scholarly journals Analysis of the combined and single effects of LULC and climate change on the streamflow of the Upper Blue Nile River Basin (UBNRB): Using statistical trend tests, remote sensing landcover maps and the SWAT model

2017 ◽  
Author(s):  
Dagnenet F. Mekonnen ◽  
Zheng Duan ◽  
Tom Rientjes ◽  
Markus Disse
Keyword(s):  
Climate Change ◽  
Change Detection ◽  
Swat Model ◽  
Extreme Rainfall ◽  
Base Flow ◽  
Annual Rainfall ◽  
Cultivated Land ◽  
Lulc Change ◽  
Extreme Rainfall Events ◽  
Run Off

Abstract. Understanding the response of land use/land cover (LULC) and climate change has become a priority issue for water management and water resource utilization of the Nile basin. This study assesses the long-term trends of rainfall and streamflow to analyse the response of LULC and climate changes on the hydrology of the UBNRB. The Mann–Kendal (MK) trend tests showed no statistically significant changes in daily, monthly and annual rainfall. Tests for mean annual and seasonal streamflow showed a statistically significant and increasing trend. Landsat satellite images for 1973, 1985, 1995 and 2010 were used for LULC change detection. The LULC change detection findings indicate the conversion of forest land to cultivated land during the period 1973–2010. Natural forest decreased from 17.4 % to 14.4 %, 12.2 % and 15.6 % while cultivated land increased from 62.9 % to 65.6 %, 67.5 % and 63.9 % from 1973 to 1985, 1995 and 2010 respectively. The hydrological SWAT model result showed that mean annual streamflow increased by 15.6 % between the 1970s and the 2000s due to the combined effect of LULC and climate change. The single effect of LULC change on streamflow analysis suggested that LULC change significantly affects surface run-off and base flow. This could be attributed to the 5.1 % reduction in forest coverage and 4.6 % increase in cultivated land. Effects of climate change revealed that increased rainfall intensity and number of extreme rainfall events from 1971 to 2010 have greatly affected the surface run-off and base flow of UBNRB.

scholarly journals Spatio-temporal Variability and Trends of Mean and Extreme Rainfall Events in the Sudano-sahelian Region of Cameroon

2021 ◽  
Author(s):  
Ibrahim NJOUENWET ◽  
Lucie A. Djiotang Tchotchou ◽  
Brian Odhiambo Ayugi ◽  
Guy Merlin Guenang ◽  
Derbetini A. Vondou ◽  
...  
Keyword(s):  
Climate Change ◽  
Extreme Rainfall ◽  
Temporal Variations ◽  
Annual Rainfall ◽  
Drought Risk ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Precipitation Concentration ◽  
Spatio Temporal ◽  
The Impact

Abstract The Sudano-Sahelian region of Cameroon is mainly drained by the Benue, Chari and Logone rivers, which are very useful for water resources, especially for irrigation, hydropower generation, and navigation. Long-term changes in mean and extreme rainfall events in the region may be of crucial importance in understanding the impact of climate change. Daily and monthly rainfall data from twenty-five synoptic stations in the study area from 1980 to 2019 and extreme indices from the Expert Team on Climate Change Detection and Indices (ETCCDI) measurements were estimated using the non-parametric Modified Mann-Kendall test and the Sen slope estimator. The precipitation concentration index (PCI), the precipitation concentration degree (PCD), and the precipitation concentration period (PCP) were used to explore the spatio-temporal variations in the characteristics of rainfall concentrations. An increase in extreme rainfall events was observed, leading to an upward trend in mean annual. Trends in consecutive dry days (CDD) are significantly increasing in most parts of the study area. This could mean that the prevalence of drought risk is higher in the study area. Overall, the increase in annual rainfall could benefit the hydro-power sector, agricultural irrigation, the availability of potable water sources, and food security.

Changes in grassland ecosystem function due to extreme rainfall events: implications for responses to climate change

2008 ◽  
Vol 14 (7) ◽  
pp. 1600-1608 ◽  
Author(s):  
PHILIP A. FAY ◽  
DAWN M. KAUFMAN ◽  
JESSE B. NIPPERT ◽  
JONATHAN D. CARLISLE ◽  
CHRISTOPHER W. HARPER
Keyword(s):  
Climate Change ◽  
Ecosystem Function ◽  
Extreme Rainfall ◽  
Grassland Ecosystem ◽  
Extreme Rainfall Events ◽  
Rainfall Events

scholarly journals Are Soybean Yields Getting a Free Ride From Climate Change? Evidence From Argentine Time Series

2018 ◽  
Author(s):  
Hildegart Ahumada ◽  
Magdalena Cornejo
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Extreme Rainfall ◽  
Co2 Concentration ◽  
Interesting Case ◽  
Extreme Rainfall Events ◽  
Beneficial Effects ◽  
Positive Effects ◽  
Long Run ◽  
Equilibrium Correction

Soybean yields are often indicated as an interesting case of climate change mitigation due to the beneficial effects of CO2 fertilization. In this paper we econometrically study this effect using a time series model of yields in a multivariate framework for a main producer and exporter of this commodity, Argentina. We have to deal with the upward behavior of soybean yields trying to identify which variables are the long-run determinants responsible of its observed trend. With this aim we adopt a partial system approach to estimate subsets of long-run relationships due to climate, technological and economic factors. Using an automatic selection algorithm we evaluate encompassing of the different obtained equilibrium correction models. We found that only technological innovations due to new crop practices and the use of modified seeds explain soybean yield in the long run. Regarding short run determinants we found positive effects associated with the use of standard fertilizers and also from changes in atmospheric CO2 concentration which would suggest a mitigation effect from global warming. However, we also found negative climate effects from periods of droughts associated with La Niña episodes, high temperatures and extreme rainfall events during the growing season of the plant.

Extreme Rainfall Events in the Macro-Metropolis of São Paulo: trends and connection with climate oscillations

2021 ◽  
Author(s):  
Carolyne B. Machado ◽  
Thamiris L. O. B. Campos ◽  
Sameh A. Abou Rafee ◽  
Jorge A. Martins ◽  
Alice M. Grimm ◽  
...  
Keyword(s):  
Urban Areas ◽  
Extreme Rainfall ◽  
Kendall Test ◽  
Rain Gauge ◽  
Sao Paulo ◽  
Annual Rainfall ◽  
São Paulo ◽  
Wet Season ◽  
Extreme Rainfall Events ◽  
Climatic Indices

AbstractIn the present work, the trend of extreme rainfall indices in the Macro-Metropolis of São Paulo (MMSP) was analyzed and correlated with largescale climatic oscillations. A cluster analysis divided a set of rain gauge stations into three homogeneous regions within MMSP, according to the annual cycle of rainfall. The entire MMSP presented an increase in the total annual rainfall, from 1940 to 2016, of 3 mm per year on average, according to Mann-Kendall test. However, there is evidence that the more urbanized areas have a greater increase in the frequency and magnitude of extreme events, while coastal and mountainous areas, and regions outside large urban areas, have increasing rainfall in a better-distributed way throughout the year. The evolution of extreme rainfall (95th percentile) is significantly correlated with climatic indices. In the center-north part of the MMSP, the combination of Pacific Decadal Oscillation (PDO) and Antarctic Oscillation (AAO) explains 45% of the P95th increase during the wet season. In turn, in southern MMSP, the Temperature of South Atlantic (TSA), the AAO, the El Niño South Oscillation (ENSO) and the Multidecadal Oscillation of the North Atlantic (AMO) better explain the increase in extreme rainfall (R2 = 0.47). However, the same is not observed during the dry season, in which the P95th variation was only negatively correlated with the AMO, undergoing a decrease from the ‘70s until the beginning of this century. The occurrence of rainy anomalous months proved to be more frequent and associated with climatic indices than dry months.

scholarly journals Evaluation of climate change impacts on extreme rainfall events characteristics using a synoptic weather typing-based daily precipitation downscaling model

2017 ◽  
Vol 8 (3) ◽  
pp. 388-411 ◽  
Author(s):  
Hamed Tavakolifar ◽  
Ebrahim Shahghasemi ◽  
Sara Nazif
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Daily Precipitation ◽  
Extreme Event ◽  
Climate Change Impacts ◽  
Extreme Rainfall ◽  
Extreme Rainfall Events ◽  
Study Region ◽  
Rainfall Events ◽  
Synoptic Weather Typing

Climate change has impacted all phenomena in the hydrologic cycle, especially extreme events. General circulation models (GCMs) are used to investigate climate change impacts but because of their low resolution, downscaling methods are developed to provide data with high enough resolution for regional studies from GCM outputs. The performance of rainfall downscaling methods is commonly acceptable in preserving average characteristics, but they do not preserve the extreme event characteristics especially rainfall amount and distribution. In this study, a novel downscaling method called synoptic statistical downscaling model is proposed for daily precipitation downscaling with an emphasis on extreme event characteristics preservation. The proposed model is applied to a region located in central Iran. The results show that the developed model can downscale all percentiles of precipitation events with an acceptable performance and there is no assumption about the similarity of future rainfall data with the historical observations. The outputs of CCSM4 GCM for two representative concentration pathways (RCPs) of RCP4.5 and RCP8.5 are used to investigate the climate change impacts in the study region. The results show 40% and 30% increase in the number of extreme rainfall events under RCP4.5 and RCP8.5, respectively.

scholarly journals Tendências em índices extremos de precipitação em Cabaceiras (PB) para períodos distintos

2020 ◽  
Vol 13 (1) ◽  
pp. 271
Author(s):  
Rafaela Lisboa Costa ◽  
Heliofábio Barros Gomes ◽  
Fabrício Daniel Dos Santos Silva ◽  
Rodrigo Lins Da Rocha Júnior ◽  
Giuliene Carla Dos Santos Silva ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Change Detection ◽  
Annual Rainfall ◽  
Positive Trend ◽  
Total Period ◽  
Significant Positive Trend ◽  
Total Length ◽  
Expert Team ◽  
Climate Change Detection

Este trabalho teve como objetivo aplicar e estudar 11 índices de extremos de precipitação formulados pelo ETCCDI (Expert Team on Climate Change Detection and Indices, www.clivar.org/organization/etccdi), para a cidade de Cabaceiras-PB, utilizando dados diários de precipitação contínuos de 90 anos. Os índices foram calculados para o comprimento total da série, 1928 a 2017, assim como para três segmentos de 30 anos (1928-1957, 1958-1987 e 1988-2017). Os resultados evidenciaram que para muitos índices, tendências opostas e estatisticamente significativas podem ser observadas a depender do subperíodo estudado, assim como haver diferença entre estas tendências e as obtidas ao analisar-se o período total dos dados. Exemplos disso aconteceram para os índices R1mm, R10mm, R20mm, CWD e PRCPTOT.  Trends in extreme precipitation indexes in Cabaceiras (PB) for different periods A B S T R A C TThis work aimed to apply and analyze 11 precipitation extremes indexes formulated by ETCCDI (Expert Team on Climate Change Detection and Indices, www.clivar.org/organization/etccdi), for the city of Cabaceiras, located in the Borborema mesoregion and microregion of Paraíba Oriental Cariri. A municipality in the semiarid region, it has the title of municipality where it rains less in Brazil, with an annual average of just over 300mm. Daily 90-year continuous precipitation data were used for the extreme indices, with the time series analyzed for four distinct periods, the total length of the series, 1928 to 2017, as well as three 30-year segments (1928-1957, 1958- 1987 and 1988-2017). The results showed that for many indices, opposite and significant trends can be observed depending on the sub period studied, as well as differences between these trends and those obtained by analyzing the total data period. The R1, R10 and R20mm indices show significant negative trends in the 1928-1957 sub period, but positive in the following two sub periods, reflecting a significant positive trend in the total period from 1928 to 2017. Other interesting examples are CDD indices for consecutive dry days, and PRCPTOT, for total annual rainfall with rainfall greater than 1mm. The CDD showed significant positive trend only in the 1928-1957 sub period, but non-significant negative trends in the subsequent sub periods, reflecting non-significant negative trends in the total length of the series. The PRCPTOT index shows behavior opposite to the CDD index, with a significant negative trend in the 1928-1957 sub period, positive in 1958-1987 and negative again in 1988-2017, but for the total length of the series the trend is positive and significant. These results show that the analysis of extreme trends is noticeably sensitive to the sample of the analyzed period, and may not reflect the reality of the time series the longer the total length of the time series, and need to be used with caution.Keywords: climate variability, dry and wet periods, semiarid.

scholarly journals Risks of seasonal extreme rainfall events in Bangladesh under 1.5 and 2.0 degrees’ warmer worlds – How anthropogenic aerosols change the story

2018 ◽  
Author(s):  
Ruksana H. Rimi ◽  
Karsten Haustein ◽  
Emily J. Barbour ◽  
Sarah N. Sparrow ◽  
Sihan Li ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Climate Model ◽  
Substantial Reduction ◽  
Extreme Rainfall ◽  
Extreme Weather Events ◽  
Future Climate Change ◽  
Anthropogenic Aerosols ◽  
Extreme Rainfall Events ◽  
Rainfall Events

Abstract. Anthropogenic climate change is likely to increase the frequency of extreme weather events in future. Previous studies have robustly shown how and where climate change has already changed the risks of weather extremes. However, developing countries have been somewhat underrepresented in these studies, despite high vulnerability and limited capacities to adapt. How additional global warming would affect the future risks of extreme rainfall events in Bangladesh needs to be addressed to limit adverse impacts. Our study focuses on understanding and quantifying the relative risks of seasonal extreme rainfall events in Bangladesh under the Paris Agreement temperature goals of 1.5 °C and 2 °C warming above pre-industrial levels. In particular, we investigate the influence of anthropogenic aerosols on these risks given their likely future reduction and resulting amplification of global warming. Using large ensemble regional climate model simulations from weather@home under different forcing scenarios, we compare the risks of rainfall events under pre-industrial (natural), current (actual), 1.5 °C, and 2.0 °C warmer and greenhouse gas only (anthropogenic aerosols removed) conditions. We find that the risk of a 1 in 100 year rainfall event has already increased significantly compared with pre-industrial levels across parts of Bangladesh, with additional increases likely for 1.5 and 2.0 degree warming (of up to 5.5 times higher, with an uncertainty range of 3.5 to 7.8 times). Impacts were observed during both the pre-monsoon and monsoon periods, but were spatially variable across the country in terms of the level of impact. Results also show that reduction in anthropogenic aerosols plays an important role in determining the overall future climate change impacts; by exacerbating the effects of GHG induced global warming and thereby increasing the rainfall intensity. We highlight that the net aerosol effect varies from region to region within Bangladesh, which leads to different outcomes of aerosol reduction on extreme rainfall statistics, and must therefore be considered in future risk assessments. Whilst there is a substantial reduction in the impacts resulting from 1.5 °C compared with 2 °C warming, the difference is spatially and temporally variable, specifically with respect to seasonal extreme rainfall events.

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