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1
Wehner, Michael, David R. Easterling, Jay H. Lawrimore, Richard R. Heim, Russell S. Vose, and Benjamin D. Santer. "Projections of Future Drought in the Continental United States and Mexico." Journal of Hydrometeorology 12, no. 6 (2011): 1359–77. http://dx.doi.org/10.1175/2011jhm1351.1.
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Abstract Using the Palmer drought severity index, the ability of 19 state-of-the-art climate models to reproduce observed statistics of drought over North America is examined. It is found that correction of substantial biases in the models’ surface air temperature and precipitation fields is necessary. However, even after a bias correction, there are significant differences in the models’ ability to reproduce observations. Using metrics based on the ability to reproduce observed temporal and spatial patterns of drought, the relationship between model performance in simulating present-day drought characteristics and their differences in projections of future drought changes is investigated. It is found that all models project increases in future drought frequency and severity. However, using the metrics presented here to increase confidence in the multimodel projection is complicated by a correlation between models’ drought metric skill and climate sensitivity. The effect of this sampling error can be removed by changing how the projection is presented, from a projection based on a specific time interval to a projection based on a specified temperature change. This modified class of projections has reduced intermodel uncertainty and could be suitable for a wide range of climate change impacts projections.
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Khan, Muhammad Imran, Xingye Zhu, Xiaoping Jiang, et al. "Projection of Future Drought Characteristics under Multiple Drought Indices." Water 13, no. 9 (2021): 1238. http://dx.doi.org/10.3390/w13091238.
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Drought is a natural phenomenon caused by the variability of climate. This study was conducted in the Songhua River Basin of China. The drought events were estimated by using the Reconnaissance Drought Index (RDI) and Standardized Precipitation Index (SPI) which are based on precipitation (P) and potential evapotranspiration (PET) data. Furthermore, drought characteristics were identified for the assessment of drought trends in the study area. Short term (3 months) and long term (12 months) projected meteorological droughts were identified by using these drought indices. Future climate precipitation and temperature time series data (2021–2099) of various Representative Concentration Pathways (RCPs) were estimated by using outputs of the Global Circulation Model downscaled with a statistical methodology. The results showed that RCP 4.5 have a greater number of moderate drought events as compared to RCP 2.6 and RCP 8.5. Moreover, it was also noted that RCP 8.5 (40 events) and RCP 4.5 (38 events) showed a higher number of severe droughts on 12-month drought analysis in the study area. A severe drought conditions projected between 2073 and 2076 with drought severity (DS-1.66) and drought intensity (DI-0.42) while extreme drying trends were projected between 2097 and 2099 with drought severity (DS-1.85) and drought intensity (DI-0.62). It was also observed that Precipitation Decile predicted a greater number of years under deficit conditions under RCP 2.6. Overall results revealed that more severe droughts are expected to occur during the late phase (2050–2099) by using RDI and SPI. A comparative analysis of 3- and 12-month drying trends showed that RDI is prevailing during the 12-month drought analysis while almost both drought indices (RDI and SPI) indicated same behavior of drought identification at 3-month drought analysis between 2021 and 2099 in the research area. The results of study will help to evaluate the risk of future drought in the study area and be beneficial for the researcher to make an appropriate mitigation strategy.
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Rhee, Jinyoung, and Jaepil Cho. "Future Changes in Drought Characteristics: Regional Analysis for South Korea under CMIP5 Projections." Journal of Hydrometeorology 17, no. 1 (2015): 437–51. http://dx.doi.org/10.1175/jhm-d-15-0027.1.
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Abstract The future changes in drought characteristics were examined on a regional scale for South Korea, in northeastern Asia, using 17 bias-corrected projections from phase 5 of the Coupled Model Intercomparison Project (CMIP5) of representative concentration pathway (RCP) scenarios 4.5 and 8.5. The frequency of severe or extreme drought, based on the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI), with time scales of 1, 3, and 12 months (i.e., SPI1, SPI3, SPI12, SPEI1, SPEI3, and SPEI12), was considered, as well as the average duration based on SPEI1. A multimodel ensemble (MME) was produced using selected models, and future changes were investigated in terms of both drought frequency and the average duration for the entire area and four river basins. The changes in drought frequency largely depend on the selection of a drought index, rather than climate projection scenarios. SPEI3 mostly projected future increases in drought frequency, while SPI3 showed varied projections. SPI12 projected decreases in drought frequency for both scenarios in the study area, while differences between river basins were observed for SPEI12. Increases in the average duration of droughts were projected based on SPEI1, indicating an increase in persistent short-term droughts in the future. The results emphasize the importance of regional- and subregional-scale analysis in northeastern Asia. The findings of the study provide valuable information that can be used for drought-related decision-making, which could not be obtained from studies on a global spatial scale.
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Wambua, Raphael Muli. "Development of a Non-Linear Integrated Drought Index (NDI) for Managing Drought and Water Resources Forecasting in the Upper Tana River Basin-Kenya." International Journal of Environmental Sustainability and Green Technologies 11, no. 1 (2020): 15–33. http://dx.doi.org/10.4018/ijesgt.2020010102.
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This article uses the non-linear integrated drought index (NDI) for managing drought and water resources forecasting in a tropical river basin. The NDI was formulated using principal component analysis (PCA). The NDI used hydro-meteorological data and forecasted using recursive multi-step neural networks. In this article, drought forecasting and projection is adopted for planning ahead for mitigation and for the adaptation of adverse effects of droughts and food insecurity in the river basin. Results that forecasting ability of NDI model using ANNs decreased with increase in lead time. The formulated NDI as a tool for projecting into the future.
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Burke, Eleanor J., and Simon J. Brown. "Evaluating Uncertainties in the Projection of Future Drought." Journal of Hydrometeorology 9, no. 2 (2008): 292–99. http://dx.doi.org/10.1175/2007jhm929.1.
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Abstract The uncertainty in the projection of future drought occurrence was explored for four different drought indices using two model ensembles. The first ensemble expresses uncertainty in the parameter space of the third Hadley Centre climate model, and the second is a multimodel ensemble that additionally expresses structural uncertainty in the climate modeling process. The standardized precipitation index (SPI), the precipitation and potential evaporation anomaly (PPEA), the Palmer drought severity index (PDSI), and the soil moisture anomaly (SMA) were derived for both a single CO2 (1×CO2) and a double CO2 (2×CO2) climate. The change in moderate drought, defined by the 20th percentile of the relevant 1×CO2 distribution, was calculated. SPI, based solely on precipitation, shows little change in the proportion of the land surface in drought. All the other indices, which include a measure of the atmospheric demand for moisture, show a significant increase with an additional 5%–45% of the land surface in drought. There are large uncertainties in regional changes in drought. Regions where the precipitation decreases show a reproducible increase in drought across ensemble members and indices. In other regions the sign and magnitude of the change in drought is dependent on index definition and ensemble member, suggesting that the selection of appropriate drought indices is important for impact studies.
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Anagnostopoulou, C. "FUTURE DROUGHT PROJECTION FOR THE GREEK REGION." Bulletin of the Geological Society of Greece 50, no. 2 (2017): 1038. http://dx.doi.org/10.12681/bgsg.11808.
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Drought is one of the most important factors of change. The epi-drops drought in one area are complex because they simultaneously affect many areas, such as climate, agriculture, the economy and in general the structure of society. This study deals only with the meteorological drought, particularly considering the phenomenon of drought through the index Standardized Precipitation Index (SPI). The Greece is characterized by frequent drought episodes that often exceed 10 consecutive days of drought (dry spells). Also, in recent years the area probably climate models have been used in a wide study of the impact of climate change in different regions on the planet. Rainfall data from five regional climate models (RCMs) have been used to calculate the SPI index in the Greek area, the reporting period and two subsequent periods by the end of the 21st century. All models show a decreasing trend of the SPI median during the period studied. For the first future period 2021-2050, there is a clear signal for a dry decade towards the end of the period that is most apparent in southern and island regions. On the other hand, in the second future period 2071-2100, there is an increasing trend resulting to normal or wetter years.
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El Qorchi, Fadoua, Mohammed Yacoubi Khebiza, Onyango Augustine Omondi, Ahmed Karmaoui, and Siham Acharki. "Projection analysis of future drought characteristics in Upper Draa Catchment (Southern Morocco)." E3S Web of Conferences 489 (2024): 04006. http://dx.doi.org/10.1051/e3sconf/202448904006.
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The consequences of global warming will aggravate the impacts of droughts. Future drought patterns are important for planning and policy formulation to mitigate the adverse effect of climate change. Consequently, this study aims at examining the projected the drought characteristics in seven meteorological stations in the Upper Draa Catchment (UDC) during the period from 1980 to 2016 using standardized precipitation index. The future climate scenarios were predicted by the model CNRM-ALADIN63 for three periods (2025–2049, 2050–2074, and 2075–2099). The changes were examined based on two Representative Concentration Pathways scenarios, namely: RCP4.5and RCP8.5. The findings indicated that increasingly extreme droughts are anticipated to occur during (2050-2074) followed by (2025-2049) than (2075-2099) under both scenarios. The results reveal a contrast in drought event frequency between historical data and projections with a noticeable variation of patterns of droughts characteristics across stations and time periods. This accentuates how urgent it is for the Upper Draa Catchment to implement proactive water resource management and adaptive strategies.
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Pratiwi, Nila Ardhyarini H., Mahawan Karuniasa, and Djoko Santoso Abi Suroso. "Exploring Historical and Projection of Drought Periods in Cirebon Regency, Indonesia." E3S Web of Conferences 68 (2018): 02007. http://dx.doi.org/10.1051/e3sconf/20186802007.
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Climate hazards that affect drought could have an impact on agricultural production. Cirebon Regency as one of West Java's food supply areahas experienced hydrological drought because ofclimate variability. Hence, there were many rice fieldswhich lack of water sources for irrigation and resulted in crop failure. Accordingly, this study aims to explore the historical and projection of drought periods as well as the severity of droughts in Cirebon Regency, Indonesia. Interpretation of weather and climate data and Standardized Precipitation Index (SPI) were employed for methods of this studyby using rainfall data only. Based on baseline data (1986-2017) from Jatiwangi Meteorological Stationand Global Circulation Model (GCM) projection simulation (2020-2045) under the Representative Concentration Pathways (RCP) 4.5 scenario, the SPI analysis results show that the drought periodsare predicted to shift in the future with increasing drought severity. This study concludes that climate variability that affects future dry rainfall will still happen in uncertain month periods.Therefore, climatic information is needed in the vulnerable area to reduce the potential impactsthat will occur in the future.
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Chamorro, Alejandro, Tobias Houska, Shailesh Singh, and Lutz Breuer. "Projection of Droughts as Multivariate Phenomenon in the Rhine River." Water 12, no. 8 (2020): 2288. http://dx.doi.org/10.3390/w12082288.
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Drought is a complex phenomenon whose characterization is best achieved from a multivariate perspective. It is well known that it can generate adverse consequences in society. In this regard, drought duration, severity, and their interrelationship play a critical role. In a climate change scenario, drought characterization and the assessment of the changes in its pattern are essential for a proper quantification of water availability and managing strategies. The purpose of this study is to characterize hydrological droughts in the Rhine River in a multivariate perspective for the historical period and estimate the expected multivariate drought patterns for the next decades. Further, a comparison of bivariate drought patterns between historical and future projections is performed for different return periods. This will, first, indicate if changes can be expected and, second, what the magnitudes of these possible changes could be. Finally, the underlying uncertainty due to climate projections is estimated. Four Representative Concentration Pathways (RCP) are used along with five General Circulation Models (GCM). The HBV hydrological model is used to simulate discharge in both periods. Characterization of droughts is accomplished by the Standardized Runoff Index and the interdependence between drought severity and duration is modelled by a two-dimensional copula. Projections from different climate models show important differences in the estimation of the number of drought events for different return periods. This study reveals that duration and severity present a clear interrelationship, suggesting strongly the appropriateness of a bivariate model. Further, projections show that the bivariate interdependencies between drought duration and severity show clearly differences depending on GCMs and RCPs. Apart from the influence of GCMs and RCMs, it is found that return periods also play an important role in these relationships and uncertainties. Finally, important changes in the bivariate drought patterns between the historical period and future projections are estimated constituting important information for water management purposes.
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Javadinejad, Safieh, Rebwar Dara, and Forough Jafary. "Evaluation of hydro-meteorological drought indices for characterizing historical and future droughts and their impact on groundwater." Resources Environment and Information Engineering 2, no. 1 (2020): 71–83. http://dx.doi.org/10.25082/reie.2020.01.003.
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The effect of meteorological and hydrological droughts is very important in arid and semi-arid regions. Analyzing these effects on groundwater supplies plays an important role for water management in those regions. This paper aims to characterize droughts in the Isfahan-Borkhar basin, an arid area of Iran. The observed hydro-climatic data (for the period of 1971-2005) were used for hydro-meteorological projections (for the period of 2006-2040). Meteorological and surface hydrological drought evaluated by Standardized Precipitation Index (SPI), Standardized Runoff Index (SRI), and the effect of hydro-meteorological droughts on groundwater was investigated by Groundwater Resources Index (GRI). Results showed that dry and wet conditions would occur in the region in the initial and subsequent decades, based on the three indices. There was a significant association between SPI, SRI, and GRI at the time scale of 12 months. The SPI estimated using only meteorological variables alone and it is useful for estimating meteorological drought forecasts. However, SRI and GRI can represent hydrological drought that computed using catchment discharge, soil moisture and groundwater level. Results showed a considerable alteration in time of drought outlines across the area and association between the variables of predicted precipitation, temperature and the kind of indices. The projection of all three drought indices indicated drier conditions in the future period (2006-2042). The results provide reasonable management strategy for management of water resources in arid coastal plains.
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Soni, Anil Kumar, Jayant Nath Tripathi, Mukul Tewari, M. Sateesh, and Tarkeshwar Singh. "Future Projection of Drought Risk over Indian Meteorological Subdivisions Using Bias-Corrected CMIP6 Scenarios." Atmosphere 14, no. 4 (2023): 725. http://dx.doi.org/10.3390/atmos14040725.
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This study presents a comprehensive analysis of extreme events, especially drought and wet events, spanning over the past years, evaluating their trends over time. An investigation of future projections under various scenarios such as SSP-126, SS-245, and SSP-585 for the near (2023–2048), mid (2049–2074), and far future (2075–2100) using the bias-corrected Coupled Model Intercomparisons Project 6 (CMIP6) multi-model ensemble method was also performed. The Standard Precipitation Index (SPI), a simple yet incredibly sensitive tool for measuring changes in drought, is utilized in this study, providing a valuable assessment of drought conditions across multiple timescales. The historical analysis shows that there is a significant increase in drought frequency in subdivisions such as East MP, Chhattisgarh, East UP, East Rajasthan, Tamil Nadu, and Rayalaseema over the past decades. Our findings from a meticulous examination of historical rainfall trends spanning from 1951 to 2022 show a noticeable decline in rainfall across various regions such as Uttar Pradesh, Chhattisgarh, Marathwada, and north-eastern states, with a concurrent increase in rainfall over areas such as Gujarat, adjoining regions of West MP and East Rajasthan, and South Interior Karnataka. The future projection portrays an unpredictable pattern of extreme events, including droughts and wet events, with indications that wet frequency is set to increase under extreme SSP scenarios, particularly over time, while highlighting the susceptibility of the northwest and south peninsula regions to a higher incidence of drought events in the near future. Analyzing the causes of the increase in drought frequency is crucial to mitigate its worst impacts, and recent experiences of drought consequences can help in effective planning and decision-making, requiring appropriate mitigation strategies in the vulnerable subdivisions.
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Liu, Rutong, Jiabo Yin, Louise Slater, et al. "Machine-learning-constrained projection of bivariate hydrological drought magnitudes and socioeconomic risks over China." Hydrology and Earth System Sciences 28, no. 14 (2024): 3305–26. http://dx.doi.org/10.5194/hess-28-3305-2024.
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Abstract. Climate change influences the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. Although machine learning is increasingly employed for hydrological simulations, few studies have used it to project hydrological droughts, not to mention bivariate risks (referring to drought duration and severity) as well as their socioeconomic effects under climate change. We developed a cascade modeling chain to project future bivariate hydrological drought characteristics in 179 catchments over China, using five bias-corrected global climate model (GCM) outputs under three shared socioeconomic pathways (SSPs), five hydrological models, and a deep-learning model. We quantified the contribution of various meteorological variables to daily streamflow by using a random forest model, and then we employed terrestrial water storage anomalies and a standardized runoff index to evaluate recent changes in hydrological drought. Subsequently, we constructed a bivariate framework to jointly model drought duration and severity by using copula functions and the most likely realization method. Finally, we used this framework to project future risks of hydrological droughts as well as the associated exposure of gross domestic product (GDP) and population. Results showed that our hybrid hydrological–deep-learning model achieved > 0.8 Kling–Gupta efficiency in 161 out of the 179 catchments. By the late 21st century, bivariate drought risk is projected to double over 60 % of the catchments mainly located in southwestern China under SSP5-85, which shows the increase in drought duration and severity. Our hybrid model also projected substantial GDP and population exposure by increasing bivariate drought risks, suggesting an urgent need to design climate mitigation strategies for a sustainable development pathway.
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Bayatavrkeshi, Maryam, Monzur Alam Imteaz, Ozgur Kisi, et al. "Drought trends projection under future climate change scenarios for Iran region." PLOS ONE 18, no. 11 (2023): e0290698. http://dx.doi.org/10.1371/journal.pone.0290698.
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The study highlights the potential characteristics of droughts under future climate change scenarios. For this purpose, the changes in Standardized Precipitation Evapotranspiration Index (SPEI) under the A1B, A2, and B1 climate change scenarios in Iran were assessed. The daily weather data of 30 synoptic stations from 1992 to 2010 were analyzed. The HadCM3 statistical model in the LARS-WG was used to predict the future weather conditions between 2011 and 2112, for three 34-year periods; 2011–2045, 2046–2079, and 2080–2112. In regard to the findings, the upward trend of the potential evapotranspiration in parallel with the downward trend of the precipitation in the next 102 years in three scenarios to the base timescale was transparent. The frequency of the SPEI in the base month indicated that 17.02% of the studied months faced the drought. Considering the scenarios of climate change for three 34-year periods (i.e., 2011–2045, 2046–2079, and 2080–2112) the average percentages of potential drought occurrences for all the stations in the next three periods will be 8.89, 16.58, and 27.27 respectively under the B1 scenario. While the predicted values under the A1B scenario are 7.63, 12.66, and 35.08%respectively. The relevant findings under the A2 scenario are 6.73, 10.16, 40.8%. As a consequence, water shortage would be more serious in the third period of study under all three scenarios. The percentage of drought occurrence in the future years under the A2, B1, and A1B will be 19.23%, 17.74%, and 18.84%, respectively which confirms the worst condition under the A2 scenario. For all stations, the number of months with moderate drought was substantially more than severe and extreme droughts. Considering the A2 scenario as a high emission scenario, the analysis of SPEI frequency illustrated that the proportion of dry periods in regions with humid and cool climate is more than hot and warm climates; however, the duration of dry periods in warmer climates is longer than colder climates. Moreover, the temporal distribution of precipitation and potential evapotranspiration indicated that in a large number of stations, there is a significant difference between them in the middle months of the year, which justifies the importance of prudent water management in warm months.
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Ashrafi, S. M., H. Gholami, and M. R. Najafi. "Uncertainties in runoff projection and hydrological drought assessment over Gharesu basin under CMIP5 RCP scenarios." Journal of Water and Climate Change 11, S1 (2020): 145–63. http://dx.doi.org/10.2166/wcc.2020.088.
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Abstract Hydrological drought plays an important role in planning and managing water resources systems to meet increasing water demands due to population growth. In this study, the effects of climate change on the hydrological drought characteristics of the Gharasu basin, as one of the major sub-basins of the Karkheh river basin, are investigated. This river basin has experienced severe droughts, and floods, in recent years. The uncertainties in projected drought conditions are characterized based on a suite of 34 general circulation models (GCMs). Based on hydrological simulations over the historical period, 12 GCMs are selected to estimate projected runoff values and the corresponding streamflow drought index (SDI) in the future period. The ‘run theory’ is applied to evaluate the drought characteristics under Representative Concentration Pathways (RCPs) 4.5 and 8.5 emission scenarios. Results show that uncertainties of drought projection under RCP8.5 are higher than under RCP4.5, where among different drought characteristics, the maximum uncertainty is detected for drought severity and maximum drought duration. Moreover, the uncertainty of drought projection in wet periods is greater than that in dry periods.
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Ghazi, Babak, Sanjana Dutt, and Ali Torabi Haghighi. "Projection of Future Meteorological Droughts in Lake Urmia Basin, Iran." Water 15, no. 8 (2023): 1558. http://dx.doi.org/10.3390/w15081558.
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Future changes (2015–2100) in precipitation and meteorological droughts in Lake Urmia Basin were investigated using an average mean ensemble of eight general circulation models (GCMs) with high-resolution datasets in socioeconomic pathway scenarios (SSPs) from the Coupled Model Intercomparison Project (CMIP6). In order to project the drought, the standardized precipitation index (SPI) was calculated. Overall, the results revealed that precipitation in Lake Urmia Basin will decrease by 3.21% and 7.18% in the SSP1-2.6 and SSP5-8.5 scenarios, respectively. The results based on 6-month-timescale SPI indices projected more “Extremely dry” events in SSP5-8.5 scenarios. The frequency of “Extremely dry” months in SSP5-8.5 compared to SSP1-2.6 is expected to increase by 14, 7, 14, 10, 5, 14, and 7 months for the Mahabad, Maragheh, Saqez, Sarab, Tabriz, Takab, and Urmia stations, respectively. In contrast, the frequency of “Extremely wet” months will decline for all stations in Lake Urmia Basin. The results of this study provide useful insight for considering drought prevention measures to be implemented in advance for Lake Urmia Basin, which is currently experiencing various environmental issues.
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Jincy Rose, M. A., and N. R. Chithra. "Evaluation of temporal drought variation and projection in a tropical river basin of Kerala." Journal of Water and Climate Change 11, S1 (2020): 115–32. http://dx.doi.org/10.2166/wcc.2020.240.
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Abstract Temperature is an indispensable parameter of climate that triggers evapotranspiration and has vital importance in aggravating drought severity. This paper analyses the existence and persistence of drought conditions which are said to prevail in a tropical river basin which was once perennial. Past observed data and future climate projections of precipitation and temperature were used for this purpose. The assessment and projection of this study employ the Standardized Precipitation Evapotranspiration Index (SPEI) compared with that of the Standardized Precipitation Index (SPI). The results indicate the existence of drought in the past and the drought conditions that may persist in the future according to RCP 4.5 and 8.5 scenarios. The past drought years identified in the study were compared with the drought declared years in the state and were found to be matching. The evaluation of the future scenarios unveils the occurrence of drought in the basin ranging from mild to extreme conditions. It has been noted that the number of moderate and severe drought months has increased based on SPEI compared to SPI, indicating the importance of temperature in drought studies. The study can be considered as a plausible scientific remark helpful in risk management and application decisions.
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Guo, Xiaolin, Yuan Yang, Zhansheng Li, et al. "Drought Trend Analysis Based on the Standardized Precipitation–Evapotranspiration Index Using NASA’s Earth Exchange Global Daily Downscaled Projections, High Spatial Resolution Coupled Model Intercomparison Project Phase 5 Projections, and Assessment of Potential Impacts on China’s Crop Yield in the 21st Century." Water 11, no. 12 (2019): 2455. http://dx.doi.org/10.3390/w11122455.
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Drought is among the costliest natural disasters on both ecosystems and agroeconomics in China. However, most previous studies have used coarse resolution data or simply stopped short of investigating drought projection and its impact on crop yield. Motivated by the newly released higher-resolution climate projection dataset and the crucial need to assess the impact of climate change on agricultural production, the overarching goal of this study was to systematically and comprehensively predict future droughts at unprecedented resolutions over China as a whole. rather than region-specific projections, and then to further investigate its impact on crop yield by innovatively using a soil water deficit drought index. Methodologically, the drought projections were quantified from very high resolution climate data and further predicted impacts on crop yield over China using the standardized precipitation–evapotranspiration index (SPEI) at a relatively high (25 km) spatial resolution from NASA’s Earth Exchange Global Daily Downscaled Projections (NEX-GDDP). The results showed that (1) overall, China is projected to experience a significant decrease in SPEI (−0.15/decade under RCP (representative concentration pathway) 4.5; −0.14/decade under RCP8.5). Seasonally, the decreasing rate of SPEI is projected to be largest in winter (−0.2/decade and −0.31/decade) and the least in summer (−0.08/decade and −0.10/decade) under respective RCPs. (2) Regionally, winter/spring will get drier, especially at high latitudes/altitudes (North China and Tibetan plateau), and summer/autumn will get wetter in southern China. (3) Both the frequency and duration for medium and severe drought are projected to decrease, while extreme drought, particularly in high latitudes/altitudes, is projected to increase. (4) The percentage of the potential crop production affected by drought would increase to 36% (47%) by 2100 under RCP4.5 (RCP8.5). Especially, the ratio impacted by extreme drought is projected to increase over time and with much worse magnitude under RCP8.5; thus, adaptive crop policies are expected to address such a risk.
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Lee, J. H., S. J. Moon, and B. S. Kang. "Drought frequency projection using regional climate scenarios reconstructed by seasonal artificial neural network model." Journal of Water and Climate Change 5, no. 4 (2014): 578–92. http://dx.doi.org/10.2166/wcc.2014.130.
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The climate change impacts on drought in the Korean peninsula were projected using Global Climate Model (GCM) output reconstructed regionally by an artificial neural network (ANN) model. The reconstructed model outputs were subsequently used as an input to project drought severity evaluated by Standard Precipitation Index (SPI). The original GCM output corresponds to the CGCM3.1/T63 under the 20C3M reference scenario and the IPCC A1B, A2 and B1 projection scenarios. Because in general GCM shows limitation in capturing typhoon generation occurred at sub-grid scale, the training and validation of the ANN model utilized a precipitation data set with typhoon-generated rainfall eliminated for enhancing the ANN's computational performance. The non-stationarity characteristics of SPI was examined using the Mann–Kendall test. The projection was implemented for the near future period (2011–2040), mid-term (2041–2070) and long-term (2071–2100) future periods. The results indicated mitigated drought severity under all scenarios in terms of frequency, magnitude and drought spells even for the mildest B1 scenario. The SDF (severity-duration-frequency) curves illustrate the common patterns of alleviated drought severity for most future scenarios and elongated drought duration. The reconstructed GCM projection recovers the underestimated precipitation and provided more realistic drought projection even though there would be still uncertainties of spatial and temporal variability.
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Shin, Ju-Young, Pham Van Chien, Myung-Jin Um, Hanbeen Kim, and Kyungmin Sung. "Projection of Changes in Rainfall and Drought Based on CMIP6 Scenarios on the Ca River Basin, Vietnam." Water 16, no. 13 (2024): 1914. http://dx.doi.org/10.3390/w16131914.
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In this study, future precipitation and drought in the Ca river basin, Vietnam, were projected based on an ensemble of 27 CMIP6 models for four climate change scenarios. The impact of climate change on precipitation and drought was investigated. Monthly precipitation observation data were adjusted using the bias correction method. To detect drought events, the Standard Precipitation Index (SPI) was employed. Changes in drought were assessed using SPI3, SPI6, and SPI12. Although the amount of annual total precipitation slightly increased, the drought events may become more severe. There is a high likelihood of increased drought intensity and severity in Vietnam due to climate change. The frequency of droughts is likely to change depending on the location and climate change scenario. We found that the frequency and severity of droughts may be altered depending on the window size of SPI. The short-term drought events will be more frequent and severe, and long-term drought events will become more severe in the Ca river basin.
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Chandrasekara, Sewwandhi S. K., Hyun-Han Kwon, Meththika Vithanage, Jayantha Obeysekera, and Tae-Woong Kim. "Drought in South Asia: A Review of Drought Assessment and Prediction in South Asian Countries." Atmosphere 12, no. 3 (2021): 369. http://dx.doi.org/10.3390/atmos12030369.
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South Asian countries have been experiencing frequent drought incidents recently, and due to this reason, many scientific studies have been carried out to explore drought in South Asia. In this context, we review scientific studies related to drought in South Asia. The study initially identifies the importance of drought-related studies and discusses drought types for South Asian regions. The representative examples of drought events, severity, frequency, and duration in South Asian countries are identified. The Standardized Precipitation Index (SPI) was mostly adopted in South Asian countries to quantify and monitor droughts. Nevertheless, the absence of drought quantification studies in Bhutan and the Maldives is of great concern. Future studies to generate a combined drought severity map for the South Asian region are required. Moreover, the drought prediction and projection in the regions is rarely studied. Furthermore, the teleconnection between drought and large-scale atmospheric circulations in the South Asia has not been discussed in detail in most of the scientific literature. Therefore, as a take-home message, there is an urgent need for scientific studies related to drought quantification for some regions in South Asia, prediction and projection of drought for an individual country (or as a region), and drought teleconnection to atmospheric circulation.
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Ibrahim, Hesham M., Abdulaziz G. Alghamdi, and Anwar A. Aly. "Assessing Drought Patterns in Al-Baha: Implications for Water Resources and Climate Adaptation." Sustainability 16, no. 22 (2024): 9882. http://dx.doi.org/10.3390/su16229882.
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Due to growing water demands and changing hydro-meteorological variables brought on by climate change, drought is becoming an increasingly serious climate concern. The Al-Baha region of Saudi Arabia is the subject of this study because it is susceptible to both agricultural and meteorological droughts. This study investigates how climate change affects patterns of drought in Al-Baha by analyzing four drought indices (Agricultural Standardized Precipitation Index (aSPI), the Standardized Precipitation Index (SPI), the Rainfall Deficiency Index (RDI), and the Effective Reconnaissance Drought Index (eRDI)) for the years 1991–2022. Analysis of rainfall data was carried out to classify drought events according to their duration, frequency, and severity. Results showed that severe droughts occurred in 2009, 2010, 2012, 2016, and 2022, with 2010 being the worst year. Results also indicated a notable decrease in precipitation, which has resulted in extended dry spells. Several indices indicate that this tendency has significant ramifications for agriculture, particularly in areas where farming is a major economic activity. In addition, the possible occurrence of hydrological drought was also observed based on the negative values for the Reservoir Storage Index (RSI) in Al-Baha. Projections for the future under two Representative Concentration Pathways (RCPs) showed notable variations in temperature and precipitation. Both the RCP4.5 (low emission) and the RCP8.5 (high emission) projection scenarios indicate that drought conditions will likely worsen further. Depending on the emission scenario, it is projected to show a temperature increase of 1–2 °C, whereas the variability in precipitation projections indicates significant uncertainty, with a reduction change in the range of 1.2–27% between 2050 and 2100. The findings highlight the urgent need for proactive adaptation strategies, effective water resource management, and the development of sophisticated drought prediction tools. Addressing these challenges is crucial for sustaining agriculture and managing water scarcity in Saudi Arabia in the face of increasing drought risk.
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Bedri, Rama, and Thomas Piechota. "Future Colorado River Basin Drought and Surplus." Hydrology 9, no. 12 (2022): 227. http://dx.doi.org/10.3390/hydrology9120227.
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Historical and future drought and surplus periods in the Colorado River basin are evaluated based on eight climate scenarios. Unimpaired streamflow from 17 stations in the Colorado River are evaluated based on U.S. Geological Survey, Bureau of Reclamation, and Coupled Modeled Intercomparison Projection 5 downscaled data from 1950–2099. Representative Concentration Pathway (RCP) 4.5 and 8.5 emission scenarios are considered for four climate models (HadGEM2-ES, CNRM-CM5, CanESM2, MI-ROC5). Drought (surplus) quantities, magnitudes, severities, and water year flows are compared for the historical and future periods. Results indicate that there is a significant difference between the historical record and future projections. The results are not consistent in terms of increase of drought or surplus; however, the intensity (as measured by magnitude and duration) will likely increase for both RCP 4.5 and 8.5. The CanESM2 and CNRM-CM5 models project wetter scenarios, and HadGEM2 and MI-ROC5 models project drier scenarios. For the critical Lees Ferry station, models indicate a chance of higher drought and surplus length and magnitude on the order of two times the historical period. In addition, basin wide flow at Lees Ferry had a shift in the future mean ensemble of approximately 3–10% for the water year. Future hydrologic changes will heighten the need for appropriate management and infrastructure options available to adapt to these changes.
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Ta, Zhijie, Kaiyu Li, Yang Yu, and Meilin Yang. "Projections of Future Drought by CMIP5 Multimodel Ensembles in Central Asia." Atmosphere 13, no. 2 (2022): 232. http://dx.doi.org/10.3390/atmos13020232.
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Future changes in drought characteristics in Central Asia are projected at the regional scale using 21 climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Based on the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI), drought characteristics were characterized by drought frequency at 1-, 3-, and 12-month timescales. The drought duration was analyzed based on SPI1 and SPEI1. Drought indices were calculated by the multimodel ensemble (MME) from 21 CMIP5 models. The varimax rotation method was used to identify drought conditions for the entire area and seven drought subregions. In general, the projection results of future drought in Central Asia are related to the choice of drought index, and SPI and SPEI show different results. The drought frequency based on SPEI1, SPEI3, and SPEI12 showed an increasing trend in the future periods, that is, the drought frequency based on monthly, seasonal, and annual timescales will show an increase trend in the future periods. However, for SPI1, SPI3, and SPI12, the drought frequency will decrease in the future. SPI projected that the duration of drought will decrease in the future, while SPEI mainly showed an increasing trend. The results of the study should be of sufficient concern to policymakers to avoid land degradation, crop loss, water resource deficit, and economic loss.
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Sung, Jang Hyun, Seung Beom Seo, and Young Ryu. "Deep Learning-Based Projection of Occurrence Frequency of Forest Fires under SSP Scenario: Exploring the Link between Drought Characteristics and Forest Fires." Sustainability 14, no. 9 (2022): 5494. http://dx.doi.org/10.3390/su14095494.
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The occurrence frequency of forest fires (OF) can be estimated using drought features because droughts are affected by climatic conditions. Previous studies have improved OF estimation performance by applying the meteorological drought index to climatic conditions. It is anticipated that the temperature will rise in South Korea in the future and that drought will become severe on account of climate change. The future OF is expected to change accordingly. This study used the standard precipitation index, relative humidity, and wind speed as predictor variables for a deep-learning-based model to estimate the OF. Climate change scenarios under shared socioeconomic pathways were used to estimate future OF. As a result, it was projected that the OF in the summer season will increase in the future (2071–2100). In particular, there will be a 15% increase in July compared to the current climate. A decrease in relative humidity and increase in wind speed will also affect the OF. Finally, drought severity was found to be the most influential factor on the OF among the four drought characteristics (severity, duration, intensity, and inter-arrival), considering inter-model variability across all global climate models.
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Petpongpan, Chanchai, Chaiwat Ekkawatpanit, Supattra Visessri, and Duangrudee Kositgittiwong. "Projection of Hydro-Climatic Extreme Events under Climate Change in Yom and Nan River Basins, Thailand." Water 13, no. 5 (2021): 665. http://dx.doi.org/10.3390/w13050665.
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Due to a continuous increase in global temperature, the climate has been changing without sign of alleviation. An increase in the air temperature has caused changes in the hydrologic cycle, which have been followed by several emergencies of natural extreme events around the world. Thailand is one of the countries that has incurred a huge loss in assets and lives from the extreme flood and drought events, especially in the northern part. Therefore, the purpose of this study was to assess the hydrological regime in the Yom and Nan River basins, affected by climate change as well as the possibility of extreme floods and droughts. The hydrological processes of the study areas were generated via the physically-based hydrological model, namely the Soil and Water Assessment Tool (SWAT) model. The projected climate conditions were dependent on the outputs of the Global Climate Models (GCMs) as the Representative Concentration Pathways (RCPs) 2.6 and 8.5 between 2021 and 2095. Results show that the average air temperature, annual rainfall, and annual runoff will be significantly increased in the intermediate future (2046–2070) onwards, especially under RCP 8.5. According to the Flow Duration Curve and return period of peak discharge, there are fluctuating trends in the occurrence of extreme floods and drought events under RCP 2.6 from the future (2021–2045) to the far future (2071–2095). However, under RCP 8.5, the extreme flood and drought events seem to be more severe. The probability of extreme flood remains constant from the reference period to the near future, then rises dramatically in the intermediate and the far future. The intensity of extreme droughts will be increased in the near future and decreased in the intermediate future due to high annual rainfall, then tending to have an upward trend in the far future.
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Gwak, Yongseok, Jaepil Cho, Imgook Jung, Dowoo Kim, and Sangmin Jang. "Projection of Future Changes in Drought Characteristics in Korea Peninsula Using Effective Drought Index." Journal of Climate Change Research 9, no. 1 (2018): 31–45. http://dx.doi.org/10.15531/ksccr.2018.9.1.31.
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Li, Zhanling, Yingtao Ye, Xiaoyu Lv, Miao Bai, and Zhanjie Li. "Hydrological Drought and Flood Projection in the Upper Heihe River Basin Based on a Multi-GCM Ensemble and the Optimal GCM." Atmosphere 15, no. 4 (2024): 439. http://dx.doi.org/10.3390/atmos15040439.
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To ensure water use and water resource security along “the Belt and Road”, the runoff and hydrological droughts and floods under future climate change conditions in the upper Heihe River Basin were projected in this study, based on the observed meteorological and runoff data from 1987 to 2014, and data from 10 GCMs from 1987 to 2014 and from 2026 to 2100, using the SWAT model, the Standardized Runoff Index, run length theory, and the entropy-weighted TOPSIS method. Both the multi-GCM ensemble (MME) and the optimal model were used to assess future hydrological drought and flood responses to climate change. The results showed that (1) the future multi-year average runoff from the MME was projected to be close to the historical period under the SSP245 scenario and to increase by 2.3% under the SSP585 scenario, and those from the optimal model CMCC-ESM2 were projected to decrease under both scenarios; (2) both the MME and the optimal model showed that drought duration and flood intensity in the future were projected to decrease, while drought intensity, drought peak, flood duration, and flood peak were projected to increase under both scenarios in their multi-year average levels; (3) drought duration was projected to decrease most after 2080, and drought intensity, flood duration, and flood peak were projected to increase most after 2080, according to the MME. The MME and the optimal model reached a consensus on the sign of hydrological extreme characteristic responses to climate change, but showed differences in the magnitude of trends.
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Deng, Yueping, Wenyu Jiang, Tianyu Zhang, et al. "Projection of Meteorological Dryness/Wetness Evolution Based on Multi-Model Scenarios in Poyang Lake Basin, China." Sustainability 15, no. 10 (2023): 8194. http://dx.doi.org/10.3390/su15108194.
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Based on the projections of three shared socioeconomic pathways (SSPs) scenarios of three climate models of CMIP6, this study analyzed the standardized precipitation evapotranspiration index (SPEI) to understand the future meteorological dryness/wetness changes in the Poyang Lake basin (PLB) from 2021 to 2100. The effect of temperature change on the dryness and wetness variation was explored by comparing the trends of SPEI and standardized precipitation index (SPI) at multiple-time scales and different SSPs scenarios. The results indicate that the frequency of drought events may increase by 1.1~3.8% than the historical period in the three scenarios, and they may be higher than that of wetness events in the future of this century. Cumulative months of drought events are higher in most decades than the wetness events, and especially in the 2090s. A total of 43 months may suffer drought events in the 2090s under the SSP585 scenario, which is more than twice the wetness events. With the enhanced concentration of greenhouse gas (GHG) emissions, both the frequency of droughts and the proportion of extreme droughts show a significant increasing trend at 99% confidence in PLB. The spatial distribution of net precipitation is generally in the southwest–northeast pattern, yet it is still in different values in most scenarios; thus, the uncertainty of dryness/wetness spatial conditions should be considered. The SPI detects more wetness events and a more intensive wetting trend, while the SPEI shows the opposite. The difference between SPI and SPEI gradually increases with GHG emission concentration, and may even lead to contrary conclusion in the last two decades at a 48-month scale under the SSP245 and 585 scenarios, indicating the unneglectable impact of increasing temperature and evapotranspiration on the dryness/wetness conditions in the future. The research results can help to predict the evolution pattern of dry and wet occurrence in the PLB in the future and promote flood/drought control and disaster mitigation.
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Kim, Byung Sik, In Gi Chang, Jang Hyun Sung, and Hae Jin Han. "Projection in Future Drought Hazard of South Korea Based on RCP Climate Change Scenario 8.5 Using SPEI." Advances in Meteorology 2016 (2016): 1–23. http://dx.doi.org/10.1155/2016/4148710.
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The Standardized Precipitation Evapotranspiration Index (SPEI) analysis was conducted using monthly precipitation data and temperature data on a 12.5 km × 12.5 km resolution based on a Representative Concentration Pathways (RCP) 8.5 climate change scenario, and the characteristics of drought were identified by the threshold. In addition, the changes in drought severity and intensity were projected using the threshold based on the run-length concept and frequency analysis. As a result of the analysis, the probability density function of the total drought and maximum drought intensity moved the upper tail for the upcoming years, and the average drought intensity was also projected to become stronger in the future than in the present to the right side. Through this, it could be projected that the drought scale and frequency and the drought intensity will become severer over South Korea because of future climate change.
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Nur, Irza Arnita, Rahmat Hidayat, Arnida Lailatul Latifah, and Misnawati. "Pengaruh koreksi bias dan metode ensemble pada data curah hujan dari empat model luaran Regional Climate Model (RCM) CORDEX-SEA di Sumatera." Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) 11, no. 1 (2021): 49–56. http://dx.doi.org/10.29244/jpsl.11.1.49-56.
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Drought is a natural disaster that occurs slowly and lasts longer until the wet season occurred. Drought occurred in expected time, so that preparations and preparedness can be made in dealing with drought disasters. Therefore, we need an overview of future drought events (or projections).In this study, Standardized Precipitation Index (SPI) was used as drought index. The occurrence of drought is closely related to weather factors and occurs repeatedly. Time-series weather data is needed to know the time-series weather conditions. Problems with data that often occur can be overcome by using numerical climate modeling which is currently widely used. Regional Climate Model (RCM) is a climate model that can be used to build long-term climate data, both time-series and projection data. The results showed RCM model data required bias correction in order to reduce bias in the CORDEX RCM model data. RCM rainfall models before correction were still biased. Thus, bias correction is needed to reduce bias in models data. Time series obtained from SPI baseline data for 2000-2005 in Lampung and West Sumatra provinces showed SPI value which smaller than the projection SPI value in 2021-2030. While SPI time series with RCP 4.5 and 8.5 scenarios showed different results. SPI with RCP 8.5 scenario have more negative value so that drought occurred more often than RCP 4.5. The negative SPI index that often occured in RCP 8.5 scenario appeared to be in RCM IPSL and MPI models year 2025-2030.
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Jiao, Yang, and Xing Yuan. "More severe hydrological drought events emerge at different warming levels over the Wudinghe watershed in northern China." Hydrology and Earth System Sciences 23, no. 1 (2019): 621–35. http://dx.doi.org/10.5194/hess-23-621-2019.
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Abstract. Assessment of changes in hydrological droughts at specific warming levels is important for an adaptive water resources management with consideration of the 2015 Paris Agreement. However, most studies focused on the response of drought frequency to the warming and neglected other drought characteristics, including severity. By using a semiarid watershed in northern China (i.e., Wudinghe) as an example, here we show less frequent but more severe hydrological drought events emerge at 1.5, 2 and 3 ∘C warming levels. We used meteorological forcings from eight Coupled Model Intercomparison Project Phase 5 climate models under four representative concentration pathways, to drive a newly developed land surface hydrological model to simulate streamflow, and analyzed historical and future hydrological drought characteristics based on the standardized streamflow index. The Wudinghe watershed will reach the 1.5, 2 and 3 ∘C warming levels around 2015–2034, 2032–2051 and 2060–2079, with an increase in precipitation of 8 %, 9 % and 18 % and runoff of 27 %, 19 % and 44 %, and a drop in hydrological drought frequency of 11 %, 26 % and 23 % as compared to the baseline period (1986–2005). However, the drought severity will rise dramatically by 184 %, 116 % and 184 %, which is mainly caused by the increased variability in precipitation and evapotranspiration. The climate models and the land surface hydrological model contribute to more than 80 % of total uncertainties in the future projection of precipitation and hydrological droughts. This study suggests that different aspects of hydrological droughts should be carefully investigated when assessing the impact of 1.5, 2 and 3 ∘C global warming.
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Park, Myungwoo, Okjeong Lee, Yoonkyung Park, and Sangdan Kim. "Future Drought Projection in Korea under AR5 RCP Climate Change Scenarios." Journal of Korean Society of Hazard Mitigation 15, no. 6 (2015): 423–33. http://dx.doi.org/10.9798/kosham.2015.15.6.423.
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Kim, Jin Hyuck, Jang Hyun Sung, Eun-Sung Chung, Sang Ug Kim, Minwoo Son, and Mohammed Sanusi Shiru. "Comparison of Projection in Meteorological and Hydrological Droughts in the Cheongmicheon Watershed for RCP4.5 and SSP2-4.5." Sustainability 13, no. 4 (2021): 2066. http://dx.doi.org/10.3390/su13042066.
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Due to the recent appearance of shares socioeconomic pathway (SSP) scenarios, there have been many studies that compare the results between Coupled Model Intercomparison Project (CMIP)5 and CMIP6 general circulation models (GCMs). This study attempted to project future drought characteristics in the Cheongmicheon watershed using SSP2-4.5 of Australian Community Climate and Earth System Simulator-coupled model (ACCESS-CM2) in addition to Representative Concentration Pathway (RCP) 4.5 of ACCESS 1-3 of the same institute. The historical precipitation and temperature data of ACCESS-CM2 were generated better than those of ACCESS 1-3. Two meteorological drought indices, namely, Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were used to project meteorological drought while a hydrological drought index, Standardized Streamflow Index (SDI), was used to project the hydrological drought characteristics. The metrological data of GCMs were bias-corrected using quantile mapping method and the streamflow was obtained using Soil and Water Assessment Tool (SWAT) and bias-corrected meteorological data. As a result, there were large differences of drought occurrences and severities between RCP4.5 and SSP2-4.5 for the values of SPI, SPEI, and SDI. The differences in the minimum values of drought index between near (2021–2060) and far futures (2061–2100) were very small in SSP2-4.5, while those in RCP4.5 were very large. In addition, the longest drought period from SDI was the largest because the variation in precipitation usually affects the streamflow with a lag. Therefore, it was concluded that it is important to consider both CMIP5 and CMIP6 GCMs in establishing the drought countermeasures for the future period.
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Babaeian, Iman, Atefeh Erfani Rahmatinia, Alireza Entezari, Mohammad Baaghideh, Mohammad Bannayan Aval, and Maral Habibi. "Future Projection of Drought Vulnerability over Northeast Provinces of Iran during 2021–2100." Atmosphere 12, no. 12 (2021): 1704. http://dx.doi.org/10.3390/atmos12121704.
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Future projection of drought vulnerability is vital for northern provinces of Iran, including North Khorasan, Khorasan-Razavi, and South Khorasan, due to the highly dependent of their economy on agriculture. The study is motivated by the fact that no research has been conducted to project the future Drought Vulnerability Index (DVI). DVI consist of three components of exposure, sensitivity, and adaptation capacity. More exposure levels of drought, higher sensitivity value, and lower adaptation capacity lead to a higher amount of vulnerability. Combined ERA-Interim-observation meteorological data, CMIP5 models under RCP4.5 and RCP8.5 scenarios, and national census data are used to estimate DVI in the past and future periods. CanESM2, GFDL-ESM2M, and CNRM-CM5 General Circulation Model (GCM) are selected from CMIP5 based on Taylor diagram results. The delta-change technique was selected for statistical downscaling of GCM outputs because it is most widely used. The study period is regarded as 1986–2005 as observation and four future 20-years periods during 2021–2100. Results indicated that the dissipation of the class of “very low” vulnerability is eminent in the near future period of 2021–2040 under the RCP4.5 scenario, and all provinces would experience a new worse class of “very high” vulnerability at 2081–2100, both under RCP4.5 and RCP8.5 scenarios.
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Yuan, Zhe, Jijun Xu, Jin Chen, et al. "Drought Assessment and Projection under Climate Change: A Case Study in the Middle and Lower Jinsha River Basin." Advances in Meteorology 2017 (2017): 1–16. http://dx.doi.org/10.1155/2017/5757238.
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To gain an insight into the spatiotemporal variability of drought events and to assess trends under future climate change scenarios are fundamental for making sound mitigation and adaptation strategies. A new drought index, standardized supply-demand water index (SSDI), has been proposed in this research. The SSDI describes drought from the view of water supply-demand relations using a simple water balance model. It was used to assess historical drought events in the middle and lower Jinsha river basin (MLJRB) located in the southwest China and applied to address the drought conditions in the MLJRB under current and future climates. The results showed the following: (1) The average drought area during 2001 to 2011 reached up to 9.9 × 103 km2, accounting for 35.4% of the whole farmland area in the MLJRB, which was about twice as the drought area during 1961 to 2000. The region for greater drought severity with more drought events and longer duration was mainly distributed in Dali, Chuxiong, Kunming, and Yuxi. (2) For the period 2021 to 2050, total drought area was projected to increase by 43.2%. The drought-prone regions could move further towards the northwest of the MLJRB.
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Minda, Thomas T., Tadele Badebo, and Abebe Kebede. "Evaluation of meteorological drought and its impact on crop yield over Afar region, northeast Ethiopia." Ethiopian Journal of Water Science and Technology 6 (November 2, 2024): 75–108. http://dx.doi.org/10.59122/17519g6.
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Drought is a natural hazard caused by a prolonged precipitation deficit that cannot meet human, livestock, and environmental demands. In Ethiopia, frequent and severe droughts increasingly affect the socio-economic and environmental sectors. This study evaluates the current and future projected meteorological drought and its impact on crop yield over the Afar region in northeast Ethiopia. We used surface stations, satellite climate estimates, downscaled atmospheric reanalysis, and regional climate model datasets. We evaluated the occurrence of drought using the Standardized Precipitation Index (SPI) and Standardized Precipitation and Evapotranspiration Index (SPEI) calculated at 3-month and 12-month time scales. The drought vs. regional cereal yield is correlated to explain yield variability in the region. Results showed that more intense droughts were analyzed in 1984, 1985, 2002, 2008, 2009, 2010, 2015, and 2016. Among these years, 1984, 2002, 2008, 2009, and 2015 were the driest years across all locations in the study area. The regression of SPI and SPEI with yield showed that the indices significantly explained (r2 = 0.56 for SPI and 0.18 for SPEI) the observed yield variation. Spatially, more intense drought prevails over the northern, northwestern, and southwestern parts of Afar, where these parts are more prone to severe drought. The projected drought pattern showed increases in the intensity and frequency of drought in the middle and end of the century. The findings of this study are helpful for stakeholders working on drought mitigation in the region. Keywords: Climate dataset, meteorological drought indices, drought projection, pastoral community.
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Cox, Timothy, Jenny Bywater, Mitchell Heineman, Dan Rodrigo, and Shayne Wood. "Forecasting extreme events: making sense of noisy climate data in support of water resources planning." H2Open Journal 2, no. 1 (2019): 45–57. http://dx.doi.org/10.2166/wcc.2018.006.
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Abstract Global climate model (GCM) projections are generally considered the best source of information for predicting future climate and hydrologic conditions in the face of a changing climate. Understanding and interpreting GCM projections is therefore critical for water resources planning. Unfortunately, this can be a challenging task as climate model data, particularly precipitation data, are notoriously noisy with large scatter and lacking in apparent patterns or trends. There is also usually large projection variability between models and model scenarios. This paper demonstrates a simple, practical method for synthesizing climate model data into more informative metrics using case studies of Atlanta, Georgia and Austin, Texas. Monthly and daily GCM projections, as well as historical observations, were translated into commonly used summary metrics for extreme event planning: peak 24-hour storm events and the Palmer Drought Severity Index (PDSI). Statistical trend analyses on these two metrics were used as a simple means to better understand the data. As expected, results identified significant, increasing, trends in projected 21st century temperatures for most GCM projections. Less expectedly, significant trends were also identified for projected future monthly and 24-hour maximum precipitation and drought severity. Implications of this work for water resources planning are discussed.
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Bayatvarkeshi, Maryam, Monzur Alam Imteaz, Ozgur Kisi, et al. "Correction: Drought trends projection under future climate change scenarios for Iran region." PLOS ONE 19, no. 12 (2024): e0315634. https://doi.org/10.1371/journal.pone.0315634.
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Wu, Chuanhao, Pat J. F. Yeh, Yi-Ying Chen, Bill X. Hu, and Guoru Huang. "Future Precipitation-Driven Meteorological Drought Changes in the CMIP5 Multimodel Ensembles under 1.5°C and 2°C Global Warming." Journal of Hydrometeorology 21, no. 9 (2020): 2177–96. http://dx.doi.org/10.1175/jhm-d-19-0299.1.
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AbstractAnthropogenic forcing is anticipated to increase the magnitude and frequency of precipitation-induced extremes such as the increase in drought risks. However, the model-projected future changes in global droughts remain largely uncertain, particularly in the context of the Paris Agreement targets. Here, by using the standardized precipitation index (SPI), we present a multiscale global assessment of the precipitation-driven meteorological drought characteristics at the 1.5° and 2°C warming levels based on 28 CMIP5 global climate models (GCMs) under three representative concentration pathways scenarios (RCP2.6, RCP4.5, and RCP8.5). The results show large uncertainties in the timing reaching 1.5° and 2°C warming and the changes in drought characteristics among GCMs, especially at longer time scales and under higher RCP scenarios. The multi-GCM ensemble mean projects a general increase in drought frequency (Df) and area (Da) over North America, Europe, and northern Asia at both 1.5° and 2°C of global warming. The additional 0.5°C warming from 1.5° to 2°C is expected to result in a trend toward wetter climatic conditions for most global regions (e.g., North America, Europe, northern Asia, and northern Africa) due to the continuing increase in precipitation under the more intensified 2°C warming. In contrast, the increase in Df is projected only in some parts of southwest Asia, South America, southern Africa, and Australia. Our results highlight the need to consider multiple GCMs in drought projection studies under the context of the Paris Agreement targets to account for large model-dependent uncertainties.
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Khalilian, Sadegh, and Negar Shahvari. "A SWAT Evaluation of the Effects of Climate Change on Renewable Water Resources in Salt Lake Sub-Basin, Iran." AgriEngineering 1, no. 1 (2018): 44–57. http://dx.doi.org/10.3390/agriengineering1010004.
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Future climate change is projected to have significant impacts on water resources availability in many parts of the world. This research evaluated climate change impacts on runoff, aquifer infiltration, renewable water resources, and drought intensity in Salt Lake sub-basin, Iran, by the Soil and Water assessment tool (SWAT) model and the Standardized Precipitation Index (SPI) under A1B, A2, and B1 climatic scenarios for 2011–2030, 2046–2065, and 2080–2099, using 1986–2016 as the reference period. The model was calibrated and validated by the SWAT-CUP software and SUFI-2 algorithm. Nash–Sutcliffe (NS) coefficients (0.58 and 0.49) and the determination coefficients (R2) (0.65 and 0.50) were obtained for the calibration and validation periods, respectively. In order to study the climatic condition in the study basin, drought intensity was calculated. Then, drought intensity was predicted using the SPI index for the period 2011–2030. The results showed that runoff, infiltration, as well as renewable water resources will decrease under all climatic scenarios. Renewable water resources will be approximately reduced 100 Mm3 by the year 2100. The future projections suggest a regional increase of 2 °C in temperature and a 20% decrease in precipitation in the sub-basin. In particular, drought intensity will be increased in the future. In 2015, this index was −1.31, and in 2016, the SPI index was lower than −2. These projection scenarios should be of interest to water resources managers in tropical regions.
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Moutia, Sara, and Mohamed Sinan. "Drought projection from CMIP6 Climate models over Morocco in the 21st century using the Standardized Precipitation Evapotranspiration Index (SPEI)." E3S Web of Conferences 489 (2024): 04003. http://dx.doi.org/10.1051/e3sconf/202448904003.
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Quantifying how climate change drives drought in the 21st century is a priority to inform policy and adaptation planning in Morocco. SPEI drought index calculated from precipitation and temperature at 12 months’ time-scale covering the agricultural year September-August was carried out for each of the five models over the future period 2023-2099. The average changes across Morocco were obtained by comparing between the averages of SPEI values and the drought zone percentages (Light, Moderate, Severe and Extreme). Also, by comparing drought characteristics for the different 11-year time horizons 2023-2033, 2034-2044, 2045-2055, 2056-2066, 2067-2077, 2078-2088 and at the end 2089-2099. The study of future drought projections based on the SSP2-4.5 scenario of the CMIP6 models indicates a worsening of drought in Morocco during the second half of the century. Moderate drought is expected to predominate, with a sharp increase in the area affected by drought, even reaching 90% over six years. These results are essential for decision-makers in water resources management, highlighting the need to put in place strategies to mitigate the adverse effects of drought, including the efficient use of water resources.
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Wang, Lin, and Wen Chen. "A CMIP5 multimodel projection of future temperature, precipitation, and climatological drought in China." International Journal of Climatology 34, no. 6 (2013): 2059–78. http://dx.doi.org/10.1002/joc.3822.
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Wu, Yanfeng, Jingxuan Sun, Boting Hu, Y. Jun Xu, Alain N. Rousseau, and Guangxin Zhang. "Can the combining of wetlands with reservoir operation reduce the risk of future floods and droughts?" Hydrology and Earth System Sciences 27, no. 14 (2023): 2725–45. http://dx.doi.org/10.5194/hess-27-2725-2023.
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Abstract. Wetlands and reservoirs are important water flow and storage regulators in a river basin; therefore, they can play a crucial role in mitigating flood and hydrological drought risks. Despite the advancement of river basin theory and modeling, our knowledge is still limited about the extent to which these two regulators could perform such a role, especially under future climate extremes. To improve our understanding, we first coupled wetlands and reservoir operations into a semi-spatially explicit hydrological model and then applied it in a case study involving a large river basin in northeast China. The projection of future floods and hydrological droughts was performed using the hydrological model during different periods (near future: 2026–2050, middle century: 2051–2075, and end century: 2076–2100) under five future climate change scenarios. We found that the risk of future floods and hydrological droughts can vary across different periods – in particular, it will experience relatively large increases and slight decreases. This large river basin will experience flood events of longer duration, with larger peak flows and volume, and of enhanced flashiness compared to the historical period. Simultaneously, the hydrological droughts will be much more frequent, with longer durations and more serious deficits. Therefore, the risk of floods and droughts will, overall, increase further under future climate change even under the combined influence of reservoirs and wetlands. These findings highlight the hydrological regulation function of wetlands and reservoirs and attest that the combining of wetlands with reservoir operation cannot fully eliminate the increasing future flood and drought risks. To improve a river basin's resilience to the risks of future climate change, we argue that the implementation of wetland restoration and the development of accurate forecasting systems for effective reservoir operation are of great importance. Furthermore, this study demonstrated a wetland–reservoir integrated modeling and assessment framework that is conducive to risk assessment of floods and hydrological droughts and that can be used for other river basins in the world.
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Sohn, Kyung Hwan, Deg Hyo Bae, and Jae Hyun Ahn. "Projection and Analysis of Drought according to Future Climate and Hydrological Information in Korea." Journal of Korea Water Resources Association 47, no. 1 (2014): 71–82. http://dx.doi.org/10.3741/jkwra.2014.47.1.71.
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Gu, Huang He, Zhong Bo Yu, and Ji Gan Wang. "Future Extreme Climates Projection over Huang-Huai-Hai Region of China." Advanced Materials Research 955-959 (June 2014): 3887–92. http://dx.doi.org/10.4028/www.scientific.net/amr.955-959.3887.
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This study projects the future extreme climate changes over Huang-Huai-Hai (3H) region in China using a regional climate model (RegCM4). The RegCM4 performs well in “current” climate (1970-1999) simulations by compared with the available surface station data, focusing on near-surface air temperature and precipitation. Future climate changes are evaluated based on experiments driven by European-Hamburg general climate model (ECHAM5) in A1B future scenario (2070-2099). The results show that the annual temperature increase about 3.4 °C-4.2 °C and the annual precipitation increase about 5-15% in most of 3H region at the end of 21st century. The model predicts a generally less frost days, longer growing season, more hot days, no obvious change in heat wave duration index, larger maximum five-day rainfall, more heavy rain days, and larger daily rainfall intensity. The results indicate a higher risk of floods in the future warmer climate. In addition, the consecutive dry days in Huai River Basin will increase, indicating more serve drought and floods conditions in this region.
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Botai, Christina M., Joel O. Botai, Nosipho N. Zwane, et al. "Hydroclimatic Extremes in the Limpopo River Basin, South Africa, under Changing Climate." Water 12, no. 12 (2020): 3299. http://dx.doi.org/10.3390/w12123299.
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This research study evaluated the projected future climate and anticipated impacts on water-linked sectors on the transboundary Limpopo River Basin (LRB) with a focus on South Africa. Streamflow was simulated from two CORDEX-Africa regional climate models (RCMs) forced by the 5th phase of the Coupled Model Inter-Comparison Project (CMIP5) Global Climate Models (GCMs), namely, the CanESM2m and IPSL-CM5A-MR climate models. Three climate projection time intervals were considered spanning from 2006 to 2099 and delineated as follows: current climatology (2006–2035), near future (2036–2065) and end of century future projection (2070–2099). Statistical metrics derived from the projected streamflow were used to assess the impacts of the changing climate on water-linked sectors. These metrics included streamflow trends, low and high flow quantile probabilities, the Standardized Streamflow Index (SSI) trends and the proportion (%) of dry and wet years, as well as drought monitoring indicators. Based on the Mann-Kendall (MK) trend test, the LRB is projected to experience reduced streamflow in both the near and the distant future. The basin is projected to experience frequent dry and wet conditions that can translate to drought and flash floods, respectively. In particular, a high proportion of dry and a few incidences of wet years are expected in the basin in the future. In general, the findings of this research study will inform and enhance climate change adaptation and mitigation policy decisions and implementation thereof, to sustain the livelihoods of vulnerable communities.
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Nedham, Usama Sameer, and Ahmed Sami Hassan. "Comparison of Some Drought Indices in Iraq." Al-Mustansiriyah Journal of Science 30, no. 4 (2020): 1. http://dx.doi.org/10.23851/mjs.v30i4.674.
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Drought in Iraq was assessed using three drought indices for two different time periods, past period from 1970 to 2015, and future period from 2016 to 2050 for 4 stations in Iraq. These indices named: the Standardized Precipitation Index (SPI), Percentage of Precipitation Anomaly (PPA), and Z-Score Index (ZSI). The main sources of data were the monthly rainfall archive from Iraqi Meteorological Organization and Seismology (IMOS) for past period, and projection monthly precipitation data from Representative Concentration Pathway scenario (RCP4.5) for Fifth Assessment Report (AR5) affiliate to the Intergovernmental Panel on Climate Change (IPCC) for future period. The results shown good correlation of among 3 indices, with different rank of them, were lowest rank was 0.85. The three indices refer to were good evaluate the drought severity of Iraq. Found too the best index was PPA during past period, and the significant index was ZSI for the future period. The North of Iraq (Mosul Station) was the least vulnerable to drought from the analysis of the results of the three indices for the last period, where the number of dry seasons were 12 on the basis of the PPA classification. South of Iraq (Basra station) has the highest number of wet season on the PPA rating were (15) season.
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Vishwakarma, Ankur, Mahendra Kumar Choudhary, and Mrityunjay Singh Chauhan. "Applicability of SPI and RDI for forthcoming drought events: a non-parametric trend and one way ANOVA approach." Journal of Water and Climate Change 11, S1 (2020): 18–28. http://dx.doi.org/10.2166/wcc.2020.042.
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Abstract Monthly, seasonal and annual trends of rainfall and temperature (both minimum and maximum) have been analyzed using the Mann–Kendall trend test (a non-parametric test) and Sen's slope estimator for Sagar division, India from 1988 to 2018. Sagar division is a drought-prone zone of Madhya Pradesh, India. The same analysis has been performed for two drought indices, the Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI). Both indices were calculated to see the trend in the drought for 35 rain-gauge stations belonging to the study area. The study revealed that the minimum temperature had increased more than the maximum temperature in the last 31 years. The strong similarity in the results of Sen's slope of SPI and RDI were seen for both significant and non-significant trends. Analysis of variance (ANOVA) testing validates the substantial similarity between SPI and RDI based on Sen's slope. It also indicated the suitability of RDI for future projection of drought using the general circulation models (GCMs) or regional climate models (RCMs) in meteorological drought as well as the agricultural drought category. In contrast, the SPI indicated the meteorological drought only. The distribution of trends of temperature and drought indices were presented using the kriging interpolation.
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Duong, Seyhakreaksmey, Layheang Song, and Rattana Chhin. "Precipitation Projection in Cambodia Using Statistically Downscaled CMIP6 Models." Climate 11, no. 12 (2023): 245. http://dx.doi.org/10.3390/cli11120245.
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The consequences of climate change are arising in the form of many types of natural disasters, such as flooding, drought, and tropical cyclones. Responding to climate change is a long horizontal run action that requires adaptation and mitigation strategies. Hence, future climate information is essential for developing effective strategies. This study explored the applicability of a statistical downscaling method, Bias-Corrected Spatial Disaggregation (BCSD), in downscaling climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and then applied the downscaled data to project the future condition of precipitation pattern and extreme events in Cambodia. We calculated four climate change indicators, namely mean precipitation changes, consecutive dry days (CDD), consecutive wet days (CWD), and maximum one-day precipitation (rx1day) under two shared socioeconomic pathways (SSPs) scenarios, which are SSP245 and SSP585. The results indicated the satisfactory performance of the BCSD method in capturing the spatial feature of orographic precipitation in Cambodia. The analysis of downscaled CMIP6 models shows that the mean precipitation in Cambodia increases during the wet season and slightly decreases in the dry season, and thus, there is a slight increase in annual rainfall. The projection of extreme climate indices shows that the CDD would likely increase under both climate change scenarios, indicating the potential threat of dry spells or drought events in Cambodia. In addition, CWD would likely increase under the SSP245 scenario and strongly decrease in the eastern part of the country under the SSP585 scenario, which inferred that the wet spell would have happened under the moderate scenario of climate change, but it would be the opposite under the SSP585 scenario. Moreover, rx1day would likely increase over most parts of Cambodia, especially under the SSP585 scenario at the end of the century. This can be inferred as a potential threat to extreme rainfall triggering flood events in the country due to climate change.
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Gautam, Sagar, Christine Costello, Claire Baffaut, Allen Thompson, and E. John Sadler. "Projection of future drought and extreme events occurrence in Goodwater Creek Experimental Watershed, Midwestern US." Hydrological Sciences Journal 66, no. 6 (2021): 1045–58. http://dx.doi.org/10.1080/02626667.2021.1906878.
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