Central Northeast Research Articles

Interdisciplinary Brain-based Learning Strategies in Addressing Liver Fluke Disease and Cultural Dietary Practices among Early Childhood Students

Liver fluke disease remains a critical public health issue in Southeast Asia, driven by cultural dietary practices involving raw or undercooked freshwater fish. This study evaluates the impact of an interdisciplinary brain-based learning intervention aimed at increasing awareness and modifying dietary behaviors among early childhood students in Central Northeast Thailand. A quasi-experimental design was employed, involving 122 students from four provinces. The intervention incorporated brain-based learning activities such as storytelling, songs, and visual aids to enhance engagement. Pre- and post-tests, behavioral observations, and attitudinal surveys were conducted to assess the program’s effectiveness. Post-intervention results indicated significant improvements in knowledge about liver fluke transmission, symptoms, and prevention, alongside positive changes in behavior, such as increased avoidance of raw fish consumption and improved hygiene practices. Attitudinal surveys showed a shift in preferences toward safer eating habits. These findings suggest integrating brain-based learning with culturally relevant health education can foster sustainable behavior change in early childhood populations. Further research is recommended to explore this approach’s long-term impacts and scalability.

Decoupling of carbon burial from productivity in the northeast Indian Ocean

The concentration of atmospheric carbon dioxide (CO2) is a crucial climate parameter as it has far-reaching implications on global temperature. The oceans are a significant sink for CO2. Biologically mediated carbon sequestration, in the form of both inorganic (CaCO3) and organic carbon (Corg), and its subsequent burial in marine sediments play a vital role in regulating atmospheric CO2. Understanding the distribution of carbon in marine sediments under different environments can help predict the fate of excess CO2 in the future. We studied the factors affecting the basin scale variation in carbon burial in the climatically sensitive northeast Indian Ocean, by using the data [CaCO3, Corg, Corg/Nitrogen, and isotopic ratio (δ13C, δ15N) of organic carbon] from a total of 718 surface sediments. The entire continental shelf and slope contain <10 % CaCO3. The highest CaCO3 is in the deepest parts of the central northeast Indian Ocean, away from the mouth of major river systems. Despite of the high productivity, the low Corg on the continental shelf is attributed to the well-oxygenated coarse-grained sediments. The lowest Corg is found in the well-oxygenated deeper central northeast Indian Ocean. Interestingly, the highest total carbon is in the deeper central and equatorial regions, far away from the highly productive marginal marine regions. Our study reveals that the grain size, terrigenous dilution, dissolved oxygen, and water masses strongly influence carbon accumulation in the northeast Indian Ocean, with only secondary influence of the productivity.

Opportunistic offering of self-sampling to non-attenders within the English cervical screening programme: a pragmatic, multicentre, implementation feasibility trial with randomly allocated cluster intervention start dates (YouScreen)

Self-sampling has game-changing potential to tackle the declining participation and inequities seen in many organised cervical screening programmes. Wide variation in uptake between settings and mode of kit offer highlight the importance of local piloting. Furthermore, harnessing the benefits of self-sampling in real-world settings has been surprisingly challenging. The YouScreen study estimated the impact of offering self-sampling to non-attenders within the English Programme and evaluated large-scale opportunistic offering of self-sampling in primary care. A pragmatic modified stepped-wedge implementation feasibility trial with randomly-allocated cluster intervention start dates at primary care practices in England (133 participating, 62 non-participating). Eligible women were aged 25-64 years and ≥6 months overdue for screening ("non-attenders"). Between January 13, 2021 and 30 November, 2021 self-sampling kits were distributed to non-attenders via an opportunistic offer in primary care when they consulted for any reason and direct mailout to those unscreened 15-months after routine invitation. Primary outcomes were the proportion of non-attenders screened each month; change in coverage; and uptake (90 days). YouScreen is registered with ISRCTN:12759467. 8338 women provided self-samples following recruitment between January 13, 2021 and 30 November, 2021. Self-samples were returned from 65.5% (6061/9248) who accepted an opportunistically offered kit and 12.9% (2777/17,604) directly-mailed kits. Responders were representative of the ethnically diverse and deprived underlying non-attendee population (64% ethnic minority groups, 60% from the two most deprived national quintiles). The self-sampling intervention resulted in a 22% (95% CI 18-26) increase in non-attenders screened per month (per-protocol analysis) and 12% (95% CI 9-15) (intention-to-treat analysis). Change in coverage at participating (mean intervention duration 7.5 months) vs non-participating practices was 1.6% (95% CI 0.4-2.8). Adverse effects were not formally collected. Opportunistically offering self-sampling to under-screened women in primary care could increase coverage in England and potentially reach underserved populations. North Central London and North East London Cancer Alliance.

Past and future joint return period of precipitation extremes over South Asia and Southeast Asia

Climate change is one of the major reasons for the increased intensity and frequency of precipitation extremes in tropical regions. This will have a significant impact on underdeveloped countries in South Asia and Southeast Asia. Therefore, this study analyzes changes in spatiotemporal patterns and the joint behavior of precipitation extremes across South Asian and Southeast Asian countries for the historical period (1975 to 2014) and future periods (2021–2060 (F1) and 2061–2100 (F2)). This study develops bias-corrected precipitation data and ranks General Circulation Models (GCMs) using the Empirical Quantile Mapping method and TOPSIS method, respectively. A multi-model ensemble of precipitation extremes is created using the top five GCMs. The Mann Kendall test is used to analyze trends in precipitation extremes. Joint probabilistic analysis is also conducted for different combinations of ETCCDI precipitation-based indices using Archimedes and Elliptical copulas. The results of the trend analysis indicate significant positive trends for R20mm (19.26%), R95pTOT (18.40%), Rx5Day (11.53%), and CWD (10.46%), while CDD (5.07%) shows a significant negative trend across the study area during historical period (1975–2014). The results of R20mm, R95pTOT, and Rx5Day under SSP585 shows almost 19 to 39% of area comes under significant positive trend during the F1 period. This becomes more evident in F2, with trends under SSP585 rising between 32% and 61%. The high-emissions scenario SSP585 reveals an increase in these positive trends compared to SSP126 in both the future periods (F1 and F2). These results indicating a noticeable rise in extreme precipitation events. The analysis of changes in the joint return period of precipitation extremes indicates that the South Peninsular India, North East India, West Central India and Central Northeast India, as well as most parts of Southeast Asian countries, will experience very heavy intensify precipitations in the future. In addition, persistent co-occurrence of dry and wet conditions will be observed in Pakistan, North West India, and Central Northeast India. This study provides useful information on the distribution of precipitation extremes in different regions of the study area.

Influence of temporary emigration on wood turtle (Glyptemys insculpta) detectability, with implications for abundance estimation.

Reliable population estimates are important for making informed management decisions about wildlife species. Standardized survey protocols have been developed for monitoring population trends of the wood turtle (Glyptemys insculpta), a semi-aquatic freshwater turtle species of conservation concern throughout its distribution in east-central North America. The protocols use repeated active search surveys of defined areas, allowing for estimation of survey-specific detection probability (p) and site-specific abundance. These protocols assume population closure within the survey area during the survey period, which is unlikely to be met as wood turtles are a highly mobile species. Additionally, current protocols use a single-pass design that does not allow for separation of availability (pa) and detectability (pd). If there are systematic influences on pa or pd that are not accounted for in the survey design or data analysis, then resulting abundance estimates could be biased. The objectives of this study were to determine if pa is a random process and if pa and pd are influenced by demographic characteristics. We modified the wood turtle survey protocol used in the upper Midwest to include a double-pass design, allowing us to estimate pa and pd using a robust design capture-recapture model. The modified protocol was implemented at 14 wood turtle monitoring sites in Minnesota and Wisconsin between 2017 and 2022. Our results indicated that pa was non-random and that pd increased with turtle carapace length. Our study suggests that model assumptions for current wood turtle population models may be violated, likely resulting in an overestimation of abundance. We discuss possible protocol and modeling modifications that could result in more accurate wood turtle abundance estimates.

Unraveling the spatial-temporal patterns of typhoon impacts on maize during the milk stage in Northeast China in 2020

Typhoons are increasing in inland areas and affecting agriculture under climate change. Assessing the large-scale impact of typhoons on crops is essential for improving agricultural resilience. However, typhoon impacts are typically intricate and uncertain, depending on the different stages of crop growth and the indicators used for assessment. Here, we leveraged satellite data to examine the spatial-temporal patterns of typhoon-induced impacts on maize during the milk stage in Northeast China in 2020. We found that land surface water index (LSWI) showed a significantly higher negative relative change of 161.5% in regions severely affected by typhoons, surpassing that of normalized difference vegetation index (NDVI, 19.7%), near-infrared reflectance of vegetation (NIRV, 31.7%), and enhanced vegetation index (EVI, 25.2%), suggesting the outperformance of LSWI in monitoring the impact of typhoons on maize. Based on LSWI, we revealed the spatial-temporal distribution of typhoon impacts. Specifically, significant impacts on maize growth were observed in central Northeast China, particularly in Heilongjiang (49% of maize fields) and Jilin provinces (53% of maize fields). Furthermore, week-long lagging typhoon impacts on maize growth were generally found but lasted until the end of the maize growing season. We also found the typhoon impacts were partially mitigated by spatial and temporal compensations. Regions with above-average maize growth offset the losses experienced in areas severely affected by typhoons. Additionally, better maize growth in the early stages enhanced its resilience against subsequent typhoon impacts. Despite the mitigating effects on maize production, typhoons may increase the risk of maize mold, which warrants further investigation. Given the projected increase in future climate extremes, this study provides valuable insights into the rapid assessment of typhoon impacts using satellite data and cloud computing and supports decision-making in crop management for sustainable agricultural production.

Multiscale association between large‐scale climate variability modes and drought in India via wavelet analysis

AbstractExtreme events, such as droughts, are influenced by climate variability modes such as El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Atlantic Multi‐decadal oscillation (AMO) and Equatorial Indian Ocean Oscillation (EQUINOO). Due to the significant interdependency among the climatic indices at various frequencies, a time‐frequency framework is necessary to better understand the teleconnection. The present study evaluates the association between climate variability modes and drought index in India using different variants of wavelet analysis such as wavelet coherence analysis (WCA), partial wavelet coherence analysis (PWCA), multiple wavelet coherence analysis (MWCA) and wavelet reconstruction methods. In this study, four major climatic indices (ENSO, PDO, AMO, EQUINOO) and the drought index, standard precipitation index (SPI), at four different monthly time periods (1, 3, 6 and 12) are considered. The results from the WCA analysis highlight significant teleconnection spectra for ENSO, PDO and EQUINOO at 2–8, 8–16 and 16–32 year time‐frequency bands. Further, PWCA results reveal significant interdependency in the teleconnection of ENSO and PDO at all the scales, while ENSO and EQUINOO are found to be independent modes of interannual drought variability in India. Finally, MWCA results show that the combination of EQUINOO and ENSO better explains the interannual variability of droughts in Northwest and Central northeast India. The results of this study will help improve drought prediction and early warning systems in India, by selection of appropriate climatic oscillations for different regions in India.

Impacts of Sea Surface Temperature Variability in the Indian Ocean on Drought Conditions over India during ENSO and IOD Events

The characteristics of terrestrial droughts are closely linked to simultaneous fluctuations in climatic factors, notably influenced by sea surface temperature (SST). This study explores the response of vegetation photosynthesis, indicated by solar-induced chlorophyll fluorescence (SIF), in India during the summer monsoon period (JJAS) under drought conditions. Notably, statistically significant associations between SST variations in the tropical Indian Ocean and land-based drought responses (precipitation, temperature, soil moisture, and SIF) were observed, which were attributed to atmospheric teleconnections. The positive phases of El Niño and the Indian Ocean Dipole (IOD) significantly impacted SST, triggering severe droughts in India in 2009 and 2015. The results revealed that positive SST anomalies weaken monsoon flow during the onset period, reducing moisture transmission to the Indian subcontinent. In 2009, the precipitation anomaly showed severe drought conditions (&lt;−1.5) primarily in the northwest, central northeast, and west-central subregions, respectively, with soil moisture deficit and reduced photosynthetic activity (indicated by negative SIF anomalies) mirroring precipitation anomalies. In 2015, moderate to severe drought conditions affected regions primarily in the west-central and peninsular areas, with corresponding consistency in SIF anomalies and soil moisture deficits. These conditions led to decreased photosynthetic rates and negative SIF anomalies observed across India. The findings provide insights for predicting droughts and understanding ecosystem impacts across India amidst rapidly changing climate conditions in the Indian Ocean region.

Two Large-Scale Meteorological Patterns are Associated with Short-Duration Dry Spells in the Northeastern United States

Abstract Large-scale meteorological pattern (LSMP)–based analysis is used in a novel way to understand meteorological conditions before and during short-duration dry spells over the northeastern United States. These LSMPs are useful to assess models and select better-performing models for future projections. Dry-spell events are identified from histograms of consecutive dry days below a daily precipitation threshold. Events lasting 12 days or longer, which correspond to ∼10% of dry-spell events, are examined. The 500-hPa streamfunction anomaly fields for the first 12 days of each event are time averaged, and k-means clustering is applied to isolate the dry-spell-related LSMPs. The first cluster has a strong low pressure anomaly over the Atlantic Ocean, southeast of the region, and is more common in winter and spring. The second cluster has strong high pressure over east-central North America and is most common during autumn. Over the region, both clusters have negative specific humidity anomalies, negative integrated vapor transport from the north, and subsidence associated with a midlatitude jet stream dipole structure that reinforces upper-level convergence. Subsidence is supported by cold-air advection in the first cluster and the location on the east side of the lower-level high pressure in the second cluster. Extratropical cyclone storm tracks are generally shifted southward of the region during the dry spells. Individual events lie on a continuum between two distinct clusters. These clusters have similar local, but different remote, properties. Although dry spells occur with greater frequency during drought months, most dry spells occur during nondrought months. Significance Statement This study examines the large-scale weather patterns and meteorological conditions associated with dry-spell events lasting at least 2 weeks while affecting the northeastern United States. A statistical approach groups events together on the basis of similar atmospheric features. We find two distinct sets of patterns that we call large-scale meteorological patterns. These patterns reduce moisture, foster localized sinking, and shift the storm track southward along the Atlantic seaboard, all of which reduce precipitation. Besides greater understanding, knowing the meteorological patterns during short-term dryness in the region provides an important tool to assess how well atmospheric models reproduce these specific patterns. More dry spells occur in nondrought months than in drought months, which means that dry spells can occur without preexisting drought conditions.

The genetic diversity and population structure of weedy rice in northeast Thailand accessed by SSR markers

AbstractThailand’s northeast (NE) region is an area of high-quality cultivated rice (Oryza sativa L.) production. However, an outbreak of weedy rice has recently spread throughout the region. Weedy rice is phenotypically and morphologically similar to cultivated rice, making identification difficult. The prospective management of weedy rice in the future will involve the study of its genetic diversity and population structure in this region. This study assesses the genetic diversity and population structure of 380 weedy rice samples in the northeast of Thailand through simple sequence repeat (SSR) markers. Thirty-one SSR markers generated 213 alleles with an average of 6.87 per locus and an overall genetic diversity of 0.723. Based on its geographic origin, weedy rice in the Southern NE are showed greater genetic diversity than that in the Central NE and Northern NE areas. The outcrossing rate in all regions was relatively high, with the highest being in the Southern NE at 9.769%. According to genetic distance analysis, the clustering of weedy rice samples in northeast Thailand was not associated with the geographic region. Neighbor-joining and principal coordinate analysis revealed that the 380 weedy rice samples fell into two major clusters. Cluster I contained three weedy rice samples and four wild. In Cluster II, 377 weedy rice samples were closely related to the four cultivated rice cultivars as well as brownbeard rice (Oryza rufipogon Griffiths) wild species. The results suggest that weedy rice in northeast Thailand may have originated as a cross between cultivated and wild rice, as seen in the closely related species, O. rufipogon. Overall, the findings of this study demonstrate the high genetic diversity of weedy rice in this region. Notably, some samples adapted, performing more like cultivated rice, which may be problematic for the future production of high-quality rice in this region. The prevention of weedy rice should, therefore, be given greater consideration in future studies.

Climatic Stress Test of Scots Pine Provenances in Northeastern Europe Reveals High Phenotypic Plasticity and Quasi-Linear Response to Warming

Research Highlights: Scots pine (Pinus sylvestris L.) phenotypic plasticity will buffer and even benefit from temperature increases in Northeast Europe this century, except for the southern peripheries of the range. Objectives: The “stress test” aimed to assess the inherent potential of existing populations to withstand projected changes in their lifetimes at their original location. Materials and Methods: This study applied an alternative analytic approach to calculate response and transfer equations from historic height growth data from provenance tests in the former USSR and Hungary. Results: Contrary to earlier analyses, the populations displayed quasi-linear responses to mimicked warming without clear ecological optima, forecasting a general growth acceleration north of Lat. 53° N. Climate-triggered mortality is predicted for the near future in the southern peripheries. Locally adapted populations at the distribution confines of the northern and southern limits deserve special attention. Conclusions: The observed adaptability to warming moderates the necessity of genetic management interventions such as assisted migration. The support of natural processes of adaptation and acclimation will be sufficient in boreal and central Northeast Europe this century. Evacuating heat and drought-tolerant populations should be envisaged in the endangered zone to conserve valuable genetic resources.

Spatio-temporal compounding of connected extreme events: Projection and hotspot identification

In general, the impact of two different connected extreme events is noticed on the same duration and spatial area. However, the connected extreme events can have footprint over different temporal and spatial scales. Thus, this article analyses the connected extreme events over India using the spatio-temporal compounding technique to understand the impact at different temporal and spatial scales. This approach is applied to analyse the historical and future connected extreme events. In the present study, coincident heat waves and droughts (Event C1), coincident heat waves and extreme precipitation (Event C2) are considered as connected extreme events. The future events are investigated using the suitable global climate models (GCMs) projections under three climate change scenarios (Shared Socioeconomic Pathways (SSP) 2–4.5, SSP3-7.0, and SSP5-8.5). The suitable GCMs are identified with the help of compromise programming. Subsequently, the hotspot regions are identified applying the Regional Climate Change Index (RCCI) method. The outcomes from the study suggest that with increasing temporal compounding, the mean duration of extreme events also increases. Highest increase in mean duration is observed for Event C1 over PI (Peninsular India), WCI (West Central India), and some parts of CNI (Central Northeast India) regions. The regions with high magnitude of duration have low magnitude of occurrence. The duration of Event C1 is likely to increase with respect to climate change scenarios and temporal compounding, especially in the PI region and some parts of WCI. However, there is insignificant change in the duration of Event C2. The PI region identified as the most vulnerable region followed by WCI and HR regions. The highest percentage of area under the emerging hotspot category is noticed under SSP5-8.5 climate change scenario.

Absence of Large‐Scale Ice Masses in Central Northeast Siberia During the Late Pleistocene

AbstractOngoing speculation regarding the existence of large Late Pleistocene ice masses in Northeast Eurasia reflects the dearth of age constraints on glaciations across this vast region. Here, we report the first dates from the central part of Northeast Siberia, consisting of 22 cosmogenic 10Be exposure ages from boulders deriving from a sequence of three moraines in the Chersky Range. The dated moraine sequence indicates progressive contraction of maximum glacier extent from Marine Isotope Stage 6 to the Last Glacial Maximum, while the remotely‐sensed mapping indicates an older, more expansive glaciation in the region yet undated. Our results show that Late Pleistocene glaciations were limited to the highlands, and Northeast Siberia did not host a large, coalescent ice sheet during the Last Glacial Maximum or Marine Isotope Stage 6.

Assessment of integrated patterns of human-animal-environment health: a holistic and stratified analysis

BackgroundData-driven research is a very important component of One Health. As the core part of the global One Health index (GOHI), the global One Health Intrinsic Drivers index (IDI) is a framework for evaluating the baseline conditions of human-animal-environment health. This study aims to assess the global performance in terms of GOH-IDI, compare it across different World Bank regions, and analyze the relationships between GOH-IDI and national economic levels.MethodsThe raw data among 146 countries were collected from authoritative databases and official reports in November 2021. Descriptive statistical analysis, data visualization and manipulation, Shapiro normality test and ridge maps were used to evaluate and identify the spatial and classificatory distribution of GOH-IDI. This paper uses the World Bank regional classification and the World Bank income groups to analyse the relationship between GOH-IDI and regional economic levels, and completes the case studies of representative countries.ResultsThe performance of One Health Intrinsic Driver in 146 countries was evaluated. The mean (standard deviation, SD) score of GOH-IDI is 54.05 (4.95). The values (mean SD) of different regions are North America (60.44, 2.36), Europe and Central Asia (57.73, 3.29), Middle East and North Africa (57.02, 2.56), East Asia and Pacific (53.87, 5.22), Latin America and the Caribbean (53.75, 2.20), South Asia (52.45, 2.61) and sub-Saharan Africa (48.27, 2.48). Gross national income per capita was moderately correlated with GOH-IDI (R2 = 0.651, Deviance explained = 66.6%, P < 0.005). Low income countries have the best performance in some secondary indicators, including Non-communicable Diseases and Mental Health and Health risks. Five indicators are not statistically different at each economic level, including Animal Epidemic Disease, Animal Biodiversity, Air Quality and Climate Change, Land Resources and Environmental Biodiversity.ConclusionsThe GOH-IDI is a crucial tool to evaluate the situation of One Health. There are inter-regional differences in GOH-IDI significantly at the worldwide level. The best performing region for GOH-IDI was North America and the worst was sub-Saharan Africa. There is a positive correlation between the GOH-IDI and country economic status, with high-income countries performing well in most indicators. GOH-IDI facilitates researchers' understanding of the multidimensional situation in each country and invests more attention in scientific questions that need to be addressed urgently.Graphical

Evaluation and future projection of the extreme precipitation over India and its homogeneous regions: A regional earth system model perspective

AbstractA regional earth system model (ROM) was used to examine the projected change in the precipitation extremes (PEs) and associated dynamical and thermodynamical processes over India during the Indian summer monsoon (ISM). In this regard, PEs are computed for India, its six homogeneous regions and subregions the Western Ghats (WG) and central India (CI). The changes are computed for mid‐future (2040–2069: MDF) and far‐future (2070–2099: FRF) with respect to the historical period (1969–2000). ROM showed better resemblance with observation in simulating PEs over other regional climate models (RCMs) that participated in the CORDEX‐CORE simulation. The intense rainfall (95th percentile: R95) is expected to be enhanced over most of the region during MDF that further intensifies in FRF except CNE (central northeast) and NEI (northeast India), where the increase in R95 was restricted only up to MDF. Interestingly, very intense rainfall (99.9th percentile: R99) showed robust increases in both MDF and FRF for all regions. Additionally, long wet (dry) events were shortened (lengthen). Moreover, the short wet and dry spell frequency has increased, while the duration of the wet (dry) spell has decreased (increased) in both time slices over India with noticeable regional variation. This is attributed to the strong cyclonic circulation, reduced vertical wind shear and enhanced moisture transport during the ISM in both time slices. It is very important to highlight the substantial changes in the precipitation extremes to have better planning and strategies that will be helpful to minimize the incurred losses.

Spatial Genetic Structure and Diversity of Large Yellow Croaker (Larimichthys crocea) from the Southern Yellow Sea and North-Central East China Sea: Implications for Conservation and Stock Enhancement

As a wild resource, the large yellow croaker Larimichthys crocea has been seriously threatened since the mid-1980s. Owing to the implementation of protection measures, such as the establishment of a protection zone, fishing prohibitions, restocking programs and successful mariculture, its resources have gradually recovered year by year. Limited by the low spatial resolution and incomplete spatial coverage of sampling stations, the spatial genetic structure and diversity of large yellow croakers from the southern Yellow Sea and north-central East China Sea remains unclear. In order to evaluate the genetic diversity status of this wild stock, 22 wild sites were collected from the southern Yellow Sea and north-central East China Sea and analyzed by investigating genetic variability and its population structure using mitochondrial COI sequence in this study. Among the 662 sequences, a total of 71 different haplotypes were defined. The haplotype diversity (h) and nucleotide diversity (π) values were 0.644~1.000 and 0.00220~0.00473 respectively. The highest h and π occurred in the southern Yellow Sea (YS). AMOVA analysis showed no genetic differentiation among those 22 sites after Bonferroni correction. By comparing with previous studies, the croaker has maintained relatively steady genetic diversity in recent years. Our result also suggested that the croakers in the South Yellow Sea and north-central East China Sea belonged to the same group. Thus, they can be released as a management unit without regard for heterogenicity among those in the sea area. The YS populations can serve as parents for released fish fries in the South Yellow Sea and north-central East China Sea.

Power and Play

Power and Play

Retention Basin Water Quality in Tubuhue Urban Village North Central East Regency

The community carries out bathing and washing activities directly in the retention basin which can cause polluted water. Water quality checks need to be carried out before treatment. The purpose of this study was to determine the quality of water in the retention basin. Determination of the sampling location by purposive sampling. Sampling was carried out once in August 2021. Parameter measurements were carried out in the field and in the laboratory. The measurement results are compared with the quality standards listed in the Regulation of the Minister of Health of the Republic of Indonesia Number 32 of 2017 concerning Environmental Health Quality standards and Water Health Requirements for Sanitary Hygiene, Swimming Pools, Solus Per Aqua and Public Baths. A parameter that passed the quality standard was E-Coli while pH, hardness, nitrate, temperature, and TDS still met the quality standards. Retention basin water in Tubuhue Village seen from the parameters of temperature, pH, TDS, hardness, and nitrate can be used for sanitation hygiene purposes, but judging from the parameter E-Coli cannot be used for sanitary hygiene purposes.

Climate warming and summer monsoon breaks drive compound dry and hot extremes in India

Considering the severe impacts of compound dry and hot extremes, we examine the primary drivers of CDHEs during the summer monsoon in India. Using ERA5 reanalysis, we show that most of the CDHEs in India occur during the droughts caused by the summer monsoon rainfall deficit. Despite a decline in the frequency of summer monsoon droughts in recent decades, increased CDHEs are mainly driven by warming and dry spells during the summer monsoon particularly in the Northeast, central northeast, and west central regions. A strong land-atmospheric coupling during droughts in the summer monsoon season leads to frequent CDHEs in the Northwest and southern peninsular regions. Furthermore, regional variations in land-atmospheric coupling cause substantial differences in the CDHE occurrence in different parts of the country. Summer monsoon rainfall variability and increased warming can pose a greater risk of compound dry and hot extremes with severe impacts on various sectors in India.

Spatial multivariate selection of climate indices for precipitation over India

Large-scale interdependent teleconnections influence precipitation at various spatio-temporal scales. Selecting the relevant climate indices based on geographical location is important. Therefore, this study focuses on the spatial multivariate selection of climate indices influencing precipitation variability over India, using the partial least square regression and variable importance of projection technique. 17 climate indices and gridded precipitation dataset (0.25 × 0.25°) from the Indian Meteorological Department for 1951–2020 at a monthly scale are considered. Results show that among all the indices, Nino 4, Nino 1 + 2, Trans Nino Index, Atlantic Multidecadal Oscillation (AMO), quasi-biennial oscillation (QBO), Arctic oscillation (AO), and North Atlantic Oscillation (NAO) have a significant influence on precipitation over India. Further, within homogenous regions, it is found that the Southern Oscillation Index and Nino 3.4 are selected majorly in the South Peninsular compared to other regions. The NAO/AO show a similar pattern and was found to be relevant in the Northeast region (>89%). AMO is selected mainly in Northwest, and West Central (>80%), AMO and QBO at about 70% of grid locations over Central Northeast India. It is to be noted that the number of climate indices identified varies spatially across the study region. Overall, the study highlights identifying the relevant climate indices would aid in developing improved predictive and parsimonious models for agriculture planning and water resources management