Positionally-independent and Extended Read Range Resonant Sensors Applied to Deep Soil Moisture Monitoring

2021 ◽  
pp. 113227
Author(s):  
Yee Jher Chan ◽  
Adam R. Carr ◽  
Subhanwit Roy ◽  
Caden M. Washburn ◽  
Nathan Neihart ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Deep Soil ◽  
Resonant Sensors ◽  
Read Range ◽  
Soil Moisture Monitoring

scholarly journals Multilayer Soil Moisture Mapping at a Regional Scale from Multisource Data via a Machine Learning Method

2019 ◽  
Vol 11 (3) ◽  
pp. 284 ◽  
Author(s):  
Linglin Zeng ◽  
Shun Hu ◽  
Daxiang Xiang ◽  
Xiang Zhang ◽  
Deren Li ◽  
...  
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Regional Scale ◽  
Remotely Sensed ◽  
Temporal Variations ◽  
Training Data ◽  
Estimation Accuracy ◽  
Learning Approaches ◽  
Remotely Sensed Data ◽  
Deep Soil

Soil moisture mapping at a regional scale is commonplace since these data are required in many applications, such as hydrological and agricultural analyses. The use of remotely sensed data for the estimation of deep soil moisture at a regional scale has received far less emphasis. The objective of this study was to map the 500-m, 8-day average and daily soil moisture at different soil depths in Oklahoma from remotely sensed and ground-measured data using the random forest (RF) method, which is one of the machine-learning approaches. In order to investigate the estimation accuracy of the RF method at both a spatial and a temporal scale, two independent soil moisture estimation experiments were conducted using data from 2010 to 2014: a year-to-year experiment (with a root mean square error (RMSE) ranging from 0.038 to 0.050 m3/m3) and a station-to-station experiment (with an RMSE ranging from 0.044 to 0.057 m3/m3). Then, the data requirements, importance factors, and spatial and temporal variations in estimation accuracy were discussed based on the results using the training data selected by iterated random sampling. The highly accurate estimations of both the surface and the deep soil moisture for the study area reveal the potential of RF methods when mapping soil moisture at a regional scale, especially when considering the high heterogeneity of land-cover types and topography in the study area.

scholarly journals State of the Art in Large-Scale Soil Moisture Monitoring

2013 ◽  
Vol 77 (6) ◽  
pp. 1888-1919 ◽  
Author(s):  
Tyson E. Ochsner ◽  
Michael H. Cosh ◽  
Richard H. Cuenca ◽  
Wouter A. Dorigo ◽  
Clara S. Draper ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Large Scale ◽  
State Of The Art ◽  
Soil Moisture Monitoring

scholarly journals The Murrumbidgee soil moisture monitoring network data set

2012 ◽  
Vol 48 (7) ◽  
Author(s):  
A. B. Smith ◽  
J. P. Walker ◽  
A. W. Western ◽  
R. I. Young ◽  
K. M. Ellett ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Monitoring Network ◽  
Network Data ◽  
Data Set ◽  
Soil Moisture Monitoring

Seasonal variation of deep soil moisture under different land uses on the semi-arid Loess Plateau of China

2018 ◽  
Vol 19 (3) ◽  
pp. 1179-1189 ◽  
Author(s):  
Bowei Yu ◽  
Gaohuan Liu ◽  
Qingsheng Liu ◽  
Chong Huang ◽  
He Li ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Seasonal Variation ◽  
Loess Plateau ◽  
Land Uses ◽  
Deep Soil ◽  
Semi Arid

Developmental and physiological traits associated with high yield and stay-green phenotype in wheat

2008 ◽  
Vol 59 (4) ◽  
pp. 354 ◽  
Author(s):  
J. T. Christopher ◽  
A. M. Manschadi ◽  
G. L. Hammer ◽  
A. K. Borrell
Keyword(s):  
Soil Moisture ◽  
Grain Filling ◽  
High Yield ◽  
Limiting Factor ◽  
Deep Soil ◽  
Stay Green ◽  
Physiological Basis ◽  
Winter Crops ◽  
Significant Yield ◽  
Grain Filling Period

Water availability is a key limiting factor in wheat production in the northern grain belt of Australia. Varieties with improved adaptation to such conditions are actively sought. The CIMMYT wheat line SeriM82 has shown a significant yield advantage in multi-environment screening trials in this region. The objective of this study was to identify the physiological basis of the adaptive traits underpinning this advantage. Six detailed experiments were conducted to compare the growth, development, and yield of SeriM82 with that of the adapted cultivar, Hartog. The experiments were undertaken in field environments that represented the range of moisture availability conditions commonly encountered by winter crops grown on the deep Vertosol soils of this region. The yield of SeriM82 was 6–28% greater than that of Hartog, and SeriM82 exhibited a stay-green phenotype by maintaining green leaf area longer during the grain-filling period in all environments where yield was significantly greater than Hartog. However, where the availability of deep soil moisture was limited, SeriM82 failed to exhibit significantly greater yield or to express the stay-green phenotype. Thus, the stay-green phenotype was closely associated with the yield advantage of SeriM82. SeriM82 also exhibited higher mean grain mass than Hartog in all environments. It is suggested that small differences in water use before anthesis, or greater water extraction from depth after anthesis, could underlie the stay-green phenotype. The inability of SeriM82 to exhibit stay-green and higher yield where deep soil moisture was depleted indicates that extraction of deep soil moisture is important.

scholarly journals Variations of deep soil moisture under different vegetation types and influencing factors in a watershed of the Loess Plateau, China

2016 ◽  
Vol 20 (8) ◽  
pp. 3309-3323 ◽  
Author(s):  
Xuening Fang ◽  
Wenwu Zhao ◽  
Lixin Wang ◽  
Qiang Feng ◽  
Jingyi Ding ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Influencing Factors ◽  
Loess Plateau ◽  
Vegetation Restoration ◽  
Native Vegetation ◽  
Watershed Scale ◽  
Vegetation Types ◽  
Deep Soil ◽  
Soil Layers ◽  
Management Measures

Abstract. Soil moisture in deep soil layers is a relatively stable water resource for vegetation growth in the semi-arid Loess Plateau of China. Characterizing the variations in deep soil moisture and its influencing factors at a moderate watershed scale is important to ensure the sustainability of vegetation restoration efforts. In this study, we focus on analyzing the variations and factors that influence the deep soil moisture (DSM) in 80–500 cm soil layers based on a soil moisture survey of the Ansai watershed in Yan'an in Shanxi Province. Our results can be divided into four main findings. (1) At the watershed scale, higher variations in the DSM occurred at 120–140 and 480–500 cm in the vertical direction. At the comparable depths, the variation in the DSM under native vegetation was much lower than that in human-managed vegetation and introduced vegetation. (2) The DSM in native vegetation and human-managed vegetation was significantly higher than that in introduced vegetation, and different degrees of soil desiccation occurred under all the introduced vegetation types. Caragana korshinskii and black locust caused the most serious desiccation. (3) Taking the DSM conditions of native vegetation as a reference, the DSM in this watershed could be divided into three layers: (i) a rainfall transpiration layer (80–220 cm); (ii) a transition layer (220–400 cm); and (iii) a stable layer (400–500 cm). (4) The factors influencing DSM at the watershed scale varied with vegetation types. The main local controls of the DSM variations were the soil particle composition and mean annual rainfall; human agricultural management measures can alter the soil bulk density, which contributes to higher DSM in farmland and apple orchards. The plant growth conditions, planting density, and litter water holding capacity of introduced vegetation showed significant relationships with the DSM. The results of this study are of practical significance for vegetation restoration strategies, especially for the choice of vegetation types, planting zones, and proper human management measures.

scholarly journals Effects of Climate Variability on Water Storage in the Colorado River Basin

2009 ◽  
Vol 10 (5) ◽  
pp. 1257-1270 ◽  
Author(s):  
Ruud Hurkmans ◽  
Peter A. Troch ◽  
Remko Uijlenhoet ◽  
Paul Torfs ◽  
Matej Durcik
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Colorado River ◽  
Decadal Variability ◽  
Southern Oscillation ◽  
Water Storage ◽  
Low Frequency ◽  
Colorado River Basin ◽  
Climate Indices ◽  
Deep Soil

Abstract Understanding the long-term (interannual–decadal) variability of water availability in river basins is paramount for water resources management. Here, the authors analyze time series of simulated terrestrial water storage components, observed precipitation, and discharge spanning 74 yr in the Colorado River basin and relate them to climate indices that describe variability of sea surface temperature and sea level pressure in the tropical and extratropical Pacific. El Niño–Southern Oscillation (ENSO) indices in winter [January–March (JFM)] are related to winter precipitation as well as to soil moisture and discharge in the lower Colorado River basin. The low-frequency mode of the Pacific decadal oscillation (PDO) appears to be strongly correlated with deep soil moisture. During the negative PDO phase, saturated storage anomalies tend to be negative and the “amplitudes” (mean absolute anomalies) of shallow soil moisture, snow, and discharge are slightly lower compared to periods of positive PDO phases. Predicting interannual variability, therefore, strongly depends on the capability of predicting PDO regime shifts. If indeed a shift to a cool PDO phase occurred in the mid-1990s, as data suggest, the current dry conditions in the Colorado River basin may persist.

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