Near - Surface Soil Moisture Assimilation for Quantifying Effective Soil Hydraulic Properties under Different Hydroclimatic Conditions

39 S oil hydraulic parameters are essential input to most hydrologic and climatic models (Mohanty et al., 2002; Mohanty and Zhu, 2007). Th ey are used to defi ne the hydraulic characteristics of the soil vital in modeling soil moisture and fl ux in the unsaturated zone near the land–atmosphere boundary. At the scale of model applications, it is very important to defi ne the appropriate parameter values to characterize the eff ective hydraulic behavior of the soil system (Wood, 1994; Vrugt et al., 2004). Th ese so-called eff ec-tive soil hydraulic parameters (Zhu and Mohanty, 2003; Jhorar et al., 2004) are not always available for practical applications. At the fi eld scale, the eff ective soil hydraulic properties are usually defi ned using a bottom-up approach wherein point-scale soil hydraulic data are scaled up using similar media scaling approaches. In these methods, scaling factors are derived and used to defi ne sets of scaled soil hydraulic properties for both θ(h) and K(h), where θ is soil moisture, K is hydraulic conductivity, and h is the pressure head Bottom-up approaches like this require extensive soil hydraulic data to establish the reference soil hydraulic functions and the statistical characteristics of the scaling factors, therefore limiting their application in larger scale hydrologic and hydroclimatic modeling. Th e spatial variability of the soil hydraulic properties within a large climatic model grid can be also accounted for by using appropriate spatial averaging of local-scale soil hydraulic parameters In larger-scale hydrologic modeling, the soil system can be considered as an equivalent homogenous unit described by a set of eff ective soil hydraulic parameters (Feddes et al., 1993a; Wood, 1994). Th is assumption is attractive to explore since a top-down approach can be developed to estimate these eff ective parameters based on inversion of remote sensing data. Feddes et al. (1993b) proposed the use of hydrologic variables derived from remote sensing as conditioning criteria for regional inverse modeling to defi ne these eff ective parameters. Evapotranspiration (ET)-based approaches evolved from this framework (e.g., Jhorar et al., 2002, 2004; Ines and Droogers, 2002a,b) by taking advantage of the improved methodologies in estimating ET from remote sensing data numerically explored the existence of these eff ective parameters with an ET-based inverse modeling approach in which ET simulated by forward modeling was matched iteratively with ET simulated by inverse modeling using a gradient-based search algorithm to optimize selected sets …