,there was no significant change in K_(s) with depth;grassland also had the lowest mean K_(s).We also established a transfer function for K_(s) for different land use patterns in the MUSL.However,the predictive factors for K_(s) in different land use patterns are known to be affected by soil cultivation methods,vegetation restoration modes,the distribution of soil moisture,and other factors,thus resulting in key differences.Therefore,when using the transfer function to predict K_(s) in other areas,it will be necessary to perform parameter calibration and further verification.Conclusions In the MUSL,the K_(s) of farmland,tree,and shrub gradually increased with soil depth;however,the K_(s) of grassland showed no significant variation in terms of vertical distribution.The mean K_(s) values of different land use patterns were ranked as follows:shrub>farmland>tree>grassland;all land use patterns showed moderate levels of variability.The K_(s) for different land use patterns exhibited differing degrees of correlation with soil physical and chemical properties;of these,clay,silt,sand,bulk density,and organic matter,were identified as important variables for predicting K_(s) in farmland,tree,shrub,and grassland,respectively.Recommendations and perspectives In this study,we used a stepwise multiple regression model to establish a transfer function prediction model for K_(s) for different land use patterns;this model possessed high estimation accuracy.The ability to predict K_(s) in the MUSL is very important in terms of the conservation of water and nutrients.展开更多
Hydraulic conductivity is the ability of a porous media to transfer water through its pore matrix. That is a key parameter for the design and analysis of soil fluid associated structures and issues. This paper present...Hydraulic conductivity is the ability of a porous media to transfer water through its pore matrix. That is a key parameter for the design and analysis of soil fluid associated structures and issues. This paper presents the test results of the vertical hydraulic conductivity k<sub>v</sub><sub> </sub>carried out on one poorly graded sand and three gap graded gravely sand. It was found that the vertical hydraulic conductivity of saturated soil depends on the grain size distribution curve, on the initial relative density of the soil. Compilation of these current test results and other test results published, shows that the common approaches predict well to some extent the vertical hydraulic conductivity k<sub>v</sub> for the poorly graded sand materials and underestimate the k<sub>v</sub> values for gap graded gravely sand materials. Therefore, new approaches are developed for the prediction of the vertical hydraulic conductivity in saturated poorly graded sand and gap graded gravely sand. The derived results from the new approaches lie in the range of the recommended values by (EAU 2012) and (NAVFAC DM 7 1974).展开更多
Kozeny-Carman(KC) equation is a well-known relation between hydraulic conductivity and pore properties in porous material. The applications of KC equation to predicting saturated hydraulic conductivities of sands and ...Kozeny-Carman(KC) equation is a well-known relation between hydraulic conductivity and pore properties in porous material. The applications of KC equation to predicting saturated hydraulic conductivities of sands and non-expansive soils are well documented. However, KC equation is incapable of predicting saturated hydraulic conductivity of expansive soil(e.g. bentonite) well. Based on a new dualpore system, this study modified KC equation for improving the prediction of saturated hydraulic conductivities of bentonites. In this study, an assumption that inter-layer space(micropore) has limited effect on fluid flow performance of compacted bentonite was adopted. The critical parameters including total porosity and total tortuosity in conventional KC equation were replaced by macroporosity and tortuosity of macropore, respectively. Macroporosity and microporosity were calculated by basal spacing of compacted bentonite, which was estimated by assuming that specific surface area is changeable during saturation process. A comprehensive comparison of bentonite’s saturated hydraulic conductivity predictions, including modified KC equation proposed in this study, conventional KC equation, and prediction method based on diffuse double layer(DDL) theory, was carried out. It was found that the predicted saturated hydraulic conductivity of bentonites calculated using modified KC equation fitted the experimental data better than others to a certain extent.展开更多
Simulation models are tools that can be used to explore, for example, effects of cultural practices on soil erosion and irrigation on crop yield. However, often these models require many soil related input data of whi...Simulation models are tools that can be used to explore, for example, effects of cultural practices on soil erosion and irrigation on crop yield. However, often these models require many soil related input data of which the saturated hydraulic conductivity (Ks) is one of the most important ones. These data are usually not available and experimental determination is both expensive and time consuming. Therefore, pedotransfer functions are often used, which make use of simple and often readily available soil information to calculate required input values for models, such as soil hydraulic values. Our objective was to test the Rosetta pedotransfer function to calculate Ks. Research was conducted in a 64-ha field near Lamesa, Texas, USA. Field measurements of soil texture and bulk density, and laboratory measurements of soil water retention at field capacity (–33 kPa) and permanent wilting point (–1500 kPa), were taken to implement Rosetta. Calculated values of Ks were then compared to measured Ks on undisturbed soil samples. Results showed that Rosetta could be used to obtain values of Ks for a field with different textures. The Root Mean Square Difference (RMSD) of Ks at 0.15 m soil depth was 7.81 × 10–7 m·s–1. Further, for a given soil texture the variability, from 2.30 × 10–7 to 2.66 × 10–6 m·s-1, of measured Ks was larger than the corresponding RMSD. We conclude that Rosetta is a tool that can be used to calculate Ks in the absence of measured values, for this particular soil. Level H5 of Rosetta yielded the best results when using the measured input data and thus calculated values of Ks can be used as input in simulation models.展开更多
Darcy’s law is applied to describe the steady flow processes in which the flux remains constant with time along the conducting system. Due to the dispersion and migration of colloidal particles and lodging in the soi...Darcy’s law is applied to describe the steady flow processes in which the flux remains constant with time along the conducting system. Due to the dispersion and migration of colloidal particles and lodging in the soil pores the reduction in hydraulic conductivity occurs with time in particular when the soil and the percolating solution are affected by electrolyte concentration. Hence, the aim of this study is to find empirical equations that can be used to predict the flux with time. Data for the effluent volume versus time (up to 6 hours) which was collected for three soils (located at Quevedo-Los Rios region) treated by two salt solutions (5 and 50 meq/l) with different SAR values were used to test certain mathematical forms of equations. Only four empirical equations were found to perfectly fit the data (flux vs time) whereas, fitting the calculated and measured data of the hydraulic conductivity for all soils produced regression factors R2 ≥ 0.99. So, these equations can be applied to predict the hydraulic conductivity and to characterize the flow process at saturated conditions of the studied soils with great confidence. The Hoerl function model was the best of all equations for application as the fitting degrees were almost perfect for all studied soils at 5 and 50 meq/l. It was observed for all equations that one of the fitting parameters would always represent the initial hydraulic conductivity (Kos) that was evaluated graphically at zero time by extrapolation.展开更多
As an important soil property,saturated hydraulic conductivity(Ks)controls many hydrological processes,such as runoff generation types,soil moisture storage and water movement.Because of the extremely harsh natural en...As an important soil property,saturated hydraulic conductivity(Ks)controls many hydrological processes,such as runoff generation types,soil moisture storage and water movement.Because of the extremely harsh natural environmental conditions and soil containing a significant fraction of gravel fragments in high-elevation mountainous catchments,the measurement data of Ks and other soil properties are seriously lacking,which leads to poor understanding on its hydrological processes and water cycle.In this study,the vertical variation(0-150 cm)of Ks and other soil properties from 38 soil profiles were measured under five different land cover types(alpine barren,forest,marshy meadow,alpine shrub and alpine meadow)in a small catchment in Qilian Mountains,northwestern China.A typical characteristic of soil in mountainous areas is widespread presence of rock and gravel,and the results showed that the more rock and gravel in the soil,the higher Ks and bulk density and the lower the soil capillary porosity,field water capacity and total porosity.The Ks of the lower layer with rock and gravel(18.49±10.22 mm·min-1)was significantly higher than that of the upper layer with relatively fine textured soil(0.18±0.18 mm·min-1).The order of values of the Ks in different land cover types was alpine barren,forest,alpine shrub,marshy meadow and alpine meadow,and the values of the Ks in the alpine barren were significantly higher than those of other land covers.Most rainfall events in the research catchment had low rain intensity(<0.04 mm·min-1),and deep percolation(DP)was the dominant runoff generation type.When the rainfall intensity increased(0.11 mm·min-1),subsurface stormflow(SSF)appeared in the alpine meadow.Infiltration excess overland flow(IOF),SSF and DP existed simultaneously only when the rainfall intensity was extremely high(1.91 mm·min-1).IOF and SSF were almost never appeared in the alpine barren because of high Ks.The alpine barren was the main runoffcontributed area in the mountainous catchment because of high Ks and low water-holding capacity,and the alpine shrub and meadow showed more ecological functions such as natural water storage and replenishment pool than contribution of runoff.展开更多
The objective of this study was to examine the effect of compost, rice straw and sawdust amendment on hydraulic and pore characteristics of a clay loam soil. Amendments were applied at an application rate of0.2 m3/m3 ...The objective of this study was to examine the effect of compost, rice straw and sawdust amendment on hydraulic and pore characteristics of a clay loam soil. Amendments were applied at an application rate of0.2 m3/m3 (apparent soil volume) in three rectangular plots each comprising an area of3.0 m2. Water retention characteristics were measured by hanging water column and centrifuge method. Hydraulic conductivity was measured by disc permeameter at -15.0, -6.0, -3.0 and0 cmof water pressure heads. Volumetric water content increased in all amended soils, compared with the control. Unsaturated hydraulic conductivity was almost identical for straw and sawdust at all pressure heads, although that for compost amended soils were much higher. Field saturated hydraulic conductivity (Kfs) was higher in organic matter amended soils as were number of macropores (14.7% - 29.2%). Contribution of each pore class to the total saturated flux was evaluated from the hydraulic conductivity and water retention measurement. A new alternative weighed factor (We) was proposed to estimate the actual contribution of macro- and mesopores to the total saturated water flux. The Wg was found to be more representative for calculating pores contribution to saturated water flux than that of hydraulic conductivity measurement. Although there is only a small fraction of the total porosity, amendment increased effective macro- and meso-porosity (qe). Pores in the amended soils were hydraulically active and water movement was dominated by gravity. Collectively, our results demonstrated that organic matter generated as agricultural by-product could effectively be used to improve soil展开更多
Saturated hydraulic conductivity (Ks) is an important soil hydraulic parameter for charactering the rate of water flow across the soils and is mainly related to its high spatial variability. In a small watershed with ...Saturated hydraulic conductivity (Ks) is an important soil hydraulic parameter for charactering the rate of water flow across the soils and is mainly related to its high spatial variability. In a small watershed with the area of 0.27 km2 in the Loess Plateau, Ks of 197 soil samples under different vegetations and landforms were measured. Ks had a moderate variability for total samples. The forestland had high Ks with low coefficient of variation (CV), but the grassland in the watershed bottom had low Ks with big CV. Ks had moderate correlation in space distribution and combined both structural and random factors. At the N-S and E-W directions of watershed being parallel and normal to the stream valley, Ks had relatively weak correlation, indicating that the random factor was the dominate reason causing spatial variance. At the NE-SW and SE-NW directions, Ks had relatively strong correlation due to structural factors such as geomorphology and vegetation distribution patterns. Kriging optimal estimation method was used to produce Ks contour map. The Kriging standard deviation (SD) was the lowest near the sampling points, and increased along with the distance to sampling points. In the Loess Plateau region, soil texture is relatively even, and the vegetation distribution pattern was the key factor affecting spatial variability of Ks.展开更多
文摘Background,aim,and scope Soil saturated hydraulic conductivity(K_(s))is a key parameter in the hydrological cycle of soil;however,we have very limited understanding of K_(s) characteristics and the factors that inf luence this key parameter in the Mu Us sandy land(MUSL).Quantifying the impact of changes in land use in the Mu Us sandy land on K_(s) will provide a key foundation for understanding the regional water cycle,but will also provide a scientific basis for the governance of the MUSL.Materials and methods In this study,we determined K_(s) and the basic physical and chemical properties of soil(i.e.,organic matter,bulk density,and soil particle composition)within the first 100 cm layer of four different land use patterns(farmland,tree,shrub,and grassland)in the MUSL.The vertical variation of K_(s) and the factors that influence this key parameter were analyzed and a transfer function for estimating K_(s) was established based on a multiple stepwise regression model.Results The K_(s) of farmland,tree,and shrub increased gradually with soil depth while that of grassland remained unchanged.The K_(s) of the four patterns of land use were moderately variable;mean K_(s)values were ranked as follows:grassland(1.38 mm·min^(-1))<tree(1.76 mm·min^(-1))<farmland(1.82 mm·min^(-1))<shrub(3.30 mm·min^(-1)).The correlation between K_(s) and organic matter,bulk density,and soil particle composition,varied across different land use patterns.A multiple stepwise regression model showed that silt,coarse sand,bulk density,and organic matter,were key predictive factors for the K_(s) of farmland,tree,shrub,and grassland,in the MUSL.Discussion The vertical distribution trend for K_(s) in farmland is known to be predominantly influenced by cultivation,fertilization,and other factors.The general aim is to improve the water-holding capacity of shallow soil on farmland(0-30 cm in depth)to conserve water and nutrients;research has shown that the K_(s) of farmland increases with soil depth.The root growth of tree and shrub in sandy land exerts mechanical force on the soil due to biophysical processes involving rhizospheres,thus leading to a significant change in K_(s).We found that shallow high-density fine roots increased the volume of soil pores and eliminated large pores,thus resulting in a reduction in shallow K_(s).Therefore,the K_(s) of tree and shrub increased with soil depth.Analysis also showed that the K_(s) of grassland did not change significantly and exhibited the lowest mean value when compared to other land use patterns.This finding was predominantly due to the shallow root system of grasslands and because this land use pattern is not subject to human activities such as cultivation and fertilization;consequently,there was no significant change in K_(s) with depth;grassland also had the lowest mean K_(s).We also established a transfer function for K_(s) for different land use patterns in the MUSL.However,the predictive factors for K_(s) in different land use patterns are known to be affected by soil cultivation methods,vegetation restoration modes,the distribution of soil moisture,and other factors,thus resulting in key differences.Therefore,when using the transfer function to predict K_(s) in other areas,it will be necessary to perform parameter calibration and further verification.Conclusions In the MUSL,the K_(s) of farmland,tree,and shrub gradually increased with soil depth;however,the K_(s) of grassland showed no significant variation in terms of vertical distribution.The mean K_(s) values of different land use patterns were ranked as follows:shrub>farmland>tree>grassland;all land use patterns showed moderate levels of variability.The K_(s) for different land use patterns exhibited differing degrees of correlation with soil physical and chemical properties;of these,clay,silt,sand,bulk density,and organic matter,were identified as important variables for predicting K_(s) in farmland,tree,shrub,and grassland,respectively.Recommendations and perspectives In this study,we used a stepwise multiple regression model to establish a transfer function prediction model for K_(s) for different land use patterns;this model possessed high estimation accuracy.The ability to predict K_(s) in the MUSL is very important in terms of the conservation of water and nutrients.
文摘Hydraulic conductivity is the ability of a porous media to transfer water through its pore matrix. That is a key parameter for the design and analysis of soil fluid associated structures and issues. This paper presents the test results of the vertical hydraulic conductivity k<sub>v</sub><sub> </sub>carried out on one poorly graded sand and three gap graded gravely sand. It was found that the vertical hydraulic conductivity of saturated soil depends on the grain size distribution curve, on the initial relative density of the soil. Compilation of these current test results and other test results published, shows that the common approaches predict well to some extent the vertical hydraulic conductivity k<sub>v</sub> for the poorly graded sand materials and underestimate the k<sub>v</sub> values for gap graded gravely sand materials. Therefore, new approaches are developed for the prediction of the vertical hydraulic conductivity in saturated poorly graded sand and gap graded gravely sand. The derived results from the new approaches lie in the range of the recommended values by (EAU 2012) and (NAVFAC DM 7 1974).
基金support from the Ministry of Economy, Trade, and Industry (METI) of Japanfunding support from Postgraduate Research & Practice Innovation Program of Jiangsu Province, China (Grant No. KYCX21_0122)
文摘Kozeny-Carman(KC) equation is a well-known relation between hydraulic conductivity and pore properties in porous material. The applications of KC equation to predicting saturated hydraulic conductivities of sands and non-expansive soils are well documented. However, KC equation is incapable of predicting saturated hydraulic conductivity of expansive soil(e.g. bentonite) well. Based on a new dualpore system, this study modified KC equation for improving the prediction of saturated hydraulic conductivities of bentonites. In this study, an assumption that inter-layer space(micropore) has limited effect on fluid flow performance of compacted bentonite was adopted. The critical parameters including total porosity and total tortuosity in conventional KC equation were replaced by macroporosity and tortuosity of macropore, respectively. Macroporosity and microporosity were calculated by basal spacing of compacted bentonite, which was estimated by assuming that specific surface area is changeable during saturation process. A comprehensive comparison of bentonite’s saturated hydraulic conductivity predictions, including modified KC equation proposed in this study, conventional KC equation, and prediction method based on diffuse double layer(DDL) theory, was carried out. It was found that the predicted saturated hydraulic conductivity of bentonites calculated using modified KC equation fitted the experimental data better than others to a certain extent.
文摘Simulation models are tools that can be used to explore, for example, effects of cultural practices on soil erosion and irrigation on crop yield. However, often these models require many soil related input data of which the saturated hydraulic conductivity (Ks) is one of the most important ones. These data are usually not available and experimental determination is both expensive and time consuming. Therefore, pedotransfer functions are often used, which make use of simple and often readily available soil information to calculate required input values for models, such as soil hydraulic values. Our objective was to test the Rosetta pedotransfer function to calculate Ks. Research was conducted in a 64-ha field near Lamesa, Texas, USA. Field measurements of soil texture and bulk density, and laboratory measurements of soil water retention at field capacity (–33 kPa) and permanent wilting point (–1500 kPa), were taken to implement Rosetta. Calculated values of Ks were then compared to measured Ks on undisturbed soil samples. Results showed that Rosetta could be used to obtain values of Ks for a field with different textures. The Root Mean Square Difference (RMSD) of Ks at 0.15 m soil depth was 7.81 × 10–7 m·s–1. Further, for a given soil texture the variability, from 2.30 × 10–7 to 2.66 × 10–6 m·s-1, of measured Ks was larger than the corresponding RMSD. We conclude that Rosetta is a tool that can be used to calculate Ks in the absence of measured values, for this particular soil. Level H5 of Rosetta yielded the best results when using the measured input data and thus calculated values of Ks can be used as input in simulation models.
文摘Darcy’s law is applied to describe the steady flow processes in which the flux remains constant with time along the conducting system. Due to the dispersion and migration of colloidal particles and lodging in the soil pores the reduction in hydraulic conductivity occurs with time in particular when the soil and the percolating solution are affected by electrolyte concentration. Hence, the aim of this study is to find empirical equations that can be used to predict the flux with time. Data for the effluent volume versus time (up to 6 hours) which was collected for three soils (located at Quevedo-Los Rios region) treated by two salt solutions (5 and 50 meq/l) with different SAR values were used to test certain mathematical forms of equations. Only four empirical equations were found to perfectly fit the data (flux vs time) whereas, fitting the calculated and measured data of the hydraulic conductivity for all soils produced regression factors R2 ≥ 0.99. So, these equations can be applied to predict the hydraulic conductivity and to characterize the flow process at saturated conditions of the studied soils with great confidence. The Hoerl function model was the best of all equations for application as the fitting degrees were almost perfect for all studied soils at 5 and 50 meq/l. It was observed for all equations that one of the fitting parameters would always represent the initial hydraulic conductivity (Kos) that was evaluated graphically at zero time by extrapolation.
基金financial support from the National Natural Sciences Foundation of China(Nos.41401041,41690141 and 41671029)。
文摘As an important soil property,saturated hydraulic conductivity(Ks)controls many hydrological processes,such as runoff generation types,soil moisture storage and water movement.Because of the extremely harsh natural environmental conditions and soil containing a significant fraction of gravel fragments in high-elevation mountainous catchments,the measurement data of Ks and other soil properties are seriously lacking,which leads to poor understanding on its hydrological processes and water cycle.In this study,the vertical variation(0-150 cm)of Ks and other soil properties from 38 soil profiles were measured under five different land cover types(alpine barren,forest,marshy meadow,alpine shrub and alpine meadow)in a small catchment in Qilian Mountains,northwestern China.A typical characteristic of soil in mountainous areas is widespread presence of rock and gravel,and the results showed that the more rock and gravel in the soil,the higher Ks and bulk density and the lower the soil capillary porosity,field water capacity and total porosity.The Ks of the lower layer with rock and gravel(18.49±10.22 mm·min-1)was significantly higher than that of the upper layer with relatively fine textured soil(0.18±0.18 mm·min-1).The order of values of the Ks in different land cover types was alpine barren,forest,alpine shrub,marshy meadow and alpine meadow,and the values of the Ks in the alpine barren were significantly higher than those of other land covers.Most rainfall events in the research catchment had low rain intensity(<0.04 mm·min-1),and deep percolation(DP)was the dominant runoff generation type.When the rainfall intensity increased(0.11 mm·min-1),subsurface stormflow(SSF)appeared in the alpine meadow.Infiltration excess overland flow(IOF),SSF and DP existed simultaneously only when the rainfall intensity was extremely high(1.91 mm·min-1).IOF and SSF were almost never appeared in the alpine barren because of high Ks.The alpine barren was the main runoffcontributed area in the mountainous catchment because of high Ks and low water-holding capacity,and the alpine shrub and meadow showed more ecological functions such as natural water storage and replenishment pool than contribution of runoff.
文摘The objective of this study was to examine the effect of compost, rice straw and sawdust amendment on hydraulic and pore characteristics of a clay loam soil. Amendments were applied at an application rate of0.2 m3/m3 (apparent soil volume) in three rectangular plots each comprising an area of3.0 m2. Water retention characteristics were measured by hanging water column and centrifuge method. Hydraulic conductivity was measured by disc permeameter at -15.0, -6.0, -3.0 and0 cmof water pressure heads. Volumetric water content increased in all amended soils, compared with the control. Unsaturated hydraulic conductivity was almost identical for straw and sawdust at all pressure heads, although that for compost amended soils were much higher. Field saturated hydraulic conductivity (Kfs) was higher in organic matter amended soils as were number of macropores (14.7% - 29.2%). Contribution of each pore class to the total saturated flux was evaluated from the hydraulic conductivity and water retention measurement. A new alternative weighed factor (We) was proposed to estimate the actual contribution of macro- and mesopores to the total saturated water flux. The Wg was found to be more representative for calculating pores contribution to saturated water flux than that of hydraulic conductivity measurement. Although there is only a small fraction of the total porosity, amendment increased effective macro- and meso-porosity (qe). Pores in the amended soils were hydraulically active and water movement was dominated by gravity. Collectively, our results demonstrated that organic matter generated as agricultural by-product could effectively be used to improve soil
基金National NaturalScience Foundation grant (40474178, 30230290)Shaanxi Provincial Office of Education special projects (05JK241)
文摘Saturated hydraulic conductivity (Ks) is an important soil hydraulic parameter for charactering the rate of water flow across the soils and is mainly related to its high spatial variability. In a small watershed with the area of 0.27 km2 in the Loess Plateau, Ks of 197 soil samples under different vegetations and landforms were measured. Ks had a moderate variability for total samples. The forestland had high Ks with low coefficient of variation (CV), but the grassland in the watershed bottom had low Ks with big CV. Ks had moderate correlation in space distribution and combined both structural and random factors. At the N-S and E-W directions of watershed being parallel and normal to the stream valley, Ks had relatively weak correlation, indicating that the random factor was the dominate reason causing spatial variance. At the NE-SW and SE-NW directions, Ks had relatively strong correlation due to structural factors such as geomorphology and vegetation distribution patterns. Kriging optimal estimation method was used to produce Ks contour map. The Kriging standard deviation (SD) was the lowest near the sampling points, and increased along with the distance to sampling points. In the Loess Plateau region, soil texture is relatively even, and the vegetation distribution pattern was the key factor affecting spatial variability of Ks.
