Using a New Criterion to Identify Sites for Mean Soil Water Storage Evaluation

Abstract

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.

Profile distribution of soil–water content and its temporal stability along a 1340-m long transect on the Loess Plateau, China

“…In the second method, Hu et al (2010a) proposed a new index of mean absolute bias error (MABE). Rearranging Eq.…”

“…8a), indicating the lack of dependence on depth. Locations with an SDRD and/or MABE under 5% are considered to be temporally stable (Starks et al, 2006;Hu et al, 2010a). The number of temporally stable locations increased with depth (Fig.…”

“…The concept of temporal stability of spatial patterns of SWC was first introduced by Vachaud et al (1985), who defined it as "the time-invariant association between spatial location and classical statistical parameters of a given soil property". The temporal stability of SWC has been investigated for different soil depths (Zhang and Shao, 2013;Heathman, 2009), land uses (Hu et al, 2010a;Williams et al, 2009;Lin, 2006), scales (Martínez-Fernández and Ceballos, 2003;Jia and Shao, 2013;Hu et al, 2010b;Gao et al, 2011), regions (Biswas and Si, 2011b;Jia et al, 2013a;Zhang and Shao, 2013), measurement periods (Guber et al, 2008;de Rosnay, et al, 2009;Zhao, et al, 2010;Biswas and Si, 2011b;Liu and Shao, 2014), and measuring instruments (Jacobs et al, 2004;Gao and Shao, 2012b;Wang et al, 2013;Penna et al, 2013). The characteristics of the temporal stability of SWC vary with depth, but little is known about the precise changes of SWC and its temporal stability in soil profiles due to coarse division of previous soil profiling.…”

“…Some studies have proposed that mean SWC can be estimated directly by identifying representative locations based on certain principles (Hu et al, 2010a;Gao and Shao, 2012a;Jia et al, 2013a), which may not always apply. As a consequence, many studies have investigated alternative approaches by attempting to find representative locations using other properties that can affect SWC, but the identification of representative locations remains inconsistent.…”

Spatio-temporal variability and temporal stability of water contents distributed within soil profiles at a hillslope scale

“…With regard to scale, the temporal stability of soil moisture has been identified at the watershed (Hu et al, 2009), hillslope (Gao and Shao, 2012c) and plot scales (Jia et al, 2013a). Hu et al (2010) have developed a new index termed the mean absolute bias error to identify the temporal stability locations (TSL). Gao and Shao (2012b) have explored the feasibility of identifying TSL by using soil properties and elevation.…”