spatio-temporal variability of global soil moisture...
TRANSCRIPT
Carsten Montzka, Kathrina Rötzer, Harry Vereecken Research Centre Jülich,
Institute of Bio- and Geosciences: Agrosphere (IBG 3), Jülich, Germany
Spatio-temporal variability of global soil moisture products
• Soil moisture plays a key role for water and energy exchange between soil and atmosphere
• Soil moisture products from different sources (active/passive microwave RS, models) perform differently in specific regions
• For further use of different soil moisture products a more detailed analysis about advantages and drawbacks of specific methods is necessary
• Further use of soil moisture products can be: • Hydrological/weather forecast model calibration • Soil moisture data assimilation • Drought/flood monitoring/forecast • …
⇒Overall aim: Closing the catchment-scale water balance
Background
SMOS
soil moisture [m³/m³]
ERA ASCAT
overall mean soil moisture:
0.16 m³/m³ 0.21 m³/m³ 0.26 m³/m³
𝜃𝜃𝑛𝑛 = 1𝑇𝑇
�𝜃𝜃𝑛𝑛𝑛𝑛
𝑇𝑇
𝑛𝑛=1
𝜃𝜃𝑛𝑛: temporal mean of soil moisture for every grid point 𝑛𝑛 over all timesteps 𝑡𝑡
Rötzer et al. 2015
Evaluation: Temporal means (2010 - 2012)
• Investigation of spatial and temporal variability of SMOS and ASCAT soil moisture products
• Comparison to modeled ERA Interim soil moisture product from ECMWF (European Centre for Medium Range Weather Forecast)
• Objectives:
Comparison of the products, determination of influences on the soil moisture patterns of the products
Investigation of suitability of the soil moisture products for specific regions
Determination of influencing factors on „real“ soil moisture distribution
Spatio-temporal variability
1. Calculation of mean relative difference 𝛿𝛿𝑛𝑛 for every pixel 𝑛𝑛 through
𝛿𝛿𝑛𝑛 = 1𝑇𝑇�
𝜃𝜃𝑛𝑛𝑛𝑛 − 𝜃𝜃𝑛𝑛�̅�𝜃𝑛𝑛
𝑇𝑇
𝑛𝑛=1
2. Ranking of 𝛿𝛿𝑛𝑛 from lowest to highest
3. Comparison of ranks for the different products through correlation analysis
=> Provides information on the similarity of soil moisture distribution of the different products
Spatio-temporal variability
Af America Tropical Rainforest
Aw America / Africa Tropical Savannah
BW Asia Arid Desert
Adapted from Peel et al. (2007): Updated world Köppen-Geiger climate classification map. Hydrol. Earth Syst. Sci. 11, 1633-1644.
Koeppen-Geiger climate classification
Correlation of ranks of mean relative differences
Global correlation of ranks of MRDs of the three soil moisture products for different climate classes. The lines are just for increasing readability and do not imply any functional relationship.
Over the entire world, the products show reasonable correlation coefficients of 0.34 (ERA/SMOS), 0.44 (SMOS/ASCAT), and 0.79 (ERA/ASCAT) => the overall soil moisture patterns are similar.
Soil moisture variability across scales
Investigation of the variability across scales of global soil moisture products
Soil moisture variability across scales
Soil moisture variability across scales
Underestimation of soil moisture variance of global soil moisture products for sub-continental studies
Wüstebach China
Spatio-temporal variability: PC Analysis
Spatio-temporal variability: PC Analysis Mean sm=0.178 Mean std sm=0.050
Graf et al. 2014
Spatio-temporal variability: PC Analysis Wüstebach China
From small scale observations we know that the shape of the PC-SMmean curves is related to variability of hydraulic properties (Qu et al., 2015 ) => The aim is to predict the variability of hydraulic properties in larger catchments
Wüstebach Nile
Stockinger et al. 2014
Soil moisture–runoff relationship
Wüstebach Huang He
Stockinger et al. 2014
Soil moisture–runoff relationship
Wüstebach Yangtse
Stockinger et al. 2014
Soil moisture–runoff relationship
• Spatio-temporal variability – Structural differences between different global soil moisture products – Overall soil moisture patterns are similar
• Soil moisture variability across scales – Global soil moisture products underestimate soil moisture variability on sub-
continental scale – only continental-scale applications suggested for SMOS, ASCAT
• Principal component analysis – Potential to inversely estimate soil parameter heterogeneity – Potential to predict runoff by soil moisture analysis
• Soil moisture-runoff relationship – Evaluation of relationship for storage estimation of a basin
=> Closing the water cycle on catchment scale
Conclusions
• Graf, A., H. R. Bogena, C. Drue, H. Hardelauf, T. Putz, G. Heinemann, and H. Vereecken (2014), Spatiotemporal relations between water budget components and soil water content in a forested tributary catchment, Water Resources Research, 50(6), 4837-4857.
• Qu, W., H. R. Bogena, J. A. Huisman, J. Vanderborght, M. Schuh, E. Priesack, and H. Vereecken (2015), Predicting subgrid variability of soil water content from basic soil information, Geophysical Research Letters, 42(3), 789-796.
• Rötzer, K., C. Montzka, and H. Vereecken (2015), Spatio-temporal variability of global soil moisture products, Journal of Hydrology, 522, 187-202.
• Stockinger, M. P., H. R. Bogena, A. Lucke, B. Diekkruger, M. Weiler, and H. Vereecken (2014), Seasonal soil moisture patterns: Controlling transit time distributions in a forested headwater catchment, Water Resources Research, 50(6), 5270-5289.
References