Meteorological and Hydrological Drought Assessment for Dong Nai River Basin, Vietnam under Climate Change

Linh, Vu Thuy; Tram, Vo Ngoc Quynh; Dung, Ho Minh; Phuong, Dang Nguyen Dong; Liem, Nguyen Duy; Nguyen, Long D.; Chao, Yin; Kortun, Ayse; Lợi, Nguyễn Kim

doi:10.1007/s11036-021-01757-x

Cited by 9 publications

(3 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many studies on drought evaluation in the VMD have been conducted utilizing meteorological drought indices (Phan et al 2020;Minh et al 2022a;Lavane et al 2023), agricultural drought indices (Tran et al 2019;Minh et al 2022a), and hydrological drought indices (Van Binh et al 2020;Xuan et al 2022). The streamflow drought index (SDI), has also been widely applied in Vietnam (Le 2017;Linh et al 2021;Lavane et al 2023), India (Malik et al 2019(Malik et al , 2021, Taiwan (Yeh et al 2015), Greece (Nalbantis 2008), Iran (Tabari et al 2013;Sardou and Bahremand 2014), and China (Hong et al 2015). Yeh (Yeh et al 2015) revealed that the SDI could be used successfully to predict significant droughts in Northern Taiwan for periods of three months (November to January) and six months (November to April) (Yeh et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Deciphering the relationship between meteorological and hydrological drought in Ben Tre province, Vietnam

Minh,

Kumar,

Van Toan

et al. 2024

Nat Hazards

View full text Add to dashboard Cite

The low-lying Vietnamese Mekong Delta (VMD) is a key agricultural production landscape increasingly threatened by anthropogenic stresses and climate change. Droughts due to extreme events, climate change and upstream developments affect the delta. This paper explores the relationship between the intensity, duration, and frequency of meteorological droughts and hydrological droughts using a range of indices. We used monthly rainfall and stream flow data for the period 1992-2021 to calculate the stream flow Drought Index (SDI), the Standardized Precipitation Index (SPI), and the Reconnaissance Drought Index (RDI) for different time intervals. We found no observed time lag, and a strong correlation coefficient between upstream hydrological and downstream meteorological drought events assessed over long-term scales (i.e.,12-months). This is true for all downstream sites, except Ben Tre City. Meteorological drought events onset lagged 5-6 months, 6-month, and 4-month behind hydrological droughts at mid-and shorter assessment time scales (9-,6-, 3-month). Average correlation coefficient between hydrological indices and SPI and 9-3 month time scales ranged only from moderate to weak. These findings shed light and advance the understanding of the progression of meteorological to hydrological droughts in the VMD. Our results aid the regional understanding of drought onset and the causative mechanism at work, important for both medium and long-term drought forecasting and adaptation planning.

show abstract

Section: Introductionmentioning

confidence: 99%

Deciphering the relationship between meteorological and hydrological drought in Ben Tre province, Vietnam

Minh,

Kumar,

Van Toan

et al. 2024

Nat Hazards

View full text Add to dashboard Cite

show abstract

“…2). According to the classification standard of the World Meteorological Organization, definitions of drought are clustered to four types: meteorological, agricultural, hydrological, and socio-economic [2,3]. Among them, meteorological drought is the main cause of agricultural drought.…”

Section: Introductionmentioning

confidence: 99%

A New Agricultural Drought Disaster Risk Assessment Framework: Coupled a Copula Function to Select Return Periods and the Jensen Model to Calculate Yield Loss

Liu

Pan

et al. 2023

Sustainability

View full text Add to dashboard Cite

China is one of the regions with the most frequent drought disasters and serious social and economic losses. Agricultural drought loss is one the most serious natural disasters. Due to climate change, the regional agricultural drought risk assessment has always been the focus of the academic circle. This study takes Zunyi City as an example, which is the most typical City of karst landform development. The monthly precipitation data set of ground meteorological observation stations in Zunyi City from 1956 to 2020 was selected, and the drought characteristic variables were extracted by the coupled use of the precipitation anomaly percentage (Pa) index and the theory of runs. The Copula function was applied to establish the joint distribution model of characteristic variables, obtaining the drought frequency and drought return periods. Combined with the Jensen model, the agricultural drought loss rate under different drought return periods in the target year (2020) was calculated and evaluated. The results showed that the Gumbel-Hougaard copula function was suitable for the joint distribution of drought joint variables in Zunyi City. From 1956 to 2020, fewer droughts occurred in Zhengan and Wuchuan, and the most droughts took place in Fenggang, Meitan, and Yuqing. The average drought duration in each county was about 1.5 months, and the average drought severity was about 0.35 in spatial distribution. Crop loss rate caused by drought increased and the affected area expanded with the increase of drought return periods (5, 10, 20, 50, and 100 years) in temporal distribution. Meanwhile, the drought disaster was most drastic in the eastern region, followed by the south, north, west, and central area. The results were highly consistent with the historical drought in Zunyi City, which verified the validity of the model. This study could provide scientific knowledge for drought resistance and reasonable mitigation programing for the security of the regional agricultural production and the sustainability of social and economic development.

show abstract

“…The Soil and Water Assessment Tool (SWAT) is a widely used hydrological model that has had successful application in many fields [31][32][33][34]. The SWAT model has many parameters, rendering calibrating the parameters time-consuming and laborious.…”

Section: Introductionmentioning

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

Meteorological and Hydrological Drought Assessment for Dong Nai River Basin, Vietnam under Climate Change

Cited by 9 publications

References 23 publications

Deciphering the relationship between meteorological and hydrological drought in Ben Tre province, Vietnam

Deciphering the relationship between meteorological and hydrological drought in Ben Tre province, Vietnam

A New Agricultural Drought Disaster Risk Assessment Framework: Coupled a Copula Function to Select Return Periods and the Jensen Model to Calculate Yield Loss

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

Contact Info

Product

Resources

About