Overuse of chemical fertilizers raises the risk of nitrate pollution of groundwater in the North China Plain. To preserve
the groundwater and reduce the economic losses, an efficiently and quickly assessment of nitrate leaching risk on
regional farmland is crucial. In this research we developed a GIS-based model named 'Arc-NLEAP' based on NLEAP
model, combined the statistical and Remote Sensing data, to estimate applied fertilizer rates and crop yields, which are
two key variables indicating amount of input and output nitrogen in crop land, since crop greenness derived by MODIS
may reflect the content of chlorophyll of canopy which is closely related to nitrogen content, and NDVI values of crop
crucial growing periods determine crop production. The simulated results showed that the value for parameter NAL
(Nitrate Available for Leaching) was between 8 kg / ha and 474 kg / ha and the average was 117 kg / ha, for NL (amount
of Nitrate Leached) 18kg / ha (Low) , 59 kg / ha (Average) and 222 kg / ha(High).Percentages of parameter
MRI(Movement Risk Index) accounted for 8%,77% and 15% for low risk, medium risk and high risk respectively.
Taking water leaching index, nitrogen available for leaching, amount of Nitrate Leached, ammonia volatilization and
denitrification into consideration, we defined the N hazard class to evaluate the nitrogen leaching risk and the result
indicated that lager 74% of the study area was labeled as low N hazard class. Despite the spatial patterns for parameters
NAL and NL were similar, the values for MRI was determined by site-specific soil type and the capacity of water
movement principally, demonstrating that measures of controlling nitrate leaching should be based on the spatial pattern
of MRI, along with decreasing the amount of application rate simultaneity.