Watershed runoff is essential for water management. However, runoff materials are lacking in poorly gauged catchments and not always accessible. Microwave remote sensing offers emerging capabilities for hydrological simulation. In this study based on multi-satellite retrievals for Global Precipitation Measurement (IMERG), Tropical Rainfall Measuring Mission (TRMM) products, and World Meteorological Organization (WMO) interpolated precipitation data, we simulated runoff using a variable infiltration capacity (VIC) model and studied the differences among the results. Then, we analyzed the impacts of the runoff on a moderate-resolution imaging spectroradiometer vegetation leaf area index (LAI) during dry seasons. The results showed that (1) IMERG V5 and TRMM products are capable of monitoring the night-day rainfall diurnal cycle and have higher correlations than the WMO daily observation interpolations. However, the WMO shows less overestimation of total precipitation than remote-sensing precipitation; (2) in the downstream, the TRMM shows better runoff simulation accuracy in the tributaries, and the WMO shows better results in the mainstreams. Therefore, at basin outlets in mainstreams, the Nash-Sutcliffe efficiency coefficients of monthly runoff by the WMO are higher than the simulations by the TRMM; (3) for the whole basin during dry seasons, the LAI variation is correlated with the outlet runoff, which is similar to the correlation with threeto six-month accumulated precipitation. TRMM products can be used to depict both precipitation deficit and runoff deficit, which cause vegetation variations. Our research suggests the potential of microwave precipitation products for detailed watershed runoff simulations and water management.Water 2019, 11, 818 2 of 15 vegetation conditions, such as the normalized difference vegetation index (NDVI), a measure of the greenness or vigor of vegetation. The higher its value, the larger the vegetation density is; a low NDVI indicates stressed or small-leaf vegetation [3]. However, the NDVI can often be saturated across densely vegetated regions or during high-growth periods [4], whereas the leaf area index (LAI) has been shown to be more effective for drought monitoring [5,6]. Previous studies have shown that the multi-temporal accumulation precipitation index has a strong correlation with vegetation response [7][8][9]. The evolution of meteorological hydrological factors affects vegetation growth [10]. Both factors-precipitation and runoff-that cause variations in the vegetation LAI, should be examined separately.Dynamic watershed runoff is essential to the water supply, irrigation management, and accurate flood prediction and control. River discharge at a site is an integrated signal of water cycle processes over the catchment. However, many catchments lack runoff observation. A hydrological model is an important tool to understand water cycle processing and to fill the gaps of runoff information. The simulation accuracy mainly depends on model mechanisms and data input. The th...

The Great Lakes Surface Temperature (GLST) is the key to understanding the effects of climate change on the Great Lakes (GL). This study provides the first techniques to retrieve pixel-based GLST under all sky conditions by merging skin temperature derived from the MODIS Land Surface Temperature (MOD11L2) and the MODIS Cloud product (MOD06L2) from 6 July 2001 to 31 December 2014, resulting in 18,807 scenes in total 9373 (9434) scenes for MOD11L2 (MOD06L2). The pixel-based GLST under all sky conditions was well-correlated with the in situ observations (R 2 = 0.9102) with a cool bias of´1.10˝C and a root mean square error (RMSE) of 1.39˝C. The study also presents the long-term trends of GLST. Contrary to expectations, it decreased slightly due to the impact of an anomalously cold winter in 2013-2014.

Abstract:This study provides the first technique to investigate the turbulent fluxes over the Great Lakes from July 2001 to December 2014 using a combination of data from satellite remote sensing, reanalysis data sets, and direct measurements. Turbulent fluxes including latent heat flux (Q E ) and sensible heat flux (Q H ) were estimated using the bulk aerodynamic approach, then compared with the direct eddy covariance measurements from the rooftop of three lighthouses-Stannard Rock Lighthouse (SR) in Lake Superior, White Shoal Lighthouse (WS) in Lake Michigan, and Spectacle Reef Lighthouse (SP) in Lake Huron. The relationship between modeled and measured Q E and Q H were in a good statistical agreement, for Q E , R 2 varied from 0.41 (WS), 0.74 (SR), and 0.87 (SP) with RMSE of 5.68, 6.93, and 4.67 W·m −2 , respectively, while Q H , R 2 ranged from 0.002 (WS), 0.8030 (SP) and 0.94 (SR) with RMSE of 6.97, 4.39 and 4.90 W·m −2 respectively. Both monthly mean Q E and Q H were highest in January for all lakes except Lake Ontario, which was highest in early December. The turbulent fluxes then sharply drop in March and are negligible during June and July. The evaporation processes continue again in August.

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