Spatial variability of soil water content and soil chemistry affect grapevine growth in degraded slopes

2021 ◽  
Author(s):  
Agota Horel ◽  
Imre Zagyva ◽  
Márton Dencső ◽  
Eszter Tóth ◽  
Györgyi Gelybó ◽  
...  
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Water System ◽  
Sensor Data ◽  
Slope Position ◽  
Area Index ◽  
Vegetation Growth

<p>Three slopes with grapevines were investigated to see changes in the soil-plant-water system over vegetation growth. The slopes have the following parameters: 1) young grapevine plants with tilled soil (YR), 2) older grapevines with grassland between rows next to the young grapevine (OR), and 3) older grapevines with grass between rows at a different location and slope position (OF). All experimental slopes had identical plant canopy management such as pruning or shoot and bunch thinning. All slopes are prone to erosion. For continuous hydrological monitoring soil water content and temperature sensors were placed at 15 cm and 40 cm below ground both at the top and bottom of the slopes. For indications of plant growth photosynthetically active radiation (PAR) sensors were placed below the canopy, and Normalized Difference Vegetation Index (NDVI) and Photochemical Reflectance Index (PRI) sensors were used to monitor leaf reflectance. All sites included a set of hemispherical sensor sets to measure incoming radiation. Leaf Area Index (LAI) was measured on a biweekly basis using a handheld ceptometer. We found that in the OR and OF sites the soil water content (VWC) was higher at the lower portion of the slope, while for the YR the VWC was the highest at the top. Soil temperature was higher at the top of the slopes over 6% for YR and 9% for OR sites compared to the bottom measuring points. The most notable difference in the NDVI values was observed for OR, where the plants at the top of the slope showed much lower NDVI values compared to the ones at the bottom of the slope. For the younger grapevines, this tendency was showing the opposite results, the plants at the top of the slope had much higher NDVI values than the lower ones, indicating higher leaf densities. The collected PAR values further support these findings, as the OR plants at the top of the slope had the highest PAR values signifying lower leaf areas and densities. The differences in the PRI values suggest that plants at the bottom of the slope have either better nutrient usage or less stress for drought conditions. The LAI values correlated well with the spectral reflectance sensor data. The OR and OF showed higher LAI at the bottom of the slope, while the younger grapevines showed the opposite. The highest LAI values were observed for the YR (max values were around 7) and the lowest for the OF plants (max LAI value was 3.2).</p>

scholarly journals The Applicability of the Cosmic Ray Neutron Sensor to Simultaneously Monitor Soil Water Content and Biomass in an Acacia mearnsii Forest

Hydrology ◽  
2020 ◽  
Vol 7 (3) ◽  
pp. 48 ◽  
Author(s):  
Thigesh Vather ◽  
Colin S. Everson ◽  
Trenton E. Franz
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Epithermal Neutron ◽  
Cosmic Ray ◽  
Field Scale ◽  
Area Index ◽  
Neutron Intensity

Soil water content is an important hydrological parameter, which is difficult to measure at a field scale due to its spatial and temporal heterogeneity. The Cosmic Ray Neutron Sensor (CRNS) is a novel and innovative approach to estimate area-averaged soil water content at an intermediate scale, which has been implemented across the globe. The CRNS is moderated by all hydrogen sources within its measurement footprint. In order to isolate the soil water content signal from the neutron intensity, the other sources of hydrogen need to be accounted for. The CRNS’s applications are not only limited to soil water content estimation, as it can potentially be used to monitor biomass. The Two-Streams clear-felling provided the unique opportunity to monitor the cosmic ray neutron intensities before, during, and after the clear-felling. The cadmium-difference method was used to obtain the pure thermal and epithermal neutron intensities from the bare and moderated detectors. The study concluded that the presence of biomass within the site reduced the epithermal neutron intensity by 12.43% and the N0 value by 13.8%. The use of the neutron ratio to monitor biomass was evaluated and changes in the neutron ratio coincided with biomass changes and resulted in a high correlation (R2 of 0.868) with the normalized difference vegetation index (NDVI) and (R2 of 0.817) leaf area index (LAI). The use of the CRNS to simultaneously monitor soil water content and biomass will be beneficial in providing more reliable soil water content estimates, provide biomass estimates at a field scale, and aid in understanding the dynamics between soil water content and vegetation.

scholarly journals Relating surface backscatter response from TRMM Precipitation Radar to soil moisture: results over a semi-arid region

2009 ◽  
Vol 6 (5) ◽  
pp. 6425-6454
Author(s):  
H. Stephen ◽  
S. Ahmad ◽  
T. C. Piechota ◽  
C. Tang
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Arid Regions ◽  
Vegetation Index ◽  
Temporal Trends ◽  
Model Parameters ◽  
Precipitation Radar ◽  
Semi Arid

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.

scholarly journals Separation of soil and canopy reflectance signatures of Mid German agricultural soils

2011 ◽  
Vol 51 (No, 7) ◽  
pp. 296-303 ◽  
Author(s):  
T. Behrens ◽  
K. Gregor ◽  
W. Diepenbrock
Keyword(s):  
Remote Sensing ◽  
Soil Properties ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Vegetation Index ◽  
Near Infrared ◽  
Field Experiments ◽  
Agricultural Soils ◽  
Soil Reflectance

Remote sensing can provide visual indications of crop growth during production season. In past, spectral optical estimations were well performed in the ability to be correlated with crop and soil properties but were not consistent within the whole production season. To better quantify vegetation properties gathered via remote sensing, models of soil reflectance under changing moisture conditions are needed. Signatures of reflected radiation were acquired for several Mid German agricultural soils in laboratory and field experiments. Results were evaluated at near-infrared spectral region at the wavelength of 850 nm. The selected soils represented different soil colors and brightness values reflecting a broad range of soil properties. At the wavelength of 850 nm soil reflectance ranged between 10% (black peat) and 74% (white quartz sand). The reflectance of topsoils varied from 21% to 32%. An interrelation was found between soil brightness rating values and spectral optical reflectance values in form of a linear regression. Increases of soil water content from 0% to 25% decreased signatures of soil reflectance at 850 nm of two different soil types about 40%. The interrelation of soil reflectance and soil moisture revealed a non-linear exponential function. Using knowledge of the individual signature of soil reflectance as well as the soil water content at the measurement, soil reflectance could be predicted. As a result, a clear separation is established between soil reflectance and reflectance of the vegetation cover if the vegetation index is known.

Coupling model of ecohydrology and simulation of typical shrub ecosystems on the Loess Plateau

2020 ◽  
Author(s):  
Yu Zhang ◽  
Xiaoyan Li ◽  
Wei Li ◽  
Weiwei Fang ◽  
Fangzhong Shi
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Loess Plateau ◽  
Field Experiments ◽  
Annual Precipitation ◽  
The Loess Plateau ◽  
Rainfall Interception ◽  
Area Index ◽  
Caragana Korshinskii

<p>Shrub is the main vegetation type for vegetation restoration in the Loess Plateau, which plays an important role in the regional ecosystem restoration. Study on the relationships between vegetation and soil water of typical shrub ecosystems are significant for the restoration and reconstruction of ecosystems in the Loess Plateau. Three typical shrub (<em>Hippophae rhamnoides</em> Linn., <em>Spiraea pubescens</em> Turcz., and <em>Caragana korshinskii</em> Kom.) ecosystems were chosen in the Loess Plateau. Field experiments were conducted to investigate the factors that influencing the processes of rainfall interception and root uptake of typical shrubs. S-Biome-BGC model was established based on the Biome-BGC model by developing the rainfall interception and soil water movement sub-models. The model was calibrated and verified using field data. The calibrated S-Biome-BGC model was used to simulate the characteristics of leaf area index (<em>LAI</em>), net primary productivity (<em>NPP</em>), soil water content and the interactions among them for the shrub ecosystems along the precipitation gradients in the Loess Plateau, respectively. The results showed that the predictions of the S-Biome-BGC model for soil water content and<em> LAI</em> of typical shrub ecosystems in Loess Plateau were significantly more accurate than that of Biome-BGC model. The simulated <em>RMSE</em> of soil water content decreased from 0.040~0.130 cm<sup>3</sup> cm<sup>-3</sup> to 0.026~0.035 cm<sup>3</sup> cm<sup>-3</sup>, and the simulated <em>RMSE</em> of<em> LAI</em> decreased from 0.37~0.70 m<sup>2</sup> m<sup>-2</sup> to 0.35~0.37 m<sup>2</sup> m<sup>-2</sup>. Therefore, the S-Biome-BGC model can reflect the interaction between plant growth and soil water content in the shrub ecosystems of the Loess Plateau. The S-Biome-BGC model simulation for <em>LAI</em>,<em> NPP</em> and soil water content of the three typical shrubs were significantly different along the precipitation gradients, and increased with annual precipitation together. However, different <em>LAI</em>, <em>NPP</em> and soil water correlations were found under different precipitation gradients.<em> LAI</em> and<em> NPP</em> have significant positive correlations with soil water content in the areas where the annual precipitation is above 460~500 mm that could afford the shrubs growth. The results of the study provide a re-vegetation threshold to guide future re-vegetation activities in the Loess Plateau.</p>

Modeling of a forested study site with the Community Land Model version 5 using climate projections for the 21st century.

2020 ◽  
Author(s):  
Lukas Strebel ◽  
Klaus Goergen ◽  
Bibi S. Naz ◽  
Heye Bogena ◽  
Harry Vereecken ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Land Surface ◽  
Model Parameters ◽  
Climate Projections ◽  
Modeling Framework ◽  
Area Index ◽  
Community Land Model

<p>Modeling forest ecosystems is important to facilitate adaptations in forest management approaches necessary to address the challenges of climate change, particularly of interest are ecohydrological states and fluxes such as soil water content, biomass, leaf area index, and evapotranspiration.</p><p>The community land model in its current version 5 (CLM5) simulates a broad collection of important land-surface processes; from moisture and energy partitioning, through biogeophysical processes, to surface and subsurface runoff. Additionally, CLM5 contains a biogeochemistry model (CLM5-BGC) which includes prognostic computation of vegetation states and carbon and nitrogen pools. However, CLM5 predictions are affected by uncertainty related to uncertain model forcings and parameters. Here, we use data assimilation methods to improve model performance by assimilating soil water content observations into CLM5 using the parallel data assimilation framework (PDAF).</p><p> </p><p>The coupled modeling framework was applied to the small (38.5 ha) forested catchment Wüstebach located in the Eifel National Park near the German-Belgian border. As part of the terrestrial environmental observatories (TERENO) network, the SoilNet sensors at the study site provide soil water content and soil temperature measurements since 2009.</p><p>CLM5 simulations for the period 2009-2100 were made, using local atmospheric observations for the period of 2009-2018 and an ensemble of regional climate model projections for 2019-2100. Simulations illustrate that data assimilation of soil water content improves the characterization of past model states, and that estimated model parameters and default model parameters result in different trajectories of ecohydrological states for 2019-2100. The simulations also illustrate that this site is hardly affected by increased water stress in the future.</p><p>The developed framework will be extended and applied for both ecosystem reanalysis as well as further simulations using climate projections across forested sites over Europe.</p>

scholarly journals Modelling soil water content and grapevine growth and development with the stics crop-soil model under two different water management strategies

OENO One ◽  
2009 ◽  
Vol 43 (1) ◽  
pp. 13 ◽  
Author(s):  
Héctor Valdés-Gómez ◽  
Florian Celette ◽  
Iñaki García de Cortázar-Atauri ◽  
Francisco Jara-Rojas ◽  
Samuel Ortega-Farías ◽  
...  
Keyword(s):  
Water Management ◽  
Water Stress ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Biomass Production ◽  
Growth And Development ◽  
Management Strategies ◽  
Production Yield ◽  
Area Index

<p style="text-align: justify;"><strong>Background and aims</strong>: Many models have been developed to evaluate crop growth and development, but few are capable of simulating grapevine systems. The present study was carried out to evaluate the ability of the STICS model to represent grapevine phenology, biomass production, yield and soil water content in two situations differing with respect to rainfall distribution and water management strategies.</p><p style="text-align: justify;"><strong>Methods and results</strong>: Simulations were performed for an irrigated vineyard in Chile and an irrigated and a non-irrigated vineyard in France. The crop model gave a good estimation of the main stages of grapevine phenology (less than six days difference between simulated and observed values). Soil water content was the best simulated variable (R2 = 0.99), whereas grapevine evapotranspiration observed only in Chile (R2 = 0.43) and leaf area index observed only in France (R2= 0.80) were the worst simulated variables. Biomass production, yield and their components were correctly simulated (within the 95 % Student confidence interval around the mean observed value). A comparison of the fraction of transpirable soil water and vine water potential measurements with the water stress indices calculated by the STICS model showed that the time and duration of the grapevine water stress period was correctly estimated.</p><p style="text-align: justify;"><strong>Conclusions</strong>: Therefore, the STICS model was reasonably successful in simulating vine growth and development, and identifying critical periods concerning the vine water status.</p><p style="text-align: justify;"><strong>Significance of the study</strong>: The STICS model can be used to evaluate various water management strategies and their impacts on grape production.</p>

scholarly journals Variations in Soil Physico-Chemical Properties along Slope Position Gradient in Secondary Vegetation of the Hilly Region, Guilin, Southwest China

2020 ◽  
Vol 12 (4) ◽  
pp. 1303 ◽  
Author(s):  
Runhong Liu ◽  
Yuanfang Pan ◽  
Han Bao ◽  
Shichu Liang ◽  
Yong Jiang ◽  
...  
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Southwest China ◽  
Chemical Properties ◽  
Slope Position ◽  
Secondary Vegetation ◽  
Physico Chemical ◽  
Hilly Region ◽  
Total Potassium

Understanding the variation of soil physico-chemical properties along slope position gradients is essential for vegetation restoration and reconstruction, but how slope positions impact the soil physico-chemical properties in the secondary vegetation of hilly regions is poorly understood. To address these uncertainties, we examined the changes in soil physico-chemical properties and their relationships along the slope position gradient in secondary vegetation of the hilly region in Guilin, southwest China. The results showed that except for the soil water content, soil total phosphorus and soil total potassium which reached the highest value at the footslope, other soil physico-chemical properties reached the highest content in the middle slope, and most of the soil physico-chemical properties showed the lowest content in the upper slope or footslope. Moreover, Pearson’s correlation analysis revealed that there were no significant correlations between most of the soil physico-chemical properties and that the correlations between soil physico-chemical properties were not consistent across different slope positions. Additionally, the principal component analysis showed that the first 4 principal components together explained 84.32% of the total variation and might be interpreted as the change of soil total nitrogen, soil organic matter, soil available nitrogen, soil available potassium, soil water content and soil total potassium. Overall, our results strongly demonstrated that slope positions showed significant effects on most of the soil physico-chemical properties and would provide an important reference for the formulation of restoration strategies in different slope positions to facilitate vegetation restoration and reconstruction and the sustainable development of the ecological environment in the hilly region.

scholarly journals Retrieving Surface Soil Water Content Using a Soil Texture Adjusted Vegetation Index and Unmanned Aerial System Images

2021 ◽  
Vol 13 (1) ◽  
pp. 145
Author(s):  
Haibin Gu ◽  
Zhe Lin ◽  
Wenxuan Guo ◽  
Sanjit Deb
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Soil Texture ◽  
Vegetation Index ◽  
Surface Soil ◽  
Field Scale ◽  
Thermal Images ◽  
Model Based ◽  
Dryness Index

Surface soil water content (SWC) is a major determinant of crop production, and accurately retrieving SWC plays a crucial role in effective water management. Unmanned aerial systems (UAS) can acquire images with high temporal and spatial resolutions for SWC monitoring at the field scale. The objective of this study was to develop an algorithm to retrieve SWC by integrating soil texture into a vegetation index derived from UAS multispectral and thermal images. The normalized difference vegetation index (NDVI) and surface temperature (Ts) derived from the UAS multispectral and thermal images were employed to construct the temperature vegetation dryness index (TVDI) using the trapezoid model. Soil texture was incorporated into the trapezoid model based on the relationship between soil texture and the lower and upper limits of SWC to form the texture temperature vegetation dryness index (TTVDI). For validation, 128 surface soil samples, 84 in 2019 and 44 in 2020, were collected to determine soil texture and gravimetric SWC. Based on the linear regression models, the TTVDI had better performance in estimating SWC compared to the TVDI, with an increase in R2 (coefficient of determination) by 14.5% and 14.9%, and a decrease in RMSE (root mean square error) by 46.1% and 10.8%, for the 2019 and 2020 samples, respectively. The application of the TTVDI model based on high-resolution multispectral and thermal UAS images has the potential to accurately and timely retrieve SWC at the field scale.

scholarly journals Changes in the Soil–Plant–Water System Due to Biochar Amendment

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1216
Author(s):  
Ágota Horel ◽  
Eszter Tóth
Keyword(s):  
Plant Growth ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Co2 Emissions ◽  
Water System ◽  
Plant Water ◽  
Soil Co2 ◽  
Soil Co2 Emissions ◽  
Biochar Amendment

The aim of this study was to do a complex examination of the soil–plant–water system and soil greenhouse gas emissions when biochar is applied to soil planted with sweet corn (Zea mays L. var. saccharata). The study covers two consecutive vegetation periods. We investigated (i) the changes in plant growth, (ii) soil water and temperature at different depths, (iii) greenhouse gas (GHG) emissions (CO2 and N2O) after biochar application, and (iv) the soil water, chemistry, and plant interactions. We used discrete measurements for plant growth, biomass production, and soil chemistry, while continuously monitoring the soil water content and temperature, and the state of plant health (i.e., using spectral reflectance sensors). Plant response in the control plot showed higher values of normalized difference vegetation index (NDVI; 0.3%) and lower values for photochemical reflectance index (PRI) and fraction of absorbed photosynthetically active radiation (fAPAR) by 26.8% and 2.24%, respectively, than for biochar treatments. We found significant negative correlations between fAPAR and soil water contents (SWC), and NDVI and SWC values (−0.59 < r < −0.30; p < 0.05). Soil temperature at the depth of 15 cm influenced soil CO2 emissions to a larger extent (r > 0.5; p < 0.01) than air temperature (0.21 < r < 0.33) or soil water content (r < 0.06; p > 0.05). Our data showed strong connections between GHG production and soil chemical parameters of soil pH, nitrogen, potassium, or phosphate concentrations. Biochar application increased soil CO2 emissions but reduced N2O emissions. Our results demonstrated that biochar amendment to soils can help plant growth initially, but might not result in enhanced crop yield. The plant parameters were substantially different between the investigated years for both control and biochar amended parcels; therefore, long-term studies are essential to document the lasting effects of these treatments.

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