Annual Rainfall Variability Research Articles

Drought assessment in a south Mediterranean transboundary catchment

ABSTRACT Predicting the impacts of climate change on water resources remains a challenging task and requires a good understanding of the dynamics of the forcing terms in the past. In this study, the variability of precipitation and drought patterns is studied over the Mediterranean catchment of the Medjerda in Tunisia based on an observed rainfall dataset collected at 41 raingauges during the period 1973–2012. The standardized precipitation index and the aridity index were used to characterize drought variability. Multivariate and geostatistical techniques were further employed to identify the spatial variability of annual rainfall. The results show that the Medjerda is marked by a significant spatio-temporal variability of drought, with varying extreme wet and dry events. Four regions with distinct rainfall regimes are identified by utilizing the K-means cluster analysis. A principal component analysis identifies the variables that are responsible for the relationships between precipitation and drought variability.

Inter-annual growth response of three Miombo tree species to climatic effects

Miombo woodlands cover a large part of Southern Africa and contribute an important wood source for the local wood industry. The already observed and further predicted changes in climatic patterns can be expected to affect the wood properties of Miombo tree species. The diameter growth response to climatic variables related to water availability and temperature of three Miombo woodland tree species (Brachystegia spiciformis, Burkea africana and Isoberlinia angolensis) was analysed using 245 trees samples in three climatic zones in Zambia. Sites were chosen to represent the range of site conditions under which these species grow in the Miombo woodlands of Zambia. The study sites differed in moisture availability and average temperature, as indicated by De Martonne’s aridity index. Tree-ring width correlated with site conditions and differed significantly between sites. A positive correlation was found between mean annual precipitation and annual ring width, as well as growth variation, while growth was almost non-responsive to temperature variations. For all three species, trees growing on the outer limits of the species’ range were found to be more responsive and sensitive to variability in annual rainfall than those growing under optimal conditions. All three species showed significant variation in inter-annual ring width with environmental conditions. Water availability was found to have a much larger effect than temperature, especially on drier sites.

Hybridization fluctuates with rainfall in Darwin’s tree finches

AbstractHybridization in natural populations may be an adaptive response to shifting climatic regimes, but understanding this can be limited by the timing of sampling effort and confident identification of hybrids. On the Galapagos Islands, Darwin’s finches regularly hybridize; the islands also show extreme annual variation in rainfall, but the effect of annual rainfall on the frequency of finch hybridization is little known. Across a 20-year period on Floreana Island, we compare patterns of hybridization in sympatric Darwin’s tree finches (N = 425; Camaryhnchus spp.) and test for an effect of annual rainfall on (1) the frequency of hybrids (C. pauper × C. parvulus) and (2) the percentage of male hybrid birds produced per year (hybrid recruitment). Annual rainfall correlated with recruitment positively for hybrids, negatively for C. parvulus and not at all for C. pauper. Furthermore, the percentage of hybrids (range: 12–56%) and C. parvulus did not change with sampling year, but the critically endangered C. pauper declined. Our findings indicate that hybrid recruitment is recurring and variable according to annual rainfall in Camarhynchus Darwin’s finches.

Deterministic Seasonal Quantitative Precipitation Forecasts: Benchmark Skill with a GCM

Many applications, from agricultural planning (such as crop choice) to estimation of hydro-power and surface water availability require quantitative precipitation forecasts (QPF). While a large number of studies have addressed the problem of forecasting seasonal Indian summer monsoon (ISM) rainfall over the decades, the emphasis generally has been on simulation and forecasting of rainfall anomalies from long-period mean. However, given the trends in monsoon rainfall, the procedure of considering anomalies has inherent errors; thus reconstruction of actual rainfall from the anomalies does not necessarily provide accurate information. Most QPF have been attempted at short-range forecasts, with a variety of techniques like model output statistics. This work represents evaluation of an atmospheric Variable Resolution General Circulation Model (VRGCM) for QPF during monsoon season. The VRGCM, with variable grid resolution provides relatively high (~ 50 km) resolution over the ISM region, has been validated over all India as well as in different regions like Central and North India, South India, North East India for seasonal forecast of monsoon rainfall. VRGCM simulated QPF appears to provide comparable information as that of anomaly forecasts of monsoon over different regions in India. The forecast skill is appreciable, with significant correlation at all India, South India and North East India regions. The Root Mean Square Error of VRGCM in forecasting quantitative rainfall overall India and Central North India is very low and bit high over South and North East region of India. The performance of VRGCM in forecasting the rainfall in extreme (deficit or excess) monsoon years is also very high with phase synchronisation of 89% in the inter annual variability of rainfall during monsoon at all India scale while the value is about 57%, 76% and 55% over Central North, South and North East India region, respectively.

English

Farmers’ local knowledge of how the climate is changing is crucial in anticipating the effects of climate change, as only farmers who know/perceive the impacts will develop coping and adaption measures. The study is designed to assess farmers’ perception and understanding in climate variability and change and to establish the observed climate change parameters with farmer’s perception and climate anomalies. Household survey, semi-structured interviews, focus group discussions and 30 years of climate data was employed. Non-parametric test using Mann-Kendall climate trend analysis and Sen’s slope estimator was employed to test the variability of climate using MAKESENSE software. The findings revealed that farmers perceived climate change in terms of increase in temperature, decrease in rainfall, increase in drought conditions and change in seasonal rainfalls. Analysis of the observed climate data for the sub-basin showed that average annual temperature trends has exhibited a positive slope and increased by 1.4°C and above the national average (1.3°C) over the study periods (1986-2014) at mean temperature rise with an average rate of 0.181°C in the last decade. The observed climate variability was confirmed by farmer’s perception. The Mann-Kendall rainfall trend analysis showed that annual and monthly precipitation variability in terms of intensity and distributions declined and vary across agro ecological zones. The analysis indicated that annual rainfall variability in Dega agro ecological zone (CV>63%) and in Kola agro ecological zone (CV>104%) was extremely variable. However, in terms of amount and distributions of precipitation, farmers understanding of precipitation in relation to observed precipitation data showed disparities. This disparity was due to understanding of agronomic drought (farmer’s view) and metrological drought (scientific view). Therefore, based on the findings, scientist and policymakers has to integrate the metrological information into farmers’ perception and knowledge of climate variability for future climate adaptations measure. Key words: Climate variability, farmers’ perception, climatological normal, local knowledge. &nbsp

Optimizing wheat (Triticum aestivum L.) management under dry environments: A case study in the West Pampas of Argentina

Water shortage, caused by large variations in the amount, frequency and timing of rainfall during the crop cycle, is one of the major abiotic stresses limiting crop production. In this context, environmental variability represents a significant challenge for farmers as optimal management practices vary from season to season. The aim of this study was to optimize wheat (Triticum aestivum L.) management practices considering rainfall variability in the West sandy Pampas of Argentina. This region is characterized by a high annual rainfall variability with predominant summer rainfall and probable deficits during winter and early spring in analogy with many other regions around the world. Two commercial cultivars, commonly used by farmers, with different time to flowering (LF: late flowering; EF: early flowering), under three initial soil water conditions (well-watered, moderately-watered and dry conditions) at three sowing dates were simulated with CERES-WHEAT for a series of 39 years. Wheat yield was higher for the LF than the EF cultivar under average (LF = 5437 vs. EF=5112 kg ha−1) and no-water restriction years (LF = 7915 vs. EF=6956 kg ha−1), while the opposite was observed in dry years (EF = 4128 vs. LF=3255 kg ha−1). Reductions in grain yield were associated with reductions in grain number, mainly explained by a lower partitioning to reproductive organs, principally limited by water shortage. The LF cultivar used more water than the EF cultivar before anthesis depleting soil water reserves (p < 0.05) and losing the yield potential advantage in dry years. Genotypic differences were more evident under initial soil well-watered conditions (16 %) compared to moderately-watered (13 %) or dry conditions (9%). Therefore, cultivar selection could partially compensate the deleterious impacts of water deficit on wheat yield under early water stress pattern environments. These results highlight the relevance of design management practices under variable water scenarios in order to reduce yield gaps.

Seasonal and Regional Variations in Rainfall Distribution Over the Punjab-Pakistan

The purpose of present study is to investigate district and division wise annual rainfall variations over theprovince of Punjab, which is the largest in terms of population size as well important contributor in agricultural producein Pakistan. The results revealed that the rainfall trend has shifted from upper and lower Punjab towards the south,west, north and east respectively. The statistical analysis has inferred an overall increasing trend for the period 1990 to2000 and a decreasing trend during period 2001 to 2010 in Punjab province. The Z test value differences in the averagerainfall for each district level meteorological station have detected three increasing and two decreasing trends duringsummers of 1981-2015.The data revealed a significant changed seasonal trend observed in Murree and Sialkot(northern Punjab), Faisalabad and Lahore (central Punjab). Particularly, the changes have been observed in the southPunjab and over the central Punjab, while the same rainfall variations have shown a southward shift. The trend of therainfall had shifted in the Faisalabad division with the significant positive trend. In the Central Punjab, the positivetrend has also been found in all the districts. In the lower Punjab, Multan, Dera Ghazi Khan districts has shown anincreasing trend of rainfall. The findings are significant in changing agro-climatic zones in the Punjab and consequentshifting patterns of agriculture therefore can have net impact on the food security situation in the Punjab-Pakistan.

Seasonal and Regional Variations in Rainfall Distribution Over the Punjab-Pakistan

The purpose of present study is to investigate district and division wise annual rainfall variations over theprovince of Punjab, which is the largest in terms of population size as well important contributor in agricultural producein Pakistan. The results revealed that the rainfall trend has shifted from upper and lower Punjab towards the south,west, north and east respectively. The statistical analysis has inferred an overall increasing trend for the period 1990 to2000 and a decreasing trend during period 2001 to 2010 in Punjab province. The Z test value differences in the averagerainfall for each district level meteorological station have detected three increasing and two decreasing trends duringsummers of 1981-2015.The data revealed a significant changed seasonal trend observed in Murree and Sialkot(northern Punjab), Faisalabad and Lahore (central Punjab). Particularly, the changes have been observed in the southPunjab and over the central Punjab, while the same rainfall variations have shown a southward shift. The trend of therainfall had shifted in the Faisalabad division with the significant positive trend. In the Central Punjab, the positivetrend has also been found in all the districts. In the lower Punjab, Multan, Dera Ghazi Khan districts has shown anincreasing trend of rainfall. The findings are significant in changing agro-climatic zones in the Punjab and consequentshifting patterns of agriculture therefore can have net impact on the food security situation in the Punjab-Pakistan.

Spatial and Temporal Dynamics of Urban Wetlands in an Indian Megacity over the Past 50 Years

Asian megacities have attracted much scientific attention in the context of global urbanization, but few quantitative studies analyze wetland transformation in the rural–urban interface. With its rampant growth and transformation from a tree-lined “Garden City” to a busy megalopolis with often-blocked highways and large built-up areas, Bengaluru (Karnataka, S-India) is a good example for assessing how urbanization has led to the acute degradation of wetlands. We therefore investigated long-term land cover and wetland changes from 1965 to 2018 based on an object-based classification of multi-temporal Corona and Landsat images. To quantify and compare the dynamics of open water surfaces and vegetation, we defined the potential wetland areas (PWA) along the rural–urban gradient and linked our analyses to an index describing the degree of urbanization (survey stratification index (SSI)). During the five decades studied, built-up areas in the Bengaluru Urban district increased ten-fold, with the highest growth rate from 2014 to 2018 (+ 8% annual change). Patches of lake wetlands were highly dynamic in space and time, partly reflecting highly variable annual rainfall patterns ranging from 501 mm in 1965 to 1374 mm in 2005 and monsoon-driven alterations in the hydrologic regime. While water bodies and flooded areas shrunk from 64 km2 in 1965 to 55 km2 in 2018, in 1965, the total rural wetland area with an SSI &gt; 0.5 was twice as high as in 2018. The rural–urban land cover pattern within potential wetland areas changed drastically during this period. This is reflected, for example, by a four-fold increase in the wetland area with an SSI of 0.3, as compared to a decline by 43% in wetland area with an SSI of 0.8. While, in urban areas, wetlands were mostly lost to construction, in areas with a rural character, open water bodies were mainly transformed into green space. The detected changes in urban wetlands were likely accompanied by ecological regime changes, triggering deteriorations in ecosystem services (ESS) which merit further research.

Impacts of rainfall variability on paddy production: A case from Bayawa minor irrigation tank in Sri Lanka

Rainfall (RF) variability has been suggested as the primary reason for low paddy production in the recent past under minor irrigation tanks (MITs). A study was conducted to verify the relationship between observed crop success/failures and the RF variability in the Bayawa MIT system in the Kurunegala district of Sri Lanka. Seasonal and annual RF variability and its effect on paddy crops were analyzed. Daily rainfall data were obtained from the Wariyapola station from 1983 to 2014. Paddy production data for 20 consecutive seasons from 2003 to 2014 were collected from the Department of Census and Statistics (DCS), Colombo. Paddy samples from the Bayawa command area were used to calculate the land productivity and compared between the two cultivation seasons. Three types of direct RF impacts on paddy production in the Bayawa MIT system were identified: (1) reductions in the cropping intensity (CI), (2) total crop failures and (3) reductions in yield. During the study period, the CI was 80–173% with an average of 140% (expected value is 200%). Sixty percent of annual and seasonal RF values were below the long-term average showing a direct effect of RF on crop failures. Low production is not only due to the variability of annual or seasonal RF during the cultivation seasons, but also due to poor water management decisions, such as not cultivating considering the available water in the MIT. Thus, there is a need for wise water management decisions of MITs in this study area based on the variability of RF for sustainable paddy production.

Inter-annual variability of Pinus pinea L. cone productivity in a non-native habitat

Pinus pinea produces the most expensive pine nuts worldwide, with a masting habit (variable cone productivity over time) in its native habitat. This study assessed the presence of masting habit in a non-native area, the correlation of annual cone production with climatic variables, and the impact of resource depletion on cone productivity 3 and 4 years after a bumper crop. During 10 years, all cones tree−1 were harvested and counted in three plantations. Cone yield stability was measured via coefficient of variation of cones tree−1. Climatic factors were correlated with stone pine masting. Results indicated that inter-annual variability of cone yield and annual rainfall during 3 years prior to seed maturity, and thermal oscillation 2 years before harvest, were significantly correlated. A correlation was found between cone productivity when reproductive shoot differentiation or when male and female primordia induction occurred, and cone productivity 3 and 4 years later. Individual tree fruit load did not reduce flower induction. The most productive trees will also be the most productive ones in the following years, a finding with practical implications for breeding programs and plant production.

Sensitivity Experiments of Rainfall to Warm Cloud Auto-Conversion Threshold and Relative Humidity Threshold of Cloudiness in RegCM4.6 over the Maritime Continent

ABSTRACTIn the present work, sensitivity experiments for two parameter schemes are conducted using the Regional Climate Model System, version 4.6, to improve the model capability for reproducing rainfall over the Maritime Continent (MC). One parameter is the warm cloud auto-conversion threshold in the Emanuel convective scheme, and the other parameter is the relative humidity threshold of cloudiness in the subgrid explicit moisture microphysics scheme. Our results show that using the optimized values of these two parameters can reduce the rainfall bias over land in the western MC. In addition, we also show that the choice of the sea surface temperature forcing data is important in improving the model's performance. The improvement is confirmed from extreme year simulations and the long-run simulation in both spatial and temporal characteristics. The optimized simulation shows improved model performance in both wet and dry seasons. The underestimation of the annual and interannual rainfall variability is alleviated in the optimized simulation. This indicates the model's ability to reproduce the MC's rainfall under the appropriate parameterization schemes. We expect that our optimized parameterization can be used to reproduce more reliable downscaled rainfall data to support various climate research activities over the MC.

An evaluation of the CORDEX regional climate models in simulating future rainfall and extreme events over Mzingwane catchment, Zimbabwe

The study evaluated CORDEX RCMs’ ability to project future rainfall and extreme events in the Mzingwane catchment using an ensemble average of three RCMs (RCA4, REMO2009 and CRCM5). Model validation employed the statistical mean and Pearson correlation, while trends in projected rainfall and number of rainy days were computed using the Mann-Kendall trend test and the magnitudes of trends were determined by Sen’s slope estimator. Temporal and spatial distribution of future extreme dryness and wetness was established by using the Standard Precipitation Index (SPI). The results show that RCMs adequately represented annual and inter-annual rainfall variability and the ensemble average outperformed individual models. Trend results for the projected rainfall suggest a significant decreasing trend in future rainfall (2016–2100) for all stations at p < 0.05. In addition, a general decreasing trend in the number of rainy days is projected for future climate, although the significance and magnitude varied with station location. Model results suggest an increased occurrence of future extreme events, particularly towards the end of the century. The findings are important for developing proactive sustainable strategies for future climate change adaption and mitigation.

Changes in rainfall patterns on the upper Ecuadorian Andean mountains: Analysis of extreme precipitation, ENSO effects and shifts of annual rainfall variation

Rainfall in the upstream drainage area of the Ecuadorian Andean Mountains (EAM) is an important source of water supply in populated areas. Managing water resource projects depend on rainfall-runoff variation. Even though, it is difficult to understand the mechanism that controls rainfall variation because of the influence of several global and local hydrological processes, this type of research is needed to improve the management of water resources. Understanding these processes is complex due to inaccessibility to these remote zones leading to inefficacy in the monitoring of these gauge stations. Furthermore, there are reports that exposed that climatic anomalies are affecting rainfall-runoff processes around the world. These climate changes cause two main problems in urban infrastructure. First, the occurrence of extreme precipitation events increasing the risk of flooding. Second, changes on annual rainfall variation that could lead to water scarcity in the management of water resource projects. This study focuses on improving the understanding of rainfall trends at EAM and its implications in the management of water resources. The results indicate that 71% of extreme precipitation events were registered in the second period of the last twenty years (1995 - 2015) with severe short rainfall events, during ENSO years in the EAM, threatening hydraulic facilities.

Assessment of seasonal and annual rainfall trend in Calabria (southern Italy) with the ITA method

Abstract In this paper, an investigation on the temporal variability of seasonal and annual rainfall in the Calabria region (southern Italy) was carried out using a homogeneous and gap-filled monthly rainfall dataset of 129 rain gauges in the period 1951–2006. In particular, possible trends have been assessed by means of the Innovative Trend Analysis (ITA) technique, which allows the identification of a trend in the low, medium and high values of a series. Moreover, the results obtained with the ITA have been compared with the ones obtained with the Mann–Kendall test. These analyses have been performed in five rainfall zones (RZs) of the study area, characterized by different climatic conditions. As a result, both the methods evidenced a negative trend of the annual rainfall in the entire study area. On a seasonal scale, this negative tendency has been confirmed in autumn and winter although with some differences among the several RZs.

Impact of R&D expenditures, rainfall and temperature variations in agricultural productivity: empirical evidence from Bangladesh

ABSTRACT This study aims to investigate dynamic relationships between research and development (R&D) expenditure, climate change (measured by annual rainfall and temperature variations), human capital (proxied by literacy) and total factor productivity (TFP) growth in Bangladesh agriculture. Pesaran’s Pooled Mean Group (PMG) estimator is used to a unique panel data of 17 regions of Bangladesh covering a 61-year period (1948–2008). In addition, the panel vector autoregression (PVAR) model is also applied to trace the responsiveness of TFP from a shock to R&D, extension services, and literacy rate. Results reveal that R&D has an insignificant impact on TFP in the short-run, while it has a significant positive impact in the long-run. The contributions of climate variables (i.e., rainfall and temperature variations) are highly significant and negative in the long run. The literacy rate is found to have a significant positive impact on TFP as expected. These results suggest that agricultural R&D investment and human capital could play an important role to ameliorate the adverse effects of climate change in the agricultural sector of Bangladesh.

Rainfall variability and its effects on growing period and grain yield for rainfed lowland rice under transplanting system in Northeast Thailand

ABSTRACTRainfall variability in Northeast Thailand during 2000–2015 was examined with objectives to determine any changes in rainfall pattern with time, and to determine its effects on duration of rice growing period and grain yield using a simulation model. Variation in mean annual rainfall over 16 years in 93 locations in the region ranged from over 1,600 to less than 1,200 mm, and the locations were grouped into 4 based on the annual rainfall. The change in annual rainfall, and early, mid and late season rainfall was analysed for the rainfall groups. There was a significant reduction in the amount of early season rainfall during the 16-year period in all groups. However, there was no significant change for annual, and mid and late season rainfall. Simulation study showed that the start of rice growing period (SGP) was delayed with reduced early rainfall during the 16 year period and the end of rice growing period (EGP) was also delayed while there was no significant change for the length of rice growing period (LGP). Simulation results showed that grain yield of KDML105, leading variety in Thailand, tended to increase during the 16 year period, as delayed planting time was optimum for achieving maximum yield in all rainfall groups. With general delay in rainfall season, occurrence of late season drought was predicted to be reduced and this helped to increase simulated grain yield. However, adaptation to changing rainfall pattern needs to be planned in advance to maximize its effect.

An Assessment of Drought in Mannar District, Sri Lanka

Due to recent climate changes and variability the frequency of occurrence and intensity of extreme climatic events such as flood, drought, etc. are increasing significantly in Sri Lanka. The main objectives of the study are to analyze the annual and seasonal rainfall variability in the last 147years from 1871-2018 with particular reference to drought and to assess the occurrence of droughts and its intensity and the impacts of drought on agriculture. For this secondary and primary data have been used. The long-term average annual rainfall of Mannar show the decreasing trend (r2= 0.0158), particularly in recent epochs higher negative anomalies of rainfall were found, as a results frequent occurrence of droughts or dry spells have been occurred. The rainfall anomaly results reveal that, out of 147years of the data period about 47years were experienced as drought and its probability is P=0.320. Accordingly, once in four to five years a drought could be possible. However, in the recent epoch of 1991-2018, higher number of droughts occurred than the any other epochs and its epochal probability is higher (P=0.40) than the normal, which indicate the effect of recent climate change.

Meteorological data and farmers’ perception of coastal climate in Bangladesh

This study compares the scientifically observed spatiotemporal climate variability with farmer perceptions. A survey of 381 farmers and ten focus group discussions (FGDs) were used to collect data from ten coastal subdistricts. We hypothesized that any gap between farmer perceptions and meteorological data could be due to variations in their individual characteristics. An unsupervised clustering algorithm was used to categorise the farmers into good and poor perception clusters to test the hypothesis. The climatic data showed a low (0.45 °C) spatial difference of the mean temperature (1988–2017) among the visited locations. Annual rainfall variations between the western and eastern coastal areas could be more than 100 cm, making the eastern coasts wetter. The FGD outputs were mostly cognate with meteorological data that the recent (2013–2017) average temperature was higher (except early winter) and, in general, rainfall was lower than that of 1998–2002. Compared to the meteorological data, greater imperfect perceptions of farmers were observed in case of rainfall and winter temperature. This resulted in a gap between the meteorological data and farmer perceptions at the household level. Among the sampled farmers, only 30% had meteorologically consistent perceptions of average-, summer- and winter-temperature, and rainfall. The cluster analysis has divided the farmers into good perception (41.2%) and poor perception (58.8%) clusters. Greater proportions of the western coastal farmers were clustered in the good perception group than that of the eastern parts. A higher accuracy of the perceptions was found among the better-off farmers who were characterized by younger age, better education, smaller family size, richer economic status, larger farm size, more affiliation with non-farm jobs, users of more communication media, closer to the marketplaces and more distant from the sea. The worse-off households, in particular, require policy and extension support to update their understanding of climate change to facilitate adaptation strategies.

Innovative trend analysis of total annual rainfall and temperature variability case study: Yesilirmak region, Turkey

It is well known that any kind of ordinary hydrometeorological parameter trend may have increasing or decreasing tendency systematically. Various methodologies are developed for possible trend identification such as the well-known Mann-Kendall test and recently Şen innovative trend analysis (ITA) approaches. The former has a set of assumptions, whereas the latter is almost without any restrictive assumption. The main purpose of this paper is to present precipitation and temperature trend behaviors by applying ITA in Yesilirmak drainage basin. Selected observation stations are mainly located at the Black Sea confluence region of Yesilirmak while few others at the middle and upper drainage basins. ITA provided visual inspection with quantitative trend slopes distinctively for low, medium, and high sub-levels with physical interpretations. Based on categorization, precipitation records have significant decreasing trends in low, medium, and high levels as an average − 3.4%, − 3.8%, and − 2.4%, respectively. In contrary to precipitation trend, and consistent to global expectation in climate change, temperature records have significantly strong increasing tendency along the basin. In sub-level of temperature, this strong trend tendencies are detected + 4.6%, + 4.8%, and + 7.2% from low to high ranges, respectively.