Rainfall Patterns Research Articles

Transient analytical solution for coupled water–gas transport in unsaturated soil cover of landfill

A new analytical solution for coupled water–gas transport in unsaturated landfill cover system is proposed, which can consider transient diffusive-advective transport of gas under transient water transport condition. The proposed analytical solution is first verified against the laboratory measurements and numerical simulations. Using the proposed solution, parametric studies are conducted on the coupled transient behaviors of water–gas transport. The results show that ignoring the coupling effect can lead to significant error in gas transport results under various conditions, e.g., the surface gas emission flux is underestimated by about 28.3%∼79.8% due to ignoring the spatial and temporal variations of water content induced by transient water transport. The influencing parameters (i.e., initial saturation degree, rainfall patterns, and evaporation rate) all have significant impact on the coupled water–gas transport behaviors. The magnitude of the error induced by ignoring the coupling effect increases with increasing initial saturation degree and increasing evaporation rate (e.g., for initial saturation degree increasing from 0.35 to 0.95, the accumulated percolation at cover bottom increases by 10.9 times and the gas emission flux at cover surface decreases by 64.7%). The results highlight that it’s imperative to consider the effect of transient water transport when one needs more accurate assessment of gas transport results in the cover. This analytical solution can also be utilized to aid landfill cover design and to verify other numerical models.

Rainfall Pattern in Kenya: Bayesian Non-parametric Model Based on the Normalized Generalized Gamma Process

Rainfall Pattern in Kenya: Bayesian Non-parametric Model Based on the Normalized Generalized Gamma Process

Investigation of pollutants accumulation in the submerged zone for pyrite-based bioretention facilities under continuous rainfall events

Submerged zone in bioretention facilities for stormwater treatment has been approved to be an effective structure amendment to improve denitrification capability. However, the role and influence of water quality changes in the submerged zone under natural continuous random rainfall patterns are still not clear, especially when the rainfall is less than the pore water in the submerged zone. In this study, continuous rainfall events with different rainfall volume (light rain-light rain-heavy rain) were designed in a lab-scale woodchip mulched pyrite bioretention facility to test the effects of rainfall pattern. The results exhibited that light rain events significantly affected the pollutant removal performance of bioretention for the next rainfall. Different effects were observed during the long-term operation. In the 5th month, light rain reduced the ammonia removal efficiency of subsequent rainstorm events by 8.70%, while in the 12th month, when nitrate leakage occurred, light rain led to a 40.24% reduction in the next heavy rain event's nitrate removal efficiency. Additionally, light rain would also affect the concentration of by-products in the next rainfall. Following a light rain, the concentration of sulfate in the subsequent light rainfall can increase by 24.4 mg/L, and by 11.92 mg/L in a heavy rain. The water quality in the submerged zone and media characteristics analysis suggested that nitrogen conversion capacity of the substrate and microbes, such as Nitrospira (2.86%) and Thiobacillus (35.71%), as well as the in-situ accumulation of pollutants under light rain played important roles. This study clarifies the relationship between successive rainfall events and provides a more comprehensive understanding of bioretention facilities. This is beneficial for field study of bioretention facilities in the face of complex rainfall events.

Evaluate climate change and anthropogenic activities influencing geochemical variations in sediment between and within the avulsion period in the Lower Yellow River avulsion channels

The geochemical data from sediments in avulsion channels provide historical evidence of climate change and human-induced alterations in river basin environments. The present study focused on the particle size of sediments in cores and the level of geochemical variation in avulsion channels of the Lower Yellow River Delta (YRD), China. The sediment samples were collected in a depth range of 20–400 cm in avulsion channels. The collected samples were analyzed for sediment particle size and geochemical composition using standard methods. The results demonstrated rapid increases in agriculture practices, rainfall pattern changes, and terrestrial sediment runoff reduction in river basins after the 1960s. The reduced sediment loads in the Sanmenxia Reservoir significantly changed the sediment grain size and geochemical levels in the avulsion channel from August 1960.8 to January −1961.1. In particular, TC, TN, and C/N levels decreased with increasing sediment depth. The C/N values of <12 denoted completely reduced terrestrial sources of organic matter in the channel during the August 1960–January 1961 period compared to the July 1953–August 1960 period. The two-way ANOVA p-values were (p <0.016-p<0.001) strong between the avulsion periods but had no significant variation within the avulsion periods. We emphasize that this study provides a close interplay of different historical periods of geochemical variation in avulsion channel sediments in the alluvial fan YRD, and we argue that the evolution of the middle upstream river basin was subjective by climate change and human developmental actions, which impacted the YRD. In particular, reservoir-interrupted water flow and sediment reduction impacts associated with geochemical fluctuations are documented in the YRD.

Assessing the effects of extreme rainfall patterns and their impact on dam safety: a case study on Indian dam failures

Assessing the effects of extreme rainfall patterns and their impact on dam safety: a case study on Indian dam failures

COPING STRATEGIES ON CLIMATE VARIABILITY AMONG COWPEA FARMERS IN KWARA STATE, NIGERIA

&lt;p&gt;&lt;strong&gt;Background.&lt;/strong&gt; The unstable climatic conditions can no longer be predicted by farmers. The unpredictability intensity of temperature and pattern of rainfall in cowpea production has affected the farmers’ decision on production practices and general productivity. Therefore, farmers are beginning to improvise on management practices to avert the effects of climate change to remain relevant and profitable in the business of cowpea production. &lt;strong&gt;Objective.&lt;/strong&gt; To examine the farmers’ coping strategies used against the effects of climate variability for cowpea production in Kwara State, Nigeria. &lt;strong&gt;Methodology.&lt;/strong&gt; A multistage sampling technique was used to select 120 cowpea-based farmers. A structured survey questionnaire was used to collect primary data. Data were analysed with frequency, percentage, mean, and standard deviation while Pearson Product Moment Correlation was used to ascertain the relationship between socioeconomic characteristics and copying strategies used by farmers. &lt;strong&gt;Results.&lt;/strong&gt; Majority (79.2%) of the respondents experienced high adverse effects of climate variability including abnormal rise in temperature (76.7%), irregular/unpredictable rainfall patterns (51.7%), and excessive rainfall (37.5%) on cowpea crop. The leading coping strategies used by farmers were use of fertilizer (x̄=2.73), herbicides (x̄=2.72), and planting early maturing variety (x̄=2.51). Farmers were mainly hindered by adequate irrigation facilities (x̄=1.72), inadequate access to extension services (x̄=1.66), and high cost of agrochemicals (x̄=1.60). Result education, cowpea farm size, years of experience in cowpea farming, membership in farmers group, and additional sources of information on cowpea production showed a positive significant relationship with the choice of coping strategies employed by cowpea farmers against the effects of climate change experienced at p&amp;lt;0.05 level. &lt;strong&gt;Implication.&lt;/strong&gt; The study showed that abnormal rise in temperature and irregular rainfall patterns are affecting cowpea production and thus, some socioeconomic attributes significantly supported farmers’ choice of coping strategies employed against the effects of climate change and variability. &lt;strong&gt;Conclusion.&lt;/strong&gt; The use of agrochemicals and cultivation of early maturing variety has played critical roles in coping with adverse effects of climate variability in cowpea production. &lt;/p&gt;

Climate change, seasonality and household water security in rural Gambia: A qualitative exploration of the complex relationship between weather and water

Climate change could pose a threat to water security for many communities, particularly in settings where rainfall patterns are becoming more varied and there is higher frequency of extreme events, such as heavy rainfall and droughts. Understanding how rainfall affects water security—including water access, water quality and water use behaviours—can inform investment in more climate-resilient infrastructure and safeguard against future health risks. This study aims to explore how households in rural Gambia experienced water security in relation to seasonal rainfall patterns and extreme weather events. Data collection focused on two communities (Kiang West and Basse) with differing access to water infrastructure, within which some villages had greater access to groundwater sources, such as solar-powered boreholes, and others primarily used uncovered wells. 46 participants were interviewed in Spring 2022 using multiple qualitative methods, including in-depth interviews and transect walks. We found that people’s experience of water security and rainfall (including seasonal rainfall, drought and heavy rainfall) was complex and varied according to the primary household water source. Both dry and rainy season posed challenges to household water security in terms of quality and quantity. Households with access to more resilient infrastructure, such as solar-powered boreholes, discussed a shift in the relationship between weather and water security, where they were less vulnerable to water shortages during dry conditions compared to those using wells. However, these sources did not fully resolve water security issues, as they experienced water shortages during cloudy conditions. Extreme weather events, such as heavy rainfall, heightened perceived water issues, as these events sometimes damaged water infrastructure and contaminated water sources. Seasonal workloads, that were higher in the rainy season, also jeopardised water security, as this limited time for water collection. Increased investment in infrastructure, maintenance, water-treatment and behavioural change is required to mitigate the risks.

Precipitation pulses and intraseasonal drought in Northeast China

30 years meteorological data were collected to analyze variations of precipitation amount, number of days, frequency and intervals using the Mann-Kendall (MK) and t test and relationships between rainfall patterns and climates over rainfed farmland. The results indicated that annual precipitation amount had a downward trend from 1989-2018. Whether in different years or months, small precipitation events(0&lt;P ≤5 mm) are a dominating feature, significantly and positively related to annual total precipitation, which mainly occur in early or late growing seasons (May or September). The precipitation intervals decrease along with the category, and are longer in the drought years than in the humid years. Percent of intervals &lt;6 days are more than 65%, the average dry days are 5. Short intervals(1-3 days) increase from May, get to the maximum in mid-growing season. Long intervals (&gt;4 days) are opposite. While in growing seasons, the average dry days are &lt;3 days.

Climate change impacts on rice cultivation paddies in the Plain of Reeds, Vietnam

Severe alterations in rainfall patterns have led to a shortage of irrigation water in rice paddies, resulting in income decline and spontaneous migration to urban centers. Recognizing the crucial significance of irrigation water for rice cultivation in the Plain of Reeds (PORs), this study aims to assess the impacts of rainfall characteristics alteration on rice yield in the concern of climate variation. The study focuses on variations in rainfall characteristics and their changing trends across the PORs. Non-parametric statistical approaches such as Mann-Kendall and Sen's slope estimator and Standardized Precipitation Index (SPI) are employed for data analysis. The study utilizes daily rainfall data spanning 38 years (1985-2022) from the National Center for Hydrometeorological Forecasting (NCHF). The results demonstrate significant changes in rainfall characteristics such as rainfall in rainy season (RRS), date of the rainy season onset (DRSO) and date of the rainy season cessation (DRSC). Rice productivity exhibits substantial changes, with increases during La-Nina years and significant decreases during strong El-Niño events across the study area. The findings provide valuable insights for discussing and formulating policies on adaptive agricultural production methods in response to changing climate conditions, ensuring sustainable crop production in the region.

Observations of enhanced rainfall variability in Kenya, East Africa

Understanding local patterns of rainfall variability is of great concern in East Africa, where agricultural productivity is dominantly rainfall dependent. However, East African rainfall climatology is influenced by numerous drivers operating at multiple scales, and local patterns of variability are not adequately understood. Here, we show evidence of substantial variability of local rainfall patterns between 1981 and 2021 at the national and county level in Kenya, East Africa. Results show anomalous patterns of both wetting and drying in both the long and short rainy seasons, with evidence of increased frequency of extreme wet and dry events through time. Observations also indicate that seasonal and intraseasonal variability increased significantly after 2013, coincident with diminished coherence between ENSO (El Nino Southern Oscillation) and rainfall. Increasing frequency and magnitude of rainfall variability suggests increasing need for local-level climate change adaptation strategies.

Assessing future urban flood hazard: A comprehensive approach to estimating the implications of future rainfall scenarios

AbstractEstimating potential changes in future flood patterns based on anticipated changes in hydrological characteristics within the basin is crucial for mitigating flood damage and managing flood risk. In this study, nonparametric probability models are used to estimate future rainfall patterns in Seoul under the GCM‐based climate change scenarios (CCS), and the estimated future daily rainfall data was temporally downscaled to hourly units using the KNNR‐GA technique. Changes in flood hazard and runoff characteristics of the target area based on the estimated future rainfall data are quantitatively assessed. The results highlight that under CCS, flood runoff may increase further into the future, resulting in more significant changes in flood patterns and accelerating the increase in flood hazard. The delta change factor of flood risk indicators increased relatively significantly in more severe CCS. This study also proposed a process to estimate future flood runoff and mitigation effects according to CCS by reflecting various flood mitigation measures in the urban drainage system model. These findings can offer valuable insights for setting the direction of current and future mitigation measures.

Ecological Studies and Epidemiological Aspects of Leptospirosis in the Northeast Region of Brazil

Introduction: Leptospirosis, a globally prevalent zoonotic infection, affects approximately one million people annually. Originating from the bacterium Leptospira, it is transmitted through contact with the urine of reservoir animals, such as rodents. In Brazil, it is endemic, especially in the Northeast region, where poor sanitary conditions contribute to its dissemination. The objective of this study is to analyze the main determining factors for the increase in leptospirosis cases in the Northeast region of Brazil, with an emphasis on rainfall patterns and deficiencies in basic sanitation. Methodology: The methodology consisted of a qualitative exploratory-descriptive bibliographic review of articles published between 2014 and 2024 in Portuguese, English, and Spanish. Inclusion criteria were relevance to the topic, while exclusion criteria involved duplicated articles or those that did not highlight the content of interest. The search was conducted in databases such as LILACS, SciELO, and PubMed, using specific descriptors. The analysis involved careful selection and exhaustive reading for the categorization of results. Results and Discussion: Leptospirosis impacts urban and poor areas, with over one million annual cases globally. Factors such as precipitation and disordered urbanization contribute to its spread, especially in tropical regions. Low-income populations are vulnerable due to the lack of basic sanitation. The unequal distribution reflects socio-economic disparities, with densely populated urban areas being more affected. Conclusion: Leptospirosis poses a challenge to public health, especially in regions with poor sanitary conditions. Effective control requires a comprehensive approach, including improvements in sanitation infrastructure, health education, and rodent control.

Revisiting the global weights of the integrated watershed health assessment framework and Weyib watershed health analysis: Ethiopia's policy prospects

AbstractWatershed health study has been considered as a global issue embodied in the United Nations' 2030 agenda toward sustainable water resources development, paving the way for integrated water resources management (IWRM) application, and visualizing intervention techniques to comprehend existing challenges. The watershed faces tremendous pressure due to erratic rainfall patterns, drastic water demand increase, hydrological extremes, and natural‐anthropogenic activities. This study aims to re‐evaluate the recently developed Integrated Watershed Health Assessment Framework (IWHF) global weights, Weyib watershed health assessment, and Ethiopia's policy implications using the integration of numerous data and multiple tools. The analytic hierarchy process (AHP) was used to estimate aggregate results from experts' survey responses, which depicted 50.89% priority for ecological conditions, followed by economic 23.30%, policy 13.82%, and 12% for socio‐cultural attributes. A slight discrepancy was exhibited when global weights were re‐evaluated, and the variables with substantial effects on IWHF in developing countries like Ethiopia were integrated. The majority of Weyib watershed health index (WWHI) indicators unveiled promising results except for stakeholders' collaboration and social obligation to restoration activities, information and educational campaigns, hydrology, wetland, and natural land‐cover. The water‐quality parameters laboratory findings were depicted as suitable for irrigation purposes. In general, the WWHI was in good health status, and a medium‐level priority was required for intervention activities to address deteriorated variables. Moreover, enhancing IWRM's application will contribute to tackling bottlenecks such as boost community awareness and stakeholder collaboration, legal and administrative gaps, overlapped mandates, and unpermitted water use resulting in undermining downstream demands and environmental low‐flow.

The possible impact of solar activity on rainfall in Nepal: A case study

This paper investigates the possible relationship between solar activity and monthly rainfall in Pokhara and Kathmandu cities in Nepal from the year 1968 to 2023. The study uses Cross Correlation Analysis (CCA) and wavelet analysis, the Cross-Wavelet Transform (XWT) and Wavelet Transform Coherence (WTC), to analyze the time series data. The CCA shows a strong positive correlation between the solar cycle and rainfall trend, with correlation coefficients of 0.77 and 0.76 and time lags of 18 months and 14 months at Pokhara and Kathmandu, respectively. The p-values, calculated to be < 0.0001 through the t-test, indicate that the observed correlations are statistically significant. The XWT results show a long-term ∼ 11-year common periodicity in solar cycle and rainfall. The WTC analysis confirms the local correlation between these two time series in time–frequency domain at a common periodicity. The results indicate that the monthly rainfall pattern in Nepal is closely related to the solar cycle pattern. Thus, solar activity likely plays a role in influencing rainfall trends in Nepal. This study shows that solar-climate interaction on a regional scale is complex and emphasizes the importance of understanding these relationships for predicting and managing climate change.

Modeling the impacts of extreme climate scenarios on soil acidity (pH and exchangeable aluminum) in Abbay River Basin, Ethiopia

The Abbay River Basin faces the looming threat of extreme climate events, including prolonged droughts and erratic rainfall patterns, which can significantly affect soil health and fertility. This study aimed to explore the influence of extreme climate conditions on soil pH and exchangeable aluminum, aiming to promote sustainable agricultural practices in Ethiopia. The Africa Soil Information Service (ASIS) provided datasets on soil pH and exchangeable aluminum. The European Copernicus Climate Change Data Store was used to download historical and future datasets of extreme climatic indices from 1980 to 2010 and 2015–2050, respectively. The Coupled Model Intercomparison Project Phase 6 model ensemble was used to predict future climate impacts under three shared socioeconomic scenarios: SSP1-2.6, SSP2-4.3, and SSP5-8.5. Data extraction, quality control, and clustering were conducted before analysis, and the model was validated for its accuracy and reliability in predicting soil parameter changes. An artificial neural network model was utilized to predict the effects of extreme climate indices on soil pH and exchangeable aluminum concentrations. The model was designed to accurately and reliably predict changes in soil parameters. This study compared the changes in soil pH and aluminum concentrations using paired t tests. The model's diagnostic results indicated a significant impact of extreme climate scenarios on soil pH and exchangeable aluminum. Extreme climate factors such as heavy precipitation and cooler night time temperatures significantly contribute to soil acidification and an increase in aluminum concentration. Under the SSP1-2.6 and SSP2-4.5 emission scenarios, soil pH levels are expected to increase by 8.38 % and 3.79 %, respectively. These changes in soil pH are expected to have significant impacts on the exchangeable aluminum content in the soil, with increases of 37 % and 5.38 %, respectively, under the same emission scenarios. However, the SSP5.8 scenario predicted a 45 % increase in exchangeable aluminum and a 9.36 % decrease in soil pH. Therefore, this study significantly enhances our understanding of the influence of climate change on soil health. The development of strategies to mitigate climate change impacts on agriculture in the region must consider the effects of extreme climate indices.

Reimagining nutrition education for pregnant adolescents in the face of climate change: a community approach

ObjectivesTo explore challenges with current nutrition education for teenage pregnant women in a drought-prone community in Kenya and to elicit the communities’ suggestions on how to best adapt it in...

Routine Climate Monitoring in the State of Hawai‘i: Establishment of State Climate Divisions

Abstract The Hawaiian Islands have some of the most spatially diverse rainfall patterns on Earth, affected by prevailing trade winds, midlatitude disturbances, tropical cyclones, and complex island topography. However, it is the only state in the United States that does not have assigned climate divisions (boundaries defining climatically homogeneous areas), which excludes it from many national climate analyses. This study establishes, for the first time, official climate divisions for the state of Hawai‘i using cluster analysis applied to monthly gridded rainfall data from 1990 to 2019. Twelve climate divisions have been identified: two divisions were found each for the islands of Kaua‘i (Leeward Kaua‘i and Windward Kaua‘i), O‘ahu (Waianae and Ko‘olau), and Maui County (Leeward Maui Nui and Windward Maui Nui), and six divisions were identified for Hawai‘i Island (Leeward Kohala, Windward Kohala, Kona, Hawai‘i Mauka, Ka‘u, and Hilo). The climate divisions were validated using a statewide area-weighted division-average rainfall index which successfully captured the annual cycle and interannual rainfall variations in the statewide average rainfall series. Distinct rainfall seasonality features and interannual/decadal variability are found among the different divisions; Leeward Maui Nui, Leeward Kaua‘i, Kona, and Hawai‘i Mauka displayed the most significant rainfall seasonality. The western Hawai‘i Island divisions show the most significant long-term decreasing trends in annual rainfall during the past 100 years (ranging from −2.5% to −5.0% per decade). With these climate divisions now available, Hawai‘i will have access to numerous operational climate analyses that will greatly improve climatic research, monitoring, education, and outreach, as well as forecasting applications.

Nature-based solution using a bioengineering strategy for soil erosion control in tropical climate with intense rainfall patterns

BackgroundIn the face of escalating soil erosion exacerbated by intense rainfall in tropical climates, the quest for sustainable and effective erosion control techniques is paramount. Nature-based solutions (NbS) using bioengineering strategies have emerged as a potential avenue, yet their efficacy and adaptability in such environmental conditions are not fully explored. ObjectiveThis study seeks to bridge the research gap by evaluating the effectiveness of a bioengineering approach, which involved a strategic plantation of Pigeonpea, Sesame, and Cowpea, as an NbS for soil erosion control under the challenging conditions of tropical climates. It emphasizes the rhizospheric characteristics of these species and their potential to offer a sustainable and environmentally friendly solution to soil erosion. MethodsEmploying a random block experimental design, the study compared the performance of Pigeonpea, Sesame, and Cowpea against conventional biosynthetic erosion control methods across various plots. Over 25 rainfall events, comprehensive data collection was undertaken, encompassing 150 measures of precipitation, surface runoff, and soil loss mass. Results: The findings reveal bioengineering solution's comparable, if not superior, effectiveness to conventional techniques, marked by minimal soil loss and enhanced water infiltration capabilities. Analysis of Covariance showcased a very large effect size, significantly underscoring bioengineering's efficacy in soil loss control. Notably, bioengineering's contribution extends beyond erosion control, fostering aquifer recharge and preventing sedimentation in water bodies. ConclusionsThis strategic plantation of Pigeonpea, Sesame, and Cowpea stands out as a promising NbS for soil erosion control in tropical climates, characterized by its sustainable approach and minimal environmental footprint. The study advocates for the broader integration of Pigeonpea, Sesame, and Cowpea in soil conservation practices, highlighting its potential to transform erosion control strategies towards greater environmental sustainability and effectiveness.

FITTING G-FAMILY PROBABILITY DISTRIBUTION AT THE RAINFALL DATA OF RAJSHAHI DISTRICT, BANGLADESH

Classical statistical distributions were recognized tool in case of different areas such as biological science, economics, finance, engineering and environmental science. But these types of distribution have some limitations for modeling real data. Researchers are trying to find out the best performing statistical distribution for modeling environmental data by adding extra parameters in these existing distributions which provide super flexibility in modeling. These extend to new families of these distributions generally defined as G-family distribution. Rainfall is one of the most important natural resources for agricultural production. The excess and deficit amount of rainfall sometimes be dangerous for agriculture production. So, the prior knowledge about the pattern of rainfall will help to solve food insecurity, water erosion and water pollution problems. In this study we compare the performance of Gamma uniform G, Log gamma G type-I, Log gamma G type-II , Marshall-Olkin G and Weibull G distribution where we consider lomax, f, chen and Weibull distribution as baseline distribution for modeling the rainfall data in case of Rajshahi district Bangladesh. The monthly rainfall data from January 1971 to December 2020 consider as study period. The empirical study shows that Marshall-Olkin Chen distribution gives better fitting results in case of Rajshahi district. This study will help policy makers to become aware of upcoming situations for solving water related problems.

Trend Analysis of Hydro-Meteorological Variables in the Wadi Ouahrane Basin, Algeria

In recent decades, a plethora of natural disasters, including floods, storms, heat waves, droughts, and various other weather-related events, have brought destruction worldwide. In particular, Algeria is facing several natural hydrometeorological and geological hazards. In this study, meteorological parameters (precipitation, temperature, relative humidity, wind speed, and sunshine) and runoff data were analyzed for the Wadi Ouahrane basin (northern Algeria), into which drains much of the surrounding agricultural land and is susceptible to floods. In particular, a trend analysis was performed using the Mann–Kendall (MK) test, the Sen’s slope estimator, and the Innovative Trend Analysis (ITA) method to detect possible trends in the time series over the period 1972/73–2017/2018. The results revealed significant trends in several hydro-meteorological variables. In particular, neither annual nor monthly precipitation showed a clear tendency, thus failing to indicate potential changes in the rainfall patterns. Temperature evidenced a warming trend, indicating a potential shift in the local climate, while streamflow revealed a decreasing trend, reflecting the complex interaction between precipitation and other hydrological factors.