Rainfall Variability Research Articles

Rainfall And Drought Characteristics For Crop Planning In Cuttack District Of Odishastate, India

The increasing frequency of agricultural droughts and variability in rainfall patterns over the past three decades prompted this study, which analyzed 34 years of block-wise daily rainfall data (1988-2021) from Cuttack district, Odisha. The aim was to determine the long-term average and temporal variability of rainfall on weekly, monthly, seasonal, and annual scales, with a focus on identifying strategies to mitigate production risks in the region. The average annual rainfall in Cuttack was 1597.6 mm, with August receiving the highest amount of rainfall (476 mm), followed by July (407 mm) during the monsoon season. A trend analysis on rainfall over the past 34 years showed an increasing pattern of an average 6.03 mm and 3.6 mm per year in annual and kharif season rainfall, respectively. Agricultural droughts were frequently observed during the early (22-28 Standard Meteorological Week) and late (36-42 SMW) stages of kharif crops. The study also revealed that the station is prone to mild-moderate meteorological droughts of different intensities, including mild,moderate, and severe. To minimize production risks, short duration, low water-requiring, high-value crops such as maize, pulses, oilseeds, and some vegetables are recommended for this region.

Madden Julian Oscillation Influence on Diurnal Variation of Rainfall in Mentawai Islands Indonesia from IMERG Observations

Abstract Mentawai is a small island located in the Indian Ocean, so its rainfall pattern tends to be different from the larger islands in Indonesian region. Various scales of factors influence this, one of which is Madden Julian Oscillation (MJO). The aim of this study is to determine effect of MJO in Mentawai Islands on the diurnal variation of rainfall. Rainfall data was collected from 2000-2022 from Integrated Multi-SatellitE Retrievals for GPM (IMERG). Diurnal variations were observed in the accumulation (PA), frequency (PF), and intensity (PI) of rainfall and MJO was classified into active phase (2, 3, 4, and 5) and inactive phase (1, 6, 7, and 8) during the seasonal period (DJF-MAM-JJA-SON). Diurnal peak times in PA, PF, and PI occur later when MJO is active than when MJO is inactive, especially in JJA and SON periods in Mentawai Islands and Mentawai Strait. When MJO is active, average PA and PF are higher than when MJO is inactive. The average of PI is higher around the ocean during active and inactive phases of MJO. The number of short-duration rainfall events occurred over the land, while long-duration rainfall occurred over the ocean.

Inter-annual variability in the phytoplankton abundance and community structure of a tropical monsoonal estuary in response to variable monsoonal patterns

The study elucidates the inter-annual and seasonal variability in the phytoplankton abundance and community structure concurrent to variable rainfall patterns in Chettuva, a tropical monsoonal estuary along the southwest coast of India. The phytoplankton community exhibited statistically significant inter-annual variation with a 1.2-fold increase in abundance (av. 19.44 ×104cellsL-1) in 2021 in comparison with 2019 (av. 15.30 ×104cellsL-1). A total of 87 phytoplankton species were observed during the study, among which Bacillariophyceae dominated with 52 species, followed by Dinophyceae (20 species), and to a lesser extent by Chlorophyceae (11 species) and Cyanophyceae (2 species). Phytoplankton community structure also showed variation, with 71 species contributing to the diversity in 2021 and 62 species in 2019. Though Bacillariophycea dominated during both years, the community was more diverse in 2021comparatively a more saline year Biddulphia sp. Coscinodiscus sp., Cyclotella striata, Melosira sulcata, Pleurosigma sp., and Skeletonema costatum were the diatoms common to both the years, though with varied abundance. Dinophyceae did not show a conspicuous change in community structure in both years, with mostly the same species contributing to the total phytoplankton population but showed slight variation in abundance. Cyanophycea was observed exclusively during the year 2021. The abundance and community structure of the species varied from year to year, but they also changed seasonally, with lower numbers observed during the monsoon compared to the post-monsoon period in both years. CCA analysis identified two groups of phytoplankton assemblages in relation to the prevailing environmental conditions. The Group I species preferred lower temperature and salinity and elevated nutrient concentrations and they dominated during the monsoon season. Group II species preferred high saline well oxygenated, nutrient-poor waters and they dominated during the post-monsoon. Furthermore, the trophic state index analysis indicated mesotrophic conditions during the monsoon, while eutrophic conditions were observed in the post-monsoon period.

Comprehensive two-dimensional analytical modeling of groundwater levels in bi-directional sloping heterogeneous aquifers under variable recharge conditions

This paper develops a comprehensive two-dimensional (2D) groundwater model that surpasses traditional one-dimensional approaches by incorporating extensive hydrological and geological data typically acquired through well drilling. The primary objective of this research is to explore and characterize the complex dynamics of groundwater flow within sloping heterogeneous aquifers subject to rainfall-induced recharge events. To achieve this, the study utilizes the 2D Boussinesq equation, which is enhanced with meticulously defined boundary conditions to more accurately reflect real-world scenarios. The Integral Transform Technique (ITT) is employed to derive an analytical solution that integrates the effects of variable rainfall recharge, aquifer inclination angles, and inherent heterogeneity. This analytical model effectively captures varying recharge dynamics, both spatially and temporally, contributing to a better understanding and management of groundwater systems. The paper presents a new analytical framework, offering deeper insights into how natural factors impact porous medium behavior, thereby providing strategic references for sustainable water resource management.

Spatiotemporal Rainfall Analysis of El Nino, Neutral and La Nina Years Across Belg and Kiremt Seasons Over Oromia Region Ethiopia

ENSO is the primary natural hazard that contributes to food insecurity and poverty. It has been influencing countries’ climatic regimes for decades, bringing frequent floods and droughts. There is limited knowledge on El Niño and La Niña occurrences that affect agricultural activities in the Oromia Region and occur during the Belg and Kiremt seasons when rainfall is distributed. Evaluating the spatiotemporal rainfall performance of ENSO years spanning Belg and Kiremt seasons rainfall distribution over the research area is the primary goal. For the study’s spatial and temporal analyses, satellite rainfall data from 1981 to 2021 was obtained from CHG-UCSB and https://earlywarning.usgs.gov/fews/ewx_lite/index.html, respectively. The study’s findings demonstrated a substantial association between the Belg and Kiremt seasons spanning El Niño and La Niña periods, with a range of correlation values indicating a weak, moderate, and strong relationship. Because of the spatial and temporal dynamics of this study area, ENSO phases indicate that exceptionally dry years are probably linked to El Niño occurrences in the region, whereas extraordinarily rainy years are likely linked to La Niña events. Seasonal rainfall performance and rainfall variability are impacted by ENSO events and other regional systems, with both positive and negative effects observed throughout the research area. In addition to examining the ENSO (Neutral, El Niño, and La Niña) that have a major impact on the seasonal rainfall performances in the Oromia region, this study also looked at the water availability, yield production, pastoralist and agro-pastoralist activities, and water availability. In summary, the results of this research can help us better understand the mechanisms underlying regional ENSO events and their causes, which will be especially useful when future climate conditions change.

Trends of Extreme Temperature and Rainfall Indices for Addis Ababa City, Ethiopia

The extreme temperature and precipitation index trend analysis for Addis Ababa city is presented in this study. The Bole and Tikur Anbesa observatories, two stations in the capital city of Addis Ababa, provide the temperature and rainfall variation used in this analysis. The RClim-Dex software has been used to find climate extreme indices for Addis Ababa city stations based on climate data for the period 1954 to 2019. The annual total precipitation trend (PRCPTOT) at the 5% significant level exhibits a positive slope at the Addis Ababa observatory and a negative slope at the Addis Ababa Bole station. SDII trends indicate an increase at the 5% significant threshold for both stations. At the 5% significance level, the trends for both stations’ maximum and lowest temperatures show a positive slope. Conversely, both stations exhibit a negative slope in the diurnal temperature ranges. The RClim-Dex results indicate that, while rainfall intensity is decreasing, there is a tendency for annual rainfall indices to increase at the Addis Ababa observatory station, but to decrease at the Bole station. Additionally, there is an upward slope for consecutive wet days for all stations. Nevertheless, steady warming patterns are evident for both the maximum and minimum temperature indices. In contrast, declining trends are shown in the diurnal temperature ranges.

Impacts of Irrigated Water Use on Household’s Income in South Wollo Zone, Amhara Regional State, Ethiopia

Agriculture is the backbone of the Sub-Saharan African economy. Ethiopia's GDP is also shared by 45 from the agriculture sectors. However, it is confronted and challenged by variable rainfall and climate changes. Particularly, in South Wollo zone, agriculture is not exceptional in facing such daunting challenges and effects of variable rainfall and climate change despite there are abundant alternative irrigated water resources. River and groundwater sources have not yet been used as alternative uses for agricultural production. As a result, rural households' income couldn’t meet their minimum food and nonfood requirements. This study, thus, attempted to evaluate the impact of irrigated water use on rural household's income in South Wollo Zone, Amhara regional state, Ethiopia. In pursuit of this, it employed a descriptive type of research design and triangulated research approach that consists of both quantitative and qualitative techniques. Primary and secondary data were collected from small scale irrigated households and secondary sources. Binary logistic regression was used to determine major significant factors that affect households' irrigated water use for agricultural production. A propensity core matching model was employed to evaluate irrigated water use and agriculture on household’s income. This study result (binary logistic regression result) showed that the household’s family size, land size and willingness were significant factors that determined irrigated water use for agricultural production at 95 percent level of significance. The propensity score matching model result also shows that irrigated water use significantly created significant impact on household’s income. It is, thus, keenly important to change and improve the smallholder farmer’s land size, extension services, rural credit, technology, education level, awareness about family size, and willingness to use irrigated water sources, such as, ground and river water for agriculture agricultural production that increase their level of income.

The Role of Climate Change and Human Intervention in Shaping Vegetation Patterns in the Fen River Basin of China: Implications of the Grain for Green Program

The Fen River Basin (FRB), an ecologically fragile region in China, exemplifies the intricate interplay between vegetation dynamics and both climatic and human-driven factors. This study leverages a 40-year (1982–2022) dataset, utilizing the kernel-based normalized difference vegetation index (kNDVI) alongside key climatic variables—rainfall (PRE), temperature (TMP), and solar radiation (SRAD)—to investigate vegetation variations and their drivers in the FRB, particularly in relation to the Grain for Green Program (GGP). Our analysis highlights significant greening across the FRB, with the kNDVI slope increasing by 0.0028 yr−1 and green-covered areas expanding by 92.8% over the study period. The GGP facilitated the greening process, resulting in a notable increase in the kNDVI slope from 0.0005 yr−1 to 0.0052 yr−1 and a marked expansion in the area of significant greening from 24.6% to 95.8%. Regional climate shifts, characterized by increased warming, heightened humidity, and a slight rise in SRAD, have further driven vegetation growth, contributing 75%, 58.7%, and 23.6% to vegetation dynamics, respectively. Notably, the GGP has amplified vegetation’s sensitivity to climatic variables, with areas significantly impacted by multiple climate factors expanding from 4.8% to 37.5%. Specially, PRE is the primary climatic influence, impacting 71.3% of the pertinent regions, followed by TMP (60.1%) and SRAD (30%). The integrated effects of climatic and anthropogenic factors, accounting for 47.8% and 52.2% of kNDVI variations, respectively, collectively influence 96% of the region’s vegetation dynamics. These findings underscore the critical role of climate change and human interventions in shaping vegetation patterns and provide a robust foundation for refining ecological conservation strategies, particularly in the context of global warming and land-use policies.

Does soil type influence the occurrence of fire outbreaks in Cerrado, Brazil?

Forest fires associated with anthropic activities in Cerrado, Brazil, have been the main cause of the degradation of the biome. Thus, this study aims to understand the dynamics of fire foci and Gross Primary Production as a function of soil classes in an Environmental Preservation Area. This study combined soil types with meteorological variables of rainfall, soil moisture and air temperature to relate to fire occurrences and Gross Primary Production (GPP) for the years 2001–2020. For the evaluated period, there was an increase in temperature (±0.5 ºC) and a reduction in rainfall (±50 % in the driest years). The highest numbers of fire outbreaks were recorded in the areas corresponding to the Neossolos (Arenosols), followed by Latossolos (Ferralsols) between August and October. The future projection of the occurrence of foci for the next 10 years indicated that there would be an increase in the number of fire foci in all soil classes (700 %), especially for Neossolos. The future projection of GPP for the next 10 years indicates that there would be a reduction in coverage, especially for Gleissolo (Gleysol, 40–80 %). As a prevention strategy, attention should be doubled between August and October, as these months are the most conducive to fire outbreaks in the Cerrado.

Unraveling the role of the western North Pacific circulation anomaly in modulating Indian summer monsoon rainfall variability beyond ENSO

The Indian summer monsoon (ISM) rainfall interannual variability is known to be strongly linked to the El-Niño–Southern Oscillation (ENSO). This linear relationship is the primary factor in controlling the interannual variation in ISM precipitation. However, there are many outlier cases, and such deviations pose significant challenges in seasonal prediction over this region. Here we show that such challenges can be attributed to anomalous atmospheric pressure patterns in the Western North Pacific (WNP) region. The anticyclonic circulation anomaly over WNP region causes the easterly wind toward the Indian subcontinent, leading to positive precipitation anomalies with stronger low-level moist convergence, while the cyclonic circulation decreases ISM precipitation. The linear baroclinic model simulation results further support that the WNP circulation pattern can serve as an independent factor for forecasting precipitation over India. The WNP circulation anomaly play the crucial role generating ISM precipitation particularly for July and September. Our study suggests that the role of the WNP circulation anomaly should be carefully considered as the secondary prevailing mechanism on the subseasonal timescale during the boreal summer in addition to the ENSO signal.

Global-scale water security and desertification management amidst climate change.

Deserts and semi-arid environments are habitats torare species, rich cultural heritage, and essential ecological processes. Approximately 46% of the world's surface area is covered by drylands (arid, semi-arid, and dry sub-humid areas), where 3 billion people live and unfortunately witness water insecurity and desertification implications. In this context, the present study argued that reduced dryland ecosystem services and decreased ecosystem health have resulted from the individual and compounding impacts of desertification, water scarcity, and climate change. At 1.5°C, 2°C, and 3°C of global warming, under the shared socio-economic pathway SSP2, the number of people living in drylands who will be affected by various effects on water, energy, and land sectors is projected to reach 951 million, 1152 million, and 1285 million, respectively. Due to combinations of land use change, rainfall variations, fire suppression, and CO2 fertilization, as well as unsustainable management, widespread woody encroachment has occurred in many shrublands and savannas in Africa, Australia, North America, and South America. This hasaltered biodiversity and reduces ecosystem services, such as water availability and grazing potential. The north side of the Mediterranean, southern Africa, and North and South America are projected to have the most semiarid expansion. Contrarily, drylands are expected to shrinkin India, northern China, eastern equatorial Africa, and the southern Sahara. Growing research evidence highlights the adoption of policy frameworks deriving the solutions from soil land management (SLM), indigenous and local knowledge (ILK), early warning systems coupled with adaptation and mitigation responses, and targets of sustainable development goals (SDGs).

Biotic and abiotic factors associated with genome size evolution in oaks.

The evolutionary processes that underlie variation in plant genome size have been much debated. Abiotic factors are thought to have played an important role, with negative and positive correlations between genome size and seasonal or stressful climatic conditions being reported in several systems. In turn, variation in genome size may influence plant traits which affect interactions with other organisms, such as herbivores. The mechanisms underlying evolutionary linkages between plant genome size and biotic and abiotic factors nonetheless remain poorly understod. To address this gap, we conducted phylogenetically controlled analyses testing for associations between genome size, climatic variables, plant traits (defenses and nutrients), and herbivory across 29 oak (Quercus) species. Genome size is significantly associated with both temperature and precipitation seasonality, whereby oak species growing in climates with lower and less variable temperatures but more variable rainfall had larger genomes. In addition, we found a negative association between genome size and leaf nutrient concentration (found to be the main predictor of herbivory), which in turn led to an indirect effect on herbivory. A follow-up test suggested that the association between genome size and leaf nutrients influencing herbivory was mediated by variation in plant growth, whereby species with larger genomes have slower growth rates, which in turn are correlated with lower nutrients. Collectively, these findings reveal novel associations between plant genome size and biotic and abiotic factors that may influence life history evolution and ecological dynamics in this widespread tree genus.

Comprehensive groundwater potential mapping in Nagaland, India using integrated geo-spatial techniques

Groundwater is essential for a sustainable future, yet identifying potential groundwater zones remains challenging in regions with varied hydro-geological conditions. Nagaland is a state in north-eastern India characterized by diverse terrain, complex geological formations, and seasonal variations in rainfall. The objective of the present study is to evaluate groundwater potential zones in Nagaland using an integrated Geographic Information System (GIS) and Analytical Hierarchy Process (AHP) methodology, resulting in the first comprehensive map addressing the region's diverse hydro-geological conditions. Several attributes like geomorphology, geology, slope, soil, rainfall, drainage density, and Land use/Land cover (LU/LC) were generated from available data resources like Landsat 8 and Sentinel-2 satellite imageries, the Geological Survey of India (GSI), Environmental Systems Research Institute (ESRI), the Food and Agriculture Organization (FAO), and the Climatic Research Unit (CRU). These datasets are extracted using the Arc-GIS (Arc-GIS Desktop 10.8.1), with weights assigned according to Saaty's scale, and subsequently normalized through the AHP. The findings reveal that 14% (2240km2) of the state has very good groundwater potential, 42% (6720 km2) is classified as good, 9% (1440 km2) as moderate, 27% (4320 km2) as poor, and 8% (1280 km2) as very poor. These insights are significant for regions like Mokokchung, Longleng, and Wokha, which require urgent intervention. Conversely, the study identifies Dimapur and Chumoukedima as areas with significant groundwater potential, capable of meeting rising water demands. The validation of these results using well discharge data from 12 monitoring wells supports these findings.

Assessment of rainfall variability in Ladakh amidst evolving climate

Assessment of rainfall variability in Ladakh amidst evolving climate

Analysis of rainfall variability and impact on the start and end dates of rainy seasons in the urban humid tropical zone: a case of the Yaoundé Town, Cameroon (Central Africa)

Analysis of rainfall variability and impact on the start and end dates of rainy seasons in the urban humid tropical zone: a case of the Yaoundé Town, Cameroon (Central Africa)

Rainfall Variability, Risk, and Resilience: A Comparative Study of Insured vs. Non-Insured Farmers in Maharashtra, India

This paper examines the risks involved in Maharashtra’s agriculture and investigates the mitigation strategies adopted by insured and non-insured farmers in Latur and Pune districts. By using a multi-stage sampling method, 400 sample households were selected from two districts. These households comprise 268 insured farmers and 134 non-insured farmers. The results reveal that both rainfall variability and reductions in crop prices significantly impact agricultural revenues. However, the specific risk that carries the most significant weight may vary depending on an individual’s insurance status. Insured farmers are most vulnerable to the unpredictable nature of rainfall, as insurance typically protects against yield losses but not necessarily against market fluctuations. Conversely, non-insured farmers face a constant threat from declining crop prices, even with a good harvest, as they lack the financial buffer provided by crop insurance. This study suggests that the government should integrate pricing risk with crop insurance to reduce risk in agricultural production. Additionally, the farmers should adopt an integrated approach to pest and disease management. The implementation of a comprehensive crop insurance program is needed to ensure equitable coverage for farmers, facilitating widespread benefits. Additionally, more efforts should focus on mitigation of identified risks such as input costs, market fluctuations, and production uncertainties.

Influence of Temperature Fluctuations on Rainfall Variations Using Statistical and Machine Learning Approaches over Selected Stations in Nigeria

Influence of Temperature Fluctuations on Rainfall Variations Using Statistical and Machine Learning Approaches over Selected Stations in Nigeria

Impact of the rural enterprise programme interventions on smallholder farmers’ climate adaptation strategies: Qualitative evidence from Ghana’s transitional agro-ecological zone

ABSTRACT This paper combines theoretical insights from vulnerability literature and interpretive paradigm using a qualitative approach involving semi-structured interviews and focus group discussions to examine smallholder farmers’ climate perception, adaptation strategies, and challenges under the rural enterprise programme interventions in the Kintampo South district of Ghana. The farmers reported rainfall variability and rising temperatures as their key observed changes. The study revealed that climate impacts on farmers and their agricultural systems are multidimensional, which affect their productive capacity and livelihoods. These impacts have pushed them to adopt adaptation strategies with the support of the programme interventions. The farmers benefitted from material and non-material resources, minimizing climate impacts and reducing vulnerabilities. The paper provides critical insights into how future agricultural development interventions could develop effective interventions to build sustainable agricultural systems and livelihoods that are inclusive, sustainable, and responsive to the needs of the most vulnerable communities and obviate smallholder farmers’ vulnerability.

Cloud computing and spatial hydrology for monitoring the Buyo and Kossou reservoirs in Côte d'Ivoire

The Buyo and Kossou reservoirs are crucial for water supply, agricultural irrigation, and hydroelectric power generation in Côte d'Ivoire. However, climate change threatens the stability and availability of these water resources by increasing rainfall variability, extending drought periods, and intensifying extreme weather events. These challenges underscore the need for precise and continuous monitoring of water levels and surface areas to ensure sustainable management. Due to the scarcity of gauging stations, the objective of this study is to leverage cloud computing technologies along with altimetric and satellite data, for effective reservoir monitoring. Tools like the EO-Africa program's Innovation Lab and Google Earth Engine (GEE), along with advanced image processing software such as PyGEE-SWToolbox and AlTis, were used to process large datasets from the Sentinel-1, Sentinel-2, and Sentinel-3 satellites. These satellites delivered extensive, high-resolution imagery and altimetric data, crucial for monitoring changes in the reservoirs. The processed data were validated with in-situ measurements, yielding a Root Mean Square Error (RMSE) of less than 0.4 m and a correlation coefficient exceeding 0.90. The results highlighted water surface and level changes from 2016 to 2022, with downward trends and seasonal variations closely aligning with in-situ measurements. The study also revealed that the relationship between water levels and surface areas is influenced by both precipitation and the hydrological regimes of the Bandama and Sassandra rivers, demonstrating the complexity of water dynamics in these reservoirs. This research emphasizes the effectiveness of integrating spatial hydrology with cloud computing tools for fast and accurate monitoring of large reservoir. The use of these advanced technologies provides near real-time, reliable, and easily accessible data, offering a significant advantage for water resource management in Côte d'Ivoire.

Intensifying droughts render more Sahel drylands unsuitable for cultivation

Two-fifth of the world's population will be confronted by dire land and water shortage for food production by 2050. Here we provide nuanced insights into the Sahel dryland dynamics and rationale behind its underperforming croplands amid climate extremes. We develop a gridded multi-criteria drought index for the growing season (June-October) and analyse its spatial and temporal degree of uniformity to designate the drought, climate and cultivable zones. Evidence is drawn from Sahelian Sudan, representing 1.03 million km2 of the African Sahel, during 1940–2020. Results show that cultivation of marginal lands has persisted apace. The peak areas of these marginal lands explain ∼50 % of the variations in crop yield, considering the two staple crops, sorghum and millet. Furthermore, the low yields mismatch the steadily growing planted areas of these crops. Compared to wet conditions, droughts expand (shrink) the median size of hyper-arid (arid) area by 466 % (46 %), limiting farming opportunities for 3.5–35.8 % of the croplands. The northernmost borderline of the arid zone determines the rainfed suitability, but potentially cultivable arid areas require contingency risk-reduction plans. Conversely, semi-arid and dry sub-humid zones reveal areas endowed with uniform climate. Skillful climate forecasting should thus guide policymaking towards sustainable agriculture therein. The paper suggests paths towards more effective agricultural policy interventions. Agricultural production entails the Sahel drought being defined in terms of agricultural impacts instead of meteorological conditions. Land use planners and inhabitants must relieve the plight of misconceiving and overlooking the fact of intrinsic interannual rainfall variability. Determining what a dangerous drought is for the Sahel agriculture sector or system is crucial. Sahel farming systems should opt for highly flexible agricultural practices based on the above-identified cultivable areas.