Compound events and associated impacts in China.

Owing to amplified impacts on human society and ecosystems, compound events (or extremes) have attracted ample attention in recent decades. China is particularly vulnerable to compound events due to the fast warming rate, dense populations, and fragile ecological environment. Recent studies have demonstrated tangible effects of climate change on compound events with mounting impacts on the economy, agriculture, public health, and infrastructure in China, posing unprecedented threats that are increasingly difficult to manage. Here, I synthesize recent progress in studies of compound events and associated impacts in China. Several lines of evidence indicate an increase in the frequency and intensity of multiple types of compound events across China. Future directions in studying compound events in China are suggested, including investigating extremes from a compound perspective, modeling compound events in the Anthropocene, quantitative evaluations of risks, and holistic adaptation measures of compound events.

Drought propagation under global warming: Characteristics, approaches, processes, and controlling factors.

Drought is a costly natural hazard with far-reaching impacts on agriculture, ecosystem, water supply, and socio-economy. While propagating through the water cycle, drought evolves into different types and affects the natural system and human society. Despite much progress made in recent decades, a synthesis of the characteristics, approaches, processes, and controlling factors of drought propagation is still lacking. We bridge this gap by reviewing the recent progress of drought propagation and discussing challenges and future directions. We first introduce drought propagation characteristics (e.g., response time scale, lag time), followed by different approaches, including statistical analysis and hydrological modeling. The recent progress in the propagation from meteorological drought to different types of drought (agricultural drought, hydrological drought, and ecological drought) is then synthesized, including the basic process, commonly used indicators, data sources, and main findings of drought propagation characteristics. Different controlling factors of drought propagations, including climate (e.g., aridity, seasonality, and anomalies of meteorological variables), catchment properties (e.g., slope, elevation, land cover, aquifer, baseflow), and human activities (e.g., reservoir operation and water diversion, irrigation, and groundwater abstraction), are then summarized. Challenges in drought propagation include the discrepancy in drought indicators (and approaches) and difficulty in characterizing the full propagation process and isolating influencing factors. Future analysis of drought propagation should shift from single indicators to multiple indicators, from individual drivers to combined drivers, from uni-directional analysis to feedbacks, from hazards to impacts, and from stationary to nonstationary assumptions. This review is expected to be useful for drought prediction and management across different regions under global warming.

Systematic assessment of the development and recovery characteristics of hydrological drought in a semi-arid area.

Studies have documented the significant effect of various factors on hydrological drought events. However, few studies have quantified drought's development and recovery process under environmental changes. This study focused on identifying hydrological drought's development and recovery characteristics and their potential causes in a typical semi-arid area. The Standardized Streamflow Index (SSI) was used as a metric for hydrological droughts, while the run theory was applied to identify the development and recovery processes of droughts. Changes in observed (human disturbed scenario) and simulated (natural scenario) droughts by employing the SWAT (Soil and Water Assessment Tool) model were also investigated from 1970 to 2016. The "simulated-observed" approach was used to assess the impacts of human regulations on hydrological drought development and recovery characteristics. Results showed that hydrological droughts occurred mainly during 1980-1990 and 2000-2016. In the natural condition, drought duration and intensity were higher, while lower severity in the drought recovery stage than development stage was observed. The drainage characteristics of the basin played the most critical role in the development and recovery characteristics of drought, which were also influenced by climatic conditions. Human activities had exacerbated recent natural hydrological drought. When considering the contribution of human activities, the reservoir operation was the dominant anthropic factor affected the development and recovery process of drought in the study area. Under the effects of reservoir regulation, long-duration hydrological droughts became rare. Moreover, the recovery ability of drought had been weakened. The effects of the reservoir were progressively crucial gradually. Although the water got from the river by the reservoir had been reduced, the negative impact on aggravating drought remains stronger than the reservoir was initially constructed. The results of our study will help improve the optimal management of reservoirs in semi-arid areas and enhance drought early warning and forecasting system.

Influences of Shifted Vegetation Phenology on Runoff Across a Hydroclimatic Gradient.

Climate warming has changed vegetation phenology, and the phenology-associated impacts on terrestrial water fluxes remain largely unquantified. The impacts are linked to plant adjustments and responses to climate change and can be different in different hydroclimatic regions. Based on remote sensing data and observed river runoff of hydrological station from six river basins across a hydroclimatic gradient from northeast to southwest in China, the relative contributions of the vegetation (including spring and autumn phenology, growing season length (GSL), and gross primary productivity) and climatic factors affecting the river runoffs over 1982-2015 were investigated by applying gray relational analysis (GRA). We found that the average GSLs in humid regions (190-241 days) were longer than that in semi-humid regions (186-192 days), and the average GSLs were consistently extended by 4.8-13.9 days in 1982-2015 period in six river basins. The extensions were mainly linked to the delayed autumn phenology in the humid regions and to advanced spring phenology in the semi-humid regions. Across all river basins, the GRA results showed that precipitation (r = 0.74) and soil moisture (r = 0.73) determine the river runoffs, and the vegetation factors (VFs) especially the vegetation phenology also affected the river runoffs (spring phenology: r = 0.66; GSL: r = 0.61; autumn phenology: r = 0.59), even larger than the contribution from temperature (r = 0.57), but its relative importance is climatic region-dependent. Interestingly, the spring phenology is the main VF in the humid region for runoffs reduction, while both spring and autumn growth phenology are the main VFs in the semi-humid region, because large autumn phenology delay and less water supply capacity in spring amplify the effect of advanced spring phenology. This article reveals diverse linkages between climatic and VFs, and runoff in different hydroclimatic regions, and provides insights that vegetation phenology influences the ecohydrology process largely depending on the local hydroclimatic conditions, which improve our understanding of terrestrial hydrological responses to climate change.

Quantifying likelihoods of extreme occurrences causing maize yield reduction at the global scale.

A variety of weather and climate extremes (e.g., droughts, heatwaves) can lead to negative impacts on crop yields and food security. It is thus important to understand likelihoods of extreme occurrences causing crop yield reduction for enhanced resilience of the food system. Here, we investigate the likelihood of occurrences of dry, hot, and compound dry-hot conditions causing crop yield reduction for ten maize-producing countries based on climate observations and country-level maize yields for the period 1961-2016. The likelihood of occurrences of different extremes causing maize yield reduction is quantified using a multivariate statistical model. Results show that the multivariate model performs well in quantifying the likelihood of extreme occurrences (i.e., dry, hot and compound dry-hot conditions) causing maize yield reduction. Overall, the likelihood of occurrences of the above three conditions leading to yield reduction varies among ten maize-producing countries and that of compound dry-hot condition is the highest for most countries, which is shown to be closely related to the precipitation-temperature dependence of each country. Moreover, the likelihood of compound dry-hot occurrences becomes higher as the severity of crop yield reduction increases. These findings highlight significant impacts of compound dry-hot conditions on maize yield reduction and provide valuable information for formulating effective agricultural measures under global warming.

Probabilistic evaluation of the impact of compound dry-hot events on global maize yields.

Weather and climate extremes, such as droughts and hot extremes, may result in marked damages to crop yields and threaten regional and global food security. Understanding the relationship between climate extremes and crop yields is of critical importance for food security under a changing climate. The objective of this study is to investigate the probabilistic variability of maize yields with respect to compound dry-hot events, which has been shown to be more stressful to crops compared with individual dry or hot events. A multivariate model is first constructed to model the joint behavior of the dry condition, hot condition, and crop yields. The response of crop yields under different dry, hot, and compound dry-hot conditions at national and global scales is then investigated based on the conditional distribution. For the major maize producing countries (top 5), the probability of maize yield reduction could increase by from 0.07 to 0.31 (from 0.04 to 0.31) when the individual extreme drought (extreme hot) conditions changed to compound dry-hot conditions. The probabilistic evaluation of compound dry-hot events' impacts on maize yields is expected to provide useful insights for the mitigation of compound events and their impacts under a changing climate.

Variations of compound precipitation and temperature extremes in China during 1961-2014.

Concurrent precipitation and temperature extremes usually have significant impacts on the society, economy and ecosystem. Changes in precipitation or temperature extremes in China have been extensively studied; however, less attention has been paid to their concurrence (or compound extremes) to date. This study explores the historical variations of compound extremes including dry/warm, dry/cold, wet/warm, and wet/cold combinations based on monthly precipitation and temperature observations during summer and winter from 1961 to 2014 over China. Results show that there is a significant increase in the frequency of compound dry/warm and wet/warm extremes while a decrease in compound dry/cold and wet/cold extremes for the period 1988-2014 relative to 1961-1987. In addition, statistically significant increase in the spatial extent exists in compound dry/warm and wet/warm extremes, while the areas affected by the compound dry/cold and wet/cold extremes present a decrease across China, which is shown to be partly related to the large-scale circulation patterns. The results of this study could improve our understanding of changes of compound precipitation and temperature extremes from a multivariate perspective.

Rainwater characteristics and interaction with atmospheric particle matter transportation analyzed by remote sensing around Beijing.

Air pollution in Beijing has attracted much more attentions, and multiple regulations have been enacted since 2013. Based on the close link between the atmospheric particle matter concentration and the deposited load in rainwater, 336 rainwater samplings with seven parameters (pH, NH4+-N, NO3--N, P, S, Cu and Cd) at five-minute intervals in 2013 and 2014 were compared. The field monitoring and the temporal patterns analysis revealed a positive development of air quality. The lesser composition of coal in the energy consumption and the effective control of traffic emission were found. The average Aerosol Optical Depth (AOD) value around the sampling point during the 7 sampling rainfall events in 2014 was 2.855, which was higher than that in 2013 (1.807). It reflected the washing effect of rain on atmospheric particulates and highlighted the urban non-point source pollution effected by atmospheric deposition. AOD was demonstrated to perform well in reflecting regional air quality. A trajectory analysis conducted by HYSPLIT model in conjunction with the spatial distribution of AOD in the Beijing-Tian-Hebei (BTH) region depicted paths of air pollutants from long-range transport. The dominant trace was to the south of region. Cities around BTH were provided with different emission-reducing targets. Both Inner Mongolia and Henan province were suggested to control agricultural emissions. Shanxi, Shandong and cities around Bohai Bay should supervise the energy consuming industries. Furthermore, NO3--N was introduced to be an indicator of effect of the regional joint prevention and control in the future.

Exposure inequality assessment for PM2.5 and the potential association with environmental health in Beijing.

Fine particulate matter (PM2.5) pollution exposure has an adverse impact on public health, and some vulnerable social groups suffer from unfair exposure. Few studies have been conducted to estimate and to compare the exposure and inequality of different residential demographics at multiple time scales. This study assessed the exposures level of age and education subgroups on the whole city and the exposure inequalities of these subgroups within a concentration interval area for PM2.5 pollution at multiple time scales in Beijing in 2015. The potential association of PM2.5 with cancer morbidity was also explored through spatial analysis. Comparing the model performance of the ordinary kriging (OK) interpolation method with that of the land use regression (LUR) model method, the OK method was applied to estimate the PM2.5 concentrations at 1 km resolution. The exposure and inequality assessments for PM2.5 pollution were conducted by calculating the population-weighted exposure level and the inequality index, respectively. The spatial correlation of PM2.5 with cancer morbidity was investigated by spatial autocorrelation and grey correlation degree analysis. Overall, for the highest 1-h concentration, older people (age ≥ 60) and residents with tertiary education were the most disproportionately exposed to PM2.5. For the higher PM2.5 concentration during the annual average, spring, autumn and winter periods, exposures to PM2.5 were disproportionately high for children (age ≤ 4) and residents with primary or secondary education. Moreover, exposures to PM2.5 were disproportionately low for the illiterate due to their geographical distribution characteristics. Additionally, the spatial distribution of cancer morbidity was similar to the spatial pattern of PM2.5, manifesting a potential spatial association between PM2.5 and cancer morbidity. These findings provide scientific support for air pollution exposure assessments and environmental epidemiology.

Using river sediments to analyze the driving force difference for non-point source pollution dynamics between two scales of watersheds.

The formation and transportation processes of non-point source (NPS) pollution varied among the studied watersheds in the Northeastern China, so we hypothesized that the driving force behind NPS pollution followed the spatial scale effect. With a watershed outlet sedimentary flux analysis and a distributed NPS pollution loading model, we investigated the temporal dynamics of NPS and the differences in driving forces. Sediment core samples were collected from two adjacent watersheds, the smaller Abujiao watershed and the larger Naoli watershed. The natural climatic conditions, long-term variations in the distribution of land use, soil properties and tillage practices were the same in the two watersheds. The vertical distributions of total nitrogen, total phosphorus, Zn and As at 1-cm intervals in the section showed clear differences between the watersheds. There were higher concentrations of total nitrogen and total phosphorus in the larger watershed, but the heavy metals were more concentrated in the smaller watershed. Lead-210 (210Pb) analyses and the constant rate of supply model provided a dated sedimentary flux, which was correlated with the corresponding yearly loading of NPS total nitrogen and total phosphorus in the two watersheds. The total phosphorus showed a stable relationship in both watersheds with an R2 value that ranged from 0.503 to 0.682. A rose figure comparison also demonstrated that the pollutant flux in the sediment was very different in the two watersheds, which had similar territorial conditions and different hydrological patterns. Redundancy analysis further indicated that expanding paddy areas had a large impact on the sedimentary flux of nitrogen and phosphorus in the smaller watershed, but precipitation had a direct impact on NPS loading in the larger watershed. We concluded that the spatial scale effect affected the NPS pollution via the transport processes in the waterway, which was mainly influenced by branch length and drainage density.

Combined impacts of land use and soil property changes on soil erosion in a mollisol area under long-term agricultural development.

Soil erosion exhibits special characteristics in the process of agricultural development. Understanding the combined impacts of land use and soil property changes on soil erosion, especially in the area under long-term agricultural cultivations, is vital to watershed agricultural and soil management. This study investigated the temporal-spatial patterns of the soil erosion based on a modified version of Universal Soil Loss Equation (USLE) and conducted a soil erosion contribution analysis. The land use data were interpreted from Landsat series images, and soil properties were obtained from field sampling, laboratory tests and SPAW (Soil-Plant-Atmosphere-Water) model calculations. Over a long period of agricultural development, the average erosion modulus decreased from 187.7tkm-2a-1 in 1979 to 158.4tkm-2a-1 in 2014. The land use types were transformed mainly in the reclamation of paddy fields and the shrinking of wetlands on a large scale. Most of the soils were converted to loam from silty or clay loam and the saturated hydraulic conductivity (Ks) of most soil types decreased by 1.11% to 43.6%. The rapidly increasing area of 49.8km2 of paddy fields together with the moderate decrease of 14.0km2 of forests, as well as Ks values explained 87.4% of the total variance in soil erosion. Although changes in soil physical and water characteristics indicated that soil erosion loads should have become higher, the upsurge in paddy fields played an important role in mitigating soil erosion in this study area. These results demonstrated that land use changes had more significant impacts than soil property changes on soil erosion. This study suggested that rational measures should be taken to extend paddy fields and control the dry land farming. These findings will benefit watershed agricultural targeting and management.

Farmland-atmosphere feedbacks amplify decreases in diffuse nitrogen pollution in a freeze-thaw agricultural area under climate warming conditions.

Although climate warming and agricultural land use changes are two of the primary instigators of increased diffuse pollution, they are usually considered separately or additively. This likely lead to poor decisions regarding climate adaptation. Climate warming and farmland responses have synergistic consequences for diffuse nitrogen pollution, which are hypothesized to present different spatio-temporal patterns. In this study, we propose a modeling framework to simulate the synergistic impacts of climate warming and warming-induced farmland shifts on diffuse pollution. Active accumulated temperature response for latitudinal and altitudinal directions was predicted based on a simple agro-climate model under different temperature increments (△T0 is from 0.8°C to 1.4°C at an interval of 0.2°C). Spatial distributions of dryland shift to paddy land were determined by considering accumulated temperature. Different temperature increments and crop distributions were inserted into Soil and Water Assessment Tool model, which quantified the spatio-temporal changes of nitrogen. Warming led to a decrease of the annual total nitrogen loading (2.6%-14.2%) in the low latitudes compared with baseline, which was larger than the decrease (0.8%-6.2%) in the high latitudes. The synergistic impacts amplified the decrease of the loading in the low and high latitudes at the sub-basin scale. Warming led to a decrease of the loading at a rate of 0.35kg/ha/°C, which was lower than the synergistic impacts (3.67kg/ha/°C) at the watershed level. However, warming led to the slight increase of the annual averaged NO3 (LAT) (0.16kg/ha/°C), which was amplified by the synergistic impacts (0.22kg/ha/°C). Expansion of paddy fields led to a decrease in the monthly total nitrogen loading throughout the year, but amplified an increase in the loading in August and September. The decreased response in spatio-temporal nitrogen patterns is substantially amplified by farmland-atmosphere feedbacks associated with farmland shifts in response to warming.

Global integrated drought monitoring and prediction system.

Drought is by far the most costly natural disaster that can lead to widespread impacts, including water and food crises. Here we present data sets available from the Global Integrated Drought Monitoring and Prediction System (GIDMaPS), which provides drought information based on multiple drought indicators. The system provides meteorological and agricultural drought information based on multiple satellite-, and model-based precipitation and soil moisture data sets. GIDMaPS includes a near real-time monitoring component and a seasonal probabilistic prediction module. The data sets include historical drought severity data from the monitoring component, and probabilistic seasonal forecasts from the prediction module. The probabilistic forecasts provide essential information for early warning, taking preventive measures, and planning mitigation strategies. GIDMaPS data sets are a significant extension to current capabilities and data sets for global drought assessment and early warning. The presented data sets would be instrumental in reducing drought impacts especially in developing countries. Our results indicate that GIDMaPS data sets reliably captured several major droughts from across the globe.