Studies in the ecology of the Riverine plain. I. The gilgai microrelief and associated flora

1955 ◽  
Vol 3 (1) ◽  
pp. 99 ◽  
Author(s):  
OB Williams
Keyword(s):  
Soil Moisture ◽  
Soil Moisture Content ◽  
Root Systems ◽  
Perennial Grasses ◽  
Physical Factors ◽  
Vegetation Changes ◽  
Winter Rainfall ◽  
Seed Retention ◽  
Annual Grasses ◽  
Normal Rainfall

The flora of the gilgai microrelief at Deniliquin, N.S.W., is described, and the major vegetation changes over a 4-year period are outlined. Until 1950 the shelf was dominated by chenopodiaceous plants, the depression by perennial grasses, and the puff by annual grasses and herbs. After heavy and persistent winter rainfall in 1951, the depressions remained waterlogged for several months. The perennial grasses died out and were replaced by species of Juncus and Carex and Eleocharis acuta R.Br. With the return to more normal rainfall the earlier flora in the depression is being slowly re-established. From measurements made on the soils it would appear that physical factors are important in determining the species which grow on the shelf, depression, and puff respectively. Some of the factors concerned are: (a) the soil moisture content at which water becomes available to plants, and particularly to seeds; (b) the intensity of soil cracking, which influences seed retention, moisture penetration, and the extent to which root systems are damaged; (c) aeration of the soil.

Soil water dynamics differ among rangeland plant communities dominated by yellow starthistle (Centaurea solstitialis), annual grasses, or perennial grasses

Weed Science ◽  
2004 ◽  
Vol 52 (6) ◽  
pp. 929-935 ◽  
Author(s):  
Stephen F. Enloe ◽  
Joseph M. DiTomaso ◽  
Steve B. Orloff ◽  
Daniel J. Drake
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Perennial Grasses ◽  
The Other ◽  
Water Dynamics ◽  
Yellow Starthistle ◽  
Community Interactions ◽  
Plant Introductions ◽  
Use Patterns ◽  
Annual Grasses

California's interior grasslands have undergone dramatic changes during the last two centuries. Changes in land-use patterns and plant introductions after European contact and settlement resulted in the conversion of perennial-dominated grasslands to exotic annual grasses. More recently, the annual grasslands have been heavily invaded by the deeply rooted late-maturing forb yellow starthistle. This series of invasions and conversions has changed the community structure and phenology of the grasslands. We hypothesized that these changes have resulted in significant differences in soil water–use patterns in the grasslands. We studied soil water depletion and recharge patterns of three grassland community types dominated by perennial grasses, annual grasses, or yellow starthistle with contrasting phenology and rooting depths for 4 yr. Soil moisture measurements were taken every month from March to December in 1998, 1999, and 2000 and every other month in 2001. Measurements were taken with a neutron probe at depths of 30 to 150 cm at 30-cm intervals. The results indicate that the yellow starthistle community maintained a significantly drier soil profile than the annual grass community. The perennial grass community maintained an intermediate soil water content that was not significantly different from either of the other two communities. Significant time by community and depth by community interactions indicated that the yellow starthistle community continued depleting soil moisture later into the season and at deeper depths than the other grass communities. This study demonstrates the effect of plant invasion on soil water recharge and depletion patterns in California grasslands.

Analysis on Soil Moisture Content in the Middle Reaches of the Yellow River

2011 ◽  
Vol 28 (1) ◽  
pp. 85-91 ◽  
Author(s):  
Run-chun LI ◽  
Xiu-zhi ZHANG ◽  
Li-hua WANG ◽  
Xin-yan LV ◽  
Yuan GAO
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Yellow River ◽  
The Yellow River

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.

Soil Moisture based Automatic Irrigation System to Improve Water Productivity

2020 ◽  
Vol 7 (04) ◽  
Author(s):  
PRADEEP H K ◽  
JASMA BALASANGAMESHWARA ◽  
K RAJAN ◽  
PRABHUDEV JAGADEESH
Keyword(s):  
Soil Moisture ◽  
Soil Moisture Content ◽  
Irrigation System ◽  
Water Productivity ◽  
Vital Role ◽  
Agricultural Water Management ◽  
Water Management System ◽  
Proposed Model ◽  
Crop Growth Stage ◽  
Experimental Findings

Irrigation automation plays a vital role in agricultural water management system. An efficient automatic irrigation system is crucial to improve crop water productivity. Soil moisture based irrigation is an economical and efficient approach for automation of irrigation system. An experiment was conducted for irrigation automation based on the soil moisture content and crop growth stage. The experimental findings exhibited that, automatic irrigation system based on the proposed model triggers the water supply accurately based on the real-time soil moisture values.

scholarly journals Mapping barrier island soil moisture using a radiative transfer model of hyperspectral imagery from an unmanned aerial system

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rehman S. Eon ◽  
Charles M. Bachmann
Keyword(s):  
Soil Moisture ◽  
Radiative Transfer ◽  
Moisture Content ◽  
Layer Thickness ◽  
Soil Moisture Content ◽  
Hyperspectral Imagery ◽  
Barrier Island ◽  
Water Layer ◽  
Radiative Transfer Model ◽  
Transfer Model

AbstractThe advent of remote sensing from unmanned aerial systems (UAS) has opened the door to more affordable and effective methods of imaging and mapping of surface geophysical properties with many important applications in areas such as coastal zone management, ecology, agriculture, and defense. We describe a study to validate and improve soil moisture content retrieval and mapping from hyperspectral imagery collected by a UAS system. Our approach uses a recently developed model known as the multilayer radiative transfer model of soil reflectance (MARMIT). MARMIT partitions contributions due to water and the sediment surface into equivalent but separate layers and describes these layers using an equivalent slab model formalism. The model water layer thickness along with the fraction of wet surface become parameters that must be optimized in a calibration step, with extinction due to water absorption being applied in the model based on equivalent water layer thickness, while transmission and reflection coefficients follow the Fresnel formalism. In this work, we evaluate the model in both field settings, using UAS hyperspectral imagery, and laboratory settings, using hyperspectral spectra obtained with a goniometer. Sediment samples obtained from four different field sites representing disparate environmental settings comprised the laboratory analysis while field validation used hyperspectral UAS imagery and coordinated ground truth obtained on a barrier island shore during field campaigns in 2018 and 2019. Analysis of the most significant wavelengths for retrieval indicate a number of different wavelengths in the short-wave infra-red (SWIR) that provide accurate fits to measured soil moisture content in the laboratory with normalized root mean square error (NRMSE)< 0.145, while independent evaluation from sequestered test data from the hyperspectral UAS imagery obtained during the field campaign obtained an average NRMSE = 0.169 and median NRMSE = 0.152 in a bootstrap analysis.

scholarly journals Estimating Agricultural Soil Moisture Content through UAV-Based Hyperspectral Images in the Arid Region

2021 ◽  
Vol 13 (8) ◽  
pp. 1562
Author(s):  
Xiangyu Ge ◽  
Jianli Ding ◽  
Xiuliang Jin ◽  
Jingzhe Wang ◽  
Xiangyue Chen ◽  
...  
Keyword(s):  
Data Mining ◽  
Soil Moisture ◽  
Moisture Content ◽  
Hyperspectral Imaging ◽  
Fractional Order ◽  
Arid Regions ◽  
Soil Moisture Content ◽  
Order Derivative ◽  
Imaging Data ◽  
Strategy I

Unmanned aerial vehicle (UAV)-based hyperspectral remote sensing is an important monitoring technology for the soil moisture content (SMC) of agroecological systems in arid regions. This technology develops precision farming and agricultural informatization. However, hyperspectral data are generally used in data mining. In this study, UAV-based hyperspectral imaging data with a resolution o 4 cm and totaling 70 soil samples (0–10 cm) were collected from farmland (2.5 × 104 m2) near Fukang City, Xinjiang Uygur Autonomous Region, China. Four estimation strategies were tested: the original image (strategy I), first- and second-order derivative methods (strategy II), the fractional-order derivative (FOD) technique (strategy III), and the optimal fractional order combined with the optimal multiband indices (strategy IV). These strategies were based on the eXtreme Gradient Boost (XGBoost) algorithm, with the aim of building the best estimation model for agricultural SMC in arid regions. The results demonstrated that FOD technology could effectively mine information (with an absolute maximum correlation coefficient of 0.768). By comparison, strategy IV yielded the best estimates out of the methods tested (R2val = 0.921, RMSEP = 1.943, and RPD = 2.736) for the SMC. The model derived from the order of 0.4 within strategy IV worked relatively well among the different derivative methods (strategy I, II, and III). In conclusion, the combination of FOD technology and the optimal multiband indices generated a highly accurate model within the XGBoost algorithm for SMC estimation. This research provided a promising data mining approach for UAV-based hyperspectral imaging data.

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