Use of geostatistical models to evaluate landscape and stream network controls on post‐fire stream nitrate concentrations

Abstract

Forested watersheds provide many ecosystem services, such as the filtration of sediment, pollutants, and nutrients, which are increasingly threatened by wildfire. For example, stream nutrient concentrations often increase following wildfire and can remain elevated for decades, making downstream waters susceptible to eutrophication. We investigated the drivers of persistent elevated stream nutrients, specifically nitrate (NO 3 À ), in nine watersheds that were burned 16 years prior by the Hayman fire, Colorado, USA. We evaluated the ability of multiple linear regression and spatial stream network modeling approaches to predict observed concentrations of the biologically active solute NO 3 À and the conservative solute sodium (Na + ) which serves as a partial control. Specifically, we quantified the degree to which landscape and stream network characteristics predict stream solute concentrations. Stream Na + exhibited strong spatial autocorrelation that was primarily controlled by topography and hydrology. In contrast, stream NO 3 À had higher spatial variability and was inversely correlated to vegetation cover, measured as mean normalized differenced moisture index (NDMI). Spatially heterogeneous wildfire behaviour left intact forest patches interspersed with high burn severity patches dominated by shrubs and grasses which contributes to the spatial variability in stream NO 3 À concentrations.Post-fire vegetation also interacts with watershed structure to influence stream NO 3 À patterns. For example, severely burned convergent hillslopes in headwaters positions were associated with the highest stream NO 3 À concentrations due to the high proportional influence of hillslope water in these locations. Our findings suggest that targeted reforestation in severely burned convergent hillslopes in headwater positions may enhance the recovery of stream NO 3 À concentrations to pre-fire levels.

Wildfires drive multi-year water quality degradation over the western U.S.

“…Future research may explore alternate modeling methods to increase model skill, examine longer response durations as additional years of data become available for recent wildfires, and incorporate additional covariates in assessment of inter-basin response variability. Normalized differenced vegetation index, soil information, and wildfire severity, for example, have previously been shown to affect post-wildfire water quality 33,34 and may be more closely correlated with constituent response magnitudes.…”

“…Linear models were built for each constituent in each basin, described in detail in Methods. Briefly, to control for hydroclimatic variability across basins and through time, candidate model covariates included total daily precipitation, potential evapotranspiration, maximum temperature, and estimated runoff, as these are known to influence basin-scale water quality 12,33,34 . The framework used for these models is the following:…”

“…Data-driven models often have lower data requirements than physical models, offering a unique opportunity to deepen understanding 16 . Studies using these techniques for post-fire water quality analysis 4,[29][30][31][32][33][34][35] have been relatively narrow in scope, for example, neglecting sediment, DOM, and nutrient responses across western U.S. Here, we apply data-driven methods to quantify postfire water quality signals across a wide range of constituents, evaluating a large sample of watersheds over several decades.…”

The Rural Fires of 2017 and Their Influences on Water Quality: An Assessment of Causes and Effects

“…The extension of the forest burnt area appears to correlate with the water's DO. Eutrophication processes tend to occur in the downstream areas of fire affected areas [46]. However, it was not observable in this particular case, being noteworthy that eutrophication requires a combination of factors such as the increasing temperatures and excessive inputs of nutrients (particularly PO 4 3− ) in surface water, creating disproportionate algae blooms [47].…”

Spatial Heterogeneity and Temporal Stability of Baseflow Stream Chemistry in an Urban Watershed

“…Synoptic stream sampling can be used to characterize spatial solute patterns along a stream length at a snapshot in time, which can complement temporal stream water chemistry measured at fixed locations. Recent work has highlighted that data from synoptic (longitudinal) stream sampling can yield insights into watershed processes and solute sources (Abbott et al, 2018;Dupas et al, 2019;Floriancic et al, 2019;Frei et al, 2021;Gu et al, 2021;Lee-Cullin et al, 2018;McGuire et al, 2014;Pardo et al, 2022;Rhea et al, 2022;Sonne et al, 2017). For example, Pardo et al (2022) used synoptic sampling to demonstrate the connection of nitrification hot spots in upland soils to the stream strongly influenced stormwater nitrate dynamics.…”