scholarly journals Scale Dependence and Time Stability of Nonstationary Soil Water Storage in a Hummocky Landscape Using Global Wavelet Coherency

10.5772/52340 ◽  
2013 ◽  
Author(s):  
Asim Biswas ◽  
Bing Cheng
Keyword(s):  
Soil Water ◽  
Water Storage ◽  
Scale Dependence ◽  
Soil Water Storage ◽  
Time Stability ◽  
Wavelet Coherency

Evaluation of time stability indices for soil water storage upscaling

2012 ◽  
Vol 475 ◽  
pp. 229-241 ◽  
Author(s):  
Wei Hu ◽  
Lindsay K. Tallon ◽  
Bing Cheng Si
Keyword(s):  
Soil Water ◽  
Water Storage ◽  
Soil Water Storage ◽  
Time Stability ◽  
Stability Indices

Scale and location dependent time stability of soil water storage in a maize cropped field

CATENA ◽  
2020 ◽  
Vol 188 ◽  
pp. 104420
Author(s):  
Duminda N. Vidana Gamage ◽  
Asim Biswas ◽  
Ian B. Strachan
Keyword(s):  
Soil Water ◽  
Water Storage ◽  
Soil Water Storage ◽  
Time Stability

scholarly journals Regression Models for Soil Water Storage Estimation Using the ESA CCI Satellite Soil Moisture Product: A Case Study in Northeast Portugal

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 37
Author(s):  
Tomás de Figueiredo ◽  
Ana Caroline Royer ◽  
Felícia Fonseca ◽  
Fabiana Costa de Araújo Schütz ◽  
Zulimar Hernández
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Regression Models ◽  
Meteorological Data ◽  
Water Storage ◽  
Model Performance ◽  
Soil Water Balance ◽  
Soil Water Storage ◽  
The Relationship

The European Space Agency Climate Change Initiative Soil Moisture (ESA CCI SM) product provides soil moisture estimates from radar satellite data with a daily temporal resolution. Despite validation exercises with ground data that have been performed since the product’s launch, SM has not yet been consistently related to soil water storage, which is a key step for its application for prediction purposes. This study aimed to analyse the relationship between soil water storage (S), which was obtained from soil water balance computations with ground meteorological data, and soil moisture, which was obtained from radar data, as affected by soil water storage capacity (Smax). As a case study, a 14-year monthly series of soil water storage, produced via soil water balance computations using ground meteorological data from northeast Portugal and Smax from 25 mm to 150 mm, were matched with the corresponding monthly averaged SM product. Linear (I) and logistic (II) regression models relating S with SM were compared. Model performance (r2 in the 0.8–0.9 range) varied non-monotonically with Smax, with it being the highest at an Smax of 50 mm. The logistic model (II) performed better than the linear model (I) in the lower range of Smax. Improvements in model performance obtained with segregation of the data series in two subsets, representing soil water recharge and depletion phases throughout the year, outlined the hysteresis in the relationship between S and SM.

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