Abstract
The relationships between a variety of hydro-meteorological variables and irrigation water use rates (WUR) were investigated in this study. Standardized Precipitation Index (SPI), Potential Evapotranspiration (PET), and Normalized Difference Vegetation Index (NDVI) were explored to identify the relationship with the WUR. The Yeongsan river basin, the agricultural land of which is mostly occupied by well-irrigated paddy, was used for the pilot study. Four different temporal scales of SPI-3, 6, 9, and 12 were tested, and PET was calculated using the Thornthwaite method. To calculate NDVI, the surface spectral reflectance data, which was acquired by Moderate Resolution Imaging Spectroradiometer (MODIS) equipped on the Terra satellite, were used. As a result, there was a statistically significant relationship between SPI9 and the WUR during drought periods in which negative values of SPI9 were obtained. The WUR was strongly correlated with both PET and NDVI. Compared with SPI, the variability of WUR in this study area was more sensitively affected by PET and NDVI, which can cause a potential lack of agricultural water supply. The finding of this study implies that SPI9, PET, and NDVI are the critical factors for predicting water withdrawal during drought conditions so that they can be used for irrigational water use management. Although a part of the findings of this study has been discussed by a few previous studies, this study is novel in that it quantifies the relationship between these factors using actual field observations of streamflow withdrawal for irrigation.
Highlights
The impact of drought on water resources systems is quantified by a variety of methods since there are various definitions of drought
Compared with Standardized Precipitation Index (SPI), the variability of water use rates (WUR) in this study area was more sensitively affected by Potential Evapotranspiration (PET) and Normalized Difference Vegetation Index (NDVI), which can cause a potential lack of agricultural water supply
The finding of this study implies that SPI9, PET, and NDVI are the critical factors for predicting water withdrawal during drought conditions so that they can be used for irrigational water use management
Summary
The impact of drought on water resources systems is quantified by a variety of methods since there are various definitions of drought. Meteorological drought index has been widely used due to its straightforward definition and easy data accessibility. SPI (Standardized Precipitation Index [3]) is a well-known meteorological drought index characterizing a lack of precipitation on a range of timescales [4,5]. SDI (Streamflow Drought Index) has been used as a hydrologic drought index, which is based on the same calculation methodology with the SPI. SDI is defined as a shortage of streamflow comparing to its normal condition [6,7,8]. To define a drought condition, i.e., to judge whether there is lack of streamflow, the proper value for threshold level should be determined. The drought condition is defined as a period when the streamflow is less than the threshold value
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