Calculation and applicability analysis of drought index based on simple meteorological factors
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DOI:10.7606/j.issn.1000-7601.2024.01.25
Key Words: meteorological drought  air temperature  relative humidity  water scarcity index (WSI)  Shaanxi Province
Author NameAffiliation
LIU Shuang The Research Center of Soil and Water Conservation and Ecological Environment, Chinese Academy of Sciences and Ministry of Education, Yangling, Shaanxi 712100, ChinaInstitute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling, Shaanxi 712100ChinaUniversity of Chinese Academy of Sciences, Beijing 100049, China 
FAN Xingke The Research Center of Soil and Water Conservation and Ecological Environment, Chinese Academy of Sciences and Ministry of Education, Yangling, Shaanxi 712100, ChinaInstitute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling, Shaanxi 712100China Institute of Soil and Water Conservation, Northwest A&F University, Yangling, Shaanxi 712100, China 
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Abstract:
      In order to establish a meteorological drought index that can effectively monitor short\|term droughts, this study, based on the mechanism of meteorological drought occurrence\|namely the imbalance between water supply and demand (primarily influenced by precipitation and evapotranspiration), introduced a drought index termed the water scarcity index (WSI). This index was defined by the ten\|day scale evapotranspiration deficit as a proportion of the water demand. The potential evapotranspiration (PET) was calculated using easily accessible meteorological factors: temperature (T, ℃) and relative humidity (RH, %). Using daily meteorological observation data from 30 weather stations in Shaanxi Province from 2000 to 2020, we analyzed the applicability characteristics of WSI. The results indicated that, without considering the effects of wind and atmospheric pressure, the error in estimating PET based on T and RH was relatively small compared to the Penman\|Monteith equation. The root mean square error (RMSE) and mean absolute error (MAE) were 1.17 mm and 0.82 mm. However, 62.1% of the data results were underestimated, with some stations having over 80% of data underestimated. Research on the recent drought development changes in different regions of Shaanxi Province showed that WSI can identify drought\|prone areas and periods in Shaanxi. It also possesses a strong ability to recognize short\|term drought events. WSI outperforms MCI in swiftly detecting droughts, offering greater flexibility and simplicity for monitoring, forecasting, and evaluating meteorological drought conditions.