Abstract
Assessment of the suitability of satellite soil moisture products at large scales is urgently needed for numerous climatic and hydrological researches, particularly in arid mountainous watersheds where soil moisture plays a key role in land-atmosphere exchanges. This study presents evaluation of the SMOS (L2) and SMAP (L2_P_E and L2_P) products against ground-based observations from the Upstream of the Heihe River Watershed in situ Soil Moisture Network (UHRWSMN) and the Ecological and Hydrological Wireless Sensor Network (EHWSN) over arid high mountainous watersheds, Northwest China. Results show that all the three products are reliable in catching the temporal trend of the in situ observations at both point and watershed scales in the study area. Due to the uncertainty in brightness temperature and the underestimation of effective temperature, the SMOS L2 product and both the SMAP L2 products show “dry bias” in the high, cold mountainous area. Because of the more accurate brightness temperature observations viewing at a constant angle and more suitable estimations of single scattering albedo and optical depth, both the SMAP L2 products performed significantly better than the SMOS product. Moreover, comparing with station density of in situ network, station representation is much more important in the evaluation of the satellite soil moisture products. Based on our analysis, we propose the following suggestions for improvement of the SMOS and SMAP product suitability in the mountainous areas: further optimization of effective temperature; revision of the retrieval algorithm of the SMOS mission to reduce the topographic impacts; and, careful selection of in situ observation stations for better representation of in situ network in future evaluations. All these improvements would lead to better applicability of the SMOS and SMAP products for soil moisture estimation to the high elevation and topographically complex mountainous areas in arid regions.
Similar content being viewed by others
References
Al Bitar A, Leroux D, Kerr Y H, Merlin O, Richaume P, Sahoo A, Wood E F. 2012. Evaluation of SMOS soil moisture products over continental U.S. using the SCAN/SNOTEL network. IEEE Trans Geosci Remote Sens, 50: 1572–1586
Al-Yaari A, Wigneron J P, Ducharne A, Kerr Y, de Rosnay P, de Jeu R, Govind A, Al Bitar A, Albergel C, Muñoz-Sabater J, Richaume P, Mialon A. 2014. Global-scale evaluation of two satellite-based passive microwave soil moisture datasets (SMOS and AMSR-E) with respect to land data assimilation system estimates. Remote Sens Environ, 149: 181–195
Al-Yaari A, Wigneron J P, Kerr Y, Rodriguez-Fernandez N, O'Neill P E, Jackson T J, De Lannoy G J M, Al Bitar A, Mialon A, Richaume P, Walker J P, Mahmoodi A, Yueh S. 2017. Evaluating soil moisture retrievals from ESA’s SMOS and NASA’s SMAP brightness temperature datasets. Remote Sens Environ, 193: 257–273
Brooks P D, Chorover J, Fan Y, Godsey S E, Maxwell R M, McNamara J P, Tague C. 2015. Hydrological partitioning in the critical zone: Recent advances and opportunities for developing transferable understanding of water cycle dynamics. Water Resour Res, 51: 6973–6987
Brown M E, Escobar V, Moran S, Entekhabi D, O’Neill P E, Njoku E G, Doorn B, Entin J K. 2013. NASA’s soil moisture active passive (SMAP) mission and opportunities for applications users. Bull Amer Meteorol Soc, 94: 1125–1128
Chan S K, Bindlish R, O’Neill P, Njoku E, Jackson T, Colliander A, Chen F, Burgin M, Dunbar S, Piepmeier J, Yueh S, Entekhabi D, Cosh M H, Caldwell T, Walker J, Wu X, Berg A, Rowlandson T, Pacheco A, McNairn H, Thibeault M, Martinez-Fernandez J, Gonzalez-Zamora A, Seyfried M, Bosch D, Starks P, Goodrich D, Prueger J, Palecki M, Small E E, Zreda M, Calvet J C, Crow W T, Kerr Y. 2016. Assessment of the SMAP passive soil moisture product. IEEE Trans Geosci Remote Sens, 54: 4994–5007
Chen F, Crow W T, Colliander A, Cosh M H, Jackson T J, Bindlish R, Reichle R H, Chan S K, Bosch D D, Starks P J, Goodrich D C, Seyfried M S. 2017. Application of triple collocation in ground-based validation of soil moisture active/passive (SMAP) Level 2 data products. IEEE J Sel Top Appl Earth Observations Remote Sens, 10: 489–502
Colliander A, Cosh M H, Misra S, Jackson T J, Crow W T, Chan S, Bindlish R, Chae C, Holifield Collins C, Yueh S H. 2017b. Validation and scaling of soil moisture in a semi-arid environment: SMAP validation experiment 2015 (SMAPVEX15). Remote Sens Environ, 196: 101–112
Colliander A, Jackson T J, Bindlish R, Chan S, Das N, Kim S B, Cosh M H, Dunbar R S, Dang L, Pashaian L, Asanuma J, Aida K, Berg A, Rowlandson T, Bosch D, Caldwell T, Caylor K, Goodrich D, al Jassar H, Lopez-Baeza E, Martínez-Fernández J, González-Zamora A, Livingston S, McNairn H, Pacheco A, Moghaddam M, Montzka C, Notarnicola C, Niedrist G, Pellarin T, Prueger J, Pulliainen J, Rautiainen K, Ramos J, Seyfried M, Starks P, Su Z, Zeng Y, van der Velde R, Thibeault M, Dorigo W, Vreugdenhil M, Walker J P, Wu X, Monerris A, O'Neill P E, Entekhabi D, Njoku E G, Yueh S. 2017a. Validation of SMAP surface soil moisture products with core validation sites. Remote Sens Environ, 191: 215–231
Cui H, Jiang L, Du J, Zhao S, Wang G, Lu Z, Wang J. 2017. Evaluation and analysis of AMSR-2, SMOS, and SMAP soil moisture products in the Genhe area of China. J Geophys Res-Atmos, 122: 8650–8666
Das N N, Entekhabi D, Dunbar R S, Njoku E G, Yueh S H. 2016. Uncertainty estimates in the SMAP combined active-passive downscaled brightness temperature. IEEE Trans Geosci Remote Sens, 54: 640–650
De Lannoy G J M, Reichle R H, Peng J, Kerr Y, Castro R, Kim E J, Qing Liu E J. 2015. Converting between SMOS and SMAP level-1 brightness temperature observations over nonfrozen land. IEEE Geosci Remote Sens Lett, 12: 1908–1912
Dente L, Su Z, Wen J. 2012. Validation of SMOS soil moisture products over the Maqu and Twente regions. Sensors, 12: 9965–9986
Ding Y, Baisheng Y E, Zhou W, 1999. Temporal and spatial precipitation distribution in the Heihe Catchment, Northwest China, during the past 40 a (in Chinese). J Glaciol Geocryol, 21: 42–48
Djamai N, Magagi R, Goïta K, Hosseini M, Cosh M H, Berg A, Toth B. 2015. Evaluation of SMOS soil moisture products over the CanEx-SM10 area. J Hydrol, 520: 254–267
Entekhabi D, Njoku E G, O'Neill P E, Kellogg K H, Crow W T, Edelstein W N, Entin J K, Goodman S D, Jackson T J, Johnson J, Kimball J, Piepmeier J R, Koster R D, Martin N, McDonald K C, Moghaddam M, Moran S, Reichle R, Shi J C, Spencer M W, Thurman S W, Tsang L, Van Zyl J. 2010. The soil moisture active passive (SMAP) mission. Proc IEEE, 98: 704–716
Entekhabi D, Yueh S, O’Neill P E, Kellogg K H, Allen A, Bindlish R, Brown M, Chan S, Colliander A, Crow W T, Das N, De Lannoy G, Dunbar R S, Edelstein W N, Entin J K, Escobar V, Goodman S D, Jackson T J, Jai B, Johnson J. 2014. SMAP Handbook. The National Aeronautics and Space Administration
Fernandez-Moran R, Wigneron J P, De Lannoy G, Lopez-Baeza E, Parrens M, Mialon A, Mahmoodi A, Al-Yaari A, Bircher S, Al Bitar A, Richaume P, Kerr Y. 2017. A new calibration of the effective scattering albedo and soil roughness parameters in the SMOS SM retrieval algorithm. Int J Appl Earth Observation Geoinf, 62: 27–38
Frye J D, Mote T L. 2010a. Convection initiation along soil moisture boundaries in the southern Great Plains. Mon Weather Rev, 138: 1140–1151
Frye J D, Mote T L. 2010b. The synergistic relationship between soil moisture and the low-level jet and its role on the prestorm environment in the southern Great Plains. J Appl Meteor Climatol, 49: 775–791
Galantowicz J F, Entekhabi D, Njoku E G. 2000. Estimation of soil-type heterogeneity effects in the retrieval of soil moisture from radiobrightness. IEEE Trans Geosci Remote Sens, 38: 312–315
Gao B, Qin Y, Wang Y, Yang D, Zheng Y. 2016. Modeling ecohydrological processes and spatial patterns in the Upper Heihe Basin in China. Forests, 7: 10
Gherboudj I, Magagi R, Goita K, Berg A A, Toth B, Walker A. 2012. Validation of SMOS data over agricultural and boreal forest areas in Canada. IEEE Trans Geosci Remote Sens, 50: 1623–1635
González-Zamora Á, Sánchez N, Martínez-Fernández J, Gumuzzio Á, Piles M, Olmedo E. 2015. Long-term SMOS soil moisture products: A comprehensive evaluation across scales and methods in the Duero Basin (Spain). Phys Chem Earth Parts A/B/C, 83-84: 123–136
Han X, Franssen H J H, Montzka C, Vereecken H. 2014. Soil moisture and soil properties estimation in the community land model with synthetic brightness temperature observations. Water Resour Res, 50: 6081–6105
Jackson T J, Bindlish R, Cosh M H, Zhao T, Starks P J, Bosch D D, Seyfried M, Moran M S, Goodrich D C, Kerr Y H, Leroux D. 2012. Validation of soil moisture and ocean salinity (SMOS) soil moisture over watershed networks in the U.S.. IEEE Trans Geosci Remote Sens, 50: 1530–1543
Jin M, Zheng X, Jiang T, Li X, Li X J, Zhao K. 2017. Evaluation and improvement of SMOS and SMAP soil moisture products for soils with high organic matter over a forested area in Northeast China. Remote Sens, 9: 387
Kang J, Jin R, Li X, Ma C, Qin J, Zhang Y. 2017. High spatio-temporal resolution mapping of soil moisture by integrating wireless sensor network observations and MODIS apparent thermal inertia in the Babao River Basin, China. Remote Sens Environ, 191: 232–245
Kerr Y H, Waldteufel P, Wigneron J P, Martinuzzi J, Font J, Berger M. 2001. Soil moisture retrieval from space: The Soil Moisture and Ocean Salinity (SMOS) mission. IEEE Trans Geosci Remote Sens, 39: 1729–1735
Kerr Y H, Font J, Martin-Neira M, Mecklenburg S. 2012a. Introduction to the special issue on the ESA’s soil moisture and ocean salinity mission (SMOS)—Instrument performance and first results. IEEE Trans Geosci Remote Sens, 50: 1351–1353
Kerr Y H, Al-Yaari A, Rodriguez-Fernandez N, Parrens M, Molero B, Leroux D, Bircher S, Mahmoodi A, Mialon A, Richaume P, Delwart S, Al Bitar A, Pellarin T, Bindlish R, Jackson T J, Rüdiger C, Waldteufel P, Mecklenburg S, Wigneron J P. 2016. Overview of SMOS performance in terms of global soil moisture monitoring after six years in operation. Remote Sens Environ, 180: 40–63
Kerr Y H, Waldteufel P, Richaume P, Wigneron J P, Ferrazzoli P, Mahmoodi A, Al Bitar A, Cabot F, Gruhier C, Juglea S E, Leroux D, Mialon A, Delwart S. 2012b. The SMOS soil moisture retrieval algorithm. IEEE Trans Geosci Remote Sens, 50: 1384–1403
Konings A G, Piles M, Rötzer K, McColl K A, Chan S K, Entekhabi D. 2016. Vegetation optical depth and scattering albedo retrieval using time series of dual-polarized L-band radiometer observations. Remote Sens Environ, 172: 178–189
Koster R D, Dirmeyer P A, Guo Z, Bonan G, Chan E, Cox P, Gordon C T, Kanae S, Kowalczyk E, Lawrence D, Liu P, Lu C H, Malyshev S, McAvaney B, Mitchell K, Mocko D, Oki T, Oleson K, Pitman A, Sud Y C, Taylor C M, Verseghy D, Vasic R, Xue Y, Yamada T, Yamada T. 2004. Regions of strong coupling between soil moisture and precipitation. Science, 305: 1138–1140
Koster R D, Mahanama S P P, Yamada T J, Balsamo G, Berg A A, Boisserie M, Dirmeyer P A, Doblas-Reyes F J, Drewitt G, Gordon C T, Guo Z, Jeong J H, Lawrence D M, Lee W S, Li Z, Luo L, Malyshev S, Merryfield W J, Seneviratne S I, Stanelle T, van den Hurk B J J M, Vitart F, Wood E F. 2010. Contribution of land surface initialization to subseasonal forecast skill: First results from a multi-model experiment. Geophys Res Lett, 37: L02402
Lei F, Huang C, Shen H, Li X. 2014. Improving the estimation of hydrological states in the SWAT model via the ensemble Kalman smoother: Synthetic experiments for the Heihe River Basin in northwest China. Adv Water Resources, 67: 32–45
Leroux D J, Kerr Y H, Richaume P, Fieuzal R. 2013. Spatial distribution and possible sources of SMOS errors at the global scale. Remote Sens Environ, 133: 240–250
Li C, Lu H, Yang K, Han M, Wright J, Chen Y, Yu L, Xu S, Huang X, Gong W. 2018. The evaluation of SMAP enhanced soil moisture products using high-resolution model simulations and in-situ observations on the Tibetan Plateau. Remote Sens, 10: 535
Li D, Jin R, Zhou J, Kang J. 2015. Analysis and reduction of the uncertainties in soil moisture estimation with the L-MEB model using EFAST and ensemble retrieval. IEEE Geosci Remote Sens Lett, 12: 1337–1341
Li X, Cheng G, Liu S, Xiao Q, Ma M, Jin R, Che T, Liu Q, Wang W, Qi Y, Wen J, Li H, Zhu G, Guo J, Ran Y, Wang S, Zhu Z, Zhou J, Hu X, Xu Z. 2013. Heihe watershed allied telemetry experimental research (Hi-WATER): Scientific objectives and experimental design. Bull Amer Meteorol Soc, 94: 1145–1160
Li Z, Xu Z, Shao Q, Yang J. 2009. Parameter estimation and uncertainty analysis of SWAT model in upper reaches of the Heihe river basin. Hydrol Process, 23: 2744–2753
Ma C, Li X, Wei L, Wang W. 2017. Multi-scale validation of SMAP soil moisture products over cold and arid regions in Northwestern China using distributed ground observation data. Remote Sens, 9: 327–341
Ma L, Zhang T, Frauenfeld O W, Qin D. 2006. Verification of ERA-40 and NCEP-1 Reanalysis Temperature Data with Ground-based Measurements in China. American Geophysical Union
Mo T, Choudhury B J, Schmugge T J, Wang J R, Jackson T J. 1982. A model for microwave emission from vegetation-covered fields. J Geophys Res, 87: 11229
O’Neill P, Chan S, Njoku E, Jackson T, Bindlish R. 2015. SMAP Level 2 & 3 Soil Moisture (Passive) Algorithm Theoretical Basis Document. Jet Propulsion Laboratory, Pasadena, CA, USA
Revision B Oliva R, Daganzo E, Kerr Y H, Mecklenburg S, Nieto S, Richaume P, Gruhier C. 2012. SMOS radio frequency interference scenario: Status and actions taken to improve the RFI environment in the 1400–1427-MHz passive band. IEEE Trans Geosci Remote Sens, 50: 1427–1439
O′Neill P, Chan S, Colliander A, Dunbar S, Njoku E, Bindlish R, Chen F, Jackson T, Burgin M, Piepmeier J, Yueh S, Entekhabi D, Cosh M, Caldwell T, Walker J, Wu X, Berg A, Rowlandson T, Pacheco A, McNairn H, Thibeault M, Martínez-Fernández J, González-Zamora Á, Seyfried M, Bosch D, Starks P, Goodrich D, Prueger J, Palecki M, Small E, Zreda M, Calvet J C, Crow W, Kerr Y. 2016. Evaluation of the validated Soil Moisture product from the SMAP radiometer. IGARSS 2016–2016 IEEE International Geoscience and Remote Sensing Symposium IEEE. 125–128
Owe M, de Jeu R, Walker J. 2001. A methodology for surface soil moisture and vegetation optical depth retrieval using the microwave polarization difference index. IEEE Trans Geosci Remote Sens, 39: 1643–1654
Pan M, Cai X, Chaney N W, Entekhabi D, Wood E F. 2016. An initial assessment of SMAP soil moisture retrievals using high-resolution model simulations and in situ observations. Geophys Res Lett, 43: 9662–9668
Panciera R, Walker J P, Kalma J D, Kim E J, Saleh K, Wigneron J P. 2009. Evaluation of the SMOS L-MEB passive microwave soil moisture retrieval algorithm. Remote Sens Environ, 113: 435–444
Parrens M, Zakharova E, Lafont S, Calvet J C, Kerr Y, Wagner W, Wigneron J P. 2012. Comparing soil moisture retrievals from SMOS and ASCAT over France. Hydrol Earth Syst Sci, 16: 423–440
Pellarin T, Mialon A, Biron R, Coulaud C, Gibon F, Kerr Y, Lafaysse M, Mercier B, Morin S, Redor I, Schwank M, Völksch I. 2016. Three years of L-band brightness temperature measurements in a mountainous area: Topography, vegetation and snowmelt issues. Remote Sens Environ, 180: 85–98
Polcher J, Piles M, Gelati E, Barella-Ortiz A, Tello M. 2016. Comparing surface-soil moisture from the SMOS mission and the ORCHIDEE land-surface model over the Iberian Peninsula. Remote Sens Environ, 174: 69–81
Reichle R, Koster R, De Lannoy G, Crow W, Kimball J. 2014. Algorithm Theoretical Basis Document Level 4 Surface and Root Zone Soil Moisture (L4_SM) Data Product. NASA. 3
Richter D B, Mobley M L. 2009. Monitoring Earth’s Critical Zone. Science, 326: 1067–1068
Ridler M E, Madsen H, Stisen S, Bircher S, Fensholt R. 2014. Assimilation of SMOS-derived soil moisture in a fully integrated hydrological and soil-vegetation-atmosphere transfer model in Western Denmark. Water Resour Res, 50: 8962–8981
Rötzer K, Montzka C, Bogena H, Wagner W, Kerr Y H, Kidd R, Vereecken H. 2014. Catchment scale validation of SMOS and ASCAT soil moisture products using hydrological modeling and temporal stability analysis. J Hydrol, 519: 934–946
Srivastava P K, Han D, Rico Ramirez M A, Islam T. 2013. Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate. J Hydrol, 498: 292–304
Taylor C M. 2015. Detecting soil moisture impacts on convective initiation in Europe. Geophys Res Lett, 42: 4631–4638
Vereecken H, Huisman J A, Pachepsky Y, Montzka C, van der Kruk J, Bogena H, Weihermüller L, Herbst M, Martinez G, Vanderborght J. 2014. On the spatio-temporal dynamics of soil moisture at the field scale. J Hydrol, 516: 76–96
Vreugdenhil M, Dorigo W, Broer M, Haas P, Eder A, Hogan P, Bloeschl G, Wagner W, 2013. Towards a high-density soil moisture network for the validation of SMAP in Petzenkirchen, Austria. IGARSS 2013–2013 IEEE International Geoscience and Remote Sensing Symposium IEEE. 1865–1868, doi: 10.1109/IGARSS.2013.6723166
Wang C, Zhao C Y. 2013. A study of the spatio-temporal distribution of precipitation in upper reaches of Heihe River of China using TRMM data (in Chinese). J Nat Resour, 28: 862–872
Wigneron J P, Kerr Y, Waldteufel P, Saleh K, Escorihuela M J, Richaume P, Ferrazzoli P, de Rosnay P, Gurney R, Calvet J C, Grant J P, Guglielmetti M, Hornbuckle B, Mätzler C, Pellarin T, Schwank M. 2007. L-band Microwave Emission of the Biosphere (L-MEB) Model: Description and calibration against experimental data sets over crop fields. Remote Sens Environ, 107: 639–655
Wigneron J P, Schwank M, Baeza E L, Kerr Y, Novello N, Millan C, Moisy C, Richaume P, Mialon A, Al Bitar A, Cabot F, Lawrence H, Guyon D, Calvet J C, Grant J P, Casal T, de Rosnay P, Saleh K, Mahmoodi A, Delwart S, Mecklenburg S. 2012. First evaluation of the simultaneous SMOS and ELBARA-II observations in the Mediterranean region. Remote Sens Environ, 124: 26–37
Wu Q, Liu H, Wang L, Deng C. 2016. Evaluation of AMSR2 soil moisture products over the contiguous United States using in situ data from the international soil moisture network. Int J Appl Earth Observation Geoinf, 45: 187–199
Yang L, Sun G, Zhi L, Zhao J. 2018. Negative soil moisture-precipitation feedback in dry and wet regions. Sci Rep, 8: 4026
Zhang L, He C, Li J, Wang Y, Wang Z. 2017b. Comparison of IDW and physically based IDEW method in hydrological modelling for a large mountainous watershed, Northwest China. River Res Applic, 33: 912–924
Zhang L, He C, Zhang M. 2017a. Multi-scale evaluation of the SMAP product using sparse in-situ network over a high mountainous watershed, Northwest China. Remote Sens, 9: 1111–1132
Zhao L, Yang K, Qin J, Chen Y, Tang W, Lu H, Yang Z L. 2014. The scaledependence of SMOS soil moisture accuracy and its improvement through land data assimilation in the central Tibetan Plateau. Remote Sens Environ, 152: 345–355
Zhao T, Shi J, Bindlish R, Jackson T, Cosh M, Jiang L, Zhang Z, Lan H. 2015. Parametric exponentially correlated surface emission model for L-band passive microwave soil moisture retrieval. Phys Chem Earth Parts A/B/C, 83-84: 65–74
Acknowledgements
This work was supported by the National Natural Science Foundation of China (Grant Nos. 41501016, 41530752, and 91125010), the Scherer Endowment Fund of Department of Geography, Western Michigan University and the Fundamental Research Funds for the Central Universities (Grant No. LZUJBKY-2017-224).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Zhang, L., He, C., Zhang, M. et al. Evaluation of the SMOS and SMAP soil moisture products under different vegetation types against two sparse in situ networks over arid mountainous watersheds, Northwest China. Sci. China Earth Sci. 62, 703–718 (2019). https://doi.org/10.1007/s11430-018-9308-9
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11430-018-9308-9