Evaluation of SMAP Core Validation Site Representativeness Errors Using Dense Networks of In Situ Sensors and Random Forests

In order to validate its soil moisture products, the NASA Soil Moisture Active Passive (SMAP) mission utilises sites with permanent networks of in situ soil moisture sensors maintained by independent calibration and validation partners in a variety of ecosystems around the world. Measurements from each core validation site (CVS) are combined in a weighted average to produce an estimate of soil moisture at a 33-km scale that represents the SMAP’s radiometer-based retrievals. Since upscaled estimates produced in this manner are dependent on the weighting scheme applied, an independent method of quantifying their biases is needed.Here,we present one such method that uses soil moisture measurements taken from a dense, but temporary, network of soil moisture sensors deployed at each CVS to train a random forests regression expressing soil moisture in terms of a set of spatial variables. The regression then serves as an independent source of upscaled estimates against which permanent network upscaled estimates can be compared in order to calculate bias statistics.This method,which offers a systematic and unified approach to estimate bias across a variety of validation sites, was applied to estimate biases at four CVSs. The results showed that the magnitude of the uncertainty in the permanent network upscaling bias can sometimes exceed 80% of the upper limit on SMAP’s entire allowable unbiased root-mean-square error(ubRMSE).Such large CVS bias uncertainties could make it more difficult to assess biases in soil moisture estimates from SMAP

Effects of canopy size and water stress over the crop coefficient of a "Tempranillo" vineyard in south-western Spain

This paper describes the assessment of the crop coefficient of an irrigated Tempranillo vineyard measured in a weighing lysimeter during 5 years in south-western Spain. During the first year of the study (2006), young vines displayed a different canopy growth compared to the subsequent years. From 2007 to 2010, vines experienced 2 years with no restriction in water supply, and two other years with short periods of crop water stress. Basal crop coefficient (K cb) started from 0. 2 at bud-break until 1. 0 at full development in every year, being this maximum management-dependent. K cb showed a good correlation with canopy size indices, which allows to interpolate these results to a wide range of commercial vine systems that are usually managed with lower vegetation size. Moreover, a simple linear model of crop evapotranspiration reduction with relative water content is presented, allowing the estimation of consumptive water use under deficit irrigation conditions. © 2012 Springer-Verlag.This work was funded by the Spanish Ministry of Science and Innovation through the projects INIA (RTA 2005-0038-C06-05) and (RTA-2008-00037-C04-03), by the project CONSOLIDER CSD2006-0067 and by the European Regional Development Fund (ERDF).Peer Reviewe