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The C-band radar instruments onboard the two-satellite GMES Sentinel-1 constellation provide global measurements with short revisit time (about six days) and medium spatial resolution (5 × 20 m), which are appropriate for watershed scale hydrological applications. This paper aims to explore the potential of Sentinel-1 for estimating surface soil moisture using a multi-temporal approach. To this end, a linear mixed effects (LME) model was developed over Poyang Lake ungauged zone, using time series Sentinel 1A and 1B images and soil moisture ground measurements from 15 automatic observation sites. The model assumed a linear relationship that varied with both time and space between soil moisture and backscattering coefficient (SM-s0). Results showed that three LME models developed with different polarized s0 images all meet the European Space Agency (ESA) accuracy requirement for GMES soil moisture product (≤5% in volume), with the vertical transmit and vertical receive (VV) polarized model achieving the best performance. However, the SM-s0 relationship was found to depend strongly on space, making it difficult to predict absolute soil moisture for each grid. Therefore, a relative soil moisture index was then proposed to correct for site effect. When compared with those of the linear fixed effects model, the soil moisture indices predicted by the LME model captured the temporal dynamics of measured soil moisture better, with the overall R2 and cross-validated R2 being 0.68 and 0.64, respectively. These results indicate that the LME model can be effectively applied to estimate soil moisture from multi-temporal Sentinel-1 images, which is useful for monitoring flood and drought disasters, and for improving stream flow prediction over ungauged zones. [ABSTRACT FROM AUTHOR]

In forested watersheds, forest changes and climatic variability have been commonly recognized as two major drivers for streamflow variations. Previous research has separated their relative contributions but mainly focused on either deforestation and climate or reforestation and climate, but rarely with single studies on both. This study used the Meijiang watershed (6983·2 km2), situated in the upper reach of the Poyang Lake basin, as an example to quantify how climate and forest changes (both deforestation and reforestation) consecutively affect streamflow dynamics. Two methods, namely modified double-mass curves and sensitivity-based approach, were used in this study. Two breakpoints (years 1968 and 1985) with significant annual streamflow changes were detected, and together with the control period, they were then used to define three distinct periods: the control (1957-1967), deforestation (1968-1984) and reforestation (1985-2006) periods. Our results show that in the deforestation period, the average annual streamflow increment attributed to deforestation was 112·78 mm year−1, while the annual streamflow variation attributed to climate variability was −111·39 mm year−1. In the reforestation period, the average annual streamflow decrease caused by reforestation was −51·04 mm year−1, while the annual streamflow variation attributed to climate variability was 52·52 mm year−1. The sensitivity-based approach also provided similar results. The positive and negative values in the streamflow changes suggest offsetting effects between forest changes and climate variability in both deforestation and reforestation periods. The similar magnitudes of streamflow changes demonstrate that the hydrological effects of forest changes can be as great as those caused by climate change. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]