Mapping and estimating water quality parameters in the Volta Lake’s Kpong Headpond of Ghana using regression model and Landsat 8

Abstract

AbstractSub-Saharan Africa faces a number of essential issues, including water quality. As such, evaluating the surface water quality of lakes and reservoirs is a crucial part of environmental monitoring and management. Especially in a region where these water bodies serve as a source of livelihood for communities living around them. Water quality parameters (WQPs) are usually taken from the site and sent to the laboratory for measurement and analysis. However, this traditional method is time-consuming, costly, and labor-intensive. Combining geographic information system and remote sensing (RS) allows researchers to analyze WQPs more conveniently. This study, therefore, used RS technology to map and estimate WQPs and correlated it with in-situ measurement. Using the empirical regression model and Landsat 8, WQPs such as chlorophyll-a (Chl-a), total suspended solids (TSS) and turbidity were estimated. The results from RS were correlated with the in-situ measurements of water quality. The results showed that the in-situ Chl-a levels varied from 0.206 to 13.5 mg/L, averaging 5.1 mg/L. The Chl-a values estimated from Landsat 8 had R2 of 0.883 and 0.853, respectively, for both periods (17 December 2022 and 16 March 2023). The green band (B3) was more instrumental in detecting Chl-a. The in-situ measurement for TSS ranged between 18 and 48 mg/L, with a mean value of 28.7 mg/L. These readings were low and within tolerable bounds of 50 mg/L. High TSS concentrations were found near farms and communities with a significant influx of silt into the surrounding lake. The comparison of in-situ water quality and the reflectance from satellite data showed that the turbidity estimated from the sensor from the two periods has R2 > 0.65. The study showed that the combination of the Landsat image and in-situ measurement offers great ways to provide timely and affordable estimation from WQPs.

Keywords

• Chlorophyll-a
• total suspended solids
• Landsat 8
• water quality parameters
• empirical regression model
• Sanjay Kumar Shukla, Edith Cowan University, Australia