Graduation Year
2018
Document Type
Thesis
Degree
M.S.E.V.
Degree Name
MS in Environmental Engr. (M.S.E.V.)
Degree Granting Department
Civil and Environmental Engineering
Major Professor
Qiong Zhang, Ph.D.
Committee Member
Mauricio E. Arias, Ph.D.
Committee Member
James R. Mihelcic, Ph.D.
Keywords
Bluewater, Climate Scenario, Streamflow, SWAT, Water Stress
Abstract
Water scarcity is a problem that will be exacerbated by climate change. Being able to model the effect of climate change on water scarcity is important to effectively plan the use of future water resources. This research integrated the Soil and Water Assessment Tool (SWAT), climate model, and water footprint analysis to measure the impact of climate change on future water scarcity. This was achieved through two objectives. The first objective was to create a modeling framework that links the output from climate model to SWAT and combined streamflow outputs from SWAT with water footprint analysis to measure how climate change will impact water scarcity of a river basin. This was accomplished through creating a SWAT model within ArcMap and inputting a topographic, soil, land use, and weather data. Climate Forecast System Reanalysis (CFSR) data were used in lieu of observed weather data due to a lack of available data. SWAT-CUP (Calibration and Uncertainty Program) was used to calibrate two upstream streamflow gauges, then calibrate and validate a third streamflow gauge at the outlet of the Senqu basin in Lesotho. The two upstream streamflow gauges were calibrated from 1986 to 2002. The downstream streamflow gauge was calibrated from 1985 to 2002 and validated from 2003 to 2013. Three Regional Climate Models (RCM), ICHEC-EC-EARTH, MIROC-MIROC5, and CCCma-CanESM2 were downloaded from the Coordinated Regional Downscaling Experiment (CORDEX) dataset. Each RCM was downloaded with two different Coupled Model Intercomparison Project (CMIP5) Representative Concentration Pathways (RCP), RCP 4.5 and RCP 8.5. The RCMs were bias corrected using a cumulative distribution function mapping technique.
These RCMs as well as an average of the RCMs were used as input for the SWAT model to generate future streamflow outputs. The streamflow outputs provide the future blue water availability of the Senqu River. The results showed an overall decrease in streamflow in both RCPs. The second objective was to apply the framework to Lesotho and use the information from the ArcSWAT model and data from the Blue Water Footprint analysis to measure the future potential Blue Water Scarcity of Lesotho. This was accomplished through the Blue Water Footprint of Lesotho generated from the 5th National Blue Footprint analysis. The annual blue water scarcity was calculated as the ratio of the Blue Water Available to Blue Water Footprint. Three approaches were adopted to analyze the water scarcity of Lesotho. The first approach used the national Blue Water Footprint in the water scarcity calculation to investigate the worst-case scenario. The second approach used the modified blue water footprint based on the population living within the Senqu river basin. The third approach used a modified blue water footprint that accounted for the projected population growth of Lesotho. The results of scenario 1 showed there was moderate water scarcity in a period of four years in climate scenario of RCP8.5. The results of scenario 3 showed there were multiple cases of water scarcity in both RCP 4.5 and RCP 8.5 with two years of severe water scarcity. This research is limited by data availability and the results for Lesotho could be improved by accurate dam data and the fine scale water footprint analysis. The modeling framework integrating climate model, hydrology, and water footprint analysis, however, can be applied to other remote places where limited data are available.
Scholar Commons Citation
Pryor, John W., "Framework Integrating Climate Model, Hydrology, and Water Footprint to Measure the Impact of Climate Change on Water Scarcity in Lesotho, Africa" (2018). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/7353