Abstract
Soil moisture is a key variable in hydrological modelling, which could be estimated by land surface modelling. However the previous studies have focused on evaluating these soil moisture estimates by using point-based measurements, and there is a lack of attention for their appraisal over basin scales particularly for hydrological applications. In this study, we carry out for the first time, a detailed evaluation of five sources of soil moisture products (NLDAS-2 multi-model simulated soil moistures: Noah, VIC, Mosaic and SAC; and a ground observation), against a widely used hydrological model Xinanjiang (XAJ) as a benchmark at a U.S. basin. Generally speaking, all products have good agreements with the hydrological soil moisture simulation, with superior performance obtained from the SAC model and the VIC model. Furthermore, the results indicate that the in-situ measurements in deeper soil layer are still usable for hydrological applications. Nevertheless further improvement is still required on the definition of land surface model layer thicknesses and the related data fusion with the remotely sensed soil moisture. The potential usage of the NLDAS-2 soil moisture datasets in real-time flood forecasting is discussed.
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References
Andersson L, Harding RJ (1991) Soil-moisture deficit simulations with models of varying complexity for forest and grassland sites in Sweden and the UK. Water Resour Manag 5:25–46
Bartholomé E, Belward A (2005) GLC2000: a new approach to global land cover mapping from Earth observation data. Int J Remote Sens 26:1959–1977
Bell JE, Palecki MA, Baker CB, Collins WG, Lawrimore JH, Leeper RD, Hall ME, Kochendorfer J, Meyers TP, Wilson T (2013) US climate reference network soil moisture and temperature observations. J Hydrometeorol 14:977–988
Betts AK, Chen F, Mitchell KE, Janjic ZI (1997) Assessment of the land surface and boundary layer models in two operational versions of the NCEP Eta Model using FIFE data. Mon Weather Rev 125:2896–2916
Burnash, R.J.C., Ferral, R.L., McGuire, R.A., McGuire, R.A., & Center, U.S.J.F.-S.R.F. (1973). A generalized streamflow simulation system: conceptual modeling for digital computers. U.S. Department of Commerce, National Weather Service, and State of California, Department of Water Resources
Cai X, Yang ZL, David CH, Niu GY, Rodell M (2014) Hydrological evaluation of the Noah-MP land surface model for the Mississippi River Basin. J Geophys Res Atmos 119:23–38
Chen F, Mitchell K, Schaake J, Xue Y, Pan HL, Koren V, Duan QY, Ek M, Betts A (1996) Modeling of land surface evaporation by four schemes and comparison with FIFE observations. J Geophys Res Atmos (1984–2012) 101:7251–7268
Chen TH, Henderson-Sellers A, Milly P, Pitman A, Beljaars A, Polcher J, Abramopoulos F, Boone A, Chang S, Chen F (1997) Cabauw experimental results from the project for intercomparison of land-surface parameterization schemes. J Clim 10:1194–1215
Chen Y, Yang K, Zhou D, Qin J, Guo X (2010) Improving the Noah land surface model in arid regions with an appropriate parameterization of the thermal roughness length. J Hydrometeorol 11:995–1006
Chen X, Yang T, Wang X, Xu C-Y, Yu Z (2013) Uncertainty intercomparison of different hydrological models in simulating extreme flows. Water Resour Manag 27:1393–1409
Daly C, Neilson RP, Phillips DL (1994) A statistical-topographic model for mapping climatological precipitation over mountainous terrain. J Appl Meteorol 33:140–158
Diamond HJ, Karl TR, Palecki MA, Baker CB, Bell JE, Leeper RD, Easterling DR, Lawrimore JH, Meyers TP, Helfert MR (2013) US climate reference network after one decade of operations. Bull Am Meteorol Soc 94:485–498
Duan Q, Schaake J, Andreassian V, Franks S, Goteti G, Gupta H, Gusev Y, Habets F, Hall A, Hay L (2006) Model Parameter Estimation Experiment (MOPEX): an overview of science strategy and major results from the second and third workshops. J Hydrol 320:3–17
Ek M, Mitchell K, Lin Y, Rogers E, Grunmann P, Koren V, Gayno G, Tarpley J (2003) Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J Geophys Res Atmos (1984–2012) 108
Engman ET, Gurney, RJ (1991) Remote sensing in hydrology. Chapman and Hall Ltd
esa (2010). Soil moisture essential climate variable. esa climate change initiative. http://www.esa-soilmoisture-cci.org/. Accessed 29 January 2015
Ganji A (2010) A modified constrained state formulation of stochastic soil moisture for crop water allocation. Water Resour Manag 24:547–561
Jackson TJ, Schmugge TJ (1989) Passive microwave remote sensing system for soil moisture: some supporting research. IEEE Trans Geosci Remote Sens 27:225–235
Kerr YH, 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
Koren V, Schaake J, Mitchell K, Duan QY, Chen F, Baker J (1999) A parameterization of snowpack and frozen ground intended for NCEP weather and climate models. J Geophys Res Atmos (1984–2012) 104:19569–19585
Koren V, Smith M, Cui Z (2014) Physically-based modifications to the Sacramento soil moisture accounting model. Part A: modeling the effects of frozen ground on the runoff generation process. J Hydrol 519:3475–3491
Koster RD, Suarez MJ (1994) The components of a ‘SVAT’ scheme and their effects on a GCM’s hydrological cycle. Adv Water Resour 17:61–78
Koster R, Suarez M (1996) Energy and water balance calculations in the Mosaic LSM. NASA Tech Memo 104606:59
Koster R, Mahanama S, Yamada T, Balsamo G, Berg A, Boisserie M, Dirmeyer P, Doblas-Reyes F, Drewitt G, Gordon C (2011) The second phase of the global land-atmosphere coupling experiment: soil moisture contributions to subseasonal forecast skill. J Hydrometeorol 12:805–822
Liang X, Lettenmaier DP, Wood EF, Burges SJ (1994) A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J Geophys Res Atmos (1984–2012) 99:14415–14428
Mendicino G, Versace P (2007) Integrated drought watch system: a case study in Southern Italy. Water Resour Manag 21:1409–1428
Mishra S, Jain M, Singh V (2004) Evaluation of the SCS-CN-based model incorporating antecedent moisture. Water Resour Manag 18:567–589
Mitchell KE, Lohmann D, Houser PR, Wood EF, Schaake JC, Robock A, Cosgrove BA, Sheffield J, Duan Q, Luo L (2004) The multi-institution North American Land Data Assimilation System (NLDAS): utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system. J Geophys Res Atmos (1984–2012) 109
Nandintsetseg B, Shinoda M (2011) Seasonal change of soil moisture in Mongolia: its climatology and modelling. Int J Climatol 31:1143–1152
Nash J, Sutcliffe J (1970) River flow forecasting through conceptual models part I—a discussion of principles. J Hydrol 10:282–290
Norbiato D, Borga M, Degli Esposti S, Gaume E, Anquetin S (2008) Flash flood warning based on rainfall thresholds and soil moisture conditions: an assessment for gauged and ungauged basins. J Hydrol 362:274–290
Ochsner TE, Cosh MH, Cuenca RH, Dorigo WA, Draper CS, Hagimoto Y, Kerr YH, Njoku EG, Small EE, Zreda M (2013) State of the art in large-scale soil moisture monitoring. Soil Sci Soc Am J 77:1888–1919
Ottlé C, Vidal-Madjar D (1994) Assimilation of soil moisture inferred from infrared remote sensing in a hydrological model over the HAPEX-MOBILHY region. J Hydrol 158:241–264
Patil M, Waghmare R, Halder S, Dharmaraj T (2011) Performance of Noah land surface model over the tropical semi-arid conditions in western India. Atmos Res 99:85–96
Peel MC, Finlayson BL, McMahon TA (2007) Updated world map of the Köppen-Geiger climate classification. Hydrol Earth Syst Sci Discuss 4:439–473
Ren-Jun Z (1992) The Xinanjiang model applied in China. J Hydrol 135:371–381
Robock A, Vinnikov KY, Srinivasan G, Entin JK, Hollinger SE, Speranskaya NA, Liu S, Namkhai A (2000) The global soil moisture data bank. Bull Am Meteorol Soc 81:1281–1299
Rosero E, Yang Z-L, Gulden LE, Niu G-Y, Gochis DJ (2009) Evaluating enhanced hydrological representations in Noah LSM over transition zones: implications for model development. J Hydrometeorol 10:600–622
Sahoo AK, Dirmeyer PA, Houser PR, Kafatos M (2008) A study of land surface processes using land surface models over the Little River Experimental Watershed, Georgia. J Geophys Res Atmos (1984–2012), 113
Seneviratne SI, Corti T, Davin EL, Hirschi M, Jaeger EB, Lehner I, Orlowsky B, Teuling AJ (2010) Investigating soil moisture–climate interactions in a changing climate: a review. Earth Sci Rev 99:125–161
She D, Liu D, Xia Y, Shao MA (2014) Modeling effects of land use and vegetation density on soil water dynamics: implications on water resource management. Water Resour Manag 28:2063–2076
Shi P, Chen C, Srinivasan R, Zhang X, Cai T, Fang X, Qu S, Chen X, Li Q (2011) Evaluating the SWAT model for hydrological modeling in the Xixian watershed and a comparison with the XAJ model. Water Resour Manag 25:2595–2612
Srivastava PK, Han D, Ramirez MR, Islam T (2013a) Machine learning techniques for downscaling SMOS satellite soil moisture using MODIS land surface temperature for hydrological application. Water Resour Manag 27:3127–3144
Srivastava PK, Han D, Rico-Ramirez MA, Al-Shrafany D, Islam T (2013b) Data fusion techniques for improving soil moisture deficit using SMOS satellite and WRF-NOAH Land surface model. Water Resour Manag 27:5069–5087
Srivastava PK, Han D, Rico Ramirez MA, Islam T (2013c) Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate. J Hydrol 498:292–304
Tombul M (2007) Mapping field surface soil moisture for hydrological modeling. Water Resour Manag 21:1865–1880
Wagner W, Bloschl G, Pampaloni P, Calvet J-C, Bizzarri B, Wigneron J-P, Kerr Y (2007) Operational readiness of microwave remote sensing of soil moisture for hydrologic applications. Nord Hydrol 38:1–20
Walker JP, Willgoose GR, Kalma JD (2004) In situ measurement of soil moisture: a comparison of techniques. J Hydrol 293:85–99
Webb RW, Rosenzweig CE, Levine, ER (2000) Global soil texture and derived water-holding capacities (Webb et al.). Data set. Available on-line [http://www.daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, USA
Xia Y, Mitchell K, Ek M, Cosgrove B, Sheffield J, Luo L, Alonge C, Wei H, Meng J, Livneh B (2012) Continental-scale water and energy flux analysis and validation for North American Land Data Assimilation System project phase 2 (NLDAS-2): 2. Validation of model-simulated streamflow. J Geophys Res Atmos (1984–2012) 117
Xia Y, Mitchell K, Ek M, Sheffield J, Cosgrove B, Wood E, Luo L, Alonge C, Wei H, Meng J (2012) Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2 (NLDAS-2): 1. Intercomparison and application of model products. J Geophys Res Atmos (1984–2012) 117
Xia Y, Sheffield J, Ek MB, Dong J, Chaney N, Wei H, Meng J, Wood EF (2014) Evaluation of multi-model simulated soil moisture in NLDAS-2. J Hydrol 512:107–125
Yang ZL, Niu GY, Mitchell KE, Chen F, Ek MB, Barlage M, Longuevergne L, Manning K, Niyogi D, Tewari M (2011) The community Noah land surface model with multiparameterization options (Noah-MP): 2. Evaluation over global river basins. J Geophys Res Atmos (1984–2012) 116
Zhao R-J (1980) The Xinanjiang model. Hydrol Forecast Proceed Oxf Symp IASH 129:351–356
Zhao R-J (1992) The Xinanjiang model applied in China. J Hydrol 135:371–381
Zhao R-J, Liu X, Singh V (1995) The Xinanjiang model. Computer models of watershed hydrology, 215–232
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Zhuo, L., Han, D., Dai, Q. et al. Appraisal of NLDAS-2 Multi-Model Simulated Soil Moistures for Hydrological Modelling. Water Resour Manage 29, 3503–3517 (2015). https://doi.org/10.1007/s11269-015-1011-1
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DOI: https://doi.org/10.1007/s11269-015-1011-1