Response of NDVI and SIF to Meteorological Drought in the Yellow River Basin from 2001 to 2020

Li, Jie; Xi, Mengfei; Pan, Ziwu; Liu, Zhenzhen; He, Zhiwei; Qin, Fen

doi:10.3390/w14192978

Cited by 13 publications

(9 citation statements)

References 52 publications

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“…With SPEI's time scale ranging from 1 to 48 months, it has a multi‐scale nature and currently spans from January 1901 to December 2020 (https://spei.csic.es/spei_database_2_7). SPEIbase v2.7, which outperforms the estimated Thornthwaite PET results, uses the FAO‐56 Penman‐Monteith model to calculate potential evapotranspiration (Li et al., 2022). Additionally, it was discovered that the SPEI drought index had a good capacity to track Pakistan's drought status (Adnan et al., 2018).…”

Section: Methodsmentioning

confidence: 99%

The Monsoon's Influence on Central Asia's Subsequent Periods of Drought and Flooding

Nzabarinda,

Bao,

Tie

et al. 2024

JGR Atmospheres

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Central Asia and its southern neighbors are being ravaged by more frequent and intense droughts and floods. While research on droughts is abundant, their interaction with floods and monsoons, especially when originating in the south, has been understudied. This study employed temperature, precipitation, standardized precipitation evapotranspiration index (SPEI), and agricultural drought indices such as water deficit index (WDI), cumulative water deficit (CWD), and Palmer drought severity index (PDSI) to investigate the role of monsoons in increasing drought and flooding in the southern part of central Asia, including Afghanistan and Pakistan, over a 31‐year period. Findings revealed increasing severity and intensity of droughts over time, along with their duration and peaks, contrasting with irregular fluctuations in flood intensity. Rising regional temperatures coincide with declining precipitation. During summer monsoon (SM), average precipitation ranged from 0.03 mm/day (2004) to 0.05 mm/day (2010), with variations across the region. The temperature varied between −14.35°C (2009) and 37.05°C (1991), with a sharp increase up to 0.114°C in Turkmenistan and Uzbekistan, as well as in northern Pakistan, Afghanistan, and western Tajikistan. A temperature drop during SM was revealed on the Mountains range of Himalaya, Hindu Kush, Karakoram, Parmir, Kunlun Shan and Tian Shan, and in Pakistan, down to −0.054°C. WDI showed a strong positive connection (0.71 and 0.64) with temperature (Tmax and Tmin) and a weak negative correlation (−0.5) with precipitation during normal time. However, during the monsoon season, it demonstrated a negative correlation with both within a no significant (−0.08) range for maximum temperature.

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Section: Methodsmentioning

confidence: 99%

The Monsoon's Influence on Central Asia's Subsequent Periods of Drought and Flooding

Nzabarinda,

Bao,

Tie

et al. 2024

JGR Atmospheres

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“…The trend of annual extreme heavy rainfall exhibits distinct regional differences, with a decrease in the duration of EPIs [27]. The YRB is a region sensitive to climate variations and is ecologically vulnerable [28]. Extreme climate events pose severe challenges to its water resources, ecological environment, and food security.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Variation in Extreme Climate in the Yellow River Basin and its Impacts on Vegetation Coverage

Li,

Xue,

Dong

et al. 2024

Forests

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Global warming and extreme climate events (ECEs) have grown more frequent, and it is essential to investigate the influences of ECEs on vegetation in the Yellow River Basin (YRB) and other environmentally fragile areas. This study was based on data from 86 meteorological stations in the YRB for the period 2000–2020. Twenty-five extreme climate indices (ECIs) were chosen, encompassing four dimensions: extreme value, intensity, duration, and frequency. The trend analysis approach was used to examine the spatiotemporal characteristics of extreme climate conditions. Additionally, geographical detectors and Pearson correlation analysis methods were employed to quantitatively assess the influence of ECEs on the Normalized Difference Vegetation Index (NDVI). The Multiscale Geographically Weighted Regression (MGWR) method was adopted to analyze the regression of twenty-five ECIs. The findings revealed the following: (1) Over the last 21 years, there has been a distinct rise in both the extreme precipitation indices (EPIs) and the extreme temperature indices (ETIs). (2) The spatial distribution of the NDVI throughout the year displayed the characteristic of being high in the south and low in the north. The annual NDVI demonstrated a noteworthy increase at a rate of 0.055/decade, with the enhancement encompassing an extensive area of 87.33%. (3) The investigation revealed that EPIs, including PRCPTOT, R10mm, CWD, R95p, and CDD, had explanatory values surpassing 0.4. This implied that the intensity, frequency, and duration of extreme precipitation played pivotal roles in steering vegetation alterations in the YRB. (4) The correlation between the EPIs and vegetation was greater than the ETIs. Grassland meadows exhibited greater sensitivity to precipitation than woody plants. The EPIs (excluding CDD and SDII) and the ETIs (TXn) displayed a substantial positive correlation with the NDVI in regions hosting grasslands, broadleaf forests, and shrubs. Desert vegetation and cultivated plants were less affected by ECEs. This study underscores the importance of the interplay between extreme climate and vegetation in the YRB. Additionally, it provides a scientific basis for formulating environmental safeguarding strategies.

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“…Frequent drought events are often accompanied by persistent or extreme heat, leading to decreased soil moisture and increased evapotranspiration. If vegetation is affected by prolonged drought, several aspects of its growth and development (e.g., seed germination, respiration, photosynthesis, nutrient cycling) are restricted ( Mohammat et al., 2013 ), and vegetation may brown ( Li et al., 2022 ), decrease in biomass ( Chen et al., 2022 ), or even die ( Castellaneta et al., 2022 ). Vegetation response to drought is characterized by reduced vigor and photosynthesis, resulting in a decrease in the carbon sink capacity of vegetation.…”

Section: Introductionmentioning

confidence: 99%

“…Conversely, reductions in carbon sinks and increases in carbon sources have an impact on climate and the carbon cycle, which in turn further exacerbate drought ( Reichstein et al., 2013 ). Vulnerability assessments of grassland drought stress under climate change have become a high-profile concern ( Li et al., 2022 ; Zeng et al., 2022 ). Quantifying the response of grassland vegetation to drought stress and identifying the areas most vulnerable to drought, as well as the types of grassland that respond most strongly to drought, are therefore critical to improving our understanding of the vulnerability of grasslands to climate change and taking appropriate measures to mitigate the effects of drought.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic assessment of drought stress vulnerability in grasslands of Xinjiang, China

et al. 2023

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In the process of climate warming, drought has increased the vulnerability of ecosystems. Due to the extreme sensitivity of grasslands to drought, grassland drought stress vulnerability assessment has become a current issue to be addressed. First, correlation analysis was used to determine the characteristics of the normalized precipitation evapotranspiration index (SPEI) response of the grassland normalized difference vegetation index (NDVI) to multiscale drought stress (SPEI-1 ~ SPEI-24) in the study area. Then, the response of grassland vegetation to drought stress at different growth periods was modeled using conjugate function analysis. Conditional probabilities were used to explore the probability of NDVI decline to the lower percentile in grasslands under different levels of drought stress (moderate, severe and extreme drought) and to further analyze the differences in drought vulnerability across climate zones and grassland types. Finally, the main influencing factors of drought stress in grassland at different periods were identified. The results of the study showed that the spatial pattern of drought response time of grassland in Xinjiang had obvious seasonality, with an increasing trend from January to March and November to December in the nongrowing season and a decreasing trend from June to October in the growing season. August was the most vulnerable period for grassland drought stress, with the highest probability of grassland loss. When the grasslands experience a certain degree of loss, they develop strategies to mitigate the effects of drought stress, thereby decreasing the probability of falling into the lower percentile. Among them, the highest probability of drought vulnerability was found in semiarid grasslands, as well as in plains grasslands and alpine subalpine grasslands. In addition, the primary drivers of April and August were temperature, whereas for September, the most significant influencing factor was evapotranspiration. The results of the study will not only deepen our understanding of the dynamics of drought stress in grasslands under climate change but also provide a scientific basis for the management of grassland ecosystems in response to drought and the allocation of water in the future.

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Response of NDVI and SIF to Meteorological Drought in the Yellow River Basin from 2001 to 2020

Cited by 13 publications

References 52 publications

The Monsoon's Influence on Central Asia's Subsequent Periods of Drought and Flooding

The Monsoon's Influence on Central Asia's Subsequent Periods of Drought and Flooding

Spatiotemporal Variation in Extreme Climate in the Yellow River Basin and its Impacts on Vegetation Coverage

Probabilistic assessment of drought stress vulnerability in grasslands of Xinjiang, China

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