B. Zawilski, F. Granouillac, N. Claverie, Baptiste Lemaire, A. Brut, T. Tallec
Abstract. Soil water content (SWC) sensors are widely used for scientific studies or for the management of agricultural practices. The most common sensing techniques provide an estimate of volumetric soil water content based on sensing of dielectric permittivity. These techniques include frequency domain reflectometry (FDR), time domain reflectometry (TDR), capacitance and even remote-sensing techniques such as ground-penetrating radar (GPR) and microwave-based techniques. Here, we will focus on frequency domain reflectometry (FDR) sensors and more specifically on the questioning of their factory calibration, which does not take into account soil-specific features and therefore possibly leads to inconsistent SWC estimates. We conducted the present study in the southwest of France on two plots that are part of the ICOS ERIC network (Integrated Carbon Observation System, European Research and Infrastructure Consortium), FR-Lam and FR-Aur. We propose a simple protocol for soil-specific calibration, particularly suitable for clayey soil, to improve the accuracy of SWC determination when using commercial FDR sensors. We compared the sensing accuracy after soil-specific calibration versus factory calibration. Our results stress the necessity of performing a thorough soil-specific calibration for very clayey soils. Hence, locally, we found that factory calibration results in a strong overestimation of the actual soil water content. Indeed, we report relative errors as large as +115 % with a factory-calibrated sensor based on the real part of dielectric permittivity and up to + 245 % with a factory-calibrated sensor based on the modulus of dielectric permittivity.
{"title":"Calculation of soil water content using dielectric-permittivity-based sensors – benefits of soil-specific calibration","authors":"B. Zawilski, F. Granouillac, N. Claverie, Baptiste Lemaire, A. Brut, T. Tallec","doi":"10.5194/gi-12-45-2023","DOIUrl":"https://doi.org/10.5194/gi-12-45-2023","url":null,"abstract":"Abstract. Soil water content (SWC) sensors are widely used for\u0000scientific studies or for the management of agricultural practices. The most\u0000common sensing techniques provide an estimate of volumetric soil water\u0000content based on sensing of dielectric permittivity. These techniques\u0000include frequency domain reflectometry (FDR), time domain reflectometry\u0000(TDR), capacitance and even remote-sensing techniques such as\u0000ground-penetrating radar (GPR) and microwave-based techniques. Here, we will\u0000focus on frequency domain reflectometry (FDR) sensors and more specifically\u0000on the questioning of their factory calibration, which does not take into\u0000account soil-specific features and therefore possibly leads to inconsistent\u0000SWC estimates. We conducted the present study in the southwest of France\u0000on two plots that are part of the ICOS ERIC network (Integrated Carbon\u0000Observation System, European Research and Infrastructure Consortium), FR-Lam\u0000and FR-Aur. We propose a simple protocol for soil-specific calibration,\u0000particularly suitable for clayey soil, to improve the accuracy of SWC\u0000determination when using commercial FDR sensors. We compared the sensing\u0000accuracy after soil-specific calibration versus factory calibration. Our\u0000results stress the necessity of performing a thorough soil-specific\u0000calibration for very clayey soils. Hence, locally, we found that factory\u0000calibration results in a strong overestimation of the actual soil water\u0000content. Indeed, we report relative errors as large as +115 % with a\u0000factory-calibrated sensor based on the real part of dielectric permittivity\u0000and up to + 245 % with a factory-calibrated sensor based on the modulus\u0000of dielectric permittivity.\u0000","PeriodicalId":48742,"journal":{"name":"Geoscientific Instrumentation Methods and Data Systems","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71234348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Späth, Verena Rajtschan, Tobias K. D. Weber, Shehan Morandage, D. Lange, Syed, Saqlain Abbas, A. Behrendt, J. Ingwersen, T. Streck, V. Wulfmeyer
Abstract. Important topics in land–atmosphere (L–A) feedback research are water and energy balances and heterogeneities of fluxes at the land surface and in the atmospheric boundary layer (ABL). To target these questions, the Land–Atmosphere Feedback Observatory (LAFO) has been installed in southwestern Germany. The instrumentation allows comprehensive and high-resolution measurements from the bedrock to the lower free troposphere. Grouped into three components, atmosphere, soil and land surface, and vegetation, the LAFO observation strategy aims for simultaneous measurements in all three compartments. For this purpose the LAFO sensor synergy contains lidar systems to measure the atmospheric key variables of humidity, temperature and wind. At the land surface, eddy covariance stations are operated to record the energy distribution of radiation, sensible, latent and ground heat fluxes. Together with a water and temperature sensor network, the soil water content and temperature are monitored in the agricultural investigation area. As for vegetation, crop height, leaf area index and phenological growth stage values are registered. The observations in LAFO are organized into operational measurements and intensive observation periods (IOPs). Operational measurements aim for long time series datasets to investigate statistics, and we present as an example the correlation between mixing layer height and surface fluxes. The potential of IOPs is demonstrated with a 24 h case study using dynamic and thermodynamic profiles with lidar and a surface layer observation that uses the scanning differential absorption lidar to relate atmospheric humidity patterns to soil water structures. Both IOPs and long-term observations will provide new insight into exchange processes and their statistics for improving the representation of L–A feedbacks in climate and numerical weather prediction models. The lidar component in particular will support the investigation of coupling to the atmosphere.
{"title":"The land–atmosphere feedback observatory: a new observational approach for characterizing land–atmosphere feedback","authors":"F. Späth, Verena Rajtschan, Tobias K. D. Weber, Shehan Morandage, D. Lange, Syed, Saqlain Abbas, A. Behrendt, J. Ingwersen, T. Streck, V. Wulfmeyer","doi":"10.5194/gi-12-25-2023","DOIUrl":"https://doi.org/10.5194/gi-12-25-2023","url":null,"abstract":"Abstract. Important topics in land–atmosphere (L–A) feedback research are water and energy balances and heterogeneities of fluxes at the land surface and in the atmospheric boundary layer (ABL). To target these questions, the Land–Atmosphere Feedback Observatory (LAFO) has been installed in southwestern Germany. The instrumentation allows comprehensive and high-resolution measurements from the bedrock to the lower free troposphere. Grouped into three components, atmosphere, soil and land surface, and vegetation, the LAFO observation strategy aims for simultaneous measurements in all three compartments. For this purpose the LAFO sensor synergy contains lidar systems to measure the atmospheric key variables of humidity, temperature and wind. At the land surface, eddy covariance stations are operated to record the energy distribution of radiation, sensible, latent and ground heat fluxes. Together with a water and temperature sensor network, the soil water content and temperature are monitored in the agricultural investigation area. As for vegetation, crop height, leaf area index and phenological growth stage values are registered. The observations in LAFO are organized into operational measurements and\u0000intensive observation periods (IOPs). Operational measurements aim for long\u0000time series datasets to investigate statistics, and we present as an example the correlation between mixing layer height and surface fluxes. The potential of IOPs is demonstrated with a 24 h case study using dynamic and thermodynamic profiles with lidar and a surface layer observation that uses the scanning differential absorption lidar to relate atmospheric humidity patterns to soil water structures. Both IOPs and long-term observations will provide new insight into exchange\u0000processes and their statistics for improving the representation of L–A feedbacks in climate and numerical weather prediction models. The lidar component in particular will support the investigation of coupling to the\u0000atmosphere.\u0000","PeriodicalId":48742,"journal":{"name":"Geoscientific Instrumentation Methods and Data Systems","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43844605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Antenor Oliveira Cruz Júnior, Cosme Ferreira da Ponte-Neto, A. Wiermann
Abstract. Geoelectrical resistivity is an excellent method to investigate the structural composition of shallow subsurfaces. However, existing commercial equipment is typically expensive and often requires proprietary accessories and software to provide full system functionality. The objective of this study was to develop a multichannel, modular, automated, and programmable geo-resistivity meter capable of user customization and programming. To this end, a conceptual prototype was built based on free software and open hardware technologies as a low-cost alternative to commercial equipment while maintaining the accuracy and quality of the data at the same level. The prototype was based on electrode multiplexing to make the switching process more efficient by reducing cabling complexity, whereas synchronous demodulation for signal detection was employed, providing strong rejection of spurious electrical noise, typical of urban areas where such equipment is frequently used. The results demonstrate the feasibility of this project and an important academic contribution to open-source instrumental research.
{"title":"Design and construction of an automated and programmable resistivity meter for shallow subsurface investigation","authors":"Antenor Oliveira Cruz Júnior, Cosme Ferreira da Ponte-Neto, A. Wiermann","doi":"10.5194/gi-12-15-2023","DOIUrl":"https://doi.org/10.5194/gi-12-15-2023","url":null,"abstract":"Abstract. Geoelectrical resistivity is an excellent method to investigate the structural composition of shallow subsurfaces. However, existing commercial equipment is typically expensive and often requires proprietary accessories and software to provide full system functionality. The objective of this study was to develop a multichannel, modular, automated, and programmable geo-resistivity meter capable of user customization and programming. To this end, a conceptual prototype was built based on free software and open hardware technologies as a low-cost alternative to commercial equipment while maintaining the accuracy and quality of the data at the same level. The prototype was based on electrode multiplexing to make the switching process more efficient by reducing cabling complexity, whereas synchronous demodulation for signal detection was employed, providing strong rejection of spurious electrical noise, typical of urban areas where such equipment is frequently used. The results demonstrate the feasibility of this project and an important academic contribution to open-source instrumental research.\u0000","PeriodicalId":48742,"journal":{"name":"Geoscientific Instrumentation Methods and Data Systems","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46282716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. The Sweeping Langmuir Probe (SLP) is one of the instruments on board the triple-unit CubeSat PICASSO, an ESA in-orbit demonstrator launched in September 2020, which is flying at about 540 km altitude. SLP comprises four small cylindrical probes mounted at the tip of the solar panels. It aims to perform in situ measurements of the plasma parameters (electron density and temperature together with ion density) and of the spacecraft potential in the ionosphere. Before the launch, the instrument, accommodated on an electrically representative PICASSO mock-up, was tested in a plasma chamber. It is shown that the traditional orbital-motion-limited collection theory used for cylindrical Langmuir probes cannot be applied directly for the interpretation of the measurements because of the limited dimensions of the probes with respect to the Debye length in the ionosphere. Nevertheless, this method can be adapted to take into account the short length of the probes. To reduce the data downlink while keeping the most important information in the current-voltage characteristics, SLP includes an on-board adaptive sweeping capability. This functionality has been validated in both the plasma chamber and in space, and it is demonstrated that with a reduced number of data points the electron retardation and electron saturation regions can be well resolved. Finally, the effect of the contamination of the probe surface, which can be a serious issue in Langmuir probe data analysis, has been investigated. If not accounted for properly, this effect could lead to substantial errors in the estimation of the electron temperature.
{"title":"Laboratory measurements of the performances of the Sweeping Langmuir Probe instrument aboard the PICASSO CubeSat","authors":"S. Ranvier, J. Lebreton","doi":"10.5194/gi-12-1-2023","DOIUrl":"https://doi.org/10.5194/gi-12-1-2023","url":null,"abstract":"Abstract. The Sweeping Langmuir Probe (SLP) is one of the\u0000instruments on board the triple-unit CubeSat PICASSO, an ESA in-orbit\u0000demonstrator launched in September 2020, which is flying at about 540 km\u0000altitude. SLP comprises four small cylindrical probes mounted at the tip of the\u0000solar panels. It aims to perform in situ measurements of the plasma\u0000parameters (electron density and temperature together with ion density) and\u0000of the spacecraft potential in the ionosphere. Before the launch, the\u0000instrument, accommodated on an electrically representative PICASSO mock-up,\u0000was tested in a plasma chamber. It is shown that the traditional\u0000orbital-motion-limited collection theory used for cylindrical Langmuir\u0000probes cannot be applied directly for the interpretation of the measurements\u0000because of the limited dimensions of the probes with respect to the Debye\u0000length in the ionosphere. Nevertheless, this method can be adapted to take\u0000into account the short length of the probes. To reduce the data downlink\u0000while keeping the most important information in the current-voltage\u0000characteristics, SLP includes an on-board adaptive sweeping capability. This\u0000functionality has been validated in both the plasma chamber and in space, and\u0000it is demonstrated that with a reduced number of data points the electron\u0000retardation and electron saturation regions can be well resolved. Finally,\u0000the effect of the contamination of the probe surface, which can be a serious\u0000issue in Langmuir probe data analysis, has been investigated. If not\u0000accounted for properly, this effect could lead to substantial errors in the\u0000estimation of the electron temperature.\u0000","PeriodicalId":48742,"journal":{"name":"Geoscientific Instrumentation Methods and Data Systems","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45679850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Juan V. Pallotta, Silvania Carvalho, Fabio J. S. Lopes, Alexandre Cacheffo, Eduardo Landulfo, Henrique M. J. Barbosa
Abstract. Lidars can simultaneously measure clouds and aerosols with high temporal and spatial resolution and hence help understand their interactions, which are the source of the largest uncertainties in current climate projections. However, lidars are typically custom-built, so there are significant differences between them. In this sense, lidar networks play a crucial role as they coordinate the efforts of different groups, providing the guidelines for quality-assured routine measurements aiming to homogenize the physical retrievals. With that in mind, this work describes an ongoing effort to develop a lidar processing pipeline (LPP) collaboratively. The LPP is a collection of tools developed in C/C++, python, and Linux script that handle all the steps of a typical lidar analysis. The first publicly released version of LPP produces data files at levels 0 (raw and metadata), 1 (averaging and layer-mask), and 2 (aerosol optical properties). We discussed the application of LPP for two case studies for Sao Paulo and Amazon, which shows the capabilities of the current release but also highlights the need for new features. From this exercise, we developed and presented a roadmap to guide future development, accommodating the needs of our community.
{"title":"Collaborative development of the Lidar Processing Pipeline (LPP)","authors":"Juan V. Pallotta, Silvania Carvalho, Fabio J. S. Lopes, Alexandre Cacheffo, Eduardo Landulfo, Henrique M. J. Barbosa","doi":"10.5194/gi-2022-19","DOIUrl":"https://doi.org/10.5194/gi-2022-19","url":null,"abstract":"<strong>Abstract.</strong> Lidars can simultaneously measure clouds and aerosols with high temporal and spatial resolution and hence help understand their interactions, which are the source of the largest uncertainties in current climate projections. However, lidars are typically custom-built, so there are significant differences between them. In this sense, lidar networks play a crucial role as they coordinate the efforts of different groups, providing the guidelines for quality-assured routine measurements aiming to homogenize the physical retrievals. With that in mind, this work describes an ongoing effort to develop a lidar processing pipeline (LPP) collaboratively. The LPP is a collection of tools developed in C/C++, python, and Linux script that handle all the steps of a typical lidar analysis. The first publicly released version of LPP produces data files at levels 0 (raw and metadata), 1 (averaging and layer-mask), and 2 (aerosol optical properties). We discussed the application of LPP for two case studies for Sao Paulo and Amazon, which shows the capabilities of the current release but also highlights the need for new features. From this exercise, we developed and presented a roadmap to guide future development, accommodating the needs of our community.","PeriodicalId":48742,"journal":{"name":"Geoscientific Instrumentation Methods and Data Systems","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138538552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Brogi, H. Bogena, M. Köhli, J. Huisman, H. Hendricks Franssen, Olga Dombrowski
Abstract. Accurate soil moisture (SM) monitoring is key in irrigation as it can greatly improve water use efficiency. Recently, cosmic-ray neutron sensors (CRNSs) have been recognized as a promising tool in SM monitoring due to their large footprint of several hectares. CRNSs also have great potential for irrigation applications, but few studies have investigated whether irrigation monitoring with CRNSs is feasible, especially for irrigated fields with a size smaller than the CRNS footprint. Therefore, the aim of this study is to use Monte Carlo simulations to investigate the feasibility of monitoring irrigation with CRNSs. This was achieved by simulating irrigation scenarios with different field dimensions (from 0.5 to 8 ha) and SM variations between 0.05 and 0.50 cm3 cm−3. Moreover, the energy-dependent response functions of eight moderators with different high-density polyethylene (HDPE) thickness or additional gadolinium thermal shielding were investigated. It was found that a considerable part of the neutrons that contribute to the CRNS footprint can originate outside an irrigated field, which is a challenge for irrigation monitoring with CRNSs. The use of thin HDPE moderators (e.g. 5 mm) generally resulted in a smaller footprint and thus stronger contributions from the irrigated area. However, a thicker 25 mm HDPE moderator with gadolinium shielding improved SM monitoring in irrigated fields due to a higher sensitivity of neutron counts with changing SM. This moderator and shielding set-up provided the highest chance of detecting irrigation events, especially when the initial SM was relatively low. However, variations in SM outside a 0.5 or 1 ha irrigated field (e.g. due to irrigation of neighbouring fields) can affect the count rate more than SM variations due to irrigation. This suggests the importance of retrieving SM data from the surrounding of a target field to obtain more meaningful information for supporting irrigation management, especially for small irrigated fields.
{"title":"Feasibility of irrigation monitoring with cosmic-ray neutron sensors","authors":"C. Brogi, H. Bogena, M. Köhli, J. Huisman, H. Hendricks Franssen, Olga Dombrowski","doi":"10.5194/gi-11-451-2022","DOIUrl":"https://doi.org/10.5194/gi-11-451-2022","url":null,"abstract":"Abstract. Accurate soil moisture (SM) monitoring is key in\u0000irrigation as it can greatly improve water use efficiency. Recently,\u0000cosmic-ray neutron sensors (CRNSs) have been recognized as a promising tool\u0000in SM monitoring due to their large footprint of several hectares. CRNSs also\u0000have great potential for irrigation applications, but few studies have\u0000investigated whether irrigation monitoring with CRNSs is feasible, especially\u0000for irrigated fields with a size smaller than the CRNS footprint. Therefore,\u0000the aim of this study is to use Monte Carlo simulations to investigate the\u0000feasibility of monitoring irrigation with CRNSs. This was achieved by\u0000simulating irrigation scenarios with different field dimensions (from 0.5\u0000to 8 ha) and SM variations between 0.05 and 0.50 cm3 cm−3.\u0000Moreover, the energy-dependent response functions of eight moderators with\u0000different high-density polyethylene (HDPE) thickness or additional\u0000gadolinium thermal shielding were investigated. It was found that a\u0000considerable part of the neutrons that contribute to the CRNS footprint can\u0000originate outside an irrigated field, which is a challenge for irrigation\u0000monitoring with CRNSs. The use of thin HDPE moderators (e.g. 5 mm) generally\u0000resulted in a smaller footprint and thus stronger contributions from the\u0000irrigated area. However, a thicker 25 mm HDPE moderator with gadolinium\u0000shielding improved SM monitoring in irrigated fields due to a higher\u0000sensitivity of neutron counts with changing SM. This moderator and shielding\u0000set-up provided the highest chance of detecting irrigation events,\u0000especially when the initial SM was relatively low. However, variations in SM\u0000outside a 0.5 or 1 ha irrigated field (e.g. due to irrigation of\u0000neighbouring fields) can affect the count rate more than SM variations due\u0000to irrigation. This suggests the importance of retrieving SM data from the\u0000surrounding of a target field to obtain more meaningful information for\u0000supporting irrigation management, especially for small irrigated fields.\u0000","PeriodicalId":48742,"journal":{"name":"Geoscientific Instrumentation Methods and Data Systems","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48353085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. Unmanned aerial vehicles (UAVs), affordable precise Global Navigation Satellite System hardware, echo sounders, open-source 3D hydrodynamic modelling software, and freely available satellite data have opened up opportunities for a robust, affordable, physics-based approach to monitor river flows. In short, the hardware can be used to produce the geometry. 3D hydrodynamic modelling offers a framework to establish relationships between river flow and state variables such as width and depth, while satellite images with surface water detection methods or altimetry records can be used to operationally monitor flows through the established rating curve. Uncertainties in the data acquisition may propagate into uncertainties in the relationships found between discharge and state variables. Variations in acquired geometry emanate from the different ground control point (GCP) densities and distributions which are used during photogrammetry-based terrain reconstruction. In this study, we develop a rating curve using affordable data collection methods and basic principles of physics. The specific objectives were to: determine how the rating curve based on a 3D hydraulic model compares with conventional methods; investigate the impact of geometry uncertainty on estimated discharge when applied in a hydraulic model; and investigate how uncertainties in continuous observations of depth and width from satellite platforms propagate into uncertainties in river flow estimates using the rating curves obtained. The study shows comparable results between the 3D and traditional river rating discharge estimations. The rating curve derived on the basis of 3D hydraulic modelling was within a 95 % confidence interval of the traditional gauging based rating curve. The physics-based estimation requires determination of the roughness coefficient within the permanent bed and the floodplain using field observation as both the end of dry and wet season. Furthermore, the study demonstrates that variations in the density of GCPs beyond an optimal number (9) has no significant influence on the resultant rating relationships. Finally, the study observes that it depends on the magnitude of the flow which state variable approximation (water level & river width) is most promising to use. Combining stage appropriate proxies (water level when the floodplain is entirely filled, and width when the floodplain is filling) in data limited environments yields more accurate discharge estimations. The study was able to successfully apply low cost technologies for accurate river monitoring through hydraulic modelling. In future studies, a larger amount of in-situ gauge readings may be considered so as to optimise the validation process.
{"title":"Towards Affordable 3D Physics-Based River Flow Rating: Application Over Luangwa River Basin","authors":"Hubert T. Samboko, Sten Schurer, Hubert H.G. Savenije, Hodson Makurira, Kawawa Banda, Hessel Winsemius","doi":"10.5194/gi-2022-21","DOIUrl":"https://doi.org/10.5194/gi-2022-21","url":null,"abstract":"<strong>Abstract.</strong> Unmanned aerial vehicles (UAVs), affordable precise Global Navigation Satellite System hardware, echo sounders, open-source 3D hydrodynamic modelling software, and freely available satellite data have opened up opportunities for a robust, affordable, physics-based approach to monitor river flows. In short, the hardware can be used to produce the geometry. 3D hydrodynamic modelling offers a framework to establish relationships between river flow and state variables such as width and depth, while satellite images with surface water detection methods or altimetry records can be used to operationally monitor flows through the established rating curve. Uncertainties in the data acquisition may propagate into uncertainties in the relationships found between discharge and state variables. Variations in acquired geometry emanate from the different ground control point (GCP) densities and distributions which are used during photogrammetry-based terrain reconstruction. In this study, we develop a rating curve using affordable data collection methods and basic principles of physics. The specific objectives were to: determine how the rating curve based on a 3D hydraulic model compares with conventional methods; investigate the impact of geometry uncertainty on estimated discharge when applied in a hydraulic model; and investigate how uncertainties in continuous observations of depth and width from satellite platforms propagate into uncertainties in river flow estimates using the rating curves obtained. The study shows comparable results between the 3D and traditional river rating discharge estimations. The rating curve derived on the basis of 3D hydraulic modelling was within a 95 % confidence interval of the traditional gauging based rating curve. The physics-based estimation requires determination of the roughness coefficient within the permanent bed and the floodplain using field observation as both the end of dry and wet season. Furthermore, the study demonstrates that variations in the density of GCPs beyond an optimal number (9) has no significant influence on the resultant rating relationships. Finally, the study observes that it depends on the magnitude of the flow which state variable approximation (water level & river width) is most promising to use. Combining stage appropriate proxies (water level when the floodplain is entirely filled, and width when the floodplain is filling) in data limited environments yields more accurate discharge estimations. The study was able to successfully apply low cost technologies for accurate river monitoring through hydraulic modelling. In future studies, a larger amount of in-situ gauge readings may be considered so as to optimise the validation process.","PeriodicalId":48742,"journal":{"name":"Geoscientific Instrumentation Methods and Data Systems","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138538565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. Drone-borne controlled-source electromagnetic (CSEM) systems combine the mobility of airborne systems with the high subsurface resolution in ground systems. As such, drone-borne systems are beneficial at sites with poor accessibility and in areas where high resolution is needed, e.g. for archaeological or subsurface pollution investigations. However, drone-borne CSEM systems are associated with challenges, which are not observed to the same degree in airborne or ground surveys. In this paper, we explore some of these challenges based on an example of a new drone-towed CSEM system. The system deploys a multi-frequency broadband electromagnetic sensor (GEM-2 uncrewed aerial vehicle, UAV), which is towed 6 m below a drone in a towing-bird configuration together with a NovAtel GNSS–IMU (global navigation satellite system–inertial measurement unit) unit, enabling centimetre-level position precision and orientation. The results of a number of controlled tests of the system are presented together with data from an initial survey at Falster (Denmark), including temperature drift, altitude vs. signal, survey mode signal dependency, and the effect of frequency choice on noise. The test results reveal the most critical issues for our system and issues that are likely encountered in similar drone-towed CSEM set-ups. We find that small altitude variations (± 0.5 m) along our flight paths drastically change the signal, and a local height vs. signal correlation is needed to correct near-surface drone-towed CSEM data. The highest measured impact was −46.2 ppm cm−1 for a transmission frequency of 91 kHz. We also observe a significant increase in the standard deviation of the noise level up to 500 % when going from one transmission frequency to five. We recommend not to use more than three transmission frequencies, and the lowest transmission frequencies should be as high as the application allows it. Finally, we find a strong temperature dependency (up to 32.2 ppm∘C-1), which is not accounted for in the instrumentation.
{"title":"Drone-towed controlled-source electromagnetic (CSEM) system for near-surface geophysical prospecting: on instrument noise, temperature drift, transmission frequency, and survey set-up","authors":"Tobias Bjerg Vilhelmsen, A. Døssing","doi":"10.5194/gi-11-435-2022","DOIUrl":"https://doi.org/10.5194/gi-11-435-2022","url":null,"abstract":"Abstract. Drone-borne controlled-source electromagnetic (CSEM) systems combine the mobility of airborne systems with the high subsurface resolution in ground\u0000systems. As such, drone-borne systems are beneficial at sites with poor accessibility and in areas where high resolution is needed, e.g. for\u0000archaeological or subsurface pollution investigations. However, drone-borne CSEM systems are associated with challenges, which are not observed to\u0000the same degree in airborne or ground surveys. In this paper, we explore some of these challenges based on an example of a new drone-towed CSEM\u0000system. The system deploys a multi-frequency broadband electromagnetic sensor (GEM-2 uncrewed aerial vehicle, UAV), which is towed 6 m below a drone in a towing-bird\u0000configuration together with a NovAtel GNSS–IMU (global navigation satellite system–inertial measurement unit) unit, enabling centimetre-level position precision and orientation. The results of a number of\u0000controlled tests of the system are presented together with data from an initial survey at Falster (Denmark), including temperature drift, altitude\u0000vs. signal, survey mode signal dependency, and the effect of frequency choice on noise. The test results reveal the most critical issues for our\u0000system and issues that are likely encountered in similar drone-towed CSEM set-ups. We find that small altitude variations (± 0.5 m)\u0000along our flight paths drastically change the signal, and a local height vs. signal correlation is needed to correct near-surface drone-towed CSEM\u0000data. The highest measured impact was −46.2 ppm cm−1 for a transmission frequency of 91 kHz. We also observe a significant increase in the\u0000standard deviation of the noise level up to 500 % when going from one transmission frequency to five. We recommend not to use more than three\u0000transmission frequencies, and the lowest transmission frequencies should be as high as the application allows it. Finally, we find a strong\u0000temperature dependency (up to 32.2 ppm∘C-1), which is not accounted for in\u0000the instrumentation.\u0000","PeriodicalId":48742,"journal":{"name":"Geoscientific Instrumentation Methods and Data Systems","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42864377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Maximilian Weigand, Egon Zimmermann, Valentin Michels, Johan Alexander Huisman, Andreas Kemna
Spectral electrical impedance tomography (sEIT) is increasingly used to characterise the structure of subsurface systems using measurements in the megahertz to kilohertz range. Additionally, hydrogeophysical and biogeophysical processes are characterised and monitored using sEIT. The method combines multiple, spatially distributed, spectroscopic measurements with tomographic inversion algorithms to obtain images of the complex electrical resistivity distribution in the subsurface at various frequencies. Spectral polarisation measurements provide additional information about the systems under investigation and can be used to reduce ambiguities that occur if only the in-phase resistivity values are analysed. However, spectral impedance measurements are very sensitive to details of the measurement setup as well as to external noise and error components. Despite promising technical progress in improving measurement quality as well as progress in the characterisation and understanding of static polarisation signatures of the subsurface, long-term (i.e. multi-month to multi-year) monitoring attempts with fixed setups are still rare. Yet, measurement targets often show inherent non-stationarity that would require monitoring for a proper system characterisation. With the aim of improving operating foundations for similar endeavours, we here report on the design and field deployment of a permanently installed monitoring system for sEIT data. The specific aim of this monitoring installation is the characterisation of crop root evolution over a full growing season, requiring multiple measurements per day over multiple months to capture relevant system dynamics. In this contribution, we discuss the general layout and design of the monitoring setup, including the data acquisition system, additional on-site equipment, required corrections to improve data quality for high frequencies, data management and remote-processing facilities used to analyse the measured data. The choice and installation of electrodes, cables and measurement configurations are discussed and quality parameters are used for the continuous assessment of system functioning and data quality. Exemplary analysis results of the first season of operation highlight the importance of continuous quality control. It is also found that proper cable elevation decreased capacitive leakage currents and in combination with the correction of inductive effects led to consistent tomographic results up to 1 kHz measurement frequency. Overall, the successful operation of an sEIT monitoring system over multiple months with multiple daily tomographic measurements was achieved.
{"title":"Design and operation of a long-term monitoring system for spectral electrical impedance tomography (sEIT)","authors":"Maximilian Weigand, Egon Zimmermann, Valentin Michels, Johan Alexander Huisman, Andreas Kemna","doi":"10.5194/gi-11-413-2022","DOIUrl":"https://doi.org/10.5194/gi-11-413-2022","url":null,"abstract":"Spectral electrical impedance tomography (sEIT) is increasingly used to\u0000characterise the structure of subsurface systems using measurements in the megahertz to kilohertz range.\u0000Additionally, hydrogeophysical and biogeophysical processes are characterised and\u0000monitored using sEIT.\u0000The method combines multiple, spatially distributed, spectroscopic measurements\u0000with tomographic inversion algorithms to obtain images of the complex\u0000electrical resistivity distribution in the subsurface at various frequencies.\u0000Spectral polarisation measurements provide additional information about the\u0000systems under investigation and can be used to reduce ambiguities that occur\u0000if only the in-phase resistivity values are analysed.\u0000However, spectral impedance measurements are very sensitive\u0000to details of the measurement setup as well as to external noise and error\u0000components.\u0000Despite promising technical progress in improving measurement quality as well\u0000as progress in the characterisation and understanding of static\u0000polarisation signatures of the subsurface, long-term (i.e. multi-month to\u0000multi-year) monitoring attempts with fixed setups are still rare.\u0000Yet, measurement targets often show inherent non-stationarity that would\u0000require monitoring for a proper system characterisation.\u0000With the aim of improving operating foundations for similar endeavours, we here\u0000report on the design and field deployment of a permanently installed monitoring\u0000system for sEIT data.\u0000The specific aim of this monitoring installation is the characterisation of\u0000crop root evolution over a full growing season, requiring multiple measurements\u0000per day over multiple months to capture relevant system dynamics.\u0000In this contribution, we discuss the general layout and design of the\u0000monitoring setup, including the data acquisition system, additional on-site\u0000equipment, required corrections to improve data quality for high frequencies,\u0000data management and remote-processing facilities used to analyse the measured\u0000data.\u0000The choice and installation of electrodes, cables and measurement\u0000configurations are discussed and quality parameters are used for the\u0000continuous assessment of system functioning and data quality.\u0000Exemplary analysis results of the first season of operation highlight the\u0000importance of continuous quality control.\u0000It is also found that proper cable elevation decreased capacitive leakage currents\u0000and in combination with the correction of inductive effects led to\u0000consistent tomographic results up to 1 kHz measurement frequency.\u0000Overall, the successful operation of an sEIT monitoring system over multiple\u0000months with multiple daily tomographic measurements was achieved.","PeriodicalId":48742,"journal":{"name":"Geoscientific Instrumentation Methods and Data Systems","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138538547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Juncu, X. Ceamanos, I. Trigo, S. Gomes, Sandra C. Freitas
Abstract. MDAL is the operational Meteosat Second Generation (MSG)-derived daily surface albedo product that has been generated and disseminated in near real time by EUMETSAT Satellite Application Facility for Land Surface Analysis (LSA-SAF) since 2005. We propose and evaluate an update to the MDAL retrieval algorithm which introduces the accounting for aerosol effects as well as other scientific developments: pre-processing recalibration of radiances acquired by the SEVIRI instrument aboard MSG and improved coefficients for atmospheric correction as well as for albedo conversion from narrow- to broadband. We compare the performance of MDAL broadband albedos pre- and post-upgrade with respect to three types of reference data: the EPS Ten-Day Albedo product ETAL is used as the primary reference, while albedo derived from in situ flux measurements acquired by ground stations and MODIS MCD43D albedo data are used to complete the validation. For the comparison to ETAL – conducted over the whole coverage area of SEVIRI – we see a reduction in average white-sky albedo mean bias error (MBE) from −0.02 to negligible levels (<0.001) and a reduction in average mean absolute error (MAE) from 0.034 to 0.026 (−24 %). Improvements can be seen for black-sky albedo as well, albeit less pronounced (14 % reduction in MAE). Further analysis distinguishing individual seasons, regions and land covers show that performance changes have spatial and temporal dependence: for white-sky albedo we see improvements over almost all regions and seasons relative to ETAL, except for Eurasia in winter; resolved by land cover we see a similar effect with improvements for all types for all seasons except winter, where some types exhibit slightly worse results (crop-, grass- and shrublands). For black-sky albedo we similarly see improvements for all seasons when averaged over the full data set, although sub-regions exhibit clear seasonal dependence: the performance of the upgraded MDAL version is generally diminished in local winter but better in local summer. The comparison with in situ observations is less conclusive due to the well-known problem of the spatial representativeness of near-ground observations with respect to satellite pixel footprint sizes. Comparison with MODIS at the same locations shows mixed results in terms of change in performance following the proposed upgrade but proves the good quality of the MDAL products in general. Based on the evidence presented in this study, we consider the updated algorithm version to be able to deliver a valuable improvement of the operational MDAL product. This improvement is two-fold: primarily, there is the refinement of the albedo values themselves; secondarily, the increased alignment with the ETAL product is beneficial for those who wish to exploit synergies between EUMETSAT's geostationary and polar satellites to generate data sets based on the LSA-SAF albedo products from the two different missions.
{"title":"Upgrade of LSA-SAF Meteosat Second Generation daily surface albedo (MDAL) retrieval algorithm incorporating aerosol correction and other improvements","authors":"D. Juncu, X. Ceamanos, I. Trigo, S. Gomes, Sandra C. Freitas","doi":"10.5194/gi-11-389-2022","DOIUrl":"https://doi.org/10.5194/gi-11-389-2022","url":null,"abstract":"Abstract. MDAL is the operational Meteosat Second Generation (MSG)-derived daily surface albedo product that has been generated and disseminated in near real time by EUMETSAT Satellite Application Facility for Land Surface Analysis (LSA-SAF) since 2005. We propose and evaluate an update to the MDAL retrieval algorithm which introduces the accounting for aerosol effects as well as other scientific developments: pre-processing recalibration of radiances acquired by the SEVIRI instrument aboard MSG and improved coefficients for atmospheric correction as well as for albedo conversion from narrow- to broadband. We compare the performance of MDAL broadband albedos pre- and post-upgrade with respect to three types of reference data: the EPS Ten-Day Albedo product ETAL is used as the primary reference, while albedo derived from in situ flux measurements acquired by ground stations and MODIS MCD43D albedo data are used to complete the validation. For the comparison to ETAL – conducted over the whole coverage area of SEVIRI – we see a reduction in average white-sky albedo mean bias error (MBE) from −0.02 to negligible levels (<0.001) and a reduction in average mean absolute error (MAE) from 0.034 to 0.026 (−24 %). Improvements can be seen for black-sky albedo as well, albeit less pronounced (14 % reduction in MAE). Further analysis distinguishing individual seasons, regions and land covers show that performance changes have spatial and temporal dependence: for white-sky albedo we see improvements over almost all regions and seasons relative to ETAL, except for Eurasia in winter; resolved by land cover we see a similar effect with improvements for all types for all seasons except winter, where some types exhibit slightly worse results (crop-, grass- and shrublands). For black-sky albedo we similarly see improvements for all seasons when averaged over the full data set, although sub-regions exhibit clear seasonal dependence: the performance of the upgraded MDAL version is generally diminished in local winter but better in local summer. The comparison with in situ observations is less conclusive due to the well-known problem of the spatial representativeness of near-ground observations with respect to satellite pixel footprint sizes. Comparison with MODIS at the same locations shows mixed results in terms of change in performance following the proposed upgrade but proves the good quality of the MDAL products in general. Based on the evidence presented in this study, we consider the updated algorithm version to be able to deliver a valuable improvement of the operational MDAL product. This improvement is two-fold: primarily, there is the refinement of the albedo values themselves; secondarily, the increased alignment with the ETAL product is beneficial for those who wish to exploit synergies between EUMETSAT's geostationary and polar satellites to generate data sets based on the LSA-SAF albedo products from the two different missions.\u0000","PeriodicalId":48742,"journal":{"name":"Geoscientific Instrumentation Methods and Data Systems","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47797494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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