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Effect of different soil data on hydrological process modeling in Weihe River basin of Northwest China

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Abstract

Hydrological process modeling depends on the soil data spatial resolution of the watershed. Especially, in a large-scale watershed, could a higher resolution of soil data contribute to a more accurate result? In this study, two soil datasets with different classification systems FAO (World Reference Base) and GSCC (the Genetic Soil Classification of China) were used as inputs for the SWAT model to study the effects of soil datasets on hydrological process modeling in Weihe River basin, China. Results show that the discharge simulated using FAO soil data was better than one simulated using GSCC soil data before model calibration, which indicates that FAO soil data needed less effort to calibrate. After model calibration, discharges were simulated better by both of FAO and GSCC soil data but statistical parameters demonstrate that we can make a relatively more accurate estimation of discharge using the GSCC rather than FAO soil data. Soil water content (SW) simulated using GSCC soil data was statistically significantly higher than those simulated using FAO soil data. However, variations in other hydrological components (surface runoff (SURQ), actual evapotranspiration (ET), and water yield (WYLD) were not statistically significant. This might be because SW is more sensitive to soil properties. For studies aiming to simulate or compare SW, merely calibrating and validating models using river discharge observations is not enough. The hydrological modelers need to identify the key hydrological components intrinsic to their study and weigh the advantages and disadvantages before selecting suitable soil data.

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References

  • Abbaspour KC, Vejdani M, Haghighat S (2007) SWAT-CUP calibration and uncertainty programs for SWAT. Modsim International Congress on Modelling & Simulation Land Water & Environmental Management Integrated Systems for Sustainability 364(3):1603–1609

    Google Scholar 

  • Arnold JG, Kiniry JR, Srinivasan R, Williams JR, Haney EB, Neitsch SL (2011) Soil and water assessment tool input/output file documentation. Available in the website http://swat.tamu.edu/documentation/

  • Beven K, Freer J (2001) Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology. J Hydrol 249(1–4):11–29

    Article  Google Scholar 

  • Bormann H (2006) Impact of spatial data resolution on simulated catchment water balances and model performance of the multi-scale TOPLATS model. Hydrol Earth Syst Sc 10(2):165–179

    Article  Google Scholar 

  • Bormann, H., B. Diekkruger and O. Richter (1999) Regionalization in hydrology, UK.

  • Bossa AY, Diekkrüger B, Igué AM, Gaiser T (2012) Analyzing the effects of different soil databases on modeling of hydrological processes and sediment yield in Benin (West Africa. Geoderma 173:61–74

    Article  Google Scholar 

  • Chaplot V (2005) Impact of DEM mesh size and soil map scale on SWAT runoff, sediment, and NO3-N loads predictions. J Hydrol 312(1–4):207–222

    Article  Google Scholar 

  • Cotter AS, Chaubey I, Costello TA, Soerens TS, Nelson MA (2003) Water quality model output uncertainty as affected by spatial resolution of input data. J Am Water Resour As 39(4):977–986

    Article  Google Scholar 

  • Freer J, Beven K, Ambroise B (1996) Bayesian estimation of uncertainty in runoff prediction and the value of data: an application of the GLUE approach. Water Resour Res 32(7):2161–2173

    Article  Google Scholar 

  • Geza M, McCray JE (2008) Effects of soil data resolution on SWAT model stream flow and water quality predictions. J Environ Manag 88(3):393–406

    Article  Google Scholar 

  • Lane LJ, Renard KG, Foster GR, Laflen JM (1992) Development and application of modern soil-erosion prediction technology—the USDA experience. Aust J Soil Res 30(6):893–912

    Article  Google Scholar 

  • Lenhart T, Fohrer N, Frede HG (2003) Effects of land use changes on the nutrient balance in mesoscale catchments. Phys Chem Earth 28(33–36):1301–1309

    Article  Google Scholar 

  • Liu JY, Deng XZ (2010) Progress of the research methodologies on the temporal and spatial process of LUCC. Chinese Sci Bull 55(14):1354–1362

    Article  Google Scholar 

  • Mednick AC (2010) Does soil data resolution matter? State Soil Geographic database versus Soil Survey Geographic database in rainfall-runoff modelling across Wisconsin. J Soil Water Conserv 65(3):190–199

    Article  Google Scholar 

  • Motovilov YG, Gottschalk L, Engeland K, Rodhe A (1999) Validation of a distributed hydrological model against spatial observations. Agric For Meteorol 98:257–277

    Article  Google Scholar 

  • Mukundan RD, Radcliffe E, Risse LM (2010) Spatial resolution of soil data and channel erosion effects on SWAT model predictions of flow and sediment. J Soil Water Conserv 65(2):92–104

    Article  Google Scholar 

  • Muttiah RS, Wurbs RA (2002) Scale-dependent soil and climate variability effects on watershed water balance of the SWAT model. J Hydrol 256(3–4):264–285

    Article  Google Scholar 

  • Nachtergaele F, Velthuizen H, Verelst L et al (2008). Harmonized world soil database. Food and Agriculture Organization of the United Nations

  • Neitsch SL, Arnold JG, Kiniry JR, Williams JR, King KW (2005). Soil and water assessment tool: theoretical documentation. Available in the website http://swat.tamu.edu/documentation/

  • Opere AO, Okello BN (2011) Hydrologic analysis for river Nyando using SWAT. Hydrol Earth Syst Sc 8(1):1765–1797

    Article  Google Scholar 

  • Peschel JM, Haan PK, Lacey RE (2006) Influences of soil dataset resolution on hydrologic modelling. J AM Water Resour As 42(5):1371–1389

    Article  Google Scholar 

  • Romanowicz AA, Vanclooster M, Rounsevell M, La Junesse I (2005) Sensitivity of the SWAT model to the soil and land use data parameterization: a case study in the Thyle catchment, Belgium. Ecol Model 187(1):27–39

    Article  Google Scholar 

  • Shi XZ, DS Y, Warner ED, Pan XZ, Petersen GW, Gong ZG, Weindorf DC (2004) Soil database of 1:1,000,000 digital soil survey and reference system of the Chinese genetic soil classification system. Soil Horizons 45:129–136

    Article  Google Scholar 

  • Shi XZ, Yu DS, Warner ED, Sun WX, Petersen GW, Gong ZT, Lin H (2006a) Cross-reference system for translating between genetic soil classification of China and soil taxonomy. Soil Sci Soc Am J 70:78–63

    Article  Google Scholar 

  • Shi XZ, DS Y, Yang GX, Wang HJ, Sun WX, GH D, Gong ZT (2006b) Cross-reference benchmarks for correlating the genetic soil classification of China and Chinese soil taxonomy. Pedosphere 16(2):147–153

    Article  Google Scholar 

  • Shi XZ, DS Y, SX X, Warner ED, Wang HJ, Sun WX (2010) Cross-reference for relating genetic soil classification of China with WRB at different scales. Geoderma 155(3):344–350

    Article  Google Scholar 

  • Thieken AH, Lucke A, Diekkruger B, Richter O (1999) Scaling input data by GIS for hydrological modelling. Hydrol Process 13(4):611–630

    Article  Google Scholar 

  • Van Griensven A, Meixner T, Grunwald S, Bishop T, Diluzio M, Srinivasan R (2006) A global sensitivity analysis tool for the parameters of multi-variable catchment models. J Hydrol 324(1–4):10–23

    Article  Google Scholar 

  • Wang X, Melesse AM (2006) Effects of STATSGO and SSURGO as inputs on SWAT model’s snowmelt simulation. J Am Water Resour As 42(5):1217–1236

    Article  Google Scholar 

  • Williams JR, Renard KG, Dyke PT (1983) A new method for assessing the effect of erosion on productivity—the EPIC model. J Soil Water Conserv 38(5):381–383

    Google Scholar 

  • Willmott CJ (1981) On the validation of models. Phys Geogr 2(2):184–194

    Google Scholar 

  • Yang J, Reichert P, Abbaspour KC, Xia J, Yang H (2008) Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China. J Hydrol 358(1–2):1–23

    Article  Google Scholar 

  • Yang X, Ren L, Singh VP, Liu X, Yuan F, Jiang S, Yong B (2012) Impacts of land use and land cover changes on evapotranspiration and runoff at Shalamulun River watershed, China. Hydrol Res 43(1–2):23–37

    Article  Google Scholar 

  • Ye XC, Zhang Q, Viney NR (2011) The effect of soil data resolution on hydrological processes modelling in a large humid watershed. Hydrol Process 25(1):130–140

    Article  Google Scholar 

Download references

Acknowledgment

This paper is funded by a project named as “Impacts of Agricultural Irrigation on Water Resources and Hydrological Cycle in Huang-Huai-Hai watershed under future Climate Scenarios (No.2013-RC-04)”, which is supported by the State Key Laboratory of Earth Surface Processes and Resource Ecology of Beijing Normal University. We are grateful to the Environmental & Eco-logical Science Data Center for West China and China Meteorological Data Sharing Service System for their help in providing data.

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  1. College of Resources, Hebei University of Engineering, Handan, Hebei, 056038, China

    Anzhou Zhao

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  1. Anzhou Zhao
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Correspondence to Anzhou Zhao.

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Zhao, A. Effect of different soil data on hydrological process modeling in Weihe River basin of Northwest China. Arab J Geosci 9, 664 (2016). https://doi.org/10.1007/s12517-016-2695-0

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