Investigating the relationships between remotely sensed and in situ drought indicators to understand streamflow discharge anomalies - Bandad, Devon Ali (Kansas State University, 2020)
Predicting drought and streamflow are important aspects of water management to help mitigate the effects that a drought has on the environment and the people involved. The goals of this research are to assess remote sensing indicators and their ability to monitor drought and streamflow changes compared to in situ indicators in order to better estimate streamflow changes in times of drought in areas and at times without station-based data. Using in situ drought indicators such as station-based Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI) helps water managers identify drought severity based on various environmental factors measured on a regular basis using station-based data. Remote sensing indicators on the other hand use satellite inputs to monitor such trends as vegetation coverage at a higher spatial resolution than an in situ index would. Remote sensing information is more readily available than most observed environmental information across the globe. The study region is located in central United States in the MINK (Missouri, Iowa, Nebraska, and Kansas) region. Data for the growing period (April-September) from 2003-2017 were used. The region varies greatly from east to west in both land cover and average precipitation amount (318 – 1397 mm per year) as the region becomes drier and changes from forests in the southeast to farmland and prairie in the west. The first part of the study evaluated various drought indices and their relationships with streamflow. The in situ indices evaluated include SPI and PDSI, which were available on a monthly basis for each climate division in the MINK region. The remote sensing indices include the Vegetation Condition Index (VCI) and the Soil Moisture Condition Index (SMCI). Each index has different data inputs, such a precipitation (PDSI and SPI) and temperature (PDSI) for the in situ indices and vegetation greenness (VCI) and soil moisture (SMCI) for the remote sensing indices. The indices were ultimately compared both spatially and temporally (annual basis) to streamflow in the form of discharge anomalies (PDA). In the second part of this study, analysis focused on how relationships between the remote sensing indices changed as land cover varies over the MINK region. Overall, results suggest that the in situ indices (PDSI and SPI) can estimate PDA changes (on an annual scale), while SMCI performed better than VCI overall though not as well as PDSI or SPI. The findings from this study have the potential to assist water managers and policy makers to better understand streamflow changes and increase drought preparedness.
Keywords: Drought; Streamflow; PDSI; SPI; VCI; SMCI