Uncertainty assessment of soil erosion model using particle filtering
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  • 作者:Yeonsu Kim ; Giha Lee ; Hyunuk An ; Jae E. Yang
  • 关键词:Data assimilation ; Particle filter ; Soil erosion modeling ; Parameter estimation ; Time variant parameter ; Mountainous catchment
  • 刊名:Journal of Mountain Science
  • 出版年:2015
  • 出版时间:July 2015
  • 年:2015
  • 卷:12
  • 期:4
  • 页码:828-840
  • 全文大小:1,315 KB
  • 参考文献:APIP (2008) Watershed hydrological modeling based on runoff and sediment transport processes: a physically-based distributed model and its lumping. Master鈥檚 Thesis, Kyoto University.
    Arulampalam M, Maskell S, Gordon N, et al. (2002) A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking, IEEE Transactions on Signal Processing 50(2): 174鈥?88. DOI:10.1109/78.978374View Article
    Beven K, Binley AM (1992) The future of distributed models: model calibration and uncertainty prediction. Hydrological Processes 6(3): 279鈥?98. DOI:10.1002/hyp.3360060305View Article
    Beven K (2005) Rainfall-runoff modeling: Introduction.in Encyclopedia of Hydrological Sciences 3: 1857鈥?868, John Wiley and Sons, Chichester. DOI: 10.1002/0470848944. hsa130
    Brazier RE, Beven KJ, Anthony SG, et al. (2001) Implications of model uncertainty for the mapping of hillslope 鈥?scale soil erosion predictions. Earth Surface Processes and Landforms 26: 1333鈥?352. DOI: 10.1002/esp.266View Article
    Doucet A, Godsills, Andrieu C (2000) On sequential Monte Carlo sampling methods for Bayesian filtering. Statistics and Computing 10(3): 197鈥?08. DOI: 10.1023/:1008935410038View Article
    Doucet A, Freitas N, Gordon N (2001) An Introduction to Sequential Monte Carlo Methods. In Sequential Monte Carlo Methods in Practice, Springer New York: 3鈥?4. DOI: 10.1007/978-1-4757-3437-9_1View Article
    Doucet A, Johansen AM (2009) A tutorial on particle filtering and smoothing: fifteen years later. Handbook of Nonlinear Filtering 12: 656鈥?04.
    Jetten V, Govers G, Hesse R (2003) Erosion models: quality and spatial predictions. Hydrological Process 17:887鈥?90. DOI: 10.1002/hyp.1168View Article
    Gupta HV, Beven KJ, Wagener T (2005) Model Calibration and Uncertainty Estimation. Encyclopedia of hydrological sciences 3, John Wiley and Sons, New York: 2015鈥?031. DOI: 10.1002/0470848944.hsa138
    Gordon NJ, Salmond DJ, Smith AFM (1993) Novel approach to nonlinear/non-Gaussian Bayesianstate estimation. IEEProceedings- F 140: 107鈥?13. DOI: 10.1049Zip-f-2.1993.0015
    Govers G (1990) Empirical relationships on the transporting capacity of overland flow. Transport and Deposition Processes, Proceedings of the Jerusalem Workshop, March-April in 1987, IAHS 189: 45鈥?3.
    Kim Y, Tachikawa Y, Shiiba M, et al. (2012) Simultaneous Estimation of Inflow and Channel Roughness Using 2d Hydraulic Model and Particle Filters. Journal of Flood Risk Management 6(2): 112鈥?23. DOI: 10.1111/j.1753-318x.2012. 01164.xView Article
    Laflen JM, Lane LJ, Foster GR (1991) WEPP - a next generation of erosion prediction technology. Journal of Soil Water Conservation 46: 34鈥?8
    Lee G, Tachikawa Y, Takara K (2009) Interaction between topographic and process parameters due to the spatial resolution of DEMs in distributed rainfall-runoff modeling. Journal of Hydrologic Engineering 14(10):1059鈥?069. DOI: 10.1061/(asce)he.1943-5584.0000098View Article
    Lee G, Kim Y, Kim Y, Lee E (2009) Analysis of suspended sediment load of donghyang and cheoncheon basin using gis based swat model, Journal of the Korean Association of Geographic Information studies 12(2): 82鈥?8 (In Korean)
    Lee G, Yu W, Jung K (2013) Catchment-scale soil erosion and sediment yield simulation using a spatially-distributed erosion model. Environmental Earth Sciences 70: 33鈥?7. DOI: 10.1007/s12665-012-2101-5View Article
    Liu Y, Weerts AH, Clark M, et al. (2012) Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities. Hydrology and Earth System Sciences 16(10): 3863鈥?887. DOI: 10.5194/hess-16-3863-2012View Article
    Ministry of Environment (2012) National Soil Erosion Research Report in Korea (In Korean).
    Moradkhani H, Hsu KL, Gupta H, et al. (2005) Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using the particle filter. Water Resources Research 41: W05012. DOI: 10.1029/2004wr003604View Article
    Morgan RPC, Quinton JN, Smith RE, et al. (1998) The European soil erosion model (EUROSEM): adynamic approach for predicting sediment transport from fields and small catchments. Earth Surface Process Landform 23:527鈥?44. DOI: 10.1002/(sici)1096鈥?837(199806)23:6<527:aidesp868>3.0.co;2鈥?View Article
    National Emergency Management Agency (1998) Study on the Sediment Yield Estimation due to Land Development (I). (In Korean)
    Renschler CS, Mannaerts C, Diekkruger B (1999) Evaluating spatial and temporal variability in soil erosion risk鈥攔ainfall erosivity and soil loss ratios in Andalusia, Spain. CATENA 34: 209鈥?25. DOI: 10.1016 0341-8162(98)00117-9View Article
    Ristic B, Arulampalam S, Gordon N (2004) Beyond the Kalman filter. ArtechHouse: 35鈥?5. DOI: 10.1109/maes.2004.1346848
    Saavedra C (2005) Estimating spatial patterns of soil erosion and deposition in the Andean region using geo-information techniques: a case study in Cochabamba, Bolivia. Wageningen Universiteit.
    Sayama T (2003) Evaluation of reliability and complexity of rainfall-sediment-runoff models. Master鈥檚 Thesis, Kyoto University.
    Sivapalan M, Kalma JD (1995) Scale problems in hydrology: the contributions of the Robertson workshop. In: Kalma JD, Sivapalan M (eds.), Scale Issues in Hydrological Modeling. John Wiley and Sons, Chichester. pp 1鈥?.
    Takasao T, Shiiba M (1988) Incorporation of the effect of concentration of flow into the kinematic wave equations and its applications to runoff system lumping. Journal of Hydrology 102:301鈥?22. DOI:10.1016/0022-1694(88)90104-7View Article
    Tachikawa Y, Nagatani G, Takara K (2004) Development of stage-discharge relationship equation incorporating saturated-unsaturated flow mechanism. Annual Journal of Hydraulic Engineering, JSCE 48: 7鈥?2 (In Japanese)View Article
    Van Oost K, Govers G, Van Muysen W (2003) A process-based conversion model for caesium-137 derived erosion rates on agricultural land: an integrated spatial approach. Earth Surface Processes and Landforms 28: 187鈥?07. DOI: 10.1002/ esp.446View Article
    Van Oost K, Govers G, Cerdan O, et al. (2005) Spatially distributed data for erosion model calibration and validation: The Ganspoel and Kinderveld datasets. CATENA 61: 105鈥?21. DOI: 10.1016/j.catena.2005.03.001View Article
    Vieux BE (2004) Distributed hydrological modeling using GIS, Kluwer, Dordrecht. DOI: 10.1007/1-4020-2460-6
    Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses. In Agriculture Handbook, No. 537, USDA-Science and Education Administration. p 58.
    Yang CT (1972) Unit stream power and sediment transport. Journal of the Hydraulics Division, ASCE 98(HYI0): 1805鈥?826.
    Yang CT (1973) Incipient motion and sediment transport. Journal of the Hydraulics Division, ASCE 99(HYI0): 1679鈥?704.
    Zhang L, Antoinette L, O鈥橬eill, et al. (1996) Modelling approaches to the prediction of soil erosion in catchment. Environmental Software 11: 123鈥?33. DOI: 10.1016/s0266-9838(96)00023-8View Article
  • 作者单位:Yeonsu Kim (1)
    Giha Lee (2)
    Hyunuk An (3)
    Jae E. Yang (4)

    1. International Water Resources Research Institute, Chungnam National University, Daejeon, 305-764, Korea
    2. Dept. of Construction & Disaster Prevention Eng., Kyungpook National University, Sangju, 742-711, Korea
    3. Dept. of Agricultural & Rural Eng., Chungnam National University, Daejeon, 305-764, Korea
    4. Dept. of Biological Environment, Kangwon National University, Chunchon, 200-701, Korea
  • 刊物主题:Earth Sciences, general; Geography (general); Environment, general; Ecology;
  • 出版者:Springer Berlin Heidelberg
  • ISSN:1993-0321
文摘
Recent advances in computer with geographic information system (GIS) technologies have allowed modelers to develop physics-based models for modeling soil erosion processes in time and space. However, it has been widely recognized that the effect of uncertainties on model predictions may be more significant when modelers apply such models for their own modeling purposes. Sources of uncertainty involved in modeling include data, model structural, and parameter uncertainty. To deal with the uncertain parameters of a catchment-scale soil erosion model (CSEM) and assess simulation uncertainties in soil erosion, particle filtering modeling (PF) is introduced in the CSEM. The proposed method, CSEM-PF, estimates parameters of non-linear and non-Gaussian systems, such as a physics-based soil erosion model by assimilating observation data such as discharge and sediment discharge sequences at outlets. PF provides timevarying feasible parameter sets as well as uncertainty bounds of outputs while traditional automatic calibration techniques result in a time-invariant global optimal parameter set. CSEM-PF was applied to a small mountainous catchment of the Yongdam dam in Korea for soil erosion modeling and uncertainty assessment for three historical typhoon events. Finally, the most optimal parameter sets and uncertainty bounds of simulation of both discharge and sediment discharge at each time step of the study events are provided.
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