Abstract:
Throughout the world, increased use of agrochemicals, warrant urgent measures to
minimise their
impacts on the aquatic environment. Monitoring is the usual practice
to
identify and quantify pollutants, however, it is an after-the-fact occurrence, and
monitoring over large spatial scales is not feasible. Mathematical models provide
an alternative to
monitoring and can be used both to forecast future pollution and to
investigate the impacts of potential control measures. This thesis is therefore
focussed on catchment scale
modelling of pesticide pollution of rivers.
Data from a 142-ha
agricultural catchment on the Unilever Colworth estate, have
been used to model
pesticide pollution at the catchment scale. After a review of
available models SWAT-2000 was selected as the modelling tool. An acceptable
performance in hydrological modelling, along with correct simulation of the
processes driving the water balance were essential first requirements. After
modification of the SWAT-2000 source code, hydrological simulation, crop growth
and
evapotranspiration patterns were realistic when compared with monitored data
SOUTCGS.
Hydrological modelling was carried out using both daily and sub-daily data with
Hargreaves and Penman-Montieth methods of evapotranspiration and the NRCS-
Curve Number and
Green-Ampt methods of runoff generation. A sensitivity
analysis identified GWQMN, AWC and ESCO as the most sensitive parameters.
These control baseflow, water content of soil layers, and depth distribution of
evaporation from the soil respectively. The best combination of runoff generation
and
evapotranspiration components was identified as Curve Number with
Hargreaves.
Modelling of sediment and pesticide loss was carried out for four pesticides.
Various
management scenarios were designed and tested with the objective of
reducing pesticide loss to streams and a web-based tool was developed to give
advice on
pesticide application. With the modifications implemented, it has been
demonstrated that SWAT is a useful tool for modelling pesticide behaviour at
catchment scale in UK conditions.
