Developing climate change adaptation pathways in the agricultural sector based on robust decision-making approach (case study: Sefidroud Irrigation Network, Iran)

Abstract

Allocation of water in the situation of climate change presents various uncertainties. Consequently, decisions must be made to ensure stability and functionality across different climatic scenarios. This study aims to examine the effectiveness of adaptation strategies in the agricultural sector, including a 5% increase in irrigation efficiency (S1) and a shift in irrigation method to Dry-DSR (direct seeded rice) under conditions of climatic uncertainty using a decision-making approach. The study focuses on the basin downstream of the Sefidroud dam, encompassing the Sefidroud irrigation and drainage network. Initially, basin modeling was conducted using the WEAP integrated management software for the period 2006–2020. Subsequently, the impact of climate change was assessed, considering RCP2.6, RCP4.5, and RCP8.5 emission scenarios on surface water resources from 2021 to 2050. Runoff and cultivated area, both subject to uncertainty, were identified as key parameters. To evaluate strategy performance under different uncertainties and determine the efficacy of each strategy, regret and satisfaction approaches were employed. Results indicate a projected decrease in future rainfall by 3.5–11.8% compared to the base period, accompanied by an increase in maximum and minimum temperatures (0.83–1.62 °C and 1.15–1.33 °C, respectively). Inflow to the Sefidroud dam is expected to decrease by 13–28%. Presently, the Sefidroud irrigation and drainage network faces an annual deficit of 505.4 MCM, and if current trends persist with the impact of climate change, this shortfall may increase to 932.7 MCM annually. Furthermore, satisfaction indices for strategy (S2) are 0.77 in an optimistic scenario and 0.70 in strategy (S1). In a pessimistic scenario, these indices are 0.67 and 0.56, respectively. Notably, changing the irrigation method with Dry-DSR is recommended as a robust strategy, demonstrating the ability to maintain basin stability under a broad range of uncertainties and climate change scenarios. It is crucial to note that the results solely highlight the effects of climate change on water sources entering the Sefidroud dam. Considering anthropogenic activities upstream of the Sefidroud basin, water resource shortages are expected to increase. Therefore, reallocating water resources and implementing practical and appropriate measures in this area are imperative.

Analyzing the Role of Changing Climate on the Variability of Intensity-Duration-Frequency Curve Using Wavelet Analysis

Abstract

Climate change has significantly influenced the occurrence of extreme events and their outcomes in developing countries, like Pakistan. This research investigates the impact of climate variability on the development of Intensity Duration Frequency (IDF) curves using wavelet analysis across two Pakistani cities i.e. Abbottabad and Islamabad. IDF curves are produced utilizing the Statistical Software Package (HEC-SSP) and Hydrological Engineering Center and Watershed Modeling System (WMS), where daily meteorological (i.e., rainfall, and the approx. temperature) data from 1960 to 2020 (60 years) at Abbottabad and Islamabad was gathered from Pakistan Meteorological Department (PMD). Initially, the relation between the observed data was extracted by applying the slope approaches of Mann-Kendall and Sen. Following the removal of serial correlation, generalized IDF curves are developed utilizing the time and turnaround for both stations. Finally, climate variability’s impact on IDF curves was studied using wavelet analysis applied to three different pairs of input data, i.e., maximum, minimum, and mean temperatures against the developed IDF curves. Results showed that wavelet analysis are extremely useful to monitor the climate variability’s influence/role on frequency and return periods of flood events (i.e., IDF curves). The developed IDF curves showed higher intensities during the monsoon period, whereas lower intensities of IDF curves are observed in other months against the 24 hours’ duration of different return periods. Results also depicted that Abbottabad has experienced higher intensity of rainfall as compared with Islamabad city, which might be linked due to the changing climate and the use of land in both cities and verified by the results obtained from wavelet analysis. Increased cloud cover and precipitation resulted from the orographic effect, coupled with the influence of lower temperatures at elevated altitudes. Wavelet analysis showed a strong impact of climate (i.e., temperature) on IDF curves, where significant changes in the period and frequency are observed between the two cities. Overall, this study will be useful to understand how IDF curves are affected by climate variability while predicting the future flood events and sustainable design of urban drainage system.

Analyzing the Role of Changing Climate on the Variability of Intensity-Duration-Frequency Curve Using Wavelet Analysis

Abstract

Climate change has significantly influenced the occurrence of extreme events and their outcomes in developing countries, like Pakistan. This research investigates the impact of climate variability on the development of Intensity Duration Frequency (IDF) curves using wavelet analysis across two Pakistani cities i.e. Abbottabad and Islamabad. IDF curves are produced utilizing the Statistical Software Package (HEC-SSP) and Hydrological Engineering Center and Watershed Modeling System (WMS), where daily meteorological (i.e., rainfall, and the approx. temperature) data from 1960 to 2020 (60 years) at Abbottabad and Islamabad was gathered from Pakistan Meteorological Department (PMD). Initially, the relation between the observed data was extracted by applying the slope approaches of Mann-Kendall and Sen. Following the removal of serial correlation, generalized IDF curves are developed utilizing the time and turnaround for both stations. Finally, climate variability’s impact on IDF curves was studied using wavelet analysis applied to three different pairs of input data, i.e., maximum, minimum, and mean temperatures against the developed IDF curves. Results showed that wavelet analysis are extremely useful to monitor the climate variability’s influence/role on frequency and return periods of flood events (i.e., IDF curves). The developed IDF curves showed higher intensities during the monsoon period, whereas lower intensities of IDF curves are observed in other months against the 24 hours’ duration of different return periods. Results also depicted that Abbottabad has experienced higher intensity of rainfall as compared with Islamabad city, which might be linked due to the changing climate and the use of land in both cities and verified by the results obtained from wavelet analysis. Increased cloud cover and precipitation resulted from the orographic effect, coupled with the influence of lower temperatures at elevated altitudes. Wavelet analysis showed a strong impact of climate (i.e., temperature) on IDF curves, where significant changes in the period and frequency are observed between the two cities. Overall, this study will be useful to understand how IDF curves are affected by climate variability while predicting the future flood events and sustainable design of urban drainage system.

The Relationship between Parenting Styles and Sexual Well-Being in Canadian Emerging Adults

Abstract

Introduction

Previous research on parental influences on sexuality has found that parenting styles influence contraceptive use and risky sexual behaviours. However, no studies have examined the effect of parenting styles on the sexual well-being (SWB) of emerging adults more broadly. The aim of the study was to examine the SWB of emerging adults and to explore the relationship between parenting styles and SWB in emerging adulthood.

Methods

A sample of 152 Canadian emerging adults 18 to 25 years of age completed an online survey administered via social media from January to February 2021. Participants answered a sociodemographic questionnaire and measures of parenting styles, parent-child sexual communication, and SWB.

Results

Emerging adults were found to have healthy sexual well-being (e.g., high sexual satisfaction, low sexual distress). Authoritative parenting was associated with more positive, higher quality parent-child sexual communication, and more positive sexual well-being in emerging adults compared to other parenting styles.

Policy Implications and Conclusions

Although more research on this topic is needed, results indicate that parenting styles can affect the sexual development of emerging adults beyond sexual risk. Therefore, parental figures need to be actively involved in educating their children about sexuality and should provide enough support to foster positive sexual development in emerging adulthood.

Assessment of historical and projected changes in extreme temperatures of Balochistan, Pakistan using extreme value theory

Abstract

The fundamental consequences of global warming include an upsurge in the intensity and frequency of temperature extremes. This study provides an insight into historical trends and projected changes in extreme temperatures on annual and seasonal scales across “Balochistan, Pakistan”. Historical trends are analyzed through the Mann Kendal test, and extreme temperatures (Tmax and Tmin) are evaluated using generalized extreme value (GEV) distribution for historical period (1991–2020) from the observational data and the two projected periods as near-future (2041–2070) and far-future (2071–2100) using a six-member bias-corrected ensemble of regional climate models (RCMs) projections from the coordinate regional downscaling experiment (CORDEX) based on the worst emission scenario (RCP8.5). The evaluation of historical temperature trends suggests that Tmax generally increase on yearly scale and give mixed signals on seasonal scale (winter, spring, summer, and autumn); however, Tmin trends gave mixed signals at both yearly and seasonal scale. Compared to the historical period, the return levels are generally expected to be higher for Tmax and Tmin during the both projection periods in the order as far-future > near-future > historical on yearly and seasonal basis; however, the changes in Tmin are more evident. Station-averaged anomalies of + 1.9 °C and + 3.6 °C were estimated in 100-year return levels for yearly Tmax for near-future and far-future, respectively, while the anomalies in Tmin were found to be + 3.5 °C and + 4.8 °C which suggest the intensified heatwaves but milder colder extreme in future. The findings provide guidance on improved quantification of changing frequencies and severity in temperature extremes and the associated impacts.

Evolving linguistic divergence on polarizing social media

Abstract

Language change is influenced by many factors, but often starts from synchronic variation, where multiple linguistic patterns or forms coexist, or where different speech communities use language in increasingly different ways. Besides regional or economic reasons, communities may form and segregate based on political alignment. The latter, referred to as political polarization, is of growing societal concern across the world. Here we map and quantify linguistic divergence across the partisan left-right divide in the United States, using social media data. We develop a general methodology to delineate (social) media users by their political preference, based on which (potentially biased) news media accounts they do and do not follow on a given platform. Our data consists of 1.5M short posts by 10k users (about 20M words) from the social media platform Twitter (now “X”). Delineating this sample involved mining the platform for the lists of followers (n = 422M) of 72 large news media accounts. We quantify divergence in topics of conversation and word frequencies, messaging sentiment, and lexical semantics of words and emoji. We find signs of linguistic divergence across all these aspects, especially in topics and themes of conversation, in line with previous research. While US American English remains largely intelligible within its large speech community, our findings point at areas where miscommunication may eventually arise given ongoing polarization and therefore potential linguistic divergence. Our flexible methodology — combining data mining, lexicostatistics, machine learning, large language models and a systematic human annotation approach — is largely language and platform agnostic. In other words, while we focus here on US political divides and US English, the same approach is applicable to other countries, languages, and social media platforms.

A Journey in Science: Molecular vaccines for global child health in troubled times of anti-science

Real innovations in medicine and science are historic and singular; the stories behind each occurrence are precious. At Molecular Medicine we have established the Anthony Cerami Award in Translational Medicine to document and preserve these histories. The monographs recount the seminal events as told in the voice of the original investigators who provided the crucial early insight. These essays capture the essence of discovery, chronicling the birth of ideas that created new fields of research and launched trajectories that persisted and ultimately influenced how disease is prevented, diagnosed, and treated. In this volume, the Cerami Award Monograph is by Peter Hotez, MD, PhD, DSc (hon), FASTMH, FAAP, co-director of the Texas Children’s Hospital Center for Vaccine Development, the Texas Children’s Hospital Endowed Chair in Tropical Pediatrics, and professor and dean of the National School of Tropical Medicine at Baylor College of Medicine. A distinguished vaccinologist, pediatrician, and global health advocate with remarkable achievements in the realm of molecular medicine, this is the story of Dr. Hotez’s scientific journey.

Realizing the full potential of behavioural science for climate change mitigation

Abstract

Behavioural science has yielded insights about the actions of individuals, particularly as consumers, that affect climate change. Behaviours in other spheres of life remain understudied. In this Perspective, we propose a collaborative research agenda that integrates behavioural science insights across multiple disciplines. To this end, we offer six recommendations for optimizing the quality and impact of research on individual climate behaviour. The recommendations are united by a shift towards more solutions-focused research that is directly useful to citizens, policymakers and other change agents. Achieving this vision will require overcoming challenges such as the limited funding for behavioural and social sciences and structural barriers within and beyond the academic system that impede collaborations across disciplines.

Knowledge, attitudes, and practices related to dengue among public school teachers in a Central Luzon Province in the Philippines: an analytic cross-sectional study

Abstract

Background

Dengue has become a major health issue in tropical regions as the numbers of reported cases and estimated infections continuously increase. In the Philippines, many challenges remain in preventing and controlling the disease amidst all the mitigation efforts of the government. This study sought to measure the health literacy of Filipino teachers and determine the associations among teachers’ knowledge, attitudes, and selected practices (KAP) against dengue.

Methods

Elementary and secondary school teachers from the consistently declared dengue hotspots in the City of San Fernando, Pampanga, Philippines, from the years 2017 to 2019 were selected as target participants in this cross-sectional study. A self-administered online survey tool was used in this study for both screening of participants and the KAP survey proper. STATA, descriptive statistics, and multiple logistic regression were used for the data analysis. Odds Ratios (ORs) and 95% confidence intervals (CIs) were reported.

Results

The study comprised 604 participants whose mean age was 38.4 years. Television was determined as the top media source of information, and various health staff were the most trusted and common source of information. Good knowledge on dengue treatment (OR = 1.81; 95% CI 1.18–2.78) and dengue prevention (OR = 1.85; 95% CI 1.26–2.71) were positively associated with having good practices on protection against mosquito bites. Good knowledge on dengue signs and symptoms (OR = 1.56; 95% CI 1.02–2.37) and dengue prevention (OR = 2.38; 95% CI 1.59–3.58) were positively associated with having good practices on preventing breeding sites. Those with positive perceived susceptibility to dengue had lower odds of having good practices on protection against mosquito bites (OR = 0.64; 95% CI 0.41–0.99) and of having good practices on preventing breeding sites (OR = 0.46; 95% CI 0.26–0.81).

Conclusion

Even with the existing dengue policies, programs, and strategies, and the high disease literacy rate of Filipinos, dengue remains a struggle with an increasing case rate. Therefore, specific concepts should be emphasized, and interventions should be fine-tuned to better reach and influence the target population to attain a dengue-free Philippines.

An exhaustive investigation of changes in projected extreme precipitation indices and streamflow using CMIP6 climate models: A case study

Abstract

This study draws attention to the better comprehension of spatio-temporal analysis of climate changes based on precipitation extremes and projection of future streamflow for efficient management of water resources in the Krishna River Basin (KRB), India. The concept of symmetric uncertainty (SU) is employed to select the top five Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to project future precipitation extreme indices under different Shared Socio-economic Pathways (SSPs). Grid-wise trend analysis reveals that there is more number of decreasing trends in extreme precipitation indices than increasing trends. From the results, it is observed that the percentage contributions of maximum one-day (RX1day) and five-day (RX5day) precipitation indices to the annual total precipitation indices are more important. In future periods, the precipitation extremes are expected to increase, especially the heavy precipitation indices such as R95p, R99p, RX1day, and RX5day, which are increasing significantly along with R50. The projection of future streamflow in the KRB is done using a Support Vector Machine (SVM) and is expected to increase under different SSPs. These precipitation extremes may increase the chance of hydrological calamities across the basin in the future.

Research highlights

  • Spatio-temporal analysis of extreme precipitation indices is carried out using CMIP6 climate model simulations over KRB.

  • One of the most efficient algorithm, symmetric uncertainty is employed to select best-performing GCMs to reduce the uncertainty in GCM selection.

  • The association between the extreme indices and discharge is carried out using Pearson correlation.

  • A significant increase is observed in projected extreme indices, especially very extreme indices such as 95th and 99th percentiles, RX1day and RX5day.

  • SVM regression is established between TOTPR and mean daily discharge to predict the future annual average streamflow under different SSP scenarios.