Spatio‐temporal drought patterns of multiple drought indices based on precipitation and soil moisture: A case study in South Korea

Droughts in the Iberian Peninsula are a natural hazard of great relevance due to their recurrence, severity and impact on multiple environmental and socioeconomic aspects. The Ebro Basin, located in the NE of the Iberian Peninsula, is particularly vulnerable to drought with consequences on agriculture, urban water supply and hydropower. This study, performed within the Project HUMID (CGL2017-85687-R), aims at evaluating the influence of the climatic, land cover and soil characteristics on the interactions between rainfall, evapotranspiration and soil moisture anomalies which define the spatio-temporal drought patterns in the basin.The onset, propagation and mitigation of droughts in the Iberian Peninsula is driven by anomalies of rainfall, evapotranspiration and soil moisture, which are related by feedback processes. To test the relative importance of such anomalies, we evaluate the contribution of climatic, land-cover and geologic heterogeneity on the definition of the spatio-temporal patterns of drought. We use the K&#246;ppen-Geiger climatic classification to assess how the contrasting climatic types within the basin determine differences on drought behavior. Land-cover types that govern the partition between evaporation and transpiration are also of great interest to discern the influence of vegetation and crop types on the anomalies of evapotranspiration across the distinct regions of the basin (e.g. forested mountains vs. crop-dominated areas). The third physical characteristic whose effect on drought we investigate is the impact of soil properties on soil moisture anomalies.The maps and time series used for the spatio-temporal analysis are based on drought indices calculated with high-resolution datasets from remote sensing (MOD16A2ET and SMOS1km) and the land-surface model SURFEX-ISBA. The Standardized Precipitation Index (SPI), the EvapoTranspiration Deficit Index (ETDI) and the Soil Moisture Deficit Index (SMDI) are the three indices chosen to characterize the anomalies of the corresponding rainfall (atmospheric), evapotranspiration (atmosphere-land interface) and soil moisture (land) anomalies (components of the water balance). The comparison of the correlations of the indices (with different time lags) between contrasting regions offers insights about the impact of climate, land-cover and soil properties in the dominance, the timing of the response and memory aspects of the interactions. The high spatial and temporal resolution of remote sensing and land-surface model data allows adopting time and spatial scales suitable to investigate the influence of these physical factors with detail beyond comparison with ground-based datasets.The spatial and temporal analysis prove useful to investigate the physical factors of influence on the anomalies between rainfall, evapotranspiration and soil moisture. This approach facilitates the physical interpretation of the anomalies of drought indices aiming to improve the characterization of drought in heterogeneous semi-arid areas like the Ebro River Basin.

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Construction of Drought Indices from Passive Microwave Remote Sensing AMSR-E Data in Huaihe River Basin

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.397-400.2503 ◽

2013 ◽

Vol 397-400 ◽

pp. 2503-2506

Author(s):

Rui Wang ◽

Jing Wen Xu ◽

Dan Wang ◽

Xing Mei Xie ◽

Peng Wang

Keyword(s):

Remote Sensing ◽

Soil Moisture ◽

River Basin ◽

Microwave Remote Sensing ◽

Passive Microwave ◽

Drought Indices ◽

Huaihe River Basin ◽

Huaihe River ◽

Passive Microwave Remote Sensing ◽

Spatio Temporal

On the basis of previous work, this paper aims to build several proper drought indices based on passive microwave remote sensing AMSR-E data in Huaihe River Basin. Compared with measured soil moisture, optimal drought indices have been selected to explore the spatio-temporal variation of drought conditions. The results indicate that there are satisfactory negative correlations between MPDIs (Microwave Polarization Index) and observed soil moisture. Moreover, MPDIs calculated by bands of 69GHz and 187GHz are much closer to variation trend of soil moisture than those obtained by other bands.

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SATELLITE BASED DROUGHT ASSESSMENT OVER LATUR, INDIA USING SOIL MOISTURE DERIVED FROM SMOS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-5-421-2018 ◽

2018 ◽

Vol XLII-5 ◽

pp. 421-425

Author(s):

D. Kolekar ◽

V. S. K. Vanama ◽

Y. S. Rao

Keyword(s):

Soil Moisture ◽

Standardized Precipitation Index ◽

Drought Monitoring ◽

Drought Indices ◽

Standardized Precipitation Evapotranspiration Index ◽

Spatial Region ◽

Drought Assessment ◽

Daily Data ◽

Ocean Salinity ◽

Spatio Temporal

Abstract. Climatological variables such as rainfall, temperature have been extensively used by researchers for drought monitoring at a larger spatial region. These variables have a direct influence on the soil moisture which in turn extends the application of soil moisture in drought assessment. With the advancement of technology, various satellites provide soil moisture data at different spatio-temporal resolutions. In this article, soil moisture obtained from Soil Moisture Ocean Salinity (SMOS) is used to analyze the drought condition over Latur district in Maharashtra, India. The monthly soil moisture derived by averaging the daily data for the years 2010 to 2015 is compared with two drought indices, i.e. Standardized Precipitation Index (SPI) calculated for years 2010 to 2015 and Standardized Precipitation-Evapotranspiration Index (SPEI) calculated for years 2010 to 2013. Even though the overall correlation among the indices with the soil moisture is not significant, the seasonal (summer) correlation is significant. From the results, it is identified that SMOS derived soil moisture can be used as a potential parameter in drought assessment.

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Sensitivity analysis of drought indices under substantially different agricultural systems in North and South Koreas

10.5194/egusphere-egu2020-8491 ◽

2020 ◽

Author(s):

Seonyoung Park ◽

Jongmin Yeom ◽

Jeongho Lee ◽

Jaese Lee ◽

Jungho Im ◽

...

Keyword(s):

Soil Moisture ◽

South Korea ◽

Soil Water ◽

Correlation Coefficient ◽

Drought Index ◽

Rice Yield ◽

Rice Production ◽

Drought Indices ◽

Irrigation Canals ◽

North And South

Rice is a staple food in the North and South Koreas. Rice yield is closely related to water supply including irrigation, precipitation, and soil water. Drought typically occurs due to the lack of precipitation, and prolonged drought leads to the decrease of soil water, which results in plant water stress. Drought monitoring is crucial for agricultural mitigation because it enables us to estimate rice production in a timely manner. The purpose of this study is to suggest an optimal drought index for monitoring agricultural drought over North and South Koreas. Although North and South Koreas have similar climate conditions, they have different levels of infrastructure for agriculture such as irrigation facilities. In this study, nine satellite-based drought indices were used and evaluated based on in situ measurements at weather stations including Standardized Precipitation Index (SPI) and rice yield. Drought indices were calculated using the Global Land Data Assimilation System (GLDAS) soil moisture, Tropical Rainfall Measuring Mission (TRMM) precipitation, Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI). Since various drought indices have been developed with their own purpose, considering the characteristics of the study area under investigation, their applications for other regions are relatively limited. Thus, comparison of various drought indices is needed to identify an optimal drought index for a certain area. The measurable objectives of this research were to 1) compare the characteristics of drought depending on the properties of drought indices such as temperature, vegetation, precipitation, and soil moisture and 2) evaluate various drought indices using SPIs and rice yield data. The performance of the drought indices was evaluated using correlation coefficient values (R) for reference data (i.e., SPI and rice yield). As expected, drought indices including NDVI showed positive relationships with rice yield in both regions (averaged R=0.37). Meanwhile, temperature based drought indices showed negative relationships with rice yield in both regions because high temperature means high solar radiation, which is essential to rice production. While the correlation coefficient between precipitation based indices and rice yield was positive in North Korea (averaged R=0.34), it was negative in South Korea (averaged R=-0.26). The opposite pattern by area is because South Korea (117,457 irrigation Canals) has more artificial controls over agricultural land such as irrigation facilities and reservoirs than North Korea (51,400 irrigation Canals).

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Adopting drought indices for estimating soil moisture: A North Carolina case study

Geophysical Research Letters ◽

10.1029/2001gl013343 ◽

2002 ◽

Vol 29 (8) ◽

pp. 24-1-24-4 ◽

Cited By ~ 78

Author(s):

Aaron P. Sims ◽

Dev dutta S. Niyogi ◽

Sethu Raman

Keyword(s):

North Carolina ◽

Soil Moisture ◽

Drought Indices

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Estimation of soil moisture using deep learning based on satellite data: a case study of South Korea

GIScience & Remote Sensing ◽

10.1080/15481603.2018.1489943 ◽

2018 ◽

Vol 56 (1) ◽

pp. 43-67 ◽

Cited By ~ 12

Author(s):

Chang suk Lee ◽

Eunha Sohn ◽

Jun Dong Park ◽

Jae-Dong Jang

Keyword(s):

Soil Moisture ◽

Deep Learning ◽

South Korea ◽

Satellite Data

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An Agricultural Drought Index for Assessing Droughts Using a Water Balance Method: A Case Study in Jilin Province, Northeast China

Remote Sensing ◽

10.3390/rs11091066 ◽

2019 ◽

Vol 11 (9) ◽

pp. 1066 ◽

Cited By ~ 5

Author(s):

Yijing Cao ◽

Shengbo Chen ◽

Lei Wang ◽

Bingxue Zhu ◽

Tianqi Lu ◽

...

Keyword(s):

Soil Moisture ◽

Potential Evapotranspiration ◽

Condition Index ◽

Agricultural Drought ◽

Drought Indices ◽

Growing Seasons ◽

Dryness Index ◽

Vegetation Health Index

Drought, which causes the economic, social, and environmental losses, also threatens food security worldwide. In this study, we developed a vegetation-soil water deficit (VSWD) method to better assess agricultural droughts. The VSWD method considers precipitation, potential evapotranspiration (PET) and soil moisture. The soil moisture from different soil layers was compared with the in situ drought indices to select the appropriate depths for calculating soil moisture during growing seasons. The VSWD method and other indices for assessing the agricultural droughts, i.e., Scaled Drought Condition Index (SDCI), Vegetation Health Index (VHI) and Temperature Vegetation Dryness Index (TVDI), were compared with the in situ and multi-scales of Standardized Precipitation Evapotranspiration Index (SPEIs). The results show that the VSWD method has better performance than SDCI, VHI, and TVDI. Based on the drought events collected from field sampling, it is found that the VSWD method can better distinguish the severities of agricultural droughts than other indices mentioned here. Moreover, the performances of VSWD, SPEIs, SDCI and VHI in the major historical drought events recorded in the study area show that VSWD has generated the most sensible results than others. However, the limitation of the VSWD method is also discussed.

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