Using a New Criterion to Identify Sites for Mean Soil Water Storage Evaluation
- Wei Huab,
- Mingan Shao *cd and
- Klaus Reichardte
- a Key Lab. of Water Cycle and Related Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
b Graduate Univ., Chinese Academy of Sciences, Beijing 100039, China
c State Key Lab. of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A & F Univ
d Institute of Soil And Water Conservation, Chinese Academy of Sciences, Ministry of Water Resource, Yangling 712100, Shaanxi, China
e Lab. of Soil Physics, Center for Nuclear Energy in Agriculture, Univ. of São Paulo, CEP 13418-900, CP 96, Piracicaba, SP, Brazil
Establishing a few sites in which measurements of soil water storage (SWS) are time stable significantly reduces the efforts involved in determining average values of SWS. This study aimed to apply a new criterion—the mean absolute bias error (MABE)—to identify temporally stable sites for mean SWS evaluation. The performance of MABE was compared with that of the commonly used criterion, the standard deviation of relative difference (SDRD). From October 2004 to October 2008, SWS of four soil layers (0–1.0, 1.0–2.0, 2.0–3.0, and 3.0–4.0 m) was measured, using a neutron probe, at 28 sites on a hillslope of the Loess Plateau, China. A total of 37 SWS data sets taken over time were divided into two subsets, the first consisting of 22 dates collected during the calibration period from October 2004 to September 2006, and the second with 15 dates collected during the validation period from October 2006 to October 2008. The results showed that if a critical value of 5% for MABE was defined, more than half the sites were temporally stable for both periods, and the number of temporally stable sites generally increased with soil depth. Compared with SDRD, MABE was more suitable for the identification of time-stable sites for mean SWS prediction. Since the absolute prediction error of drier sites is more sensitive to changes in relative difference in terms of mean SWS prediction, the sites of wet sectors should be preferable for mean SWS prediction for the same changes in relative difference.Please view the pdf by using the Full Text (PDF) link under 'View' to the left.
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