SPARROW Model Research Articles

A novel framework reveals anthropogenic stressors of phosphorus polluted river-lake connection water system in Poyang lake basin of China

Poyang lake (PYL), as China's largest freshwater lake, has been suffering from increasing total phosphorus (TP) pollution associated with rapid basinal socio-economic development. However, anthropogenic phosphorus stressors were rarely examined in PYL basin due to its large-scale and complex river-lake connection water system, hampering phosphorus pollution control efforts. In this study, water pollution stress from multiple anthropogenic activities is quantitatively examined in PYL basin based on a newly developed framework coupling grey water footprint (GWF) analysis with the SPARROW model. Results show that the phosphorus source-sink process in PYL basin has been well simulated by SPARROW model quantifying an overall TP delivery rate of 0.39, with catchments closer to PYL showing higher delivery rate of phosphorus (up to over 0.8). The GWF analysis demonstrates that anthropogenic phosphorus sources have imposed much higher pollution stress on PYL than its inflowing rivers, with twelve catchments nearby PYL identified as critical source areas of TP contamination. Agricultural farming, livestock & poultry production, and urban household are recognized as the dominant anthropogenic stressors burdening water environment of PYL. Based on these, policy recommendations are provided for advancing control of the phosphorus pollution stressors. The methodology is effective in refined examination of water pollution sources, which is expected to be applied in other watersheds providing informative diagnosis of water issues especially in lakes.

Seasonally varying contributions of contemporaneous and lagged sources of instream total nitrogen and phosphorus load across the Illinois River basin

Quantifying nutrient sources in streams, their temporal and spatial variability, and drivers of that variability can support effective water resources management. Yet a lack of data and modeling capabilities has previously prevented comprehensive quantification across both space and time. Here a dynamic SPARROW (Spatially Referenced Regressions on Watershed attributes) model that accounts for a lagged delivery of nutrients to streams was developed and applied to simulate seasonal and source-specific total nitrogen (TN) and total phosphorus (TP) loads in streams across the Illinois River basin (IRB). Dynamic load predictions from 2000 through 2020 revealed that a third of the TN and a quarter of the TP instream load originated from non-point sources that were lagged in their delivery from land-application to streams by more than a season. This lagged mass was the largest overall TN source—which was estimated as a lagged expression of previous seasonal non-point sources including fertilizer, manure, atmospheric deposition and fixation, and urban land use. Treated wastewater effluent was the largest TP source exported from the basin, contributing 39 % of the TP load and 15 % of the TN load, and dominated the load in the upper Illinois River near Chicago. Loads in the lower river during this period, conversely, were attributed primarily to a mix of agricultural sources and their lagged fractions from headwater tributaries. Instream processes removed 10 % of the TN load while only 4 % of the TP load was removed during instream transport. With appropriate datasets, the models could be extended to other basins or time periods and used to forecast future seasonal nutrient loads.

A Quantitative Approach for Identifying Nitrogen Sources in Complex Yeongsan River Watershed, Republic of Korea, Based on Dual Nitrogen Isotope Ratios and Hydrological Model

Effective management of nitrate loading in complex river systems requires quantitative estimation to trace different nitrogen sources. This study aims to validate an integrated framework using soluble nitrogen isotope ratios (δ15N–NH4 and δ15N–NO3) and hydrological modeling (hydrological simulation program SPARROW) of the main stream and tributaries in the Yeongsan River to determine anthropogenic nitrogen fluxes among different land-use types in the complex river watershed. The δ15N–NH4 and δ15N–NO3 isotopic compositions varied across different land-use types (4.9 to 15.5‰ for δ15N–NH4 and −4.9 to 12.1‰ for δ15N–NO3), reflecting the different sources of nitrogen in the watershed (soil N including synthetic fertilizer N, manure N, and sewage treatment plant effluent N). We compared the soluble nitrogen isotopic compositions (δ15N–NH4 and δ15N–NO3) of the river water with various nitrogen sources (soil N, manure N, and sewage N) to assess their contribution, revealing that N from sewage treatment plant effluent as a point source was dominant during the dry season and N from forest- and soil-derived non-point sources was dominant due to intensive rainfall during the wet season. The coefficient of determination (R2) between the measured pollution load and the predicted pollution load calculated by the SPARROW model was 0.95, indicating a high correlation. In addition, the EMMA-based nitrogen contributions compared to the SPARROW-based nitrogen fluxes were similar to each other, indicating that large amounts of forest- and soil-derived N may be transported to the Yeongsan River watershed as non-point sources, along with the effect of sewage treatment plant effluent N as a point source. This study provides valuable insights for the formulation of management policies to control nitrogen inputs from point and non-point sources across different land-use types for the restoration of water quality and aquatic ecosystems in complex river systems. Given the recent escalation in human activity near aquatic environments, this framework is effective in estimating the quantitative contribution of individual anthropogenic nitrogen sources transported along riverine systems.

Forested watersheds provide the highest water quality among all land cover types, but the benefit of this ecosystem service depends on landscape context

Conversion of natural land cover can degrade water quality in water supply watersheds and increase treatment costs for Public Water Systems (PWSs), but there are few studies that have fully evaluated land cover and water quality relationships in mixed use watersheds across broad hydroclimatic settings. We related upstream land cover (forest, other natural land covers, development, and agriculture) to observed and modeled water quality across the southeastern US and specifically at 1746 PWS drinking water intake facilities. While there was considerable complexity and variability in the relationship between land cover and water quality, results suggest that Total Nitrogen (TN), Total Phosphorus (TP) and Suspended Sediment (SS) concentrations decrease significantly with increasing forest cover, and increase with increasing developed or agricultural cover. Catchments with dominant (>90 %) agricultural land cover had the greatest export rates for TN, TP, and SS based on SPARROW model estimates, followed by developed-dominant, then forest- and other-natural-dominant catchments. Variability in modeled TN, TP, and SS export rates by land cover type was driven by variability in natural background sources and catchment characteristics that affected water quality even in forest-dominated catchments. Both intake setting (i.e., run-of-river or reservoir) and upstream land cover were important determinants of water quality at PWS intakes. Of all PWS intakes, 15 % had high raw water quality, and 85 % of those were on reservoirs. Of the run-of-river intakes with high raw water quality, 75 % had at least 50 % forest land cover upstream. In addition, PWS intakes obtaining surface water supply from smaller upstream catchments may experience the largest losses of natural land cover based on projections of land cover in 2070. These results illustrate the complexity and variability in the relationship between land cover and water quality at broad scales, but also suggest that forest conservation can enhance the resilience of drinking water supplies.

The evaluation of N/P fate using the SPARROW model: a case study in an arid and semi-arid region, northern China.

The assessment of nutrients' fate from source to sink is critical to water quality control. As an important ecological reserve in the arid and semi-arid regions of China, the Luanhe River Basin (LRB) has suffered from the deterioration of water quality, thus leading to the urgent management and control. However, few studies have devoted to exploring the fate of N/P contaminations for the entire watershed, due possibly to the large drainage area and heterogeneous watershed composition. Here, we attempt to illustrate N/P contaminations delivery and retention processes using the SPAtially Referenced Regression On Watershed attributes (SPARROW) model. The model reveals 97% of the spatial variability in the TN load and 81% in the TP load, verifying its availability and credibility. The results indicate that anthropogenic sources are dominating the N/P load, which account for 68.5% of N and 74.6% of P inputs. The results highlight the significant retention effects of streams and reservoirs, with 16.4% of N and 13.4% of P removals by streams and 24.3% of N and 10.7% of P removals by reservoirs, respectively. Ultimately, only 49,045.2 t yr-1 (or 16.9%) of N and 1668.7 t yr-1 (or 17.1%) of P being transported to the Bohai Sea. In addition, the analysis of influencing factors showed that regional characteristics (e.g., topography, rainfall), stream size, and delivery distance are potential factors affecting the riverine transport, whereas flow rate and surface area are primarily affecting the reservoirs attenuation. In the future, the watershed water quality management should pay more attention to source management and pollution legacy risks to achieve sustainable and healthy watershed development.

Design and Motion Simulation Analysis of a Novel 2D Bionic Flutter Aircraft

In order to improve the symmetry of the flutter mechanism in the bionic flutter aircraft, and then improve the overall motion stability of the flutter aircraft. In this paper, an innovative flutter wing configuration is designed based on a planar crank-slider mechanism and a sparrow model. The geometric relationship of the flutter mechanism is established, the motion of the flutter aircraft is modeled, and the dimensions of the model are optimized. The geometric relationship of the flutter structure was simulated and analyzed by CATIA. The results show that the upper limit angle of the designed flutter structure is βmax=25.82° and the lower limit angle is βmin=6.34°. The CATIA simulation data are consistent with the theoretical values of the established structural geometry model. Meeting the needs of small and medium-sized flutter aircraft.The design provides a theoretical basis for the design and development of the bionic flutter vehicle and the fabrication of a solid prototype.

Ammonium Nitrogen Streamflow Transport Modelling and Spatial Analysis in Two Chinese Basins

Ammonium nitrogen (NH4+-N), which naturally arises from the decomposition of organic substances through ammonification, has a tremendous influence on local water quality. Therefore, it is vital for water quality protection to assess the amount, sources, and streamflow transport of NH4+-N. SPAtially Referenced Regressions on Watershed attributes (SPARROW), which is a hybrid empirical and mechanistic modeling technique based on a regression approach, can be used to conduct studies of different spatial scales on nutrient streamflow transport. In this paper, the load and delivery of NH4+-N in Poyang Lake Basin (PLB) and Haihe River Basin (HRB) were estimated using SPARROW. In PLB, NH4+-N load streamflow transport originating from point sources and farmland accounted for 41.83% and 32.84%, respectively. In HRB, NH4+-N load streamflow transport originating from residential land and farmland accounted for 40.16% and 36.75%, respectively. Hence, the following measures should be taken: In PLB, it is important to enhance the management of the point sources, such as municipal and industrial wastewater. In HRB, feasible measures include controlling the domestic pollution and reducing the usage of chemical fertilizers. In addition, increasing the vegetation coverage of both basins may be beneficial to their nutrient management. The SPARROW models built for PLB and HRB can serve as references for future uses for different basins with various conditions, extending this model’s scope and adaptability.

An ensemble of Bayesian SPARROW models for the Precambrian Shield in the eastern Georgian Bay drainage basin, Ontario, Canada

The present study applied an ensemble of Bayesian SPARROW models in the eastern Georgian Bay drainage basin informed by multi-agency tributary water quality monitoring data collected in the area. Consistent with our current understanding of the role of wetlands in the Precambrian Shield, our analysis showed that they could be responsible for nearly 30% of the total phosphorus (TP) loading from forested areas and 23% of the delivered TP from the eastern Georgian Bay drainage basin. Agricultural areas contribute over 40% of the TP loading associated with anthropogenic activities, which was two times higher than the predicted nutrient losses per unit area in southern Georgian Bay. This finding raises concerns regarding the likelihood of elevated eutrophication risks from future expansion of agriculture in central and northern Ontario. Considering the uncertainty pertaining to their broader influence, cottage septic fields were estimated to be the second anthropogenic P source after agriculture, accounting for 9% of the delivered TP loading to the downstream outlets into Georgian Bay. Research on eutrophication of coastal embayments in Georgian Bay has historically focused on factors, such as basin morphometry, internal P loading, and dreissenid-mediated nearshore shunt. In this context, our SPARROW model offered an additional perspective by estimating that a significant fraction (≈90%) of the TP loading delivered to the Georgian Bay embayments could be originating from upstream sites, even though our predictions suggested that nearly half (49%) of P loading reaching the stream network deposits on the sediments of inland lakes in central Ontario.

Estimating urban air pollution contribution to South Platte River nitrogen loads with National Atmospheric Deposition Program data and SPARROW model

Air pollution is commonly disregarded as a source of nutrient loading to impaired surface waters managed under the Clean Water Act per states’ 303(d) list programs. The contribution of air pollution to 2017–2018 South Platte River nitrogen (N) loads was estimated from the headwaters to the gage at Weldona, Colorado, USA (100 km downstream of Denver), using data from the National Atmospheric Deposition Program (NADP) and the SPAtially Referenced Regressions On Watershed attributes (SPARROW) model. The NADP offers wet-deposition raster created by spatial interpolation of data collected from regionally representative monitoring sites, excluding the influences from urban site data. For this study, NADP wet-deposition data obtained from sites within the Denver-Boulder, Colorado, urban corridor were included and excluded in new spatial interpolations of wet-deposition raster, which were used as input for SPARROW to model the influence of urban air pollution sources on South Platte River loads. Because urban air pollution is already incorporated into the NADP Total Deposition modeling methodology, dry N deposition was held constant for each SPARROW modeling scenario when dry deposition was included. By including the urban wet-deposition data in the model, estimated N loading to the South Platte River at Denver increased by 9–11 percent. Factoring in dry deposition at a 1:1.8 dry:wet ratio obtained from the results, urban air pollution was estimated to contribute as much as 20 percent of the nitrate Total Maximum Daily Load for Segment 14 of the South Platte River.

Quantify phosphorus transport distinction of different reaches to estuary under long-term anthropogenic perturbation.

Typical diffuse pollutants such as phosphorus (P) have long been a hot topic in the surface-water research field. As the fifth-largest river in the world, the Yellow River Basin (YRB) suffers from significant soil erosion and relatively high intensity of agricultural activities, which bring large amounts of P loads. However, owing to the large drainage area, few studies have investigated the transport and attenuation dynamic processes or provided a precise calculation of the total phosphorus (TP) load for the entire YRB. In this study, the SPAtially Referenced Regressions on Watershed Attributes (SPARROW) model was used to simulate and investigate the spatial variation and transport mechanism of P in the YRB. The YRB was divided into 60 sub-basins, and the data of drainage area, spatial attribute, streamflow, and monitored flux were integrated into the model correspondingly. Calculated R2 values confirm that 84% of the spatial variability in annual TP loads can represent regional processes. The estimated YRB TP load was 41,760 tons per year, contributed by farmland (64%), construction land (27%), grassland (5%), and forest (4%). In addition, the P transport dynamic process, contribution, and sensitivity of different P flux sources in different reaches were represented and identified. Our study highlights the significance of farmland as the most significant factor exacerbating TP pollution. As the study conducted the first attempt to develop a SPARROW model, integrated management strategies that consider the spatially varying P sources and associated TP transport were proposed. Additionally, to improve the ecological health of basin, it is critical to further increase P utilization efficiency and enhance cross-regional cooperation throughout the basin.

Nitrogen and Phosphorus Sources and Delivery from the Mississippi/Atchafalaya River Basin: An Update Using 2012 SPARROW Models

AbstractNitrogen (N) and phosphorus (P) inputs throughout the Mississippi/Atchafalaya River Basin (MARB) have been linked to the Gulf of Mexico hypoxia and water‐quality problems throughout the MARB. To describe N and P loading throughout the MARB, SPAtially Referenced Regression On Watershed attributes (SPARROW) models were previously developed based on nutrient inputs and management similar to 1992 and 2002. In this study, refined SPARROW models were developed with higher resolution basin delineation, updated (2012) source inputs, improved calibration (load) targets, and additional statistical techniques than used in the previous SPARROW models. Based on the refined models, consistent with past models, N and P loads/yields were the highest from the central part of the MARB (Corn Belt) and along the Mississippi River. Agricultural activities remained the most important N and P source, but more so for N because its input, which could now be distinguished from atmospheric deposition, could be estimated. Natural loss of P from geologic material throughout the MARB was an important source, contributing about 23% of the total P from the MARB, and resulted in specific areas, such as Kentucky and Tennessee, being larger sources of P than previously estimated. This information can help managers decide where efforts will have the largest effects (highest ranked areas) on reducing nutrient loading to the Gulf hypoxia and what are the most important sources of N and P in these areas.

Risk assessment of non-point source pollution of land use system of mountainous watershed and spatially referenced regressions on watershed attributes simulation under geological environment assessment

In order to evaluate and analyze the non-point source pollution risk of mountainous watershed, the multi-criteria analysis method is used for assessment, and the Spatially Referenced Regressions on Watershed Attributes (SPARROW) model is adopted for simulation analysis. The non-point source pollution risk is evaluated based on the geological environment assessment and the relevant theories of the land use system combined with the multi-criteria analysis method. According to the evaluation results, subarea governance is implemented in the mountainous watershed. Besides, the SPARROW model is applied to simulate and analyze the total nitrogen transport in the watershed. The evaluation results reveal that the NPA value, the non-point source pollution risk assessment index, of some areas of the mountainous watershed has reached 0.9 or higher, which belong to heavily polluted areas. The pollution sources mainly come from agricultural production, and deep application of fertilizer can reduce total nitrogen emission. The simulation results show that the pH of the soil is instrumental in the total nitrogen reduction, with the total nitrogen loading coefficient being about 2.74. The research provides important reference for the control and governance of non-point source pollution in mountainous watershed.

Estimate of nutrient sources and transport into Bohai Bay in China from a lower plain urban watershed using a SPARROW model.

In the development of a land-sea coordination management strategy, it is necessary to analyze pollution sources and loads of pollutants entering the sea. This study estimated the sources and transport of total nitrogen (TN) and total phosphorus (TP) entering Bohai Bay in Tianjin, a lower plain urban watershed, using a SPAtially Referenced Regression On Watershed attributes (SPARROW) model. We calibrated the model using TN and TP data from 26 and 27 sites, respectively. The results demonstrated that the R2 values of TN and TP were both above 0.99. In 2013, the TN load delivered to Bohai Bay was 21,320 ton, which could be traced to various sources: upstream (39%), industrial discharge (10%), sewage discharge (34%), fertilizer application (3%), livestock breeding (7%), aquaculture (5%), and rural communities (2%). The TP load delivered to Bohai Bay was 1504 ton, which originated from upstream (33%), industrial discharge (5%), sewage discharge (21%), fertilizer application (5%), livestock breeding (12%), aquaculture (10%), and rural communities (14%). Rational management of the water resources in streams, enhancement of water circulation between rivers and wetlands, and making full use of the effect of both land and water on pollutant retention are the suitable strategies in watershed management, reducing marine pollution.

Modelling the sources and transport of ammonium nitrogen with the SPARROW model: A case study in a karst basin

The assessment of nutrients delivered to aquatic ecosystems is important for water quality controls. Mainly due to the complex terrains and subsurface hydrological systems in karst regions, it is challenging to understand nutrient delivery pathways and quantify contributions of various sources to surface waterbodies in karst basins, e.g., via the use of mechanistic models. To resolve this issue, a statistical water quality model (i.e., the SPAtially Referenced Regression On Watershed attributes-SPARROW model) was tested to estimate the mean annual transport, concentration, and yield of ammonium nitrogen (NH4+-N) contributed by natural and human sources in the Wujiang River Basin (WRB) in southwest China, where the nutrient inputs and pathways have been significantly altered by anthropogenic activities. Overall, the modelling results explained about 86% of the variability in the observed mean annual NH4+-N fluxes, attesting the applicability of the SPARROW model for estimating NH4+-N transport at mean annual time scales in karst basins. Moreover, the results indicated that the anthropogenic sources (i.e., fertilizer, livestock manure, and waste water) were the main origins of NH4+-N, accounting for a total load of 66.8% in waterbodies. In addition, the leakage of NH4+-N into groundwater from the karst area was evaluated, leading to a reduction of NH4+-N delivery to surface waterbodies for about 36.9% with a range from 31.3% to 52.2% in the seven main subbasins in the WRB. The damming effect of the constructed reservoirs on the NH4+-N delivery differed noticeably with the lowest reduction rate (2.4%) in the Suofengying reservoir and the highest rate (79.1%) in the Hongfenghu reservoir. It was found that the interception efficiency of lake-type reservoirs was generally higher than that of river-type reservoirs in the WRB. The results of this study demonstrate the usefulness of the SPARROW model for evaluating nutrient transport and pathways in karst regions, which can provide critical information for better management to control nutrients in those regions.

Advances in Quantifying Streamflow Variability Across Continental Scales: 1. Identifying Natural and Anthropogenic Controlling Factors in the USA Using a Spatially Explicit Modeling Method

AbstractDespite considerable progress in hydrological modeling, challenges remain in the interpretation and accurate transfer of hydrological information across watersheds and scales. In the conterminous United States (CONUS), these limitations are related to spatial inconsistencies and constraints in hydrological model structures, including a lack of spatially explicit process components (streams, reservoirs, and watershed development) and restricted estimation of model parameters across watersheds. Collectively, such limitations can impede identification of the causes of streamflow variations across the diversity of watershed sizes and land uses in the CONUS and contribute to model imprecision and spatial inconsistencies in prediction uncertainties. We addressed these concerns with a new approach, the first hybrid (statistical‐mechanistic) SPARROW (SPAtially Referenced Regression On Watershed attributes) model of long‐term mean annual streamflow, applied across diverse environmental settings of the CONUS. The hybrid model coupled previous catchment‐scale (1 km) water balance predictions of “natural” unit area runoff, which are inclusive of major water cycling processes, with additional explanatory variables (e.g., soils, vegetation, land use, topography, water losses in streams, and reservoirs) that account for the effects of natural and cultural water supply and demand processes that operate over large spatial scales and explain streamflow variability across CONUS river basins. Accounting for these statistically unique effects, including a nonlinear surface area‐dependent scaling of water loss in river networks, significantly improved the accuracy of mean streamflow predictions in CONUS basins. Our hybrid modeling approach provides new methods for transferring hydrological information to ungauged locations in river networks, especially those in larger and more culturally diverse CONUS watersheds.

CLUES model calibration and its implications for estimating contaminant attenuation

Catchment water quality models are essential for fresh water management; however, their value is dependent on their performance and level of uncertainty and for this information to be communicated in a transparent and understandable way to key stakeholders.Here we present the latest calibration of the Catchment Landuse for Environmental Sustainability model (CLUES) and examine the implications of the calibration for estimating in-stream contaminant attenuation. CLUES estimates catchment mean annual loads of Total Nitrogen, Total Phosphorus and E. coli and is widely used in New Zealand for both catchment planning and policy development. CLUES contains three freshwater model components derived from existing water quality models. Two are based on the New Zealand Overseer and SPASMO models and have been pre-calibrated for use in CLUES. The third component is based on the USGS SPARROW model and its parameters have been calibrated against annual loads estimated from monthly water quality data from catchments across the country.We found that CLUES gives reasonable load estimates at the catchment scale (Nash-Sutcliff efficiencies > 0.8 for all the contaminants). However, there was significant uncertainty in the SPARROW parameterisation. We conclude that while CLUES can be used to estimate catchment contaminant loads, it cannot adequately estimate instream attenuation. Improved representation of lower order streams in the calibration data would allow us to evaluate the source yields from each of the model components to better estimate attenuation.

M55 WEIGHTED GENE CO-EXPRESSION NETWORK ANALYSIS OF THE HUMAN FRONTAL CORTEX REVEALS NOVEL INSIGHTS INTO THE SCHIZOPHRENIA-ASSOCIATED 3Q29 DELETION SYNDROME

Catchment water quality models are essential for fresh water management; however, their value is dependent on their performance and level of uncertainty and for this information to be communicated in a transparent and understandable way to key stakeholders.Here we present the latest calibration of the Catchment Landuse for Environmental Sustainability model (CLUES) and examine the implications of the calibration for estimating in-stream contaminant attenuation. CLUES estimates catchment mean annual loads of Total Nitrogen, Total Phosphorus and E. coli and is widely used in New Zealand for both catchment planning and policy development. CLUES contains three freshwater model components derived from existing water quality models. Two are based on the New Zealand Overseer and SPASMO models and have been pre-calibrated for use in CLUES. The third component is based on the USGS SPARROW model and its parameters have been calibrated against annual loads estimated from monthly water quality data from catchments across the country.We found that CLUES gives reasonable load estimates at the catchment scale (Nash-Sutcliff efficiencies > 0.8 for all the contaminants). However, there was significant uncertainty in the SPARROW parameterisation. We conclude that while CLUES can be used to estimate catchment contaminant loads, it cannot adequately estimate instream attenuation. Improved representation of lower order streams in the calibration data would allow us to evaluate the source yields from each of the model components to better estimate attenuation.

Phosphorus and Nitrogen Transport in the Binational Great Lakes Basin Estimated Using SPARROW Watershed Models

AbstractEutrophication problems in the Great Lakes are caused by excessive nutrient inputs (primarily phosphorus, P, and nitrogen, N) from various sources throughout its basin. In developing protection and restoration plans, it is important to know where and from what sources the nutrients originate. As part of a binational effort, Midcontinent SPARROW (SPAtially Referenced Regression On Watershed attributes) models were developed and used to estimate P and N loading from throughout the entire basin based on nutrient inputs similar to 2002; previous SPARROW models only estimated U.S. contributions. The new models have a higher resolution (~2‐km2 catchments) enabling improved descriptions of where nutrients originate and the sources at various spatial scales. The models were developed using harmonized geospatial datasets describing the stream network, nutrient sources, and environmental characteristics affecting P and N delivery. The models were calibrated using loads from sites estimated with ratio estimator and regression techniques and additional statistical approaches to reduce spatial correlation in the residuals and have all monitoring sites equally influence model development. SPARROW results, along with interlake transfers and direct atmospheric inputs, were used to quantify the entire P and N input to each lake and describe the importance of each nutrient source. Model results can be used to compare loading and yields from various tributaries and jurisdictions.

Salinity Yield Modeling of the Upper Colorado River Basin Using 30‐m Resolution Soil Maps and Random Forests

AbstractSalinity loading in the Upper Colorado River Basin (UCRB) costs local economies upward of $300 million U.S. dollars annually. Salinity source models have generally included coarse spatial data to represent nonagriculture sources. We developed new predictive soil property and cover maps at 30‐m resolution to improve source representation in salinity modeling. Salinity loading erosion risk indices were also created based on soil properties, remotely sensed bare ground exposure, and topographic factors to examine potential surface soil erosion drivers. These new maps and data from previous SPARROW models were related to recently updated records of salinity at 309 stream gauges in the UCRB using random forest regressions. Resulting salinity yield predictions indicate more diffuse salinity sources, with slightly higher yields in more arid portions of the UCRB, and less overall load coming from irrigated agricultural sources. Model simulations still indicate irrigation to be the major human source of salinity (661,000 Mg or 12%) and also suggest that 75,000 Mg (1.4%) of annual salinity in the UCRB is coming from areas with excessive exposed bare ground in high‐elevation mountain areas. Model inputs allow for field‐scale screening of locations that could be targeted for salinity control projects. Results confirm recent studies indicating limited surface erosional influence on salinity loading in UCRB surface waters, but impacts of monsoonal runoff events are still not fully understood, particularly in drylands. The study highlights the utility of new predictive soil maps and machine learning for environmental modeling.

Radiative Heat Transfer in Two-Dimensional Cylindrical Medium Coupled with BRDF Surface

For radiative heat transfer analysis and temperature measurements, the surface is usually assumed to be blackbody, diffuse, or specular, which may cause obvious errors under actual working conditions. The bidirectional reflectance distribution function (BRDF), which is considered as a relatively strict approach for characterizing a real surface, has been adopted in heat transfer analysis. In this study, two BRDF models—the Minnaert model and the Torrance and Sparrow model—are applied to investigate the effects of different boundary conditions on the radiative heat transfer. Additionally, the distribution of ratios of energy scattered by the medium or reflected by the boundary surface method is extended to solve the radiative transfer in a two-dimensional graded-index medium coupled with BRDF surfaces in a cylindrical coordinate system. The results show that greater deviation of the BRDF surface from the diffuse characteristics yields a larger difference of the radiative heat flux and intensity distributions between the BRDF and the diffuse surface. The radiative heat flux deviation reaches 12.78%, and more significant differences exist in the radiative intensity along some directions under different boundary conditions. The specular reflection plays a leading role at high reflection angles. However, the increased scattering ability can weaken the influence of the reflection of the BRDF on the radiative intensity distributions.