Evaluation of the SMOS and SMAP soil moisture products under different vegetation types against two sparse in situ networks over arid mountainous watersheds, Northwest China

Assessment of the suitability of satellite soil moisture products at large scales is urgently needed for numerous climatic and hydrological researches, particularly in arid mountainous watersheds where soil moisture plays a key role in landatmosphere exchanges. This study presents evaluation of the SMOS(L2) and SMAP(L2_P_E and L2_P) products against ground-based observations from the Upstream of the Heihe River Watershed in situ Soil Moisture Network(UHRWSMN) and the Ecological and Hydrological Wireless Sensor Network(EHWSN) over arid high mountainous watersheds, Northwest China.Results show that all the three products are reliable in catching the temporal trend of the in situ observations at both point and watershed scales in the study area. Due to the uncertainty in brightness temperature and the underestimation of effective temperature, the SMOS L2 product and both the SMAP L2 products show "dry bias" in the high, cold mountainous area. Because of the more accurate brightness temperature observations viewing at a constant angle and more suitable estimations of single scattering albedo and optical depth, both the SMAP L2 products performed significantly better than the SMOS product.Moreover, comparing with station density of in situ network, station representation is much more important in the evaluation of the satellite soil moisture products. Based on our analysis, we propose the following suggestions for improvement of the SMOS and SMAP product suitability in the mountainous areas: further optimization of effective temperature; revision of the retrieval algorithm of the SMOS mission to reduce the topographic impacts; and, careful selection of in situ observation stations for better representation of in situ network in future evaluations. All these improvements would lead to better applicability of the SMOS and SMAP products for soil moisture estimation to the high elevation and topographically complex mountainous areas in arid regions.

Applicability of cosmic-ray neutron sensor for measuring soil moisture at the agricultural-pastoral ecotone in northwest China

Accurate monitoring of soil moisture is crucial in hydrological and ecological studies.Cosmic-ray neutron sensors(CRNS)measure area-average soil moisture at field scale,filling a spatial scale gap between in-situ observations and remote sensing measurements.However,its applicability has not been assessed in the agricultural-pastoral ecotone,a data scarce semiarid and arid region in Northwest China(APENC).In this study,we calibrated and assessed the CRNS(the standard N0 method)estimates of soil moisture.Results show that Pearson correlation coefficient,RP,and the root mean square error(RMSE)between the CRNS soil moisture and the gravimetric soil moisture are 0.904 and less than 0.016 m3 m–3,respectively,indicating that the CRNS is able to estimate the area-average soil moisture well at our study site.Compared with the in-situ sensor network measurements(ECH2O sensors),the CRNS is more sensitive to the changes in moisture in its footprint,which overestimates and underestimates the soil moisture under precipitation and dry conditions,respectively.The three shape parameters a0,a1,a2 in the standard calibration equation(N0 method)are not well suited to the study area.The calibrated parameters improved the accuracy of the CRNS soil moisture estimates.Due to the lack of low gravimetric soil moisture data,performance of the calibrated N0 function is still poor in the extremely dry conditions.Moreover,aboveground biomass including vegetation biomass,canopy interception and widely developed biological soil crusts adds to the uncertainty of the CRNS soil moisture estimates.Such biomass impacts need to be taken into consideration to further improve the accuracy of soil moisture estimation by the CRNS in the data scarce areas such as agricultural-pastoral ecotone in Northwest China.