Responses of stream water quality concentrations to vegetative cover variation in Muar River watershed

Abstract

Analysis of the historical land-cover of Muar River watershed has shown that forest and agriculture are the dominant land-covers over the last three decades. This information was used to evaluate the relationship between the vegetative landscape variation to stream water quality concentrations which was to provide an insight for management of water quality under humid tropical climate. Three out of the six water quality variables simulated using the hydrological simulation program FORTRAN (HSPF) model are sensitive to change in vegetative land-covers which include; biochemical oxygen demand (BOD), nitrate-nitrogen (NO3-N), and orthophosphate (PO4) concentrations. However, total suspended solids (TSS), dissolved oxygen (DO), and ammonia-nitrogen (NH3-N) concentrations remain insensitive. Further analysis shows that patch density (PD) has a little impact on BOD, NO3-N, and PO4 concentrations compared to edge density (ED), largest patch index (LPI), and landscape shape index (LSI) under varied landscape conditions. However, large ED, LPI, and LSI indices in both forest and agriculture will result to increase in BOD, NO3-N, and PO4 concentrations. Therefore, adequate knowledge of the responses of the water quality concentrations to landscape pattern and its dynamics can serve as an alternative solution to stream water quality deterioration in an abundant rainfall region.

Keywords

• Landscape pattern
• HSPF model
• regression model
• remote sensing
• tropical climate