Watershed Modeling and Landuse Change: A new approach Chris Duffy Lele Shu Penn State University
Issues
Goals of the Study-> Watershed Context for LUC Develop a high resolution integrated hydrologic and coupled landuse change model of the Conestoga watershed including a distributed approach to landuse classes (1979-2010) Determine historical, present and future scenarios of landuse change in the watershed as a function of population growth Contrast historical versus future climate (IPCC projections) on Landuse Change and Green Infrastructure Soil function: For agricultural, urban and suburban landuse classes simulate the local green performance or changes in the water balance due to healthy and/or degraded soils. A distributed water balance tool accessible by stakeholders to access the simulated water balance data for any site in the Conestoga watershed. Assess spatial architecture of LU Types & GI Design
A Hydrologicc Modeling Strategy for Water Resources in the Conestoga Watershed based on Dynamic LUC CALUC ( Cellular Automata for Land Use Change) Tools GIS - Geographic Information System Accessibility - distance to road, river, etc. Suitability - attractive/repulsive tend to topographic features Zoning - water, wetland, reserve land Inertia - priority of transition of each landuse Random - to avoid too deterministic C. Duffy, L. Shu
Essential Terrestrial Variables: Water Cycle Research for Watersheds & River Basins Atmospheric Forcing (precipitation, snow cover, wind, relative humidity, temperature, net radiation, albedo, photosynthestic atmospheric radiation) Digital elevation models (30, 10, 3, 1m resolution) River/Stream discharge, stage, cross-section Soil (texture, C/N, organic, hydrologic & thermal properties) Groundwater (levels, extent, hydrogeologic properties, 3D Architecture) Land Cover (biomass/leaf area index, phenology,. ) Land Use (human infrastructure, demography, ecosystem disturbance, property & political boundaries) Environmental Tracers- stable isotopes Water Use and Water Transfers Lake/Reservoir/Diversion (levels, extent, discharge, operating rules) to be cont d..?? Most data reside on federal servers.many terabytes
www.hydroterre.psu.edu Need workflow here
PASDA: and Hydrologic Conceptual Model, PA DEP Conceptual Hydrologic Model: Susquehanna River
DEP Conceptual Model Groundwater flow in the Allegheny Plateau Section. GIS Data_Model Example of the SWAP GIS for the surface geology coverage.
Conestoga watershed Area ~1300km 2; Population ~520,000 13 HUC subwatersheds Elevation range: 45m~380m above sea level Deforestation + Urbanization
Spatial Data from HydroTerre
Current Landuse Photos credit to Mike Marra, Nevin WeaverJim_Harrison
A Multi-Scale Modeling Strategy for Water Resources in the Chesapeake Bay Watershed PIHM: The Penn State Integrated Hydrologic Model Objectives To develop s physically-based, multi-scale model for water, solute and energy budgets in complex large-scale hydrologic systems To provide reliable water, solute, sediment, and energy budgets To estimate recharge, bank storage, ephemeral stream losses, climate and landuse effects across river basins To provide a scientific basis for the next generation of predictive tools for water resource managers Tools GIS - Geographic Information System TIN - Domain Decomposition: Triangular Irregular Net FVM - Finite Volume Method PDE - Partial Differential Equations ODE - Ordinary Differential Equations PDAE - Differential-Algebraic Equations C. Duffy, Y.Qu, M. Kumar, G. Bhatt, Y. Tang, S. Li,
Subsurface Profile z θ 13
Parameters related to LUC 1) Overland flow 2) Parameters of land use NLCD code TYPE VegFrac RzD LAIMAX ROUGH SoilDgrd ImpArea 11 Open Water 0.08 0.6 0.85 0.0375 0 0 21 Developed, Open Space 22 Developed, Low Intensity 23 Developed, Medium Intensity 24 Developed, High intensity 0.66 0.37 4.81 0.037 0.3 0.1 0.51 0.28 4.87 0.0295 0.5 0.3 0.32 0.17 4.94 0.0205 0.8 0.6 0.16 0.09 5 0.013 0.95 0.9 31 Barren land 0.09 0.08 0.09 0.0358 0.2 0 41 Deciduous Forest 0.77 0.52 6.22 0.058 0 0 42 Evergreen Forest 0.83 0.52 4.98 0.058 0 0 43 Mixed Forest 0.77 0.52 7.21 0.052 0 0 81 Pasture/Hay 0.5 0.24 2.87 0.024 0.5 0 82 Cultivated Crops 0.5 0.24 2.87 0.024 0.5 0 90 Woody Wetland 0.4 0.26 1.53 0.041 0 0 NLCD (2001, 2006, 2011)
Parameters related to LUC 3) Leaf Area Index 4) Macropore effect https://ldas.gsfc.nasa.gov/nldas/web/web.veg.monthly.table.html
Macropore effects (Horizontal)
Infiltration in Macro-porous Soils Macropore Flow Initiation Water supply to the macropores Macropores make a healthy soil and are critical to soil and landuse hydrologic performance Interaction Water transfer between macropores and the surrounding soil matrix 17
Cellular Automata Land Use Change The LUC model gives the likelihood that current landuse will change based on the demand for a particular land type and several factors (white et. al 1997, 2000)
Factors of Transition Potential (0 < α < 1) (urban center, road network) Accessibility (Slope, natural hazards, soil fertility) (Reserved area) (Forest -> Agriculture->Urban tendency) (Rules about existing LU) (white et. al 1997, 2000)
Population growth and demand for land use change 1750 2015
Comparing Observed and Simulated LUC 1800-2011 White et. al (1997, 2001)
LUC Projections 2001 to 2101
Land Use Scenarios-Constant Climate 3 land use scenarios Past: early-settlement(before 1700) Present: recent scenario (1900-2011) Future: future development(2006-2100) Analysis: 1. Discharge 2. Water storage 3. Water balance CALUC LUC 2006-2100 Popullation & Climate Data 1979-2010 NLDAS-2 PIHMgis PIHM Three Scenarios Past, Present and future Analysis results Water yield, balance, flood/drought, storage
Change in runoff/precip. ratio
Change in ET/P ratio
High, mean and low flows
Rating curve, observed and predicted Flood stage: Grofftown Road will flood Major Flood: many homes near the river area affected by high water Rating Curve of the Conestoga river Floods Past Present Future Flood stage (3.35m) 3 4 5 Major Flood (4.57m) 1 2 2 Green dots: USGS gage and discharge data 2007-2016 https://nwis.waterdata.usgs.gov/nwis/dv?site_no=01576500
Change of Ground Water Future Present Dryer Wetter Wetter Wetter Dryer Dryer GWT increased in urbanized area GWT decreased in agricultural land
Watershed Water Balance and LU Water balance in watershed scale Increased runoff yield Decreased interception, transpiration Water balance respect to four categories Less ET along deforestation and urbanization
Dynamic Land Use and Future Climate Change Climate RCP4.5 RCP8.5 CALUC LU 2010 LUC 2006-2100 PIHMgi s PIHM RCP4.5 HadGEM2-AO RCP8.5 Scenario matrix ST45, ST85, DN45, DN85 Dynamic LU Change DN45 DN85 Analysis results Water yield, balance, flood/drought, storage
Ground Water Change & Climate Dryer Wetter Yearly mean ground water table Spatial change 2010s to 2090s
Tools for local water studies Choose location Any variables(state/flux variables, Flow duration cure, ) Any periods (year, monty ) Any resolution(hourly, daily, monthly, )
Detailed Site Specific Data Analytics
History of Tropical Storm Rainfall-Runoff in a Small Upland Watershed
Conclusions: Conestoga watershed Deforestation has had a dramatic impact on floods and droughts Urbanization increases runoff yield and decreases ET. Agriculture development increases runoff and decreases ET. Spatial patterns of land use change were associated with increasing ground water levels under urban land use. The land use change increases runoff variability. The relative effect of climate change on runoff variability is somewhat larger than land use change. Dynamic climate and land use change together tend to accelerate the hydrologic cycle at watershed scale.