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Soil Properties and Computer Models How soil properties are used in environmental models.

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Presentation on theme: "Soil Properties and Computer Models How soil properties are used in environmental models."— Presentation transcript:

1 Soil Properties and Computer Models How soil properties are used in environmental models

2 NRCS Models AGNPS EPIC GLA GLEAMS HUWQ HYDRIC MMP NAPRA NUTRIENT SCREEN ROSETTA RUSLE2 RUSLE2 RZWQ RZWQ SWAT SWAT SWRRB SWRRB VEGSPEC VEGSPEC WATER BUDGET WATER BUDGET WEBD WEBD WEPS WEPS WEQ WEQ WinPST WinPST

3 AGNPS AGricultural Non-Point Source (AGNPS) Developed by Agricultural Research Service (ARS) Predicts soil erosion and nutrient transport/loadings from agricultural watersheds using 8 GIS layers

4 AGNPS GIS Layers Soils Elevation Land use Management practice Fertilizer or nutrient inputs Type of machinery used for land preparation Channel slope Slope length factor

5 AGNPS – Soil Factors Albedo Base Saturation Bulk Density CaCO3Clay Ratio Field Capacity Fine Sand Ratio Hydrologic Soil Group Impervious Depth Inorganic N Ratio Inorganic P Ratio K-Factor Layer Depth Number Soil Layers Organic Matter Ratio Organic Matter Ratio Ph Ph Rock Ratio Rock Ratio Sand Ratio Sand Ratio Saturated Conductivity Saturated Conductivity Silt Ratio Silt Ratio Soil Name Soil Name Soil Texture Soil Texture Specific Gravity Specific Gravity Volcanic Code Volcanic Code Wilting Point Wilting Point Organic N Ratio * Organic N Ratio * Organic P Ratio * Organic P Ratio *

6 EPIC Erosion Productivity-Impact Calculator Developed by Agricultural Research Service (ARS) Assess the effect of soil erosion on productivity. Predict the effects of management decisions on soil, water, nutrient, and pesticide movements and their combined impact on soil loss, water quality, and crop yields for areas with homogeneous soils and management.

7 EPIC Layer Depth Bulk Density Wilting Point Field Capacity Sand Content Silt Content Organic N Concentration pH Sum of Bases Organic Carbon Calcium Carbonate Cation Exchange Capacity Coarse Fragment Content Bulk Density Oven Dry Saturated Conductivity Saturated Conductivity Electrical Conductivity Electrical Conductivity surface texture and modifier surface texture and modifier slope gradient l and h slope gradient l and h flooding frequency flooding frequency other phase criteria other phase criteria Kw & Kf Kw & Kf T I Hydrologic Group Hydrologic Group NIRR capability class NIRR capability class IRR capability class IRR capability class

8 GLEAMS Groundwater Loading Effects of Agricultural Management Systems Developed by Agricultural Research Service (ARS) GLEAMS was developed to evaluate the impact of management practices on potential pesticide and nutrient leaching within, through, and below the root zone.

9 GLEAMS clay total separate rock frag 3 to 10 in rock frag greater than 10 in organic matter percent l, rv, h bulk density one third bar water satiated sieve number 4 particle density

10 HUWQ Hydrologic Unit Water Quality Developed by NRCS ITC conceived as a common interface for four of the pollutant loading models (GLEAMS), (EPIC), (AGNPS), and (SWRRBWQ)

11 HUWQ albedo dry bulk density one third bar bulk density fifteen bar calcium carbonate equivalent cation exch capcty nh4oacph7 clay total separate effective cation exch capcty Component soil moisture depth_ l restriction depth to top water one third bar water one tenth bar hydrologic group soil erodibility factor whole soil erodibility factor whole soil erodibility factor Kf soil erodibility factor Kf sat hydraulic conductivity sat hydraulic conductivity rock frag 3 to 10 in rock frag 3 to 10 in rock frag greater than 10 in rock frag greater than 10 in horizon depth to top horizon depth to top Map unit symbol Map unit symbol organic matter percent organic matter percent water satiated water satiated linear extensibility percent linear extensibility percent silt total separate silt total separate sieve number 4 sieve number 4 ph 1 1 water ph 1 1 water particle density particle density

12 HYDRIC component interp component interp restriction component kind component name component percent r drainage class flooding duration class flooding frequency class geomorph feat name geomorph feat type name horizon depth to bottom r horizon depth to top r mapunit acres mapunit name mapunit symbol mapunit symbol ponding duration class ponding duration class ponding frequency class ponding frequency class sat hydraulic conductivity h sat hydraulic conductivity h sat hydraulic conductivity l sat hydraulic conductivity l sat hydraulic conductivity r sat hydraulic conductivity r soil moist depth to top h soil moist depth to top h soil moist depth to top l soil moist depth to top l soil moist depth to top r soil moist depth to top r soil moisture status soil moisture status taxonomic great group taxonomic great group taxonomic order taxonomic order taxonomic subgroup taxonomic subgroup taxonomic suborder taxonomic suborder taxonomic temp regime taxonomic temp regime

13 MMP Manure Management Planner Developed by Purdue University used to create manure management plans for crop and animal feeding operations

14 MMP Area symbol Component name Component pct r Map unit symbol Organic matter h Organic matter l Restriction depth l Slope h Slope l Texture

15 NAPRA National Agricultural Pesticide Risk Analysis developed jointly by NRCS and the University of Massachusetts. evaluates the potential loss of pesticides to ground and surface waters by modeling pesticide movement, toxicity and crop management techniques under specific weather and soil conditions

16 NAPRA bulk density one third bar clay total separate ECEC horizon depth to top ? hydrologic group organic matter percent pore quantity pore shape pore size restriction depth to top sand coarse separate sat hydraulic conductivity sieve number 4 sieve number 4 silt total separate silt total separate sodium adsorption ratio sodium adsorption ratio soil erodibility factor rf soil erodibility factor rf soil erodibility factor whole soil erodibility factor whole Soil moisture depth ? Soil moisture depth ? Soil moisture status Soil moisture status water fifteen bar water fifteen bar water one tenth bar water one tenth bar water one third bar water one third bar water satiated water satiated

17 ROSETTA U.S. ARS Salinity Laboratory m Rosetta can be used to estimate the following properties: Water retention parameters according to van Genuchten (1980) Saturated hydraulic conductivity Unsaturated hydraulic conductivity parameters according to van Genuchten (1980) and Mualem (1976)

18 ROSETTA Area symbol Clay total separate r Comp name Db third bar_r Hz depb_r Hz dept_r Mu sym Sand total_r Silt total_r Water fifteen bar_r Water third bar_r

19 RUSLE2 Revised Universal Soil Loss Equation, Version 2 (RUSLE2) Developed by Agricultural Research Service (ARS) SLE2_Technology.htm primarily to guide conservation planning, inventory erosion rates and estimate sediment delivery.

20 RUSLE2 Component Name Component Percent Hydrologic Soil Group – drained and/or undrained K Factor (Kf) Map Unit Symbol Map Unit Name – slope phase, erosion phase Soil Texture And Modifier T Factor Taxonomic Order Total RV Clay For The Surface Horizon Total RV Sand For The Surface Horizon Total RV Silt For The Surface Horizon

21 RZWQ Root Zone Water Quality Developed by Agricultural Research Service (ARS) process-based model that simulates the growth of the plant and the movement of water, nutrients and agro-chemicals over, within and below the crop root zone of a unit area of an agricultural cropping system under a range of common management practices

22 RZWQ cec7 clay_total_separate Db third bar hzdepb_r om pH 01m cacl2 pH 1to1 h2o sand_total_separate silt_total_separate water_one_tenth_bar water_one_third_bar

23 SWAT Soil & Water Assessment Tool Soil & Water Assessment Tool USDA Agricultural Research Service at the Grassland, Soil and Water Research Laboratory in Temple, Texas, USA. USDA Agricultural Research Service at the Grassland, Soil and Water Research Laboratory in Temple, Texas, USA. SWAT is a river basin scale model developed to quantify the impact of land management practices in large, complex watersheds. SWAT is a river basin scale model developed to quantify the impact of land management practices in large, complex watersheds. Other inputs: Weather, surface runoff, return flow, percolation, ET, transmission losses, pond and reservoir storage, crop growth and irrigation, groundwater flow, reach routing, nutrient and pesticide loading, water transfer. Other inputs: Weather, surface runoff, return flow, percolation, ET, transmission losses, pond and reservoir storage, crop growth and irrigation, groundwater flow, reach routing, nutrient and pesticide loading, water transfer.

24 SWAT Soil name Soil name Hydrologic group Hydrologic group Maximum rooting depth (hzdept and hzdepb) Maximum rooting depth (hzdept and hzdepb) Anion exclusion (pH) Anion exclusion (pH) Soil crack (LEP) Soil crack (LEP) Texture Texture Bulk density (moist) Bulk density (moist) Available water capacity Available water capacity Ksat Ksat Organic carbon Organic carbon Clay content Clay content Silt content Silt content Sand content Sand content Rock fragments Rock fragments Albedo (moist) Albedo (moist) USLE_Kfactor USLE_Kfactor EC EC

25 SWRRB Simulator for Water Resources in Rural Basins-Water Quality Developed by Agricultural Research Service (ARS) predict the effect of management decisions on water, sediment, and pesticide yield with reasonable accuracy for ungaged rural basins

26 SWRRB albedo_dry rock_frag_greater_than_10_in rock_frag_3_to_10_in bulk_density_one_third_bar organic_matter_percent_? sieve_number_4

27 VEGSPEC Vegetative Practice Design Application Developed by NRCS ITC VegSpec utilizes soil, plant, and climate data to select plant species that are (1) site-specifically adapted, (2) suitable for the selected practice, and (3) appropriate for the purposes and objectives for which the planting is intended.

28 VEGSPEC area_symbol area_type_name cointerp comonth component_name component_percent flooding_duration_class flooding_frequency_class horizon_designation mapunit.mapunit_symbol ponding_depth ponding_depth ponding_duration_class ponding_duration_class ponding_frequency_class ponding_frequency_class restriction_depth_to_top restriction_depth_to_top restriction_kind restriction_kind sequence_number sequence_number slope_gradient slope_gradient soil_moist_depth_to_top soil_moist_depth_to_top taxonomic_order taxonomic_order texture_class texture_class

29 WEPS Wind Erosion Prediction System Developed by Agricultural Research Service (ARS) a continuous, daily, time-step model, it simulates not only the basic wind erosion processes, but also the processes that modify a soil's susceptibility to wind erosion

30 WEPS albedo_dry areaname areasymbol bulk_density_one_third_bar bulk_density_oven_dry calcium_carbonate_equivalent cation_exch_capcty_nh4oacph7 chfrags.fragment_volume chtexturegrp.texture_class clay_total_separate component_name component_percent component surface fragments depth to restriction ecec horizon_thickness linear_extensibility_percent local phase local phase mapunit.mapunit_symbol mapunit.mapunit_symbol organic_matter_percent organic_matter_percent ph_01m_cacl2 ph_01m_cacl2 ph_1_1_water ph_1_1_water sand_coarse_separate sand_coarse_separate sand_fine_separate sand_fine_separate sand_medium_separate sand_medium_separate sand_total_separate sand_total_separate sand_very_fine_separate sand_very_fine_separate sat_hydraulic_conductivity sat_hydraulic_conductivity slope_gradient slope_gradient T_factor T_factor taxonomic_order taxonomic_order water_fifteen_bar water_fifteen_bar water_one_tenth_bar water_one_tenth_bar water_one_third_bar water_one_third_bar

31 WINPST Windows based Soil-Pesticide Interaction Screening Tool Developed by NRCS NWCC a pesticide environmental risk screening tool that considers the impact of water table depth, irrigation, residue management and pesticide application area, method and rate class

32 WINPST area_name area_symbol comonth.month compname comppct_r cosoilmoist.soimoiststat hydgrp hzdepb_r kwfact lep_r mapunit.musym om_h om_l om_r ph01mcacl2_h ph01mcacl2_h ph01mcacl2_l ph01mcacl2_l ph1to1h2o_h ph1to1h2o_h ph1to1h2o_l ph1to1h2o_l resdept_h resdept_h resdept_l resdept_l seqnum seqnum slope_h slope_h slope_l slope_l soimoistdept_h soimoistdept_h soimoistdept_l soimoistdept_l texture texture

33 Soil Properties for Models albedo dry area name area symbol area type name base saturation bulk density fifteen bar bulk density one third bar bulk density oven dry caco3clay ratio calcium carbonate equivalent cec nh4oac ph7 clay total separate r coarse fragment volume comonth.month component interp component interp restriction component kind component name component percent r cosoilmoist.soimoiststat cosoimoistdept l drainage class ecec fine sand separate flooding duration class flooding frequency class geomorph feat name geomorph feat type name horizon depth to bottom r horizon depth to top r horizon designation horizon thickness hydrologic soil group kf factor kw factor layer depth linear extensibility percent map unit symbol mapunit acres mapunit name organic matter percent l, rv, h particle density ph 01m cacl2 ph 1to1 h2o pore quantity, shape, size restriction depth to top h restriction depth to top l rock frag 3 to 10 in rock frag greater than 10 sand coarse separate sand total separate sat hydraulic conductivity sieve number 4 silt total separate slope l, h soil texture and modifier sum of bases t factor water fifteen bar r water one tenth bar water one third bar water satiated

34 Focus Concentrate on collecting property data Concentrate on collecting property data Compare field collected data to database properties Compare field collected data to database properties Emphasize the collection of the following estimated properties on field descriptions Emphasize the collection of the following estimated properties on field descriptions Sand (and fractions) Sand (and fractions) Silt Silt Clay Clay Coarse fragments Coarse fragments Organic Matter Organic Matter Bulk Density Bulk Density Water States Water States

35 Focus The “mapping” of soils for the US is essentially complete. NRCS is now in need of “soil scientists” and no longer in need of “soil mappers”. The paradigm must shift from drawing lines on a map to analyzing and improving the quality of our data to meet the needs of our customers. The product focus on the initial soil survey was a bound publication. The product focus on the maintenance soil survey is electronic management of our “data” and electronic delivery of our “information”.


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