Impact of Spatio-Temporal Variability of Droughts on Streamflow: A Remote-Sensing Approach Integrating Combined Drought Index
Understanding how spatial drought variability influences streamflow is critical for sustainable water management under changing climate conditions. This study developed a novel Combined Drought Index (CDI) and a method to assess spatial drought impacts on different flow components by integrating rem...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-06-01
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| Series: | Hydrology |
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| Online Access: | https://www.mdpi.com/2306-5338/12/6/142 |
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| author | Anoma Srimali Luminda Gunawardhana Janaka Bamunawala Jeewanthi Sirisena Lalith Rajapakse |
| author_facet | Anoma Srimali Luminda Gunawardhana Janaka Bamunawala Jeewanthi Sirisena Lalith Rajapakse |
| author_sort | Anoma Srimali |
| collection | DOAJ |
| description | Understanding how spatial drought variability influences streamflow is critical for sustainable water management under changing climate conditions. This study developed a novel Combined Drought Index (CDI) and a method to assess spatial drought impacts on different flow components by integrating remote sensing and hydrological modelling frameworks with generic applicability. The CDI was constructed using Principal Component Analysis to merge multiple standardized indicators: the Standardized Precipitation Evapotranspiration Index, Temperature Condition Index, Vegetation Condition Index, and Soil Moisture Condition Index. The developed framework was applied to the Giriulla sub-basin of the Maha Oya River Basin, Sri Lanka. The CDI strongly correlated with standardized streamflow with a Pearson correlation coefficient of 0.74 and successfully captured major drought and flood events between 2015 and 2023. A semi-distributed hydrological model was used to simulate streamflow variations across sub-catchments under varying drought conditions. Results show upstream sub-catchments were more sensitive to droughts, with sharper declines in specific discharge. Spatial drought variability had different impacts under high- and low-flow conditions: wetter sub-catchments contributed more during high flows, while resilience during low flows varied with catchment characteristics. This integrated approach provides a valuable framework that can be generically applicable for enhanced drought impact assessments. |
| format | Article |
| id | doaj-art-ac556d11c83c46b5972ee4a1df9e5f60 |
| institution | Matheson Library |
| issn | 2306-5338 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Hydrology |
| spelling | doaj-art-ac556d11c83c46b5972ee4a1df9e5f602025-06-25T13:56:19ZengMDPI AGHydrology2306-53382025-06-0112614210.3390/hydrology12060142Impact of Spatio-Temporal Variability of Droughts on Streamflow: A Remote-Sensing Approach Integrating Combined Drought IndexAnoma Srimali0Luminda Gunawardhana1Janaka Bamunawala2Jeewanthi Sirisena3Lalith Rajapakse4Department of Civil Engineering, University of Moratuwa, Katubedda 10400, Sri LankaDepartment of Civil Engineering, University of Moratuwa, Katubedda 10400, Sri LankaDepartment of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku University, Sendai 980-8579, JapanClimate Service Center Germany (GERICS), Helmholtz-Zentrum Hereon, 20095 Hamburg, GermanyDepartment of Civil Engineering, University of Moratuwa, Katubedda 10400, Sri LankaUnderstanding how spatial drought variability influences streamflow is critical for sustainable water management under changing climate conditions. This study developed a novel Combined Drought Index (CDI) and a method to assess spatial drought impacts on different flow components by integrating remote sensing and hydrological modelling frameworks with generic applicability. The CDI was constructed using Principal Component Analysis to merge multiple standardized indicators: the Standardized Precipitation Evapotranspiration Index, Temperature Condition Index, Vegetation Condition Index, and Soil Moisture Condition Index. The developed framework was applied to the Giriulla sub-basin of the Maha Oya River Basin, Sri Lanka. The CDI strongly correlated with standardized streamflow with a Pearson correlation coefficient of 0.74 and successfully captured major drought and flood events between 2015 and 2023. A semi-distributed hydrological model was used to simulate streamflow variations across sub-catchments under varying drought conditions. Results show upstream sub-catchments were more sensitive to droughts, with sharper declines in specific discharge. Spatial drought variability had different impacts under high- and low-flow conditions: wetter sub-catchments contributed more during high flows, while resilience during low flows varied with catchment characteristics. This integrated approach provides a valuable framework that can be generically applicable for enhanced drought impact assessments.https://www.mdpi.com/2306-5338/12/6/142Combined Drought IndexHEC-HMS modellingPrincipal Component Analysis (PCA)soil moisturestreamflow variability |
| spellingShingle | Anoma Srimali Luminda Gunawardhana Janaka Bamunawala Jeewanthi Sirisena Lalith Rajapakse Impact of Spatio-Temporal Variability of Droughts on Streamflow: A Remote-Sensing Approach Integrating Combined Drought Index Hydrology Combined Drought Index HEC-HMS modelling Principal Component Analysis (PCA) soil moisture streamflow variability |
| title | Impact of Spatio-Temporal Variability of Droughts on Streamflow: A Remote-Sensing Approach Integrating Combined Drought Index |
| title_full | Impact of Spatio-Temporal Variability of Droughts on Streamflow: A Remote-Sensing Approach Integrating Combined Drought Index |
| title_fullStr | Impact of Spatio-Temporal Variability of Droughts on Streamflow: A Remote-Sensing Approach Integrating Combined Drought Index |
| title_full_unstemmed | Impact of Spatio-Temporal Variability of Droughts on Streamflow: A Remote-Sensing Approach Integrating Combined Drought Index |
| title_short | Impact of Spatio-Temporal Variability of Droughts on Streamflow: A Remote-Sensing Approach Integrating Combined Drought Index |
| title_sort | impact of spatio temporal variability of droughts on streamflow a remote sensing approach integrating combined drought index |
| topic | Combined Drought Index HEC-HMS modelling Principal Component Analysis (PCA) soil moisture streamflow variability |
| url | https://www.mdpi.com/2306-5338/12/6/142 |
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