Soil microbes play a crucial role in ecosystem function. Here, the effects of soil and water conservation measures on soil microbial community structures, biodiversity, and co-occurrence networks are investigated and compared. We sampled soils at three different depths (0–10 cm, 10–20 cm and 20–40 cm) in a citrus orchard that uses long-term soil and water conservation measures, which includes Bermuda grass strip intercropping (BS), Bermuda grass full coverage (BF), Radish–soybean crop rotation strip intercropping (RS) and clear tillage orchards (CT). Results demonstrated that BS and BF yields a significant increase in bacterial richness and diversity of fungal in soils, while BF contains more beneficial microbial taxa, especially those with degrading and nutrient cycling capabilities. Microbial community structures differed significantly among the applied measures. In addition, co-occurrence networks under BS, BF and RS were more complex and robust than that of CT, and the stability of the network in BF was the highest. Microbial interactive stability and potential interactions in bacterial networks were stronger than those of fungi. The distribution of dominant phyla showed that Chloroflexi and Ascomycota dominated the different soil and water conservation measures. Proteobacteria and Ascomycota are revealed to be keystone species in bacterial networks and fungal networks, respectively, while Proteobacteria was the keystone species in microbial networks. Though the relative abundance of Chloroflexi turned out to have increased among the four measures, the relative abundance for Proteobacteria, Acidobacteria and Actinobacteria all decreased along the soil profile, with Acidobacteria under BS to be an exception. Soils under BS and BF had higher total nitrogen, microbial biomass carbon and organic carbon than CT and RS. Organic carbon(C) and total nitrogen(N) in soil were the major drivers of these bacterial community patterns, while there was no significant correlation between them and fungi. Overall, BF increases soil nutrients and microbial diversity, and also promotes ecological stability and interrelations among microbial taxa that collectively improve soil quality in the citrus orchard studied. Therefore, we recommended BF to be an ideal application for citrus orchards of southeast China.

Residential energy consumption (REC) is now the second largest energy sector in China. However, decoupling analysis of REC has not received enough attention. Here, we explore the decoupling relationship between REC and economic growth in urban and rural Guangdong from 2000 to 2017. First, we use the Tapio decoupling model to study the decoupling state. Then, key drivers affecting the decoupling were explored by combining the Tapio decoupling model with the Log-mean Divisa Index (LMDI) method. Finally, the decoupling efforts were evaluated by using the decoupling efforts model. The main results are as follows: (1) The decoupling state in urban regions was better than that in rural regions. Urban regions experienced weak decoupling (WD) in most years during 2000–2017, while expansive negative decoupling (END) mostly was seen in rural regions. (2) The per capita income effect was the most important driver inhibiting decoupling in Guangdong urban and rural regions. The energy intensity effect was the biggest driver promoting decoupling in urban Guangdong, followed by the family size effect. In contrast, the family size effect exerted the dominant influence on accelerating the decoupling in rural Guangdong. Overall, the household effect inhibited decoupling in urban regions, but promoted decoupling in rural regions. (3) The decoupling efforts results suggest that the energy efficiency improvement played a major role in the decoupling efforts of urban Guangdong, while the decrease of family size in rural Guangdong was the leading contributor to the decoupling efforts.

Understanding nodal tidal characteristics is essential for accurate long-term tidal prediction. Observational nodal evolution of tides is mainly based on tide gauge records in coastal areas which are limited in time and space, thus impeding coherent determinations of basin-wide patterns of tidal variability. In this paper, we indicate the potential of satellite altimeter data to investigate 18.61-year nodal modulations of main constituents in the Gulf of Tonkin. Three tide gauges and multi-source satellite altimeter observations (TOPEX/Poseidon, Jason1, Jason2, and Jason3) revealed that 18.61-year nodal cycles in tidal amplitudes have noticeable deviations from the equilibrium tidal theory in the Gulf of Tonkin. In general, M₂ and N₂ nodal modulations are anomalously larger than theoretical values while K₂, K₁, and O₁ nodal modulations are noticeably smaller than theoretical values. Compared to point-based tide gauges, satellite altimeter records can provide basin-wide features of nodal modulations of main constituents. Although overlapping geographical blocks are applied to eliminate the effect of tidal alias originated from long-period sampling intervals, the estimation of nodal cycles of minor constituents are still questionable. Nevertheless, the methods described here provide a strong foundation for future research on time-varying tidal dynamics using the combination of tide gauges and satellite altimeter data.

Sentinel-1 synthetic aperture radar (SAR) is one of the most advanced open-access satellite systems available, benefitting from its capability for earth observation under all-weather conditions. In this study, more than 280 Sentinel-1 SAR images are used to derive significant wave heights (H_s) of the sea surface using a polarization-enhanced methodology. Two study areas are selected: one is located near Hawai’i in a deep water region, and the other is in transitional water off the U.S. west coast, where the U.S. National Oceanic and Atmospheric Administration (NOAA) buoy data are available for validations. The enhanced H_s retrieval methodology utilizes dual-polarization SAR image data with strong non-Bragg radar backscattering, resulting in a better estimate of the cut-off wavelength than from those using single-polarization SAR data. The new method to derive H_s is applied to SAR images from 2017 taken from both deep water (near Hawai’i) and coastal water locations (off the U.S. West coast). The assessments of the retrieved H_s from SAR images suggest that the dual-polarization methodology can reduce the estimated H_s RMSE by 24.6% as compared to a single-polarization approach. Long-term reliability of the SAR image-derived H_s products based on the new methodology is also consolidated by large amount of in-situ buoy observations for both the coastal and deep waters.

Chinese coastal topography has changed significantly over the last two decades due to human actions such as the development of extensive land reclamation projects. Newly-reclaimed lands typically have low elevations (<10 m) and often experience severe ground subsidence. These conditions, combined with the more frequent occurrence of extreme sea-level events amplified by global climate change, lead to an increased risk of flooding of coastal regions. This work focuses on twelve Chinese coastal areas that underwent significant changes from 2000 to 2015 in their environments, correlated to relevant land reclamation projects. First, the ground changes between 2000 and 2015 were roughly computed by comparing the TanDEM-X and the Shuttle Radar Topography Mission (SRTM) digital elevation models of the investigated areas. These results indicate that six of the analyzed coastal zones have reclaimed more than 200 km² of new lands from 2000 to 2015, with five of them in northern China. Second, we focused specifically on the city of Shanghai, and characterized the risk of flood in this area. To this purpose, two independent sets of synthetic aperture radar (SAR) data collected at the X- and C-band through the COSMO-SkyMed (CSK) and the European Copernicus Sentinel-1 (S-1) sensors were exploited. We assumed that the still extreme seawater depth is chi-square distributed, and estimated the probability of waves overtopping the coast. We also evaluated the impact on the territory of potential extreme flood events by counting the number of very-coherent objects (at most anthropic, such as buildings and public infrastructures) that could be seriously affected by a flood. To forecast possible inundation patterns, we used the LISFLOOD-FP hydrodynamic model. Assuming that an extreme event destroyed a given sector of the coastline, we finally computed the extent of the flooded areas and quantified its impact in terms of coherent structures potentially damaged by the inundation. Experimental results showed that two coastline segments located in the southern districts of Shanghai, where the seawalls height is lower, had the highest probability of wave overtopping and the most significant density of coherent objects potentially subjected to severe flood impacts.

Remote sensing technologies are extensively applied to prevent, monitor, and forecast hazardous risk conditions in the present-day global climate change era. This paper presents an overview of the current stage of remote sensing approaches employed to study coastal and delta river regions. The advantages and limitations of Earth Observation technology in characterizing the effects of climate variations on coastal environments are also presented. The role of the constellations of satellite sensors for Earth Observation, collecting helpful information on the Earth’s system and its temporal changes, is emphasized. For some key technologies, the principal characteristics of the processing chains adopted to obtain from the collected raw data added-value products are summarized. Emphasis is put on studying various disaster risks that affect coastal and megacity areas, where heterogeneous and interlinked hazard conditions can severely affect the population.