Abstract:
Nitrate contamination in surface and groundwater remains a widespread problem in agricultural
watersheds is primarily associated to high levels of percolation or leakage from fertilized soil,
which allows easy infiltration from soil into groundwater. This study was aimed to predict canopy
water content to determine the nitrate contamination index resulting from nitrogen fertilizer loss
in surface and groundwater. The study used Geographically Weighted Regression (GWR) model
using MODIS 006 MOD13Q1-EVI Earth observation data, crop information and rainfall data.
Satellite data collection was synchronized with regional crop calendars and calibrated to plant
biomass. The average plant biomass during observed plant growth stages was between 0.19 kg/
m
at the minimum and 0.57 kg/m
2
at the maximum. These values are based on the growth stages
of crops and provide a solid basis for monitoring and validating crop water productivity data. The
simulation results were validated with a high correlation coefficient (R
2
=0.996, P < 0.0005) for
the observed rainfall in the growing zone compared to the predicted canopy water content. The
nitrate contamination index assessment was conducted in 2004, 2008, 2009, 2010, 2011, 2013,
2014, 2015, 2018 and 2020. Canopy water content and root zone seasonal water content were
measured in (%) per portion as indicators of the NO
3-N-nitrate contamination index in these
years (0.391, 0.316, 0.298, 0.389, 0.380, 0.339, 0.242, 0.342 and 0.356).
