Narrow Results

Due to non-stationary nature of Indian summer monsoon rainfall (ISMR), analysis of its patterns and behaviors is a very tedious task. Advance prediction and behaviors play a significant role in various domains. Literature review reveals that researchers’ works are limited to design predictive models but not on inherited patterns and behaviors for the ISMR. In this study, a novel method based on the hybridization of two computational techniques, viz., fuzzy and rough sets is proposed for patterns and behaviors. The proposed method initially classifies the information into the four distinct regions, as fuzzy positive region, fuzzy negative region, completely fuzzy region, and gray fuzzy region. Based on four regions, four different patterns of decision rules are explored. Further, a method is discussed to represent such decision rules in terms of graph, which helps to analyze the patterns of ISMR by discovering new knowledge. The proposed method is validated by performing various statistical analyses.

Singapore Firm Receives US$1 Million from NIH.

Science Crosses Political Barriers.

Soiken Developing Health Drink with Unnamed Partner.

Cipla Launches Arthritis Drug Mobix.

Drought — A Global Concern.

Big Money in Human Tissue Trade.

SINGAPORE – NUS Researchers Uncover Potent Parasite-killing Mechanism of Nobel Prize-Winning Anti-Malarial Drug.

SINGAPORE – Robotic Glove Invented by NUS Researchers Helps Patients Restore Hand Movements.

UNITED STATES – Study Reveals Environment, Behavior Contribute to Some 80 Percent of Cancers.

UNITED STATES – Probing the Mystery of How Cancer Cells Die.

UNITED STATES – Liver Hormone Works Through Brain's Reward Pathway to Reduce Preference for Sweets & Alcohol.

UNITED STATES – How Three Genes You've Never Heard of May Influence Human Fertility.

UNITED STATES – Researchers Find Link between Processed Foods and Autoimmune Diseases.

UNITED KINGDOM – Is Evolution More Intelligent Than We Thought?

UNITED KINGDOM – Unravelling the Genetics of Pregnancy and Heart Failure.

SWITZERLAND – New Global Framework to Eliminate Rabies.

CANADA – Droughts Hit Cereal Crops Harder Since 1980s.

TAIWAN – Discovery of Key Autophagy Terminator that Contributes to Cell Survival and Muscle Homeostasis.

Tropical countries, like Nigeria, depend on rainfall for agriculture, power generation, transportation and other economic activities. Drought will hinder the performance of these activities, hence, it poses a significant threat to the economy. Understanding fluctuations and structures in droughts will help in forecasting, planning and mitigating its impact on livelihoods. In this study, the multifractal properties of drought at four temporal scales were investigated over different locations across Nigeria. Drought was computed using the standardized precipitation index from monthly precipitation data from 1980 to 2010. Using multifractal detrended fluctuation analysis, meteorological drought was found to have multifractal properties at 1-, 6-, 12- and 24-month temporal scale. The generalized Hurst exponent of drought at different time-scale showed dependence on scaling exponent. Long-range correlations were found to be main source of multifractality at all temporal scales. The multifractal strength increases with increasing temporal scale except for a few locations. The range of spectrum width were found to be 0.306–0.464 and 0.596–0.993 at 1- and 24-month temporal scale, respectively. No significant trend was found in the degree of multifractality across different climatic zones of Nigeria.

This study examines the effect of climate variability on water resource management during droughts. We use data from local droughts in Japan over three decades to investigate how variability in precipitation and temperature affects water restrictions implemented by drought coordination councils. We find that climate variability is significantly related to water restrictions in terms of both intensity and duration. The regression results show that a 100-mm decrease in annual precipitation is associated with a 0.2% increase in the water withdrawal restriction rate and an increase of one day in the restriction period. Our findings suggest that climate variability might induce more stringent water restrictions, implying negative consequences for water availability. This study thus shows the importance of strategically building adaptive capacity to climate change due to the risks of extreme weather events, such as prolonged droughts and extended summer seasons.

This paper examines the impact of weather shocks on crime in Pernambuco-Northeast, one of the states most affected by climate disasters in the Brazilian semi-arid region. We show that precipitation and temperature shocks in the form of droughts have a significant impact on the increase of rates of intentional lethal violent crimes (ILVC), property crimes (PC), and homicides. The effects of precipitation fluctuations in the form of droughts persist beyond the agricultural season and in the medium-term, and vary according to municipal and criminological characteristics. Moreover, adverse weather conditions (e.g., droughts) have a greater impact on income-related crimes. Consistent with this evidence, we find that the persistent response of crime rates to adverse weather conditions is driven by negative shocks to rural income, followed by a deterioration in overall economic activity, urban labor market conditions, and the government’s ability to provide public goods. The patterns we identify align with a relationship between weather and crime explained by reduced opportunity costs associated with criminal activity. Regarding policy recommendations, our findings suggest that local governments should prioritize investments in water infrastructure, agricultural irrigation, expansion of water coverage, and conservation of forested areas. These measures can contribute to climate adaptation and mitigate the economic impact of weather shocks on crime.

Drought events and their impacts pose a considerable problem for governments, businesses and individuals. Superimposed on this is the risk of anthropogenic climate change. Climate models are increasingly being used to understand how climate change may affect future drought regimes. However, methodologies to quantify economic costs which could occur under these future scenarios are virtually non-existent. In this study, historic drought events were identified in regional precipitation data using the Standardized Precipitation Index, and their magnitude quantified and linked to reported economic costs. Drought damage functions were created for Australia, Brazil, China, India, Spain/Portugal and the USA. Projections of drought magnitude for 2003–2050 were modeled using the Community Integrated Assessment System, for a range of climate and emission scenarios, and future economic costs estimated. Severe and extreme drought events were projected to cause estimated additional losses ranging between 0.04 and 9 percent of national GDP in Australia, the USA and Spain/Portugal under future scenarios of climate change. The combined effect on global GDP from projected long-term drought events in the countries analyzed resulted in additional annual losses of 0.01 to 0.25 percent. This is considered conservative as the analysis is representative of seven countries only; does not incorporate the possibility of successive drought events, or compounding effects on vulnerability from interactions with other extreme events. Furthermore, it excludes indirect economic effects; social and environmental losses; the possibility of increasing vulnerability due to changing socio-economic conditions; and the possibility of irreversible or systemic collapse of economies as the study highlighted that under future climate change drought magnitude may exceed current experience potentially passing thresholds of social and economic resilience. Stringent mitigation had little effect on the increasing impacts of drought in the first half of the 21st century, so in the short-term adaptation in drought "hot spots" will be crucial.

Extreme daily and transient precipitation events have been on the rise in the continental United States. These changes have the potential to disrupt human and natural systems. Tree rings can reconstruct annual estimates of past climate, but have limitations in reconstructing extreme precipitation events. We analyzed instrumental records to evaluate patterns in daily, weekly, and seasonal precipitation in four regions spanning a climatic gradient in the eastern United States. Relationships between tree-ring reconstructions of hydroclimate and precipitation events were analyzed to characterize extreme years over the last 1000 years. From 1944–2013, the Hudson Valley and Ohio Valley regions have experienced wetter summers as well as an increase in the frequency of daily rainfall. Coinciding with these increases, half or more of the extreme wet years in these two regions have occurred in the last 20 years. Significant differences in the structure of weekly growing-season precipitation between extreme wet and dry years were found in late May and late June in the Ohio Valley and early June in the Mississippi Valley, with negligible differences in the northern and southern ends of our gradient. We also found dry-spell duration was significantly different between extreme wet and dry years in all regions except for the northern end of our study gradient. In contrast, dry-spell frequency was significantly different between extreme wet and dry years in all regions except for the southern end of our gradient. Reconstructed Palmer Drought Severity Index (PDSI) was significantly and positively correlated with total summer rainfall and significantly and negatively correlated with rainless-day frequency in all regions, with stronger correlations during extreme years. Working in the region with the strongest relations, we reconstructed summer precipitation and summer rainless days in the Hudson Valley back to 1525 CE and 1625 CE, respectively. From these reconstructions, we infer that the 20th century is characterized by more extreme summer precipitation totals and a decline in rainless days with 75.8% of the last 33 years having fewer dry days than the 377-year mean. The forecasted changes toward longer, more intense droughts over the next century are not yet realized in our study regions. However, should these shifts occur, human and natural systems will likely undergo abrupt change in response to alterations in hydrology, ecological disturbance, and terrestrial productivity, with the Northeast potentially being most vulnerable.

Increasingly, city governments are having to deal with climate change repercussions alongside those of other disasters, all while addressing its implications for both daily life and future sustainability. This paper argues that to build resilience to future climate extreme events and multi-hazards, it is essential to establish a systemic approach across sectors at the city scale. The City of Cape Town recently endured an extreme drought, followed by the COVID-19 pandemic. Through a series of interviews and engagements with senior government officials, a detailed understanding of the City of Cape Town’s response to the 2015–2018 drought and the COVID-19 pandemic in 2020–2021 was attained. In reviewing the City’s response, five inter-related adaptive governance capacities were identified as necessary for building a rapid and effective systemic response to future extreme events within city government. First, local government must be able to respond to hazards and risk systemically; second, system-level data is needed to quantify and develop an integrated understanding of important system components; and third, flexible governance mechanisms can help support agile leadership at the senior city management level. The fourth capacity is that of project execution skills for the rapid implementation of responses and infrastructure; the fifth is the ability to partner with civil society and the private sector. An analysis of these two proximate extreme events reveals the nature of these five capacities and how they have been put into practice in Cape Town. It is important to unpack and share the nature of these capacities and how they enabled a more systemic response, especially given the call for more attention to be paid to what adaptive urban governance looks like in practice when managing multi-risk and extreme events in cities.

Western China is typically sensitive to climate change and ecologically fragile. It also has large numbers of people living in poverty, and it is a hot spot for emigration. This paper takes the Ningxia Hui Autonomous Region (NHAR) as a case and, employing a mixed-method research combining exploratory research and confirmatory research where quantitative analysis and qualitative analysis are made, conducts an empirical study on the dynamics of climate change impacts on migration. Firstly, this paper identified the fragile characteristics of different types of migrant groups (including policy-facilitated migrants, voluntary migrants and economic migrants) in the context of climate change; secondly, based on confirmatory factor analysis, this paper conducted climate change vulnerability assessment at county level, and explored several common potential factors affecting the regional fragility of climate change in Ningxia, include: climate capacity, social and economic development level, human capital, transportation infrastructure, and education level, etc. The result shows that the climate capacity factor accounts for 37.5% of contribution to regional climate change vulnerability. This paper justified that lacking climate capacity in long-term climate change is the major driving factor of climate-induced poverty and migration in the middle and south Ningxia. Based on a DPISR model, this paper developed a theoretical framework with its core concept “climate capacity”. Within this analytical framework, a series of indicators on climate capacity and climate-induced poverty were suggested to assess climate change related migration risks, which can support local migration planning in Ningxia and other western China areas.

The water shortage crisis is one of the main concerns that is threatening the biological security in Iran. According to available data and information, providing a framework for the assessment of water poverty in Iran seems crucial. The land-dividing unit in Iran is the province, and most of the governmental information is gathered based on this unit. In this sense, Isfahan province, which is one of the central provinces in Iran that is suffering from water crises, has been selected. The water poverty index (WPI), which is adopted in accordance with Iran’s situation, including five components of resources, access, capacity, use, and environment, has been used for each of Isfahan’s cities. “Capacity” and “use” has the greatest correlation, and it seems any advancement in water utilization for economic purposes might result in increased capacity, and vice versa. Also, there is a positive correlation between WPI and components of access, capacity, use, and environment. It can be interpreted that the lack of access to water services may be due to a lack of income or education. Finally, access, capacity, and use showed the strongest relationships between WPI and its subcategories. Therefore, these three elements should be the main focus of any initiative to manage the water poverty in Isfahan province.

Introducing a causal model to study the drought disaster around the world is the need of the planet today. There are many causes and effects of drought disasters around the world. These parameters, by affecting and being influenced by each other, cause the formation of processes that can make the experience of this event unpleasant. By planning and formulating appropriate strategies based on the results of this model, this event can be properly treated. For this purpose, in this research, the causal model of drought disasters is introduced. First, effective criteria or parameters in the occurrence of drought are identified. The tool used in this research is the modified fuzzy DEMATEL model. After responding to the direct relations matrix and defuzzification of this matrix, the causes and effects of the drought disaster are finally realized. The results of this study indicate that the criteria of global warming, mismanagement, and war are causal parameters or causes and the criteria of climate change, deforestation and soil degradation, dam construction, agriculture and livestock, and additional water needs are the parameters of the effect. Therefore, by establishing the conditions of each of the causal parameters, drought occurs or intensifies, and with the occurrence of drought, the effect parameters are created and show their effect on the causal parameters in the occurrence of drought.

Understanding the economic value of irrigation water is essential for supporting policies relating to the irrigation sector, irrigation water allocation decisions, water pricing and to compare the variable impacts of water reform within and across sectors of the economy. In this paper, we apply the residual method as a complement to other methods for determining the value of the water used over a wide range of irrigated crops in different seasons and regions of Australia’s Murray–Darling Basin. Using Monte Carlo simulation and probability theory, we estimated the combined impacts of biophysical and economic factors on the economic productivity of irrigation water use by individual activities. The estimated residual values vary across regions and in response to water availability as we would expect and warrant consideration of these factors in making any future water policy and investment decisions in different regions. As anticipated perennial (fruits and nuts, grapes) and high capital annual activities (cotton) represent the highest value water uses. Water trading from low to high value activities results in economic losses that are much lower than the proportional decline in water availability during periods of drought.

Water utilities use demand-side management (DSM) policies to incentivize conservation during shortages. However, because utilities often use DSM policies for the first time during drought, it may be difficult to determine the extent to which policy responsiveness relates to an overall conservation culture, and short-term policy responsiveness may not be generalizable to non-drought periods. This research evaluates the impact of drought and utility policies using 10 years of household-level panel data in the first known application of a fixed-effects, latent-class model [Deb, P and PK Trivedi (2013). Finite mixture for panels with fixed effects. Journal of Econometric Methods, 2(1), 35–51] to water demand data. This flexible estimation approach identifies heterogeneity in policy responsiveness over time as it relates to drought conditions and changes in the utility’s billing structure. Two classes of water demand are identified — one associated with responsiveness to weather and a second with responsiveness to policies. In the class of water demand associated with weather, households are less sensitive to policy changes but exhibit increased sensitivity to precipitation both when the utility is actively promoting conservation (during severe drought) and in post-drought years. Implications for long-term effectiveness of utility conservation policies are discussed.

This paper aims to evaluate the economic implications of meteorological drought in Spain. The study seeks to provide decision-makers with crucial insights into the macroeconomic effects of drought, enabling them to devise mitigation strategies and minimize its impact on economic activity. The Partial Hypothetical Extraction Method (HEM) is employed within the Input-Output analysis framework extended to a Social Accounting Matrix (SAM) of Spain to achieve this goal. The database utilized for this analysis is the FNAM for Spain in 2017, in millions of euros, obtained from the Full International and Global Accounts for Research in Input-Output Analysis (FIGARO) project, a collaboration between Eurostat and the European Commission. The study aims to estimate the economic impact of drought on the productive sectors of the Spanish economy in terms of sectoral production and GDP. This involves simulating the partial reduction in value-added resulting from variations in average water productivity per gross value added, based on the drought indicator SPI-24. Three scenarios are generated: (1) drought, (2) moderate drought and (3) severe drought. In quantitative terms, the simulated drought scenarios could lead to a drop in GDP of 0.88% for the drought scenario, 1.61% for the moderate drought scenario, and 1.76% for the severe drought scenario. Additionally, it is important to recognize that water scarcity hampers the social and economic development of cities and regions beyond the results in quantitative terms.

Climate change and water scarcity may badly affect existing rice production system in Bangladesh. With a view to sustain rice productivity and mitigate yield scaled CH₄ emission in the changing climatic conditions, a pot experiment was conducted under different soil water contents, biochar and silicate amendments with inorganic fertilization (NPKS). In this regard, 12 treatments combinations of biochar, silicate and NPKS fertilizer along with continuous standing water (CSW), soil saturation water content and field capacity (100% and 50%) moisture levels were arranged into rice planted potted soils. Gas samples were collected from rice planted pots through Closed Chamber technique and analyzed by Gas Chromatograph. This study revealed that seasonal CH₄ emissions were suppressed through integrated biochar and silicate amendments with NPKS fertilizer (50–75% of the recommended doze), while increased rice yield significantly at different soil water contents. Biochar and silicate amendments with NPKS fertilizer (50% of the recommended doze) increased rice grain yield by 10.9%, 18.1%, 13.0% and 14.2%, while decreased seasonal CH₄ emissions by 22.8%, 20.9%, 23.3% and 24.3% at continuous standing water level (CSW) (T9), at saturated soil water content (T10), at 100% field capacity soil water content (T11) and at 50% field capacity soil water content (T12), respectively. Soil porosity, soil redox status, SOC and free iron oxide contents were improved with biochar and silicate amendments. Furthermore, rice root oxidation activity (ROA) was found more dominant in water stress condition compared to flooded and saturated soil water contents, which ultimately reduced seasonal CH₄ emissions as well as yield scaled CH₄ emission. Conclusively, soil amendments with biochar and silicate fertilizer may be a rational practice to reduce the demand for inorganic fertilization and mitigate CH₄ emissions during rice cultivation under water stress drought conditions.

We measure the impact of extreme weather events—droughts and floods—on health-care utilization and expenditures in Sri Lanka. We find that frequently occurring local floods and droughts impose a significant health risk when individuals are directly exposed to these hazards. Individuals are also at risk when their communities are exposed even if they themselves are unaffected. These impacts, especially the indirect spillover effects to households not directly affected, are associated with land use in affected regions and access to sanitation and hygiene. Finally, both direct and indirect health risks associated with floods and droughts have an economic cost: our estimates suggest that Sri Lanka spends $19 million per year directly on health-care costs associated with floods and droughts. This cost is divided almost equally between the public purse and households, with 83% of it spent on flood-related health care and the rest on drought-related health care. In Sri Lanka, both the frequency and intensity of droughts and floods are likely to increase because of climatic change. Consequently, the health burden associated with these events will likely increase.

This study examined the response of crop yield (maize, rice, soybean, and wheat) in the Asian monsoon region to meteorological drought during 1981–2016. The meteorological drought index was developed based on multiple timescale SPEI (Standardized Precipitation-Evapotranspiration Index) using a global dataset. The crop yield response was assessed using de-trended crop yield based on the global dataset of historical yields in a 0.5 grid resolution. Monthly indices were then obtained in the harvest month of each crop to consider the crop growing period annually. Then the crop yield response to drought was estimated by Pearson correlation and linear regression analysis. Results show that crop yield anomaly is more associated with the 9-month precipitation aggregation of SPEI than the other time scales used in this study (1–12 months). The drought events variations explain approximately 15, 11, 22, and 10% of the total crop area for maize, rice, soybean, and wheat crop, respectively, in the region (p-value < 0.1). By country, China, India, and Indonesia, the three largest crop producers account for around 76% of the region’s total significantly affected crop area. Based on this historical analysis, this study implies that droughts affect crop yield in this region, whose climatic conditions are strongly driven by various global phenomena (e.g., El Niño–Southern Oscillation). This study is also essential for understanding crop-drought vulnerability, particularly for the Asian monsoon region.

Plants respond to abiotic stresses, such as drought, high salinity, and cold, to acquire stress tolerance. Molecular and genomic studies have shown that a number of genes with various functions are induced by abiotic stresses, and that various transcription factors are involved in the regulation of stress-inducible genes in Arabidopsis and rice. These gene products function not only in stress tolerance but also in stress response. In this review, recent progress in the analysis of complex cascades of gene expression in drought and cold stress responses is summarized. Various genes involved in stress tolerance are also discussed for their application to molecular breeding of drought, salinity, and/or cold stress tolerance.

Droughts are severe meteorological disasters in China, and more comprehensive evaluation methods for droughts can provide a reliable reference for policy-making in reducing the impact of droughts. The existing methods of drought evaluation are lacking universally, and cannot be used generally. Based on the theory of Variable Fuzzy Sets, a comprehensive drought evaluation model is proposed to solve the problem. The methodology for the proposed solution is written in this paper and is applied in the Qucun Yellow River Irrigation Region. The results have shown that the model is not only reasonable and feasible, but also simple and practical. The model and its methods can provide academic support and serve as reference for policy-making for the comprehensive evaluation of droughts in the North Region of China.