Estimating Nitrogen Runoff From Agriculture to Coastal Zones by a Rapid GIS and Remote Sensing-Based Method for a Case Study From the Irrigation District Río Mayo, Gulf of California, México

Coastal eutrophication due to agricultural runoff is one of the main ecological problems for coastal zones around the world. The increase in nutrients has created multiple consequences on marine ecosystems, such as harmful algal blooms, zones of hypoxia or anoxia, and loss of biodiversity. The coastal areas of México are no exception. In the scientific community, there has been a great effort to estimate the amount of nutrients that enter marine ecosystems. However, a rapid method to make this estimation without field data is still required. In this study, the cultivated area and the entrance of nutrients to the coastal marine environment were determined for one of the main irrigation districts located in the state of Sonora, which drains into the Gulf of California, Mexico. We used an elevation model combined with the digitization of drain canal maps to delimitate sub-basins and allocate the coastal runoff entry points. Landsat 8 satellite data were classified and validated for the period of two agrarian cycles (2015–2016) to obtain the agriculture parcels by sub-basins. The quantity of the nutrient runoff was estimated using the cultivation area and nitrogen runoff percentage, according to values found in published reports. As a result, we identified eight sub-basins, two of which stand out for the amount of nitrogen that drains both into a coastal lagoon and directly to the sea. We confirmed this information by correlation analysis using Moderate Resolution Imaging Spectroradiometer (MODIS) of the diffuse attenuation coefficient at 490 nm K_d(490) detected around the coastal runoff entry points. We concluded that there is a high input in the coastal zones and lagoons of nutrients and other pollutants from the agricultural zones of the Río Mayo irrigation district. We also concluded that the performance of the method applied to estimate the volume of the nitrogen runoff is useful, rapid, and can be improved with in situ data.