Modeling phosphorus in the environment - Chapter 9 pptx

215 9 Phosphorus Modeling in the Annualized Agricultural Nonpoint Source Pollution (AnnAGNPS) Model Yongping Yuan U.S. Department of Agriculture-Agricultural Research Service, Oxford, MS Ronald L. Bingner U.S. Department of Agriculture-Agricultural Research Service, Oxford, MS Indrajeet Chaubey University of Arkansas, Fayetteville, AR CONTENTS 9.1 Model Introduction 216 9.2 Watershed Processes Considered in AnnAGNPS 216 9.3 Model Inputs and Outputs 217 9.4 AnnAGNPS Model of Phosphorus Processes 219 9.4.1 Soil Initial Phosphorus Content 220 9.4.2 Organic P Simulation Processes 221 9.4.3 Inorganic P Simulation Processes 222 9.4.3.1 Calculation of Inorganic P Additions to a Cell 222 9.4.3.2 Calculation of Intermediate Inorganic P Mass Balance 223 9.4.3.3 Calculation of Inorganic P Losses from the Soil Profile 224 9.4.4 Total Runoff Losses 226 9.5 Model Application 226 9.5.1 Study Watershed and Monitoring Information 226 9.5.2 Input Data Preparation 227 © 2007 by Taylor & Francis Group, LLC 216 Modeling Phosphorus in the Environment 9.5.3 Sensitivity Analysis 229 9.5.4 Model Calibration and Validation 232 9.6 Model Limitations 238 9.7 Conclusions 238 References 238 9.1 MODEL INTRODUCTION The Annualized Agricultural Nonpoint Source Pollution (AnnAGNPS) model is an advanced technological watershed evaluation tool that has been developed through a partnership between two U.S. Department of Agriculture (USDA) agencies — the Agriculture Research Service (ARS) and the Natural Resources Conservation Service (NRCS) — to aid in the evaluation of watershed responses to agricultural management practices (Bingner and Theurer 2001). AnnAGNPS is a continuous-simulation, daily time-step, pollutant loading model designed to simulate long-term chemical and sedi- ment movement from agricultural watersheds (Bingner et al. 2003). The spatial vari- ability of soils, land use, and topography within a watershed is accounted for by dividing the watershed into many user-specified, homogeneous, drainage-area-determined cells. For individual cells, runoff, sediment, and pollutant loadings can be predicted from precipitation events that include rainfall, snowmelt, and irrigation. Each day, AnnAGNPS simulates runoff, sediment, nutrients, and pesticides leaving the land surface and being transported through the watershed channel system to the watershed outlet before the next day is considered. The model routes the physical and chemical constituents from each cell into the stream network and finally to the watershed outlet and has the capability to identify the sources of pollutants at their origin and to track them as they move through the watershed system. The AnnAGNPS model has evolved from the original single-event Agricultural Nonpoint Source (AGNPS) model developed in the early 1980s by the USDA-ARS (Young et al. 1989, 1995). The AGNPS model was developed to simulate runoff and water-quality response of agricultural watersheds ranging from a few hectares to 20,000 hectares from a single rainfall event. The AGNPS model has been applied throughout the world to investigate various water quality problems. The AnnAGNPS model includes significantly more advanced features but retains many of the impor- tant features of AGNPS. (The complete suite of AnnAGNPS model, composed of programs, pre- and post-processors, technical documentations, and user’s manuals, is currently available at http://www.ars.usda.gov/Research/docs.htm?docid=5199.) 9.2 WATERSHED PROCESSES CONSIDERED IN AnnAGNPS The hydrology components considered within AnnAGNPS are rainfall, interception, runoff, evapotranspiration (ET), infiltration/percolation, subsurface lateral flow, and sub- surface drainage. The runoff from each cell is calculated using the Soil Conservation Service (SCS) curve number (CN) method (Soil Conservation Service 1985). The mod- ified Penman equation (Jenson et al. 1990; Penman 1948) is used to calculate the potential ET, and the actual ET is represented as a fraction of potential ET. The fraction is a linear © 2007 by Taylor & Francis Group, LLC Phosphorus Modeling 217 function of soil moisture between wilting point and field capacity. For percolation, only the downward drainage of soil water by gravity is calculated (Bingner et al. 2003). Lateral flow is calculated using Darcy’s equation, and subsurface drainage is calculated using Hooghoudt’s equation (Freeze and Cherry 1979; Smedema and Rycroft 1983). Amount of sheet and rill soil erosion loss — not field deposition — for each runoff event is calculated using the Revised Universal Soil Loss Equation (RUSLE) model (Renard et al. 1997). A delivery ratio, which quantifies the amount of sediment deposited in the field and the amount of sediment delivered to the stream, is calcu- lated using the Hydrogeomorphic Universal Soil Loss Equation (HUSLE) model (Theurer and Clarke 1991). Ephemeral gully erosion is based on the Ephemeral Gully Erosion model (Merkel et al. 1988). The model uses the Bagnold equation (Bagnold 1966) to determine the sediment transport capacity of the stream and a modified Einstein equation to determine the sediment transport in the stream system (Bingner et al. 2003). Sediment is partitioned into five classes: clay, silt, sand, small aggregates, and large aggregates. The model estimates particle-size distribution of deposited sediment by taking into account the density and fall velocity of each class. The AnnAGNPS model calculates a daily mass balance within each cell for soil moisture, nitrogen (N), phosphorus (P), organic carbon (OC), and pesticides. Plant uptake of nutrients, fertilization, residue decomposition, mineralization, and trans- port are major factors considered to determine the fate of nutrients in the watershed. Both soluble and sediment adsorbed nutrients are considered by the model. The pesticide component is adopted from the Groundwater Loading Effects of Agricultural Management Systems (GLEAMS) model (Leonard et al. 1987). The AnnAGNPS model allows simulation of any number of pesticides and treats each pesticide separately with independent equilibrium assumed for each pesticide. Both soluble and sediment-adsorbed fractions of each pesticide are calculated on a daily time scale. Factors affecting fate and transport of pesticides include foliage wash- off, vertical transport in the soil profile, and degradation. 9.3 MODEL INPUTS AND OUTPUTS A complete list of AnnAGNPS input data sections is shown in Figure 9.1. These data can be grouped into the following categories: climate, watershed physical information, land-management operations, chemical characteristics, and feedlot operations. Daily precipitation, maximum and minimum temperatures, dew point temperature, sky cover, and wind speed are climate data required by the model to perform continuous simulation. Climate data used with AnnAGNPS can be histor- ically measured, synthetically generated using the climate generator program (Johnson et al. 2000), or a combination of the two. Geographic information systems (GIS) data layers of a watershed are needed to characterize the watershed. The GIS data layers must be in sufficient spatial detail to permit the model to accurately reflect the real landscape it represents. Using the GIS layers of digital elevation model (DEM), soils, and land use, a majority of the large data input requirements can be developed using a customized ArcView GIS interface. Those input requirements include watershed and cell delineation, cell land slope, slope direction, cell land use and soil type, and stream reach data, can be © 2007 by Taylor & Francis Group, LLC 218 Modeling Phosphorus in the Environment FIGURE 9.1 A complete list of AnnAGNPS input data sections. Required Required if Referenced Optional AnnAGNPS Identifier Watershed Data Simulation Period Daily Climate Verification Data Global Output Gully Point Source Feedlot Feedlot Management Field Pond Field Pond Management Soils Management Field Tile Drain Impoundment Reach Channel Geometry Reach Nutrient Half Life Management Schedule Fertilizer Application Pesticides Application Management Operation Strip Crop Contours Crop Runoff Curve Number Irrigation Fertilizer Reference Pesticides Reference Non-Crop Cell Data Reach Data © 2007 by Taylor & Francis Group, LLC Phosphorus Modeling 219 developed by using a customized ArcView GIS interface. Additional input require- ments, which include developing the soil layer attributes to supplement the soil spatial layer, describing crop operations and management practices, defining channel hydraulic characteristics, and entering many other optional data sections as needed by the watershed (Figure 9.1), can be organized using the AnnAGNPS Input Editor. The Input Editor is a graphical user interface developed to aid users in selecting appropriate input parameters. Much of the information needed to characterize crop characteristics, field operations (e.g., crop rotation, tillage, planting, harvesting), chemical characteristics, feedlots, and soils can be obtained from databases imported from RUSLE or from other USDA-NRCS data sources. Feedlot information includes daily manure production rates, manure character- istics, amount of manure removed from the field lot, and residual amount of manure available from previous operations. The model outputs include runoff, sediment, nutrient, and pesticide at a temporal scale ranging from daily to yearly. All model outputs can be obtained at any desired location such as specific cells, stream reaches, feedlots, gullies, or point sources. The model also has capabilities to provide source accounting information in terms of the fraction of a pollutant loading passing through any reach location that originated from a user-specified pollutant source area. Cronshey and Theurer (1998), Geter and Theurer (1998), and Theurer and Cronshey (1998) provide detailed information on available model outputs. 9.4 AnnAGNPS MODEL OF PHOSPHORUS PROCESSES Simulation of P transport and transformation processes at a watershed scale is very challenging because of the complexities and uncertainties related to the processes. A complete understanding of the relationship of various P pools and their chemical, physical, and biological interactions in the soil profile is essential for a full descrip- tion of the P cycle in soils and plants (Jones et al. 1984). A model based on mathematical descriptions of fundamental chemical, physical, and biological mech- anisms of the soil P behavior would be ideal for P modeling. In general, the chemical component in AnnAGNPS exists in two phases: dis- solved (solution) in the surface runoff and attached (adsorbed) to clay-size particles resulting from sheet and rill erosion. To simulate P loading, daily soil mass balances of P in a cell are maintained for each computational layer. The daily mass balances of P are adapted from the Erosion Productivity Impact Calculator (EPIC) model (Sharpley et al. 1984; Sharpley and Williams 1990). The P processes simulated in AnnAGNPS are shown in Figure 9.2. More specifically, P is partitioned into inorganic P and organic P, and a separate mass balance is maintained for each. Inorganic P is further broken down into (1) labile P, or P readily available for plant uptake; (2) active P, or P that is more or less reversibly adsorbed to the soil; and (3) stable P, or adsorbed P that is fixed or relatively irreversibly chemisorbed to the soil adsorption complex or as discrete insoluble P minerals. The model simulates the effect of P adsorption that controls P availability to plant uptake and runoff loss, and the model also simulates P movements between labile P and active P and between active P and stable P. Sediment-attached © 2007 by Taylor & Francis Group, LLC 220 Modeling Phosphorus in the Environment P estimated from soil erosion is assumed to be associated with the clay-size fraction of the soil and consists of both organic and inorganic P. Major processes considered are residue decomposition and mineralization, fertilizer application, plant uptake, runoff, and erosion losses. Plant uptake of P is modeled through a simple crop-growth stage index either specified by the user or by the model (Bingner et al. 2003). Phosphorus losses from each AnnAGNPS cell within a stream reach are added to an AnnAGNPS reach. Phosphorus is reequilibrated between dissolved P and sediment-attached P in the reach during transport to the watershed outlet. 9.4.1 S OIL I NITIAL P HOSPHORUS C ONTENT The initial soil P content is needed to initialize AnnAGNPS simulation. Usually, calibration is recommended to define the initial soil P content. The input P levels in the soil profile are input as concentrations, but AnnAGNPS performs calculations on a mass basis. To convert a concentration to a mass, AnnAGNPS uses a conversion factor, conv (Equation 9.1). The conversion factor converts nutrient concentration in soil to mass (in kilograms) using Equation 9.1: (9.1) where conv is the intensive unit-to-extensive-unit conversion factor (kg), ρ b is the bulk density of composite soil layer (g/cm 3 or mg/ m 3 ), D is thickness of soil layer (mm), and A cell is the AnnAGNPS cell area (ha). FIGURE 9.2 Phosphorus processes simulated in AnnAGNPS. Inorganic Organic Erosion loss Erosion loss Runoff loss Plant uptake Plant residue Inorganic fertilizer Organic fertilizer Active Stable Solution Active and Stable (Humic) Fresh Desorption Adsorption Mineralization Decay Residue mineralization conv D A= 10,000 b cell ρ © 2007 by Taylor & Francis Group, LLC Phosphorus Modeling 221 9.4.2 O RGANIC P S IMULATION P ROCESSES All AnnAGNPS mass balances are based on AnnAGNPS cells and are maintained for two composite soil layers. The first soil layer is 203 mm in depth from the surface, typically defined as the tillage layer by RUSLE. The second soil layer is from the bottom of the tillage layer to either an impervious layer or the user-supplied depth of the soil profile. The mass balance equation for organic P simulation is as follows: (9.2) where orgP t is organic P concentration in the composite soil layer for the current day (mg/kg), orgP t–1 is organic P concentration in the composite soil layer for the previous day (mg/kg), resP is organic P addition to a cell from decomposed fresh crop residue (kg), orgP fer is organic P addition to a cell from fertilizer application (kg), hmnP is the mineralization from the humus active organic P pool (kg), and orgP sed is organic P loss from a cell by attaching to sediment (kg). Decomposition is calculated once a day. Equations for residue decomposition were adapted from RUSLE. Only surface decomposition is calculated for crop land. Cell organic P from fertilizer application is the product of the fertilizer applied for the current day and the organic P fraction in the fertilizer. The organic P fraction can be obtained from the fertilizer reference database in AnnAGNPS. The P mineralization equation is adapted from the EPIC model (Sharpley and Williams 1990). Temperature and aeration, represented by soil moisture, are con- sidered for P mineralization (Sharpley and Williams 1990). AnnAGNPS assumes that organic phosphorous is associated with the clay fraction of the soil. Sediment- attached organic P is calculated by Equation 9.3: (9.3) where f orgP is a decimal fraction of organic P in clay in soil layer (g/g), and sed clay is the amount of clay in the mass of sediment (mg). The decimal fraction of organic P is: (9.4) where orgP is the organic P concentration in the composite soil layer (mg/kg), and f clay is the fraction of clay to total composite soil, provided by the soil database. Organic P mass balance is maintained for the second soil layer the same way as the first layer except that fertilizer application and rainfall-induced runoff and sediment loss are not considered. AnnAGNPS assumes that fertilizer application, rainfall-induced runoff, and sediment loss are associated only with the top soil layer. Equation 9.5 represents the mass balance for the second layer: (9.5) orgP orgP resP orgP hmnP orgP tt fer sed 1, =+ +−− −1 ()0000,000 conv orgP f sed sed orgP clay 1000=× × f orgP f orgP clay 1,000,000 = × orgP orgP hmnP conv tt 1,000,000 =− −1 © 2007 by Taylor & Francis Group, LLC 222 Modeling Phosphorus in the Environment 9.4.3 INORGANIC P SIMULATION PROCESSES AnnAGNPS simulates three different pools of inorganic P in the soil. It adapts the principles of the soil mineral P model developed by Jones et al. (1984). Mineral P is transferred among three forms: labile P in solution (available for plant use and runoff loss), active P, and stable P. AnnAGNPS assumes that inorganic P added from fertilizers initially goes to the labile P pool and the active P pool, based on a value of the P sorption coefficient. Fertilizer P that is labile at application may be quickly transferred to the active mineral pool. Many studies have shown that after an appli- cation of inorganic P fertilizer, solution P concentration in the soil decreases rapidly with time due to reaction with the soil. This initial fast reaction is followed by a much slower decrease in solution P that may continue for several years (Barrow and Shaw 1975; Munns and Fox 1976; Rajan and Fox 1972; Sharpley 1982). Flow between the active and stable mineral pools is governed by a P exchange rate. Within each inorganic P pool, addition from fertilizer application is calculated first, followed by the mineralization of organic P. Then, losses through runoff, erosion, and plant uptake are calculated. At the end of each day, the mass balance is updated for each P pool. The simulation is a sequence of adjusting the mass balance of each inorganic P pool. 9.4.3.1 Calculation of Inorganic P Additions to a Cell Fertilizer additions are simulated in one of two ways: well mixed with the top soil layer or unincorporated on the soil surface. On a daily basis, AnnAGNPS checks if there is a tillage operation and the percentage of soil disturbance from the tillage operation. If the soil disturbance exceeds 50% of the top soil layer, any fertilizer applications are considered as mixed. Otherwise, it assumes the applied fertilizer stays on the soil surface. In addition, when the soil disturbance exceeds 50% of the soil, it incorporates not only the applied fertilizer on the current day but also any fertilizer left on the soil surface from previous applications. Therefore, when soil disturbance exceeds 50% of the top soil layer, (9.6) where mnaP is the mass of inorganic P added to the soil profile from the current operation (kg) (and it is assumed to be well mixed with the first soil layer), and surf_inorgP is the surface inorganic P in a cell, added through fertilization at the soil surface (kg). If a fertilizer is applied in the current operation, then (9.7) where inorgP fer is inorganic P applied during the current operation (kg). It is calcu- lated using the rate of fertilizer applied for the current day times the inorganic P fraction (from the fertilizer reference database mass/mass). When soil disturbance is less than 50% of the soil, the fertilizer on the soil surface remains on the soil surface and nothing is incorporated into the soil profile. If a fertilizer is applied for the current operation, then (9.8) mnaP surf inorgP= _ mnaP mnaP inorgP=+ fer surf inorgP surf inorgP inorgP__=+ fer © 2007 by Taylor & Francis Group, LLC Phosphorus Modeling 223 Then, AnnAGNPS checks if a rainfall event occurred, and if so, soil inorganic P is adjusted to reflect the rainfall impact. When a rainfall event occurs, it dissolves the soluble P on the soil surface. When the rainfall generates runoff, AnnAGNPS assumes that inorganic P on the soil surface is totally dissolved in the water and is either carried away with runoff or is carried into the soil profile with infiltration. The amount of inorganic P carried away with runoff or carried into the soil profile with infiltration is determined based on the amount of runoff and infiltration from the rainfall event. (9.9) (9.10) where surf_sol_P is mass of inorganic P in runoff (kg), inf_sol_P is the amount of inorganic P carried into the soil profile by infiltration (kg), Q is the amount of surface runoff (mm), and inf is the amount of infiltration (mm). Then, the amount of inorganic P carried into the soil profile by infiltration is added to the mnaP value to reflect the impact of the current rainfall event. 9.4.3.2 Calculation of Intermediate Inorganic P Mass Balance The intermediate inorganic P mass balance refers to P pools with P additions but prior to any P losses to runoff, erosion, and plant uptake. Bottom soil-layer inorganic P does not change with this operation. A portion of the incorporated inorganic P is added into the labile P pool: (9.11) where labP i is the concentration of intermediate labile inorganic P in the composite soil layer (mg/kg), labP start is the concentration of labile inorganic P at the beginning of a day, and it is equal to the labile P at the end of the previous day (mg/kg), mpr is the flow rate of P between labile and active P pools on the current day (+ implies flow from labile to active pool; – implies flow in the opposite direction) (mg/kg/d) (Sharpley and Williams 1990), Psp is the soil type-dependent P sorption coefficient (dimensionless) (Sharpley and Williams 1990), and mnaP is mass of inorganic P added to a cell soil profile (kg). The rest of the incorporated inorganic P is added into the active P pool: (9.12) surf sol P Q Qinf surf inorgP__ () _= + inf sol P inf Qinf surf inorgP__ () _= + labP labP mpr Psp mnaP conv istart 1,000,000 =−+ actP actP mpr Psp mnaP con istart 1,000,000 =++ −()1 vv aspr− © 2007 by Taylor & Francis Group, LLC 224 Modeling Phosphorus in the Environment where actP i is the concentration of intermediate active inorganic P in the composite soil layer (mg/kg), actP start is the concentration of active inorganic P at the beginning of a day (equal to the active P at the end of the previous day) (mg/kg), and aspr is the flow rate of P between active and stable P pools on the current day (+ implies flow from active to stable pool; – implies flow in the opposite direction) (mg/kg/d) (Sharpley and Williams 1990). Stable P pool size is calculated as follows: (9.13) where stbP i is concentration of intermediate stable inorganic P in the composite soil layer (mg/kg) and stbP start is the concentration of stable inorganic P at the beginning of a day (equals to the stable P at the end of the previous day) (mg/kg). Then, the inorganic P pools are further adjusted to add the organic P from mineralization. This mineralized P is partitioned among three inorganic P pools based on the fraction of each inorganic P pool to total inorganic P. (9.14) (9.15) (9.16) where hmnP is the mineralization from the humus active organic P pool in the soil layer on the current day (kg), f lab is the fraction of labile P to total P (total P is the sum of labile P, active P, and stable P), f act is the fraction of active P to total P, and f stb is the fraction of stable P to total P. 9.4.3.3 Calculation of Inorganic P Losses from the Soil Profile This calculation includes sequential adjustments to the P pool size to reflect losses from a cell. 9.4.3.3.1 Loss through Surface Runoff When a rainfall event occurs, runoff interacts with soil and carries soluble inorganic P in the soil profile away from fields. AnnAGNPS assumes the effective depth of runoff interaction with soil to be 10 mm. All soluble inorganic P in the top 10 mm of soil is carried away by the runoff. Soil soluble inorganic P in the top soil layer available for runoff loss is calculated as (9.17) stbP stbP aspr istart =+ labP labP hmnP f conv ii lab 1,000,000 + =+ 1 actP actP hmnP f conv ii act 1,000,000 + =+ × 1 stbP stbP hmnP f conv ii stb 1,000,000 + =+ × 1 soil solinorgP labP Kd inorgP __ (_ ) = +1 © 2007 by Taylor & Francis Group, LLC [...]... information at harvest may © 2007 by Taylor & Francis Group, LLC Phosphorus Modeling 237 Dissolved P loss (g/ha) 1200 Observed 1000 Predicted 800 600 400 200 0 Oct -9 6 Mar -9 7 Sep -9 7 Mar -9 8 Sep -9 8 Mar -9 9 Sep -9 9 Mar-00 Sep-00 Time (months) FIGURE 9. 4 Time series comparison of observed and predicted dissolved P loss 1800 Total P loss (g/ha) 1600 Observed 1400 Predicted 1200 1000 800 600 400 200 0 Oct -9 6 ... crop planting, and pesticide usages have been maintained since 199 6 (Yuan et al 2001) A rate of 72 .9 kg/ha phosphate fertilizer was applied to cotton fields on October 6, 199 8, with equipment that knifes in the material at a depth of 100 mm without further mixing with soil No fertilizer was applied to soybean fields or during the winter wheat cover crop-growth period In the period of 199 5 to 199 6, the U.S... 0.00 0. 19 0. 29 0.37 145 64 0 115 123 117 9 0 0 5 19 41 126 1 79 0 123 124 124 0 0 0 127 63 178 437 231 0 262 768 92 5 47 0 0 37 124 314 2 69 2 29 0 1 69 388 291 0 0 0 162 106 265 199 8 January(142)b February (98 )b March (95 )b April May 106.6 90 .0 88.7 130.8 111.5 59. 3 36.5 37.7 72.6 84.6 69. 6 35.3 18 .9 48 .9 64.3 0.58 0.47 0.18 0.46 0.81 0.51 0.22 0.08 0.43 2.08 39 41 9 101 13 121 55 1 19 177 63 378 3 89 86 468... 236 Modeling Phosphorus in the Environment organic or inorganic initial soil P content increased both dissolved and sedimentattached P losses Based on the sensitivity analysis, attached P loss is more sensitive to the initial soil organic P than soil inorganic P Thus, attempts were made to increase total P loss by increasing the initial soil organic P content, which resulted in an increase in the dissolved... Mar -9 7 Sep -9 7 Mar -9 8 Sep -9 8 Mar -9 9 Sep -9 9 Mar-00 Sep-00 Time (months) FIGURE 9. 5 Time series comparison of observed and predicted total P loss provide a better estimation of plant P uptake parameters than using literature values In addition, after calibration of initial soil P contents, additional calibration of plant P uptakes may also improve simulation results Plant P uptake directly impacts the. .. users could focus their data collection on the more sensitive parameters In a study of the Water Erosion Prediction Project (WEPP) model sensitivity, Nearing et al ( 199 0) used a single value to represent sensitivity of the output parameter over the entire range of the input parameter tested The index described by Equation 9. 24 (Nearing et al 199 0) was selected for sensitivity testing of the AnnAGNPS P... I12 (9. 24) where I1 and I2 are the least and greatest values of input used, respectively, I12 is the average of I1 and I2, O1 and O2 are the output values in response to the two input values, and O12 is the average of O1 and O2 The parameter S represents the ratio of a relative normalized change in output to a normalized change in input An index of 1 indicates a one-to-one relationship between the input... Group, LLC 230 Modeling Phosphorus in the Environment TABLE 9. 1 Input Parameters Considered in the Sensitivity Analysis Values Input Parameters A B(Base Value) P Mixing Code P application rate (kg/ha) Initial soil P Organic P content in Inorganic P the top soil layer (mg/kg) Plant P uptake Cotton (ratio) Soybean Winter wheat YES NA 50 25 NO 72 .9 500 250 0.0003 0.0075 0.0005 0.0023 0.0 095 0.0025 Note:... losses to P mixing code differs from the other parameters analyzed It is similar, however, to P application rate in that the dissolved P is sensitive to the P mixing code whereas the attached P is not The sensitivity of P losses to the P mixing code increases with the increase of P application rate as expected (Table 9. 2) 9. 5.4 MODEL CALIBRATION AND VALIDATION Since initial soil P content had the greatest.. .Phosphorus Modeling 225 where soil_sol_inorgP is the concentration of soluble P available for runoff loss in a cell soil profile on the current day (mg/kg) and Kd_inorgP is the linear partitioning coefficient for inorganic P (the ratio of the mass of adsorbed P to the mass of P in solution) Soluble inorganic P removed by runoff from the top 10 mm of soil is calculated as cell_ soil_ sol_ inorgP . system. The AnnAGNPS model has evolved from the original single-event Agricultural Nonpoint Source (AGNPS) model developed in the early 198 0s by the USDA-ARS (Young et al. 198 9, 199 5). The AGNPS. LLC 222 Modeling Phosphorus in the Environment 9. 4.3 INORGANIC P SIMULATION PROCESSES AnnAGNPS simulates three different pools of inorganic P in the soil. It adapts the principles of the soil mineral. further mixing with soil. No fertilizer was applied to soybean fields or during the winter wheat cover crop-growth period. In the period of 199 5 to 199 6, the U.S. Geological Survey (USGS) installed