Effect of Soil Depth on the Quantification of Soil Moisture Content Value Estimated from NOAA Satellite Images

2014 ◽  
Vol 567 ◽  
pp. 705-710
Author(s):  
Abdalhaleem A. Hassaballa ◽  
Abdul Nasir Matori ◽  
Helmi Z.M. Shafri
Keyword(s):  
Soil Moisture ◽  
Critical Parameter ◽  
Satellite Images ◽  
Soil Moisture Content ◽  
Soil Depth ◽  
Vegetation Indices ◽  
Field Measurements ◽  
Spatial Estimation ◽  
Optical Images

Soil moisture (MC) is considered as the most significant boundary conditions controlling most of the hydrological cycle’s processes especially over humid areas. However, MC is very critical parameter to measure because of its variability in both space and time. The fluctuation of MC along the soil depth in turn, makes it so difficult to assess from optical satellite techniques. The study aims to produce a rectified satellite’s surface temperature (Ts) in order to enhance the spatial estimation of MC. The study also aims to produce MC estimates from three variable depths of the soil using optical images from NOAA 17 in order to examine the potential of satellite techniques in assessing the MC along the soil depths. The universal triangle (UT) algorithm was used for MC assessment based on Ts, vegetation Indices (VI) and field measurements of MC; which were conducted at variable depths. The study area was divided into three classes according to the nature of surface cover. The resultant MC extracted from the UT method with rectified Ts, produced accuracies of MC ranging from 0.65 to 0.89 when validated with in-situ measured MC at depths 5cm and 10 cm respectively.

scholarly journals Anatomy of the 2018 agricultural drought in The Netherlands using in situ soil moisture and satellite vegetation indices

2020 ◽  
Author(s):  
Joost Buitink ◽  
Anne M. Swank ◽  
Martine van der Ploeg ◽  
Naomi E. Smith ◽  
Harm-Jan F. Benninga ◽  
...  
Keyword(s):  
Soil Moisture ◽  
The Netherlands ◽  
Moisture Content ◽  
Land Surface ◽  
Soil Moisture Content ◽  
Vegetation Indices ◽  
Agricultural Drought ◽  
Summer Drought ◽  
The Impact

Abstract. The soil moisture status near the land surface is a key determinant of vegetation productivity. The critical soil moisture content determines the transition from an energy-limited to a water-limited evapotranspiration regime. This study quantifies the critical soil moisture content by comparison of in situ soil moisture profile measurements of the Raam and Twenthe networks in the Netherlands, with two satellite derived vegetation indices (NIRv and VOD) during the 2018 summer drought. The critical soil moisture content is obtained through a piece-wise linear correlation of the NIRv and VOD anomalies with soil moisture on different depths of the profile. This nonlinear relation reflects the observation that negative soil moisture anomalies develop weeks before the first reduction in vegetation indices. Furthermore, the inferred critical soil moisture content was found to increase with observation depth and this relationship is shown to be linear and distinctive per area, reflecting the tendency of roots to take up water from deeper layers when drought progresses. The relations of non-stressed towards water-stressed vegetation conditions on distinct depths are derived using Remote Sensing, enabling the parameterization of reduced evapotranspiration and its effect on GPP in models to study the impact of a drought on the carbon cycle.

scholarly journals Anatomy of the 2018 agricultural drought in the Netherlands using in situ soil moisture and satellite vegetation indices

2020 ◽  
Vol 24 (12) ◽  
pp. 6021-6031
Author(s):  
Joost Buitink ◽  
Anne M. Swank ◽  
Martine van der Ploeg ◽  
Naomi E. Smith ◽  
Harm-Jan F. Benninga ◽  
...  
Keyword(s):  
Soil Moisture ◽  
The Netherlands ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Vegetation Indices ◽  
Agricultural Drought ◽  
Summer Drought ◽  
Near Infrared Reflectance ◽  
The Impact

Abstract. The soil moisture status near the land surface is a key determinant of vegetation productivity. The critical soil moisture content determines the transition from an energy-limited to a water-limited evapotranspiration regime. This study quantifies the critical soil moisture content by comparison of in situ soil moisture profile measurements of the Raam and Twente networks in the Netherlands, with two satellite-derived vegetation indices (near-infrared reflectance of terrestrial vegetation, NIRv, and vegetation optical depth, VOD) during the 2018 summer drought. The critical soil moisture content is obtained through a piece-wise linear correlation of the NIRv and VOD anomalies with soil moisture on different depths of the profile. This non-linear relation reflects the observation that negative soil moisture anomalies develop weeks before the first reduction in vegetation indices: 2–3 weeks in this case. Furthermore, the inferred critical soil moisture content was found to increase with observation depth, and this relationship is shown to be linear and distinctive per area, reflecting the tendency of roots to take up water from deeper layers when drought progresses. The relations of non-stressed towards water-stressed vegetation conditions on distinct depths are derived using remote sensing, enabling the parameterization of reduced evapotranspiration and its effect on gross primary productivity in models to study the impact of a drought on the carbon cycle.

scholarly journals Effect of deficit irrigation and in situ moisture conservation on soil moisture content and frequency of irrigation in kiwifruit cultivar Allison

2016 ◽  
Vol 8 (4) ◽  
pp. 2093-2098
Author(s):  
Preet Pratima ◽  
N. Sharma ◽  
Rajesh Kaushal
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Deficit Irrigation ◽  
Soil Moisture Content ◽  
Soil Depth ◽  
Block Design ◽  
Field Capacity ◽  
Plastic Mulch ◽  
Randomized Block Design

The effect of deficit irrigation and in situ moisture conservation in kiwifruit cv. Allison vines was studied during the years 2011 and 2012 in the Department of Fruit Science, Dr. Y. S. Parmar University of Horticulture and Forestry, Solan, HP, India. Soil moisture content and frequency of irrigation were investigated in kiwifruit in response to deficit irrigation and in situ moisture conservation techniques. Seven treatments viz., irrigation at 80 per cent Field Capacity (T1), 60 per cent Field Capacity (T2) and 40 per cent Field Capacity (T3), 60 per cent Field Capacity (FC) plus grass mulch (T4) or black polythene (T5) and 40 per cent FC plus grass mulch (T6) or black polythene (T7) were applied from March to October with three replications in Randomized Block Design (RBD). During the year 2011, the soil moisture content under kiwifruit vines was highest under the treatment T1 (15.3, 16.9) , followed by T5 (15.2, 16.8) and T4 (14.9, 16.6) at 30 cm and at 60 cm soil depth, respectively. Whereas, during the year 2012, the soil moisture content under kiwifruit vines was highest under the treatment T1 (14.9, 16.4), followed by T5 (15.0, 16.3) and T4 (14.6, 16.1) at 30 cm and at 60 cm soil depth, respectively. However,the least soil moisture content was, however, observed under T3 (11.0, 12.8) at 30 cm and 60 cm soil depth , respectively, during the year 2011, similarly, during the year 2012, the least soil moisture content was also observed under T3 (10.6, 12.7) at 30 cm and 60 cm soil depth, respectively. The frequency of irrigation was highest under T1 (16 irrigations) followed T2 (10 irrigations) while the least was recorded under T6 and T7 (7irrigations). Total numbers of irrigations applied were reduced from 16 (under T1) to 8 (under T5). The use of black plastic mulch may be beneficial as it helped to conserve moistureunder DI regime which is comparable to those in well irrigated vines. It may also reduce the high irrigation requirement of kiwifruit in areas where sufficient water is not available.

Distribution of soil moisture content and its effect on the potential growth of the over-story species in North-East Chalkidiki

2001 ◽  
Vol 66 ◽  
Author(s):  
M. Aslanidou ◽  
P. Smiris
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Soil Depth ◽  
Moisture Distribution ◽  
Taxus Baccata ◽  
Mixed Stands ◽  
Potential Growth ◽  
North East ◽  
Soil Moisture Distribution

This  study deals with the soil moisture distribution and its effect on the  potential growth and    adaptation of the over-story species in north-east Chalkidiki. These  species are: Quercus    dalechampii Ten, Quercus  conferta Kit, Quercus  pubescens Willd, Castanea  sativa Mill, Fagus    moesiaca Maly-Domin and also Taxus baccata L. in mixed stands  with Fagus moesiaca.    Samples of soil, 1-2 kg per 20cm depth, were taken and the moisture content  of each sample    was measured in order to determine soil moisture distribution and its  contribution to the growth    of the forest species. The most important results are: i) available water  is influenced by the soil    depth. During the summer, at a soil depth of 10 cm a significant  restriction was observed. ii) the    large duration of the dry period in the deep soil layers has less adverse  effect on stands growth than in the case of the soil surface layers, due to the fact that the root system mainly spreads out    at a soil depth of 40 cm iii) in the beginning of the growing season, the  soil moisture content is    greater than 30 % at a soil depth of 60 cm, in beech and mixed beech-yew  stands, is 10-15 % in    the Q. pubescens  stands and it's more than 30 % at a soil depth of 60 cm in Q. dalechampii    stands.

scholarly journals Modified Richards’ Equation to Improve Estimates of Soil Moisture in Two-Layered Soils after Infiltration

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1174 ◽  
Author(s):  
Honglin Zhu ◽  
Tingxi Liu ◽  
Baolin Xue ◽  
Yinglan A. ◽  
Guoqiang Wang
Keyword(s):  
Soil Moisture ◽  
Overland Flow ◽  
Hydrological Cycle ◽  
Soil Depth ◽  
Controlling Factors ◽  
Moisture Distribution ◽  
Richards Equation ◽  
Infiltration Process ◽  
Soil Moisture Distribution

Soil moisture distribution plays a significant role in soil erosion, evapotranspiration, and overland flow. Infiltration is a main component of the hydrological cycle, and simulations of soil moisture can improve infiltration process modeling. Different environmental factors affect soil moisture distribution in different soil layers. Soil moisture distribution is influenced mainly by soil properties (e.g., porosity) in the upper layer (10 cm), but by gravity-related factors (e.g., slope) in the deeper layer (50 cm). Richards’ equation is a widely used infiltration equation in hydrological models, but its homogeneous assumptions simplify the pattern of soil moisture distribution, leading to overestimates. Here, we present a modified Richards’ equation to predict soil moisture distribution in different layers along vertical infiltration. Two formulae considering different controlling factors were used to estimate soil moisture distribution at a given time and depth. Data for factors including slope, soil depth, porosity, and hydraulic conductivity were obtained from the literature and in situ measurements and used as prior information. Simulations were compared between the modified and the original Richards’ equations and with measurements taken at different times and depths. Comparisons with soil moisture data measured in situ indicated that the modified Richards’ equation still had limitations in terms of reproducing soil moisture in different slope positions and rainfall periods. However, compared with the original Richards’ equation, the modified equation estimated soil moisture with spatial diversity in the infiltration process more accurately. The equation may benefit from further solutions that consider various controlling factors in layers. Our results show that the proposed modified Richards’ equation provides a more effective approach to predict soil moisture in the vertical infiltration process.

Improving Dryland Crop Simulation by Assimilating Soil Moisture and Vegetation Data

2020 ◽  
Author(s):  
Yang Lu ◽  
Justin Sheffield
Keyword(s):  
Soil Moisture ◽  
Crop Production ◽  
Management Practices ◽  
Water Productivity ◽  
Vegetation Indices ◽  
Screening Method ◽  
Model Performance ◽  
State Parameter ◽  
Aquacrop Model

<p>Global population is projected to keep increasing rapidly in the next 3 decades, particularly in dryland regions of the developing world, making it a global imperative to enhance crop production. However, improving current crop production in these regions is hampered by yield gaps due to poor soils, lack of irrigation and other management practices. Here we develop a crop modelling capability to help understand gaps, and apply to dryland regions where data for parametrizing and testing models is generally lacking. We present a data assimilation framework to improve simulation capability by assimilating in-situ soil moisture and vegetation data into the FAO AquaCrop model. AquaCrop is a water-driven model that simulates canopy growth, biomass and crop yield as a function of water productivity. The key strength of AquaCrop lies in the low requirement for input data thanks to its simple structure. A global sensitivity analysis is first performed using the Morris screening method and the variance-based Extended Fourier Amplitude Sensitivity Test (EFAST) method to identify the key influential parameters on the model outputs. We begin with state-only updates by assimilating different combinations of soil moisture and vegetation data (vegetation indices, biomass, etc.), and different filtering/smoothing assimilation strategies are tested. Based on the state-only assimilation results, we further evaluate the utility of joint state-parameter (augmented-states) assimilation in improving the model performance. The framework will eventually be extended to assimilate remote sensing estimates of soil moisture and vegetation data to overcome the lack of in-situ data more generally in dryland regions.</p>

Thermal properties of Antarctic soils: wetting controls subsurface thermal state

2016 ◽  
Vol 28 (5) ◽  
pp. 361-370 ◽  
Author(s):  
Joseph S. Levy ◽  
Logan M. Schmidt
Keyword(s):  
Soil Moisture ◽  
Thermal Diffusivity ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Thermal State ◽  
Thermal Characteristics ◽  
Field Measurements ◽  
Dry Valleys ◽  
Ground Ice ◽  
Mineral Soils

AbstractMineral soils in the McMurdo Dry Valleys (MDV), Antarctica, are commonly considered to be dry, and therefore to be good insulators with low thermal diffusivity values (~0.2 mm2s-1). However, field measurements of soil moisture profiles with depth, coupled with observations of rapid ground ice melt, suggest that the thermal characteristics of MDV soils, and thus their resistance to thaw, may be spatially variable and strongly controlled by soil moisture content. The thermal conductivity, heat capacity and thermal diffusivity of 17 MDV soils were measured over a range of soil moisture conditions from dry to saturated. We found that thermal diffusivity varied by a factor of eight for these soils, despite the fact that they consist of members of only two soil groups. The thermal diffusivity of the soils increased in all cases with increasing soil moisture content, suggesting that permafrost and ground ice thaw in mineral soils may generate a positive thawing feedback in which wet soils conduct additional heat to depth, enhancing rates of permafrost thaw and thermokarst formation.

scholarly journals Analyzing Effects of Crops on SMAP Satellite-based Soil Moisture using a Rainfall-Runoff Model in the U.S. Corn Belt

2021 ◽  
Author(s):  
Navid Jadidoleslam ◽  
Brian K Hornbuckle ◽  
Witold F. Krajewski ◽  
Ricardo Mantilla ◽  
Michael H. Cosh
Keyword(s):  
Soil Moisture ◽  
Vegetation Indices ◽  
Hydrologic Model ◽  
Corn Belt ◽  
Row Crops ◽  
In Situ Data ◽  
Row Crop ◽  
In Situ Sensors ◽  
Crop Agriculture

L-band microwave satellite missions provide soil moisture information potentially useful for streamflow and hence flood predictions. However, these observations are also sensitive to the presence of vegetation that makes satellite soil moisture estimations prone to errors. In this study, the authors evaluate satellite soil moisture estimations from SMAP (Soil Moisture Active Passive) and SMOS (Soil Moisture Ocean Salinity), and two distributed hydrologic models with measurements from in~situ sensors in the Corn Belt state of Iowa, a region dominated by annual row crops of corn and soybean. First, the authors compare model and satellite soil moisture products across Iowa using in~situ data for more than 30 stations. Then, they compare satellite soil moisture products with state-wide model-based fields to identify regions of low and high agreement. Finally, the authors analyze and explain the resulting spatial patterns with MODIS (Moderate Resolution Imaging Spectroradiometer) vegetation indices and SMAP vegetation optical depth. The results indicate that satellite soil moisture estimations are drier than those provided by the hydrologic model and the spatial bias depends on the intensity of row-crop agriculture. The work highlights the importance of developing a revised SMAP algorithm for regions of intensive row-crop agriculture to increase SMAP utility in the real-time streamflow predictions.

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