scholarly journals Analysis of the Evolution of Drought, Flood, and Drought-Flood Abrupt Alternation Events under Climate Change Using the Daily SWAP Index

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1969
Author(s):  
Ying Zhao ◽  
Zhaohui Weng ◽  
Hua Chen ◽  
Jiawei Yang
Keyword(s):  
Climate Change ◽  
Weighted Average ◽  
Correction Method ◽  
Flood Frequency ◽  
Upward Trend ◽  
Drought And Flood ◽  
Average Precipitation ◽  
The Future ◽  
Spatial Distribution Of Intensity ◽  
Rapid Transformation

With the increase of drought and flood frequency, the drought-flood abrupt alternation events occur frequently. Due to the coexistence and rapid transformation of drought and flood, the drought-flood abrupt alternation events is often more harmful and threatening than the single drought or flood event to the security of the society. This study is to synthetically evaluate the evolving characteristics of drought, flood, and drought-flood abrupt alternation events under climate change, which are identified by using the Standard Weighted Average Precipitation (SWAP) index. The variability of drought, flood, and drought-flood abrupt alternation events in the future is predicted by using GCM projections, whose outputs are corrected by using a daily bias correction method. The results show that: (1) The SWAP index has the capability to judge reliably the onset, duration, and intensity over the study areas, and can be used to monitor drought-flood abrupt alternation events efficiently; (2) In the reference period (1961–2005), for the drought-flood abrupt alternation events, the frequency has a downward trend in the upper reaches and an upward trend in the lower reaches, and the spatial distribution of intensity shows a contrary law to that of frequency; (3) The frequency and intensity of drought-flood abrupt alternation events show an upward trend in the whole basin in the future period (2021–2095), under the RCP4.5 and RCP8.5 scenarios. These results indicate that drought-flood abrupt alternation events can be more frequent, and the intensity will significantly increase in the 21st century, which may likely pose a serious impact on this basin.

scholarly journals Selection of Bias Correction Methods to Assess the Impact of Climate Change on Flood Frequency Curves

Proceedings ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 14 ◽  
Author(s):  
Enrique Soriano ◽  
Luis Mediero ◽  
Carlos Garijo
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Correction Method ◽  
Flood Frequency ◽  
Precipitation Extremes ◽  
Bias Correction Method ◽  
Simulated Precipitation ◽  
The Future ◽  
The Impact ◽  
Frequency Curves

Annual maximum daily rainfalls will change in the future because of climate change, according to climate projections provided by EURO-CORDEX. This study aims at understanding how the expected changes in precipitation extremes will affect the flood behavior in the future. Hydrological modeling is required to characterize the rainfall-runoff process adequately in a changing climate to estimate flood changes. Precipitation and temperature projections given by climate models in the control period usually do not fit the observations in the same period exactly from a statistical point of view. To correct such errors, bias correction methods are used. This paper aims at finding the most adequate bias correction method for both temperature and precipitation projections, minimizing the errors between observed and simulated precipitation and flood frequency curves. Four catchments located in central western Spain have been selected as case studies. The HBV hydrological model has been calibrated, using the observed precipitation, temperature, and streamflow data available at a daily scale. Expected changes in precipitation extremes are usually smoothed by the reduction of soil moisture content due to expected increases in temperatures and decreases in mean annual precipitation. Consequently, rainfall is the most significant input to the model and polynomial quantile mapping is the best bias correction method.

scholarly journals Selection of Bias Correction Methods to Assess the Impact of Climate Change on Flood Frequency Curves

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2266 ◽  
Author(s):  
Enrique Soriano ◽  
Luis Mediero ◽  
Carlos Garijo
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Control Period ◽  
Flood Frequency ◽  
Climate Projections ◽  
The Future ◽  
Flood Quantiles ◽  
The Impact

Climate projections provided by EURO-CORDEX predict changes in annual maximum series of daily rainfall in the future in some areas of Spain because of climate change. Precipitation and temperature projections supplied by climate models do not usually fit exactly the statistical properties of the observed time series in the control period. Bias correction methods are used to reduce such errors. This paper seeks to find the most adequate bias correction techniques for temperature and precipitation projections that minimizes the errors between observations and climate model simulations in the control period. Errors in flood quantiles are considered to identify the best bias correction techniques, as flood quantiles are used for hydraulic infrastructure design and safety assessment. In addition, this study aims to understand how the expected changes in precipitation extremes and temperature will affect the catchment response in flood events in the future. Hydrological modelling is required to characterize rainfall-runoff processes adequately in a changing climate, in order to estimate flood changes expected in the future. Four catchments located in the central-western part of Spain have been selected as case studies. The HBV hydrological model has been calibrated in the four catchments by using the observed precipitation, temperature and streamflow data available on a daily scale. Rainfall has been identified as the most significant input to the model, in terms of its influence on flood response. The quantile mapping polynomial correction has been found to be the best bias correction method for precipitation. A general reduction in flood quantiles is expected in the future, smoothing the increases identified in precipitation quantiles by the reduction of soil moisture content in catchments, due to the expected increase in temperature and decrease in mean annual precipitations.

scholarly journals Climate Change Projections of Dry and Wet Events in Iberia Based on the WASP-Index

Climate ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 94
Author(s):  
Cristina Andrade ◽  
Joana Contente ◽  
João A. Santos
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Standardized Precipitation Index ◽  
Frequency Of Occurrence ◽  
Model Ensemble ◽  
Upward Trend ◽  
Climate Change Projections ◽  
Mean Values ◽  
Representative Concentration Pathways ◽  
The Future

The Weighted Anomaly of Standardized Precipitation Index (WASP-Index) was computed over Iberia for three monthly timescales (3-month, 6-month and 12-month) in 1961–2020, based on an observational gridded precipitation dataset (E-OBS), and between 2021 and 2070, based on bias-corrected precipitation generated by a six-member climate model ensemble from EURO-CORDEX, under two Representative Concentration Pathways (RCPs), RCP4.5 and RCP8.5. The area-mean values revealed an upward trend in the frequency of occurrence of intermediate-to-severe dry events over Iberia, which will be strengthened in the future, particularly for the 12-month WASP (12m-WASP) intermediate dry events under RCP8.5. Besides, the number of 3-month WASP (3m-WASP) intermediate-to-severe wet events is projected to increase (mostly the severest events under RCP4.5) but no evidence was found for an increase in the number of more persistent 12m-WASP wet events under both RCPs. Despite important spatial heterogeneities, an increase/decrease of the intensity, duration and frequency of occurrence of the 12m-WASP intermediate-to-severe dry/wet events was found under both scenarios, mainly in the southernmost regions of Iberia (mainly Comunidad Valenciana, Región de Murcia, Andalucía in Spain, Alentejo, and Algarve in Portugal), thus becoming more exposed to prolonged and severe droughts in the future. This finding corroborates the results of previous studies.

scholarly journals Climate Change Projections of Dry and Wet Events in Iberia Based on the WASP-Index

2021 ◽  
Author(s):  
Cristina Andrade ◽  
Joana Contente ◽  
João Andrade Santos
Keyword(s):  
Climate Change ◽  
Spatial Patterns ◽  
Climate Model ◽  
Frequency Of Occurrence ◽  
Model Ensemble ◽  
Upward Trend ◽  
Climate Change Projections ◽  
Mean Values ◽  
The Future ◽  
Good Agreement

The WASP-Index is computed over Iberia for three monthly timescales in 1961-2020, based on an observational gridded precipitation dataset (E-OBS), and in 2021-2070, based on bias-corrected precipitation generated by a six-member climate model ensemble from EURO-CORDEX, under RCP4.5 and RCP8.5. The WASP performance in identifying extremely dry or wet events, reported by the EM-DAT disaster database, is assessed for 1961–2020. An overall good agreement between the WASP spatial patterns and the EM-DAT records is found. The areolar mean values revealed an upward trend in the frequency of occurrence of intermediate-to-severe dry events over Iberia, which will be strengthened in the future, particularly for the 12m-WASP intermediate dry events under RCP8.5. Besides, the number of 3m-WASP intermediate-to-severe wet events is projected to increase, mostly the severest events under RCP4.5, but no evidence was found for an increase in the number of more persistent (12m-WASP) wet events under both RCPs. Despite important spatial heterogeneities, an increase(decrease) of the intensity, duration, and frequency of occurrence of the 12m-WASP intermediate-to-severe dry(wet) events is found under both scenarios, mainly in the southernmost regions of Iberia, thus becoming more exposed to prolonged and severe droughts in the future, corroborating the results from previous studies.

scholarly journals Climate Change Will Reduce the Carbon Use Efficiency of Terrestrial Ecosystems on the Qinghai-Tibet Plateau: An Analysis Based on Multiple Models

Forests ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 12
Author(s):  
Yue Wang ◽  
Jinming Hu ◽  
Yanzheng Yang ◽  
Ruonan Li ◽  
Changhui Peng ◽  
...  
Keyword(s):  
Climate Change ◽  
Terrestrial Ecosystems ◽  
Tibet Plateau ◽  
Model Intercomparison ◽  
Upward Trend ◽  
The Future ◽  
Long Time ◽  
Intercomparison Project ◽  
Use Efficiency ◽  
Qinghai Tibet Plateau

The carbon use efficiency (CUE) of ecosystems, expressed as the ratio of net primary production (NPP) and gross primary production (GPP), is extremely sensitive to climate change and has a great effect on the carbon cycles of terrestrial ecosystems. Climate change leads to changes in vegetation, resulting in different CUE values, especially on the Qinghai-Tibet Plateau, one of the most climate-sensitive regions in the world. However, the change trend and the intrinsic mechanism of climate effects on CUE in the future climate change scenario are not clear in this region. Based on the scheme of the coupled model intercomparison project (CMIP6), we analyze the simulation results of the five models of the scenario model intercomparison project (ScenarioMIP) under three different typical future climate scenarios, including SSP1-2.6, SSP3-7.0 and SSP5-8.5, on the Qinghai-Tibet Plateau in 2015–2100 with methods of model-averaging to average the long-term forecast of the five several well-known forecast models for three alternative climate scenarios with three radiative forcing levels to discuss the CUE changes and a structural equations modeling (SEM) approach to examine how the trends in GPP, NPP, and CUE related to different climate factors. The results show that (1) GPP and NPP demonstrated an upward trend in a long time series of 86 years, and the upward trend became increasingly substantial with the increase in radiation forcing; (2) the ecosystem CUE of the Qinghai-Tibet Plateau will decrease in the long time series in the future, and it shows a substantial decreasing trend with the increase in radiation forcing; and (3) the dominant climate factor affecting CUE is temperature of the factors included in these models, which affects CUE mainly through GPP and NPP to produce indirect effects. Temperature has a higher comprehensive effect on CUE than precipitation and CO2, which are negative effects on CUE on an annual scale. Our finding that the CUE decreases in the future suggests that we must pay more attention to the vegetation and CUE changes, which will produce great effects on the regional carbon dynamics and balance.

Climate change impacts on biomes and aridity in Peru

2020 ◽  
Author(s):  
Jose Augusto Zevallos Ruiz ◽  
Adrian Huerta ◽  
Waldo Lavado ◽  
Evelin Sabino ◽  
Fiorella vega ◽  
...  
Keyword(s):  
Climate Change ◽  
Random Forest ◽  
Confusion Matrix ◽  
Imbalanced Data ◽  
Weighted Average ◽  
Aridity Index ◽  
Climate Change Impacts ◽  
Machine Learning Algorithms ◽  
The Pacific ◽  
The Future

<p>In recent years, there has been an increasing interest in estimate future conditions on biomes and aridity due to climate change. Using a new observed-based gridded dataset and remote sensing products, we evaluate the future features in terms of potential biomes (PB) and aridity index (AI) over Peru. </p><p>Ten PBs were established for the present conditions by grouping the ecosystems maps at the national scale. The map presents biomes within areas from 1.08 to 42.44% of total coverage. In order to handle imbalanced data, we designed a calibration and validation scheme for three machine learning algorithms (Random Forest, SVM, and KNN) as follow: first, we perform a gridded search for the best parameters of each model; second, we tested the robustness of each model with a cross validations, checking their f1 score, the confusion matrix and the weighted average precision-recall; finally, we performed a cost-sensitive learning to make more suitable the learning approach for very imbalanced data. The best model is going to be used to predict future conditions of PB. For AI, we evaluate the present trend and quantified the contributions of climate variables to Ai variations. Also, the relationship between AI and vegetative greening was explored. The future change of AI is seen by its spatial variation (migration) of the dryland subtypes.</p><p>The preliminary results showed that random forest worked best for the PB imbalanced data, having a 0.84 weighted average in precision and recall metric. The model reproduces 9 of the PB with low error 4.5% and overestimates 34.52 % one of them in the Amazon. Furthermore, there is an increasing slight trend (not significant) of AI at the drainage-scale, mainly in the Pacific. We hypothesize that there is a migration of dryland subtypes from dry to wet areas in the present time. </p><p>This research is part of the project “Apoyo a la Gestión del Cambio Climatico 2da. Fase” financed by The Swiss Agency for Development and Cooperation (SDC).</p>

scholarly journals Impact of Bias-Correction Methods in Assessing the Potential Flood Frequency Change in the Bago River

2020 ◽  
Vol 15 (3) ◽  
pp. 288-299
Author(s):  
Ralph Allen E. Acierto ◽  
Akiyuki Kawasaki ◽  
Win Win Zin ◽  
◽  
Keyword(s):  
Climate Change ◽  
Frequency Analysis ◽  
Bias Correction ◽  
Correction Method ◽  
Flood Frequency ◽  
Climate Projections ◽  
Frequency Change ◽  
Annual Maximum ◽  
Quantile Mapping ◽  
Bias Correction Method

The increasing flood risks in the Bago River due to rapid urbanization and climate change have great implications on the local development and quality of life in the basin. Therefore, the current flood hazard and potential future changes in flooding due to climate change must be assessed. This study investigates the potential flood frequency change in the Bago River and its sensitivity to the bias-correction method used in climate projections from the downscaled Global Climate Model (GCM) output. A pseudo-global warming method using MIROC5 RCP 8.5 was employed to produce 12-km 30-y historical and future climate projections. Empirical quantile mapping (EQM), gamma quantile mapping (GQM), and the multiplicative scaling method (SCM) were used for bias-correcting the rainfall input of the water-energy budget distributed hydrological model (WEB-DHM). The impacts of bias-correction methods used in reproducing the annual maximum series in the frequency analysis are sensitive to the trend of potential future changes in flood discharge frequency estimation. All methods exhibited decreases in the flood peak discharge for 50-yr and 100-yr flood predictions, which may primarily be due to the MIROC5 GCM used. However, the variation in the magnitude of the change is wide. This demonstrates the uncertainty of the frequency analysis for flood magnitude due to the employed bias-correction method. This uncertainty has significant implications on risk quantification conducted using downscaled climate projections. The effect of the uncertainty of the bias-correction method on the annual maximum rainfall time series should be communicated properly when conducting risk and hazard assessment studies.

What we can learn from the parallels between the COVID-19 and the future climate change crises

2020 ◽  
Author(s):  
Rubén D. Manzanedo ◽  
Peter Manning
Keyword(s):  
Climate Change ◽  
Global Economy ◽  
Global Climate ◽  
Future Climate Change ◽  
Substantial Portion ◽  
Preventative Measures ◽  
The Future ◽  
Behavioral Norm ◽  
Climate Crisis ◽  
Global Population

The ongoing COVID-19 outbreak pandemic is now a global crisis. It has caused 1.6+ million confirmed cases and 100 000+ deaths at the time of writing and triggered unprecedented preventative measures that have put a substantial portion of the global population under confinement, imposed isolation, and established ‘social distancing’ as a new global behavioral norm. The COVID-19 crisis has affected all aspects of everyday life and work, while also threatening the health of the global economy. This crisis offers also an unprecedented view of what the global climate crisis may look like. In fact, some of the parallels between the COVID-19 crisis and what we expect from the looming global climate emergency are remarkable. Reflecting upon the most challenging aspects of today’s crisis and how they compare with those expected from the climate change emergency may help us better prepare for the future.

Love, Inc.

2019 ◽  
Author(s):  
Laurie Essig
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Structural Changes ◽  
Global Climate ◽  
Dating Apps ◽  
Sense Of Security ◽  
True Love ◽  
The Future ◽  
False Sense ◽  
Global Movements

In Love, Inc., Laurie Essig argues that love is not all we need. As the future became less secure—with global climate change and the transfer of wealth to the few—Americans became more romantic. Romance is not just what lovers do but also what lovers learn through ideology. As an ideology, romance allowed us to privatize our futures, to imagine ourselves as safe and secure tomorrow if only we could find our "one true love" today. But the fairy dust of romance blinded us to what we really need: global movements and structural changes. By traveling through dating apps and spectacular engagements, white weddings and Disney honeymoons, Essig shows us how romance was sold to us and why we bought it. Love, Inc. seduced so many of us into a false sense of security, but it also, paradoxically, gives us hope in hopeless times. This book explores the struggle between our inner cynics and our inner romantic.

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