Geology topics

Samuel Saxe

Publications and source records attributed to Samuel Saxe.

7 recordsLinked to original sources

USGS2023

Ensemble estimation of historical evapotranspiration for the conterminous U.S.

Evapotranspiration (ET) is the largest component of the water budget, accounting for the majority of the water available from precipitation. ET is challenging to quantify because of the uncertainties associated with the many ET equations currently in use, and because observations of ET are uncertain and sparse. In this study, we combine information provided by available ET data and equations to produce a new monthly data set for ET for the conterminous U.S. (CONUS). These maps are produced from 1895 to 2018 at an 800 m spatial scale, marking a finer resolution than currently available products over this time period. In our approach, the relative performance of a suite of ET equations is assessed using water balance, flux tower, and remotely sensed ET estimates. At the observation locations, we use error distributions to quantify relative weights for the equations and use these in a modified Bayesian model averaging weighted ensemble approach. The relative weights are spatially generalized using a random forest regression, which is applied to wall-to-wall explanatory variable maps to generate CONUS-wide relative weight maps and ensemble estimates. We assess the performance of the ensemble using a reserved subset of the observations and compare this performance against other national-scale map products for historical to modern ET. The ensemble ET maps are shown to provide an improved accuracy over the alternative comparison products. These ET maps could be useful for a variety of hydrologic modeling and assessment applications that benefit from a long record, such as the study of periods of water scarcity through time.

Water Resources Research↗

USGS2023

Implications of fire-induced evapotranspiration shifts for recharge-runoff generation and vegetation conversion in the western United States

Wildfire has been shown to increase, decrease, or have no detectable effect on actual evapotranspiration (ETa) fluxes in the western United States. Where disturbance-induced shifts are significant, source-water hydrology may be impacted as ETa constitutes the largest outgoing water flux in much of the arid West. We conducted pixel-scale analysis of 30-m ETa data and various meteorologic and landscape variables at 13 burn scars to understand how wildfire disturbance impacted hillslope-to-burn scar-scale hydrology and vegetation conversion. Significant fire-induced ETa reductions (between approximately −15 to −50%) were detected at nine burn scars through the tenth post-fire year, while ETa recovery rate varied substantially by ecoregion and pre-fire vegetation type. Along elevation gradients, both climate and land disturbance influenced the location of runoff/recharge generation zones, and more net water was generated from a snow-dominated burn scar in dry post-fire years than in wet pre-fire years. However, especially in arid locations where ETa is water-limited, compensatory ETa pathways may be more likely to dampen fire effects on total basin water yield where intact vegetation is located between the disturbance footprint and the basin outlet. Relationships between post-fire ETa shifts and early-successional vegetation conversion were also tracked. The majority of burn scars with significant fire-induced ETa reductions experienced conversion patterns typical of the western United States following stand-replacing disturbance, with forests converting to shrub/scrub and/or grassland/herbaceous cover through at least the end of the study period (eight to 15 years depending on date of the fire event). This could have important implications for high-elevation, snow-dominated watersheds – some of the most critical source water areas - as previous research indicates that wildfire activity is moving upslope and into vegetation communities that have not evolved to withstand fire. Finally, we show that much of the Colorado River Basin’s high-yield source water areas are vulnerable to the fire-induced ETa reductions and vegetation conversion observed herein. As such, water managers in the Colorado River Basin can anticipate changes in burn scar hydrology and snowpack mechanics following fire disturbance.

Journal of Hydrology X↗

USGS2021

Machine learning can assign geologic basin to produced water samples using major ion geochemistry

Understanding the geochemistry of waters produced during petroleum extraction is essential to informing the best treatment and reuse options, which can potentially be optimized for a given geologic basin. Here, we used the US Geological Survey’s National Produced Waters Geochemical Database (PWGD) to determine if major ion chemistry could be used to classify accurately a produced water sample to a given geologic basin based on similarities to a given training dataset. Two datasets were derived from the PWGD: one with seven features but more samples (PWGD7), and another with nine features but fewer samples (PWGD9). The seven-feature dataset, prior to randomly generating a training and testing (i.e., validation) dataset, had 58,541 samples, 20 basins, and was classified based on total dissolved solids (TDS), bicarbonate (HCO 3 ), Ca, Na, Cl, Mg, and sulfate (SO 4 ). The nine-feature dataset, prior to randomly splitting into a training and testing (i.e., validation) dataset, contained 33,271 samples, 19 basins, and was classified based on TDS, HCO 3 , Ca, Na, Cl, Mg, SO 4 , pH, and specific gravity. Three supervised machine learning algorithms—Random Forest, k-Nearest Neighbors, and Naïve Bayes—were used to develop multi-class classification models to predict a basin of origin for produced waters using major ion chemistry. After training, the models were tested on three different datasets: Validation7, Validation9, and one based on data absent from the PWGD. Prediction accuracies across the models ranged from 23.5 to 73.5% when tested on the two PWGD-based datasets. A model using the Random Forest algorithm predicted most accurately compared to all other models tested. The models generally predicted basin of origin more accurately on the PWGD7-based dataset than on the PWGD9-based dataset. An additional dataset, which contained data not in the PWGD, was used to test the most accurate model; results suggest that some basins may lack geochemical diversity or may not be well described, while others may be geochemically diverse or are well described. A compelling result of this work is that a produced water basin of origin can be determined using major ions alone and, therefore, deep basinal fluid compositions may not be as variable within a given basin as previously thought. Applications include predicting the geochemistry of produced fluid prior to drilling at different intervals and assigning historical produced water data to a producing basin.

Natural Resources Research↗

USGS2021

Implications of model selection: A comparison of publicly available, conterminous US-extent hydrologic component estimates

Spatiotemporally continuous estimates of the hydrologic cycle are often generated through hydrologic modeling, reanalysis, or remote sensing (RS) methods and are commonly applied as a supplement to, or a substitute for, in situ measurements when observational data are sparse or unavailable. This study compares estimates of precipitation ( P ), actual evapotranspiration (ET), runoff ( R ), snow water equivalent (SWE), and soil moisture (SM) from 87 unique data sets generated by 47 hydrologic models, reanalysis data sets, and remote sensing products across the conterminous United States (CONUS). Uncertainty between hydrologic component estimates was shown to be high in the western CONUS, with median uncertainty (measured as the coefficient of variation) ranging from 11 % to 21 % for P , 14 % to 26 % for ET, 28 % to 82 % for R , 76 % to 84 % for SWE, and 36 % to 96 % for SM. Uncertainty between estimates was lower in the eastern CONUS, with medians ranging from 5 % to 14 % for P, 13 % to 22 % for ET, 28 % to 82 % for R , 53 % to 63 % for SWE, and 42 % to 83 % for SM. Interannual trends in estimates from 1982 to 2010 show common disagreement in R, SWE, and SM. Correlating fluxes and stores against remote-sensing-derived products show poor overall correlation in the western CONUS for ET and SM estimates. Study results show that disagreement between estimates can be substantial, sometimes exceeding the magnitude of the measurements themselves. The authors conclude that multimodel ensembles are not only useful but are in fact a necessity for accurately representing uncertainty in research results. Spatial biases of model disagreement values in the western United States show that targeted research efforts in arid and semiarid water-limited regions are warranted, with the greatest emphasis on storage and runoff components, to better describe complexities of the terrestrial hydrologic system and reconcile model disagreement.

Hydrology and Earth System Sciences↗

USGS2019

GRACE storage change characteristics (2003–2016) over major surface basins and principal aquifers in the Conterminous United States

In this research, we characterized the changes in Gravity Recovery and Climate Experiment’s (GRACE) monthly total water storage anomaly (TWSA) in 18 surface basins and 12 principal aquifers in the Conterminous United States (CONUS) over 2003–2016. Regions with high variability in storage were identified. Ten basins and 4 aquifers showed significant change in storage. Eight surface basins and 8 aquifers were found to show decadal stability in storage. A pixel-based analysis of storage showed that New England basin and North Atlantic Coastal Plain aquifer showed the largest area under positive storage change. Whereas, the Lower Colorado basin and California aquifers showed largest area under negative change. This study found that historically wetter regions (with more storage) are becoming wetter and dryer regions (with less storage) are becoming dryer. Fourier analysis of the GRACE data showed that while all basins exhibited prominent annual periodicities, significant sub-annual and multi-annual cycles also exist in some basins. The storage turnover period was estimated to range between 6 to 12 months. The primary explanatory variable (PEV) of TWSA was identified for each region. This study provides new insights on several aspects of basin or aquifer storage that are important for understanding basin/aquifer hydrology.

Remote Sensing↗

USGS2019

Evaluating the factors responsible for post-fire water quality response in forests of the western USA

Wildfires commonly increase nutrient, carbon, sediment, and metal inputs to streams yet the factors responsible for the type, magnitude and duration of water quality effects are poorly understood. Prior work by the current authors found increased nitrogen, phosphorus and cation exports were common the first five post-fire years from a synthesis of 159 wildfires across the western United States. In the current study, an analysis is undertaken to determine factors that best explain post-fire streamwater responses observed in those watersheds. Increased post-fire total nitrogen and phosphorus loading were proportional to the catchment extent of moderate and high burn severity. Post-fire dissolved metal concentrations increased in catchments with < 2% pre-fire soil organic matter. In contrast, in catchments with > 2% soil organic matter, post-fire dissolved metal concentrations decreased compared to pre-fire conditions. Where post-fire normalized difference vegetation index (NDVI), a remote sensing indicator of live green vegetation, was low, total metal concentrations increased by 25% on average and by > 100% in some cases. When pre-fire soil field capacity exceeded 17%, there was a 750% median increase in total metals export to streams. Overall, the current analysis identified burn severity, post-fire vegetation cover, and several soil properties as the key variables explaining extended post-fire water quality response across a broad range of conditions found in the western US.

Arizona, California, Colorado, Idaho, Montana, New↗

USGS2018

Characterization and evaluation of controls on post-fire streamflow response across western U.S. watersheds

This research investigates the impact of wildfires on watershed flow regimes, specifically focusing on evaluation of fire events within specified hydroclimatic regions in the western United States, and evaluating the impact of climate and geophysical variables on response. Eighty-two watersheds were identified with at least 10 years of continuous pre-fire daily streamflow records and 5 years of continuous post-fire daily flow records. Percent change in annual runoff ratio, low flows, high flows, peak flows, number of zero flow days, baseflow index, and Richards–Baker flashiness index were calculated for each watershed using pre- and post-fire periods. Independent variables were identified for each watershed and fire event, including topographic, vegetation, climate, burn severity, percent area burned, and soils data. Results show that low flows, high flows, and peak flows increase in the first 2 years following a wildfire and decrease over time. Relative response was used to scale response variables with the respective percent area of watershed burned in order to compare regional differences in watershed response. To account for variability in precipitation events, runoff ratio was used to compare runoff directly to PRISM precipitation estimates. To account for regional differences in climate patterns, watersheds were divided into nine regions, or clusters, through k-means clustering using climate data, and regression models were produced for watersheds grouped by total area burned. Watersheds in Cluster 9 (eastern California, western Nevada, Oregon) demonstrate a small negative response to observed flow regimes after fire. Cluster 8 watersheds (coastal California) display the greatest flow responses, typically within the first year following wildfire. Most other watersheds show a positive mean relative response. In addition, simple regression models show low correlation between percent watershed burned and streamflow response, implying that other watershed factors strongly influence response. Spearman correlation identified NDVI, aridity index, percent of a watershed's precipitation that falls as rain, and slope as being positively correlated with post-fire streamflow response. This metric also suggested a negative correlation between response and the soil erodibility factor, watershed area, and percent low burn severity. Regression models identified only moderate burn severity and watershed area as being consistently positively/negatively correlated, respectively, with response. The random forest model identified only slope and percent area burned as significant watershed parameters controlling response. Results will help inform post-fire runoff management decisions by helping to identify expected changes to flow regimes, as well as facilitate parameterization for model application in burned watersheds.

Hydrology and Earth System Sciences↗