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Re-conceptualizing the Soil Moisture Accounting of CN-based Runoff Estimation Method in SWAT

Re-conceptualizing the Soil Moisture Accounting of CN-based Runoff Estimation Method in SWAT. Venkatesh Merwade Adnan Rajib Cibin Raj Purdue University, USA. Presentation Outline. Re-conceptualizing the Soil Moisture Accounting of CN-based Runoff Estimation Method in SWAT.

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Re-conceptualizing the Soil Moisture Accounting of CN-based Runoff Estimation Method in SWAT

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  1. Re-conceptualizing the Soil Moisture Accounting ofCN-based Runoff Estimation Method in SWAT VenkateshMerwade AdnanRajib Cibin Raj Purdue University, USA

  2. Presentation Outline Re-conceptualizing the Soil Moisture Accounting of CN-based Runoff Estimation Method in SWAT Detailing the existing CN method in SWAT and its structural inconsistencies (2) Concept of a modified soil moisture accounting-based CN method (3) SWAT’s sub-routine call-structure for runoff estimation (4) Study Area descriptions (5) Results on different hydrologic components: possible changes by the new method (6) Future Scope of Work Study Objective An SMA-based CN approach is incorporated within SWAT's existing model-structure, with a view to identify potential changes in hydrologic components compared to SWAT's conventional CN method

  3. CN-based Runoff Estimation Method in SWAT SWAT’s Soil Moisture-based Approach CNII (t+1) = 25400/ [S(t+1) +254] CNI (t) Wilting Point CNII (t) CNIII (t) FC condition FC, SAT Role of Soil Moisture Level (SW): How Utilized? Expression of Time: Why Needed? Smax, w1, w2 SW(t) S(t) = Smax [1- SW(t)/ {SW(t) + exp (w1 –w2. SW(t)} ] Ia = 0.2 S(t) Pe (t) = P(t) – Ia(t) Q (t) = Pe2(t) / [Pe(t) + S(t)] SW(t+1) = SW(t) + [P(t) – Q(t) – ET(t) –Qqw(t)] If P(t) > Ia Water Balance

  4. Modification Perspectives SWAT’s Soil Moisture-based CN Method • Expression of Time: Why Needed? • Originally, CN method is an event-based model, valid for cumulative P • An actual storm event can • continuously span over several time-steps, or • end-up ahead of the time-step • based on the chosen time-threshold of a continuous simulation • For continuous simulation, CN method should be valid at any instant along a storm • Role of Soil Moisture Level (SW) • SW is used only in • Calculating Retention Parameter, S • Updating daily CN • Contribution of SW is lumped in Ia • SW(t) S(t) Ia(t) SURQ(t) • Runoff is calculated based on a single lumped condition P > Ia • No volumetric contribution of SW inside runoff equation

  5. CN-based Runoff Estimation Method in SWAT Introducing an Advanced Soil Moisture Accounting Features of the New Model: Expression of time, dP/dt and dQ/dt New SW-based threshold for runoff to occur (V > V0 + Ia) Application SW(t) in directly in Q(t) equation Original CN Method With respect to time New Soil Moisture Threshold (Sa)

  6. SWAT Modification Sub-routine Call Structure for Runoff Estimation Call canopyint (Partial) Call snom Call surq_SMA_daycn Call crackvol Call surq_daycn Call dailycn Call simulate Call surq_greenampt Call volq Call surface Call etpot Call command Call Subbasin Call etact Call crpmd Call SWU • sub-routine dailycn • Updates retention parameter and curve number at individual time-steps • Kept unaltered • sub-routine surq_daycn • Contains runoff equations • Extracted in Visual Fortran compiler and re-coded. Compiled with rest of the codes This can be kept as a separate new sub-routine ( e.g. surq_SMA_daycn)

  7. Study Area Cedar Creek 270 sq. miles Indiana, USA USGS gauge NCDC Weather Station White River 1635 sq. miles

  8. RESULTS Surface Runoff (SURQ) • SMA-based SURQ values are underestimated • The difference shown by the SMA based method is more prominent in case of urban areas HRU with LU- Forest Cedar Creek HRU with LU- Medium Developed SURQ (mm) White River Rainfall on the HRU (mm) Days in a Year (2011) • The overall lowering of SURQ by the modified method is a desired outcome with respect to Williams et al. (2012), Neitsch et al. (2011) and Kannan et al. (2008), who noted the over-estimating tendency of SWAT’s conventional CN based runoff estimation method

  9. Streamflow at the USGS Outlet RESULTS Underestimation of high flows by the SMA method White River at Indianapolis Streamflow at USGS Outlet (cms) Days in a Year (2011) For low flows, difference is negligible

  10. RESULTS Soil Moisture: Individual LU Contexts HRU with LU- Medium Developed White River HRU-level SW (mm) Rainfall (mm) Rainfall (mm) HRU-level SW (mm) HRU with LU- Aggri Cedar Creek Days (2011) Days (2011) • Lower SW in summer • Similar SW in Spring (all LU types) • Difference is negligible for Forested HRUs Rainfall (mm) HRU-level SW (mm) HRU with LU- Forest White River Lower SURQ, Lower SW in the SMA method Net Water Balance? Days (2011)

  11. RESULTS: Daily Water Balance in Individual HRUs SW (end of day) = SW (start of day) + PRECIP + Snow Melt – ET – Surface Run - Percolation Calculated Water Balance is showing R2 ≈1 between the conventional and new method for all LU HRUs NEW SMA-based CN METHOD Runoff (lower) Soil Water (lower) Water Balance PET ? Soil Evaporation ? Plant Water Uptake ?

  12. RESULTS: Higher Evapotranspiration SWAT’s ET Estimation Structure PET Full depletion of canstor PETremain = PET - canev partitioning if PET > canstor soil plant es_max ep_max Maximum possible soil evaporation for the day Maximum possible Plant uptake for the day Actual Soil Evp in a day Actual Plant Uptake in a day Actual ET

  13. RESULTS: Higher Evapotranspiration SMA-based CN Method • The change in the partitioned amounts of Actual Soil and Plant ET need to be evaluated • PET remains the same for both methods • Higher ET amounts by the modified method particularly in summer days; matches otherwise

  14. Summary Re-conceptualizing the Soil Moisture Accounting of CN-based Runoff Estimation Method in SWAT • A modified CN method is incorporated into existing SWAT source code which is more realistic from SMA perspective • Individual HRU results reveal lowering of surface runoff with lesser soil moisture by the SMA technique compared to the conventional model • The reduction in soil moisture along with other related ground water components in the modified model has found to have been attributed with a higher ET. • Importantly, the calculated HRU-level daily net water balance has turned out to be almost same in both cases.

  15. Future Work Re-conceptualizing the Soil Moisture Accounting of CN-based Runoff Estimation Method in SWAT Tracking of additional variables like the canopy storage, potential maximum moisture retention, actual soil evaporation and plant uptake are likely to be decisive at this stage Vigorous experimentations are necessary under diverse scenarios of landuse, irrigation and tile drainage, cropping pattern, water quality, and climatic change This will establish a sounder runoff method for continuous simulation in SWAT Thank You! • Contact: • VenkateshMerwade • vmerwade@purdue.edu • http://web.ics.purdue.edu/~vmerwade

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