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

The characteristic of compound drought and saltwater intrusion events in the several major river estuaries worldwide

Compound Drought and Saltwater intrusion Events (CDSEs) refer to hydrologic drought and saltwater intrusion occurring simultaneously or consecutively in estuaries, and exacerbate the negative impacts resulting from an individual extreme event. CDSEs have been drawing increasing attention due to their potential adverse impacts on water resources, crop production, and food security. A new Standardized compound Drought and Saltwater intrusion Index (SDSI) was developed in this study to systematically detect changes in the severity of CDSEs in six estuaries (Little Back, Ebro, Rhine, Orange, Pearl River and Murray). The results illustrated that (1) compared to the Standardized Runoff Index (SRI), SDSI effectively characterizes and quantifies the occurrences and severity of CDSEs in major river estuaries worldwide. (2) Temporally, the SDSI trend varied across estuaries. Specifically, a decreasing trend was observed in the Little Back, Ebro, and Orange estuaries, with corresponding Zs values of -2.43, -3.63, and -3.23. (3) Spatially, moderate CDSEs occurred more frequently among different estuaries, and their frequency, duration and severity varied in different estuaries. Notably, Ebro, Rhine and Murray River estuaries had the highest probability of CDSEs, nearing 60%. Among them, the Murray Estuary had the longest average duration, spanning 7.68 months, and the highest severity was 5.94. (4) According to the contributions analysis, saltwater intrusion plays a dominant role in influencing SDSI severity, accounting for a substantial percentage (54%-95.30%) compared to runoff. Notably, the Orange Estuary experienced the greatest impact from saltwater intrusion (81.54%-95.30%), while the Murray Estuary had relatively equal contributions from hydrological drought and saltwater intrusion.

Compound drought and heat waves variation and association with SST modes across China

Compound drought and heatwaves (CDH) have garnered increasing attention because concurrent extreme events can exacerbate the harmful impacts caused by univariate extremes. However, various severities in CDH events and their relationships with sea surface temperature (SST) variations in China remain little understood. Here, we accurately identify CDH events and multi-aspect of characteristics using the standardized precipitation evapotranspiration index (SPEI) and the excess heat factor (EHF) during the extended summer (May-September) of 1961-2017. The evolution of multifaceted characteristics of CDH and their association with SST variation are further explored. The results suggest that the number, frequency, duration and intensity of regional CDH events show heterogeneous spatial patterns, with a significant increasing trend. A consistent abrupt transition in CDH characteristics averaged over China occurred in the period of 1993-1996. Mild and moderate CDHs occur more commonly in Northwest and North China, whereas severe CDHs are mainly found in central and eastern regions. Mild and moderate CDHs are more susceptible to SST modes than severe CDH, and there are strong positive correlations between mild and moderate CDH characteristics and SST variations in the northwest and northern regions. Compared to El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) plays a dominant role in the intensifications of mild and moderate CDH events. Regionally, the northwest and north have experienced longer, more frequent and severe CDH events during the positive phase of IOD. These findings reveal the divergent evolutions in CDH characteristics with various severities and inconsistent impacts of different SST modes on the compound events.

Impacts of climate change and anthropogenic stressors on runoff variations in major river basins in China since 1950

Runoff is one of the main components of hydrological cycle and an important index for water resources evaluation, understanding the runoff change and their causes is vital to water resource management. In the study, we analyzed the runoff change and the impacts of climate change and land use alteration on runoff variation based on natural runoff and previous studies in China. The results showed that there was a significant increasing trend in the annual runoff during 1961-2018 (p < 0.05), with change rate of 0.4 mm/a and abrupt point at 1999 across China, climate change dominated the runoff variation with a contribution of 54 %. In previous studies, the runoff of the major basins in China had a downward trend on the whole (-0.99 mm/a) except Continental River Basin (CRB) showed an increasing trend (0.25 mm/a), the abrupt points were mainly concentrated in 1991-2000, and human activity was the leading factor of runoff change with the contribution of 54 % across China. Human activity was the dominant factor of runoff change in Songhua and Liao River Basin (SLRB), Yellow River Basin (YRB), Hai River Basin (HRB) and Pearl River Basin (PRB), the contribution was >56 %, while climate change was the dominant factor of runoff change in Huai River Basin (HuRB), CRB, and Yangtze River Basin (YZRB). Overall, there was a significant correlation between runoff and precipitation, unused land, urban and grassland in China. We concluded that runoff change and the contribution of climate change and human activities varies greatly among different basins. The findings in this work can shed light on the quantitative understanding of runoff changes in national scale and offer a scientific basis for sustainable water management.

Spatiotemporal changes in summer days (SU25) in China from 1961 to 2017 and associated circulation factors

Understanding the spatiotemporal variations in climate extremes indices, as well as the influencing factors, is critical to the scientific response to climate change. The temporal and spatial variations of SU25 (annual count of days when daily maximum temperature > 25 °C) were discussed in this study, based on daily maximum temperature data from 2398 meteorological stations in China from 1961 to 2017. The contributions of associated large-scale circulation factors to SU25 were quantitatively assessed by using the geographical detector method (GMD). The overall spatial distribution of SU25 was marked by a considerable increase from north to south. The SU25 increased significantly over time, with the national SU25 increasing at a rate of 2.5 days/decade. The Tibet Plateau (TP) had the slowest growth rate, with an average increase rate of 1.4 days/decade. The Hurst values of SU25 in all the subregions were generally high, indicating that most stations of SU25 would continue to increase in the future. Except for TP, the tipping years of other subregions were concentrated in the 1990s, and SU25 increased after the years. Among the large-scale circulation factors affecting SU25 in each subregion, Atlantic Multidecadal Oscillation (AMO) played a major role in SU25 variability. As a whole, the result of the pairwise interaction of each circulation factor was mainly nonlinear enhancement. The joint contributions of multiple factors to SU25 were larger than the contribution of each individual factor.

Risk assessment and disease burden of extreme precipitation on hospitalizations for acute aortic dissection in a subtropical coastal Chinese city

Background

Extreme precipitation events are becoming more frequent due to climate change. The present study aimed to explore the impacts of extreme precipitation on hospitalizations for acute aortic dissection (AAD) and to identify susceptible populations and quantify the corresponding disease burden.

Methods

The present study used a distributed lag nonlinear model (DLNM) with a quasi-Poisson function to investigate the association between extreme precipitation (≥95th percentile) and the risk of hospitalizations for AAD from 2015 to 2020 in Shantou, Guangdong Province, China.

Results

The significant adverse effects of extreme precipitation (relative to no precipitation) on daily AAD hospitalizations lasted from lag 5 [relative risk (RR): 1.0318, 95% confidence interval (CI): 1.0067-1.0575] to lag 9 (RR: 1.0297, 95% CI: 1.0045-1.0555) and reached its maximum at lag 7 (RR: 1.0382, 95% CI: 1.0105-1.0665). Males and older adult individuals (≥60 years) were more susceptible to extreme precipitation. A total of 3.68% (118 cases) of AAD hospitalizations were due to extreme precipitation.

Conclusion

Extreme precipitation was significantly correlated with AAD hospitalizations. Government departments should actively implement extreme precipitation intervention measures to strengthen the protection of males and the older adult (≥60 years) and effectively reduce AAD hospitalizations.

Developing a novel framework to re-examine half a century of compound drought and heatwave events in mainland China

Compound drought and heatwave events (CDHEs) are more devastating than single drought or heatwave events and have gained widespread attention. However, previous studies have not investigated the impacts of the precipitation attenuation effect (PAE) (i.e., the effect of previous precipitation on the dryness and wetness of the current system is attenuated) and event merging (EM) (i.e., merging two CDHEs with short intervals into a single event). Moreover, few studies have assessed short-term CDHEs within monthly scales and their variation characteristics under different background temperatures. Here we propose a novel framework for assessing CDHEs on a daily scale and considering the PAE and EM. We applied this framework to mainland China and investigated the spatiotemporal variation of the CDHE indicators (spatial extent (CDHE_spa), frequency (CDHE_fre), duration (CHHE_dur), and severity (CDHE_sev)) from 1968 to 2019. The results suggested that ignoring the PAE and EM led to significant changes in the spatial distribution and magnitude of the CDHE indicators. Daily-scale assessments allowed for monitoring the detailed evolution of CDHEs and facilitated the timely development of mitigation measures. Mainland China experienced frequent CDHEs from 1968 to 2019 (except for the southwestern part of Northwest China (NWC) and the western part of Southwest China (SWC)), whereas, hotspot areas of CDHE_dur and CDHE_sev had a patchy distribution in different geographical subregions. The CDHE indicators were higher in the warmer 1994-2019 period than in the colder 1968-1993 period, but the rate of increase of the indicators was lower or there was a downward trend. Overall, CDHEs in mainland China have been in a state of remarkable continuous strengthening over the past half a century. This study provides a new quantitative analysis approach for CDHEs.

Evolution and prediction of drought-flood abrupt alternation events in Huang-Huai-Hai River Basin, China

Drought-flood abrupt alternation (DFAA) as a compound natural disaster can cause severe socioeconomic loss and environmental destruction. Under climate change, the Huang-Huai-Hai River Basin has experienced evident increases in temperature and variability of precipitation. However, the study of the evolution characteristics of DFAA in the Huang-Huai-Hai River Basin is limited and the risk of exposure to DFAA events under future climatic conditions should be comprehensively assessed. In this study, the DFAA events including drought to flood (DTF) and flood to drought (FTD) events in the Yellow River Basin (YRB), Huai River Basin (HuRB), and Hai River Basin (HaRB) are identified by the long-cycle drought-flood abrupt alternation index (LDFAI) and the temporal variation and spatial distribution of the number and intensity of DFAA events from 1961 to 2020 are examined. The 24 climate model simulations of Coupled Model Intercomparison Project Phase 6 (CMIP6) are used to evaluate the variation of DFAA events based on the bias-corrected method. The results show that both DTF and FTD events occurred >10 times in most areas of the Huang-Huai-Hai River Basin from 1961 to 2020, and severe DFAA events occurred more frequently in the HaRB. The occurrence of DTF events decreased and FTD events continuously increased in the YRB, while they showed opposite trends in the HuRB and HaRB. In the future, the Huang-Huai-Hai River Basin is projected to experience more DTF events under the SSP1-2.6 and SSP2-4.5 scenarios, while more FTD events under the SSP3-7.0 and SSP5-8.5 scenarios. Most areas in the Huang-Huai-Hai River Basin are projected to be at medium or high risk of the frequency and intensity of DFAA events under different future scenarios, especially in the central part of the YRB. These findings can provide scientific reference to the formulation of management policies and mitigation strategies.

Driving role of climatic and socioenvironmental factors on human brucellosis in China: machine-learning-based predictive analyses

BACKGROUND

Brucellosis is a common zoonotic infectious disease in China. This study aimed to investigate the incidence trends of brucellosis in China, construct an optimal prediction model, and analyze the driving role of climatic factors for human brucellosis.

METHODS

Using brucellosis incidence, and the socioeconomic and climatic data for 2014-2020 in China, we performed spatiotemporal analyses and calculated correlations with brucellosis incidence in China, developed and compared a series of regression and Seasonal Autoregressive Integrated Moving Average X (SARIMAX) models for brucellosis prediction based on socioeconomic and climatic data, and analyzed the relationship between extreme weather conditions and brucellosis incidence using copula models.

RESULTS

In total, 327,456 brucellosis cases were reported in China in 2014-2020 (monthly average of 3898 cases). The incidence of brucellosis was distinctly seasonal, with a high incidence in spring and summer and an average annual peak in May. The incidence rate was highest in the northern regions' arid and continental climatic zones (1.88 and 0.47 per million people, respectively) and lowest in the tropics (0.003 per million people). The incidence of brucellosis showed opposite trends of decrease and increase in northern and southern China, respectively, with an overall severe epidemic in northern China. Most regression models using socioeconomic and climatic data cannot predict brucellosis incidence. The SARIMAX model was suitable for brucellosis prediction. There were significant negative correlations between the proportion of extreme weather values for both high sunshine and high humidity and the incidence of brucellosis as follows: high sunshine, [Formula: see text] = -0.59 and -0.69 in arid and temperate zones; high humidity, [Formula: see text] = -0.62, -0.64, and -0.65 in arid, temperate, and tropical zones.

CONCLUSIONS

Significant seasonal and climatic zone differences were observed for brucellosis incidence in China. Sunlight, humidity, and wind speed significantly influenced brucellosis. The SARIMAX model performed better for brucellosis prediction than did the regression model. Notably, high sunshine and humidity values in extreme weather conditions negatively affect brucellosis. Brucellosis should be managed according to the "One Health" concept.

Causes for an extreme cold condition over Northeast Asia during April 2020

Although 2020 was the fourth warmest year on record in northern Asia, the cold condition in April 2020 caused severe damage to the agricultural and marine ecosystems in northeastern Asia. Previous studies have indicated that the dipole atmospheric circulation over Siberia and the East Sea (Japan Sea) produced this cold environment with strong northwesterly wind. However, the potential causes of the dipole circulation over northeastern Asia remain unclear. In this study, we found that the East Atlantic/Western Russia (EAWR) pattern and blocking combined to produce the atmospheric structure. The wave train originated from the vorticity forcing of northwestern/central Russia and propagated from Western Europe to the East Sea via the background westerly and northerly winds. In addition, the Siberian blocking days increased eleven times in April 2020 relative to the climatological average, and an easterly (westerly) anomaly was observed over Mongolia-northeastern China (northern Russia). The strong blocking and EAWR pattern led to the robust atmospheric dipole structure with a prevailing northerly flow in April 2020, thereby causing the extreme cold condition over northeastern Asia. Our results provide novel insights into the cause of extreme cold condition in April over northeastern Asia.

Effects of Land Cover Changes on Compound Extremes over West Africa Using the Regional Climate Model RegCM4

This study aims to characterize the impacts of the Sahel–Sahara interface reforestation on compound extremes in the Sahel region during the West African monsoon season (June–July–August–September, JJAS). For this purpose, we performed a simulation with the standard version of the RegCM4 model, and another simulation with the altered version of the same model, taking into account the incorporated forest. Results show that reforestation may strongly influence the frequency of individual extreme events (dry and warm days) by decreasing them over and off the reforested zone. The reduction in these extreme dry and warm days may be due partly to the strengthening of the atmospheric moisture content over most parts of the West African domain and the weakening of the sensible heat flux south of 16° N. The analysis also shows an increase in extreme wet days over and off the reforested zone, which could be associated partly with the strengthening of evapotranspiration over most parts of the West African domain, including the reforested area. The analysis of compound extremes shows a strong occurrence of the compound dry/warm mode over the northern Sahel for both runs, probably due to the weak precipitation recorded in this zone. Both experiments also simulated a strong compound wet/warm mode occurrence over the Sahel due to a high rainfall occurrence over this region. When comparing both runs, the impact of the reforestation was to decrease (increase) the compound extreme dry/warm (wet/warm) mode over the reforested zone. The dry/warm mode decrease is consistent with that of individual extreme dry and warm days, while the compound wet/warm mode increase may be driven by that of the extreme wet days. Finally, when considering the seasonal cycle, the dry/warm mode exhibits a more substantial decrease in the beginning (June–July, JJ) than during the peak of the West African summer monsoon season (August–September, AS). Moreover, reforestation similarly affects the compound wet/warm mode in JJ and AS by increasing it in the reforested region and decreasing it over the Southern Sahel (south of 15° N). This work suggests that reforestation may be a good solution for West African policymakers to mitigate climate change over the region and to develop better strategies for water resource management.

The Study on Compound Drought and Heatwave Events in China Using Complex Networks

Compound extreme events can severely impact water security, food security, and social and economic development. Compared with single-hazard events, compound extreme events cause greater losses. Therefore, understanding the spatial and temporal variations in compound extreme events is important to prevent the risks they cause. Only a few studies have analyzed the spatial and temporal relations of compound extreme events from the perspective of a complex network. In this study, we define compound drought and heatwave events (CDHEs) using the monthly scale standard precipitation index (SPI), and the definition of a heatwave is based on daily maximum temperature. We evaluate the spatial and temporal variations in CDHEs in China from 1961 to 2018 and discuss the impact of maximum temperature and precipitation changes on the annual frequency and annual magnitude trends of CDHEs. Furthermore, a synchronization strength network is established using the event synchronization method, and the proposed synchronization strength index (SSI) is used to divide the network into eight communities to identify the propagation extent of CDHEs, where each community represents a region with high synchronization strength. Finally, we explore the impact of summer Atlantic multidecadal oscillation (AMO) and Pacific decadal oscillation (PDO) on CDHEs in different communities. The results show that, at a national scale, the mean frequency of CDHEs takes on a non-significant decreasing trend, and the mean magnitude of CDHEs takes on a non-significant increasing trend. The significant trends in the annual frequency and annual magnitude of CDHEs are attributed to maximum temperature and precipitation changes. AMO positively modulates the mean frequency and mean magnitude of CDHEs within community 1 and 2, and negatively modulates the mean magnitude of CDHEs within community 3. PDO negatively modulates the mean frequency and mean magnitude of CDHEs within community 4. AMO and PDO jointly modulate the mean magnitude of CDHEs within community 6 and 8. Overall, this study provides a new understanding of CDHEs to mitigate their severe effects.

Population Exposure to Compound Droughts and Heatwaves in the Observations and ERA5 Reanalysis Data in the Gan River Basin, China

The frequency, duration, and magnitude of heatwaves and droughts are expected to increase in a warming climate, which can have profound impacts on the environment, society, and public health, and these may be severely affected specifically by compound droughts and heatwaves (CDHWs). On the basis of daily maximum temperature data and the one-month standardized precipitation evapotranspiration index (SPEI) from 1961 to 2018, the Gan River Basin (GRB) was taken as a case here to construct CDHW identification indicators and quantify the population exposure to CDHWs. We found that ERA5 reanalysis data performed well in overall simulating temperature, precipitation, one-month SPEI, heatwaves, and CDHWs in the GRB from 1961 to 2018. CDHWs during the period from 1997 to 2018 were slightly higher than that in 1961–1997. CDHWs were more likely to occur in the southern parts of the basin due to the relatively high values of drought–heatwave dependence indices. Atmospheric circulation analysis of the 2003 CDHW in the GRB showed a relatively long-lasting anomalous high pressure and anticyclonic circulation system, accompanied by the positive convective inhibition and surface net solar radiation anomalies. These circulating background fields eventually led to the exceptional 2003 CDHW occurrence in the GRB. The population exposure to CDHWs basically increased, especially for the moderate CDHWs in ERA5. The change in total exposure was mainly due to climate change. Compared with the period from 1989 to 1998, the contributions of the population change effect in 2009–2018 gradually increased with the increase in the CDHW magnitude both in the observations and ERA5 reanalysis data.

Disentangling increasing compound extremes at regional scale during Indian summer monsoon

Compound extremes exhibit greater adverse impacts than their univariate counterparts. Studies have reported changes in frequency and the spatial extent of extremes in India; however, investigation of compound extremes is in the infancy state. This study investigates the historical variation of compound dry and hot extremes (CDHE) and compound wet and cold extremes (CWCE) during the Indian summer monsoon period from 1951 to 2019 using monthly data. Results are analyzed for 10 identified homogeneous regions for India. Our results unravelled that CDHE (CWCE) frequency has increased (decreased) by 1-3 events per decade for the recent period (1977-2019) relative to the base period (1951-1976). Overall, the increasing (decreasing) pattern of CDHE (CWCE) is high across North-central India, Western India, North-eastern India and South-eastern coastlines. Our findings help in identification of the parts of the country affected by frequent and widespread CDHE during the recent period, which is alarming. More detailed assessments are required to disentangle the complex physical process of compound extremes to improve risk management options.

Forest Resistance and Resilience to 2002 Drought in Northern China

Drought can weaken forest activity and even lead to forest mortality, and the response of different forest types to drought can be diverse. Deciduous broadleaf forest (DBF) and deciduous needleleaf forest (DNF) are two of the majority forest types in northern China. In this region, a severe drought event happened in 2002. However, due to the lack of data, the spatio-temporal characteristics of the ecosystem stability of different forest types here remain unclear. In this study, we used a machine learning approach (model tree ensemble, MTE) to drive fluxsite gross primary productivity (GPP), combined with remote sensing-based GPP and a vegetation index data (EVI), to analyze the spatial and temporal characteristics of resistance and resilience of DNF and DBF in northern China during and after the 2002 drought. The results showed that the DBFs were more acclimatized to the drought, while the resistance and resilience of DNF and DBF were diverse under different consecutive drought events. These results could be suggestive for forest conservation and vegetation modeling.

Evaluation and Future Projection of Extreme Climate Events in the Yellow River Basin and Yangtze River Basin in China Using Ensembled CMIP5 Models Data

The Yellow River Basin (YLRB) and Yangtze River Basin (YZRB) are heavily populated, important grain-producing areas in China, and they are sensitive to climate change. In order to study the temporal and spatial distribution of extreme climate events in the two river basins, seven extreme temperature indices and seven extreme precipitation indices were projected for the periods of 2010-2039, 2040-2069, and 2070-2099 using data from 16 Coupled Model Intercomparison Project Phase 5 (CMIP5) models, and the delta change and reliability ensemble averaging (REA) methods were applied to obtain more robust ensemble values. First, the present evaluation indicated that the simulations satisfactorily reproduced the spatial distribution of temperature extremes, and the spatial distribution of precipitation extremes was generally suitably captured. Next, the REA values were adopted to conduct projections under different representative concentration pathway (RCP) scenarios (i.e., RCP4.5, and RCP8.5) in the 21st century. Warming extremes were projected to increase while cold events were projected to decrease, particularly on the eastern Tibetan Plateau, the Loess Plateau, and the lower reaches of the YZRB. In addition, the number of wet days (CWD) was projected to decrease in most regions of the two basins, but the highest five-day precipitation (Rx5day) and precipitation intensity (SDII) index values were projected to increase in the YZRB. The number of consecutive dry days (CDD) was projected to decrease in the northern and western regions of the two basins. Specifically, the warming trends in the two basins were correlated with altitude and atmospheric circulation patterns, and the wetting trends were related to the atmospheric water vapor content increases in summer and the strength of external radiative forcing. Notably, the magnitude of the changes in the extreme climate events was projected to increase with increasing warming targets, especially under the RCP8.5 scenario.

More frequent and widespread persistent compound drought and heat event observed in China

Compound drought and heat event (CDHE) causes severe impacts on agriculture, ecosystem, and human health. Based on daily maximum surface air temperature and meteorological drought composite index data in China, changing features of CDHEs in warm season from 1961 to 2018 is explored at a daily time scale based on a strict and objective definition in this study. Results reveal that CDHEs have occurred more frequently and widely in China, especially since the late 1990s. Notably, such changes are more obvious in Southwest China, eastern Northwest China, northern North China, and the coastal area of southeastern China. A prominent feature is that persistent CDHEs on a daily scale have increased significantly. To better understand climate change of compound extreme events, further studies on the physical mechanism, especially attribution analyses at a regional scale, are urgently needed.

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.

It Is Not Easy Being Green: Recognizing Unintended Consequences of Green Stormwater Infrastructure

Green infrastructure designed to address urban drainage and water quality issues is often deployed without full knowledge of potential unintended social, ecological, and human health consequences. Though understood in their respective fields of study, these diverse impacts are seldom discussed together in a format understood by a broader audience. This paper takes a first step in addressing that gap by exploring tradeoffs associated with green infrastructure practices that manage urban stormwater including urban trees, stormwater ponds, filtration, infiltration, rain gardens, and green roofs. Each green infrastructure practice type performs best under specific conditions and when targeting specific goals, but regular inspections, maintenance, and monitoring are necessary for any green stormwater infrastructure (GSI) practice to succeed. We review how each of the above practices is intended to function and how they could malfunction in order to improve how green stormwater infrastructure is designed, constructed, monitored, and maintained. Our proposed decision-making framework, using both biophysical (biological and physical) science and social science, could lead to GSI projects that are effective, cost efficient, and just.

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.