Seasonal Rainfall Variability Research Articles

ASSESSMENT OF TEMPORAL VARIABILITY OF TEMPERATURE AND PRECIPITATION TRENDS IN KARGI, MAIKONA, DAKABARICHA AND SOLOLO WARDS OF MARSABIT COUNTY, KENYA

<p><strong>Background.</strong> Climate change is a global phenomenon, with varying indicators and impacts from one region to another. The impacts of the changing climate are high in developing countries that are mainly dependent on climate-driven economic sectors such as pastoral and agro-pastoral livelihoods. <strong>Objective.</strong> Analyze the temporal trend, the variability in temperature and precipitation, and the relationship between both parameters to determine the influence of the El Niño phenomenon in Marsabit County, Kenya, from 1981 to 2021. <strong>Methodology.</strong> Daily rainfall and temperature data for the four study locations (Maikona, Kargi, Dakabaricha, and Sololo) were obtained. The analysis of extremes was the main method used in the analysis of the temporal and spatial variability of rainfall and temperature to establish the frequency and magnitude of climate variability in the study area. The seasonal mean plus or minus 1 Standard deviation for the entire period of study was used in the analysis of extremes. <strong>Results.</strong> Findings from trend analysis showed that rainfall trends have significantly increased in Marsabit County. Further, results on seasonal trends and variability of rainfall showed that March-April-May rainfall has been decreasing over the years. Below average rainfall has been experienced in Maikona in 2000 and 2011 with a magnitude of -42.9 mm, and -39.3 mm, respectively, while below average rainfall has been experienced in Kargi in 2000, 2009, 2011, and 2012 with a magnitude of -41.7 mm, -24.2 mm, -35.3 mm, and -34.3 mm, respectively. Analysis of the temperature trends and variability showed that both night and day temperatures have significantly increased over the years in Marsabit County. The magnitude of warming was found to be double that of cooling. The regression analysis further showed that there exists a negative correlation between temperatures and rainfall, implying that generally, rainfall decreases with increasing temperatures. <strong>Implications.</strong> This finding is important because it could help policymakers and people working on development in Marsabit County see what temperature and precipitation changes are happening locally. This could help them plan for climate change better. Both pastoral and agro-pastoral areas have been affected by both El Niño and La Niña activities, with the El Niño years recording the highest amounts of rainfall while the La Niña years recording the lowest amounts. <strong>Conclusion</strong><strong>s</strong><strong>.</strong> This study recommends the use of rainwater harvesting during the October to December Season to take advantage of the increasing Trends and flood episodes associated with high magnitudes and frequencies of above average rainfall and use the same to cope with reduced rainfall in the March to May season. </p>

Vulnerability of communities' livelihoods to the impacts of climate change in north-western highlands of Tanzania

Climate change has emerged as one of the critical challenges to human well-being. Changing climate places direct and indirect impacts on human activities and is mainly triggered by non-climatic stressors, which are diverse and inherent in many communities. However, there has been diversity in how climate and non-climatic stress factors affect human well-being and thus requiring locally specific contextualisation of how climate change is driving change in many ecosystems. This study analysed climate and non-climate factors for communities' vulnerability and impacts using a landscape approach in selected villages in the western highlands of Tanzania, specifically in Kasulu and Buhigwe districts in Kigoma Region. The aim was to understand communities' vulnerability to the impacts of climate, and non-climate processes, particularly with regard to livelihoods and impacts, particularly in forest resources. Study sites and respondents were selected through simple random and purposive sampling methods. Data were collected through household surveys, key informants interviews, and focus group discussions. Meteorological data were used for the analysis of climatic changes. Quantitative data analysis tools included meteorological statistics software such as CLIDATA, INSTAT, XLSTAT and SPSS. Theme-content analysis was used to analyse qualitative data. Findings indicate inter-annual and seasonal variabilities of rainfall and temperature levels from the normal across the study sites. The study revealed significant increasing trends for mean annual Maximum and Minimum temperature. Significant changes in rainfall patterns were decreasing seasonal and annual rainfall trends, unreliable onset and cessation, and erratic seasonal rainfall. The maximum decline of seasonal rainfall had slope values of −14.51, while the maximum decline of annual rainfall trends had a slope value of −12.76. The minimum decline for seasonal rainfall had slope values of −2.17, and annual rainfall trends had slope values of −1.36. Villages in the highland zone were found to be highly vulnerable to the impacts of climate change and non-climate stress factors, with a 0.61 vulnerability index value. Major climate stress factors for communities' vulnerability included seasonal variability of rainfall and temperature increase, which influenced the increase of pests and diseases and other unfavourable climatic conditions that affect crop production and livestock keeping. The effects, directly and indirectly, influenced the low agricultural yields and decreased income. Non-climate stress factors such as landscape characteristics, mobility, inadequate extension services, and low household asset endowment might have been accelerating communities' vulnerability to the effects of the changing climate. Moreover, the study shows the climate change on a community's resilience. Generally, changes in climate conditions result in many adverse consequences and have been influencing communities' vulnerability.

The burden of water insecurity: a review of the challenges to water resource management and connected health risks associated with water stress in small island developing states

Abstract Water resources, whether exceeding per capita water abundance thresholds or below water scarcity thresholds, are health determinants within small island developing states (SIDS). Thresholds indicate water stress vulnerability in SIDS, but underestimate the physicality associated with a lack of water. The objectives of this study were to capture the main challenges of consistently meeting water demand in SIDS and to present their intersection with certain diseases or factors associated with specific health conditions like dengue fever, gastrointestinal disorders, dehydration, and malnutrition. This review utilized archival evidence to categorize the challenges undermining water availability in SIDS with the view that these issues present or exacerbate health outcomes. Seasonal rainfall variations (73%), inadequate distribution infrastructure (64%), saltwater intrusion (61%), contamination (58%), human-induced watershed change (19%), and sea level rise (17%) were identified from 108 country-specific sources as challenges to consistently meeting water demand by 59 SIDS. Any water stress indicator must consider that it is contingent on its human burden. These challenges affect food security through agricultural drought and soil salinization, and the proliferation of vector-borne and sanitation-related diseases across SIDS. This review is the first step in determining the human health burden of water insecurity in SIDS.

Spatio-Temporal Variability of Rainfall Over Kathmandu Valley of Nepal

The present study used and analyzed rainfall data from 18 meteorological stations from 1971 to 2013 to examine the spatial and temporal variability of seasonal and annual rainfall based on rain gauge measurements. The monthly to annual rainfall analysis was carried out for each site of Kathmandu Valley. Rainfall amounts in Kathmandu Valley vary considerably in space and time. The minimum mean monthly rainfall is observed in November which is 6.5 mm and maximums of 447.8 mm in July. Monsoon is the main contributor of the rainfall which is 80% followed by pre-monsoon with 13.6%, post-monsoon with 3.6% and winter with 2.8%. Spatial interpolation was used to explore spatial variability of seasonal and annual rainfall over Kathmandu Valley. There is large spatial variability of monsoon rainfall; generally, the upper parts of the Kathmandu Valley received the heavy monsoon rainfall than the lower parts of the Valley floor. The rainfall of Kathmandu has marked decreasing in recent a couple of decades. Annual rainfall has decreased by 0.96 mm/year observed in Kathmandu Valley.

Combined use of graphical and statistical approaches for rainfall trend analysis in the Mae Klong River Basin, Thailand

Abstract The main purpose of this paper was to investigate the monthly, seasonal, and annual rainfall variability in the Mae Klong River Basin in Thailand using the Mann–Kendall (MK) test, Sen's slope method, Spearman's Rho (SR) test, and the innovative trend analysis (ITA) method. The monthly rainfall data of eight stations for the period 1971–2015 were used for trend analysis. Datasets with significant serial correlation were corrected by the trend-free pre-whitening (TFPW) approach for statistical methods. The MK test showed increasing rainfall trends for five out of eight stations in the dry season while 50% of stations indicated increasing trends in the wet season. On an annual scale, 75% of the stations exhibited increasing rainfall trends. The results of the SR test were in line with the MK test for seasonal and annual rainfall. The ITA method showed comparable findings with those of the statistical methods. For the entire basin, trend analysis found increasing rainfall on both seasonal and annual scales by all the tests. The findings of this study could benefit water supply and management, drought monitoring, agricultural production activities, and socioeconomic development in the Mae Klong River Basin in the future.

Climate and soil-based constraints to rainfed cotton yield in the Northern Territory, Australia – A modelling approach using APSIM-OZCOT

Cotton production in Australia is expanding to the northern semi-arid tropical regions as a means to droughtproof the industry. The majority of expansion is expected to come from rainfed farming systems. However, little is known on tropical rainfed cotton, particularly on climate and soil-based constraints that determine cotton production. Using the Northern Territory (NT) as case study, we investigated the effects of between and intra seasonal rainfall variability and key soil types on soil moisture dynamics,timely operations, lint yield, and industry viability. We examined several regions with greatest potential for rainfed agriculture in the NT, including sites in the Daly Basin, Mataranka and Larrimah. To this purpose we applied a locally calibrated and validated cotton growth model (APSIM-OZCOT) using weather files sourced from the SILO database of Australian climate data, and soil profile parameters for three red Kandosols: Blain, Oolloo and Tippera. Our study shows that simulated median lint yields ranged from 570 to 996 kg ha−1, with larger yields achieved on soils that hold more moisture (Blain > Oolloo > Tippera), and at locations that received greater amounts of seasonal rainfall. Planting window largely governed soil-moisture availability and thus sowing opportunities. An early planting (1–15 December) increased yields (greater available soil-moisture) but reduced planting opportunities due to insufficient mulch cover at planting. A late planting (15 Jan to 1 Feb) reduced cotton yields due to less seasonal rainfall, but increased the number of sowing opportunities in the drier regions since more time was allowed to establish sufficient cover crop. Availability of deep soil-moisture was important, particularly in the later crop phases when the roots reach deeper layers, and sufficient soil moisture is required to grow and finish bolls. Our assessment further highlights the potential impact of excessively wet conditions on cotton production. Short periods of intense rainfall (known as “burst” events); a typical characteristic of the monsoon, reduce cotton yield through waterlogging. Scaling our simulated yields to the potential area of suitable soils in the NT shows considerable benefits to the regional economy and should be considered when planning industry development, including the establishment of cotton gins. The insights gained from this study are relevant to industry developments in similar environments, such as in parts of Brazil, India, and Sahelian Africa

Determination of October to December Seasonal Rainfall Variability, its Seasonal Onset and Cessation Dates in Zanzibar, Tanzania

Determination of October to December Seasonal Rainfall Variability, its Seasonal Onset and Cessation Dates in Zanzibar, Tanzania

Underpinning Terroir with Data: Integrating Vineyard Performance Metrics with Soil and Climate Data to Better Understand Within-Region Variation in Marlborough, New Zealand

Background and Aims. Previous work in Australia has demonstrated the value of data-driven approaches to terroir analysis but, like other terroir research, focussed predominantly on the natural resources (soils, topography, and climate) on which winegrowing depends. In only very few cases have metrics of production performance also been considered. In this study, focussed on the Marlborough region of New Zealand, we integrated data pertaining to vineyard performance with biophysical data (soils and climate) describing the conditions under which grapes are grown to give a more holistic indication of regional-scale variation in the terroir of the Marlborough production system. Methods and Results. Digital map layers describing variation in climate, soil properties, and the yield and harvest date of Sauvignon Blanc (Vitis vinifera L.) were assembled and analysed for similarity in their patterns of spatial variation over six vintages (2014–2019) using k-means clustering. The results suggest that the Marlborough region has a characteristically variable Sauvignon Blanc production with crop phenology and harvest date strongly influenced by variation in temperature, and yield variation impacted by soil properties. Spatial variation in seasonal rainfall did not appear to impact on vineyard performance. Importantly, the Wairau and Awatere valleys which, hitherto, have been considered together as parts of a single Marlborough region, are shown to be distinct. Conclusions. This analysis is strongly suggestive of the Marlborough terroir being variable at the within-region scale. It also lends weight to the idea that estimates of vineyard performance in some parts of the region may be used to predict performance in others. Significance of the Study. The results have potentially important implications for the management of both vineyard operations and winery logistics, for wine marketing and for whole-of-industry planning around expansion or contraction. The methods used are free of any bias introduced to many previous studies of terroir zoning through adherence to historical or geopolitical boundaries, expert opinion of wines, and other heuristics.

Rainfall Variability in Ratnapura District: A Comparative Study of the Two 30-year Standard Periods of 1961-1990 and 1991-2020

Ratnapura district in Sri Lanka could be identified as an area that is constantly affected by the adverse effects of rainfall variability; hence it is important to study the temporal patterns and distribution of rainfall variability in the area during the recent past decades. Therefore, this research aims to compare the annual and seasonal rainfall variability of the Ratnapura district based on the standard 30-year periods of 1961-1990 and 1991-2020. Fundamental statistical methods of coefficient of variation, Precipitation Concentration Index, and Standardised Precipitation Index were used to analyse the data. The study revealed that temporal patterns of rainfall variability in the district showed almost similar situations for both the 30-year periods. Temporal distribution of annual and seasonal rainfall variability also showed almost similar situations for both periods and was remarkable with uniform and moderate concentrations of rainfall variability. Relatively the highest variability of rainfall could be detected during the Northeast monsoon season. Although no differences in occurring extreme wet conditions between the two 30-year periods, it is clear that drier conditions of rainfall have decreased in the second 30-year period. The study also confirmed that no prolonged wet and dry conditions were reported in the Ratnapura district during the considered two 30-year periods.

Examining the past 120 years’ climate dynamics of Ethiopia

Climate change is one of the environmental threats around the globe. However, this change is not uniform throughout the world, both spatially and temporally. This study, therefore, examined the spatiotemporal (annual and seasonal) variability and trends of rainfall and temperature over Ethiopia from 1901 to 2020. Monthly rainfall and temperature (maximum, minimum, and mean) data were extracted from the latest version of the Climatic Research Unit (CRU 4.05) dataset. Using long-term seasonal rainfall patterns and pixel-based correlation techniques, five homogeneous rainfall zones were identified. The rainfall and temperature from CRU were validated using observed data from 235 and 145 meteorological stations, respectively. The results revealed that inter-seasonal rainfall and temperature variabilities are more pronounced than interannual variabilities in all rainfall zones. Only 19% (215,700 km2) and 3% (33, 900 km2) of the country’s total area experienced statistically significant (α = 0.05) decreasing and increasing trends of rainfall, respectively from 1901 to 2020. A statistically significant decreasing trend in rainfall with time was observed during the summer in only one zone that received rainfall in all months. A precipitation concentration index analysis revealed that the country exhibited a moderate to strongly irregular annual and seasonal rainfall distribution, except during the summer when the rainfall distribution was uniform. There was hence a high degree of rainfall seasonality throughout the study period. In addition to the devastating 1984 nationwide drought, Ethiopia also experienced local droughts for a number of 10 to 20 years. Unlike rainfall, there was a significant (α = 0.05) spatiotemporal increasing trend of temperature over the country. The spatial and temporal increasing trend of mean temperature over 120 years ranged from 0.24oC to 1.92oC and 0.72oC to 1.08oC, respectively. This increasing trend was higher in two zones located in the western and northwest parts of Ethiopia and the inflection points occurred after the 1970s in all zones. It is noteworthy that the maximum temperature increased at a lower rate than the minimum temperature. The warming trends and changes in rainfall patterns are likely to increase the frequency of climate extreme events and impact ecosystem services. This study suggests that climate change-sensitive zones require more attention and further study to enhance awareness of climate change in Ethiopia and facilitate adaptation to climate change and inform actions to mitigate adverse effects.

Pesticides in aquifers from Latin America and the Caribbean

In Latin America and the Caribbean (LAC), agriculture is the primary consumer of water and the biggest user of pesticides worldwide. Given that groundwater is a crucial resource in this region, a systematic review was conducted to evaluate the current state of knowledge on the presence of pesticides in aquifers. The review examined 48 research papers published between 1998 and 2020, and found that only six countries in the region have information on pesticides in groundwater. A total of 70 agrochemicals were detected, encompassing legacy pesticides, herbicides, insecticides, fungicides, and metabolites. Herbicides, including the widely used atrazine and glyphosate, were the most commonly detected current-use pesticides. These herbicides are being gradually banned or restricted due to their potentially harmful effects on the environment. Factors that contribute to the presence of these contaminants in aquifers include preferential flows, seasonal variations in rainfall, aquifer type, unsaturated zone thickness, and land use and management practices. Researchers noted that analysis of these contaminants is often beyond the economic or methodological scope, and analytical capacity in the region is generally limited. Based on the findings of this review, there is a clear need for groundwater pesticide monitoring in the region to reduce health risks to humans and ecosystems.

Analysis of Rainfall Variability and Shifts in Season in Relation to the Rice Cultivation Period in Sleman Regency

The research aimed to determine seasonal rainfall variability in Sleman Regency to determine shifts in season in Sleman Regency, and the relationship between the shift in season and rice cultivation period in Sleman Regency. The method was the coefficient of variation to determine seasonal rainfall variability. The shift in season was analysed in 10-year periods. The relationship between the shift in season and the rice cultivation period was analysed using the Chi-Square test. The result of this research showed that the rainfall variability in the dry season was higher than that in the rainy season in Sleman Regency from 1990-2019. The dry season in 2000-2009 came 10 days earlier in 6 subdistricts. The dry season in 2010-2019 was delayed in a period of 10-50 days. The rainy season in 2000-2009 came 20 days earlier in 7 subdistricts, delayed in a period of 10 days in 3 subdistricts. The rainy season in 2010-2019 was delayed in a period of 10 days in 8 subdistricts. The Chi-Square count was greater than the Chi-Square table, meaning that there was a relationship between shift in season and rice cultivation period in Sleman Regency.

Effects of seasonal rainfall variations on the hydrothermal state and thermal stability of the permafrost active layer in the central Qinghai-Tibet Plateau of China

Rainfall significantly impacts the hydrothermal state and thermal stability of the permafrost active layer by modifying surface energy boundary conditions. The quantitative characterization of hydrothermal changes in the Qinghai-Tibet Plateau has long been a crucial issue, yet the mechanisms underlying the effects of seasonal rainfall on the hydrothermal state within the permafrost active layer remain poorly understood. Therefore, this study investigated the influence of seasonal rainfall variations on the hydrothermal state within the permafrost active layer based on a water-vapour-heat coupled model that optimises the surface energy balance boundary conditions. The results show that regardless of whether the spring rainfall changes or not, the Bowen ratio is >1, indicating that the main energy exchange mode between the atmosphere and surface is sensible heat flux. But following the increase in rainfall in summer and autumn, the Bowen ratio is <1, indicating that the main energy exchange mode is latent heat flux. Meanwhile, increased seasonal rainfall leads to an increase in liquid water flux and a decrease in water vapour flux, whereas decreased seasonal rainfall leads to the opposite trend. Heat conduction, water vapour thermal convection, and water vapour diffusion latent heat decrease with increasing rainfall in various seasons. However, liquid water thermal convection increases with increasing rainfall during various seasons. Seasonal rainfall variations ultimately affect permafrost thermal stability by influencing water-vapour migration and energy changes within the permafrost active layer. Among them, the active layer thickness remains basically unchanged after the spring rainfall increases by 2.0 times, whereas it decreases by 4 and 6 cm after the summer and autumn rainfall increase by 1.5 and 2.0 times, respectively. Additionally, when the rainfall during spring, summer, and autumn decreases by 2.0, 1.5, and 2.0 times, respectively, the active layer thickness increases by 7, 6, and 3 cm, respectively. Therefore, increased seasonal rainfall can alleviate permafrost degradation. Otherwise, it is unfavourable for the preservation of permafrost thermal stability.

Hysteretic Behavior of Global to Regional Monsoon Area Under CO2 Ramp‐Up and Ramp‐Down

AbstractWhen projecting future monsoon changes by carbon dioxide (CO2) pathway, most studies have analyzed precipitation responses without considering monsoon area (total area of monsoon domain, MA) variations. However, how MA responds to CO2 removal remains uncertain. This study evaluates MA variations and impacts in idealized CO2 ramp‐up (toward CO2 quadrupling), ramp‐down, and stabilized simulations using the Community Earth System Model version 1. Global MA negatively overshoots (i.e., recovery with decreasing tendency beyond the original MA) during the ramp‐down period due to reduced or rapidly recovered MA in several regional monsoons, including Northern and Southern Africa, South and East Asia, and South America, showing hysteresis when comparing CO2 ramp‐up and ramp‐down periods despite similar global warming levels. These non‐linear regional MA variations come from distinct regional summer and winter precipitation variations, which are found to be mostly associated with Intertropical Convergence Zone movements and El Niño‐like response. Further, regional monsoon precipitation characteristics also vary through CO2 ramp‐up and ramp‐down periods consistently with overall hysteresis. Changes in total monsoon precipitation resemble the distinct responses of MA. Our results suggest that regions characterized by a monsoonal climate may experience reduced seasonal rainfall variations under net‐negative CO2 emissions.

Spatio-temporal variability and rainfall trend affects seasonal calendar of maize production in southern central Rift Valley of Ethiopia

Understanding rainfall variability is important to establish crop calendar related agronomic decisions. To this end, we defined start and end of seasons, analyzed dry spell and evaluated conditional risks of alternative planting dates using a thirty years daily rainfall data across southern central rift valley of Ethiopia. Results showed that the probability of annual rainfall being greater than 1000 mm was 97, 24, 94, and 61%, in Dilla, Bilate, Shamana, and Hawassa clusters, respectively. The variability of annual total rainfall in the lowland areas of Dilla and Bilate was above 25%, whereas for Shamana and Hawassa was below 20%. Variability of seasonal rainfall during FMAM was 33.7%, which is higher than ONDJ (27.1%) and JJAS (27.9%), which could lead to maize plants suffering moisture stress during FMAM season. The onset of rains had variability of 29.2, 19.5, 17.5 and 26.5%, and also LGP showed variability of 22.8, 22.1, 21.2 and 20.3% in Shamana, Bilate, Hawassa, and Dilla clusters, respectively. Moreover Shamana, Bilate, Hawassa and Dilla clusters are hit by agricultural drought in one out of 2.61, 2.3, 2.5 and 2.5 years, respectively. Model based analysis of conditional risk of farmers planting dates also showed a success rate of less than 10, 7, 40 and 63% for maize variety in Shamana, Bilate, Hawassa and Dilla clusters, respectively. However, the success rate of risk taker farmers’ is higher than anticipated by the model. The farmers who take risk were encouraged in Shamana cluster by local edaphic, physiographic, socioeconomic and climatic differences. Hence, there is a need to seek real time local agro-metrological advisory and follow the necessary tactical and strategic farming decisions. Moreover, there is also a need to incorporate local factors with modern climate models to obtain synchronized calendar estimates.

Effect of urbanization on East African climate as simulated by coupled urban-climate model

This study examines the effect of urbanization on climate variability over East Africa. Seasonal trend of rainfall and temperature was analyzed using Mann-Kendall trend test and statistically significant rainfall trend is observed during spring (February-May) and summer (June-September) over northeast and spring/“bega”(October-January) seasons in southeastern regions of Ethiopia, thereby suggesting a seasonal shift of rainfall distribution. The temperature trend showed significant warming in the simulated field, except in central East Sudan, where there has been a significant decline. A numbers of idealized sensitivity experiments have been conducted with the Regional Climate Model (RegCM4.6) to investigate the contribution of urbanization to the East African region climate variability and trend. Model assessment against observed climate variables showed good performance in the simulation of spatial and temporal variability of regional climate variables. The results of the sensitivity experiment by prescribing different urban environments (tall building district (TBD), high density (HD), medium density (MD) and original land use) for the surface scheme (CLM4.5) reveal statistically significant impacts of urbanized surfaces on surface temperatures and precipitation due to variations in energy budget, local circulation and disturbance of hydro meteorological variables. It is noted that TBD urban environment has a higher impact on the local climate than other urban environments. Patterns of seasonal rainfall variability simulated using artificially urbanized land cover suggests involvement of complex interactions and is less similar to the observed rainfall trend, while surface temperature variability is significantly affected by local land-cover change and is very similar to the observed surface temperature trend.

Assessing land suitability and spatial variability in lucerne yields across New Zealand

Lucerne (Medicago sativa L.) is a widely grown perennial legume worldwide which can provide high biomass and protein yields, biological N fixation, deep soil water extraction and a range of ecosystems services relevant to current and future agricultural systems. The potential to expand lucerne beyond its current cultivated areas in New Zealand, and its potential productivity across the country’s contrasting climate zones, are currently unknown. To gain such insights, we estimated land suitability and spatial distribution of lucerne above-ground biomass across New Zealand lands considering contrasting growth conditions (rain-fed or irrigated for different soils types) and two simulation methods of different complexity (process- and GIS-based approaches). This aimed to assess yield-estimate spatial patterns and sensitivity to model selection for a wide range of combinations of water supply (i.e. irrigation and soil water storage) across New Zealand climate zones. For example, highly suitable areas for lucerne cultivation, were estimated in ∼21 thousand km2 when considering the exclusion of steep slopes, poor soil drainage and excess annual rainfall. The two crop-yield models were applied in response to 30 years of daily historical (1971–2000) weather data downscaled at 5 km resolution on suitable areas. Simulated average lucerne yields ranged from ∼4.5–28 t dry matter/ha per year. Simulations showed a distinct spatial pattern of yield decline from north to south, mainly in response to decreasing temperatures. Temporally, water limited yields were up to 4-fold more variable than under irrigation, depending on the degree of drought stress across different years. Results also unveiled systematic spatial patterns of model uncertainty quantified as yield sensitivity to model selection. For instance, simulated yields were most sensitive to model selection (6–31% of total variability, Ti) within high abiotic-stress environments (e.g. low temperature and limited water supply). Overall, soil type selection accounted for most of yield variability (58–78% Ti), being particularly important in warmer environments with variable seasonal rainfall regimes (e.g. northern regions). As expected, water supply (i.e. rain-fed or irrigated systems) was relatively more impactful on yield (8–20% Ti) for limited rainfall areas, where crops are most drought prone (e.g. east coast and central southern regions). Long-term regional scale comparisons of annual lucerne yield, between 30-year simulated distributions and point-based observations from the AgYields database, helped identify hotspots of yield overestimation. Such insights are useful to guide future research on high yield gap areas (e.g. southern colder and drier locations) and highlight key areas for model improvement (e.g. representation of multiple biotic stresses). Overall, our results provide a first gridded-model assessment of lucerne suitability and yield at national scale and quantify the share of variability explained by key climatic, management and methodological components in spatial analysis studies. These insights can inform future modelling efforts and support agricultural planning that considers the expansion of lucerne and other perennial legumes.

Effect of climate and flooding on the phenology of Attalea phalerata (Arecaceae) in a white‐water floodplain forest of the Amazon River

AbstractLittle is known about the effect of the polymodal tide of the Amazon estuary on the phenology of palms. We evaluated the effect of climate/flood and biotic factors on the phenology of 80 Attalea phalerata palms over 1‐year period. Bract emission and young leaves percentage were negatively correlated to accumulated rainfall. Inflorescence and leaf production occurred mainly in the dry season. Immature fruit was positively correlated with rainfall, showing that fruit development occurs during the rainy season. The production of flowers, unripe fruit, and young leaves were positively correlated to flooding. The production of infructescence, per palm, varied from 0 to 4 and 18% of the variance was explained by variables of stem diameter, number of new leaves, altitude, and flood amplitude. The number of infructescence increased for large palms and decreased for individuals subjected to high amplitudes of flooding. These findings reveal that phenological patterns of A. phalerata are driven by seasonal variation in rainfall and flooding. Furthermore, infructescence production can be predicted by plant size and this production is sensitive to variations in flood amplitude. Alteration in rainfall and flooding due to climate change may have a negative impact on fruit production if extreme events increase in frequency.

Apportioning Human-Induced and Climate-Induced Land Degradation: A Case of the Greater Sekhukhune District Municipality

Land degradation (LD) is a global issue that affects sustainability and livelihoods of approximately 1.5 billion people, especially in arid/semi-arid regions. Hence, identifying and assessing LD and its driving forces (natural and anthropogenic) is important in order to design and adopt appropriate sustainable land management interventions. Therefore, using vegetation as a proxy for LD, this study aimed to distinguish anthropogenic from rainfall-driven LD in the Greater Sekhukhune District Municipality from 1990 to 2019. It is widely established that rainfall highly correlates with vegetation productivity. A linear regression was performed between the Normalized Difference Vegetation Index (NDVI) and rainfall. The human-induced LD was then distinguished from that of rainfall using the spatial residual trend (RESTREND) method and the Mann–Kendall (MK) trend. RESTREND results showed that 11.59% of the district was degraded due to human activities such as overgrazing and injudicious rangeland management. While about 41.41% was degraded due to seasonal rainfall variability and an increasing frequency of droughts. Climate variability affected vegetation cover and contributed to different forms of soil erosion and gully formation. These findings provide relevant spatial information on rainfall or human-induced LD, which is useful for policy formulation and the design of LD mitigation measures in semi-arid regions.

Determination of Exploitable Coefficient of Coral Island Freshwater Lens Considering the Integrated Effects of Lens Growth and Contraction

Groundwater on small coral islands (so-called freshwater lens) is an important water resource for residents and local ecosystems. However, an overexploitation of it may induce a contamination by saltwater. In this paper, we strive to determine the exploitable coefficient of the freshwater lens considering the integrated effects of lens growth and contraction and examine the impacts of well layout schemes on the evolution of the freshwater lens. For this purpose, a numerical model is setup to simulate the saltwater upconing and recovery process under pumping conditions during different evolution stages. Our results show that long-term and higher intensity pumping activities are suggested to be conducted at the latter stage of the lens evolution. Meanwhile, the seasonal contraction of the freshwater lens caused by the seasonal variation in rainfall is characterized by a quicker response of center thickness than maximum thickness of the lens, which further impacts the pumping intensity. The results also indicate that the exploitable coefficient (ρ) of the freshwater lens in small coral island is generally smaller than that in inland areas, ranging from 0.09 to 0.37 under different well layout schemes. Additionally, it is also affected by the uncertainty of hydrogeological parameters. Finally, a safe exploitable coefficient is proposed under the most unfavorable parameter combination for the studied island. The study has important implications for the protection and sustainable exploitation of subsurface freshwater resources on island.