The Experts below are selected from a list of 16281 Experts worldwide ranked by ideXlab platform
Andrew Ireson - One of the best experts on this subject based on the ideXlab platform.
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Estimating field-scale root zone soil moisture using the cosmic-ray Neutron Probe
Hydrology and Earth System Sciences, 2016Co-Authors: Amber Peterson, Warren Helgason, Andrew IresonAbstract:Abstract. Many practical hydrological, meteorological, and agricultural management problems require estimates of soil moisture with an areal footprint equivalent to field scale, integrated over the entire root zone. The cosmic-ray Neutron Probe is a promising instrument to provide field-scale areal coverage, but these observations are shallow and require depth-scaling in order to be considered representative of the entire root zone. A study to identify appropriate depth-scaling techniques was conducted at a grazing pasture site in central Saskatchewan, Canada over a 2-year period. Area-averaged soil moisture was assessed using a cosmic-ray Neutron Probe. Root zone soil moisture was measured at 21 locations within the 500 m × 500 m study area, using a down-hole Neutron Probe. The cosmic-ray Neutron Probe was found to provide accurate estimates of field-scale surface soil moisture, but measurements represented less than 40 % of the seasonal change in root zone storage due to its shallow measurement depth. The root zone estimation methods evaluated were: (a) the coupling of the cosmic-ray Neutron Probe with a time-stable Neutron Probe monitoring location, (b) coupling the cosmic-ray Neutron Probe with a representative landscape unit monitoring approach, and (c) convolution of the cosmic-ray Neutron Probe measurements with the exponential filter. The time stability method provided the best estimate of root zone soil moisture (RMSE = 0.005 cm3 cm−3), followed by the exponential filter (RMSE = 0.014 cm3 cm−3). The landscape unit approach, which required no calibration, had a negative bias but estimated the cumulative change in storage reasonably. The feasibility of applying these methods to field sites without existing instrumentation is discussed. Based upon its observed performance and its minimal data requirements, it is concluded that the exponential filter method has the most potential for estimating root zone soil moisture from cosmic-ray Neutron Probe data.
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Estimating field scale root zone soil moisture using the cosmic-ray Neutron Probe
Hydrology and Earth System Sciences Discussions, 2015Co-Authors: A. M. Peterson, Warren Helgason, Andrew IresonAbstract:Abstract. Many practical hydrological, meteorological and agricultural management problems require estimates of soil moisture with an areal footprint equivalent to "field scale", integrated over the entire root zone. The cosmic-ray Neutron Probe is a promising instrument to provide field scale areal coverage, but these observations are shallow and require depth scaling in order to be considered representative of the entire root zone. A study to identify appropriate depth-scaling techniques was conducted at a grazing pasture site in central Saskatchewan, Canada over a two year period. Area-averaged soil moisture was assessed using a cosmic-ray Neutron Probe. Root zone soil moisture was measured at 21 locations within the 5002 m2 area, using a down-hole Neutron Probe. The cosmic-ray Neutron Probe was found to provide accurate estimates of field scale surface soil moisture, but accounted for less than 40 % of the seasonal change in root zone storage due to its shallow measurement depth. The root zone estimation methods evaluated were: (1) the coupling of the cosmic-ray Neutron Probe with a time stable Neutron Probe monitoring location, (2) coupling the cosmic-ray Neutron Probe with a representative landscape unit monitoring approach, and (3) convolution of the cosmic-ray Neutron Probe measurements with the exponential filter. The time stability method provided the best estimate of root zone soil moisture (RMSE = 0.004 cm3 cm−3), followed by the exponential filter (RMSE = 0.012 cm3 cm−3). The landscape unit approach, which required no calibration, had a negative bias but estimated the cumulative change in storage reasonably. The feasibility of applying these methods to field sites without existing instrumentation is discussed. It is concluded that the exponential filter method has the most potential for estimating root zone soil moisture from cosmic-ray Neutron Probe data.
Minha Choi - One of the best experts on this subject based on the ideXlab platform.
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extension of cosmic ray Neutron Probe measurement depth for improving field scale root zone soil moisture estimation by coupling with representative in situ sensors
Journal of Hydrology, 2019Co-Authors: Hoang Hai Nguyen, Jaehwan Jeong, Minha ChoiAbstract:Abstract Accurate estimation of field-scale root-zone soil moisture (RZSM) is essential for hydro-meteorological and agricultural management. The cosmic-ray Neutron Probe (CRNP) is an innovative technique for field-scale soil moisture observation. However, it is limited at deeper depths, and requires suitable methods for scaling the CRNP effective depth to represent the root-zone layer (up to 100 cm depth). A merging framework was developed in this study for improving field-scale RZSM with the CRNP via coupling the representative ancillary RZSM information with cosmic-ray soil moisture. By using ancillary RZSM retrieved at the most time stable location, this approach alleviates the problems associated with lack of independent datasets, while maintaining scale representativeness. A linear autoregressive model was adopted to forecast the errors between two input datasets (the cosmic-ray soil moisture and ancillary RZSM) and a reference product, which was computed by spatially weighting the deepest in-situ soil moisture measurements apart from the most time stable location. The variances of estimated errors were then used to compute a suitable weight for each single product by following the original linear combination of forecasts, and subsequently merging the ancillary RZSM and cosmic-ray soil moisture. Performance of the merged RZSM in comparison to input datasets and exponential filter-based RZSM over three different environments was evaluated against the reference RZSM product. The results indicated that differences in vegetation coverages related to total aboveground and belowground biomass accumulation, root water uptake rate and canopy density are the major factors controlling the temporal variation in merged RZSM, and they can be partly interpreted via the framework procedure. Superior performance achieved by the merging framework demonstrated its robustness in improving field-scale RZSM measurement compared to other products. This study also underlines the strong relationship between input data quality and the performance of the selected merging method, with respect to variations of CRNP effective depths. Overall, the merging framework is simple to apply, enables unrestricted-use in different environments, and is flexible to combine further standalone data sources.
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Evaluation of the soil water content using cosmic-ray Neutron Probe in a heterogeneous monsoon climate-dominated region
Advances in Water Resources, 2017Co-Authors: Hoang Hai Nguyen, Hyunglok Kim, Minha ChoiAbstract:Abstract This study was conducted to evaluate the performance of a preliminary soil moisture product estimated from the cosmic-ray Neutron Probe (CRNP) installed at a densely vegetated and monsoon climate area, namely the Soil Moisture - FDR and Cosmic-ray (SM-FC) site in South Korea. In this study, different calibration approaches, considering soil wetness conditions, were evaluated to select the most appropriate calibration method for deriving the best cosmic-ray soil moisture at the SM-FC site. We tested the potential application of two horizontal-vertical weighting methods, including the linear and non-linear approaches, with regard to the specific characteristics of the SM-FC site. The comparison of the two weighting approaches for in-situ soil moisture measurement suggested that the linear approach provided better performance compared to the non-linear in term of representing field-average soil moisture within the CRNP footprint. Our calibration results revealed that dry condition-based calibration outperformed wet condition-based calibration. The comparison of the cosmic-ray soil moisture utilizing dry condition-based calibration showed reasonable agreement with the linear weighted average soil moisture estimated from the FDR sensor network, with RMSE = 0.035 m3 m−3, and bias = −0.003 m3 m−3; while the worst calibration solution with the wettest conditions had RMSE and bias values of 0.077 m3 m−3 and 0.063 m3 m−3, respectively. The application of a biomass correction significantly improved the cosmic-ray soil moisture product at the SM-FC site, resulting in the reduction of RMSE from 0.035 to 0.013 m3 m−3. A temporal stability analysis was conducted to demonstrate the feasibility of cosmic-ray soil moisture in representing soil moisture for a large heterogeneous SM-FC site. Our temporal stability analysis results indicated the representativeness of cosmic-ray soil moisture over an area with a high degree of heterogeneity, compared to single measurements from FDR stations.
Mingan Shao - One of the best experts on this subject based on the ideXlab platform.
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Footprint radius of a cosmic-ray Neutron Probe for measuring soil-water content and its spatiotemporal variability in an alpine meadow ecosystem
Journal of Hydrology, 2018Co-Authors: Xuchao Zhu, Mingan Shao, Rui‐xue Cao, Yin LiangAbstract:Abstract Cosmic-ray Neutron Probes (CRNPs) have footprint radii for measuring soil-water content (SWC). The theoretical radius is much larger at high altitude, such as the northern Tibetan Plateau, than the radius at sea level. The most probable practical radius of CRNPs for the northern Tibetan Plateau, however, is not known due to the lack of SWC data in this hostile environment. We calculated the theoretical footprint of the CRNP based on a recent simulation and analyzed the practical radius of a CRNP for the northern Tibetan Plateau by measuring SWC at 113 sampling locations on 21 measuring occasions to a depth of 30 cm in a 33.5 ha plot in an alpine meadow at 4600 m a.s.l. The temporal variability and spatial heterogeneity of SWC within the footprint were then analyzed. The theoretical footprint radius was between 360 and 420 m after accounting for the influences of air humidity, soil moisture, vegetation and air pressure. A comparison of SWCs measured by the CRNP and a Neutron Probe from access tubes in circles with different radii conservatively indicated that the most probable experimental footprint radius was >200 m. SWC within the CRNP footprint was moderately variable over both time and space, but the temporal variability was higher. Spatial heterogeneity was weak, but should be considered in future CRNP calibrations. This study provided theoretical and practical bases for the application and promotion of CRNPs in alpine meadows on the Tibetan Plateau.
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Application of temporal stability analysis in depth-scaling estimated soil water content by cosmic-ray Neutron Probe on the northern Tibetan Plateau.
Journal of Hydrology, 2017Co-Authors: Xuchao Zhu, Mingan Shao, Xiaoxu Jia, Laiming Huang, Juntao Zhu, Yangjian ZhangAbstract:Abstract Soil moisture is a key limiting factor in grass growth and restoration in alpine meadow ecosystems on the northern Tibetan Plateau. In the deeper layers, soil moisture influences the processes of freeze-thaw, erosion and water cycle. Cosmic-ray Neutron Probe (CRNP) is a new method for continuously monitoring mean soil water content (SWC) at hectometer scale, which has been applied in an alpine meadow at a high accuracy. However, with CRNP measuring depth of only 30 cm, depth-scaling is needed for sufficient insight into deep-layer soil moisture. This study evaluated the accuracy of CRNP measurement of SWC in the 2015 and 2016 growing seasons and the performance of temporal stability (TS) analysis in depth-scaling CRNP-estimated SWC. During the study period, 11 field samplings were done for calibration of CRNP-estimated SWC. Using 22 occasions of Neutron Probe measurements for each of 113 investigated locations, the TS of SWC was analyzed and its performance in depth-scaling CRNP-estimated SWC at five soil depths (10, 20, 30, 40 and 50 cm) was evaluated. The results showed that the mean SWCs to the depth of 50 cm were 12.9 and 17.0%, respectively in 2015 and 2016 growing seasons and were temporally influenced by precipitation and spatially by soil depth. The accuracy of the CRNP-measured SWC was high, with root mean square error and Nash-Sutcliffe efficiency coefficient (NSE) of 2.1% and 0.832, respectively. Representative locations for TS existed in all the soil layers, which increased with increasing soil depth. For the various soil layers, TS-estimated SWC was close to field-measured value. Only a relatively small error and high NSE were noted, suggesting that TS was reliable in application in CRNP depth-scaling. The study provided further scientific basis for the application of CRNP and an effective way of depth-scaling CRNP-estimated mean SWC in alpine meadow ecosystems.
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time stability of soil water storage measured by Neutron Probe and the effects of calibration procedures in a small watershed
Catena, 2009Co-Authors: Mingan Shao, Quanjiu Wang, Klaus ReichardtAbstract:The knowledge of soil water storage (SWS) of soil profiles is crucial for the adoption of vegetation restoration practices. With the aim of identifying representative sites to obtain the mean SWS of a watershed, a time stability analysis of Neutron Probe evaluations of SWS was performed by the means of relative differences and Spearman rank correlation coefficients. At the same time, the effects of different Neutron Probe calibration procedures were explored on time stability analysis. mean SWS estimation. and preservation of the spatial variability of SWS. The selected watershed, with deep gullies and undulating slopes which cover an area of 20 ha, is characterized by an Ust-Sandiic Entisol and an Aeolian sandy soil. The dominant vegetation species are bunge needlegrass (Stipa bungeana Trim) and korshinsk peashrub (Carugano Korshinskii kom.). From June 11, 2007 to July 23,2008, SWS of the top1 m soil layer was evaluated for 20 dates, based on Neutron Probe data of 12 sampling sites. Three calibration procedures were employed: type 1, most complete, with each site having its own linear calibration equation (TrE); type II. with TrE equations extended over the whole field: and type III, with one single linear calibration curve for the whole field (UnE) and also correcting its intercept based on site specific relative difference analysis (RdE) and on linear fitting of data (RcE), both maintaining the same slope. A strong time stability of SWS estimated by TrE equations was identified. Soil particle size and soil organic matter content were recognized as the influencing factors for spatial variability of SWS. Land use influenced neither the spatial variability nor the time stability of SWS. Time stability analysis identified one site to represent the mean SWS of the whole watershed with mean absolute percentage errors of less than 10%, therefore. this site can be used as a predictor for the mean SWS of the watershed. Some equations of type II were found to be unsatisfactory to yield reliable mean SWS values or in preserving the associated soil spatial variability. Hence, it is recommended to be cautious in extending calibration equations to other sites since they might not consider the field variability. For the equations with corrected intercept (type III), which consider the spatial variability of calibration in a different way in relation to TrE, it was found that they can yield satisfactory means and standard deviation of SWS, except for the RdE equations, which largely leveled off the SWS values in the watershed. Correlation analysis showed that the Neutron Probe calibration was linked to soil bulk density and to organic matter content. Therefore, spatial variability of soil properties should be taken into account during the process of Neutron Probe calibration. This study provides useful information on the mean SWS observation with a time stable site and on distinct Neutron Probe calibration procedures, and it should be extended to soil water management studies with Neutron Probes, e.g., the process of vegetation restoration in wider area and soil types of the Loess Plateau in China. (C) 2009 Elsevier B.V. All rights reserved.
Warren Helgason - One of the best experts on this subject based on the ideXlab platform.
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Estimating field-scale root zone soil moisture using the cosmic-ray Neutron Probe
Hydrology and Earth System Sciences, 2016Co-Authors: Amber Peterson, Warren Helgason, Andrew IresonAbstract:Abstract. Many practical hydrological, meteorological, and agricultural management problems require estimates of soil moisture with an areal footprint equivalent to field scale, integrated over the entire root zone. The cosmic-ray Neutron Probe is a promising instrument to provide field-scale areal coverage, but these observations are shallow and require depth-scaling in order to be considered representative of the entire root zone. A study to identify appropriate depth-scaling techniques was conducted at a grazing pasture site in central Saskatchewan, Canada over a 2-year period. Area-averaged soil moisture was assessed using a cosmic-ray Neutron Probe. Root zone soil moisture was measured at 21 locations within the 500 m × 500 m study area, using a down-hole Neutron Probe. The cosmic-ray Neutron Probe was found to provide accurate estimates of field-scale surface soil moisture, but measurements represented less than 40 % of the seasonal change in root zone storage due to its shallow measurement depth. The root zone estimation methods evaluated were: (a) the coupling of the cosmic-ray Neutron Probe with a time-stable Neutron Probe monitoring location, (b) coupling the cosmic-ray Neutron Probe with a representative landscape unit monitoring approach, and (c) convolution of the cosmic-ray Neutron Probe measurements with the exponential filter. The time stability method provided the best estimate of root zone soil moisture (RMSE = 0.005 cm3 cm−3), followed by the exponential filter (RMSE = 0.014 cm3 cm−3). The landscape unit approach, which required no calibration, had a negative bias but estimated the cumulative change in storage reasonably. The feasibility of applying these methods to field sites without existing instrumentation is discussed. Based upon its observed performance and its minimal data requirements, it is concluded that the exponential filter method has the most potential for estimating root zone soil moisture from cosmic-ray Neutron Probe data.
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Estimating field scale root zone soil moisture using the cosmic-ray Neutron Probe
Hydrology and Earth System Sciences Discussions, 2015Co-Authors: A. M. Peterson, Warren Helgason, Andrew IresonAbstract:Abstract. Many practical hydrological, meteorological and agricultural management problems require estimates of soil moisture with an areal footprint equivalent to "field scale", integrated over the entire root zone. The cosmic-ray Neutron Probe is a promising instrument to provide field scale areal coverage, but these observations are shallow and require depth scaling in order to be considered representative of the entire root zone. A study to identify appropriate depth-scaling techniques was conducted at a grazing pasture site in central Saskatchewan, Canada over a two year period. Area-averaged soil moisture was assessed using a cosmic-ray Neutron Probe. Root zone soil moisture was measured at 21 locations within the 5002 m2 area, using a down-hole Neutron Probe. The cosmic-ray Neutron Probe was found to provide accurate estimates of field scale surface soil moisture, but accounted for less than 40 % of the seasonal change in root zone storage due to its shallow measurement depth. The root zone estimation methods evaluated were: (1) the coupling of the cosmic-ray Neutron Probe with a time stable Neutron Probe monitoring location, (2) coupling the cosmic-ray Neutron Probe with a representative landscape unit monitoring approach, and (3) convolution of the cosmic-ray Neutron Probe measurements with the exponential filter. The time stability method provided the best estimate of root zone soil moisture (RMSE = 0.004 cm3 cm−3), followed by the exponential filter (RMSE = 0.012 cm3 cm−3). The landscape unit approach, which required no calibration, had a negative bias but estimated the cumulative change in storage reasonably. The feasibility of applying these methods to field sites without existing instrumentation is discussed. It is concluded that the exponential filter method has the most potential for estimating root zone soil moisture from cosmic-ray Neutron Probe data.
Hoang Hai Nguyen - One of the best experts on this subject based on the ideXlab platform.
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extension of cosmic ray Neutron Probe measurement depth for improving field scale root zone soil moisture estimation by coupling with representative in situ sensors
Journal of Hydrology, 2019Co-Authors: Hoang Hai Nguyen, Jaehwan Jeong, Minha ChoiAbstract:Abstract Accurate estimation of field-scale root-zone soil moisture (RZSM) is essential for hydro-meteorological and agricultural management. The cosmic-ray Neutron Probe (CRNP) is an innovative technique for field-scale soil moisture observation. However, it is limited at deeper depths, and requires suitable methods for scaling the CRNP effective depth to represent the root-zone layer (up to 100 cm depth). A merging framework was developed in this study for improving field-scale RZSM with the CRNP via coupling the representative ancillary RZSM information with cosmic-ray soil moisture. By using ancillary RZSM retrieved at the most time stable location, this approach alleviates the problems associated with lack of independent datasets, while maintaining scale representativeness. A linear autoregressive model was adopted to forecast the errors between two input datasets (the cosmic-ray soil moisture and ancillary RZSM) and a reference product, which was computed by spatially weighting the deepest in-situ soil moisture measurements apart from the most time stable location. The variances of estimated errors were then used to compute a suitable weight for each single product by following the original linear combination of forecasts, and subsequently merging the ancillary RZSM and cosmic-ray soil moisture. Performance of the merged RZSM in comparison to input datasets and exponential filter-based RZSM over three different environments was evaluated against the reference RZSM product. The results indicated that differences in vegetation coverages related to total aboveground and belowground biomass accumulation, root water uptake rate and canopy density are the major factors controlling the temporal variation in merged RZSM, and they can be partly interpreted via the framework procedure. Superior performance achieved by the merging framework demonstrated its robustness in improving field-scale RZSM measurement compared to other products. This study also underlines the strong relationship between input data quality and the performance of the selected merging method, with respect to variations of CRNP effective depths. Overall, the merging framework is simple to apply, enables unrestricted-use in different environments, and is flexible to combine further standalone data sources.
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Evaluation of the soil water content using cosmic-ray Neutron Probe in a heterogeneous monsoon climate-dominated region
Advances in Water Resources, 2017Co-Authors: Hoang Hai Nguyen, Hyunglok Kim, Minha ChoiAbstract:Abstract This study was conducted to evaluate the performance of a preliminary soil moisture product estimated from the cosmic-ray Neutron Probe (CRNP) installed at a densely vegetated and monsoon climate area, namely the Soil Moisture - FDR and Cosmic-ray (SM-FC) site in South Korea. In this study, different calibration approaches, considering soil wetness conditions, were evaluated to select the most appropriate calibration method for deriving the best cosmic-ray soil moisture at the SM-FC site. We tested the potential application of two horizontal-vertical weighting methods, including the linear and non-linear approaches, with regard to the specific characteristics of the SM-FC site. The comparison of the two weighting approaches for in-situ soil moisture measurement suggested that the linear approach provided better performance compared to the non-linear in term of representing field-average soil moisture within the CRNP footprint. Our calibration results revealed that dry condition-based calibration outperformed wet condition-based calibration. The comparison of the cosmic-ray soil moisture utilizing dry condition-based calibration showed reasonable agreement with the linear weighted average soil moisture estimated from the FDR sensor network, with RMSE = 0.035 m3 m−3, and bias = −0.003 m3 m−3; while the worst calibration solution with the wettest conditions had RMSE and bias values of 0.077 m3 m−3 and 0.063 m3 m−3, respectively. The application of a biomass correction significantly improved the cosmic-ray soil moisture product at the SM-FC site, resulting in the reduction of RMSE from 0.035 to 0.013 m3 m−3. A temporal stability analysis was conducted to demonstrate the feasibility of cosmic-ray soil moisture in representing soil moisture for a large heterogeneous SM-FC site. Our temporal stability analysis results indicated the representativeness of cosmic-ray soil moisture over an area with a high degree of heterogeneity, compared to single measurements from FDR stations.