Location: Hydrology and Remote Sensing Laboratory
Publications
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A global flash drought inventory based on soil moisture volatility
- (Peer Reviewed Journal)
Osman, M., Zaitchik, B.F., Otkin, J., Anderson, M.C. 2024. A global flash drought inventory based on soil moisture volatility. Nature Scientific Reports. 11/965. https://doi.org/10.1038/s41597-024-03809-9.
USDA LTAR Common Experiment measurement: Soil water content
- (Research Notes)
Correction of thin cirrus absorption effects in Landsat 8 TIRS Images using the OLI cirrus band on the same satellite platform
- (Peer Reviewed Journal)
Gao, B., Li, R., Yang, Y., Anderson, M.C. 2024. Correction of thin cirrus absorption effects in Landsat 8 TIRS Images using the OLI cirrus band on the same satellite platform. Sensors. 24/4697. https://doi.org/10.3390/s24144697.
The utility and applicability of vegetation index based models for the spatial disaggregation of evapotranspiration
- (Peer Reviewed Journal)
Munusamy, S., Rajasekjaran, E., Saraswat, D., Kustas, W.P., Bambach, N., Mcelrone, A., Castro, S.J., Prueger, J.H., Alfieri, J.G., Alsina, M.M. (2024) The utility and applicability of vegetation index based models for the spatial disaggregation of evapotranspiration. Irrigation Science. https://doi.org/10.1007/s00271-024-00963-1.
High-throughput physiological phenotyping of crop evapotranspiration at the plot scale
- (Peer Reviewed Journal)
Status of the National Coordinated Soil Moisture Monitoring Network: Updates for 2024
- (Abstract Only)
Calculating a Minimum Overlap Period for Successful Intercalibration of Soil Moisture Sensors
- (Abstract Only)
Global soil moisture from combined active and passive microwave observations: integrating ASCAT and SMAP observations based on machine learning approaches
- (Peer Reviewed Journal)
Ma, H., Zeng, J., Wigneron, J., Li, X., Fu, P., Kolassa, J., Cosh, M.H. 2024. Global soil moisture from combined active and passive microwave observations: integrating ASCAT and SMAP observations based on machine learning approaches. Remote Sensing of Environment. 308:114197. https://doi.org/10.1016/j.rse.2024.114197.
Remote sensing of drought: satellite-based monitoring tools for the United States
- (Book / Chapter)
Spatial calibration and uncertainty reduction of the SWAT model using multiple remotely sensed data
- (Peer Reviewed Journal)
Lee, S., Kim, D., McCarty, G.W., Anderson, M.C., Gao, F.N., Lei, F., Moglen, G.E., Zhang, X., Yen, H., Qi, Y., Crow, W.T., Yeo, I.Y., Sun, L. 2024. Spatial calibration and uncertainty reduction of the SWAT model using multiple remotely sensed data. Heliyon. 10(10): Article e30923. https://doi.org/10.1016/j.heliyon.2024.e30923.
Retrieving forest soil moisture from SMAP observations considering a microwave polarization difference index (MPDI) to tau-omega model
- (Peer Reviewed Journal)
Park, C., Colliander, A., Jagdhuber, T., Berg, A., Lee, J., Boo, K., Cosh, M.H. 2024. Retrieving forest soil moisture from SMAP observations considering a microwave polarization difference index (MPDI) to tau-omega model. Remote Sensing of Environment. 9. Article e100131. https://doi.org/10.1016/j.srs.2024.100131.
Evaluating the precise grapevine water stress detection using unmanned aerial vehicles and evapotranspiration-based metrics
- (Peer Reviewed Journal)
Burchard-Levine, V., Nieto, H., Kustas, W.P., Guerra, J., Borra, I., Dorado, J., Mesias-Ruiz, G., McKee, L.G., Pena, J. 2024. Evaluating the precise grapevine water stress detection using unmanned aerial vehicles and evapotranspiration-based metrics. Irrigation Science. https://doi.org/10.1007/s00271-024-00931-9.
Monitoring field scale soil moisture with sUAS mounted L-band radiometer
- (Abstract Only)
Within-field soil moisture variability and time-invariant spatial structures of agricultural fields in the US Midwest
- (Peer Reviewed Journal)
Yang, Y., Peng, B., Guan, K., Pan, M., Franz, T., Cosh, M.H., Bernacchi, C.J. 2024. Within-field soil moisture variability and time-invariant spatial structures of agricultural fields in the US Midwest. Vadose Zone Journal. Article e20337. https://doi.org/10.1002/vzj2.20337.
Soil moisture profiles of ecosystem water use revealed with ECOSTRESS
- (Peer Reviewed Journal)
Feldman, A., Koster, R., Cawse-Nicholson, K., Crow, W.T., Holmes, T., Poutler, B. 2024. Soil moisture profiles of ecosystem water use revealed with ECOSTRESS. Geophysical Research Letters. 51. https://doi.org/10.1029/2024GL108326.
Precision Soil Moisture Monitoring with Passive Microwave L-band UAS Mapping
- (Peer Reviewed Journal)
Kim, K.Y., Zhu, Z., Zhang, R., Fang, B., Cosh, M.H., Russ, A.L., Dai, E., Elston, J., Stachura, M., Gasiewski, A., Lakshmi, V. 2024. Precision Soil Moisture Monitoring with Passive Microwave L-band UAS Mapping. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17:7684-7694. https://doi.org/10.1109/JSTARS.2024.3382045.
A brief history of the thermal IR-based Two-Source Energy Balance (TSEB) model – diagnosing water and energy fluxes from plant to global scales
- (Peer Reviewed Journal)
Anderson, M.C., Kustas, W.P., Norman, J., Diak, G., Hain, C., Gao, F.N., Yang, Y., Knipper, K.R., Xue, J., Yang, Y., Crow, W.T., Holmes, T., Nieto, H., Guzinski, R., Otkin, J., Mecikalski, J., Cammalleri, C., Torres-Rua, A., Zhan, X., Fang, L., Colaizzi, P.D., Agam, N. 2024. A brief history of the thermal IR-based Two-Source Energy Balance (TSEB) model – diagnosing water and energy fluxes from plant to global scales. Agricultural and Forest Meteorology. 350. Article e109951. https://doi.org/10.1016/j.agrformet.2024.109951.
County-level evaluation of large-scale gridded datasets of irrigated area over China
- (Peer Reviewed Journal)
Tian, X., Dong, J., Chen, X., Zhou, J., Gao, M., Wei, L., Kang, X., Zhao, D., Zhang, H., Crow, W.T. 2024. County-level evaluation of large-scale gridded datasets of irrigated area over China. Journal of Geophysical Research Atmospheres. Article e2024GL108326. https://doi.org/10.1029/2024GL108326.
Advancements in dielectric soil moisture sensor Calibration: A comprehensive review of methods and techniques
- (Peer Reviewed Journal)
Mane, S., Das, N., Singh, G., Cosh, M.H., Dong, Y. 2024. Advancements in dielectric soil moisture sensor Calibration: A comprehensive review of methods and techniques. Computers and Electronics in Agriculture. 218. Article e 108686. https://doi.org/10.1016/j.compag.2024.108686.
Neglect of potential seasonal streamflow forecasting skill in the United States national water model
- (Peer Reviewed Journal)
Crow, W.T., Koster, R., Reichle, R., Chen, F., Liu, Q. 2024. Neglect of potential seasonal streamflow forecasting skill in the United States national water model. Geophysical Research Letters. 51. https://doi.org/10.1029/2023GL105649.
Estimating hydrological regimes from observational soil moisture, evapotranspiration, and air temperature data
- (Peer Reviewed Journal)
Koster, R., Feldman, A., Holmes, T., Anderson, M.C., Crow, W.T., Hain, C. 2024. Estimating hydrological regimes from observational soil moisture, evapotranspiration, and air temperature data. Journal of Hydrometeorology. 25(3):495-513. https://doi.org/10.1175/JHM-D-23-0140.1.
Developmental framework for a desktop hydrogeomorphic wetland functional assessment derived from field-based data
- (Peer Reviewed Journal)
Backhaus, P., Wardrop, D., Mccarty, G.W., Brooks, R. 2024. Developmental framework for a desktop hydrogeomorphic wetland functional assessment derived from field-based data. Methods in Ecology and Evolution. 196: Article e217. https://doi.org/10.1007/s10661-024-12373-z.
Photosynthetically active radiation separation model for high-latitude regions in agrivoltaic systems modeling
- (Peer Reviewed Journal)
Ma Lu, S., Yang, D., Anderson, M.C., Zainali, S., Stridh, B., Avelin, A., Campana, P. 2024. Photosynthetically active radiation separation model for high-latitude regions in agrivoltaic systems modeling. Solar Energy. 16(1). Article e0181311. https://doi.org/10.1063/5.0181311.
Good practices for land product validation
- (Abstract Only)
Soil Moisture Volatility Index (SMVI) global flash droughts
- (Database / Dataset)
Development of a gridded yield data archive for farm management and research at the USDA Beltsville Agricultural Research Center
- (Peer Reviewed Journal)
Dulaney, W.P., Anderson, M.C., Gao, F.N., Stern, A.J., Meyers, G.E., Daughtry, C.S., White, W.A., Akumaga, U., Showalter, J.J., Moglen, G.E. 2024. Development of a gridded yield data archive for farm management and research at the USDA Beltsville Agricultural Research Center. Agrosystems, Geosciences & Environment. 7(1). Article e20474. https://doi.org/10.1002/agg2.20474.
First mapping of polarization-dependent vegetation optical depth and soil moisture from SMAP L-band radiometry
- (Peer Reviewed Journal)
Peng, Z., Zhao, T., Shi, J.C., Hu, L., Rodriguez-Fernandez, N., Wigneron, J., Jackson, T.J., Walker, J., Cosh, M.H., Yang, K., Lu, H., Bai, Y., Yao, P., Zheng, J., Wei, Z. 2023. First mapping of polarization-dependent vegetation optical depth and soil moisture from SMAP L-band radiometry. IEEE Transactions on Geoscience and Remote Sensing. 302. Article e113970. https://doi.org/10.1016/j.rse.2023.113970.
Inter-basin water transfer compensates for unsustainable water use in the North China Plain
- (Peer Reviewed Journal)
Dong, J., Li, Y., Wei, L., Tangdamrongsub, N., Crow, W.T., Chen, X. 2023. Inter-basin water transfer compensates for unsustainable water use in the North China Plain. Nature Climate Change. Article e2023WR035129. https://doi.org/10.1029/2023WR035129.
Forming the future of agrohydrology research
- (Peer Reviewed Journal)
Smidt, S., Haaker, E., Bai, X., Cherkauer, K., Choat, B., Crompton, O.V., Deines, J., Groh, J., Guzman, S., Hartman, K., Kenall, A., Khan, S., Kustas, W.P., McGill, B.M., Nocco, M.A., Pensky, J., Rapp, J., Schreiner-McGraw, A.P., Simmons, T., Sprenger, M., Wan, L., Weldegebriel, L., Zipper, S., Zoccatelli, D. 2023. Forming the future of agrohydrology research. Earth's Future. https://doi.org/10.1029/2022EF003410.
Spatial estimation of actual evapotranspiration over irrigated turfgrass using sUAS thermal and multispectral imagery and TSEB model
- (Peer Reviewed Journal)
Meza, K., Torres, A., Hipps, L.E., Kustas, W.P., Gao, R., Christianse, L., Kopp, K., Nieto, H., Burchard-Levine, V., Martin, M., Coopmans, C., Gowing, I. 2023. Spatial estimation of actual evapotranspiration over irrigated turfgrass using sUAS thermal and multispectral imagery and TSEB model. Irrigation Science. https://doi.org/10.1007/s00271-023-00899-y.
Multivariate calibration of an ecohydrological model using spatial patterns of remote sensing-derived land surface temperature
- (Peer Reviewed Journal)
Duethmann, D., Anderson, M.C., Maneta, M., Tetzlaff, D. 2023. Multivariate calibration of an ecohydrological model using spatial patterns of remote sensing-derived land surface temperature. Hydrological Processes. 628. Article e130433. https://doi.org/10.1016/j.jhydrol.2023.130433.
Interpreting effective hydrologic depth estimates derived from soil moisture remote sensing: A Bayesian non-linear modelling approach
- (Peer Reviewed Journal)
Hyunglok, K., Crow, W.T. 2023. Interpreting effective hydrologic depth estimates derived from soil moisture remote sensing: A Bayesian non-linear modelling approach. Remote Sensing of Environment. 908. https://doi.org/10.1016/j.scitotenv.2023.168067.
Validating NISAR’s cropland mapping approach and the USDA/NASS Cropland Data Layer against ground truth data in a fragmented urban agricultural region
- (Peer Reviewed Journal)
Kraatz, S.G., Lamb, B.T., Hively, W.D., Jennewein, J.S., Gao, F.N., Cosh, M.H., Siqueira, P. 2023. Validating NISAR’s cropland mapping approach and the USDA/NASS Cropland Data Layer against ground truth data in a fragmented urban agricultural region. Sensors. 23(20). https://doi.org/10.3390/s23208595.
Systematic modelling errors undermine the application of land data assimilation systems for hydrological and weather forecasting
- (Peer Reviewed Journal)
Crow, W.T., Kim, H., Kumar, S. 2023. Systematic modelling errors undermine the application of land data assimilation systems for hydrological and weather forecasting. Journal of Hydrometeorology. 25, 3-26. https://doi.org/10.1175/JHM-D-23-0069.1.
Assessing the accuracy of OpenET satellite-based evapotranspiration data to support water resource and land management applications
- (Peer Reviewed Journal)
Volk, J., Huntington, J., Melton, F., Allen, R.G., Anderson, M.C., Fisher, J., Kilic, A., Ruhoff, A., Senay, G.B., Minor, B., Morton, C., Ott, T., Carrara, W., Doherty, C., Dunkerly, C., Friedrichs, M., Guzman, A., Hain, C., Halverson, G., Johnson, L., Kang, Y., Knipper, K.R., Ortega-Salazar, S., Pearson, C., Parrish, G.E., Purdy, A.J., Revelle, P.M., Wang, T., Yang, Y., Laipelt, L., Comini De Andrade, B. 2024. Assessing the accuracy of OpenET satellite-based evapotranspiration data to support water resource and land management applications. Nature Water. 2:193-205. https://doi.org/10.1038/s44221-023-00181-7.
Large-scale urban building function mapping by integrating multi-source web-based geospatial data
- (Peer Reviewed Journal)
Chen, W., Zhou, Y., Stokes, E.C., Zhang, X. 2023. Large-scale urban building function mapping by integrating multi-source web-based geospatial data. Geo-spatial Information Science. 1-15. https://doi.org/10.1080/10095020.2023.2264342.
The 50-year Landsat collection 2 archive
- (Peer Reviewed Journal)
Crawford, C., Roy, D., Arab, S., Barnes, C., Vermote, E., Hulley, G., Gerace, A., Choate, M., Engebretson, C., Schmidt, G., Anderson, C., Anderson, M.C., Bouchard, M., Skakun, S., Yan, L., Zhang, H., Zhu, Z., Zahn, S. 2023. The 50-year Landsat collection 2 archive. Science of Remote Sensing. 8. Article e100103. https://doi.org/10.1016/j.srs.2023.100103.
Nitrous oxide emissions from multiple agroecosystems in the U.S. Corn Belt simulated using the modified SWAT-C model
- (Peer Reviewed Journal)
Liang, K., Qi, J., Zhang, X., Emmett, B.D., Johnson, J.M., Malone, R.W., Moglen, G.E., Venterea, R.T. 2023. Nitrous oxide emissions from multiple agroecosystems in the U.S. Corn Belt simulated using the modified SWAT-C model . Environmental Pollution. 337(2023). Article e122537. https://doi.org/10.1016/j.envpol.2023.122537.
A basic and applied remote sensing research project (GRAPEX) for actual evapotranspiration monitoring to improve vineyard water management
- (Peer Reviewed Journal)
True global error maps for SMAP, SMOS, and ASCAT soil moisture data based on machine learning and triple collocation analysis
- (Peer Reviewed Journal)
Kim, H., Crow, W.T., Li, X., Wagner, W., Hahn, S., Lakshmi, V. 2023. True global error maps for SMAP, SMOS, and ASCAT soil moisture data based on machine learning and triple collocation analysis. Remote Sensing of Environment. 298: Article e113776. https://doi.org/10.1016/j.rse.2023.113776.
Watershed scale modeling of dissolved organic carbon export from variable source areas
- (Peer Reviewed Journal)
Mukundan, R., Gelda, R., Moknation, M., Zhang, X., Steenhuis, T. 2023. Watershed scale modeling of dissolved organic carbon export from variable source areas. Journal of Hydrology. 625(S1). Article e130052. https://doi.org/10.1016/j.jhydrol.2023.130052.
An introduction to Bayesian Machine Learning with an application in global-scale active and passive satellite-based soil moisture error pattern analysis
- (Peer Reviewed Journal)
Kim, H., Wagner, W., Crow, W.T., Li, X., Lakshmi, V. 2023. An introduction to Bayesian Machine Learning with an application in global-scale active and passive satellite-based soil moisture error pattern analysis. Remote Sensing of Environment. 296. https://doi.org/10.1016/j.rse.2023.113718.
The effects of forest composition and management on evapotranspiration in the New Jersey Pinelands
- (Peer Reviewed Journal)
Isaacson, B., Yang, Y., Clark, K., Anderson, M.C., Grabosky, J. 2023. The effects of forest composition and management on evapotranspiration in the New Jersey Pinelands. Agricultural and Forest Meteorology. 339. Article e109588. https://doi.org/10.1016/j.agrformet.2023.109588.
IMERG precipitation improves the SMAP level-4 soil moisture product
- (Peer Reviewed Journal)
Reichle, R., Liu, Q., Ardizzone, J., Crow, W.T., De Lannoy, G., Kimball, J., Koster, R. 2023. IMERG precipitation improves the SMAP level-4 soil moisture product. Journal of Hydrometeorology. 24, 1699-1723. https://doi.org/10.1175/JHM-D-23-0063.1.
Estimating drought-induced crop yield losses in near-real time
- (Peer Reviewed Journal)
Meitner, J., Balek, J., Bláhová, M., Semerádová, D., Hlavinka, P., Lukas, V., Jurecka, F., Žalud, Z., Klem, K., Anderson, M.C., Dorigo, W.A., Fischer, M., Trnka, M. 2023. Estimating drought-induced crop yield losses in near-real time. Agronomy. 13(7):1669. https://doi.org/10.3390/agronomy13071669.
Late-fall satellite-based soil moisture observations show clear connections to subsequent spring streamflow
- (Peer Reviewed Journal)
Koster, R.D., Liu, Q., Crow, W.T., Reichle, R.H. 2023. Late-fall satellite-based soil moisture observations show clear connections to subsequent spring streamflow. Nature Communications. 14:35-45. https://doi.org/10.1038/s41467-023-39318-3.
Attributing the drivers of runoff decline in the Thaya River basin
- (Peer Reviewed Journal)
Fischer, M., Pavik, P., Vizina, A., Bernsteinova, J., Parajka, J., Anderson, M.C., Rehor, J., Ivancicova, J., Stepanek, P., Balek, J., Hain, C., Tacheci, P., Hanel, M., Lukes, P., Blahova, M., Zahradnicek, P., Maca, P., Rapantova, N., Feng, S., Janal, P., Zeman, E., Zalud, Z., Trnka, M. 2023. Attributing the drivers of runoff decline in the Thaya River basin. Journal of Hydrology. 48. Article e101436. https://doi.org/10.1016/j.ejrh.2023.101436.
Multivariate calibration of the SWAT model using remotely sensed datasets
- (Peer Reviewed Journal)
Dangol, S., Zhang, X., Liang, X., Anderson, M.C., Crow, W.T., Lee, S., Moglen, G.E., McCarty, G.W. 2023. Multivariate calibration of the SWAT model using remotely sensed datasets. Remote Sensing. 15(9):2417. https://doi.org/10.3390/rs15092417.
Inversion and Validation of FY-4A Official Land Surface Temperature Product
- (Peer Reviewed Journal)
Dong, L., Wang, F., Cosh, M.H., Min, M. 2023. Inversion and Validation of FY-4A Official Land Surface Temperature Product. Journal of Photogrammetry and Remote Sensing. 15(9):2437. https://doi.org/10.3390/rs15092437.
SWAT-3PG: Improving forest growth simulation with a process-based forest model in SWAT
- (Peer Reviewed Journal)
Karki, R., Qi, J., Gonzales-Benecke, C., Zhang, X., Martin, T., Arnold, J.G. 2023. SWAT-3PG: Improving forest growth simulation with a process-based forest model in SWAT. Journal of Environmental Modeling and Software. 164. Article 105705. https://doi.org/10.1016/j.envsoft.2023.105705.
Potential of remote sensing surface temperature- and evapotranspiration-based land-atmosphere coupling metrics for land surface model calibration
- (Peer Reviewed Journal)
Zhou, J., Yang, K., Crow, W.T., Ding, J., Zhao, L., Fenng, H., Zou, M., Lu, H., Tang, R. 2023. Potential of remote sensing surface temperature- and evapotranspiration-based land-atmosphere coupling metrics for land surface model calibration. Remote Sensing of Environment. 291. Article 113557. https://doi.org/10.1016/j.rse.2023.113557.
Form field observations to temporally dynamic roughness retrievals in the corn belt
- (Peer Reviewed Journal)
Walker, V., Yildrim, E., Wallace, V., Eichinger, W., Cosh, M.H., Hornbuckle, B. 2023. Form field observations to temporally dynamic roughness retrievals in the corn belt. Remote Sensing of Environment. 287. Article e113458. https://doi.org/10.1016/j.rse.2023.113458.
Surface Albedo VALidation (SALVAL) platform: towards CEOS LPV validation stage 4. Application to three global al-bedo
climate data records
- (Peer Reviewed Journal)
Sanchez-Zapero, J., Martinez-Sanchez, E., Camacho, F., Wang, Z., Carrer, D., Schaaf, C., Garcia-Haro, F., Nickeson, J., Cosh, M.H. 2023. Surface Albedo VALidation (SALVAL) platform: towards CEOS LPV validation stage 4. Application to three global albedo climate data records. Remote Sensing. 15:1081. https://doi.org/10.3390/rs15041081.
ET partitioning assessment using the TSEB model and sUAS information across California Central Valley vineyards
- (Peer Reviewed Journal)
Gao, R., Torres-Rua, A., Nieto, H., Zahn, E., Hipps, L., Kustas, W.P., Alsina, M., Ortiz, N., Castro, S., Prueger, J., Alfieri, J.G., McKee, L.G., White, W.A., Gao, F.N., McElrone, A.J., Anderson, M.C., Knipper, K.R., Coopmans, C., Gowing, I., Agam, N., Sanchez, L., Dokoozlian, N. 2023. ET partitioning assessment using the TSEB model and sUAS information across California Central Valley vineyards. Remote Sensing. 15(3). Article 756. https://doi.org/10.3390/rs15030756.
Near real-time detection of winter cover crop termination using harmonized Landsat and Sentinel-2 (HLS) to support ecosystem assessment
- (Peer Reviewed Journal)
Gao, F.N., Jennewein, J.S., Hively, W.D., Soroka, A., Thieme, A., Bradley, D., Keppler, J., Mirsky, S.B., Akumaga, U. 2022. Near real-time detection of winter cover crop termination using harmonized Landsat and Sentinel-2 (HLS) to support ecosystem assessment. Science of Remote Sensing. 7. Article 100073. https://doi.org/10.1016/j.srs.2022.100073.
Improved estimation of vegetation water content and its impact on L-band soil moisture retrieval over cropland
- (Peer Reviewed Journal)
Feng, S., Qui, J., Crow, W.T., Mo, X., Wang, S., Gao, L. 2022. Improved estimation of vegetation water content and its impact on L-band soil moisture retrieval over cropland. Journal of Photogrammetry and Remote Sensing. 617. Article 129015. https://doi.org/10.1016/j.jhydrol.2022.129015.
Estimation of base and surface flow using deep neural networks and a hydrologic model in two watersheds of the Chesapeake Bay
- (Peer Reviewed Journal)
Lee, J., Abbas, A., McCarty, G.W., Zhang, X., Lee, S., Cho, K. 2022. Estimation of base and surface flow using deep neural networks and a hydrologic model in two watersheds of the Chesapeake Bay. Journal of Hydrology. 617. Article 128916. https://doi.org/10.1016/j.jhydrol.2022.128916.
Integrating vegetation phenology and SWAT model for improved modeling of ecohydrological processes
- (Peer Reviewed Journal)
Chen, S., Fu, Y., Wu, Z., Hao, F., Hao, Z., Guo, Y., Geng, X., Li, X., Zhang, X., Tang, J., Singh, V.P., Zhang, X. 2022. Integrating vegetation phenology and SWAT model for improved modeling of ecohydrological processes. Remote Sensing. 616:128817. https://doi.org/10.1016/j.jhydrol.2022.128817.
Working toward a National Coordinated Soil Moisture Monitoring Network: vision, progress, and future directions
- (Peer Reviewed Journal)
Baker, B., Cosh, M.H., Brusberg, M., Bolten, J., Caldwell, T., Connolly, S., Goble, P., Meyers, T., Ochsner, T., Quiring, S., Svoboda, M., Skumanich, M., Woloszyn, M. 2022. Working toward a National Coordinated Soil Moisture Monitoring Network: vision, progress, and future directions. Bulletin of the American Meteorological Society. 103(12):E2719–E2732. https://doi.org/10.1175/BAMS-D-21-0178.1.
A global implementation of single- and dual-source surface energy balance models for estimating actual evapotranspiration at 30-m resolution using Google Earth Engine
- (Peer Reviewed Journal)
Jafaar, H., Mourad, R., Kustas, W.P., Anderson, M.C. 2022. A global implementation of single- and dual-source surface energy balance models for estimating actual evapotranspiration at 30-m resolution using Google Earth Engine. Water Resources Research. 58. Article e2022WR032800. https://doi.org/10.1029/2022WR032800.
In situ soil moisture sensors in undisturbed soils
- (Peer Reviewed Journal)
Caldwell, T., Cosh, M.H., Evett, S.R., Edwards, N., Hofman, H., Illston, B., Meyers, T., Skumanich, M., Sutcliffe, K. 2022. In situ soil moisture sensors in undisturbed soils. Journal of Visualized Experiments. https://doi.org/10.3791/64498.
An agenda for land data assimilation priorities: Realizing the promise of terrestrial water, energy, and vegetation observations from space
- (Peer Reviewed Journal)
Kumar, S., Kolassa, J., Reichle, R., De Lannoy, G., De Rosnay, P., Macbean, N., Girotto, M., Fox, A., Quaife, T., Draper, C., Forman, B., Balsamo, G., Steele-Dunne, S., Albergel, C., Bonan, B., Calvet, J.C., Dong, J., Liddy, H., Ruston, B., Crow, W.T. 2022. An agenda for land data assimilation priorities: Realizing the promise of terrestrial water, energy, and vegetation observations from space. Journal of Advances in Modeling Earth Systems. 14(11). https://doi.org/10.1029/2022MS003259.
Benchmarking downscaled satellite-based soil moisture products using sparse, point-scale ground observations
- (Peer Reviewed Journal)
Crow, W.T., Chen, F., Colliander, A. 2022. Benchmarking downscaled satellite-based soil moisture products using sparse, point-scale ground observations. Remote Sensing of Environment. 283. Article 113300. https://doi.org/10.1016/j.rse.2022.113300.
From vine to vineyard: The GRAPEX multi-scale remote sensing experiment for improving vineyard irrigation management
- (Review Article)
High-resolution soil moisture data reveal complex multi-scale spatial variability across the United States
- (Peer Reviewed Journal)
Vergopolan, N., Sheffield, J., Chaney, N., Pan, M., Beck, H., Ferguson, C., Torres-Rojas, L., Eigenbrod, F., Crow, W.T., Wood, E. 2022. High-resolution soil moisture data reveal complex multi-scale spatial variability across the United States. Geophysical Research Letters. 49(15):e2022GL098586. https://doi.org/10.1029/2022GL098586.
Fifty years of Landsat science and impacts
- (Peer Reviewed Journal)
Wulder, M., Roy, D., Radeloff, V., Loveland, T., Anderson, M.C., Johnson, D., Healey, S., Zhu, Z., Scambos, T., Pahlevan, N., Hansen, M., Gorelick, N., Crawford, C., Masek, J., Hermosilla, T., White, J., Belward, A., Schaaf, C., Woodcock, C., Huntington, J., Lymburner, L., Hostert, P., Gao, F.N., Lyapustin, A., Pekel, J., Strobl, P., Cook, B. 2022. Fifty years of Landsat science and impacts. Remote Sensing of Environment. 280. Article 113195. https://doi.org/10.1016/j.rse.2022.113195.
Assessing the spatiotemporal variability of SMAP soil moisture accuracy in a deciduous forest region
- (Peer Reviewed Journal)
Abdelkader, M., Temimi, M., Colliander, A., Cosh, M.H., Kelly, V., Lakhankar, T., Fares, A. 2022. Assessing the spatiotemporal variability of SMAP soil moisture accuracy in a deciduous forest region. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 14(14). https://doi.org/10.3390/rs14143329.
NRCS curve number method: A comparison of methods for estimating the curve number from rainfall-runoff data
- (Peer Reviewed Journal)
Moglen, G.E., Sadeq, H., Hughes, L., Meadows, M., Miller, J.J., Ramirez-Avila, J., Tollner, E. 2022. NRCS curve number method: A comparison of methods for estimating the curve number from rainfall-runoff data. Journal Hydrologic Engineering. https://doi.org/10.1061/(ASCE)HE.1943-5584.0002210.
Seeing our planet anew: fifty years of Landsat
- (Peer Reviewed Journal)
Loveland, T., Anderson, M.C., Huntington, J., Irons, J., Johnson, D., Rocchio, L., Woodcock, C., Wulder, M. 2022. Seeing our planet anew: fifty years of Landsat. Photogrammetric Engineering and Remote Sensing. 88:7. https://doi.org/10.14358/PERS.88.7.429.
A twenty-year dataset of soil moisture and vegetation optical depth from AMSR-E/2 measurements using the multichannel collaborative algorithm
- (Peer Reviewed Journal)
Hu, L., Zhao, T., Ju, W., Peng, Z., Shi, J., Wigneron, J., Rodrigues-Fernandez, N., Cosh, M.H., Yang, K., Lu, H., Yao, P. 2023. A twenty-year dataset of soil moisture and vegetation optical depth from AMSR-E/2 measurements using the multichannel collaborative algorithm. Remote Sensing of Environment. 292:113595. https://doi.org/10.1016/j.rse.2023.113595.
LAI estimation across California vineyards using sUAS multi-seasonal multi-spectral, thermal, and elevation information and machine learning
- (Peer Reviewed Journal)
Gao, R., Torres, A., Aboutalebi, M., White, W.A., Anderson, M.C., Kustas, W.P., Agam, N., Alsina, N., Alfieri, J.G., Hipps, L., Dokoozlian, N., Nieto, H., Gao, F.N., McKee, L.G., Prueger, J.H., Sanchez, L., McElrone, A.J., Bambach, N., Coopmans, C., Gowing, I. 2022. LAI estimation across California vineyards using sUAS multi-seasonal multi-spectral, thermal, and elevation information and machine learning. Irrigation Science. 40:731-759. https://doi.org/10.1007/s00271-022-00776-0.