Surface soil moisture (SM) plays a fundamental role in energy and water partitioning in the soil–plant–atmosphere continuum. A reliable and operational algorithm is much needed to retrieve regional surface SM at high spatial and temporal resolutions. Here, we provide an operational framework of estimating surface SM at fine spatial resolutions (using visible/thermal infrared images and concurrent meteorological data) based on a trapezoidal space defined by remotely sensed vegetation cover (F_c) and land surface temperature (LST). Theoretical solutions of the wet and dry edges were derived to achieve a more accurate and effective determination of the F_c/LST space. Subjectivity and uncertainty arising from visual examination of extreme boundaries can consequently be largely reduced. In addition, theoretical derivation of the extreme boundaries allows a per-pixel determination of the VI/LST space such that the assumption of uniform atmospheric forcing over the entire domain is no longer required. The developed approach was tested at the Tibetan Plateau Soil Moisture/Temperature Monitoring Network (SMTMN) site in central Tibet, China, from August 2010 to August 2011 using Moderate Resolution Imaging Spectroradiometer (MODIS) Terra images. Results indicate that the developed trapezoid model reproduced the spatial and temporal patterns of observed surface SM reasonably well, with showing a root-mean-square error of 0.06 m³·m⁻³ at the site level and 0.03 m³·m⁻³ at the regional scale. In addition, a case study on 2 September 2010 highlighted the importance of the theoretically calculated wet and dry edges, as they can effectively obviate subjectivity and uncertainties in determining the F_c/LST space arising from visual interpretation of satellite images. Compared with Land Surface Models (LSMs) in Global Land Data Assimilation System-1, the remote sensing-based trapezoid approach gave generally better surface SM estimates, whereas the LSMs showed systematic underestimation. Sensitivity analyses suggested that the trapezoid method is most sensitive to field capacity and temperature but less sensitive to other meteorological observations and parameters.

Pulses of rainfall are particularly pivotal in controlling plant physiological processes in ecosystems controlled by limited water, and the response of desert plants to rainfall is a key to understanding the responses of desert ecosystems to global climatic change. We used a portable photosynthesis system to measure the responses of the diurnal course of photosynthesis, light-response curves, and CO₂-response curves of two desert shrubs (Nitraria sphaerocarpa Maxim. and Calligonum mongolicum Turcz) to a rainfall pulse in a desert-oasis ecotone in northwestern China. The photosynthetic parameters, light- and CO₂-response curves differed significantly before and after the rainfall pulse. Their maximum net photosynthetic rate (P _N) values were 23.27 and 32.92 μmol(CO₂) m⁻² s⁻¹ for N. sphaerocarpa and C. mongolicum, respectively, with corresponding maximum stomatal conductance (g _s) values of 0.47 and 0.39 mol(H₂O) m⁻² s⁻¹. The P _N of N. sphaerocarpa after the rainfall was 1.65 to 1.75 times the value before rainfall, whereas those of C. mongolicum increased to approximately 2 times the prerainfall value, demonstrating the importance of the desert plants response by improving their assimilation rate to precipitation patterns under a future climate.