The Impact of Climate Change on Hydro-meteorological Droughts Using Copula Functions

2021 ◽  
Author(s):  
Zahra Fahimirad ◽  
Nazanin Shahkarami
Keyword(s):  
Climate Change ◽  
Distribution Functions ◽  
Cmip5 Models ◽  
Drought Severity ◽  
Accurate Estimation ◽  
Copula Functions ◽  
Realistic Condition ◽  
The Impact ◽  
Univariate Distribution ◽  
Meteorological Droughts

Abstract Climate change has made many alterations to the Earth's climate, including hydro-climatic extreme events. For investigating the effect of climate change on hydro-meteorological droughts in the Kamal-Saleh dam basin in Markazi province, Iran, a new and comprehensive index was developed for accurate estimation of drought in a more realistic condition, for future climate conditions. This aggregate drought index (ADI) represents the main characteristics of meteorological and hydrological drought. Temperature and precipitation projections for future climates were simulated by five CMIP5 models and downscaled over the study area for the periods of 2050s (2040-2069) and 2080s (2070-2099) relative to the baseline period (1976-2005). By fitting five univariate distribution functions on drought severity and duration, proper marginal distributions were selected. The joint distribution of drought severity and duration was chosen from five types of copula functions. The results revealed that severe droughts are expected to occur frequently in a shorter period in the future.

scholarly journals Variations of Drought Tendency, Frequency, and Characteristics and Their Responses to Climate Change under CMIP5 RCP Scenarios in Huai River Basin, China

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2174 ◽  
Author(s):  
Jingcai Wang ◽  
Hui Lin ◽  
Jinbai Huang ◽  
Chenjuan Jiang ◽  
Yangyang Xie ◽  
...  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Eastern China ◽  
Cmip5 Models ◽  
Drought Severity ◽  
Global Circulation Models ◽  
Huai River Basin ◽  
Huai River ◽  
The Future ◽  
The Impact

Huai River Basin (HRB) is an important food and industrial production area and a frequently drought-affected basin in eastern China. It is necessary to consider the future drought development for reducing the impact of drought disasters. Three global circulation models (GCMs) from Coupled Model Intercomparison Project phase 5 (CMIP5), such as CNRM-CM5 (CNR), HadGEM2-ES (Had) and MIROC5 (MIR), were used to assessment the future drought conditions under two Representative Concentration Pathways (RCPs) scenarios, namely, RCP4.5 and RCP8.5. The standardized precipitation evapotranspiration index (SPEI), statistical method, Mann-Kendall test, and run theory were carried out to study the variations of drought tendency, frequency, and characteristics and their responses to climate change. The research showed that the three CMIP5 models differ in describing the future seasonal and annual variations of precipitation and temperature in the basin and thus lead to the differences in describing drought trends, frequency, and drought characteristics, such as drought severity, drought duration, and drought intensity. However, the drought trend, frequency, and characteristics in the future are more serious than the history. The drought frequency and characteristics tend to be strengthened under the scenario of high concentration of RCP8.5, and the drought trend is larger than that of low concentration of RCP4.5. The lower precipitation and the higher temperature are the main factors affecting the occurrence of drought. All three CMIP5 models show that precipitation would increase in the future, but it could not offset the evapotranspiration loss caused by significant temperature rise. The serious risk of drought in the future is still higher. Considering the uncertainty of climate models for simulation and prediction, attention should be paid to distinguish the effects of different models in the future drought assessment.

Representation of the Angolan low and Southern African Summer Precipitation in the CORDEX and CMIP5 models. 

2021 ◽  
Author(s):  
Sabina Abba-Omar ◽  
Francesca Raffaele ◽  
Erika Coppola ◽  
Daniela Jacob ◽  
Claas Teichmann ◽  
...  
Keyword(s):  
Climate Change ◽  
Regression Analysis ◽  
Southern Africa ◽  
Summer Precipitation ◽  
Precipitation Variability ◽  
Cmip5 Models ◽  
Impact Of Climate Change ◽  
The Future ◽  
Rainfall Patterns ◽  
The Impact

<p>The impact of climate change on precipitation over Southern Africa is of particular interest due to its possible devastating societal impacts. To add to this, simulating precipitation is challenging and models tend to show strong biases over this region, especially during the Austral Summer (DJF) months. One of the reasons for this is the mis-representation of the Angolan Low (AL) and its influence on Southern Africa’s Summer precipitation in the models. Therefore, this study aims to explore and compare different models’ ability to capture the AL and its link to precipitation variability as well as consider the impact climate change may have on this link. We also explore how the interaction between ENSO, another important mode of variability for precipitation, and the Angolan Low, impact precipitation, how the models simulate this and whether this could change in the future under climate change. </p><p>We computed the position and strength of the AL in reanalysis data and compared these results to three different model ensembles with varying resolutions. Namely, the CORDEX-CORE ensemble (CCORE), a new phase of CORDEX simulations with higher resolutions (0.22 degrees), the lower resolution (0.44 degrees) CORDEX-phase 1 ensemble (C44) and the CMIP5 models that drive the two RCM ensembles. We also used Self Organizing Maps to group DJF yearly anomaly patterns and identify which combination of ENSO and AL strength scenarios are responsible for particularly wet or dry conditions. Regression analysis was performed to analyze the relationships between precipitation and the AL and ENSO. This analysis was repeated for near (2041-2060) and far (2080-2099) future climate and compared with the present to understand how the strength of the AL, and its connection to precipitation variability and ENSO, changes in the future. </p><p>We found that, in line with previous studies, models with stronger AL tend to produce more rainfall. CCORE tends to simulate a stronger AL than C44 and therefore, higher precipitation biases. However, the regression analysis shows us that CCORE is able to capture the relationship between precipitation and the AL strength variability as well as ENSO better than the other ensembles. We found that generally dry rainfall patterns over Southern Africa are associated with a weak AL and El Nino event whereas wet rainfall patterns occur during a strong AL and La Nina year. While the models are able to capture this, they also tend to show more neutral ENSO conditions associated with these wet and dry patterns which possibly indicates less of a connection between AL strength and ENSO than seen in the observed results. Analysis of the future results indicates that the AL weakens, this is shown across all the ensembles and could be a contributing factor to some of the drying seen. These results have applications in understanding and improving model representation of precipitation over Southern Africa as well as providing some insight into the impact of climate change on precipitation and some of its associated dynamics over this region.</p>

scholarly journals Hydrological Drought Regimes of the Huai River Basin, China: Probabilistic Behavior, Causes and Implications

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2390 ◽  
Author(s):  
Sun ◽  
Zhang ◽  
Yao ◽  
Wen
Keyword(s):  
River Basin ◽  
Hydrological Drought ◽  
Drought Severity ◽  
Copula Functions ◽  
Drought Duration ◽  
Huai River Basin ◽  
Huai River ◽  
The Impact ◽  
Hydrological Droughts ◽  
The Huai River Basin

: Hydrological droughts were characterized using the run-length theory and the AIC (Akaike information criterion) techniques were accepted to evaluate the modeling performance of nine probability functions. In addition, the copula functions were used to describe joint probability behaviors of drought duration and drought severity for the major tributaries of the Huai River Basin (HRB) which is located in the transitional zone between humid and semi-humid climates. The results indicated that: (1) the frequency of hydrological droughts in the upper HRB is higher than that in the central HRB, while the duration of the hydrological drought is in reverse spatial pattern. The drought frequency across the Shiguan River along the south bank of the HRB is higher than the other two tributaries; (2) generalized Pareto distribution is the appropriate distribution function with the best performance in modelling the drought duration over the HRB; while the Generalized Extreme Value (GEV) distribution can effectively describe the probabilistic properties of the drought severity. Joe copula and Tawn copula functions are the best choices and were used in this study. Given return periods of droughts of <30 years, the droughts in the upper HRB are the longest, and the shortest are in the central HRB; (3) the frequency of droughts along the mainstream of the HRB is higher than tributaries of the HRB. However, concurrence probability of droughts along the mainstream of the HRB is lower than the tributaries of the HRB. The drought resistance capacity of HRB has been significantly improved, effectively reducing the impact of hydrological drought on crops after 2010.

scholarly journals Attribution Analysis of Hydrological Drought Risk Under Climate Change and Human Activities: A Case Study on Kuye River Basin in China

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1958 ◽  
Author(s):  
Zhang ◽  
Wang ◽  
Zhou
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Human Activities ◽  
Large Scale ◽  
Research Area ◽  
Drought Severity ◽  
Drought Risk ◽  
Drought Duration ◽  
Recurrence Period ◽  
The Impact

This study conducted quantitative diagnosis on the impact of climate change and human activities on drought risk. Taking the Kuye river basin (KRB) in China as the research area, we used variation point diagnosis, simulation of precipitation and runoff, drought risk assessment, and attribution quantification. The results show that: (1) the annual runoff sequence of KRB changed significantly after 1979, which was consistent with the introduction of large-scale coal mining; (2) under the same drought recurrence period, the drought duration and severity in the human activity stage were significantly worse than in the natural and simulation stages, indicating that human activities changed the drought risk in this area; and (3) human activities had little impact on drought severity in the short duration and low recurrence period, but had a greater impact in the long duration and high recurrence period. These results provide scientific guidance for the management, prevention, and resistance of drought; and guarantee sustainable economic and social development in the KRB.

Impact of climate change on the future of tourism areas in the Canary Islands

2021 ◽  
Author(s):  
Judit Carrillo ◽  
Albano González ◽  
Juan C. Pérez ◽  
Francisco J. Expósito ◽  
Juan P. Díaz
Keyword(s):  
Climate Change ◽  
Boundary Conditions ◽  
Canary Islands ◽  
Climate Model ◽  
Regional Climate ◽  
Leisure Activities ◽  
Cmip5 Models ◽  
Climate Index ◽  
Impact Of Climate Change ◽  
The Impact

&lt;p&gt;Tourism is an essential sector of the economy of the Canary Islands. Tourism Climate Index (TCI) and Holiday Climate Index (HCI) are good indicators of environmental conditions for leisure activities. Regional climate model (RCM) has been addressed to analyze the impact of climate change on the indices of tourist areas. The initial and boundary conditions for future scenarios are prescribed through three CMIP5 models (GFDL, IPSL and MIROC)&amp;#160; surface and lateral boundary conditions within the Meteorological Research and Forecast (WRF), with a high resolution, 3x3 km. Two time periods (2030 &amp;#8211; 2059, and 2070-2099) and two Representative Concentration Pathways (RCPs 4.5 and 8.5) are considered. Tourism indicators are projected to improve significantly during the winter and shoulder seasons, but will worsen in the summer months, including October, in the southeast, which is where hotels are currently located.&lt;/p&gt;

scholarly journals AGRICULTURAL DROUGHT AND SOIL MOISTURE ANALYSIS USING SATELLITE IMAGE BASED INDICES

2019 ◽  
Vol XLII-3/W6 ◽  
pp. 507-514
Author(s):  
S. Sreekesh ◽  
N. Kaur ◽  
S. R. Sreerama Naik
Keyword(s):  
Soil Moisture ◽  
Satellite Image ◽  
Condition Index ◽  
Agricultural Drought ◽  
Drought Severity ◽  
Severe Drought ◽  
Landsat Images ◽  
Moisture Conditions ◽  
The Impact ◽  
Meteorological Droughts

<p><strong>Abstract.</strong> The deficiency in rainfall leads to meteorological droughts. Its manifestations are visible both in the vegetation cover and soil moisture. The present study assessed the characteristics of agricultural drought following meteorological droughts. The study also assessed the severity of meteorological droughts and their manifestation on the agriculture and soil moisture in a semi-arid area. The study has been carried out for the Malaprabha sub-basin which partly covers three districts of North Interior Karnataka, India. India Meteorological Department’s (IMD) criteria have been used to identify the drought years, and its severity has been assessed through the Standard Precipitation Index (SPI). The IMD’s monthly rainfall data were used to identify the drought years and periods for the region. Among the drought years, the mild, moderate, and severe drought along with deficit and excess rainfall years were considered to assess and characterize the soil moisture conditions and the agricultural drought. The satellite image based indices for these selected years were constructed to determine the soil moisture conditions and the agricultural drought severity. The Temperature-Vegetation Dryness Index (TVDI) was used to determine the soil moisture conditions. The indices employed to determine the agriculture drought are NDVI, Thermal Condition Index (TCI), Vegetation Condition Index (VCI), and Vegetation Health Index (VHI). These satellite-based indices were calculated using the Landsat images of the selected drought and non-drought years. The results showed that the seasonal and annual drought are frequent in the study area. There are spatial and temporal variations in the drought years and their severity. The satellite-based indices clearly indicate the spatial variation in the agriculture droughts and its intensity. It has been found that the impact of drought on agriculture has significantly reduced due to the development of well-irrigation in the sub-basin. VHI is more appropriate in determining the agricultural drought and its characteristics.</p>

AFRICAP - The impact of climate change on agriculture in Tanzania, Malawi, Zambia and South Africa

2020 ◽  
Author(s):  
Sarah Chapman ◽  
Cathryn Birch ◽  
Edward Pope ◽  
Susannah Sallu ◽  
Catherine Bradshaw ◽  
...  
Keyword(s):  
Climate Change ◽  
South Africa ◽  
Sub Saharan Africa ◽  
Cmip5 Models ◽  
Comprehensive Treatment ◽  
Climate Projections ◽  
Suitability Analysis ◽  
Crop Suitability ◽  
Sub Saharan ◽  
The Impact

&lt;p&gt;Sub-Saharan Africa is one of the most food insecure regions in the world and is highly vulnerable to climate change. We use a comprehensive set of bias-corrected global (CMIP5) and regional (CORDEX-Africa) models and a new convection-permitting pan-Africa simulation (and its parameterized counterpart) to examine changes in rainfall and temperature and the impact on agricultural suitability of maize, cassava and soy in sub-Saharan Africa by 2100 (RCP8.5). This is the first time a convection-permitting projection has been used to examine agricultural suitability in Africa. Increasing temperatures and declining rainfall led to large parts of sub-Saharan Africa becoming unsuitable for multiple staple crops, which may necessitate a transition to more heat and drought resistant crops to ensure food and nutrition security. Soy was resilient to temperature increases, however maize and cassava were not, leading to declines in crop suitability. Inclusion of sensitivity to extreme temperatures led to larger declines in maize suitability than when this was excluded. The variation in rainfall projections within the multi-model ensemble was examined in detail for Tanzania, Malawi, Zambia and South Africa. In each country the range of projections included wetting and drying, but the majority of models projected rainfall declines, except in Tanzania, leading to declines in crop suitability. Overall, the CORDEX and CMIP5 models gave similar results for agricultural suitability. Explicit-convection led to more temperature extremes, but had little systematic impact on temperature and rainfall, and the resulting suitability analysis. Global model uncertainty, rather than convection parameterizations, still makes up the largest part of the uncertainty in future climate. Explicit-convection may have more impact if suitability included a more comprehensive treatment of extremes. This work highlights the key uncertainty from global climate projections for crop suitability projections, and the need for improved information on sensitivities of African crops to extremes, in order to give better predictions and make better use of the new generation of explicit-convection models.&lt;/p&gt;

scholarly journals Run Theory and Copula-Based Drought Risk Analysis for Songnen Grassland in Northeastern China

2019 ◽  
Vol 11 (21) ◽  
pp. 6032 ◽  
Author(s):  
Wu ◽  
Zhang ◽  
Bao ◽  
Guo
Keyword(s):  
Risk Analysis ◽  
Goodness Of Fit ◽  
Distribution Functions ◽  
Drought Severity ◽  
Dependence Structure ◽  
Drought Risk ◽  
Drought Event ◽  
Return Periods ◽  
Copula Functions ◽  
Run Theory

Droughts are among the more costly natural hazards, and drought risk analysis has become urgent for the proper planning and management of water resources in grassland ecosystems. We chose Songnen grassland as a case study, used a standardized precipitation evapotranspiration index (SPEI) to model drought characteristics, employed run theory to define the drought event, and chose copula functions to construct the joint distribution for drought variables. We applied two kinds of return periods to conduct a drought risk assessment. After evaluating and comparing several distribution functions, drought severity (DS) was best described by the generalized extreme value (GEV) distribution, whereas drought duration (DD) was best fitted by gamma distribution. The root mean square error (RMSE) and Akaike Information Criterion (AIC) goodness-of-fit measures to evaluate their performance, the best-performing copula is Frank copula to model the joint dependence structure for each drought variables. The results of the secondary return periods indicate that a higher risk of droughts occurs in Keshan county, Longjiang county, Qiqiha’er city, Taonan city, and Baicheng city. Furthermore, a relatively lower risk of drought was found in Bei’an city, Mingquan county, Qinggang county, and qian’an county, and also in the Changling county and Shuangliao city. According to the calculation of the secondary return periods, which considered all possible scenarios in our study, we found that the secondary return period may be the best indicator for evaluating grassland ecosystem drought risk management.

scholarly journals Analysis and Prioritization the Effective Factors on Increasing Farmers Resilience Under Climate Change and Drought

2020 ◽  
Author(s):  
Safieh Javadinejad ◽  
Rebwar Dara ◽  
Forough Jafary
Keyword(s):  
Climate Change ◽  
Agricultural Land ◽  
Statistical Tests ◽  
Cmip5 Models ◽  
Agricultural Insurance ◽  
Statistical Population ◽  
Factors Affecting ◽  
Effective Factors ◽  
Future Time Period ◽  
The Impact

Abstract California is severely exposed to drought and damage due to the climate change and drought belt, which has a major impact on agriculture. So, after the drought crisis, there are various reactions from farmers. The extent of the damage caused by the socioeconomic, environment and the extent of the resistance of farmers to this crisis is manifested in a variety of ways. Recognizing the population’s resilience and the involved human groups is a tool for preventing a catastrophe-based increase in life-threatening areas in high-risk areas. Sometimes the inability to manage this phenomenon (especially under the climate change) leads to farmers’ desertification and agricultural land release, which itself indicates a low level of resilience and resilience to the crisis. The recent drought under the climate change condition in California and the severity of the damage sustained by farmers continue to be vulnerable. The present study seeks to prioritize and prioritize resilience of farmers to the crisis under the climate change. This study simulated drought condition with using PDSI value for current and future time period. In order to calculate PDSI values, the climatic parameters extracted from CMIP5 models and downscaled under the scenario of RCP 8.5. Also in order to understand the resilience of the agriculture activities under the climate change, this study was performed using statistical tests and data from the questionnaire completed in the statistical population of 320 farmers in the Tulare region in California. The findings of the research by t test showed that the average level of effective factors in increasing the resilience of farmers in the region is low. This is particularly significant in relation to the factors affecting government policies and support. So that only the mean of five variables is higher than the numerical desirability of the test and the other 15 variables do not have a suitable status for increasing the resilience of the farmers. Also, the results of the Vikor model showed that most of the impact on their resilience to drought and climate change was the development of agricultural insurance, the second important impact belongs to drought monitoring system, climate change and damage assessment, and variable of attention to knowledge is in third place of the important factor.

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