Assessment of drought condition using remotely sensed drought severity index and its correlations with soil moisture product in Inner Mongolia

Wang, Lusha; Kotani, Ayumi; Tanaka, Takafumi; Ohta, Takeshi

doi:10.1007/s00704-020-03242-z

Cited by 7 publications

(9 citation statements)

References 41 publications

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“…For the three drought years of 2001, 2007 and 2009, we compared the spatial distribution of the IDSI and the original DSI, which was investigated by Wang et al (2020). The DSI in the western part could not be calculated because of the lack of ET and PET.…”

Section: Difference Between Original and Improved Drought Severity Inmentioning

confidence: 99%

“…According to Wang et al (2020), the evapotranspiration component of DSI included NDVI effects, while soil moisture is almost unrelated to the NDVI. Replacing the ET/PET component with soil moisture is equivalent to removing the duplicate effect of the NDVI in the DSI.…”

Section: Difference Between Original and Improved Drought Severity Inmentioning

confidence: 99%

“…In DSI calculations, soil moisture and precipitation are not used as input items (Mu et al, 2013a). When Wang et al (2020) used Mu et al's (2013a) DSI to evaluate drought in Inner Mongolia during 2001-2010, they examined the relationship between the DSI and soil moisture and came to the following conclusions: (1) The relationship between the DSI and soil moisture was mainly controlled by the relationship between ET/PET and soil moisture, whereas the relationship between the NDVI and soil moisture was very limited. (2) ET/PET and the NDVI were not mutually independent, because the NDVI affected ET/PET.…”

Section: Introductionmentioning

confidence: 99%

“…Mishra and Singh (2010) also attributed the lack of soil moisture to agricultural drought, and pointed out that precipitation is one of the important factors affecting soil moisture. We first used the IDSI to evaluate the drought situation in Inner Mongolia throughout the growing season (May-September) during 2001-2010, which is the same time period studied by Wang et al (2020). Then we clarify the relationship between the IDSI and precipitation.…”

Section: Introductionmentioning

confidence: 99%

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Application of Improved Remotely Sensed Drought Severity Index Based on Soil Moisture Product in Inner Mongolia

Wang

Kotani

Tanaka

et al. 2020

SOLA

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Based on the drought severity index (DSI), which is derived from the ratio of evapotranspiration (ET) to potential evapotranspiration (PET) and normalized difference vegetation index (NDVI), as measured by remote sensing, we replaced the ET/PET ratio with soil moisture (0-10 cm) to establish an improved index (IDSI) and evaluated the drought situation in Inner Mongolia. The two components in IDSI are independently derived; however, the effects of evapotranspiration are contained in the soil moisture, and even precipitation changes could be reflected. We used monthly IDSI data for Inner Mongolia to evaluate drought throughout the growing season (May-September) during 2001-2010. The IDSI showed that 2001, 2007, and 2009 were years with significant drought. Areas that experienced extreme drought were less extensive than those found by the DSI because we removed the ET/PET component, which already contains the effects of the NDVI. IDSI results not only contained the degree of precipitation change for a given month through soil moisture, but also reflected the influence of water and heat in the previous month through the NDVI. Moreover, IDSI results were generally consistent with agricultural drought disaster records.

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Section: Difference Between Original and Improved Drought Severity Inmentioning

confidence: 99%

Section: Difference Between Original and Improved Drought Severity Inmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Application of Improved Remotely Sensed Drought Severity Index Based on Soil Moisture Product in Inner Mongolia

Wang

Kotani

Tanaka

et al. 2020

SOLA

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“…A precipitation-based drought study for Iran was done by Mahmoudi et al(Mahmoudi et al, 2019). Vegetation and soil moisture, which can be obtained by remote sensing, are data sources commonly used in drought studies(Drisya et al, 2018, Wang et al, 2020, Zhu et al, 2018. High-resolution vegetation change information provided both temporal and spatial by vegetation indices (e.g., NDVI), can contribute to drought-related research without requiring additional information on drought.…”

mentioning

confidence: 99%

Drought Analysis for the Seyhan Basin with NDVI and VCI Vegetation Indices

Aksel¹,

Dikici²

2021

Preprint

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Various drought indices have been developed to monitor the drought, which is one of the results of climate change and mitigates its adverse effects on water resources, especially agriculture. Vegetation indices determined by remote sensing have been the subject of many studies in recent years and shed light on drought risk management. This study is examined in the Seyhan River Basin, a basin with Turkey’s considerable population density counts and is situated south of the country. Normalized Difference Vegetation Index (NDVI) and Vegetation Condition Index (VCI) are the most widely used vegetation indices and are very useful because they give results only based on satellite images. This study examined the Seyhan Basin by using satellite data in which the vegetation transformation occurring due to the decline of agricultural and forest areas was also seen. An increase in drought frequency was detected in the Seyhan Basin using NDVI and VCI indices. It was determined that climate change and drought increased with a linear uptrend. It is recommended that decision-makers should take the necessary measures by considering the drought risk maps and that long-term drought management plans should be made and implemented.

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Changes in soil moisture and vegetation over the Tibetan Plateau during 2000–2019

Shi

Zeng

Chen

et al. 2021

2021 CIE International Conference on Radar (Radar)

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Assessment of drought condition using remotely sensed drought severity index and its correlations with soil moisture product in Inner Mongolia

Cited by 7 publications

References 41 publications

Application of Improved Remotely Sensed Drought Severity Index Based on Soil Moisture Product in Inner Mongolia

Application of Improved Remotely Sensed Drought Severity Index Based on Soil Moisture Product in Inner Mongolia

Drought Analysis for the Seyhan Basin with NDVI and VCI Vegetation Indices

Changes in soil moisture and vegetation over the Tibetan Plateau during 2000–2019

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