Trend In Annual Rainfall Research Articles

Analysis of spatiotemporal distribution, variability, and trends of rainfall in Wollo area, Northeastern Ethiopia.

Ethiopia's agriculture is mostly dependent on rain, though the rainfall distribution and amount are varied in spatiotemporal context. The study was conducted to analyze the distribution, trends, and variability of monthly, seasonal, and annual rainfall data over the Wollo area from 1981 to 2022. To accomplish this, the study utilized the Climate Hazards Group Infrared Precipitation with Stations version two (CHIRPS-v2) data. Standard Rainfall Anomaly Index (SRA) and Coefficient of Variation (CV) were employed to examine rainfall variability and develop drought indices over southern Ethiopia. The Modified Mann Kendall (MMK) test, Sen's slope estimator and the innovative trend analysis (ITA) were employed to detect temporal changes in rainfall trends over the study period. The study found that the area experienced considerable rainfall variability and change, resulting in extended drought and flood events within the study period. Results from SRA and CV revealed interannual and seasonal rainfall variability, with the proportions of years below and above the long-term mean being estimated at 56% and 44%, respectively. The MMK test showed that the annual rainfall during the Kiremt (summer-main rainy season) had an increasing trend. On the other hand, rainfall for the Belg (short rain season for the study area) season and the Bega (winter) season showed a significantly decreasing trend (p < 0.05). Results from the innovative trend analysis (ITA) also revealed that the annual and seasonal rainfall trends exhibited different trends in varied magnitude for different stations. On a spatial basis, the eastern and northeastern regions of the study area showed trends of increasing rainfall during the Kiremt (JJA). Decision-makers and development planners need to design strategies to mitigate the risks posed by changes in rainfall variability and distribution and enhance community adaptation and mitigation capacities in Wollo, Ethiopia.

Spatial and Temporal Variability of Rainfall in the Western Region of Nepal

The temporal and spatial variability of seasonal, annual, and decadal rainfall over 44 years in western Nepal was investigated using rainfall data from 36 meteorological stations in various physiographic regions. Missing data were addressed using the normal ratio method, and significant trends in annual rainfall were assessed through the Man-Kendall test. Western Nepal receives about 79.7% of annual rainfall during the monsoon, followed by 10.7% during the pre-monsoon, 3.3% during the post-monsoon, and 6.3% during the winter. The analysis revealed distinct seasonal excess and deficit episodes, with the highest monsoon rainfall recorded in 2000 and the lowest in 1979. During the study period, there is a large temporal variability of seasonal and annual rainfall. The central part of western Nepal receives heavy rainfall in monsoon seasons than other parts. In winter seasons more rainfall is received in the Northwest part and decreases towards the central and eastern parts of western Nepal. The midlands of western Nepal received higher annual rainfall than the other regions. The present study identified that the seasonal rainfall has been decreasing patterns in the Western region of Nepal for the past four decades.

A hybrid ecological evaluation of the fisheries in changing climate: case study from a peri-urban tropical wetland of Kolkata, Eastern India.

The degradation of peri-urban wetlands has been a significant consequence of urban development and climate change. The present study discovered the decadal changes in land cover and climate impact on Raja Wetland, revealing significant alterations from 2011 to 2021. The analysis indicates substantial reductions in agricultural land (36.36%), fallow land (30.90%), water spread areas (10.14%) and surrounding wetlands (18.06%). Conversely, settlements, terrestrial vegetation and aquatic macrophytes increased by 19.77%, 3.39% and 1.16%, respectively. The primary driver of wetland shrinkage was urban expansion leading to a decrease in wetland area from 43.39ha in 2011 to 38.99ha in 2021. Climate data from 1991 to 2020 show a decreasing trend in annual rainfall (τ = - 0.274, p = 0.035) and an increasing trend in annual temperature (τ = 0.339, p = 0.009), with significant warming particularly during the monsoon months. The wetland's physicochemical attributes fluctuate seasonally, with eutrophic conditions prevailing (TSI range: 61.41-80.36). Notably, fish diversity is impacted by the dominance of the invasive species Oreochromis niloticus, which constitutes 89.31% of the catch. The established planktonic indicator genera of organic pollution were found to be abundant throughout the study period. These, combined with urban pollution and eutrophication, have led to a reduction in native fish species and overall aquatic health. The study highlights the urgent need for conservation measures to address the ecological imbalance and restore wetland resilience amidst ongoing climate and anthropogenic pressures. The communication also proposes various recommendations for the recovery and sustainable future use of wetland fisheries in the context of ongoing changes.

Regulatory Threshold of Soil and Water Conservation Measures on Runoff and Sediment Processes in the Sanchuan River Basin

Research on the runoff and sediment reduction effects of soil and water conservation measures has always been a topic of interest, which is of great significance for carrying out sustainable strategies for soil and water conservation in the Yellow River Basin. This study aims to find the threshold years of soil and water conservation measures for reductions in runoff and sediment. Through the analysis of various soil and water conservation measures, runoff, sediment, and rainfall data in the Sanchuan River Basin from 1960 to 2019, we determined the threshold years of soil and water conservation measures on runoff and sediment processes using the Hydrology and Lagrange Multiplier method. The results are as follows: The trend in flood season rainfall and annual rainfall in the Sanchuan River Basin is consistent. The 1990s was a turning period in the annual rainfall and flood season rainfall of the Sanchuan River Basin. The 2000s was a turning period of the runoff in the Sanchuan River Basin, while the sediment entered a stable period after 2000. The best periods for reducing runoff and sediment were the initial treatment period (1967–1979) and the centralized treatment period (1980–1996). The runoff and sediment reduction effects of each soil and water conservation measure during the initial treatment period (1967–1979) were terrace (32.8%) &gt; dam (30.1%) &gt; grass (18.6%) &gt; forest (18.5%), while their effects during the centralized treatment period (1980–1996) were grass (53.7%) &gt; terrace (20.7%) &gt; dam (14.6%) &gt; forest (11.0%). The runoff and sediment reduction effects of various soil and water conservation measures during different treatment periods indicate that the runoff reduction effect reached its peak in 2003–2005, while the sediment reduction benefit reached its peak in 2013–2015. Based on the comprehensive benefits of runoff and sediment regulation, 2013–2015 are considered to be the threshold years for various soil and water conservation measures, with the measures covering respective average areas of 4.85 × 104, 17.80 × 104, 1.15 × 104, and 0.82 × 104 hm2. These research results will have a certain significance for the reasonable allocation of soil and water conservation measures and sustainable development in the Yellow River Basin.

Investigating precipitation pattern and variability in the Niger Delta: a statistical analysis of trends and change points (1972–2022)

There has been significant variation in precipitation in different parts of the world, and increasingly this has been attributed to climate change. Despite reliance on rain-fed agriculture, detailed analysis of regional precipitation trends within specific sub-national areas, such as the Niger Delta, remains scant. This study examines annual rainfall trends over 51 years (1972–2022) across seven stations in the Niger Delta using different statistical methods. Descriptive statistics show different patterns among stations, some showing upward trends, others declines. Mean annual rainfall ranges from 1,969.05 mm in Akure to 2385.04 mm in Port Harcourt, showing significant regional variability. Linear regression and LOWESS analysis show mixed trends; Mann–Kendall and Spearman’s Rho tests showed significant increase in Owerri, while Sen’s slope analysis confirms varying trends across the region. Pettitt test results confirms Owerri’s significant increase in precipitation. This study contributes to a greater understanding of precipitation trends in the Niger Delta.

Spatial-temporal seasonal and annual rainfall trends and variability assessment in the Pangani Basin, East Africa

Although in situ rainfall data remains the most accurate, the gauge network density in East Africa is sparse. It lacks continuity, thus making it inadequate to assess the spatial and long-term rainfall trend and variability accurately. As such, rainfall remote sensing data are normally used instead of ground station data. This study evaluates the capabilities and limitations of remote sensing data compared with ground-based observations in Tanzania's Pangani Basin in assessing the seasonal and annual rainfall trends and variability. Data from the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) and twenty-three ground stations were analyzed, comprising a time series from 1990 to 2022. Trend analysis was conducted using the Mann-Kendall test, while the spatial distribution of precipitation was determined using Sen's slope method. CHIRPS annual rainfall showed good agreement with station rainfall data, with NSE, R2, slope, Pbias, MAE, and RMSE values of 0.84, 0.92, 0.92, 7.55%, 297.4, and 397.1, respectively. The coefficient of variation from station data indicated extreme variability, exceeding 30% for annual rainfall, while CHIRPS data showed moderate variability, ranging from 20% to 30%. Both station data and remote sensing data showed an increasing trend for annual and seasonal rainfall at least 10 stations. However, stations like Maji Moshi, Kiungu Primary School, Segera C. Tank, and Kibong'oto exhibited an increasing trend for vuli rainfall with CHIRPS data, while station data indicated a significant decreasing trend.The study highlights the necessity for calibration and validation to avert misinterpretations in climate trend analyses, especially at the basin level.

Climatic and non-climatic factors driving the livelihood vulnerability of smallholder farmers in Ahafo Ano North District, Ghana

Smallholder farmers in Ahafo Ano North District, Ghana, face multiple climatic and non-climatic issues. This study assessed the factors contributing to the livelihood vulnerability of smallholder farmers in this district by household surveys with 200 respondents and focus group discussions (FGDs) with 10 respondents. The Mann–Kendall trend test was used to assess mean annual rainfall and temperature trends from 2002 to 2022. The relative importance index (RII) value was used to rank the climatic and non-climatic factors perceived by respondents. The socioeconomic characteristics affecting smallholder farmers’ perceptions of climatic and non-climatic factors were evaluated by the binary logistic regression model. Results showed that mean annual rainfall decreased (P>0.05) but mean annual temperature significantly increased (P<0.05) from 2002 to 2022 in the district. The key climatic factors perceived by smallholder farmers were extreme heat or increasing temperature (RII=0.498), erratic rainfall (RII=0.485), and increased windstorms (RII=0.475). The critical non-climatic factors were high cost of farm inputs (RII=0.485), high cost of healthcare (RII=0.435), and poor condition of roads to farms (RII=0.415). Smallholder farmers’ perceptions of climatic and non-climatic factors were significantly affected by their socioeconomic characteristics (P<0.05). This study concluded that these factors negatively impact the livelihoods and well-being of smallholder farmers and socioeconomic characteristics influence their perceptions of these factors. Therefore, to enhance the resilience of smallholder farmers to climate change, it is necessary to adopt a comprehensive and context-specific approach that accounts for climatic and non-climatic factors.

Rainfall Trend Analysis in Mysuru and Bengaluru Districts of Karnataka, India

Climate change is one of the most pressing challenges facing humanity today, with temperature, precipitation, and runoff being key indicators closely linked to its impact. Understanding the spatial variability and temporal trends of rainfall is crucial for effective water resource management and agriculture. This study focuses on analyzing rainfall data from the Mysuru and Bengaluru districts, located in the Southern and Eastern dry zones of Karnataka, respectively. These regions play a pivotal role in the state's agricultural development and overall economic growth. We utilized daily precipitation records from two meteorological stations, spanning the period from 1983 to 2018, to analyze rainfall trends on monthly, seasonal, and annual scales. To assess these trends, we applied both parametric and non-parametric statistical methods, including the simple regression method, Mann-Kendall test, and Sen’s slope estimator. The Mann-Kendall test was used to detect significant trends in the precipitation time series, while Sen’s slope estimator quantified the magnitude of these trends. Bengaluru had higher average annual rainfall (928.81 mm) compared to Mysuru (681.65 mm), with excess rainfall in 2005 and a positive Pre-Monsoon trend (+3.543 mm/year), while Mysuru experienced maximum rainfall deficit in 2016 and a negative Monsoon trend (-3.238 mm/year). Neither district showed a significant trend in annual rainfall. The findings of this trend analysis are essential for informed water resource planning and management in the region.

Long-Term Seasonal and Annual Rainfall Trend Analysis of Giridih District, Jharkhand, India

District Giridih is primarily rain dependent on its 95 per cent net cultivable land under summer-monsoon crops. It is classified as a mono-cropping area as it lacks irrigation facilities, essential for winter crops. In the last few years, the district experienced water stress due to the shortage of monsoon rainfall. We study long term seasonal and annual rainfall trend analyses for the Giridih district of Jharkhand in India using linear regression modelling. The last 100 years of data were taken for the study and were divided into two-time phases of 50 years each to analyse the changing pattern of rainfall trends. We found a decreasing trend in monsoon rainfall from 1 mm y-1 to 3 mm y-1 between the initial (1921-1971) and final (1972-2021) phase of the study period. Similarly, the return period of droughts (rainfall deficit years) has also reduced from 11 years to 5 years. The study has shown that the rainfall pattern has changed, with the winter months showing a decrease and the pre-monsoon months an increase in their relative contributions to the annual rainfalls. The study may help in the formulation of water resource conservation-oriented decision-making to cope-up with the rainfall uncertainties and meet the future water demand.

Assessing the current and future trends of climate extremes at Zarima subbasin North Western Ethiopia

Climate extreme events in Ethiopia have increased, impacting the country’s agriculture dependent economy. Localized studies on rainfall extremes provides valuable insights to develop mitigation measures. This study focuses on the analysis of rainfall extremes for the observed (1984–2018) and the future mid time period (2031–2065) and end time period (2066–2100) projected under RCP4.5: moderate emissions reduction scenario aiming to stabilize greenhouse gas concentrations by the mid-21st century and RCP8.5: high emissions scenario with continued increase in greenhouse gas emissions throughout the twenty-first century. Trend analysis was done using R statistical software modified Man Kendell package. The result revealed that the observed total rainfall in wet days (PRCPTOT) showed insignificant declining trend across the subbasin. Under the RCP4.5 scenario, mid time period projections indicated increasing trends in PRCPTOT at Maytsebri, Adiremet and Debarik stations while decreasing trends expected at Ketema Niguse and Zarima stations. In the RCP4.5 end time period, Debarik and Zarima stations showed increasing trends while other stations exhibited decreasing trends. Under the RCP8.5 scenario, PRCPTOT showed insignificant decreasing trend except Ketema Niguse station which showed significant increasing trend during the mid time period. The observed annual maximum 1-day rainfall (RX1day) and annual RX5day rainfall had both positive and negative trends over subbasin. The RCP4.5 scenario projected declining trends in annual RX1day rainfall, while the RCP8.5 scenario projected increasing trends, except the end time projection of Debarik station. Consecutive dry days (CDD) increased and Consecutive wet days (CWD) decreased insignificantly in majority the subbasin. Projections indicated higher CDD and decreased CWD are expected in majority of the subbasin area. These finding implied that further investigation is required on the impact of climate extremes.

Climate trend analysis in the ramis catchment, upper wabi shebelle basin, Ethiopia, using the CMIP6 dataset

Climate change, a global concern, has significant implications for rainfall and temperature patterns. A critical knowledge gap exists in understanding these implications for the Ramis catchment of the Upper Wabi-Shebelle Basin. This research projects future rainfall and temperature patterns in the Ramis catchment of the Upper Wabe-Shebelle basin. The projection utilized a multimodel comprising eight distinct general circulation models from coupled model intercomparison phase six (CMIP6) data simulation. These models were selected based on their performance, considering two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5). The Quantile Mapping (QM) bias correction technique, implemented in R, was used to enhance the reliability of extracted data. The Mann‒Kendall (MK) trend test method was employed to analyze temperature and precipitation trends for two future periods, 2030–2060 and 2061–2090, annually and seasonally. The results suggest a decrease in rainfall during the spring and Winter seasons for 2030 to 2060 and 2061 to 2090 respectively, potentially leading to water scarcity that could impact crop growth and water supply. A decreasing trend in annual rainfall was observed from 2030 to 2060 under SSP2-4.5 and SSP5-8.5 scenarios. The study also uncovered significant and consistent warming trends in maximum and minimum temperatures across the Ramis catchment under both the SSP2-4.5 and SSP5-8.5 scenarios. Rainfall Anomaly Index (RAI) analysis predicts a minor increase in rainfall in the Ramis catchment from 2030 to 2090 under both scenarios, with a notable RAI decrease expected in 2043–2071, indicating potential drought conditions. These findings offer critical insights for regional climate change impact assessments across the Ramis catchment.

Influence of large scale climate drivers on hydro-climate variability in Dwangwa River Basin, Malawi

Large-scale climate processes such as the Indian Ocean Dipole (IOD) have significant roles in modulating rainfall and hydrological systems. Understanding such processes can inform adaptation measures for climate change and variability, as well as water resource management and planning. This study investigated the impact of the Indian Ocean Dipole (IOD) on rainfall and discharge variability in the Dwangwa River Basin (DRB) in Malawi, a key inflow to Lake Malawi. Specifically, the study analysed annual rainfall variability trends from 1985 to 2015 using the Coefficient of Variation (CV) and the annual Precipitation Concentration Index (PCI). The significance and direction of rainfall and discharge trends were quantified using the Mann–Kendall trend test at α = 0.05 significance level. To evaluate the association between rainfall and IOD, the Pearson product moment used three IOD phases: positive, negative, and neutral. Simple linear regression was utilised to check the response of the river during the concerned IOD phases. The study found CVs between 20 and 30%, typical of climates with moderate monthly rainfall variability. The PCI ranged from 20 to 30%, suggesting a strongly seasonal and highly variable temporal intra-annual rainfall distribution in the DRB. Moreover, the Mann–Kendall test statistics showed insignificant decrease in annual rainfall trends. Further, the findings demonstrated an insignificant negative correlation between rainfall and positive IOD, with rainfall increases associated with negative IOD, whereas positive IOD is associated with decreased river discharge. Consequently, El Niño and a positive IOD could cause DRB to have low water availability. Therefore, the study demonstrates that rainfall is experiencing a decreasing trend, which is driven by large-scale mechanics.

Characterizing the variability and trend of rainfall in central highlands of Abbay Basin, Ethiopia: using IMERG-06 dataset

ABSTRACT This study examines the spatiotemporal variability and trends of rainfall in the central highlands of Abbay Basin using the Integrated Multi-satellite Retrievals for GPM (IMERG-06) dataset. Parameters on onset and cessation dates, dry spells, Coefficient of Variation (CV%), and Standardized Rainfall Anomalies were utilized to evaluate rainfall variability and seasonality. Trend analysis was carried out using Mann-Kendall test and Sen’s slope estimator. The results highlighted a consistent pattern of late onset and early cessation of rainfall. The CV values for annual (10.7%), kiremt (11.7%), and belg (10.6%) seasons rainfall indicate moderate variability, while bega (22.6%) rainfall showed higher variability. SRA findings reveal episodic fluctuations between wet and dry years. The trend analysis demonstrates a statistically significant increasing trend in annual (9.14 mm/year) and belg seasons (6.94 mm/year) rainfall. However, kiremt season exhibited statistically non-significant (p > 0.05) decreasing trend. The temporal variability in rainfall onset, cessation dates and duration significantly impacts agricultural processes such as tillage and planting operations, affecting crop production. While the study area holds potential for agricultural activities, climate variability may reduce productivity. Therefore, the study findings are valuable for agricultural developers, planners and water resource managers. Including additional weather elements is crucial to enhance the precision and reliability of these findings for practical applications.

Modelling and predicting annual rainfall over the Vietnamese Mekong Delta (VMD) using SARIMA

Climate and rainfall are extremely non-linear and complicated phenomena, which require numerical modelling to simulate for accurate prediction. We obtained local historical rainfall data for 12 meteorological stations in the Vietnamese Mekong Delta (VMD) for the 45-year period 1978–2022, to predict annual rainfall trends. A statistical time series predicting technique was used based on the autoregressive integrated moving average (ARIMA) model. We utilized the seasonal ARIMA process of the form (p,1,q)(P,1,Q) for our study area. The best seasonal autoregressive integrated moving average (SARIMA) models were then selected based on the autocorrelation function (ACF) and partial autocorrelation function (PACF), the minimum values of Akaike Information Criterion (AIC) and the Schwarz Bayesian Information (SBC). The seasonal autoregressive integrated moving average model with external regressors (SARIMAX) was discovered, and a series of SARIMA models of various orders were estimated and diagnosed. To evaluate model fitting, we used the Nash–Sutcliffe coefficient (Nash) and the root-mean-square error (RMSE). The study has shown that the SARIMA (1, 1, 1)(2, 1, 1)11 and SARIMA (1, 1, 1)(2, 1, 1)12 model were appropriate for analyzing and forecasting future rainfall patterns at particular meteorological station in the VMD. The results showed the SARIMA model is more reliable and provides more accurate projections than other commonly used statistical methods, notably interval forecasts. We found that interpretable and reliable near-term location-specific rainfall predicts can be provided by the SARIMA-based statistical predicting model.

GIS-based spatio-temporal analysis of rainfall trends under climate change in different agro-ecological zones of Wolaita zone, south Ethiopia

Understanding the spatiotemporal dynamics of climatic conditions within a region is paramount for informed rural planning and decision-making processes, particularly in light of the prevailing challenges posed by climate change and variability. This study undertook an assessment of the spatial and temporal patterns of rainfall trends across various agro-ecological zones (AEZs) within Wolaita, utilizing data collected from ten strategically positioned rain gauge stations. The detection of trends and their magnitudes was facilitated through the application of the Mann–Kendall (MKs) test in conjunction with Sen's slope estimator. Spatial variability and temporal trends of rainfall were further analyzed utilizing ArcGIS10.8 environment and XLSTAT with R programming tools. The outcomes derived from ordinary kriging analyses unveiled notable disparities in the coefficient of variability (CV) for mean annual rainfall across distinct AEZs. Specifically, observations indicated that lowland regions exhibit relatively warmer climates and lower precipitation levels compared to their highland counterparts. Within the lowland AEZs, the majority of stations showcased statistically non-significant positive trends (p > 0.05) in annual rainfall, whereas approximately two-thirds of midland AEZ stations depicted statistically non-significant negative trends. Conversely, over half of the stations situated within highland AEZs displayed statistically non-significant positive trends in annual rainfall. During the rainy season, highland AEZs experienced higher precipitation levels, while the south-central midland areas received a moderate amount of rainfall. In contrast, the northeast and southeast lowland AEZs consistently received diminished rainfall across all seasons compared to other regions. This study underscores the necessity for the climate resilient development and implementation of spatiotemporally informed interventions through implementing region-specific adaptation strategies, such as water conservation measures and crop diversification, to mitigate the potential impact of changing rainfall patterns on agricultural productivity in Wolaita.

Trend Analysis of Climatic Variables in the Cross River Basin, Nigeria

There have been several incidences of flood recently, which are believed to be aggravated by increased climatic variables as a result of perceived changes in climatic conditions (due to climate change) in the Cross River Basin. The basin is the most extensively developed and used river basin in the management of the water resources of the Cross River and Akwa Ibom States in Nigeria. In this paper, 30 years (from 1992 to 2021) of hydro-meteorological data (annual average rainfall, maximum and minimum temperatures, hu midity, duration of sunlight (sunshine hours), evaporation, wind speed, soil temperature, cloud cover, solar radiation, and atmospheric pressure) from four stations in the Cross River Basin were obtained from the Nigerian Meteorological Agency (NIMET), Abuja and subjected to trend detection analysis using the Mann–Kendall test to determine the trend in climatic parameters. The results indicate that there is a significant upward trend in annual rainfall in Ogoja but a downward trend in Calabar. The evaporation trend is significantly downward in Eket, whereas in Calabar, there is an upward trend in solar radiation. Generally, there is a significant rise in annual maximum temperature across the basin. Serial correlation and segmented regression analyses were performed to measure the impact of fluctuations in monthly and long-term Tahiti and Darwin’s Sea level pressures on the climatic variables at the Cross River Basin catchment. These analyses were necessary to determine the extent of the influence of the El Nino Southern Oscillation climatic cycle. The analyses show no significant association between the El Niño Southern Oscillation (ENSO) and rainfall or between the ENSO and runoff in the catchment. This implies that the impact of the ENSO on rainfall and runoff in the Cross River Basin catchment is not considerable. The intercepts derived from the segmented regression in Eket and Ogoja show significant positive trends in both areas for rainfall and runoff. The trends in intercepts suggest that there are external factors influencing rainfall and runoff other than ENSO events, thus strengthening the assertion of climate change. Results from this study will facilitate the understanding of the variability in climatic parameters by stakeholders in the basin, researchers, policymakers, and water resource managers.

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.

Mapping long-term Transformation of Wetlands and Annual Rainfall Variability in Madhubani District (1975-2022).

In addition to supporting a rich biodiversity, wetlands serve as ecosystems that connect aquatic and terrestrial settings. They also play a critical ecological role by providing essential supplies. According to the National Wetland Atlas (2010), Bihar has a total of 21,988 wetlands with a total area of 4,03,209 hectares. These wetlands exhibit great range of floral and faunal diversity with large number of endemic species. The present paper endeavors to map the natural wetlands of Madhubani district of North Bihar and assess their evolving hydro-physiographic characteristics. The study area is endowed with numerous small wetlands as it receives high average annual rainfall in Bihar. This study primarily emphasizes on identification of wetlands and their spatial-temporal assessment during the period 1975-2022 by utilizing datasets from various sources like topographical maps, satellite imageries, and other ancillary data. It uses geospatial tool like Arc Hydro and indices like Topographic Wetness Index (TWI) and Normalized Difference Wetness Index (NDWI) for identification and spatial-temporal assessment of wetlands during pre-monsoon and post-monsoon season. The study finds that despite being one of the rainiest districts of Bihar, the annual rainfall trends in Madhubani is decreasing. This has impacted upon the water quality, productivity, biodiversity and annual recharge of wetlands of Madhubani. Its entire geographic region has thus been significantly reduced as a result. Other important factors like accelerated anthropogenic intervention, land use changes and process of urbanization have contributed towards rapid transformation of floodplains of Madhubani District. These changes may affect future water potential of the region and thus threaten sustainability in the region.

Analysing Spatial and Temporal Rainfall Variability of Southern Rajasthan using GIS Approach

This study focuses on analysing the behavioral patterns of rainfall in southern Rajasthan, particularly in reference to its amount and variation over time. The study made use of standard meteorological weeks (SMW) and historic weekly rainfall records. IDW (Inverse Distance Weighting) interpolation technique within the ArcGIS platform was used for spatial analysis, creating spatial variation maps. It was found that significant rainfall occurred from Standard Meteorological Week (SMW)-22 to SMW-42. The weekly mean rainfall across the study area during the monsoon period ranged from 2.1 to 68.4 mm, with corresponding standard deviations ranging from 9.3 to 79.7 mm. Notably, the standard deviation was often higher than the mean, indicating substantial variability in weekly rainfall. Trend analysis using the Mann-Kendall test revealed that most stations in the study area exhibited no significant trend in annual rainfall data. Similarly, weekly rainfall data showed a trend in SMW-30 for 44 stations, while all other weekly data series did not exhibit significant trends, except for SMW-30. Stationarity was generally accepted for most weekly data series, except for SMW-30 and SMW-32, which showed non-stationary behavior. However, homogeneity tests indicated homogeneity in weekly rainfall data series for almost all selected stations. Overall, the study highlighted the significant variability in rainfall patterns in southern Rajasthan, with no significant trend in annual rainfall, except during the peak monsoon period (SMW-30). These findings contribute to a better understanding of regional rainfall behavior, which is crucial for water resource management and agricultural planning in the region.

Characterization of annual and seasonal rainfall trend using innovative trend analysis (ITA) and classical methods: the case of Wadi Sebou basin (WSB) Morocco

Characterization of annual and seasonal rainfall trend using innovative trend analysis (ITA) and classical methods: the case of Wadi Sebou basin (WSB) Morocco