Characterization of drought in the Kerio Valley Basin, Kenya using the Standardized Precipitation Evapotranspiration Index: 1960−2016

Kimosop, Peter

doi:10.1111/sjtg.12270

Cited by 5 publications

(4 citation statements)

References 53 publications

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“…It is constructed from precipitation, temperature, and potential evapotranspiration and can be calculated on a variety of time scales [41]. Recently, SPEI has been widely used in many fields, such as climate change, environmental quality assessment, and drought assessment [42]. The key concept of SPEI is to describe the degree of drought in an area by calculating how far the difference between precipitation and potential evapotranspiration deviates from the average state.…”

Section: Standardized Precipitation Evapotranspiration Indexmentioning

confidence: 99%

Spatiotemporal Trends of Forest Carbon Stock and Its Response to Environmental Factors in the Yangtze River Basin during 2005–2020

Cao,

Chen,

et al. 2023

Forests

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It is of great significance to accurately assess the carbon sink capacity and trend of forest ecosystems on a regional scale, which is a key step to realizing sustainable forest management and carbon sink. Based on several remote sensing datasets, this study analyzes the dynamic characteristics of forest carbon stock in the Yangtze River Basin and its response to environmental factors using the Mann–Kendall nonparametric test, correlation analysis, and BP neural network during 2005–2020. The results show that forest carbon stock in the Yangtze River Basin shows a fluctuating upward trend, with an average annual growth rate of 0.91%. Forest carbon stock in western high-altitude areas and areas with high human activity in the east showed a downward trend, while the central plains showed a stable growth trend. In the vast plains of the Yangtze River Basin, a suitable drought degree (−0.5 < SPEI < 0.5) is helpful to the accumulation of forest carbon reserves. In the future, rich forest resources should be fully developed to promote synergy between environmental protection and economic development from the perspective of developing green carbon trading, such as the carbon-sink forestry projects of CCER.

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Section: Standardized Precipitation Evapotranspiration Indexmentioning

confidence: 99%

Spatiotemporal Trends of Forest Carbon Stock and Its Response to Environmental Factors in the Yangtze River Basin during 2005–2020

Cao,

Chen,

et al. 2023

Forests

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“…However, due to the different subjects and purposes, researchers have proposed numerous drought indices. As listed in the technical report of the World Meteorological Organization (WMO, 1975;2016), there are as many as 58 drought indices from different countries (Wang et al, 2019). Among the many indices, the PDSI (Palmer, 1965), SPI (McKee et al, 1993), and SPEI (Vicente-Serrano et al, 2010a) are widely used.…”

Section: Speimentioning

confidence: 99%

“…Drought can typically be characterized by four characteristics: duration, severity, intensity, and frequency (Mishra and Singh, 2010;Kimosop, 2019). The calculation methods are as follows: Zero was used as the criterion to determine whether drought occurred in this study (as shown in Table 1); i.e., when the SPEI was less than 0, this value indicated the occurrence of drought.…”

Section: Characteristics Of Droughtmentioning

confidence: 99%

Zonal Patterns of Meteorological Drought on the Yunnan-Guizhou Plateau, China

Wang

Yang³

2021

Front. Environ. Sci.

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Drought is a natural phenomenon caused by a shortage of water resources and has a great impact on agriculture, the economy, and the environment. To study the Spatio-temporal distribution and explore the zonal patterns of drought, this paper took the Yunnan-Guizhou Plateau (YGP) as the research region, selected the air temperature, relative humidity, sunshine duration, wind speed, and precipitation data from 47 meteorological stations on the YGP. First, the standardized precipitation evapotranspiration index (SPEI) was calculated, and then the Spatio-temporal distribution of YGP drought was analyzed with the SPEI, Mann–Kendall test, and principal component analysis (PCA). Finally, the correlations between the average SPEI, drought characteristics extracted from the SPEI, and longitude/elevation/latitude were analyzed with the linear regression method, and then the zonal patterns of the YGP drought were obtained. The results revealed that the annual and seasonal SPEI values mainly decreased. Because the first component of the SPEI (the largest eigenvalue makes it the most important component) in annual and winter had a poor relationship with longitude/elevation, its correlation was weak, while the average SPEI values in other seasons were significantly correlated with longitude/elevation (α = 0.001), and the absolute value of the correlation coefficient was between 0.6879–0.9453. Except for PC1 in annual and winter, PC1 and PC2 were significantly correlated with longitude/elevation (α = 0.001), and the absolute value of the correlation coefficient was between 0.5087–0.9501. The duration, severity, intensity, frequency of drought were significantly correlated with longitude/elevation (α = 0.001) in most situations. The average SPEI values and drought characteristics showed a good multivariate linear correlation with longitude, latitude, and elevation, indicating that drought exhibited strong zonal patterns. This study will provide new ideas for drought research and technical support for regional industrial layouts, planting structure adjustments, and drought and disaster reduction.

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“…At present, SPEI is often estimated globally through station observations [12][13][14] or climate datasets released by climate research organizations [1,9,10,[15][16][17][18][19][20]. However, the detailed spatial patterns of SPEI cannot be obtained from these sources because of the current low densities of weather stations and the low spatial resolutions (e.g., >50 km per grid cell) of climate datasets [21,22].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Trends and Attribution of Drought across China from 1901–2100

2020

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Investigating long-term drought trends is of great importance in coping with the adverse effects of global warming. However, little attention has been focused on studying the detailed spatial variability and attribution of drought variation in China. In this study, we first generated a 1 km resolution monthly climate dataset for the period 1901–2100 across China using the delta spatial downscaling method to assess the variability of the Standardized Precipitation Evaporation Index (SPEI). We then developed a simple approach to quantifying the contributions of water supply (precipitation) and demand (potential evapotranspiration, PET) on SPEI variability, according to the meaning of the differentiating SPEI equation. The results indicated that the delta framework could accurately downscale and correct low-spatial-resolution monthly temperatures and precipitation from the Climatic Research Unit and general circulation models (GCMs). Of the 27 GCMs analyzed, the BNU-ESM, CESM1-CAM5, and GFDL-ESM2M were found to be the most accurate in modeling future temperatures and precipitation. We also found that, compared with the past (1901–2017), the climate in the future (2018–2100) will tend toward significant droughts, although both periods showed a high spatial heterogeneity across China. Moreover, the proportion of areas with significantly decreasing SPEI trends was far greater than the proportion of those with increasing trends in most cases, especially for northwestern and northern China. Finally, the proposed approach to quantifying precipitation and PET contributions performed well according to logical evaluations. The percentage contributions of precipitation and PET on SPEI variability varied with study periods, representative concentration pathway scenarios, trend directions, and geographic spaces. In the past, PET contributions for significant downward trends and precipitation contributions for significantly upward trends accounted for 95% and 72%, while their future contributions were 57 ± 22%–149 ± 20% and 95 ± 27%–190 ± 58%, respectively. Overall, our results provide detailed insights for planning flexible adaptation and mitigation strategies to cope with the adverse effects of climate drought across China.

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Characterization of drought in the Kerio Valley Basin, Kenya using the Standardized Precipitation Evapotranspiration Index: 1960−2016

Cited by 5 publications

References 53 publications

Spatiotemporal Trends of Forest Carbon Stock and Its Response to Environmental Factors in the Yangtze River Basin during 2005–2020

Spatiotemporal Trends of Forest Carbon Stock and Its Response to Environmental Factors in the Yangtze River Basin during 2005–2020

Zonal Patterns of Meteorological Drought on the Yunnan-Guizhou Plateau, China

Spatiotemporal Trends and Attribution of Drought across China from 1901–2100

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