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Surface conductance (G s ) is a key parameter in estimating land surface evapotranspiration (ET) and difficult to determine. Here we proposed an approach for determining G s according to the stomatal conductance of sunlit and shaded leaves that is estimated from their respective gross primary production (GPP) with the Ball-Berry model. Central to this approach, GPP is separately simulated for sunlit and shaded leaves with a revised two-leaf light use efficiency model. We tested the approach at 17 FLUXNET sites with seven different vegetation types. The revised two-leaf light use efficiency model outperforms its predecessor in estimating GPP at most sites. As to G s estimation, although our proposed algorithm has higher Akaike information criterion values than has the model estimating G s using vegetation indices, it was able to capture G s variations at all sites, while models estimating G s using leaf area index and vegetation indices performed poor at some sites. The proposed algorithm also improves ET estimation, indicated by lower Akaike information criterion, higher determination coefficient (R 2 ), and lower root mean square error of simulated daily ET for both calibration and validation data sets. This study demonstrates the usefulness of differentiating sunlit and shaded leaves in improving canopy conductance and ET estimates.

Abstract:In the Indian monsoon region, frequent cloud cover in the rainy season results in less valid satellite observations during the vegetation growth period, making it difficult to extract land surface phenology (LSP). Even worse, many valid but humid observations were misidentified as clouds in the MODIS cloud mask, causing severe gaps in the LSP product. Using a refined cloud detection approach to separate clear-sky and cloudy observations, this study found that potentially valid observations during the vegetation growth period could be identified. Furthermore, the varied vegetation growth trajectories cannot be well-fitted by a global curve-fitting approach, but can be modelled by using the locally adjusted cubic-spline capping approach, which performed well for any seasonal patterns. Applying this approach, the start of growing season (SOS) was determined with 9.18% of vegetation growth amplitude between the maximum and minimum NDVI to generate the SOS product (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016). The valid percentage of this regional product largely increased from 29.30% to 69.76% compared with the MCD12Q2 product, and its reliability was approximate to that of deciduous broadleaf forest in North America and Europe. This product could serve as a basis for understanding the response of terrestrial ecosystems to the changing Indian monsoon.

Soil water content (SWC) plays a crucial role in the hydrological cycle and ecological restoration in arid and semi-arid areas. Studying the temporal stability of SWC spatial distribution is a requirement for the dynamic monitoring of SWC and the optimization of water resource management. The SWC in a Pinus tabulaeformis Carr. forest on the slope of the Loess Plateau of China were analyzed in five soil layers (0–100 cm with an interval of 20 cm) in the rainy and dry seasons from July 2014 to November 2017. The mean SWC was estimated and the main factors affecting the temporal stability of the SWC were further analyzed. Results showed that the SWC had strong temporal stability during the two seasons for several consecutive years. The temporal stability of SWC and the number of representative locations varied with season and depth. The elevation, soil total phosphorus (STP), clay, silt, or sand content of the representative locations approached the corresponding mean value of the study area. A single representative location accurately represented the mean SWC for the five depths in the rainy and dry seasons (RMSE <2%; rainy season: 0.81 < R2 < 0.94; dry season: 0.63 < R2 < 0.83; p < 0.01). The mean relative difference (MRD) and the relative difference standard deviation (SDRD) changed with the seasons and were significantly correlated with elevation, root density, and sand and silt content in two seasons (p < 0.05). Elevation, root density, and sand content were the main factors influencing the change of SWC temporal stability in different seasons. The results provide scientific guidance to monitor SWC by using a small number of locations and enrich our understanding of the factors affecting the temporal stability of SWC in the rainy and dry seasons of the Loess Plateau of China.