Setting the Course for Improved Water Quality Collecting Land Use Data for TMDLs

Transcription

1 Setting the Course for Improved Water Quality Collecting Land Use Data for TMDLs A TMDL training program for local government leaders and other water managers Session 6b wq-iw3-56b

2 In this presentation Understanding the whole watershed system why watershed assessment data is as important as water quality data Gathering needed assessment data Planning and documenting your assessment approach Submitting data to MPCA staff

3 Your project to date Scoped the project Began data inventory (existing water quality, land use, geomorphology, hydrogeology, biology, etc.) Identified data gaps for all types of data Next: Fill data gaps The focus of this presentation: Collecting watershed assessment data

4 Why is watershed data as important as water quality data? To effectively manage water quality, we must understand the whole system that affects an impaired waterbody

5 In the past Our inclination has been to focus on water quality data alone The need to examine other sets of data was often an afterthought (considered less important)

6 What can watershed data contribute to a TMDL Study? Watershed data: allows us to describe that multi-dimensional, complex watershed (topography, soils, vegetation, climate, geology, etc.) helps us explain the impact of land use activities on water quality (nonpoint pollution contributions) provides data needed to model future conditions

7 What can watershed data contribute to a TMDL Study? Watershed data: helps to identify pollutant sources specific to certain land uses assists in the quantification of pollutant loads from those land uses are required when identifying priority areas for implementation of Best Management Practices (BMPs)

8 Watershed assessment: data needs A watershed assessment typically requires 4 major data sets: 1.Land use (land cover, kinds of facilities) 2.Geomorphology (geology, channel size and shape) 3.Hydrogeology (soils, water table characteristics, groundwater quality) 4.Surface water (hydrography, overland flow, water quality monitoring)

9 Planning Your Watershed Data Collection Activities

10 Creating a data collection plan Gaps in your watershed data? Develop a plan to fill the gaps Your Monitoring Plan should include a section devoted to gathering watershed data

11 Creating a data collection plan Fill out Worksheets 7-1 to 7-3 to help you plan and document your watershed assessment activities Keep record of your decisions in your project file

12 Monitoring plan Include: Data collection goals and objectives General data collection approach Timeline Roles and responsibilities for data collectors Data storage and management plan

13 Watershed data collection goals Examples of goals: 1. Determine: source contributions conditions under which pollutants are delivered pathways for surface and groundwater flow 2. Develop and/or calibrate hydrologic or water quality models

14 Who gathers and stores the data and when? Your monitoring plan should identify who will gather and manage data sets Typically, local government staff will gather existing data In some cases, local officials or consultants will need to collect new data (be specific about data needs) Develop timeline, identify roles

15 Data collection objectives example Goal: Determine source contributions Data collection objective 1 Collect comprehensive agricultural land use data for watershed to include: 1. Crop type 7. Culverts 2. Tillage 8. Topography 3. Percent crop residue 9. Location of roads 4. Soil types 10. Watershed divides 5. Fertilizer data 11. Other infrastructure 6. Tile lines 12. Feedlots

16 Gathering New Watershed Data

17 Scope/extent of watershed assessments will vary Watershed data is an integral part of most TMDL projects The level of detail needed for a watershed assessment may vary

18 Scope/extent of watershed assessments will vary Example: Minnesota River Critical conditions occur during low flow, therefore event driven runoff events were not significant factor in low DO impairment Land use assessment data deemed less important

19 When should you collect new watershed data? 1.Initially assess existing water quality data 2.Define the problem 3.Collect data A well-defined problem allows you to appropriately scope watershed assessment (Example: assess point sources only if needed)

20 TMDL study process Scope the project Conduct data inventory Identify water quality data gaps Identify watershed data gaps Determine whether new data is needed Develop data collection plans Collect new water quality data Collect bio monitoring data Analyze WQ data Define water quality problem Collect new watershed data It is likely to be iterative! Modeling Develop allocation formula

21 Remember Value watershed data as much as water quality data Prepare: It can be time consuming!

22 What kinds of watershed data are typically gathered? Photos: Courtesy of USDA NRCS 1a. Land use agricultural areas Crop type Tillage % crop residue Soil types Tile lines (location, diameter, flow direction, material) Fertilizer data: 1. Type (manure, commercial granular, anhydrous) 2. Application rate (weight/time) 3. Composition (nitrogen, phosphorus, potassium) 4. Application method (chisel plowed, injected, surface applied)

23 Gathering land use data 1a. Land use agricultural areas Culverts (location, diameter, depth, flow direction, material) Topography Location of roads Watershed divides Other infrastructure (buildings, wells, etc.) Feedlots (use manual for Feedlot Evaluation Model) Photos: Courtesy of USDA NRCS

24 Gathering land use data 1b. Land use urban areas Impervious area (road surfaces and roofs) Pervious area (lawns, gravel, mixed vegetation) Forested areas Construction sites Photos: Courtesy of USDA NRCS

25 Gathering Land Use Data 1b. Land use urban areas Gravel pits Location of storm sewers (alignment, diameter, flow direction, material, shape) Road sanding practices (also grain analysis, if available) (e.g., tons/month from November through April) Street sweeping practices (date occurs, volume collected, grain analysis, soil classification)

26 Ground-truthing Usually, the accuracy of land use data must be verified requiring 1. Windshield surveys for crop types, tillage, and types of pervious surfaces 2. Field-checking the crop residue, culvert locations and flow directions, and impervious area

27 Gathering geomorphology data 2. Geomorphology Changes in impervious surfaces within the last century (use GIS/aerial photos) Changes in vegetative management over the last century Channel changes (systemic or local?) Specific measurements to use in Rosgen analysis

28 Gathering geomorphology data 2. Geomorphology Cross sectional data for main channel and floodplain stream slope, length Valley length Grain size, classification of bed/bank soils Location, size, and rate (volume/time) of streambank slumps Location of sand and gravel bars Photo: Jason Ewert

29 Gathering geomorphology data 2. Geomorphology Erosion resistance and shear strength of bed and bank materials Stream, streambank, and floodplain vegetation Location and details of hydraulic structures (dams, drain tiles, culverts, bridge crossings, etc.) Local geologic stratigraphy Photo: Courtesy of USDA NRCS

30 Gathering hydrogeology data 3. Hydrogeology Project location within the state (geologic perspective) Geologic influences on the waterbody (impacts the kinds of data needed) Impacts of land uses, when superimposed on area geology

31 Gathering hydrogeology data 3. Hydrogeology Delineation of the areal extent of each aquifer discharging to receiving water Delineation of groundwater recharge areas Land use and surficial soil types within recharge areas Regional geological stratigraphy (obtained from soil borings, well logs, geologic atlas) Photo: Courtesy of USDA NRCS

32 Gathering hydrogeology data 3. Hydrogeology Groundwater chemistry Environmental isotope monitoring to determine groundwater age and source areas

33 Gathering surface water data 4. Surface water Hydrologic pathways and processes of source water Impact of wetlands and lakes on impaired water (where applicable) More information in module 8

34 Where do you obtain data sets? Agricultural data 1. Soil and Water Conservation Districts 2. Commercial fertilizer applicators 3. Landowners 4. Farm Services Administration (FSA) (FSA data especially important if you have phosphorus or dissolved oxygen impairments!) Urban data 1. Metropolitan Council 2. Cities 3. Land Management Information Center (LMIC)

35 Where do you obtain data sets? Geomorphology 1. US Geological Survey 2. MPCA 3. MnDNR Hydrogeology 1. US Geological Survey 2. MPCA 3. MnDNR 4. USDA - NRCS

36 Where do you obtain data sets? Surface Water 1. MPCA 2. Mn DNR 3. Local Planning Departments 4. SWCDs 5. US Geologic Survey 6. Mn Dept. of Agriculture 7. Met Council (metro area) 8. US EPA 9. US Fish and Wildlife Service 10. Extension Service Groundwater 1. Mn Department of Health 2. MPCA

37 How do you format data submitted to MPCA? Excel spreadsheets GIS Access databases for feedlots

38 What software does MPCA use to analyze data? ARC-GIS (most common) EPA software package (BASINS)

39 How do we use the data? Evaluate possible pollutant sources (using watershed model, GIS or both) Generate GIS maps that can assist in prioritization of management activities Locate and design BMPs Inform stakeholders

40 Remember, in most cases Detailed Accurate, Complete, DATA Strong analysis Precise implementation plan

41 Limitations of watershed assessments Difficult to isolate individual source inputs Results depend upon data input quality Need correct data for assessment approach Photo: Jason Ewert

42 Document your assessment process Develop a report. Include: Detailed locational information of identified features (latitude, longitude, legal description) Time of data collection (month, year) Data sources and who collected it

43 Summary Watershed data is as important as water quality data Watershed data allow us to understand the whole system we need to manage If there are gaps in your watershed data, develop a (monitoring) plan to help you get what you need

44 Summary Detailed information on land use, geomorphology, hydrogeology, and surface water is usually needed The more detailed your watershed data, the stronger the analysis Data quality is critical Document your assessment process and keep a file of relevant material

45 Remember: Discipline is required! But, make sure to put the pieces back together to understand the whole system Even experts are tempted to look at data sets in isolation

46 Need help? Call MPCA modelers: Hafiz Munir Nick Gervino John Erdmann

47 In an age when man has forgotten his origins and is blind even to his most essential needs for survival, water along with other resources, has become the victim of his indifference. Rachel Carson