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Water Management In Ayubia National Park. Study Participants Hassan Bukhari, Kanwal Rizvi Joveria Baig, Wafa Veljee Syed Ali Raza LUMS School of Science and Engineering International Conference on Water Resources, Engineering and Management 2011, UET. Motivation.
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Water Management In Ayubia National Park Study Participants Hassan Bukhari, Kanwal Rizvi Joveria Baig, Wafa Veljee Syed Ali Raza LUMS School of Science and Engineering International Conference on Water Resources, Engineering and Management 2011, UET
Motivation • Studying the effects of deforestation on hydrology of ANP is critical due to the changing environment • WWF in collaboration with Coca cola is working on these problems and wanted a mathematical model • Wanted to explore avenues of undergraduate research
How did we do this • Literature review of papers from all around the world on this topic. • There are widely used well defined methods which were beyond our scope, budget and time. • Support from WWF • Support from SSE instructors from the Math, Physics and Biology Departments who guided us and provided resources
Final model • Collected and documented maximum observables on the field using most efficient techniques. • 3 days, 18 sites from forested and deforested areas • Linear Regression of collected data in MATLAB Infiltration = A1 Vegetation + A2 Slope + A3 Elevation + A4…
Data Collection Methods Cheap and Effective
Infiltration • Self Fabricated steel double ring infiltrometer, with 3 and 4 inches diameter pipes.
Water Content Saturated water content = Vol water/Vol soil Gravimetric water content = Mass water/ bulk mass
Other Variables • Vegetation • Trees in 100m2(Blue Pine, Fir) • Deciduous bushes • Grasses and Shrubs • Canopy • Slope • Elevation • Latitude Longitude • Air and Soil Temperature
Results and Analysis Linear Regression at its best
Results: Infiltration Model • Predicted and actual infiltration • Error: 22.28
Outliers • Site 1 in the forested area was our first site. • Site 3 in the deforested area was infected with ants • Site 8 in the deforested area was a small clump of trees (control)
Outliers Removed • Error:6.42
Results: Porosity Model • Predicted and actual effective porosity • Error: 0.0451
Same sites removed • Error: 0.0264
Analysis for Infiltration Model • Error= 6.42
Can it predict? • We randomly eliminated sites from our model and predicted the value of infiltration for the site. Even with only 17 sites the agreement was good.
What we concluded for WWF/ Coke • Coke was interested in ground water recharge • Above ground: • Precipitation = Surface Runoff + Evaporation + Increment in Surface Water Retention + Infiltration • Below Ground: • Infiltration = Underground Runoff + Ground evaporation + Ground Water Recharge
Assumption • Big assumption 1: All infiltration occurs at saturation. • Assumption 2: Precipitation patterns are unchanged by limited plantation • Assumption 3: ∆Underground Runoff = 0 or less than zero
Total Infiltration = Rate x Time • Infiltration Forested = Rate in forest x Time Infiltration Deforested Rate in Deforested x Time Infiltration Forested = Rate F/ Rate D Infiltration Deforested Infiltration Forested = 2.76 Infiltration Deforested ∆Infiltration = 1.76 Total Infiltration Deforested Area ∆Water Recharge = 1.76 TID – 167mm
Conclusion Foresting an area will increase the total infiltration by up to 75%! Surprisingly good fit for linear regression model for infiltration and porosity
Learning Outcomes • Shrubs, bushes and dense canopy are more essential than a large number of trees for a healthy hydrological system. • We have developed and tested an economically feasible and technically appropriate methods to quantitatively model complex hydrological relationships • Good opportunity for undergraduate research