No abstract

Many works suggest that the intensity of extreme precipitation might be changing under the background of global warming. Because of the importance of extreme precipitation in the Yellow–Huaihe and Yangtze–Huaihe River basins of China and to compare the spatial difference, the generalized Pareto distribution (GPD) function is used to fit the daily precipitation series in these basins and an estimate of the extreme precipitation spatial distribution is presented. At the same time, its long-term trends are estimated for the period between 1951 and 2004 by using a generalized linear model (GLM), which is based on GPD. High quality daily precipitation data from 215 observation stations over the area are used in this study. The statistical significance of the trend fields is tested with a Monte Carlo experiment based on a two-dimensional Hurst coefficient, H2. The spatial distribution of the shape parameter of GPD indicates that the upper reaches of the Huaihe River (HuR) basin have the largest probability of extreme rainfall events, which is consistent with most historical flood records in this region. Spatial variations in extreme precipitation trends are found and show significant positive trends in the upper reaches of Poyang Lake in the Yangtze River (YaR) basin and a significant negative trend in the mid- to lower reaches of the Yellow River (YeR) and Haihe River (HaR) basins. The trends in the HuR basin and the lower reaches of Poyang Lake in the YaR basin are nearly neutral. All trend fields are significant at the 5% level of significance from the Monte Carlo experiments.

Controversial results in the drying and wetting trends were found with different indices and potential evapotranspiration calculations in previous studies. Here we make an attempt to find robust conclusions of drying and wetting trends over regions by coherent results of various independent indices by using China (1961–2012) as a study area. Precipitation, statistical, and physical drought indices, including the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI) and self‐calibrating PDSI (sc_PDSI), with both the Penman‐Monteith (PM) and Thornthwaite (TH) approaches in PDSI calculation are considered. In consequence, four PDSI variants of PDSI_pm, sc_PDSI_pm, PDSI_th, and sc_PDSI_th are involved. To illustrate regional characteristics, six climatic regions based on the Köppen climate classification are defined. At the national scale, precipitation and SPEI indicate wetting trends but all PDSI variants have drying trends. On the other hand, these six indices exhibit coherent results in five of these six regions. Increases in wetness occur in arid region and the Qinghai‐Tibet Plateau. Drying trends were found in semiarid and cold and temperate semihumid regions. Only the humid region in southeastern China is seen to have increasing precipitation and SPEI and decreasing PDSI variants. From the perspective of climatic regions, the drying trends mainly occur in the transition regions between the humid and arid regions in China. The spatial pattern of changes in droughts could be categorized by climatic zones, and the changes at regional scale are robust based on these six indices.

No abstract

To meet the growing demand for food, land is being managed to be more productive using agricultural intensification practices, such as the use of irrigation. Understanding the specific environmental impacts of irrigation is a critical part of using it as a sustainable way to provide food security. However, our knowledge of irrigation effects on climate is still limited to daytime effects. This is a critical issue to define the effects of irrigation on warming related to greenhouse gases (GHGs). This study shows that irrigation led to an increasing temperature (0.002• C year −1 ) by enhancing nighttime warming (0.009• C year −1 ) more than daytime cooling (−0.007 • C year −1 ) during the dry season from 1961-2004 over the North China Plain (NCP), which is one of largest irrigated areas in the world. By implementing irrigation processes in regional climate model simulations, the consistent warming effect of irrigation on nighttime temperatures over the NCP was shown to match observations. The intensive nocturnal warming is attributed to energy storage in the wetter soil during the daytime, which contributed to the nighttime surface warming. Our results suggest that irrigation could locally amplify the warming related to GHGs, and this effect should be taken into account in future climate change projections.

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Sediment microbial communities from plain river networks exert different effects on pollutant transformation and migration in lake basins. In this study, we examined millions of Illumina reads (16S rRNA gene amplicons) to compare lake, lake wetland, and estuary bacterial communities through a technically consistent approach. Results showed that bacterial communities in the sampled lake sediments had the highest alpha-diversity (Group B), than in sampled lake wetland sediments and estuary sediments. Proteobacteria was the most abundant (more than 30%) phyla in all the sediments. The lake sediments had more Nitrospirae (1.63%-11.75%) and Acidobacteria (3.46%-10.21%) than the lake wetland and estuary sediments, and estuary sediments had a greater abundance of the phylum Firmicutes (mean of 22.30%). Statistical analysis (LEfSe) revealed that lake wetland sediments contained greater abundances of the class Anaerolineaceae, orders Xanthomonadales, Pseudomonadales, and genera Flavobacterium, Acinetobacter. The lake sediments had a distinct community of diverse primary producers, such as phylum Acidobacteria, order Ignavibacteriales, and families Nitrospiraceae, Hydrogenophilaceae. Total phosphorus and organic matter were the main factors influencing the bacterial communities in sediments from several parts of the lake wetland and river estuary (p < .05). The novel insights into basin pollution control in plain river networks may be obtained from microbial distribution in sediments from different basin regions.

Current understanding of volcanic effects on El Niño–Southern Oscillation in terms of eruption type and initial ocean condition (IOC) remains elusive. We use last‐millennium proxy reconstructions to show how volcanic impacts depend on eruption type and IOC. When the IOC is not a strong El Niño, it is likely that an El Niño will mature in the second winter following 79% (p < 0.01) of Northern Hemispheric eruptions and in the first winter following 81% (p < 0.01) of tropical and 69% of Southern Hemispheric eruptions. For a strong El Niño‐IOC, no significant El Niño will occur in the first winter after any type of eruption. The eruptions need to be large enough to cause these diverse effects. Our last‐millennium simulation confirms the IOC effect, except that a La Niña occurs in the first winter following most tropical eruptions due to overestimated volcanic cooling in the model.