Distribution Of Soil Moisture Content Research Articles

Estimating soil moisture content in citrus orchards using multi-temporal sentinel-1A data-based LSTM and PSO-LSTM models

Soil moisture content is a vital variable in agricultural, hydrological, ecological and climatological processes. However, susceptible to soil type, soil structure, topography, vegetation and human activities, soil moisture content exhibits strong spatial heterogeneity in spatial distribution, which makes it difficult to accurately estimate the soil moisture content distribution information at a large scale using conventional methods. To solve the problem, this study proposed a novel hybrid model (PSO-LSTM) based on the particle swarm optimization (PSO) and long short-term memory (LSTM) network model to accurately predict soil moisture content at a large scale. Five different input combinations were constructed based on the vertical polarization (VV) and cross-polarization (VH) of multi-phase Sentinel-1A data, and the soil moisture content at depths of 5 cm, 10 cm, 20 cm and 40 cm in citrus orchards were estimated using the standalone LSTM and hybrid PSO-LSTM models. The results showed that the estimation accuracy of the hybrid PSO-LSTM model was greater than that of the standalone LSTM model at different depths, with the normalized root mean square error (NRMSE) of 4.568–11.023 % and 18.056–30.156 %, respectively. With the VV polarization as the only inputs, the PSO-LSTM model obtained high prediction accuracy, with the normalized root mean square error (NRMSE) of 5.458–10.125 %, respectively. Therefore, the PSO-LSTM model with VV polarization input was recommended to estimate the soil moisture content at different depths in citrus orchards, which provides important data for decision-making on distributed precision irrigation at a large scale.

Estimation of spatial distribution of soil moisture on steep hillslopes by state-space approach (SSA)

Soil moisture is a critical variable that quantifies precipitation, floods, droughts, irrigation, and other factors with regard to decision-making and risk evaluation. An accurate prediction of soil moisture dynamics is important for soil and environmental management. However, the complex topographic condition and land use in hilly and mountainous areas make it a challenge to monitor and predict soil moisture dynamics in these areas. In this study, the determinants of soil moisture variability were determined by structural equation modeling, and then an attempt was made to estimate the spatial distribution of soil moisture content on steep hillslope using the state-space method. Herein, soil moisture at different depths (0–10, 10–20, and 20–30 cm) was monitored by portable time-domain reflectometer (TDR) along this hillslope (100 m × 180 m). It showed that the spatial variability of soil moisture decreased with increasing soil wetness, primarily in the topsoil (0–10 cm). Soil moisture was correlated with elevation (r = 0.28, 0.50, and 0.28), capillary porosity (r = 0.06, 0.37, and 0.28), soil texture (r for Clay: 0.20, 0.24, and 0.16; r for Sand: −0.25, −0.18, and −0.28), organic carbon (r = −0.31, −0.08, and 0.10) and land use (r = −0.01, 0.28, and 0.24) under different conditions (dry, moderate, and wet). Among these determinants, elevation made direct contributions to soil moisture variation, especially under moderate conditions, while land use made its impacts by altering soil texture. It is encouraging that the state-space approach yielded precise and cost-effective predictions of soil moisture dynamics along this steep hillslope since it gives the minimum root-mean-square error (RMSE) and Akaike information criterion (AIC). Moreover, soil organic carbon (AIC = −4.497, RMSE = 0.104, R2 = 0.899), rock fragment contents (AIC = −4.366, RMSE = 0.111, R2 = 0.878), and elevation (AIC = −3.693, RMSE = 0.156, R2 = 0.629) effectively anticipated the spatial distribution of soil moisture under dry, moderate, and wet conditions, respectively. This study confirms the efficacy of the state-space approach as a valuable tool for soil moisture prediction in areas characterized by complex and spatially heterogeneous conditions.

Distribution of soil moisture content and salts in soil profile affected by subsurface drip irrigation system under different discharge rates of emitter

Distribution of soil moisture content and salts in soil profile affected by subsurface drip irrigation system under different discharge rates of emitter

Study of the water vertical infiltration path in unsaturated soil based on a variational method: application of power function distribution of D(θ)

ABSTRACT The classical Richards equation of water infiltration in unsaturated soil is a partial differential equation, which is non-linear and difficult to solve analytically. Taking time as the variable with the least action, the infiltration path as a function of time is established based on the Richards equation. The vertical infiltration problem of unsaturated soil under gravity is transformed into the functional extremum problem, and solved with the Euler-Lagrange equation. The results show that the diffusion coefficient D(θ) has a functional relationship with the depth of the wetting front. When the type of diffusion coefficient is known, the moisture content of the wetting front at a specified depth, the moisture content of the farthest wetting front and the maximum entropy distribution of soil moisture content can be obtained at the optimal path. Taking the optimal path as the standard, the accuracy of solving the Richards equation by Boltzmann transformation and linear transformation is tested.

Study on the stability analysis of rainfall slope based on G-A model considering moisture content

In this paper, the moisture content on the wetting front is obtained by using the Van Genuchten (VG) model of unsaturated soil, and then the distribution of moisture content in the upper part of the wetting front is simplified as a trapezoid. The Green-Ampt (G-A) infiltration model of infinite slope with unsaturated characteristics is derived. The analytical expression of safety coefficient (FOS) of infinite slope with rainfall is solved by combining the limit equilibrium method with the unsaturated soil shear strength theory phase. The results show that: 1) compared with the traditional G-A model and the combined rectangular and 1/4 oval model, the upper part of the wetting front is simplified to a trapezoidal model, which has great advantages in infiltration rate and cumulative infiltration, especially when the slope is large or the rain intensity is heavy; 2) since the distribution of soil moisture content above the wetting front is considered, the matrix suction at the wetting front is not neglected, and the safety coefficient calculated by the method proposed in this paper is closer to the actual situation than the traditional G-A model.

Spatial Distribution of Soil Moisture Content and Tree Volume Estimation in International Institute of Tropical Agriculture Forest, Ibadan, Nigeria

The role of soil moisture in the survival and growth of trees cannot be over-emphasized and it contributes to the net productivity of the forest. However, information on the spatial distribution of the soil moisture content regarding the tree volume in forest ecosystems especially in Nigeria is limited. Therefore, this study combined spatial and ground data to determine soil moisture distribution and tree volume in the International Institute of Tropical Agriculture (IITA) forest, Ibadan. Satellite images of 1989, 1999, 2009 and 2019 were obtained and processed using topographic and vegetation-based models to examine the soil moisture status of the forest. Satellite-based soil moisture obtained was validated with ground soil moisture data collected in 2019. Tree growth variables were obtained for tree volume computation using Newton’s formular. Forest soil moisture models employed in this study include Topographic Wetness Index (TWI), Temperature Dryness Vegetation Index (TDVI) and Modified Normalized Difference Wetness Index (MNDWI). Relationships between index-based and ground base Soil Moisture Content (SMC), as well as the correlation between soil moisture and tree volume, were examined. The study revealed strong relationships between tree volume and TDVI, SMC, TWI with R2 values of 0.91, 0.85, and 0.75, respectively. The regression values of 0.89 between in-situ soil data and TWI and 0.83 with TDVI ascertain the reliability of satellite data in soil moisture mapping. The decision of which index to apply between TWI and TDVI, therefore, depends on available data since both proved to be reliable. The TWI surface is considered to be a more suitable soil moisture prediction index, while MNDWI exhibited a weak relationship (R2 = 0.03) with ground data. The strong relationships between soil moisture and tree volume suggest tree volume can be predicted based on available soil moisture content. Any slight undesirable change in soil moisture could lead to severe forest conditions.

Spatial‐Temporal Simulations of Soil Moisture Content in a Large Basin of the Loess Plateau, China

Soil moisture is a crucial factor limiting the growth and survival of plants on the Loess Plateau. Its level has a severe impact on plants’ growth and development and the type and distribution characteristics of communities. This study area is the Jihe Basin in the Loess Plateau, China. Multiple linear regression models with different environmental variables (land use, topographic and meteorological factors, etc.) were developed to simulate soil moisture’s spatial and temporal changes by integrating field experiments, indoor analysis, and GIS spatial analysis. The model performances were evaluated in the Jihe Basin, with soil moisture content measurements. The result shows that soil moisture content is positively correlated with soil bulk density, monthly rainfall, topographic wetness index, land use coefficient, and slope aspect coefficient but negatively correlated with the monthly‐averaged temperature and the relative elevation coefficient. The selected variables are all related to the soil moisture content and can account for 75% of the variations of soil moisture content, and the remaining 25% of the variations are related to other factors. Comparing the simulated and measured values at all sampling points shows that the average error of all the simulated values is 0.09, indicating that the simulation has high accuracy. The spatial distribution of soil moisture content is significantly affected by land use and topographic factors, and seasonal variation is remarkable in the year. Seasonal variation of soil moisture content is determined by the seasonal variation of rainfall and the air temperature (determining evaporation) and vegetation growth cycle. Therefore, the proposed model can simulate the spatial and temporal variation of soil moisture content and support developing the soil and water loss model on a basin scale.

Comparison Quality of Interpolation Methods to Estimate Spatial Distribution of Soil Moisture Content

ABSTRACT Determining and predicting both the spatial and temporal variability of soil moisture content is a critical factor in crop production in semi-arid agricultural systems. The objective of this research was to predict the spatial distribution of soil moisture content using ordinary kriging (OK), regression kriging (RK) and cokriging (CK) models. For that purpose, the soil moisture was monitored in the wet period (March, April and May) and dry period (August, September and October) in Kadınhanı district of Konya Province, Turkey. In each monthly sampling period of the study, a total of 278 samples were collected from locations within an area of 29,608.6 ha. The coefficients of variation (CV) of the soil moisture in dry and wet soil conditions were 0.39 and 0.20, respectively. Soil texture, bulk density (BD) and land use were the most important factors influencing soil moisture. In addition, dry soil generally had a smaller nugget effect than wet soil. Overall, CK was able to better estimate the soil moisture content than OK and RK, as evidenced by the smaller mean absolute error (MAE) and mean square error (MSE). RK estimation is more vulnerable to error than CK and OK estimations because the low coefficients of determination in the regression equation lead to increased error and lower confidence in the estimates. The insights generated by the modeling utilized in this study can assist land use planners, land managers and farmers to more efficiently predict, manage and utilize soil moisture content and hence produce larger crops more sustainably.

Slope Stability from a Hydrological Perspective: Taking Typical Soil Slope as an Example

In the traditional research of slope stability, it is difficult to continuously obtain the moisture content of soil in long time sequences. In combination with the precipitation, temperature, and vegetation cover data in the study area, the variable infiltration capacity hydrological model is used to estimate the daily variation of soil moisture content, which is used as a calculation condition for the analysis of slope stability. The results show that, from 1970 to 2010, the spatial‐temporal distribution of soil moisture content in the Weihe River Basin showed an increasing trend. Moreover, the shear strength of soil decreased, but the range was stable at approximately 2%. The strength reduction method based on the M‐C inscribed circle criterion (DP3) shows that the slope stability factor k had an increasing trend for over 40 y. The portion of the period with a k value higher than 1.2 is more than 85% of the entire period, that with a k value between 1 and 1.2 is approximately 9%, and that with a k value less than 1 is approximately 5.5%. The R/S analysis results show that the Hurst coefficients of the τ‐t curve and the k‐t curve are 0.5568 and 0.5888, respectively, and that the slope is in a state of no variation. Based on these factors, the present and future of the slope is in a stable state. This scheme is a method of studying slope stability based on hydrology, and it provides a modern alternative for soil shear strength calculation and geological hazard assessment.

Spatiotemporal distribution of soil moisture in gully facies

Gully erosion is one of the most important forms of land degradation in many regions of the world. Understanding the process of gully erosion therefore is important for better management of the watersheds prone to gully erosion. However, many different aspects of gully erosion, like hydrological behavior, are still not fully understood. The present study investigates the spatial distribution of soil moisture content (SMC), as one of the hydrological factors, at different depths and points across the cross section in the vicinity of the headcut of three gullies located in the Kalat County, Khorasan Razavi Province, Iran. SMCs were measured at depths of 10, 20, 30, 50, 70 and 100 cm at each seven points across the study cross sections one to three days after occurrence of three rain events. Two sampling points were symmetrically located at a distance of 50 cm outside the gully banks, two at the vertex of the sidewalls, two in the middle of the sidewalls and one at the center of gully cross section. SMCs were measured using a weighted method. Results of the study revealed a broad range of changes in SMCs at various depths and points. The minimum and maximum SMCs were found to be about 2% and 38%, respectively, for the study period and gullies under consideration. The coefficient of variation (CV) had drastic changes for various gullies and storm events from 2 to 107%. Results further indicated that SMC moved from the sidewalls towards the floor of the cross section. Accordingly, the maximum SMC for storm events was associated with the point located in the center of gullies, which indicated the role of gully system in draining soil moisture. The findings of this study will help watershed managers understand the important role of gully facies in changing water content of the soil that affects other ecohydrological processes.

Analysis of Spatial Distribution of Soil Moisture Content for Different Soil Layers in Mango Greenhouse

Water content in soil or generally known as soil moisture plays an important role in plant growth. In moving towards a better farm management in precision agriculture concept, it is vital to maintain the uniform growth of plants by preserving the same amount of moisture in the soil. In this study, spatial distribution analysis of soil moisture content was conducted to observe the variability of topsoil and subsoil. A total of 80 soil samples were collected randomly and analysed using the gravimetric method. The data were used to produce soil moisture distribution maps using ArcGIS software. The results show subsoil layer has higher moisture content compared to the topsoil layer with a mean value of 26.17% and 22.84%, respectively. Even though the maps revealed two different patterns of moisture content, both layers fall in high moisture class (21.01% – 28%) with less variation. Thus, this indicates both layers have sufficient amount of moisture content for mango growth and irrigation water supply was adequate.

English

A prototype of a real-time closed loop automatic control system has been successfully developed to suit trickle irrigation systems management. The control system was designed to manage the irrigation system based on collecting data through soil moisture sensors located at three different locations acting each third of the lateral to put the effect of emitters’ flow rate variation along laterals on soil moisture content distribution in consideration. Soil moisture content which will be used to start and stop the irrigation process will be based on the average of three sensors’ readings. Required inputs to manage the irrigation system were soil field capacity (FC), permanent wilting point (WP), and percentage of moisture allowed depletion (MAD). Irrigation process will begin when the soil moisture content equals the desired percentage of available water and it will stop after reaching soil field capacity. The system was provided with ability to check some defects that are related to the irrigation system like clogging, poor uniformity, and water pumping failure. Laboratory assessment showed that the control system has applied the design considerations and is expected to save irrigation time if implemented with low or poor uniformity trickle irrigation networks when compared to high uniformity networks. The study recommended evaluating the effect of this control system implementation in field especially with trickle irrigation networks which show poor uniformity to use the potentials of the control system to predict emitter clogging, and poor uniformity which are mostly appear in such irrigation systems. Key words: Automatic control, closed loop, flow rate variation, modern irrigation systems, real time. &nbsp

Feasibility Investigation of Improving the Modified Green–Ampt Model for Treatment of Horizontal Infiltration in Soil

Water infiltration in soil is a complex process that still requires appreciation of interactions among three phases (soil particles, water and air) to enable accurate estimation of water transport rates. To simulate this process, the Green–Ampt (GA) model and the Modified Green-Ampt (MGA) model introduced in the paper “A new method to estimate soil water infiltration based on a modified Green–Ampt model” have been widely used. The GA model is based on the hypothesis that the advance of the wetting front in soil under matric suction can be treated as a rectangular piston flow that is instantaneously transformed after passage of the infiltration front, and the MGA model does not contain the influence of pore size change. This cannot accurately reflect the soil moisture change process from unsaturation to saturation. Due to soil stratification and other inhomogeneity, predictions produced with these models often differ widely from observations. To quickly obtain the soil moisture distribution after passage of the wetting front for horizontal infiltration, an improved modified Green–Ampt (IMGA) model is presented, which estimates the soil moisture profile along a horizontal column in a piecewise manner with three functions. A logarithmic function is used to describe the gradual soil saturation process in the transmission zone, and two linear functions are used to represent the wetting zone. The algorithm of the IMGA model for estimating the water infiltration rate and cumulative infiltration is configured. To verify the effectiveness of IMGA model, a lab model test was performed, and a numerical model was built to solve the horizontal one-dimensional Richards equation using the finite–element method. The results show that the IMGA model is more accurate than the GA and MGA models. The horizontal soil moisture profiles obtained by the IMGA model are closer to the measured data than the numerical simulation results. The relative errors of the MGA and IMGA models decrease with an increase in infiltration time, whereas that of the GA model first decreases and then increases with infiltration time. The primary novelty of this study is nonlinear description of soil moisture content distribution, and derivation of unit transfer coefficient.

Effect of low and high irrigation water salinity on the soil moisture content distribution and corn crop productivity using

A field experiment was conducted during the autumn season of 2016 at the research station of College of agriculture, University of Basrah, Iraq. The soil texture was clay. The aims of the experiment were to study the effect of two irrigation water salinity levels, which were low water salinity (3.00-3.60 DSm-1) and high water salinity (7-8 DSm-1) and soil amendments on the soil moisture distribution and the yield of corn crop (Zea mays). The irrigation treatments included six treatments using the proposed double drip irrigation system. These treatments are first 100% high water salinity, second 100% Low water salinity, third 50% high water salinity plus 50% low water Salinity (remained constant along the growth season), fourth 50% low water salinity plus 50% high water salinity (variable), fifth 25% low water salinity plus 75% high water salinity and sixth 75% low water salinity plus 25% high water salinity. 20% irrigation water was added as leaching requirements. The soil amendment treatments are: first (0.2% fuel oil plus 0.2% lubrication oil) used on dry weight after they were emulsificated with irrigation water and applicated as a single treatment, second animals manure (2% amendment after C / N adjustment and third the control treatment. The treatments were applicated using RCBD. At the end of growth season of the corn crop the results showed that the moisture content of the soil increased as the amount of the water salinity increased and when the soil amendments were added to the soil. The animal manure surpassed the fuel oil plus lubrication oil in increasing the soil ability in moisture retention. The corn crop yield increased significantly when low water salinity was used with amendment addition. The gravimetric moisture content decreased as the lateral distance increased away from the driper. The highest moisture content was recorded for depth of (15-30 cm).

Effect of low and high irrigation water salinity on the soil moisture content distribution and corn crop productivity using double drip irrigation system.

A field experiment was conducted during the autumn season of 2016 at the research station of College of agriculture, University of Basrah, Iraq. The soil texture was clay. The aims of the experiment were to study the effect of two irrigation water salinity levels, which were low water salinity (3.00-3.60 DSm-1) and high water salinity (7-8 DSm-1) and soil amendments on the soil moisture distribution and the yield of corn crop (Zea mays). The irrigation treatments included six treatments using the proposed double drip irrigation system. These treatments are first 100% high water salinity, second 100% Low water salinity, third 50% high water salinity plus 50% low water Salinity (remained constant along the growth season), fourth 50% low water salinity plus 50% high water salinity (variable), fifth 25% low water salinity plus 75% high water salinity and sixth 75% low water salinity plus 25% high water salinity. 20% irrigation water was added as leaching requirements. The soil amendment treatments are: first (0.2% fuel oil plus 0.2% lubrication oil) used on dry weight after they were emulsificated with irrigation water and applicated as a single treatment, second animals manure (2% amendment after C / N adjustment and third the control treatment. The treatments were applicated using RCBD. At the end of growth season of the corn crop the results showed that the moisture content of the soil increased as the amount of the water salinity increased and when the soil amendments were added to the soil. The animal manure surpassed the fuel oil plus lubrication oil in increasing the soil ability in moisture retention. The corn crop yield increased significantly when low water salinity was used with amendment addition. The gravimetric moisture content decreased as the lateral distance increased away from the driper. The highest moisture content was recorded for depth of (15-30 cm).

Spatial distribution of soil moisture, soil salinity, and root density beneath a cotton field under mulched drip irrigation with brackish and fresh water

Root systems play a vital role in soil-plant interactions. The dynamics and distributions of soil moisture content (SMC), soil salinity, and cotton (Gossypium hirsutum L.) root density under mulched drip irrigation are complex and their interactions are not well understood. The aim of this study is to describe these dynamics and distributions and to evaluate their impacts on cotton above-ground growth and yield during two-year field experiments in a cotton field under mulched drip irrigation with brackish and fresh water. Significant differences were observed for the distributions of SMC, soil salinity, and root length density (RLD) in the root zone for brackish water irrigation treatment (BWT) and fresh water irrigation treatment (FWT). The average SMC and soil salinity in the root zone were higher for BWT than for FWT. The spacing of irrigation lines also had measurable impacts. SMC was less variable when irrigation spacing was small (narrow rows) than beneath wide rows. SMC for BWT and FWT decreased after irrigation due to root water uptake; simultaneously, salt concentration increased, especially in regions where RLD was relatively high. More roots were observed growing in the mulched narrow and wide rows than in the no-mulch zone. Roots were concentrated in the shallowest 30cm. Our study indicated that the average values of the ECe (electrical conductivity of soil saturation extract) in the root zone after BWT irrigation were higher than the published threshold value for optimal cotton yield. The average RLD, shoot dry weight and yield for BWT were observed to be lower than those of FWT as a result of the elevated soil salinity associated with BWT.

Comparative analysis on spatial variability of soil moisture under different land use types in orchard

Spatial variability of soil moisture under different land use types of orchard in Weibei rainfed highland of China was investigated by means of geostatistics. Classical statistical analysis showed that the average soil moisture content of clean tillage, grass land and straw land ranged from 9.36 to 20.86, 8.78 to 23.37 and 10.84 to 20.49, respectively. In 0–40cm soil layer, 10%<CV%<100%, which belongs to moderate variability. Depth in 120–160cm and 160–200cm, CV≤10%, which belong to weak variability. And with the increasing of depth, coefficient of variation decreased. S-W test values pointed out that the distribution of soil moisture content accorded with normal distribution.The results of variation function analysis indicated that the ranges of grass land were larger than clean tillage. Spatial autocorrelation in surface soil was weaker than that of the bottom soil. The reason was that surface soil was more easily influenced by exterior factors. Fractal dimension value decreased with the increasing of soil depth. While the average content of soil moisture showed the opposite trend. According to kriging interpolation, the high-value areas of clean tillage mainly concentrated in (13.4, 27.8), (28.0, 32.5) and (27.0, 10.4), and low-value areas were in (13.8, 6.6). However, the high-value of grass areas mainly focused on around (11.5, 11.5), and low-value were in (11.2, 11.2) and (25.5, 25.5). The change of the other areas’ soil moisture were not obvious in a wide range. It has a good consistency. Therefore, in the dry season, it was advisable to choose straw mulching, and reduce grass cultivation, to achieve the goal of improving soil moisture content.

Parallel Algorithms in a Physically-Based Hydrologic Soil Model

Enormous river basin information has been collected by for high resolution of the physically-based distributed hydrological model, while the scales of computational domain are often restricted by the intensive calculation. The parallel algorithms of physically-based regional hydrologic soil model (P-RHSM) in OpenGeoSys are brought forward in this paper. The object-oriented C++ programming in the model approaches the two objectives: one is data structure organizations including the spatial discretization of the computation domain with nodes density arrangement and solutions communication of temporal variables, the other is computational efficiency by parallel computing. The Message passing interface (MPI) communication is implemented in P-RHSM which is carried out on Linux supported symmetric multiprocessing computers. P-RHSM is applied to Heihe basin in the northwest China. The high-resolution results of temporal soil moisture content distribution, front movement and parallel performance is presented.

典型岩溶洼地土壤水分的空间分布及影响因素

PDF HTML阅读 XML下载 导出引用 引用提醒 典型岩溶洼地土壤水分的空间分布及影响因素 DOI: 10.5846/stxb201310282597 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 中国科学院西部行动计划（KZCX2-XB3-10）；国家自然科学基金项目（41171187，41201291）；国家科技支撑计划课题（2010BAE00739-02） Research on spatial distribution and influencing factor of soil moisture in typical depression area of karst region Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:在桂西北典型岩溶洼地的旱季和雨季，用地统计学结合GIS方法研究了洼地表层（0-16cm）土壤水分的空间分布特征及其影响因素。结果表明：土壤含水量受前期降雨量的影响，且旱季土壤水分对降雨量的反应较雨季敏感。土壤水分均呈中等变异且变异系数随着平均含水量的增加而减少。土壤水分的半方差参数显示土壤水分空间变异及其主导因素随旱、雨季而不同。此外，不同取样区域及取样时段内土壤含水量高低差别明显，分布格局及空间变异程度各异，这主要与当地环境和人为因素的综合影响有关。旱、雨季土壤水分均与前期降雨导致的土壤平均含水量变化呈相反趋势，且不同土地利用方式下的土壤含水量不同。土壤含水量还与土壤有机碳含量呈显著正相关，此外，地势及裸岩率也是造成洼地土壤水分变异及其分布差异的重要因素。下一步应根据旱季和雨季土壤水分分布及影响因素的差异，在岩溶洼地采取有针对性地土壤水资源利用及其水分管理策略。 Abstract:The characterization of the spatial variability, distribution and influencing factor of soil moisture is of paramount importance in many ecological processes and operational applications, especially in the karst area of China. In this study, soil moisture was measured with a portable T DR for a layer depth of 0-16 cm in a karst depression area of southwest China during the dry and rainy seasons of 2005, and the spatial variability, distribution and influencing factors of soil moisture content were investigated by using the geo-statistics and GIS method. The results indicated that the surface soil moisture content was influenced by the antecedent rainfall (the rainfall accumulation 10 days before the sampling time) and it was more sensitive to the antecedent rainfall in dry season than that in rainy season. The mean soil moisture content varied from 21.67% to 28.79% during the dry and rainy seasons. The soil moisture content showed middle variability, and the CV values decreased with the increasing mean soil moisture content either in dry or rainy season. The parameters of semi-variogram theoretical models of soil moisture content indicated that the spatial variability and its dominant influencing factor of soil moisture content both changed with the dry and rainy season. Similar results were also obtained from the pattern of soil moisture content, which generated by the ordinary kriging interpolation. The soil moisture content, its distribution and variability were always different at different sampling time and region. But, a similar pattern of the soil moisture content was observed on the whole in the two seasons, with drier zones always becoming drier and vice versa. Also, the distribution of soil moisture content showed mosaic pattern in dry season, compared with the strip or band pattern in rainy season, which were caused by the combined influence of environmental factors and human activities. What's more, the variability of soil moisture content by CV values decreased with the increasing mean soil moisture content due to the antecedent rainfall either in dry or rainy season. And the soil moisture content was different in different land use types. The abandoned field and orchard field always had relatively higher soil moisture content either in dry or rainy season, followed by the rehabilitated field and gazing field, and the cultivated field had relative lower soil moisture content. Furthermore, a significant positive correlation was found between the soil moisture content and the soil organic carbon. Altitude and bare-rock ratio were also important factors influencing the soil moisture content in the depression area. Therefore, rational strategies of soil water resource usage and management should be made according to the different spatial distributions and influencing factors of soil moisture content in dry and rainy season in the depression area of karst region. 参考文献 相似文献 引证文献

A Physically Based Microscopic Model of Root-Water Uptake

The present study involves development of a microscopic numerical model for simulating radial and vertical moisture flow towards plant root, root-water uptake and finally flow through the plant to the atmosphere. The model essentially comprises a numerical solution of the Richard’s equation in axis-symmetric polar co-ordinate system by finite difference method. The simulation of the subsequent water movement (from root to canopy and from canopy to atmosphere) is accomplished indirectly through a boundary condition at the root-soil interface. This boundary condition is derived by invoking the meteorological conditions prevailing over the plant leaf surface, and a plant conductivity parameter (plant transmissivity) is defined herein. The model provides distribution of soil moisture content, and the root-water uptake at discrete times. The plant transmissivity has been estimated for wheat crop. KeywordsRoot-Water Uptake; Microscopic Model; Richard’s Equation; Transpiration