Combining static and portable Cosmic ray neutron sensor data to assess catchment scale heterogeneity in soil water storage and their integrated role in catchment runoff response

Dimitrova‐Petrova, Katya; Rosolem, Rafael; Soulsby, Chris; Wilkinson, Mark; Lilly, Allan; Geris, Josie

doi:10.1016/j.jhydrol.2021.126659

Cited by 5 publications

(3 citation statements)

References 107 publications

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“…The CRN system is noninvasive, and a mobile application can provide SM maps across a range of spatial scales. This has been shown in previous research where moderated neutron detectors fitted into a backpack (Dimitrova‐Petrova et al., 2021; Franz, 2018) or installed in, for example, a vehicle was transported through smaller and larger landscape areas (Chrisman & Zreda, 2013; Desilets et al., 2010; Dong et al., 2014; Fersch et al., 2018; Franz et al., 2015; Heistermann et al., 2022; Jakobi et al., 2020; McJannet et al., 2017). The published study areas have mainly been relatively homogeneous in terms of land cover and soil type, where simple on‐site calibration based on small‐scale soil samples is adequate.…”

Section: Introductionsupporting

confidence: 72%

Mapping spatiotemporal soil moisture in highly heterogeneous agricultural landscapes using mobile dual‐spectra cosmic‐ray neutron sensing

Andreasen,

Kragh,

Meyer

et al. 2023

Vadose Zone Journal

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Accurate large‐scale soil moisture (SM) maps are crucial for catchment‐scale hydrological models used for water resource management and warning systems for droughts, floods, and wildfires. SM can be mapped by mobile cosmic‐ray neutron (CRN) systems of moderated detectors at homogeneous landscapes of similar soil and vegetation. In this study, we present a new approach for mobile CRN detection to perform to its full potential, where CRN measurements can also be converted to SM at heterogeneous landscapes. The approach is based solely on thermal and epithermal neutron datasets obtained from mobile dual‐spectra CRN detection, combined with theoretical developments using a particle transport model. For each measurement point, the land cover type is identified using the thermal‐to‐epithermal (T/E) ratio, and the relevant neutron‐count‐to‐soil‐moisture conversion function is estimated from CRN stations located at the main land cover types in the catchment. With this approach, the requirement of collecting 100+ soil samples for each point along the survey route is omitted. We use this T/E‐dependent approach to obtain SM maps from 12 CRN surveys and compare it with a simple approach where only the conversion function from the agricultural site is used. SM by the simple approach is comparable to the estimates of the agricultural stations of a capacitance sensor network, while the estimates of the T/E‐dependent approach also compare well with the heathland and forest stations. With accurate SM estimates for all landcover types, the average error is reduced from 0.089 to 0.038 when comparing CRN SM with space‐borne Soil Moisture Active Passive Mission estimates.

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Section: Introductionsupporting

confidence: 72%

Mapping spatiotemporal soil moisture in highly heterogeneous agricultural landscapes using mobile dual‐spectra cosmic‐ray neutron sensing

Andreasen,

Kragh,

Meyer

et al. 2023

Vadose Zone Journal

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“…This also indicates that it is challenging to capture the temporal soil moisture variations at hourly scale for sites with low bulk density and high organic soils. This might be related to the fact that organic soils contain hydrogen and also that the variations of organic soil content could lead to uncertainties in soil moisture calibration (Dimitrova-Petrova et al, 2021;Peng et al, 2021;Bogena et al, 2013).…”

Section: Rank Of Reanalysis Products For Different Regionsmentioning

confidence: 99%

“…4b) might also be the reason for explaining the lower performance for these UK sites. Although the impact of soil organic carbon on CRNS observations has been taken into account according to the crspy tool (Power et al, 2021a) used in this study, as mentioned in previous studies, it is more difficult to obtain the accurate soil moisture estimation and quantify the uncertainties of CRNS observations at sites with high soil organic carbon or in humid climates (Iwema et al, 2021;Bogena et al, 2013;Peng et al, 2021;Sigouin et al, 2016;Zhu et al, 2014;Franz et al, 2013a;Dimitrova-Petrova et al, 2021).…”

Section: Reanalysis Products' Performancementioning

confidence: 99%

Evaluation of reanalysis soil moisture products using cosmic ray neutron sensor observations across the globe

Zheng,

Coxon,

Woods

et al. 2024

Hydrol. Earth Syst. Sci.

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Abstract. Reanalysis soil moisture products are valuable for diverse applications, but their quality assessment is limited due to scale discrepancies when compared to traditional in situ point-scale measurements. The emergence of cosmic ray neutron sensors (CRNSs) with field-scale soil moisture estimates (∼ 250 m radius, up to 0.7 m deep) is more suitable for the product evaluation owing to their larger footprint. In this study, we perform a comprehensive evaluation of eight widely used reanalysis soil moisture products (ERA5-Land, CFSv2, MERRA2, JRA55, GLDAS-Noah, CRA40, GLEAM and SMAP L4 datasets) against 135 CRNS sites from the COSMOS-UK, COSMOS-Europe, COSMOS USA and CosmOz Australia networks. We evaluate the products using six metrics capturing different aspects of soil moisture dynamics. Results show that all reanalysis products generally exhibit good temporal correlation with the measurements, with the median temporal correlation coefficient (R) values spanning 0.69 to 0.79, though large deviations are found at sites with seasonally varying vegetation cover. Poor performance is observed across products for soil moisture anomalies time series, with R values varying from 0.46 to 0.66. The performance of reanalysis products differs greatly across regions, climate, land covers and topographic conditions. In general, all products tend to overestimate data in arid climates and underestimate data in humid regions as well as grassland. Most reanalysis products perform poorly in steep terrain. Relatively low temporal correlation and high bias are detected in some sites from the west of the UK, which might be associated with relatively low bulk density and high soil organic carbon. Overall, ERA5-Land, CRA40, CFSv2, SMAP L4 and GLEAM exhibit superior performance compared to MERRA2, GLDAS-Noah and JRA55. We recommend that ERA5-Land and CFSv2 could be used in humid climates, whereas SMAP L4 and CRA40 perform better in arid regions. SMAP L4 has good performance for cropland, while GLEAM is more effective in shrubland regions. Our findings also provide insights into directions for improvement of soil moisture products for product developers.

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Review on intelligent pipeline technologies: A life cycle perspective

Liang

et al. 2023

Computers & Chemical Engineering

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Combining static and portable Cosmic ray neutron sensor data to assess catchment scale heterogeneity in soil water storage and their integrated role in catchment runoff response

Cited by 5 publications

References 107 publications

Mapping spatiotemporal soil moisture in highly heterogeneous agricultural landscapes using mobile dual‐spectra cosmic‐ray neutron sensing

Mapping spatiotemporal soil moisture in highly heterogeneous agricultural landscapes using mobile dual‐spectra cosmic‐ray neutron sensing

Evaluation of reanalysis soil moisture products using cosmic ray neutron sensor observations across the globe

Review on intelligent pipeline technologies: A life cycle perspective

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