Spatiotemporal variability and assessment of drought in the Wei River basin of China

Cai, Siyang; Zuo, Depeng; Xu, Zongxue; Han, Xinhui; Gao, Xiaoxi

doi:10.5194/piahs-379-73-2018

Cited by 9 publications

(3 citation statements)

References 27 publications

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“…The Vegetation Health Index was defined as combination of VCI and TCI. It has been widely used to detect drought in many Places (Cai S. et al,2018). VHI was proposed to address the limitations of VCI in areas with excessive soil wetness and/or long periods of cloudiness (Kogan F.N.…”

Section: Methodsmentioning

confidence: 99%

Trends Analysis of Agricultural Drought in Central Anatolian Basin, Turkey

Ergene,

Bektaş Balçık,

Balik Şanlı

2024

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Drought is a natural disaster that can have devastating economic, environmental, and social impacts on a global, national, and regional scale. Remote sensing technology is the most powerful tool to determine of drought categories and analyse drought severity, vulnerability and its trends. Because data that is temporal, quick, wide-area, and repeating can be obtained via remote sensing technologies. The calculation of drought indices with the use of remote sensing technology is crucial for assessing the severity of the drought and its evolution over time. In this study, the Central Anatolian Basin, one of Turkey's agricultural basins, was subjected to a temporal and spatial drought analysis between 2000 and 2023. In order to analyze the agricultural drought in the Central Anatolian Basin, drought indices such as Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Drought Index (NDDI), Vegetation Condition Index (VCI), Temperature condition index (TCI), Vegetation Health Index (VHI), Precipitation Condition Index (PCI), and Scaled Drought Condition Index (SDCI) were calculated. Moderate resolution Imaging Spectroradiometer (MODIS) data collection were used to calculate the NDVI, NDWI, NDDI VCI and TCI drought indices and PCI was calculated using the Climate Hazards Group Infrared Precipitation with Station CHIRPS data set. With the results obtained, the change in drought severity in the Central Anatolian Basin over the years was observed and drought severity, plant health status and surface temperature were compared. Additionally Temporal trend and Spatial trend of agricultural drought were determine using Sen’s slope and The Mann – Kendal non parametric test.

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Section: Methodsmentioning

confidence: 99%

Trends Analysis of Agricultural Drought in Central Anatolian Basin, Turkey

Ergene,

Bektaş Balçık,

Balik Şanlı

2024

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…The SPI can transform the skewness distribution to normal distribution, which is not only convenient for different data comparisons, but also can eliminate spatial and temporal distribution differences. At present, many studies have applied the SPI to characterize the meteorological arid conditions in the WRB and all have good results (Huang et al 2014a(Huang et al , 2014bCai et al 2018).…”

Section: Standardized Precipitation Indexmentioning

confidence: 99%

Propagation dynamics and causes of hydrological drought in response to meteorological drought at seasonal timescales

Huang

et al. 2021

Hydrology Research

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According to the widely accepted definition of drought, meteorological and hydrological droughts originally develop from rainfall and runoff deficits, respectively. Runoff deficit is mainly derived from rainfall deficit, and the propagation from meteorological drought to hydrological drought is critical for agricultural water management. Nevertheless, the characteristics and dynamics of drought propagation in the spatiotemporal scale remain unresolved. To this end, the characteristics and dynamics of drought propagation in different seasons and their linkages with key forcing factors are evaluated. In this study, meteorological and hydrological droughts are characterized by the Standardized Precipitation Index (SPI) and the Standardized Runoff Index (SRI), respectively. Propagation time is identified by the corresponding timescale of the maximum correlation coefficient between the SPI and the SRI. Then, a 20-year sliding window is adopted to explore the propagation dynamic in various seasons. Furthermore, the multiple linear regression model is established to quantitatively explore the influence of meteorological factors, underlying surface features and teleconnection factors on the propagation time variations. The Wei River Basin, a typical Loess Plateau watershed in China, is selected as a case study. Results indicate the following: (1) the propagation time from meteorological to hydrological drought is shorter in summer (2 months) and autumn (3 months), whereas it is longer in spring (8 months) and winter (13 months). Moreover, the propagation rates exhibit a decreasing trend in warm seasons, which, however, show an increasing trend in cold seasons; (2) a significant slowing propagation in autumn is mainly caused by the decreasing soil moisture and precipitation, whereas the non-significant tendency in summer is generally induced by the offset between insignificant increasing precipitation and significant decreasing soil moisture; (3) the replenishment from streamflow to groundwater in advance prompts the faster propagation from meteorological to hydrological drought in spring and winter and (4) teleconnection factors have strong influences on the propagation in autumn, in which Arctic Oscillation, El Niño-Southern Oscillation and Pacific Decadal Oscillation mainly affect participation, arid index and soil moisture, thereby impacting drought propagation.

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“…Drought classification based on Vegetation Health Index (VHI)[78]. Drought classification based on Vegetation Health Index (VHI)[78].…”

mentioning

confidence: 99%

Satellite-Based Meteorological and Agricultural Drought Monitoring for Agricultural Sustainability in Sri Lanka

2021

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For Sri Lanka, as an agricultural country, a methodical drought monitoring mechanism, including spatial and temporal variations, may significantly contribute to its agricultural sustainability. Investigating long-term meteorological and agricultural drought occurrences in Sri Lanka and assessing drought hazard at the district level are the main objectives of the study. Standardized Precipitation Index (SPI), Rainfall Anomaly Index (RAI), and Vegetation Health Index (VHI) were used as drought indicators to investigate the spatial and temporal distribution of agriculture and metrological droughts. Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data from 1989 to 2019 was used to calculate SPI and RAI. MOD13A1 and MOD11A2 data from Moderate Resolution Imaging Spectroradiometer (MODIS) from 2001 to 2019, were used to generate the Vegetation Condition Index (VCI) and Temperature Condition Index (TCI). Agricultural drought monitoring was done using VHI and generated using the spatial integration of VCI and TCI. Thus, various spatial data analysis techniques were extensively employed for vector and raster data integration and analysis. A methodology has been developed for the drought declaration of the country using the VHI-derived drought area percentage. Accordingly, for a particular year, if the country-wide annual extreme and severe drought area percentage based on VHI drought classes is ≥30%, it can be declared as a drought year. Moreover, administrative districts of Sri Lanka were classified into four hazard classes, No drought, Low drought, Moderate drought, and High drought, using the natural-beak classification scheme for both agricultural and metrological droughts. The findings of this study can be used effectively by the relevant decision-makers for drought risk management (DRM), resilience, sustainable agriculture, and policymaking.

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Spatiotemporal variability and assessment of drought in the Wei River basin of China

Cited by 9 publications

References 27 publications

Trends Analysis of Agricultural Drought in Central Anatolian Basin, Turkey

Trends Analysis of Agricultural Drought in Central Anatolian Basin, Turkey

Propagation dynamics and causes of hydrological drought in response to meteorological drought at seasonal timescales

Satellite-Based Meteorological and Agricultural Drought Monitoring for Agricultural Sustainability in Sri Lanka

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