Nitrate Runoff Contributing from the Agriculturally Intensive San Joaquin River Watershed to Bay-Delta in California

Abstract

Nitrogen loading from agricultural landscapes can trigger a cascade of detrimental effects on aquatic ecosystems. Recently, the spread of aquatic weed infestations (Eichhornia crassipes, Egeria densa, Ludwigia spp., and Onagraceae) in the Sacramento-San Joaquin Delta of northern California has raised concerns, and nitrogen loading from California’s intensive farming regions is considered as one of the major contributors. In this study, we employed the Soil and Water Assessment Tool (SWAT) to simulate nitrogen exports from the agriculturally intensive San Joaquin River watershed to the Delta. The alternate tile drainage routine in SWAT was tested against monitoring data in the tile-drained area of the watershed to examine the suitability of the new routine for a tile nitrate simulation. We found that the physically based Hooghoudt and Kirkham tile drain routine improved model performance in representing tile nitrate runoff, which contributed to 40% of the nitrate loading to the San Joaquin River. Calibration results show that the simulated riverine nitrate loads matched the observed data fairly well. According to model simulation, the San Joaquin River plays a critical role in exporting nitrogen to the Delta by exporting 3135 tons of nitrate-nitrogen annually, which has a strong ecological implication in supporting the growth of aquatic weeds, which has impeded water flow, impairs commercial navigation and recreational activities, and degrades water quality in Bay-Delta waterways. Since nitrate loadings contributed by upstream runoff are an important nutrient to facilitate weed development, our study results should be seen as a prerequisite to evaluate the potential growth impact of aquatic weeds and scientific evidence for area-wide weed control decisions.

Comparison of Two Tile-Drain Methods in SWAT via Temporal and Spatial Testing for an Iowa Watershed

“…The NSE and KGE results for the original and modified equations were statistically similar, although the Pbias indicated slightly better agreement (6.5% versus 8.0%) for the modified method. These results are similar to those found by Wang et al (2019), where there were no differences between the two methods for comparing streamflow on a monthly basis. The NSE and Pbias values exceeded ratings of very good and good (table 4), respectively, underscoring that the accuracy of the hydrological simulations was maintained with both methods.…”

“…It is important to note that all of these model applications (Kalcic et al, 2015;Boles et al, 2015;Guo et al, 2018) were performed for relatively small watersheds with drainage areas ≤ 69 km 2 (table 1). Wang et al (2019) did not report significant differences between the two methods in monthly flow simulations for a 40,000 km 2 watershed (table 1). However, they found that the modified method resulted in an improved match between simulated and measured nitrate loads.…”

Restoring wetlands on intensive agricultural lands modifies nitrogen cycling microbial communities and reduces N2O production potential

“…At the pasture site, the soil pH was even lower than at the alfalfa and corn site, with a mean value of 4.8. Therefore, the low nifH gene abundance at the pasture site will show that atmospheric N fixation is negligible, and cattle grazing could be currently the main N input source (Wang et al, 2019).…”

“…(Miller et al, 2008;Miller and Fujii, 2010). Since intensive agriculture is causing elevated nitrate concentration in both drainage water and river water (Schlegel and Domagalski, 2015;Wang et al, 2019), all of these wetlands will receive N through the inflow water, which maintains the water level. In addition, all of these wetland sites will experience at least some growth of Azolla spp.…”