scholarly journals RESEARCH NOTEA comparison between reference transpiration and measurements of evaporation for a riparian grassland site

1998 ◽  
Vol 2 (1) ◽  
pp. 129-136 ◽  
Author(s):  
J. W. Finch ◽  
R. J. Harding
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Free Water ◽  
Eddy Correlation ◽  
Meteorological Variables ◽  
Direct Measurements ◽  
Riparian Grassland ◽  
Grassland Site

Abstract. This paper compares direct measurements of evaporation with the values predicted for reference transpiration. The measurements of actual evaporation were made using an eddy correlation device on a grass field adjacent to the river Thames. Measurements of soil moisture and the driving meteorological variables were also made. The results showed that, during a period with minimal rainfall but no water stress, the cumulative values of reference transpiration compared very well with the cumulative measured evaporation and changes in soil moisture content. However, the values on specific days did not compare well. Following significant rainfall, the measured evaporation increased for a few days, probably due to evaporation of free water from the canopy or soil. Reference transpiration fell consistently below the measured evaporation once the soil moisture deficits exceeded 140 to 150 mm.

scholarly journals Difference in Canopy and Air Temperature as an Indicator of Grassland Water Stress

2013 ◽  
Vol 1 (No. 4) ◽  
pp. 127-138 ◽  
Author(s):  
Duffková Renata
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Moisture Content ◽  
Air Temperature ◽  
Temperature Difference ◽  
Soil Moisture Content ◽  
Growing Season ◽  
Plant Residues ◽  
Dead Plant ◽  
Linear Correlations

In 2003–2005 in conditions of the moderately warm region of the Třeboň Basin (Czech Republic) the difference between canopy temperature (Tc) and air temperature at 2 m (Ta) was tested as an indicator of grass­land water stress. To evaluate water stress ten-minute averages of temperature difference Tc–Ta were chosen recorded on days without rainfall with intensive solar radiation from 11.00 to 14.00 CET. Water stress in the zone of the major portion of root biomass (0–0.2 m) in the peak growing season (minimum presence of dead plant residues) documented by a sudden increase in temperature difference, its value 5–12°C and unfavourable canopy temperatures due to overheating (> 30°C) was indicated after high values of suction pressure approach­ing the wilting point (1300 kPa) were reached. High variability of temperature difference in the conditions of sufficient supply of water to plants was explained by the amount of dead plant residues in canopy, value of va­pour pressure deficit (VPD), actual evapotranspiration rate (ETA) and soil moisture content. At the beginning of the growing season (presence of dead plant residues and voids) we proved moderately strong negative linear correlations of Tc–Ta with VPD and Tc–Ta with ETA rate and moderately strong positive linear correlations of ETA rate with VPD. In the period of intensive growth (the coverage of dead plant residues and voids lower than 10%) moderately strong linear correlations of Tc–Ta with VPD and multiple linear correlations of Tc–Ta with VPD and soil moisture content at a depth of 0.10–0.40 m were demonstrated.

scholarly journals Assessment of Drought Tolerance of Miscanthus Genotypes through Dry-Down Treatment and Fixed-Soil-Moisture-Content Techniques

Agriculture ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 6
Author(s):  
Tzu-Ya Weng ◽  
Taiken Nakashima ◽  
Antonio Villanueva-Morales ◽  
J. Ryan Stewart ◽  
Erik J. Sacks ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Drought Tolerance ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Influential Factor ◽  
Miscanthus Sinensis ◽  
Genetic Cluster ◽  
Drought Tolerant ◽  
Dry Down

Miscanthus, a high-yielding, warm-season C4 grass, shows promise as a potential bioenergy crop in temperate regions. However, drought may restrain productivity of most genotypes. In this study, total 29 Miscanthus genotypes of East-Asian origin were screened for drought tolerance with two methods, a dry-down treatment in two locations and a system where soil moisture content (SMC) was maintained at fixed levels using an automatic irrigation system in one location. One genotype, Miscanthus sinensis PMS-285, showed relatively high drought-tolerance capacity under moderate drought stress. Miscanthus sinensis PMS-285, aligned with the M. sinensis ‘Yangtze-Qinling’ genetic cluster, had relatively high principal component analysis ranking values in both two locations experiments, Hokkaido University and Brigham Young University. Genotypes derived from the ‘Yangtze-Qinling’ genetic cluster showed relatively greater photosynthetic performance than other genetic clusters, suggesting germplasm from this group could be a potential source of drought-tolerant plant material. Diploid genotypes showed stronger drought tolerance than tetraploid genotypes, suggesting ploidy could be an influential factor for this trait. Of the two methods, the dry-down treatment appears more suitable for selecting drought-tolerant genotypes given that it reflects water-stress conditions in the field. However, the fixed-SMC experiment may be good for understanding the physiological responses of plants to relatively constant water-stress levels.

Effect of soil moisture on transpiration.

1953 ◽  
Vol 4 (3) ◽  
pp. 326 ◽  
Author(s):  
ES West ◽  
O Perkman
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Exponential Function ◽  
Water Surface ◽  
Soil Moisture Content ◽  
Free Water ◽  
Soil Sampling ◽  
Water Withdrawal ◽  
Citrus Grove ◽  
Free Water Surface

The march of soil moisture content in an experimental citrus grove was determined by successive soil sampling. Following an irrigation the soil moisture content progressively falls owing to withdrawal of water by the plants. It was found that the soil moisture content could be expressed as an exponential function of the accumulated evaporation from a free water surface since the last irrigation. Curves of this type were constructed for the three kinds of cultural treatment studied. The rate of water withdrawal is a function of the soil moisture content.

Optimizing Irrigation Rates for Cotton Production in an Extremely Arid Area Using RZWQM2-Simulated Water Stress

2017 ◽  
Vol 60 (6) ◽  
pp. 2041-2052 ◽  
Author(s):  
Che Liu ◽  
Zhiming Qi ◽  
Zhe Gu ◽  
Dongwei Gui ◽  
Fanjiang Zeng
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Moisture Content ◽  
Water Balance ◽  
Soil Moisture Content ◽  
Irrigation Scheduling ◽  
Arid Area ◽  
Cotton Production ◽  
Crop Water ◽  
Crop Water Stress

Abstract. Quantifying crop water demand and optimizing irrigation management practices are essential to water resource management in arid desert oases. Agricultural systems modeling can serve to develop a better understanding of the hydrologic cycle under various irrigation and climate conditions. RZWQM2-simulated water stress can be used as an indicator for irrigation scheduling but has not been applied to extremely arid zones. The objectives of this study were to (1) evaluate the performance of RZWQM2 in simulating soil moisture content and crop production in an extremely arid area and (2) develop an optimal irrigation strategy using model-simulated crop water stress. In this study, RZWQM2 hybridized with DSSAT was calibrated and validated against soil moisture, cottield, and development stage data collected from 2006 to 2013 in a flood-irrigated cotton field located in an extremely dry oasis in Cele, situated in Xinjiang, China (mean annual precipitation 37 mm). The simulated water balance was analyzed to determine the actual crop water consumption, crop water requirements, and seepage loss. Subsequently, an optimal irrigation scheme was developed using RZWQM2 by averting crop water stress from planting to 90% open boll. In comparison to similar studies, the accuracy of soil moisture content simulations was deemed acceptable based on percent bias (PBIAS < ±15%), coefficient of determination (0.378 = R2 = 0.636), Nash-Sutcliffe model efficiency (0.130 = ME = 0.557), and root mean squared error (0.022 m3 m-3 = RMSE = 0.031 m3 m-3). The model performed well in simulating cotton yield (R2 = 0.79, ME = 0.75, RMSE = 417.0 kg ha-1, and relative RMSE (rRMSE) = 12.5%). Model-simulated plant emergence dates were generally six days late because of the model’s lack of a component for mulching after seeding. Other phenological dates were closely matched, with a mean difference of ±4 days. On average, over eight years, the simulated growing season (planting to 90% open boll) water balance showed that the cotton crop consumed 532 mm year-1 of water under current irrigation practices, while 109 mm of water was lost through deep seepage. However, based on simulated PET, the crop water requirement was 641 mm year-1, suggesting water stress under current irrigation practices. Under these conditions, water stress occurred mainly during the late stages of cotton growth. The model-simulated actual evapotranspiration (ET) is comparable to the calculated ET using the water balance method, with percent error of -1.3%, indicating the rationality of applying model-simulated results in a water stress-based irrigation scheduling method. On average, the water stress-minimizing RZWQM2 irrigation schedule resulted in an apparent irrigation water savings of 32 mm year-1 (4.9%) and an annual yield increase of 527 kg ha-1 (16.3%). RZWQM2 was shown to be suitable for simulating soil hydrology and crop development in an agricultural system implemented in an extremely dry climate. Rescheduling of irrigation using a water stress-based method can be used to optimize irrigation water use and cotton production. Keywords: Cotton production, Optimum irrigation, RZWQM2, Soil water content, Water stress, WS-based regime.

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.

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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