Rainfall Deficit Research Articles

Determination of effects of climate change on hydropower generation at Kamburu dam-Kenya.

This study aimed to determine the effects of climate change on hydropower generation at Kamburu Dam, Kenya. Kamburu power plant has been experiencing low volumes of water with the shortage of rainfall from its catchment area. This study primarily utilised rainfall and temperature data, as well as field survey data collected through questionnaires. Primary data was collected using questionnaires, photography, checklists, and observation guides. Secondary data sources included Kengen and the meteorological department's annual reports. The study used simple stratified sampling. The four villages of the Kivaa sub-location were sampled into 20 households, making a total of 80 households; Kengen and meteorological stations sampled every 10 respondents to make a total of 100 respondents. Collected data from the questionnaires were coded and analysed using SPSS 29. The results of this research showed that the area experiences increasing temperatures of 0.044? every year and decreasing rainfall of 0.5897mm every year. The research forecasted a decadal increase in temperature of 0.44? and a decadal decrease in rainfall of 5.897mm. The research also showed a decrease in hydropower of 18,790MWH every year, translating to a decadal decrease of 187,790MWH. The research concluded that climate change has greatly affected hydropower production at the Kamburu Dam power plant. The research recommends afforestation and re-afforestation activities, putting rules and regulations of watershed management, upgrading the Kamburu dam infrastructure to fit climate-resilient, expanding the capacity of the dam, and energy storage, among others.

A Copernicus-based evapotranspiration dataset at 100 m spatial resolution over four Mediterranean basins

Abstract. Evapotranspiration (ET) is responsible for regulating the hydrological cycle, with a relevant impact on air humidity and precipitation that is particularly important in the context of acute drought events in recent years. With the intensification of rainfall deficits and extreme heat events, the Mediterranean region requires regular monitoring to enhance water resource management. Even though remote sensing provides spatially continuous information for estimating ET on large scales, existing global products with spatial resolutions ≥ 0.5 km are insufficient for capturing spatial detail at a local level. In the framework of ESA's 4DMED-Hydrology project, we generate an ET dataset at both high spatial and high temporal resolutions using the Priestley–Taylor Two-Source Energy Balance (TSEB-PT) model driven by Copernicus satellite data. We build an automatic workflow to generate a 100 m ET product by combining data from Sentinel-2 (S2) MultiSpectral Instrument (MSI) and Sentinel-3 (S3) land surface temperature (LST) with ERA5 climate reanalysis derived within the period 2017–2021 over four Mediterranean basins in Italy, Spain, France, and Tunisia (Po, Ebro, Hérault, and Medjerda). First, original S2 data are pre-processed before deriving 100 m inputs for the ET estimation. Next, biophysical variables, like leaf area index and fractional vegetation cover, are generated, and then they are temporally composited within a 10 d window according to S3 acquisitions. Consequently, decadal S2 mosaics are used to derive the remaining TSEB-PT inputs. In parallel, we sharpen 1 km S3 by exploiting the dependency between coarse-resolution LST and 100 m S2 reflectances using a decision tree algorithm. Afterwards, climate forcings are utilized to model energy fluxes and then for daily ET retrieval. The daily ET composites demonstrate reasonable TSEB-PT estimates. Based on the validation results against eight eddy covariance (EC) towers between 2017 and 2021, the model predicts 100 m ET with an average RMSE of 1.38 mm d−1 and a Pearson coefficient equal to 0.60. Regardless of some constraints mostly related to the high complexity of EC sites, TSEB-PT can effectively estimate 100 m ET, which opens up new opportunities for monitoring the hydrological cycle on a regional scale. The full dataset is freely available at https://doi.org/10.48784/b90a02d6-5d13-4acd-b11c-99a0d381ca9a, https://doi.org/10.48784/fb631817-189f-4b57-af6a-38cef217bad3, https://doi.org/10.48784/70cd192c-0d46-4811-ad1d-51a09734a2e9, and https://doi.org/10.48784/7abdbd94-ddfe-48df-ab09-341ad2f52e47 for the Ebro, Hérault, Medjerda, and Po catchments, respectively (Bartkowiak et al., 2023a–d).

Satellite Based Composite Weather Insurance Product for assessing mid-term adversary

The present study formulated a satellite-based rainfall insurance product (SRIP) at sub-seasonal scale during 2015–2020 by integrating meteorological, geophysical and vegetation index products e.g. rainfall (CHIRPS:Climate Hazards Group InfraRed Precipitation with Station), soil moisture (SMAP), normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) from moderate resolution imaging spectro-radiometer (MODIS). The SRIP was meticulously designed to integrate both cause (rainfall) and impact (NDVI, NDWI, soil moisture) parameters to enhance the assessment of min-season crop risks, with a particular emphasis on deficit rainfall. The performance evaluation of SRIP was conducted in two distinct agro-climatic zones viz. Deoria district of Uttar Pradesh (Upper Gangetic Plain Region) and Krishna district of Andhra Pradesh (Southern Plateau and Hills Region) spanned from June to October, which aligns with the major crop-growing season corresponding to the Southwest monsoon period in India. Three sets of SRIPs were investigated i.e. SRIP with cause parameter (SRIP1), SRIP with cause-impact parameters with no lag response (SRIP2) and SRIP with cause-impact parameters with one-month lag response (SRIP3). The SRIP was structured to provide a numerical index on a scale ranging from 0 to 1, representing poor to good crop-growing conditions that could effectively identify the rainfall deficit threshold (SRIP≤0.43) corresponding to negative percent deviation in rainfall (PDR≤−20%). This threshold level was recognized for compensation of triggers at the multiple crop growth phases during the crop-growing season. The district average of SRIP and PDR showed fair correlation co-efficient (0.77 ≤ r ≤ 0.88). Good correlation between sub-seasonal (monthly, bi-monthly, tri-monthly) SRIP and normalized MODIS Gross Primary Productivity (0.65 ≤ r ≤ 0.98), and SRIP deviation and yield deviation (0.45 ≤ r ≤ 0.97) reflect sensitivity of SRIP to crop carbon productivity and crop yield. The findings of the present study recommend SRIP not only a multi-phase composite index for assessing mid-season crop risks in terms of rainfall deficit for clusters of insurance units, but it has the potential to be used by insurance agencies to settle the claims by farmers in a transparent and faster manner for crop loss due to large-scale rainfall deficits. However, SRIP needs to be customized in future to make it more adaptable to settle insurance claims due to weather adversaries at individual farm level.

Contrasted agronomical and physiological responses of five Coffea arabica genotypes under soil water deficit in field conditions.

Breeding programs have developed high-yielding Coffea arabica F1-hybrids as an adaptation against adverse conditions associated with climate change. However, theresponse to drought of coffee F1 hybrids has seldom been assessed. A trial was established with five C. arabica genotypes (2 pure lines: Catimor and Marsellesa and 3 F1 hybrids: Starmaya, Centroamericano and Mundo Maya) planted under the leguminous tree species Leuceana leucocephala. Coffee growth, yield and physiological responses were assessed under a rain-fed (control: CON) and a rainfall reduction treatment (RR) for 2 years. The RR treatment created a long-term rainfall deficit in a region with suboptimal temperature similar to those predicted by climate change scenarios. Moreover, the RR treatment reduced soil water content by 14% over 2 successive years of production and increased hydric stress of the three F1-hybrids (leaf water potentials averaged -0.8 MPa under RR compared with -0.4 MPa under CON). Under RR, coffee yields were reduced from 16 to 75% compared to CON. Mundo Maya F1 hybrid was the sole high-yielding genotype apable of sustaining its yield under RR conditions. Our results suggested that its significant increase in fine root density (CON = 300 and RR = 910 root.m-2) and its maintenance of photosynthetic rate (2.5 - 3.5 mmol CO2 m-2 s-1) at high evaporative demand might explain why this genotype maintained high yield under RR condition. This work highlights a possible drought tolerance mechanism in fruit bearing adult coffee trees where the plant fine root number increases to intake more water in order to preserve turgor and sustainphotosynthesis at high ETo and therefore conserves high yield in dry conditions.

Occasional Occurrences and Distributions of Red Billed Quelea (Quelea quelea) Birds on Cultivating Crops during the Belg Season at Raya Azebo District of Tigray, Ethiopia

The Belg season plays a crucial role in the agricultural calendar of the Raya District, particularly due to the shortage of rainfall during the summer season. This seasonal pattern of rainfall scarcity necessitates the significance of the Belg season for agricultural activities in this region. Aim of the study was to assess the Quelea bird incidence and its association agronomic practice and environmental factors. Field survey was conducted in Raya-azebo district during 2024 Belg season. A total of 49 farmers field were assessed for the incidence and prevalence of the quelea bird. Result indicated that out of the assessed fields, 69.39% was affected by Quelea birds the assessed fields. The damage level caused by birds was varied from 0% to 100%. On average, it was determined that approximately 32.37% of the cultivated crops were affected by birds. The mean percentage of crop damage across all kebelles was observed. Ewo had the highest mean damage at 61.45%, followed by Kara-Adishaho at 57.5%. On the other hand, Tsigea experienced a significantly lower damage rate of 1.67% followed by Genete with damage rat of 11%. Independent variables such as crop types, planting time, harvesting time, source of water, and coverage of trees play a significant (p<0.05) role in influencing bird damage in belg season crops. The lowest bird damage percentage were observed in crops planted in middle March, with 6.19% and late May harvesting, with a rate of 19.38%. Adopting practices such as cultivating crops in clusters and planting crops of similar maturity at the same time can be effective strategies for controlling Quelea birds’ damage in agricultural settings.

How unusual was Australia's 2017–2019 Tinderbox Drought?

Australia’s Murray-Darling Basin experienced three consecutive years of meteorological drought across 2017–2019, collectively named the ‘Tinderbox Drought’. Rainfall deficits during the three-year drought were most pronounced in the Australian cool season (April to September). Deficits in both the cool season and annual total rainfall were unprecedented in the instrumental record. However, the instrumental record provides just one of a range of equally plausible climate trajectories that could have occurred during this period. To determine if the Tinderbox Drought was outside this range, we used observational data from prior to the onset of the drought to construct Linear Inverse Models (LIMs) that emulate the stationary statistics of Australian rainfall and its connection to global sea surface temperature (SST) anomalies. Overall, we find that rainfall deficits were most unusual in the northern Murray-Darling Basin, and during the final year of the drought. The global SST anomalies observed during the first two years of the Tinderbox Drought, particularly the cool anomalies in the central tropical Pacific and western Indian Ocean, are not typically associated with low rainfall across the Murray-Darling Basin. In terms of single-year rainfall anomalies, the only aspect of the Tinderbox Drought that was beyond the range of the LIMs was annual-total rainfall over the northern Murray-Darling Basin during 2019. This coincided with an extreme positive Indian Ocean Dipole event that was also beyond the range of the LIMs. When considered in terms of basin-wide rainfall over the full three years, rainfall deficits during the Tinderbox Drought were beyond the LIM range in terms of both cool-season and annual-total rainfall. This suggests an anthropogenic contribution to the severity of the drought—likely exacerbated by the 2019 extreme positive Indian Ocean Dipole event.

Design of wastewater treatment unit using End-of-Life (EoL) Reverse Osmosis membrane

Abstract Sultanate of Oman is facing severe challenges due to water scarcity, shortage of rainfall, and limited freshwater resources. Over the past few decades, 90% of the natural water resources are consumed by agriculture. Hence, there is an urgent need to find an alternative to obtain fresh water. Water desalination by Reverse Osmosis (RO) is currently practiced in Oman as freshwater source, since it contributes 80% of the total desalination plants installed worldwide. The RO process results in environmental concerns triggered by emission of gases, and discharge of Reverse Osmosis (RO) membranes. The lifespan of membranes depends on the water quality and the operating conditions, and the membrane life is estimated as 5 to 10 years. In order to mitigate the environmental impact for a sustainable desalination output, reuse of discarded end-of-life (EoL) RO membrane is a feasible solution to enhance the water quality. The efficiency of RO membranes is affected by the fouling, scaling, and chemical cleaning for the yearlong operation which lead to reduced salt rejection rate. Hence, this research aimed to reuse the old RO elements by transforming them into Ultrafiltration unit (UF) by removing the active layer and increasing the pore size of membrane. Additionally, modifying the membrane by open configuration and separating all 28 membrane sheets from the permeating tubes are designed as RO-MBR panels. The study shows that, after 5 weeks of operation, the average turbidity rejection rate was 94%, and the average permeated flux per unit was 6.9 LMH. The new configuration shows the permeate flux stability and acceptable BOD, and COD reduction.

Relevance of Bacteria in Causing Rain and Snow.

The Earth's climate is influenced by both natural phenomena (solar fluctuations, oceanic patterns, volcanic eruptions, and tectonic movements) and human activities (deforestation, CO and CO2 emissions, and desertification), all of which contribute to ongoing climate change and the resulting global warming. However, human actions are a major factor in exacerbating global warming and amplifying its adverse impacts worldwide. . With rising temperatures, water evaporation from water bodies and soils intensifies, leading to heightened water scarcity, particularly in drought-prone regions. This scarcity compounds rainfall deficits, posing significant challenges. Precipitation, essential for the biosphere's hydrological cycle, replenishes much of the world's freshwater. It occurs when condensed water vapor in the atmosphere falls back to Earth as rain, drizzle, sleet, graupel, hail, or snow due to gravity. Literature highlights the indispensable role of bacterial populations in this process, termed bio-precipitation. This phenomenon begins with bacterial colonization on plant surfaces, with colonies subsequently dispersed into the atmosphere by winds, triggering ice crystal formation. Through their ice nucleating property, these bacteria facilitate the growth of larger ice crystals, which eventually melt and precipitate as rain or snow. This mechanism aids in nutrient transfer from clouds to soil or vegetation. Pseudomonas syringae stands out as the most notable microorganism exhibiting this ice-nucleation property, serving as the primary source of ice nucleators driving bio-precipitation. Despite limited literature on "rain and snow-causing bacteria," this review comprehensively explores the conceptual background of bio-precipitation, the involved bioprocesses, and the critical role of bacteria like P. syringae, offering insights into future research directions.

The assessment of low flow at El Abid river basin for a good management of water resource (High Atlas/Morocco)

Abstract In a scenario where pressures on aquatic ecosystems and the water demands of communities are on the rise, coupled with the impacts of global changes, understanding low water flows becomes a critical concern. Low flow is characterized as a natural and seasonal phenomenon, typically stemming from varying degrees of prolonged and severe rainfall deficits. This phenomenon is prone to temporal and spatial fluctuations, ultimately causing a reduction in streamflow. The El Abid River Basin is located within the big Oum Er Rbia watershed, covering an area of 30.600 km2. El Abid river stands out as the principal tributary of the Oum Er Rbia, boasting an average annual flow of 32 m3/s−1, with a maximum average flow reaching 77 m3/s−1 and a minimum average flow of 10 m3/s−1. The hydrological regime of this river exhibits a pattern of intermittent and extreme floods, as well as periods of low flow sustained by water from the karst hydrosystems of the central High Atlas. The aim of this study is to characterize the low flow rates within the upstream part of El Abid river basin, intending to enhance the management of water resources in this basin. The methodology employed involves extracting the minimum flows, calculating the severity thresholds for low flow, determining the lowest average monthly flow of the year, computing low flow rates based on monthly flow averages, and calculating low flow values for specific return periods. Monthly discharge data from two hydrometric stations within our study area, namely Ait Ouchéne and Tizi Nisly, were utilized. The dataset spans the period from 1976 to 2018.

Recent variations of water area in the Tabular Middle Atlas lakes, Morocco

Abstract The shrinkage of the lake’s water area is considered an indicator of change in climatic parameters and anthropogenic impact on landscapes through changes in land use practices. The present study focuses on utilizing remote sensing data to track the evolution of the water area in three lakes (Aoua, Afourgagh, and Ifrah) located in the Tabular Middle Atlas. The processing of Landsat satellite images between August 1984 and August 2022 reveals a significant shrinkage of the lakes, with drying periods in recent years. The concerning situation of the lakes is attributed to the increased rainfall deficit since the 1980s and the extension of irrigated areas in intramountain depressions. In three decades, the area of irrigated lands has extended by more than 540 %. The results obtained in this study indicate significant variations in the Tabular Middle Atlas lakes and reflect the dramatic situation of water resources.

The 2019–21 drought in southern Madagascar

Two consecutive failed rainy seasons in the southern part of Madagascar in 2019–21 had devastating impacts on the population, including an amplification of the ongoing food insecurity in the area. The drought events were second in severity only to the 1990–92 drought and were estimated in a previous study to have a return period of 135 years. In this study, the physical mechanisms that led to these consecutive drought events are investigated.We found that the anomalously cold sea surface temperatures (SSTs) that persisted to the south of Madagascar between December 2019 and December 2020 led to a decrease in the transport of moist air over land. These cold SST anomalies were the most negative anomalies in the past four decades and intensified the rainfall deficit resulting from a negative Subtropical Indian Ocean Dipole (SIOD) mode during the rainy season of December 2019 to March 2020 and during December 2020. We also found that the rainfall response to the SST anomaly south of Madagascar was three times greater than that of a canonical SIOD.A weak Mozambique Channel Trough and a strong Angola low system, on the other hand, modulated the expected above-normal rainfall from a La Niña event in January–February 2021. Our study demonstrates how local factors can modulate the impacts of large-scale drivers, and that both local and global drivers, and their interactions, should be considered when producing seasonal forecasts and advisories, as well as climate change adaptation and mitigation plans for southern Madagascar.

Physiological Characterization of Banana Germplasm of North East India for Tolerance against Moisture Deficit

Background: Water deficit stress is a serious environmental constrain to banana productivity in north east (NE) India. A field experiment was conducted to appraise the performance of 29 banana germplasm of NE India under moisture deficit condition of Assam that naturally prevails due to deficit rainfall every year during November to January. Methods: Randomized block design with five replications was the experimental design used. Irrigation was not applied during the crop growing season. Various physio-chemical parameters were measured in the main crop on 7th and 9th months after planting (MAP) that coincided with November and January. Result: Significant variations were observed in leaf relative water content, leaf area plant-1, leaf area index, total chlorophyll content, leaf proline content, lipid peroxidation, hands bunch-1 and bunch weight amongst germplasm studied. During moisture deficit period, germplasm Barjahaji, Bhimkal, Athiya and Bogimonahar could maintained better values in the physio-chemical traits studied except lipid peroxidation. The germplasm that showed superior values in the physio-chemical traits and lower value for lipid peroxidation registered the higher bunch weight. Significant positive correlation of bunch weight with leaf area (0.42 and 0.45 respectively for 7th and 9th MAP) and relative leaf water content (0.38 respectively for both 7th and 9th MAP) and significant negative correlation with lipid peroxidation (-0.45 and -0.49 respectively for 7th and 9th MAP) were observed at 5 per cent level of significant. Significant strong positive correlation between leaf chlorophyll content and proline content in leaf (0.85) was observed at 9th MAP. Germplasm Barjahaji, Bhimkal, Bogimanohar and Athiya are considered physiologically more tolerant to moisture deficit which can be used for future breeding programs and the physio-chemical parameters viz., leaf area, chlorophyll content, relative leaf water content and proline content can be considered as physiological indices for drought tolerance.

Predicting agricultural and meteorological droughts using Holt Winter Conventional 2D-Long Short-Term Memory (HW-Conv2DLSTM).

Drought is an extended shortage of rainfall resulting in water scarcity and affecting a region's social and economic conditions through environmental deterioration. Its adverse environmental effects can be minimised by timely prediction. Drought detection uses only ground observation stations, but satellite-based supervision scans huge land mass stretches and offers highly effective monitoring. This paper puts forward a novel drought monitoring system using satellite imagery by considering the effects of droughts that devastated agriculture in Thanjavur district, Tamil Nadu, between 2000 and 2022. The proposed method uses Holt Winter Conventional 2D-Long Short-Term Memory (HW-Conv2DLSTM) to forecast meteorological and agricultural droughts. It employs Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data precipitation index datasets, MODIS 11A1 temperature index, and MODIS 13Q1 vegetation index. It extracts the time series data from satellite images using trend and seasonal patterns and smoothens them using Holt Winter alpha, beta, and gamma parameters. Finally, an effective drought prediction procedure is developed using Conv2D-LSTM to calculate the spatiotemporal correlation amongst drought indices. The HW-Conv2DLSTM offers a better R2 value of 0.97. It holds promise as an effective computer-assisted strategy to predict droughts and maintain agricultural productivity, which is vital to feed the ever-increasing human population.

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.

Variable persistence of an iconic arboreal mammal through the Black Summer wildfires

Wildfires are predicted to increase in frequency and severity with climate change but detailed understanding of their influence on forest wildlife is lacking for many species. Wildfires vary in their extent and severity among landscapes, limiting generalisations about impacts from a single wildfire. We investigated post-wildfire persistence in the threatened exudivorous yellow-bellied glider (Petaurus australis) in south-eastern Australia. The widespread occurrence of wildfires in the ‘Black Summer’ of 2019–20 enabled populations in three landscapes (90–160 km apart) to be studied. This species has a slow life history (one young per year and >1 year to mature) so post-fire recovery is predicted to be slow. We conducted repeat surveys over 3 years post-fire in each landscape at 25–29 sites that were occupied pre-wildfire. All survey sites were burnt in two landscapes but only 40 % were burnt in the third. We estimated declines in occupancy of 13 %, 40 % and 66 % in burnt forest. The factors driving the variation in decline appear to be a combination of fire severity and the abundance of very large (≥80 cm) hollow (i.e. cavity) -bearing trees that serve as den sites. The implications of this study are that the impacts of wildfires on populations of tree-hollow dependent species can be expected to vary in different landscapes as a consequence of fire severity, rainfall deficit and logging history. Our study suggests the importance of ensuring populations are conserved across a wide geographic gradient, and the value of very large hollow-bearing trees rather than simply the number of any hollow-bearing trees.

Gravel Mulching Significantly Improves Crop Yield and Water Productivity in Arid and Semi-Arid Regions of Northwest China: Evidence from a Meta-Analysis

In the arid and semi-arid regions of Northwest China, periodic rainfall deficits, high field evaporation, limited freshwater resources, and high irrigation costs restrict crop yield and water productivity (WP). Gravel mulching (GM), a traditional agricultural tillage management practice widely used in arid and semi-arid regions, improves crop yield and WP. However, the combined impacts of GM on crop yield and WP are unclear. This study aimed to examine the effects of GM on crop yield and WP under different factors and to find the most critical regional factors and gravel characteristics that affect crop yield and WP. To quantitatively assess the impact of GM on crop yield and WP, this study performed a meta-analysis, a regression analysis, and a path analysis of 185 yield comparisons and 130 WP comparisons from 30 peer-reviewed scientific reports. This study found that GM significantly increased crop yield and WP by an average of 29.47% and 28.03%, respectively. GM was reported with the highest response percentages (I) of crop yield and WP in regions whose average annual precipitation (AAP) was 200–400 mm, average annual temperature (AAT) was 0–9 °C, and altitude (A) was >1000 m. Overall, AAP, AAT, and A had significant effects on the I of crop yield (p < 0.001), but AAT and A had an insignificant impact on the I of crop WP (p > 0.05). Gravel size (GS), the amount of gravel mulching (AGM), the degree of gravel mulching (DGM), and the gravel mulching thickness (GMT) had a significantly positive impact on crop yield and WP (p < 0.05). The stepwise multiple linear regression analysis results indicated that the primary regional factors influencing yield were AAT and A, contributing 43.14% and 53.09%, respectively. GMT and GS were identified as significant gravel characterization factors impacting yield, contributing 82.63% and 17.37%, respectively. AAP and GMT were the main regional factors and gravel characterization factors affecting WP. Furthermore, the I values for cash crop yield and WP were higher than that for food crops, and moderate fertilization and irrigation would increase the I values of yield and WP. The benefits of GM are strongly correlated with the planting year. This study’s results show that GM generally improves crop yield and WP, although the extent of this impact varies based on different conditions. These findings are not only useful in relation to their direct applicability to other countries worldwide but also due to their potential to provide new ideas for agricultural practices in similar crop-growing environments.

Drought risk in Moldova under global warming and possible crop adaptation strategies.

This study analyzes the relationship between drought processes and crop yields in Moldova, together with the effects of possible future climate change on crops. The severity of drought is analyzed over time in Moldova using the Standard Precipitation Index, the Standardized Precipitation Evapotranspiration Index, and their relationship with crop yields. In addition, rainfall variability and its relationship with crop yields are examined using spectral analysis and squared wavelet coherence. Observed station data (1950-2020 and 1850-2020), ERA5 reanalysis data (1950-2020), and climate model simulations (period 1970-2100) are used. Crop yield data (maize, sunflower, grape), data from experimental plots (wheat), and the Enhanced Vegetation Index from Moderate Resolution Imaging Spectroradiometer satellites were also used. Results show that although the severity of meteorological droughts has decreased in the last 170 years, the impact of precipitation deficits on different crop yields has increased, concurrent with a sharp increase in temperature, which negatively affected crop yields. Annual crops are now more vulnerable to natural rainfall variability and, in years characterized by rainfall deficits, the possibility of reductions in crop yield increases due to sharp increases in temperature. Projections reveal a pessimistic outlook in the absence of adaptation, highlighting the urgency of developing new agricultural management strategies.

Studies on Variation of Temperature and Rainfall using Climatological data for the Plain and Hill zones of Uttarakhand

The present study examines long-term annual, seasonal and monthly changes and short-term fluctuations in monsoonal rainfall and temperature over plain and hill zones of Uttarakhand. Both rainfall and temperature data for period of 1981-2020 were analyzed in this study. Statistical trend analysis techniques namely Mann–Kendall test and Sen’s slope estimator were used to examine and analyze the problems. The detailed analysis of the data for 40 years indicates that the annual range of temperature is increasing in the hill zone. In the context of agriculture, the observed trends in temperature and rainfall patterns pose significant implications for farming practices and crop yields in Uttarakhand. The increasing annual range of temperature, particularly in the hill zone, suggests a heightened risk of temperature extremes such as heat waves and cold spells. During the monsoon season, while rainfall levels may remain relatively stable or exhibit minor fluctuations, the variability highlighted by the box and whisker plots underscores the importance of preparedness for both excess and deficit rainfall scenarios.

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.

Does Climate Variability Influence Internal Migration Flows in Senegal? An Empirical Analysis

This paper aims to estimate the total effect of climate variability on interregional migration flows in Senegal. We match regional climate data at origin, represented by normalised rainfall and normalised temperatures (maximum and minimum), with regional migration flow data from Senegal’s Agence Nationale de la Statistique et de la Démographie (ANSD) censuses to construct a panel database covering the five-yearly internal migration waves of 1976, 1988, 2001 and 2013. Using a gravity equation model where migration flows are explained by measures of climatic variability at origin, controlled for geographical, socioeconomic and demographic factors traditionally identified in the literature. Our results show that only negative precipitation anomalies at the origin area act as a push factor and accelerate emigration. In the predominantly agricultural regions, rainfall deficits appear, alongside traditional socioeconomic variables, as an additional significant factor shaping mobility across the country.