Global Sensitivity Analysis of the Standardized Precipitation Evapotranspiration Index at Different Time Scales in Jilin Province, China

Chen, Taotao; Chi, Daocai

doi:10.3390/su12051713

Cited by 8 publications

(6 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, these limitations were addressed by the development of the standardized precipitation evapotranspiration index (SPEI) [22]. The following literature extensively summarizes recent SPEI based studies at a regional scale, temporal scale, types of datasets used and statistical method used [23][24][25][26][27][28][29][30][31][32][33][34][35][36]. Using different drought indices, most of these studies revealed that SPEI is most sensitive to drought conditions due to the evaporative demand component (as demonstrated in potential evapotranspiration (PET)) indicating SPEI importance as a favorable drought index.…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Analysis of Drought Variability in Myanmar Based on the Standardized Precipitation Evapotranspiration Index (SPEI) and Its Impact on Crop Production

et al. 2021

View full text Add to dashboard Cite

Drought research is an important aspect of drought disaster mitigation and adaptation. For this purpose, we used the Standardized Precipitation Evapotranspiration Index (SPEI) to investigate the spatial-temporal pattern of drought and its impact on crop production. Using monthly precipitation (Precip) and temperature (Temp) data from 1986–2015 for 39 weather stations, the drought index was obtained for the time scale of 3, 6, and 12 months. The Mann–Kendall test was used to determine trends and rates of change. Precip and Temp anomalies were investigated using the regression analysis and compared with the drought index. The link between drought with large-scale atmospheric circulation anomalies using the Pearson correlation coefficient (R) was explored. Results showed a non-uniform spatial pattern of dryness and wetness which varied across Myanmar agro-ecological zones and under different time scales. Generally, results showed an increasing trend for the SPEI in the three-time scales, signifying a high tendency of decreased drought from 1986–2015. The fluctuations in dryness/wetness might linked to reduction crop production between 1986–1999 and 2005, 2008, 2010, 2013 cropping years. Results show relationship between main crops production and climate (teleconnection) factors. However, the low correlation values (i.e., <0.49) indicate the extent of the relationship within the natural variability. However, readers are urged to interpret this result cautiously as reductions in crop production may also be affected by other factors. We have demonstrated droughts evolution and trends using weather stations, thus providing useful information to aid policymakers in developing spatially relevant climate change adaptation and mitigation management plans for Myanmar.

show abstract

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Analysis of Drought Variability in Myanmar Based on the Standardized Precipitation Evapotranspiration Index (SPEI) and Its Impact on Crop Production

et al. 2021

View full text Add to dashboard Cite

show abstract

“…According to the appropriate search function, model y = f (X) can be converted into y = f (s) and obtained with Fourier transform [58,59].…”

Section: Efast Analysis Methodsmentioning

confidence: 99%

Parameter Sensitivity Analysis of SWAT Modeling in the Upper Heihe River Basin Using Four Typical Approaches

Xiang

Xiao

et al. 2022

Applied Sciences

View full text Add to dashboard Cite

Parameter sensitivity analysis is a significant part of quantifying model uncertainty, effectively identifying key parameters, and improving the efficiency of parameter optimization. The Soil and Water Assessment Tool (SWAT) model was applied to the upper Heihe River basin (UHRB) in China to simulate the monthly runoff for 11 years (1990–2000). Four typical sensitivity analyses, namely, the Morris screening, Sobol analysis, Fourier amplitude sensitivity test (FAST), and extended Fourier amplitude sensitivity test (EFAST), were used to determine the critical parameters affecting hydrological processes. The results show that the sensitivity parameters defined by the four methods were significantly different, resulting in a specific difference in the simulation effect of the SWAT model. The reason may be the different sampling process, sensitivity index, and calculation principle of each method. The snow-melt base temperature (SMTMP) and snowfall temperature (SFTMP) related to the snow-melt process, the available water capacity of the soil layer (SOL_AWC), saturated hydraulic conductivity (SOL_K), depth from the soil surface to the bottom of the layer (SOL_Z), moist bulk density (SOL_BD), deep aquifer percolation fraction (RCHRG_DP), and threshold depth of water in the shallow aquifer required for return flow to occur (GWQMN) related to the soil water and groundwater movement, baseflow alpha factor for bank storage (ALPHA_BNK) related to the base flow regression, and average slope steepness (HRU_SLP) are all very sensitive parameters. The 10 key parameters were optimized 100 times with the sequential uncertainty fitting procedure version 2 (SUFI-2). The Nash–Sutcliffe efficiency coefficient (NSE), Kling–Gupta efficiency coefficient (KGE), mean square error (MSE), and percentage bias (PBIAS) were 0.89, 200, 8.60, and 0.90, respectively. The simulation results are better than optimizing the sensitive parameters defined by the single method and all the selected parameters. The differences illustrate the rationality and importance of parameter sensitivity analysis for hydrological models and the synthesis of multiple approaches to define sensitive parameters. These conclusions have reference significance in the parameter optimization of the SWAT model when studying alpine rivers by constructing the SWAT model.

show abstract

“…where C 0 = 2.515517, C 1 = 0.802853, C 2 = 0.010328, d 1 = 1.432788, d 2 = 0.189269, and d 3 = 0.001308 [12,52,53].…”

Section: Speimentioning

confidence: 99%

Assessment of Two Drought Indices to Quantify and Characterize Drought Incidents: A Case Study of the Northern Part of Burundi

Ndayiragije

Nkunzimana

2022

Atmosphere

View full text Add to dashboard Cite

Droughts are natural catastrophes that cost the health and wealth of humans due to their harmful effects on the natural environment, ecology, hydrology, and agriculture in particular. Droughts are recurring incidents that last for prolonged periods of time in the northern part of Burundi. Despite the region being prone to drought and often suffering from dry conditions, drought has not been widely investigated. For the quantification and characterization of dryness conditions, this research utilized two drought indices, the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Precipitation Index (SPI), at 2-, 6-, 24-, and 48-month timescales, where 2-, 6-, 24-, and 48-months correspond to agricultural and hydrological droughts, respectively. The two drought indices were compared, and the difference between SPEI and SPI was illustrated by quantifying and characterizing drought incidents. The findings revealed that different types of droughts threatened the northern part of Burundi during the periods of 1993–2000 and 2002–2009. Both indices illustrated that 2005, 2006, and 2007 were extremely dry years. The drought incidents detected by the SPEI index were classified into moderate and severe categories, characterized by long duration and greater magnitude. In contrast, the drought incidents detected by SPI were classified into the “extremely dry” category, characterized by limited duration and lower magnitude but with higher intensities. This research highlighted that SPEI differs from SPI in quantifying and characterizing droughts and highly suggests the use of both SPEI and SPI when assessing droughts. The outcome of this study will be useful in drought prevention and mitigation strategies across Burundi, specifically for agricultural purposes.

show abstract

Global Sensitivity Analysis of the Standardized Precipitation Evapotranspiration Index at Different Time Scales in Jilin Province, China

Cited by 8 publications

References 56 publications

Spatio-Temporal Analysis of Drought Variability in Myanmar Based on the Standardized Precipitation Evapotranspiration Index (SPEI) and Its Impact on Crop Production

Spatio-Temporal Analysis of Drought Variability in Myanmar Based on the Standardized Precipitation Evapotranspiration Index (SPEI) and Its Impact on Crop Production

Parameter Sensitivity Analysis of SWAT Modeling in the Upper Heihe River Basin Using Four Typical Approaches

Assessment of Two Drought Indices to Quantify and Characterize Drought Incidents: A Case Study of the Northern Part of Burundi

Contact Info

Product

Resources

About