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Comparison of NLDAS-2 Simulated and NASMD Observed Daily Soil Moisture. Part II: Impact of Soil Texture Classification and Vegetation Type Mismatches

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  • 1 National Centers for Environmental Prediction/Environmental Modeling Center, and I. M. System Group at NCEP/EMC, College Park, Maryland
  • | 2 National Centers for Environmental Prediction/Environmental Modeling Center, College Park, Maryland
  • | 3 National Centers for Environmental Prediction/Environmental Modeling Center, and I. M. System Group at NCEP/EMC, College Park, Maryland
  • | 4 Department of Geography, Texas A&M University, College Station, Texas
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Abstract

In this second part of a two-part paper, the impacts of soil texture and vegetation type misclassification and their combined effect on soil moisture, evapotranspiration, and total runoff simulation are investigated using the Noah model. The results show that these impacts are significant for most regions and soil layers, although they vary depending on soil texture classification, vegetation type, and season. The use of site-observed soil texture classification and vegetation type in the model does not necessarily improve anomaly correlations and reduce mean absolute error for soil moisture simulations. Instead, results are mixed when examining all regions and soil layers. This is attributed to the compensation effects (e.g., effect of ill-calibrated model parameters), as Noah has been more or less calibrated with model-specified soil texture classification and vegetation type. The site-based analysis shows that Noah can reasonably simulate the variation of daily evapotranspiration, soil moisture, and total runoff when soil texture classification (vegetation type) is corrected from loam (forest) to clay (grasslands) or vice versa. This suggests that the performance of Noah can be further improved by tuning model parameters when site-observed soil texture and vegetation type are used.

Corresponding author address: Youlong Xia, IMSG at NCEP/EMC, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD 20740. E-mail: youlong.xia@noaa.gov

Abstract

In this second part of a two-part paper, the impacts of soil texture and vegetation type misclassification and their combined effect on soil moisture, evapotranspiration, and total runoff simulation are investigated using the Noah model. The results show that these impacts are significant for most regions and soil layers, although they vary depending on soil texture classification, vegetation type, and season. The use of site-observed soil texture classification and vegetation type in the model does not necessarily improve anomaly correlations and reduce mean absolute error for soil moisture simulations. Instead, results are mixed when examining all regions and soil layers. This is attributed to the compensation effects (e.g., effect of ill-calibrated model parameters), as Noah has been more or less calibrated with model-specified soil texture classification and vegetation type. The site-based analysis shows that Noah can reasonably simulate the variation of daily evapotranspiration, soil moisture, and total runoff when soil texture classification (vegetation type) is corrected from loam (forest) to clay (grasslands) or vice versa. This suggests that the performance of Noah can be further improved by tuning model parameters when site-observed soil texture and vegetation type are used.

Corresponding author address: Youlong Xia, IMSG at NCEP/EMC, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD 20740. E-mail: youlong.xia@noaa.gov
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