Percentage Changes In Rainfall Research Articles

Spatiotemporal variability and change in rainfall in the Oti River Basin, West Africa

Abstract Understanding rainwater dispersion in a spatiotemporal context is invaluable toward resourceful water management and a food-secure society. This study, therefore, assessed the variations in rainfall at a spatiotemporal scale in the Oti River Basin of West Africa for observed (1981–2010) and future periods (2021–2050) under the representative concentration pathways (RCPs) 4.5 and 8.5 emission scenarios. Rainfall data from meteorological stations and Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) were used. The percentage changes in rainfall for the peak month as well as for rainy and dry seasons under the two climate scenarios were determined. The coefficient of variation (CV) and the standardized anomaly index (SAI) were used to assess annual variations in rainfall. In general, under both emission scenarios, rainfall is projected to decrease over the study area. However, the amount of rainfall during the peak month (August) for RCP4.5 and RCP8.5 could increase by 0.26 and 9.3%, respectively. The highest SAIs for the observed period were +1.58 (2009) and −2.29 (1983) with the latter showing a relationship with historic drought in the basin. The projected SAI under RCP4.5 and RCP8.5 indicated extremely wet (+2.12) and very wet (+1.91) periods for the years 2037 and 2028, respectively. The study provides relevant information and a chance to aid the design of innovative adaptation measures toward efficient water management and agricultural planning for the basin.

Rainfall and temperature changes under different climate scenarios at the watersheds surrounding the Ngorongoro Conservation Area in Tanzania

Considering the high vulnerability of Northern Tanzania to climate change, an in-depth assessment at the local scale is required urgently to formulate sustainable adaptations measures. Therefore, this study analyzed the future (2021-2050) changes in rainfall and temperature under the representative concentration pathways (RCP4.5 and RCP8.5) for the watersheds surrounding the Ngorongoro Conservation Area (NCA) at a spatio-temporal scale relative to the observed historical (1982-2011) period. The climate change analysis was performed at monthly and annual scale using outputs from a multi-model ensemble of Regional Climate Models (RCMs) and statistically downscaled Global Climate Models (GCMs). The performance of the RCMs were evaluated, and the downscaling of the GCMs were performed using Statistical Downscaling System Model (SDSM) and LARS-WG, with all the models indicating a higher accuracy at monthly scale when evaluated using statistical indicators such as correlation (r), Nash-Sutcliff Efficiency (NSE) and percentage bias (PBIAS). The results show an increase in the mean annual rainfall and temperature in both RCPs. The percentage change in rainfall indicated an increase relative to historical data for all seasons under both RCPs, except for the June, July, August and September (JJAS) season, which showed a decrease in rainfall. Spatially, rainfall would increase over the entire basin under both RCPs with higher increase under RCP4.5. Similar spatial increase results are also projected for temperature under both RCPs. The results of this study provide vital information for the planning and management of the studied watershed under changing climatic conditions.

The Impact of Regional Climate Change on Hydroelectric Resources in South America

The objective of this study is to estimate the impact of climate change on the hydroelectric potential of various basins across South America. Three different downscaled global climate models are used to estimate the percentage changes in rainfall and streamflow by the 2030s and 2080s under a high emission scenario in comparison to 1961–1990 baseline data. While rainfall is projected to increase slightly over the Uruguay River basin, rainfall over the Amazon and Brazil’s Northeast region is expected to decline. As a consequence of climate change, streamflow in the São Francisco River, Tocantins River and Parnaiba River is projected to decline 46%, 31% and 26%, respectively in the coming 3 decades compared to data from 1961 to 1990. Furthermore, the increasing demands for water from the São Francisco River could become greater than available streamflow by the 2030s. Additionally, one of the three climate models indicated that the São Francisco and Parnaiba Rivers’ streamflow and hydroelectric production could potentially cease in the second half of the 21st century. Despite some inconsistencies between the long term projections from the 3 different climate models, the results of this research are important in the context of regional climate change, agricultural and energy resource planning.

Comparison of Ensembles Projections of Rainfall from Four Bias Correction Methods over Nigeria

This study compares multi model ensemble (MME) projections of rainfall using general quantile mapping, gamma quantile mapping, Power Transformation and Linear Scaling bias correction (BC) methods for representative concentration pathways (RCPs) 4.5 and 8.5 of the Coupled Model Intercomparison Project phase 5 (CMIP5) global climate models (GCMs). Using the Global Precipitation Climatology Centre historical period (1961–2005) rainfall data as the reference, projection was conducted over 323 grid points of Nigeria for the periods 2010–2039, 2040–2069 and 2070–2099. The performances of the different BC methods in removing biases from the GCMs were assessed using different statistical indices. The computation of the MME of the projected rainfall was conducted by aggregation of 20 GCMs using random forest regression method. The percentage differences in the future rainfall relative to the historical period were estimated for all BC methods. Spatial projection of the percentage changes in rainfall for Linear scaling, which was the best performing BC method, showed increases in rainfall of 5.5–6.9% under RCPs 4.5 and 8.5, respectively, while the decrease range was −3.2–−4.2% respectively during the wet season. The range of annual increases in precipitation was 5.7–7.3% for RCP 4.5 and 8.5, respectively, while the decrease range was −1.0–−4.3%. This study also revealed monthly rainfall within the country will decrease during the wet season between June and September, which is a significant period where most crops need the water for growth. Findings from this study can be of importance to policy makers in the management of changes in hydrological processes due to climate change and management of related disasters such as floods and droughts.

Modeling water resources under competing demands for sustainable development: A case study of Kaligandaki Gorge Hydropower Project in Nepal

The challenges posed by climate change require that the quantity and quality of water resources in Nepal be managed with sustainable development practices. The communities around the Kaligandaki Gorge Hydropower Project in the Myagdi District of Nepal depend on river flow for most of their rural and agricultural needs. Without a sustainable development plan, the growing population of the region, confined in an area with declining water resources, will face serious challenges to economic growth. Meteorological data show increasing annual average rainfall at a slight rate of about 0.284 mm/year, with erratic annual percentage change in rainfall in the area. The mean and minimum temperatures show decreasing trends at the rates of 0.05°C and 0.14°C per year, respectively. An assessment of the impacts on water availability for domestic and irrigation usage in the face of competing demands caused by the hydropower development project in the Kaligandaki Gorge was undertaken. The water demand and supply modeling were conducted using the water evaluation and planning (WEAP) model, based on discharge data from the Kaligandaki River, which were obtained from the Department of Hydrology and Meteorology, Nepal. The available data from 2001 to 2003 were used to estimate the model parameters while the stability of these parameters was tested with a validation period from 2004 to 2007. The performance of the model was assessed through statistical measures of calibration with the root mean square error and coefficient of determination, whose values were 0.046% and 0.79, respectively. Two scenarios were created in addition to the base case scenario: the discharge decrement scenario and new irrigation technology scenario. Analysis showed that a prioritization of demands will be necessary in the area in the near future for the purpose of sustainability of water resources, due to climate change impacts.

Simulated sensitivity of African terrestrial ecosystem photosynthesis to rainfall frequency, intensity, and rainy season length

There is growing evidence of ongoing changes in the statistics of intra-seasonal rainfall variability over large parts of the world. Changes in annual total rainfall may arise from shifts, either singly or in a combination, of distinctive intra-seasonal characteristics –i.e. rainfall frequency, rainfall intensity, and rainfall seasonality. Understanding how various ecosystems respond to the changes in intra-seasonal rainfall characteristics is critical for predictions of future biome shifts and ecosystem services under climate change, especially for arid and semi-arid ecosystems. Here, we use an advanced dynamic vegetation model (SEIB-DGVM) coupled with a stochastic rainfall/weather simulator to answer the following question: how does the productivity of ecosystems respond to a given percentage change in the total seasonal rainfall that is realized by varying only one of the three rainfall characteristics (rainfall frequency, intensity, and rainy season length)? We conducted ensemble simulations for continental Africa for a realistic range of changes (−20% ~ +20%) in total rainfall amount. We find that the simulated ecosystem productivity (measured by gross primary production, GPP) shows distinctive responses to the intra-seasonal rainfall characteristics. Specifically, increase in rainfall frequency can lead to 28% more GPP increase than the same percentage increase in rainfall intensity; in tropical woodlands, GPP sensitivity to changes in rainy season length is ~4 times larger than to the same percentage changes in rainfall frequency or intensity. In contrast, shifts in the simulated biome distribution are much less sensitive to intra-seasonal rainfall characteristics than they are to total rainfall amount. Our results reveal three major distinctive productivity responses to seasonal rainfall variability—‘chronic water stress’, ‘acute water stress’ and ‘minimum water stress’ - which are respectively associated with three broad spatial patterns of African ecosystem physiognomy, i.e. savannas, woodlands, and tropical forests.

Climate change impacts on phenology and yields of five broadacre crops at four climatologically distinct locations in Australia

Shifts in rainfall and rising temperatures due to climate change pose a formidable challenge to the sustainability of broadacre crop yields in Western and South-Eastern Australia. Output from18 Global Climate Models (GCMs) for the Special Report on Emission Scenarios (SRES) A2 scenario was statistically downscaled to four contrasting locations. For the first time in these regions, bias corrected statistically downscaled climate data were employed to drive the Agricultural Production Systems Simulator (APSIM) crop model that integrates the effects of soil, crop phenotype, and management options for a quantitative comparison of crop yields and phenology under an historical and a plausible projected climate. The dynamic APSIM simulation model explore the implications of climate change across multiple locations and multiple time periods (1961–2010, 2030, 2060 and 2090) for multiple key crops (wheat, barley, lupin, canola, field pea) grown in three different types of soil. On average, the ensemble of downscaled GCM projections show a decrease in rainfall in the future at the four locations considered, with increased variability at two locations. At all locations and for five crops, future changes in both crop biomass and grain yield are strongly associated with changes in rainfall (P = 0.05 to P = 0.001). The overall rainfall amount is critical in determining yields but, equally, higher future temperatures can contribute to reducing crop productivity primarily due to advanced crop phenology. For example, for wheat cropping at Hamilton (a higher rainfall site), there is a significant advancement in median flowering date for 2030, 2060, and 2090 of 10, 18, and 29 days respectively with a significant 0.50% grain yield changes for each percentage change in rainfall compared to significant 0.90% grain yield changes in Cunderdin (a lower rainfall site). At all sites except Hamilton, the change in crop grain yield is significantly correlated (P = 0.001) with the percentage change in the future rainfall and the impact increased progressively from higher rainfall to lower rainfall sites. However, the magnitude of the change in crop phenology and yield were not significantly different between soil types. These results help to define regions of concern and their relative importance in the coming years. In this future climate the negative consequences for crop yields and advancement of phenology relative to baseline are not uniform across crops and locations. Of the crops studied – wheat, barley, lupin, canola and field pea – field pea is the most sensitive to the projected future climate changes, and the ensemble median changes in field pea yield range from a decrease of 12% to a decrease of 45%, depending on location. These results highlight the importance of research and policy to support strategies for adapting to climate change, such as advances in agronomy, soil moisture conservation, seasonal climate forecasting and breeding new crop varieties.

Economic growth and ethnic violence: An empirical investigation of Hindu–Muslim riots in India

Most studies of Hindu–Muslim riots in India have tended to emphasize the effects of social, cultural, or political factors on the occurrence of ethnic violence. In this article, the authors focus on the relationship between economic conditions and riots. Specifically, this article examines the effect of economic growth on the outbreak of Hindu–Muslim riots in 15 Indian states between 1982 and 1995. Controlling for other factors, the authors find that just a 1% increase in the growth rate decreases the expected number of riots by over 5%. While short-term changes in growth influence the occurrence of riots, this study finds no evidence of a relationship between the levels of wealth in a state and the incidence of ethnic riots. Moreover, by including state fixed effects, the authors determine that the negative relationship found between economic growth and riots is driven primarily by the relationship between growth and riots within a state over time rather than across states. These results are robust to controlling for a number of other factors such as economic inequality, demographic variables, political competition, temporal lags, spillover effects from adjacent states, and year effects. Finally, to address potential concerns that economic growth could be a consequence rather than a cause of violence or that other unobserved factors could confound the relationship between economic growth and the occurrence of Hindu–Muslim riots, the authors also employ instrumental variables (IV) estimation, using percentage change in rainfall as an instrument for growth. The results with IV estimation are similar to the results with non-IV estimation in terms of sign and significance, indicating that the negative effect of economic growth on riots is not due to reverse causality or omitted variables bias.

Climate change impact on water and salt balances: an assessment of the impact of climate change on catchment salt and water balances in the Murray-Darling Basin, Australia

Climate change has potentially significant implications for hydrology and the quantity and quality of water resources. This study investigated the impacts of climate change and revegetation on water and salt balance, and stream salt concentration for catchments within the Murray-Darling Basin, Australia. The Biophysical Capacity to Change model was used with climate change scenarios obtained using the CSIRO DARLAM 125 (125 km resolution) and Cubic Conformal (50 km resolution) regional climate models. These models predicted up to 25% reduction in mean annual rainfall and a similar magnitude of increase in potential evapotranspiration by 2070. Relatively modest changes in rainfall and temperature can lead to significant reductions in mean annual runoff and salt yield and increases in stream salt concentrations within the Basin. The modelled reductions in mean annual runoff were up to 45% in the wetter/cooler southern catchments and up to 64% in the drier/hotter western and northern catchments. The maximum reductions in salt yield were estimated to be up to 34% in the southern catchments and up to 49% in the northern and western catchments. These changes are associated with average catchment rainfall decreases of 13 to 21%. The results suggest that percentage changes in rainfall will be amplified in runoff. This study demonstrates that climate change poses significant challenges to natural resource management in Australia.

Modelling the impacts of climate change on Australian streamflow

AbstractThis paper presents the likely impacts of climate change on runoff, evapotranspiration and soil moisture in the more populated and important agricultural regions of Australia. The impacts are estimated by comparing the water fluxes simulated by a hydrologic model using present climate data and greenhouse‐enhanced climate scenarios predicted by general circulation models. The results indicate that changes in rainfall are amplified in runoff. In wet and temperate catchments the percentage change in runoff is about twice the percentage change in rainfall, whereas in ephemeral catchments with low runoff coefficients the percentage change in runoff can be more than four times the percentage change in rainfall. The modelling study estimates that the annual runoffs in catchments on the northeast coast and east coast of Australia could change by −5 to +15% and ±15% respectively by the year 2030. The annual runoff in southeast Australia could decrease by up to 20%, and in Tasmania a ±10% change in runoff by 2030 is possible. The model simulates a decrease in the annual runoff in catchments in the South Australian Gulf of up to 25% by 2030, and a change of −25% to +10% in the runoff on the southwest coast of Australia. Although there are large uncertainties in these estimates, the results show the potential for climate change to bring about runoff modifications that may require a significant planning response. Copyright © 2002 John Wiley & Sons, Ltd.

A six-year study of sapling and large-tree growth and mortality responses to natural and induced variability in precipitation and throughfall.

Global climatic change may cause changes in regional precipitation that have important implications for forest growth in the southern United States. In 1993, a stand-level experiment was initiated on Walker Branch Watershed, Tennessee, to study the sensitivity of forest saplings and large trees to changes in soil water content. Soil water content was manipulated by gravity-driven transfer of precipitation throughfall from a dry treatment plot (-33%) to a wet treatment plot (+33%). A control plot was included. Each plot was 6400 m2. Measurements of stem diameter and observations of mortality were made on large trees and saplings of Acer rubrum L., Cornus florida L., Liriodendron tulipifera L., Nyssa sylvatica Marsh, Quercus alba L. and Quercus prinus L. every 2 weeks during six growing seasons. Saplings of C. florida and A. rubrum grew faster and mortality was less on the wet plot compared with the dry and control plots, through 6 years of soil water manipulation. Conversely, diameter growth of large trees was unaffected by the treatments. However, tree diameter growth averaged across treatments was affected by year-to- year changes in soil water status. Growth in wet years was as much as 2-3 times greater than in dry years. Relationships between tree growth, phenology and soil water potential were consistent among species and quantitative expressions were developed for application in models. These field growth data indicate that differences in seasonal patterns of rainfall within and between years have greater impacts on growth than percentage changes in rainfall applied to all rainfall events.

Simulation of the impacts of climate change on runoff and soil moisture in Australian catchments

The impacts of climate change on runoff and soil moisture in 28 Australian catchments are simulated using a hydrologic daily rainfall-runoff model. Two methods are used to provide the climate change scenarios. First, a range of arbitrary changes in temperature and precipitation are applied to the calibrated rainfall-runoff model to study the sensitivity of runoff and soil moisture to potential changes in the climate. Second, results from five global climate model (GCM) enhanced greenhouse experiments are analysed to provide regional climate change scenarios to estimate the range of plausible changes in runoff and soil moisture by the years 2030 and 2070. The sensitivity analyses indicate that changes in rainfall are always amplified in runoff with the amplification factor for runoff being higher in drier catchments. The change in rainfall has little effect on the soil moisture in wet catchments but in drier catchments, the percentage change in soil moisture levels can be greater than the percentage change in rainfall. Compared to precipitation, temperature increases alone have negligible impacts on the runoff and soil moisture. The simulations using the GCM scenarios indicate increases in annual runoff of up to 25% by the year 2030 in the wet tropical catchments near the north-east coast of Australia. The GCMs do not agree in the direction of rainfall change in south-east Australia, and the simulations show runoff changes of up to ±20% by 2030. For Tasmanian catchments, up to 10% increase in runoff is simulated whereas for catchments in the South Australian Gulf, up to 35% decrease in annual runoff is simulated for 2030. Near the western coast of Australia, the simulations show runoff changes of up to ±50%. These results show the potential for climate change to bring about runoff modifications that may require a significant planning response. They are also indicative of the fact that hydrological impacts affecting water supply and flood studies may be important in considering the cost and benefits of potential climate change.