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GEOG5060 GIS and Environment

School of Geography FACULTY OF ENVIRONMENT. GEOG5060 GIS and Environment. Dr Steve Carver Email: S.J.Carver@leeds.ac.uk. Lecture 9. Hydrological modelling 2: runoff models. Outline: Incorporating time Distributed models Other examples. Introduction.

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GEOG5060 GIS and Environment

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  1. School of Geography FACULTY OF ENVIRONMENT GEOG5060 GIS and Environment Dr Steve Carver Email: S.J.Carver@leeds.ac.uk

  2. Lecture 9.Hydrological modelling 2: runoff models Outline: Incorporating time Distributed models Other examples

  3. Introduction • Runoff modelling is time dependent • antecedent conditions • precipitation • ground cover • slope length (time to reach channel) • channel length (time to reach gauging station) • Predict catchment response

  4. Incorporating time • Difficult • GIS data model not suited to handling time • Time-series analysis • model response per unit time • run sequence of results • Model integration • link external runoff model with GIS

  5. Distributed models • Lumped models: • no spatial component • example: RUNMOD • Distributed models: • spatially variable • inputs • control variables • outputs • example: TOPMOD

  6. Mass balance models • Mass balance models • based on estimating relative volumes of inputs and outputs • size of stores? • Runoff mass balance: RO = (P – Int – ET – SS) + run-on

  7. Implementing a mass balance model • Simplified mass balance model: RO = (P – Int – ET – SS) + run-on RO = P + run-on (assuming Int, ET and SS are negligible) • P is simulated or known • rain guage or radar data • Run-on • calculated from weighted flow accumulation

  8. Example • Simple mass balance model: • Create hydrologically correct DEM • Calculate flow direction • Calculated flow accumulation for time Tn using rainfall Tn as weight grid • Determine water volume at pour point for time Tn • Repeat steps 3-4 n times

  9. Example: Burnhope Burn

  10. Example: RF and response RF t=1 Response t=1 RF t=2 Response t=2

  11. Example: simulated storm event t=1 t=2 t=3 t=4 t=5 t=6

  12. t=2 t=3 t=1 t=4 t=5 t=6 Example: response t=1-6

  13. Example: predicted hydrograph

  14. Question… • What problems might there be with such a model?

  15. Time/area response • Based on: • upstream contributing area (volume estimate) • distance from channel (time to peak) • used to estimate discharge (Q) at any point on drainage network for given rainfall event • use soils, geology and land use data to compensate for effects of: • interception, infiltration and percolation • throughflow events • surface roughness • surface storage (puddles - lakes) • etc.

  16. A time/area response model • Time/area runoff response model: 1. calculate contributing areas and channel lengths 2. derive slopes and channel gradients 3. calculate channel velocities using Manning’s n as follows... V = 1 / n . R2/3 . S1/2 4. calculate time from channel length and velocity... t = L/V 5. interpolate from channel over catchment 6. use with distributed rainfall data to predict flows

  17. DEM Flow direction Flow accumulation Channel length Mean channel slope Distance to nearest channel n = 0.035-0.04, mean channel response time = approx. 3hrs, plus slope runoff times

  18. Question… • What problems exist with the time/area response model?

  19. Conclusions • Not easy to do runoff calculations in GIS • time critical • spatio-temporal variability of controls • calibration/validation issues • Two basic examples: • mass balance model • time/area response model

  20. Workshop • Running dynamic models • weighted flow accumulation • incorporating spatio-temporal variables

  21. Practical • Running a GIS-based hydrological model • Task: Derive a simple hydrograph from a mass balance model • Data: The following datasets are provided… • Section of Upper Tyne Valley DEM (50m resolution) and 10m contours • River network (1:50,000) • Precipitation layers 1 through 6 (simulated)

  22. Practical • Steps: • Calculate hydrologically correct DEM using flowdirection, sinks and fill • Calculate channel response to precipitation using flowaccumulation with the weight_grid option • Note maximum flow value • Repeat steps 2-3 for each time step • Plot maximum flow value vs time

  23. Practical • Experience with building and running models • Familiarity with functions in Arc/Info for building hydrological response models

  24. Next week… • Land suitability modelling • Multi-criteria evaluation (MCE) • Multi-objective land allocation (MOLA) • Examples • Workshop: MCE and MOLA • Practical: MCE in GRID

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