scholarly journals Soil Moisture Retrieval Model for Remote Sensing Using Reflected Hyperspectral Information

2019 ◽  
Vol 11 (3) ◽  
pp. 366 ◽  
Author(s):  
Jing Yuan ◽  
Xin Wang ◽  
Chang-xiang Yan ◽  
Shu-rong Wang ◽  
Xue-ping Ju ◽  
...  

The variation and the spatial–temporal distribution of soil water content have significant effects on heat balance, agricultural moisture, etc. A soil moisture (SM) retrieval model can provide a theoretical basis for realizing a rapid test and revealing the spatial–temporal variation of the surface water. However, remote sensors do not measure soil water content directly. Therefore, it is of great importance to establish a SM retrieval model. In this paper, the relationship between SM and diffuse reflectance was first derived using the absorption coefficient and scattering coefficient related to SM. Then, based on Kubelka–Munk (KM) theory, the SM retrieval model using reflectance information was further derived, which is a semi-empirical model with an unknown parameter obtained either from fitting or from experimental measurements. The validity and reliability of the model were confirmed with the validation set. The results showed that the root mean square errors of prediction (RMSEPs) of four soils were generally less than 0.017, while the coefficients of determination (R2s) of four soils were generally more than 0.85, and the ratios of the performance to deviation (RPDs) of four soils were greater than 2.5 (470–2400 nm). Therefore, the model has high prediction accuracy, and can be well applied to the prediction of water content in different sorts of soils.

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 1007 ◽  
Author(s):  
Bruno Silva Ursulino ◽  
Suzana Maria Gico Lima Montenegro ◽  
Artur Paiva Coutinho ◽  
Victor Hugo Rabelo Coelho ◽  
Diego Cezar dos Santos Araújo ◽  
...  

Knowledge about soil moisture dynamics and their relation with rainfall, evapotranspiration, and soil physical properties is fundamental for understanding the hydrological processes in a region. Given the difficulties of measurement and the scarcity of surface soil moisture data in some places such as Northeast Brazil, modelling has become a robust tool to overcome such limitations. This study investigated the dynamics of soil water content in two plots in the Gameleira Experimental River Basin, Northeast Brazil. For this, Time Domain Reflectometry (TDR) probes and Hydrus-1D for modelling one-dimensional flow were used in two stages: with hydraulic parameters estimated with the Beerkan Estimation of Soil Transfer Parameters (BEST) method and optimized by inverse modelling. The results showed that the soil water content in the plots is strongly influenced by rainfall, with the greatest variability in the dry–wet–dry transition periods. The modelling results were considered satisfactory with the data estimated by the BEST method (Root Mean Square Errors, RMSE = 0.023 and 0.022 and coefficients of determination, R2 = 0.72 and 0.81) and after the optimization (RMSE = 0.012 and 0.020 and R2 = 0.83 and 0.72). The performance analysis of the simulations provided strong indications of the efficiency of parameters estimated by BEST to predict the soil moisture variability in the studied river basin without the need for calibration or complex numerical approaches.


2009 ◽  
Vol 6 (5) ◽  
pp. 6425-6454
Author(s):  
H. Stephen ◽  
S. Ahmad ◽  
T. C. Piechota ◽  
C. Tang

Abstract. The Tropical Rainfall Measuring Mission (TRMM) carries aboard the Precipitation Radar (TRMMPR) that measures the backscatter (σ°) of the surface. σ° is sensitive to surface soil moisture and vegetation conditions. Due to sparse vegetation in arid and semi-arid regions, TRMMPR σ° primarily depends on the soil water content. In this study we relate TRMMPR σ° measurements to soil water content (ms) in Lower Colorado River Basin (LCRB). σ° dependence on ms is studied for different vegetation greenness values determined through Normalized Difference Vegetation Index (NDVI). A new model of σ° that couples incidence angle, ms, and NDVI is used to derive parameters and retrieve soil water content. The calibration and validation of this model are performed using simulated and measured ms data. Simulated ms is estimated using Variable Infiltration Capacity (VIC) model whereas measured ms is acquired from ground measuring stations in Walnut Gulch Experimental Watershed (WGEW). σ° model is calibrated using VIC and WGEW ms data during 1998 and the calibrated model is used to derive ms during later years. The temporal trends of derived ms are consistent with VIC and WGEW ms data with correlation coefficient (R) of 0.89 and 0.74, respectively. Derived ms is also consistent with the measured precipitation data with R=0.76. The gridded VIC data is used to calibrate the model at each grid point in LCRB and spatial maps of the model parameters are prepared. The model parameters are spatially coherent with the general regional topography in LCRB. TRMMPR σ° derived soil moisture maps during May (dry) and August (wet) 1999 are spatially similar to VIC estimates with correlation 0.67 and 0.76, respectively. This research provides new insights into Ku-band σ° dependence on soil water content in the arid regions.


Biologia ◽  
2007 ◽  
Vol 62 (5) ◽  
Author(s):  
Horst Gerke ◽  
Rolf Kuchenbuch

AbstractPlants can affect soil moisture and the soil hydraulic properties both directly by root water uptake and indirectly by modifying the soil structure. Furthermore, water in plant roots is mostly neglected when studying soil hydraulic properties. In this contribution, we analyze effects of the moisture content inside roots as compared to bulk soil moisture contents and speculate on implications of non-capillary-bound root water for determination of soil moisture and calibration of soil hydraulic properties.In a field crop of maize (Zea mays) of 75 cm row spacing, we sampled the total soil volumes of 0.7 m × 0.4 m and 0.3 m deep plots at the time of tasseling. For each of the 84 soil cubes of 10 cm edge length, root mass and length as well as moisture content and soil bulk density were determined. Roots were separated in 3 size classes for which a mean root porosity of 0.82 was obtained from the relation between root dry mass density and root bulk density using pycnometers. The spatially distributed fractions of root water contents were compared with those of the water in capillary pores of the soil matrix.Water inside roots was mostly below 2–5% of total soil water content; however, locally near the plant rows it was up to 20%. The results suggest that soil moisture in roots should be separately considered. Upon drying, the relation between the soil and root water may change towards water remaining in roots. Relations depend especially on soil water retention properties, growth stages, and root distributions. Gravimetric soil water content measurement could be misleading and TDR probes providing an integrated signal are difficult to interpret. Root effects should be more intensively studied for improved field soil water balance calculations.


2002 ◽  
Vol 82 (4) ◽  
pp. 855-859 ◽  
Author(s):  
M. L. Leblanc ◽  
D. C. Cloutier ◽  
C. Hamel

A 2-year field study was conducted in corn to determine the influence of rainfall, irrigation and soil water content on common lambsquarters and barnyardgrass emergence. Rainfall or irrigation had no influence on the final weed density and little on the pattern of weed emergence because the soil water content was at or greater than field capacity during the main weed emergence period. Irrigation may hasten the first weed emergence by warming the soil when temperature is limiting for germination. In southwestern Quebec, temperature appears to be the most important factor regulating germination in the spring since soil moisture is normally at field capacity for a long period, in part because of the melting of snow. Key words: Irrigation, weed emergence, soil moisture


2009 ◽  
Vol 16 (1) ◽  
pp. 141-150 ◽  
Author(s):  
M. Gebremichael ◽  
R. Rigon ◽  
G. Bertoldi ◽  
T. M. Over

Abstract. By providing continuous high-resolution simulations of soil moisture fields, distributed hydrologic models could be powerful tools to advance the scientific community's understanding of the space-time variability and scaling characteristics of soil moisture fields. However, in order to use the soil moisture simulations from hydrologic models with confidence, it is important to understand whether the models are able to represent in a reliable way the processes regulating soil moisture variability. In this study, a comparison of the scaling characteristics of spatial soil moisture fields derived from a set of microwave radiometer observations from the Southern Great Plains 1997 experiment and corresponding simulations using the distributed hydrologic model GEOtop is performed through the use of generalized variograms. Microwave observations and model simulations are in agreement with respect to suggesting the existence of a scale-invariance property in the variograms of spatial soil moisture fields, and indicating that the scaling characteristics vary with changes in the spatial average soil water content. However, observations and simulations give contradictory results regarding the relationship between the scaling parameters (i.e. spatial organization) and average soil water content. The drying process increased the spatial correlation of the microwave observations at both short and long separation distances while increasing the rate of decay of correlation with distance. The effect of drying on the spatial correlation of the model simulations was more complex, depending on the storm and the simulation examined, but for the largest storm in the simulation most similar to the observations, drying increased the long-range correlation but decreased the short-range. This is an indication that model simulations, while reproducing correctly the total streamflow at the outlet of the watershed, may not accurately reproduce the runoff production mechanisms. Consideration of the scaling characteristics of spatial soil moisture fields can therefore serve as a more intensive means for validating distributed hydrologic models, compared to the traditional approach of only comparing the streamflow hydrographs.


2003 ◽  
Vol 37 (4) ◽  
pp. 243-248 ◽  
Author(s):  
Teruhito MIYAMOTO ◽  
Mahithon PUTISO ◽  
Takahiro SHIONO ◽  
Hiroyuki TARUYA ◽  
Jiro CHIKUSHI

2014 ◽  
Vol 6 (4) ◽  
pp. 125 ◽  
Author(s):  
Anne Karuma ◽  
Peter Mtakwa ◽  
Nyambilila Amuri ◽  
Charles K. Gachene ◽  
Patrick Gicheru

Soil water conservation through tillage is one of the appropriate ways of addressing soil moisture deficit in rainfed agriculture. This study evaluated the effects of tillage practices on soil moisture conservation and crop yields in Mwala District, Eastern Kenya during the long rains (LR) and short rains (SR) of 2012/13. Six tillage systems: Disc plough (MB), Disc plough and harrowing (MBH), Ox-ploughing (OX), Subsoiling – ripping (SR), Hand hoe and Tied Ridges (HTR) and Hand hoe only (H) and, three cropping systems namely, sole maize, sole bean and maize - bean intercrop, were investigated in a split-plot design with four replicates. Data on soil water content was monitored at different weeks after planting and the crop yields at end of each growing season. A three-season average shows that soil water content and crop yields were higher in conventional tillage methods compared to the conservation tillage methods. Long term tillage experiments are thus required at different locations, under various environmental and soil conditions to validate the study findings.


2020 ◽  
Vol 63 (1) ◽  
pp. 141-152
Author(s):  
Jasreman Singh ◽  
Derek M. Heeren ◽  
Daran R. Rudnick ◽  
Wayne E. Woldt ◽  
Geng Bai ◽  
...  

HighlightsCapacitance-based electromagnetic soil moisture sensors were tested in disturbed and undisturbed soils.The uncertainty in estimation of soil water depth was lower using the undisturbed soil sample calibrations.The uncertainty in estimation of soil water depletion was lower than the uncertainty in volumetric water content.Undisturbed calibration of water depletion quantifies water demand with better precision and avoids over-watering.Abstract. The physical properties of soil, such as structure and texture, can affect the performance of an electromagnetic sensor in measuring soil water content. Historically, calibrations have been performed on repacked samples in the laboratory and on soils in the field, but little research has been done on laboratory calibrations with intact (undisturbed) soil cores. In this study, three replications each of disturbed and undisturbed soil samples were collected from two soil texture classes (Yutan silty clay loam and Fillmore silt loam) at a field site in eastern Nebraska to investigate the effects of soil structure and texture on the precision of a METER Group GS-1 capacitance-based sensor calibration. In addition, GS-1 sensors were installed in the field near the soil collection sites at three depths (0.15, 0.46, and 0.76 m). The soil moisture sensor had higher precision in the undisturbed laboratory setup, as the undisturbed calibration had a better correlation [slope closer to one, R2undisturbed (0.89) > R2disturbed (0.73)] than the disturbed calibrations for the Yutan and Fillmore texture classes, and the root mean square difference using the laboratory calibration (RMSDL) was higher for pooled disturbed samples (0.053 m3 m-3) in comparison to pooled undisturbed samples (0.023 m3 m-3). The uncertainty in determination of volumetric water content (?v) was higher using the factory calibration (RMSDF) in comparison to the laboratory calibration (RMSDL) for the different soil structures and texture classes. In general, the uncertainty in estimation of soil water depth was greater than the uncertainty in estimation of soil water depletion by the sensors installed in the field, and the uncertainties in estimation of depth and depletion were lower using the calibration developed from the undisturbed soil samples. The undisturbed calibration of soil water depletion would determine water demand with better precision and potentially avoid over-watering, offering relief from water shortages. Further investigation of sensor calibration techniques is required to enhance the applicability of soil moisture sensors for efficient irrigation management. Keywords: Calibration, Capacitance, Depletion, Irrigation, Precision, Sensor, Soil water content, Structure, Uncertainty.


Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3414
Author(s):  
Giuseppe Provenzano ◽  
Giovanni Rallo ◽  
Ceres Duarte Guedes Cabral de Almeida ◽  
Brivaldo Gomes de Almeida

This study aimed to develop a new model, valid for soil with and without expandable characters, to estimate volumetric soil water content (θ) from readings of scaled frequency (SF) acquired with the Diviner 2000® sensor. The analysis was carried out on six soils collected in western Sicily, sieved at 5 mm, and repacked to obtain the maximum and minimum bulk density (ρb). During an air-drying process SF values, the corresponding gravimetric soil water content (U) and ρb were monitored. In shrinking/swelling clay soils, due to the contraction process, the variation of dielectric permittivity was affected by the combination of the mutual proportions between the water volumes and the air present in the soil. Thus, to account for the changes of ρb with U, the proposed model assumed θ as the dependent variable being SF and ρb the independent variables; then the model’s parameters were estimated based on the sand and clay fractions. The model validation was finally carried out based on data acquired in undisturbed monoliths sampled in the same areas. The estimated θ, θestim, was generally close to the corresponding measured, θmeas, with Root Mean Square Errors (RMSE) generally lower than 0.049 cm3 cm−3, quite low Mean Bias Errors (MBE), ranging between −0.028 and 0.045 cm3 cm−3, and always positive Nash-Sutcliffe Efficiency index (NSE), confirming the good performance of the model.


Geosciences ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 238
Author(s):  
Kenta Iwasaki ◽  
Makoto Tamura ◽  
Hirokazu Sato ◽  
Kazuhiko Masaka ◽  
Daisuke Oka ◽  
...  

The development of a method to easily investigate the spatial distribution of soil moisture and soil hardness in tree windbreaks is necessary because these windbreaks often decline due to inappropriate soil moisture condition and soil compaction. This research examined the applicability of ground-penetrating radar (GPR) and a combined penetrometer–moisture probe (CPMP) for evaluating the spatial distribution of soil moisture and soil hardness in four windbreaks with different soil characteristics. A GPR-reflecting interface was observed at a less permeable layer in a coastal windbreak and at a depth affected by soil compaction in an inland windbreak with andosol. The spatial distribution of the groundwater table could also be evaluated by examining the attenuation of GPR reflection in a coastal windbreak. In contrast, GPR was not applicable in an inland windbreak with peat because of high soil water content near the soil surface. The CPMP could detect vertical distributions of soil hardness and soil water content regardless of soil type. The CPMP was useful for interpreting GPR profiles, and GPR was useful for interpolating the information about the horizontal distribution of soil moisture and soil hardness between survey points made with the CPMP. Thus, the combination of GPR and a CPMP is ideal for examining the two-dimensional spatial distribution of soil moisture and soil hardness at windbreaks with soils for which both methods are applicable.


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