Skip to main content
ARS Home » Southeast Area » Florence, South Carolina » Coastal Plain Soil, Water and Plant Conservation Research » Research » Publications at this Location » Publication #366184
Research Project: Managing Water Availability and Quality for Sustainable Agricultural Production and Conservation of Natural Resources in Humid Regions

Location: Coastal Plain Soil, Water and Plant Conservation Research

Title: Outlook on future streamflow drought patterns using SWAT interpretation of hydrologic scenarios

Author
item Sohoulande, Clement

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 10/30/2019
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: In water resources and environmental management, hydrologic indices are often valued as decision support tools because of their practical interpretability. This is true with streamflow drought index (SDI) which is considered as a relevant tool for assessing the availability of water resources at the watershed level. Hence, the future of freshwater resources at the watershed scale could be better understood by achieving a realistic projection of SDI. This study uses a process-based watershed Chi assessment tool (SWAT) model is employed to simulate distinctly two watersheds located in the State of Texas (i.e. the Trinity and the Neches river basins). The SWAT model is calibrated with monthly streamflow of the period 1990 to 1995. The model is later validated with two decades discharge data (i.e. period 1996 to 2015). The evaluation of the SWAT performance during the calibration and validation stages, reveals acceptable values of efficiency criteria for both watersheds (i.e. Nash-Sutcliffe's Efficiency ranging from 0.56 to 0.65; Index of agreement from 0.79 to 0.92). Thus, the calibrated model is considered to simulate runoff for the future period 2041 to 2070 using inputs retrieved from a future climate scenario. However, the SDI calculation requires the knowledge of the probability distribution of cumulative discharge data. A Kolmogorov-Smirnov’s goodness-of-fit analysis was conducted for both observed and simulated cumulative discharges. A lognormal distribution is henceforth considered for estimating time series of SDI. During the period 1996 to 2015, the SDI values recovered from the SWAT simulations, match closely with the ones derived directly from the observed discharge data (0.52=R2=0.91 for Neches river, 0.79= R2 = 0.89 for Trinity river). This result portends the capacity of the analytical procedure to capture and project realistically SDI signals. However, a statistic’s analysis of the SDI patterns during the past and the future periods does not reveal any significant difference.