Assessing Future Flooding Risk in a Coastal Lagoon Using Hydrogeological Approaches and Analysis of the 2021 Flood Event: A Case Study of Tasi-Tolu Lagoon, Dili, Timor-Leste

This study aims to apply a hydrogeological approaches and analysis of the 2021 flood event of Tasi-Tolu Lagoon to achieve four specific goals. Firstly, the study seeks to determine the natural characteristics of the lagoon, which include factors such as size, depth, water quality, and ecosystem composition. Secondly, the influence of precipitation on the water volume in the lagoon will be examined. This analysis involves assessing historical rainfall patterns in the region, as well as the amount and frequency of precipitation during the 2021 flood event. Thirdly, the hydrogeologic and geologic conditions of the lagoon will be evaluated. This involves examining factors such as the type and structure of the soil and bedrock, the presence of aquifers or other underground water sources, and the movement of water through the surrounding landscape. Finally, the study seeks to assess the risk of future flooding in Tasi-Tolu Lagoon, based on the insights gained from the previous analyses. Overall, this study’s goal is to provide a comprehensive understanding of the hydrogeological factors that contribute to flooding in Tasi-Tolu Lagoon. This knowledge could be used to inform flood mitigation strategies or to improve our ability to predict and respond to future flooding events in the region.

Climate change and Aedes albopictus risks in China:current impact and future projection

Background Future distribution of dengue risk is usually predicted based on predicted climate changes using general circulation models(GCMs).However,it is difficult to validate the GCM results and assess the uncertainty of the predictions.The observed changes in climate may be very different from the GCM results.We aim to utilize trends in observed climate dynamics to predict future risks of Aedes albopictus in China.Methods We collected Ae.albopictus surveillance data and observed climate records from 80 meteorological stations from 1970 to 2021.We analyzed the trends in climate change in China and made predictions on future climate for the years 2050 and 2080 based on trend analyses.We analyzed the relationship between climatic variables and the prevalence of Ae.albopictus in different months/seasons.We built a classification tree model(based on the average of 999 runs of classification and regression tree analyses)to predict the monthly/seasonal Ae.albopictus distribution based on the average climate from 1970 to 2000 and assessed the contributions of different climatic variables to the Ae.albopictus distribution.Using these models,we projected the future distributions of Ae.albopictus for 2050 and 2080.Results The study included Ae.albopictus surveillance from 259 sites in China found that winter to early spring(November–February)temperatures were strongly correlated with Ae.albopictus prevalence(prediction accuracy ranges 93.0–98.8%)—the higher the temperature the higher the prevalence,while precipitation in summer(June–September)was important predictor for Ae.albopictus prevalence.The machine learning tree models predicted the current prevalence of Ae.albopictus with high levels of agreement(accuracy>90%and Kappa agreement>80%for all 12 months).Overall,winter temperature contributed the most to Ae.albopictus distribution,followed by summer precipitation.An increase in temperature was observed from 1970 to 2021 in most places in China,and annual change rates varied substantially from-0.22℃/year to 0.58℃/year among sites,with the largest increase in temperature occurring from February to April(an annual increase of 1.4–4.7℃ in monthly mean,0.6–4.0℃ in monthly minimum,and 1.3–4.3℃ in monthly maximum temperature)and the smallest in November and December.Temperature increases were lower in the tropics/subtropics(1.5–2.3℃ from February–April)compared to the high-latitude areas(2.6–4.6℃ from February–April).The projected temperatures in 2050 and 2080 by this study were approximately 1–1.5℃ higher than those projected by GCMs.The estimated current Ae.albopictus risk distribution had a northern boundary of north-central China and the southern edge of northeastern China,with a risk period of June–September.The projected future Ae.albopictus risks in 2050 and 2080 cover nearly all of China,with an expanded risk period of April–October.The current at-risk population was estimated to be 960 million and the future at-risk population was projected to be 1.2 billion.Conclusions The magnitude of climate change in China is likely to surpass GCM predictions.Future dengue risks will expand to cover nearly all of China if current climate trends continue.

Current asthma control predicts future risk of asthma exacerbation： a 12-month prospective cohort study

Background The performance of asthma control test （ACT） at baseline for predicting future risk of asthma exacerbation has not been previously demonstrated. This study was designed to explore the ability of the baseline ACT score to predict future risk of asthma exacerbation during a 12-month follow-up. Methods This post hoc analysis included data from a 12-month prospective cohort study in patients with asthma （n=290）. The time to the first asthma exacerbation was analyzed and the association between baseline ACT scores and future risk of asthma exacerbation was calculated as adjusted odds ratio （OR） using Logistic regression models. Further, sensitivity and specificity were estimated at each cut-point of ACT scores for predicting asthma exacerbations. Results The subjects were divided into three groups, which were uncontrolled （U, n=128）, partly-controlled （PC, n=111）, and well controlled （C, n=51） asthma. After adjustment, the decreased ACT scores at baseline in the U and PC groups were associated with an increased probability of asthma exacerbations （OR 3.65 and OR 5.75, respectively）, unplanned visits （OR 8.03 and OR 8.21, respectively） and emergency visits （OR 20.00 and OR 22.60, respectively） over a 12-month follow-up period. The time to the first asthma exacerbation was shorter in the groups with U and PC asthma （all P 〈0.05）. The baseline ACT of 20 identified as the cut-point for screening the patients at high risk of asthma exacerbations had an increased sensitivity of over 90.0% but a lower specificity of about 30.0%. Conclusion Our findings indicate that the baseline ACT score with a high sensitivity could rule out patients at low risk of asthma exacerbations and predict future risk of asthma exacerbations in clinical practice.

气候变化和物候变动对东北黑土区农业生产的协同作用及未来粮食生产风险

The black soil region of northeast China is a vital food base and is one of the most sensitive regions to climate change in China.However,the characteristics of the crop phenological response and the integrated impact of climate and phenological changes on agricultural productivity in the region under the background of climate change are not clear.The future agricultural risk assessment has been insufficiently quantified and the existing risk level formulation lacks a sound basis.Based on remote sensing products,climate data,and model simulations,this study integrated a logistic function fitting curvature derivation,multiple linear regression,and scenario simulation to investigate crop phenology dynamics and their climate response characteristics in the black soil region.Additionally,the compound effects of climate and phenology changes on agricultural production and possible future risks were identified.The key results were as follows:(1)From 2000 to 2017,29.76%of the black soil region of northeast China experienced a significant delay in the start of the growing season(SOS)and 16.71%of the total area displayed a trend for the end of the growing season(EOS)to arrive earlier.The time lagged effects of the SOS in terms of the crop response to climatic factors were site and climatic parameter dependent.The influence of temperature was widespread and its effect had a longer lag time in general;(2)Both climatic and phenological changes have had a significant effect on the inter-annual variability of crop production,and the predictive ability of both increased by 70.23%,while the predictive area expanded by 85.04%,as compared to that of climate change in the same period of the growing season;(3)Under the RCP8.5 scenario,there was a risk that the future crop yield would decrease in the north and increase in the south,and the risk area was constantly expanding.With a 2.0℃rise in global temperature,the crop yield of the southern Songnen black soil sub-region would reduce by almost 10%.This finding will improve our understanding of the mechanisms underlying climate change and vegetation productivity dynamics,and is also helpful in the promotion of the risk management of agrometeorological disasters.