Bias-Corrected RADARSAT-2 Soil Moisture Dynamics Reveal Discharge Hysteresis at An Agricultural Watershed
Satellites are designed to monitor geospatial data over large areas at a catchment scale. However, most of satellite validation works are conducted at local point scales with a lack of spatial representativeness. Although upscaling them with a spatial average of several point data collected in the f...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/10/2677 |
| _version_ | 1797598447902130176 |
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| author | Ju Hyoung Lee Karl-Erich Lindenschmidt |
| author_facet | Ju Hyoung Lee Karl-Erich Lindenschmidt |
| author_sort | Ju Hyoung Lee |
| collection | DOAJ |
| description | Satellites are designed to monitor geospatial data over large areas at a catchment scale. However, most of satellite validation works are conducted at local point scales with a lack of spatial representativeness. Although upscaling them with a spatial average of several point data collected in the field, it is almost impossible to reorganize backscattering responses at pixel scales. Considering the influence of soil storage on watershed streamflow, we thus suggested watershed-scale hydrological validation. In addition, to overcome the limitations of backscattering models that are widely used for C-band Synthetic Aperture Radar (SAR) soil moisture but applied to bare soils only, in this study, RADARSAT-2 soil moisture was stochastically retrieved to correct vegetation effects arising from agricultural lands. Roughness-corrected soil moisture retrievals were assessed at various spatial scales over the Brightwater Creek basin (land cover: crop lands, gross drainage area: 1540 km<sup>2</sup>) in Saskatchewan, Canada. At the point scale, local station data showed that the Root Mean Square Errors (RMSEs), Unbiased RMSEs (ubRMSEs) and biases of Radarsat-2 were 0.06~0.09 m<sup>3</sup>/m<sup>3</sup>, 0.04~0.08 m<sup>3</sup>/m<sup>3</sup> and 0.01~0.05 m<sup>3</sup>/m<sup>3</sup>, respectively, while 1 km Soil Moisture Active Passive (SMAP) showed underestimation at RMSEs of 0.1~0.22 m<sup>3</sup>/m<sup>3</sup> and biases of −0.036~−0.2080 m<sup>3</sup>/m<sup>3</sup>. Although SMAP soil moisture better distinguished the contributing area at the catchment scale, Radarsat-2 soil moisture showed a better discharge hysteresis. A reliable estimation of the soil storage dynamics is more important for discharge forecasting than a static classification of contributing and noncontributing areas. |
| first_indexed | 2024-03-11T03:21:22Z |
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| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T03:21:22Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-5604dc25689b4a3a94662a47020bc0292023-11-18T03:08:35ZengMDPI AGRemote Sensing2072-42922023-05-011510267710.3390/rs15102677Bias-Corrected RADARSAT-2 Soil Moisture Dynamics Reveal Discharge Hysteresis at An Agricultural WatershedJu Hyoung Lee0Karl-Erich Lindenschmidt1Department of Geography, Environment & Geomatics, University of Guelph, 50 Stone Rd E, Guelph, ON N1G 2W1, CanadaGlobal Institute for Water Security, School of Environment and Sustainability, University of Saskatchewan, 11 Innovation Boulevard, Saskatoon, SK S7N 3H5, CanadaSatellites are designed to monitor geospatial data over large areas at a catchment scale. However, most of satellite validation works are conducted at local point scales with a lack of spatial representativeness. Although upscaling them with a spatial average of several point data collected in the field, it is almost impossible to reorganize backscattering responses at pixel scales. Considering the influence of soil storage on watershed streamflow, we thus suggested watershed-scale hydrological validation. In addition, to overcome the limitations of backscattering models that are widely used for C-band Synthetic Aperture Radar (SAR) soil moisture but applied to bare soils only, in this study, RADARSAT-2 soil moisture was stochastically retrieved to correct vegetation effects arising from agricultural lands. Roughness-corrected soil moisture retrievals were assessed at various spatial scales over the Brightwater Creek basin (land cover: crop lands, gross drainage area: 1540 km<sup>2</sup>) in Saskatchewan, Canada. At the point scale, local station data showed that the Root Mean Square Errors (RMSEs), Unbiased RMSEs (ubRMSEs) and biases of Radarsat-2 were 0.06~0.09 m<sup>3</sup>/m<sup>3</sup>, 0.04~0.08 m<sup>3</sup>/m<sup>3</sup> and 0.01~0.05 m<sup>3</sup>/m<sup>3</sup>, respectively, while 1 km Soil Moisture Active Passive (SMAP) showed underestimation at RMSEs of 0.1~0.22 m<sup>3</sup>/m<sup>3</sup> and biases of −0.036~−0.2080 m<sup>3</sup>/m<sup>3</sup>. Although SMAP soil moisture better distinguished the contributing area at the catchment scale, Radarsat-2 soil moisture showed a better discharge hysteresis. A reliable estimation of the soil storage dynamics is more important for discharge forecasting than a static classification of contributing and noncontributing areas.https://www.mdpi.com/2072-4292/15/10/2677soil moistureRADARSAT-2SMAPstochastic retrievalsbias correction |
| spellingShingle | Ju Hyoung Lee Karl-Erich Lindenschmidt Bias-Corrected RADARSAT-2 Soil Moisture Dynamics Reveal Discharge Hysteresis at An Agricultural Watershed Remote Sensing soil moisture RADARSAT-2 SMAP stochastic retrievals bias correction |
| title | Bias-Corrected RADARSAT-2 Soil Moisture Dynamics Reveal Discharge Hysteresis at An Agricultural Watershed |
| title_full | Bias-Corrected RADARSAT-2 Soil Moisture Dynamics Reveal Discharge Hysteresis at An Agricultural Watershed |
| title_fullStr | Bias-Corrected RADARSAT-2 Soil Moisture Dynamics Reveal Discharge Hysteresis at An Agricultural Watershed |
| title_full_unstemmed | Bias-Corrected RADARSAT-2 Soil Moisture Dynamics Reveal Discharge Hysteresis at An Agricultural Watershed |
| title_short | Bias-Corrected RADARSAT-2 Soil Moisture Dynamics Reveal Discharge Hysteresis at An Agricultural Watershed |
| title_sort | bias corrected radarsat 2 soil moisture dynamics reveal discharge hysteresis at an agricultural watershed |
| topic | soil moisture RADARSAT-2 SMAP stochastic retrievals bias correction |
| url | https://www.mdpi.com/2072-4292/15/10/2677 |
| work_keys_str_mv | AT juhyounglee biascorrectedradarsat2soilmoisturedynamicsrevealdischargehysteresisatanagriculturalwatershed AT karlerichlindenschmidt biascorrectedradarsat2soilmoisturedynamicsrevealdischargehysteresisatanagriculturalwatershed |