Drought Characteristics and Cascading Dynamics in South India: On the Key Influencing Factors
摘要
The interplay among different drought types—meteorological, agricultural, hydrological, and groundwater—triggers cascading effects across multiple interconnected sectors. Therefore, a comprehensive understanding of the drought cascading and its governing factors is essential for water-stressed and highly vulnerable Southern India. Here, we leverage 7,167 in situ well data and the GRACE-based drought severity index to assess groundwater drought. Standardized precipitation, soil moisture, and runoff indices are used to analyze meteorological, agricultural, and hydrological droughts, respectively. The average intensity of meteorological, agricultural, and hydrological droughts was higher during 2012–2021 compared to 2003–2011. Results reveal a decrease in the area affected by meteorological and groundwater droughts, from 24% and 85% of the total area during 2003–2011 to 17.6% and 69.76%, respectively, during 2012–2021. In contrast, hydrological and agricultural droughts became more widespread, affecting 80.01% and 90.2% of the region, respectively, in 2012–2021, compared to 19.90% and 9.72% in 2003–2011. Notably, the propagation relationship from agricultural to hydrological droughts is the strongest among the studied drought types. The propagation time between meteorological, agricultural, and hydrological droughts is relatively shorter during the monsoon and post-monsoon seasons (1–4 months) compared to the pre-monsoon and winter seasons (1–6 months). Groundwater droughts respond more weakly to hydrological droughts than to meteorological or agricultural droughts. ENSO emerged as the most dominant driving climatic factor influencing drought propagation, compared to the PDO and the IOD.
Graphical AbstractThis graphical snapshot presents an investigation into the characteristics of four drought types (meteorological, agricultural, hydrological, and groundwater) within the hydrological cycle, along with their internal propagation relationships and possible key influencing factors over South India (SI)—a region highly vulnerable to extreme hydrological events, particularly droughts, due to pronounced rainfall variability and anthropogenic activities. To analyze groundwater drought, we use two mascon products from the Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow On (GRACE-FO) missions, along with Global Land Data Assimilation System (GLDAS) datasets. These two mascon products were validated using GLDAS and groundwater storage data from 7,167 wells across the SI (Sect. 1 in the top-right corner of the graphical abstract). The results indicate that the Center for Space Research (CSR) mascon data slightly outperforms the Jet Propulsion Laboratory (JPL) mascon. Meteorological, agricultural, and hydrological droughts were characterized both spatially and temporally using non-parametric standardized precipitation, soil moisture, and surface runoff indices, respectively. Results show that meteorological drought conditions improved (observed trends were noticeable but largely not statistically significant), while agricultural and hydrological droughts intensified from 2003 to 2021. The average intensity of meteorological, agricultural, and hydrological droughts was higher during 2012–2021 compared to 2003–2011 (Sect. 2). Groundwater drought was analyzed using the GRACE-based Drought Severity Index. The analysis shows that groundwater drought conditions improved, similar to meteorological droughts. Drought propagation relationships were analyzed using Pearson’s correlation analysis both temporally and spatially. The propagation relationship from agricultural to hydrological droughts is the strongest amongst all (Sect. 3). The influence of large-scale climate oscillations on drought propagation was explored using the cross-wavelet transform method (Sect. 4). It is found that ENSO exerts the strongest influence on drought propagation among the three large-scale climatic factors (ENSO, IOD, and PDO) across SI.