scholarly journals Future drought analysis using SPI and EDDI to consider climate change in South Korea

2020 ◽  
Vol 20 (8) ◽  
pp. 3266-3280
Author(s):  
Jeongeun Won ◽  
Sangdan Kim
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Standardized Precipitation Index ◽  
Drought Indices ◽  
Drought Severity ◽  
Climate Change Scenarios ◽  
Climate Data ◽  
Evaporative Demand ◽  
The Standardized Precipitation Index ◽  
The Impact

Abstract Prediction of drought is important for efficient water management, as the occurrence of droughts affects large areas over a long period. According to various climate change scenarios, it is reported that in the future, Korea's climate is likely to increase in temperature with increasing rainfall. This increase in temperature will have a big impact on evapotranspiration. The occurrence of drought begins mainly with two causes: lack of rainfall or an increase in evapotranspiration. Therefore, in this study, the impact of climate change on future droughts is revealed through the Standardized Precipitation Index (SPI) and the Evaporative Demand Drought Index (EDDI). These two drought indices with different characteristics are used to examine the trend of future drought, and a drought Severity-Duration-Frequency (SDF) curve was derived to quantitatively analyze the depth of future drought. Future droughts are projected by applying future climate data generated from various climate models.

scholarly journals The Assessment of Climate Change Impact on Meteorological Draught Susceptability on Sampean Watershed

2021 ◽  
Vol 9 (4) ◽  
pp. 146
Author(s):  
Masita Ratih ◽  
Gusfan Halik ◽  
Retno Utami Agung Wiyono
Keyword(s):  
Climate Change ◽  
Atmospheric Circulation ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Assessment Method ◽  
Precipitation Index ◽  
Climate Change Scenarios ◽  
Change Impact ◽  
The Standardized Precipitation Index ◽  
The Impact

Drought disasters that occur in the Sampean watershed from time to time have increased, both the intensity of events and the area affected by drought. The general objective of this research is to develop an assessment method for the impact of climate chan ge on vulnerability to drought disasters based on atmospheric circulation data. The specific objectives of this study are to model rainfall predictions based on atmospheric circulation data, predict rainfall in various climate change scenarios (Intergovernm ental Panel on Climate Change, IPCC – AR5), and assess vulnerability to drought disasters using a meteorological approach. The Standardized Precipitation Index (SPI) is one way to analyze the drought index in an area which was developed previous researcher. The Standardized Precipitation Index (SPI) is designed to quantitatively determine the rainfall deficit with various time scales. The advantage of the Standardized Precipitation Index (SPI) is that it is enough to use monthly rainfall data to compare drou ght levels between regions even with different climate types. To facilitate the presentation of the data base on the identification of d rought susceptibility, we need a system that can assist in building, storing, managing and displaying geographically ref erenced information in the form of spatial mapping. This research facilitates monitoring of the area of drought-prone areas, predicts drought levels, prevents future drought disasters, and prepares plans for rebuilding drought-prone areas in the Sampean watershed.

scholarly journals Variabilidad espacio-temporal de las sequías en la cuenca Pacífico Norte de México (1961-2010)

2016 ◽  
Vol 42 (1) ◽  
pp. 185 ◽  
Author(s):  
L. Serrano-Barrios ◽  
S. M. Vicente-Serrano ◽  
H. Flores-Magdaleno ◽  
L. Tijerina-Chávez ◽  
D. Vázquez-Soto
Keyword(s):  
Standardized Precipitation Index ◽  
Maximum Temperature ◽  
Drought Indices ◽  
Drought Severity ◽  
Evaporative Demand ◽  
The North ◽  
Weather Stations ◽  
Potential Impact ◽  
Spatio Temporal ◽  
The Standardized Precipitation Index

This article analyses the spatio-temporal variability of droughts in the North Pacific Basin of México between 1961 and 2010, using two drought indices: the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). We used data from 48 weather stations with available data of precipitation and monthly minimum and maximum temperature. In 22 of the weather stations, time series of Piché evaporation were also available. The reference evapotranspiration, necessary to obtain the SPEI, was calculated by means of the Hargreaves equation. Results show that major droughts occurred in the 1980s and 2000s, although there is a noticeable spatial variability across the region. Finally, the potential impact of the atmospheric evaporative demand on drought severity observed by the different drought indices is discussed, and the possible implications for an appropriate risk assessment.

scholarly journals Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part II: Climate Change Impact Assessment)

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1548
Author(s):  
Suresh Marahatta ◽  
Deepak Aryal ◽  
Laxmi Prasad Devkota ◽  
Utsav Bhattarai ◽  
Dibesh Shrestha
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Climate Models ◽  
Assessment Tool ◽  
Swat Model ◽  
Global Climate Models ◽  
Climate Data ◽  
The Future ◽  
The Impact ◽  
Mountainous River

This study aims at analysing the impact of climate change (CC) on the river hydrology of a complex mountainous river basin—the Budhigandaki River Basin (BRB)—using the Soil and Water Assessment Tool (SWAT) hydrological model that was calibrated and validated in Part I of this research. A relatively new approach of selecting global climate models (GCMs) for each of the two selected RCPs, 4.5 (stabilization scenario) and 8.5 (high emission scenario), representing four extreme cases (warm-wet, cold-wet, warm-dry, and cold-dry conditions), was applied. Future climate data was bias corrected using a quantile mapping method. The bias-corrected GCM data were forced into the SWAT model one at a time to simulate the future flows of BRB for three 30-year time windows: Immediate Future (2021–2050), Mid Future (2046–2075), and Far Future (2070–2099). The projected flows were compared with the corresponding monthly, seasonal, annual, and fractional differences of extreme flows of the simulated baseline period (1983–2012). The results showed that future long-term average annual flows are expected to increase in all climatic conditions for both RCPs compared to the baseline. The range of predicted changes in future monthly, seasonal, and annual flows shows high uncertainty. The comparative frequency analysis of the annual one-day-maximum and -minimum flows shows increased high flows and decreased low flows in the future. These results imply the necessity for design modifications in hydraulic structures as well as the preference of storage over run-of-river water resources development projects in the study basin from the perspective of climate resilience.

scholarly journals Long-Term, Gridded Standardized Precipitation Index for Hawai‘i

Data ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 109
Author(s):  
Matthew P. Lucas ◽  
Clay Trauernicht ◽  
Abby G. Frazier ◽  
Tomoaki Miura
Keyword(s):  
High Spatial Resolution ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Drought Indices ◽  
Drought Severity ◽  
Spatially Explicit ◽  
Historical Period ◽  
The Standardized Precipitation Index ◽  
Climatic Information

Spatially explicit, wall-to-wall rainfall data provide foundational climatic information but alone are inadequate for characterizing meteorological, hydrological, agricultural, or ecological drought. The Standardized Precipitation Index (SPI) is one of the most widely used indicators of drought and defines localized conditions of both drought and excess rainfall based on period-specific (e.g., 1-month, 6-month, 12-month) accumulated precipitation relative to multi-year averages. A 93-year (1920–2012), high-resolution (250 m) gridded dataset of monthly rainfall available for the State of Hawai‘i was used to derive gridded, monthly SPI values for 1-, 3-, 6-, 9-, 12-, 24-, 36-, 48-, and 60-month intervals. Gridded SPI data were validated against independent, station-based calculations of SPI provided by the National Weather Service. The gridded SPI product was also compared with the U.S. Drought Monitor during the overlapping period. This SPI product provides several advantages over currently available drought indices for Hawai‘i in that it has statewide coverage over a long historical period at high spatial resolution to capture fine-scale climatic gradients and monitor changes in local drought severity.

scholarly journals Climate Change Impact on the Frequency of Hydrometeorological Extremes in the Island of Crete

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 587 ◽  
Author(s):  
Evdokia Tapoglou ◽  
Anthi Vozinaki ◽  
Ioannis Tsanis
Keyword(s):  
Climate Change ◽  
Frequency Analysis ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Regional Climate ◽  
Standardized Precipitation Index ◽  
Hydrological Drought ◽  
Drought Indices ◽  
Rcp Scenarios ◽  
The Impact

Frequency analysis on extreme hydrological and meteorological events under the effect of climate change is performed in the island of Crete. Data from Regional Climate Model simulations (RCMs) that follow three Representative Concentration Pathways (RCP2.6, RCP4.5, RCP8.5) are used in the analysis. The analysis was performed for the 1985–2100 time period, divided into three equal-duration time slices (1985–2010, 2025–2050, and 2075–2100). Comparison between the results from the three time slices for the different RCMs under different RCP scenarios indicate that drought events are expected to increase in the future. The meteorological and hydrological drought indices, relative Standardized Precipitation Index (SPI) and Standardized Runoff index (SRI), are used to identify the number of drought events for each RCM. Results from extreme precipitation, extreme flow, meteorological and hydrological drought frequency analysis over Crete show that the impact of climate change on the magnitude of 100 years return period extreme events will also increase, along with the magnitude of extreme precipitation and flow events.

scholarly journals Evaluating Uncertainties in the Projection of Future Drought

2008 ◽  
Vol 9 (2) ◽  
pp. 292-299 ◽  
Author(s):  
Eleanor J. Burke ◽  
Simon J. Brown
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Climate Modeling ◽  
Standardized Precipitation Index ◽  
Severity Index ◽  
Ensemble Member ◽  
Drought Indices ◽  
Drought Severity ◽  
Hadley Centre ◽  
The Standardized Precipitation Index

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.

scholarly journals Reference crop evapotranspiration database in Spain (1961–2014)

2019 ◽  
Vol 11 (4) ◽  
pp. 1917-1930 ◽  
Author(s):  
Miquel Tomas-Burguera ◽  
Sergio M. Vicente-Serrano ◽  
Santiago Beguería ◽  
Fergus Reig ◽  
Borja Latorre
Keyword(s):  
Climate Models ◽  
Severity Index ◽  
Important Variable ◽  
Drought Indices ◽  
Drought Severity ◽  
Climate Variables ◽  
Evaporative Demand ◽  
Research Areas ◽  
Climate Studies ◽  
Reference Crop

Abstract. Obtaining climate grids describing distinct variables is important for developing better climate studies. These grids are also useful products for other researchers and end users. The atmospheric evaporative demand (AED) may be measured in terms of the reference evapotranspiration (ETo), a key variable for understanding water and energy terrestrial balances and an important variable in climatology, hydrology and agronomy. Despite its importance, the calculation of ETo is not commonly undertaken, mainly because datasets consisting of a high number of climate variables are required and some of the required variables are not commonly available. To address this problem, a strategy based on the spatial interpolation of climate variables prior to the calculation of ETo using FAO-56 Penman–Monteith equation was followed to obtain an ETo database for continental Spain and the Balearic Islands, covering the 1961–2014 period at a spatial resolution of 1.1 km and at a weekly temporal resolution. In this database, values for the radiative and aerodynamic components as well as the estimated uncertainty related to ETo were also provided. This database is available for download in the Network Common Data Form (netCDF) at https://doi.org/10.20350/digitalCSIC/8615 (Tomas-Burguera et al., 2019). A map visualization tool (http://speto.csic.es, last access: 10 December 2019) is available to help users download the data corresponding to one specific point in comma-separated values (csv) format. A relevant number of research areas could take advantage of this database. For example, (i) studies of the Budyko curve, which relates rainfall data to the evapotranspiration and AED at the watershed scale, (ii) calculations of drought indices using AED data, such as the Standardized Precipitation–Evapotranspiration Index (SPEI) or Palmer Drought Severity Index (PDSI), (iii) agroclimatic studies related to irrigation requirements, (iv) validation of climate models' water and energy balance, and (v) studies of the impacts of climate change in terms of the AED.

Seasonal and Long-Term Changes to Pavement Life Caused by Rising Temperatures from Climate Change

2019 ◽  
Vol 2673 (6) ◽  
pp. 267-278 ◽  
Author(s):  
Jayne F. Knott ◽  
Jo E. Sias ◽  
Eshan V. Dave ◽  
Jennifer M. Jacobs
Keyword(s):  
Climate Change ◽  
Temperature Rise ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Climate Change Scenarios ◽  
Top Down ◽  
Bottom Up ◽  
Pavement Damage ◽  
The Impact

Pavements are vulnerable to reduced life with climate-change-induced temperature rise. Greenhouse gas emissions have caused an increase in global temperatures since the mid-20th century and the warming is projected to accelerate. Many studies have characterized this risk with a top-down approach in which climate-change scenarios are chosen and applied to predict pavement-life reduction. This approach is useful in identifying possible pavement futures but may miss short-term or seasonal pavement-response trends that are essential for adaptation planning. A bottom-up approach focuses on a pavement’s response to incremental temperature change resulting in a more complete understanding of temperature-induced pavement damage. In this study, a hybrid bottom-up/top-down approach was used to quantify the impact of changing pavement seasons and temperatures on pavement life with incremental temperature rise from 0 to 5°C at a site in coastal New Hampshire. Changes in season length, seasonal average temperatures, and temperature-dependent resilient modulus were used in layered-elastic analysis to simulate the pavement’s response to temperature rise. Projected temperature rise from downscaled global climate models was then superimposed on the results to determine the timing of the effects. The winter pavement season is projected to end by mid-century, replaced by a lengthening fall season. Seasonal pavement damage, currently dominated by the late spring and summer seasons, is projected to be distributed more evenly throughout the year as temperatures rise. A 7% to 32% increase in the asphalt-layer thickness is recommended to protect the base and subgrade with rising temperatures from early century to late-mid-century.

Flash Drought in CMIP5 Models

2021 ◽  
Author(s):  
David Hoffmann ◽  
Ailie J. E. Gallant ◽  
Mike Hobbins
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Climate Models ◽  
Standardized Precipitation Index ◽  
Rapid Onset ◽  
Stress Index ◽  
Cmip5 Models ◽  
Drought Indices ◽  
Similar Proportion ◽  
Evaporative Demand

Abstract‘Flash drought’ (FD) describes the rapid onset of drought on sub-seasonal times scales. It is of particular interest for agriculture as it can deplete soil moisture for crop growth in just a few weeks. To better understand the processes causing FD, we evaluate the importance of evaporative demand and precipitation by comparing three different drought indices that estimate this hazard using meteorological and hydrological parameters from the CMIP5 suite of models. We apply the Standardized Precipitation Index (SPI); the Evaporative Demand Drought Index (EDDI), derived from evaporative demand (E0); and the Evaporative Stress Index (ESI), which connects atmospheric and soil moisture conditions by measuring the ratio of actual and potential evaporation. The results show moderate-to-strong relationships (r2 > 0.5) between drought indices and upper level soil moisture on daily time scales, especially in drought-prone regions. We find that all indices are able to identify FD in the top 10-cm layer of soil moisture in a similar proportion to that in the models’ climatologies. However, there is significant inter-model spread in the characteristics of the FDs identified. This spread is mainly caused by an overestimation of E0, indicating stark differences in the land surface models and coupling in individual CMIP5 models. Of all indices, the SPI provides the highest skill in predicting FD prior to or at the time of onset in soil moisture, while both EDDI and ESI show significantly lower skill. The results highlight that the lack of precipitation is the main contributor to FDs in climate models, with E0 playing a secondary role.

scholarly journals Assessing the Impact of Projected Climate Change on Zoo Visitation in Toronto (Canada)

2016 ◽  
Vol 8 (2) ◽  
pp. 30 ◽  
Author(s):  
Micah J. Hewer ◽  
William A. Gough
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Positive Impact ◽  
Global Climate ◽  
Global Climate Models ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Intergovernmental Panel ◽  
Local Climate ◽  
The Impact

Weather and climate have been widely recognised as having an important influence on tourism and recreational activities. However, the nature of these relationships varies depending on the type, timing and location of these activities. Climate change is expected to have considerable and diverse impacts on recreation and tourism. Nonetheless, the potential impact of climate change on zoo visitation has yet to be assessed in a scientific manner. This case study begins by establishing the baseline conditions and statistical relationship between weather and zoo visitation in Toronto, Canada. Regression analysis, relying on historical weather and visitation data, measured at the daily time scale, formed the basis for this analysis. Climate change projections relied on output produced by Global Climate Models (GCMs) for the Intergovernmental Panel on Climate Change’s 2013 Fifth Assessment Report, ranked and selected using the herein defined Selective Ensemble Approach. This seasonal GCM output was then used to inform daily, local, climate change scenarios, generated using Statistical Down-Scaling Model Version 5.2. A series of seasonal models were then used to assess the impact of projected climate change on zoo visitation. While accounting for the negative effects of precipitation and extreme heat, the models suggested that annual visitation to the zoo will likely increase over the course of the 21st century due to projected climate change: from +8% in the 2020s to +18% by the 2080s, for the least change scenario; and from +8% in the 2020s to +34% in the 2080s, for the greatest change scenario. The majority of the positive impact of projected climate change on zoo visitation in Toronto will likely occur in the shoulder season (spring and fall); with only moderate increases in the off season (winter) and potentially negative impacts associated with the peak season (summer), especially if warming exceeds 3.5 °C.

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