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| Campo DC | Valor | Lengua/Idioma |
|---|---|---|
| dc.contributor.advisor | Chavoya Peña, Arturo | |
| dc.contributor.advisor | Benavides Solorio, Juan De Dios | |
| dc.contributor.advisor | Durán Limón, Héctor Alejandro | |
| dc.contributor.author | Vergara Blanco, Javier Eugenio | |
| dc.date.accessioned | 2021-10-02T20:27:10Z | - |
| dc.date.available | 2021-10-02T20:27:10Z | - |
| dc.date.issued | 2018-07-18 | |
| dc.identifier.uri | https://wdg.biblio.udg.mx | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12104/83348 | - |
| dc.description.tableofcontents | Contents 1 Introduction 2 1.1 Background....................................... 2 1.2 Context......................................... 3 1.3 Objective ........................................ 3 2 Modelling approaches and techniques 5 2.1 Dynamicsystemscharacterisation .......................... 5 2.1.1 Deterministicvsstochastic .......................... 5 2.1.2 Discretevscontinuous............................. 5 2.1.3 Linearvsnon-linear .............................. 6 2.2 Ecologicaldynamicsmodellingtechniques ...................... 6 2.2.1 Systemsanalysis ................................ 6 2.2.2 Steadystatemodelsofecologicalsystems .................. 7 2.2.3 Differentialequations ............................. 7 2.2.4 Lesliematrices ................................. 8 2.2.5 Fuzzylogic ................................... 8 2.2.6 Grammar-basedmodels ............................ 9 2.2.7 Individual-basedmodels............................ 10 2.2.8 Speciesdistributionsmodelling ........................ 10 2.2.9 Classicalartificialneuralnetworks ...................... 11 2.2.10 Markovchain.................................. 12 2.2.11 Cellularautomatamodellingapplications . . . . . . . . . . . . . . . . . . 12 2.3 Foresttreesandstandsmodellingapproaches .................... 13 2.4 Dynamic spatially linked spatio-temporal (SLST) models . . . . . . . . . . . . . 15 2.5 Needforarainfalldynamicssimulationsystem ................... 17 2.6 Cellularautomatamodellingapplications ...................... 18 3 Simulation system 20 3.1 Objectivesandscope.................................. 20 3.2 Assumptions ...................................... 21 3.3 Discreteelementrepresentation............................ 24 3.3.1 Thecells .................................... 26 3.3.2 Updaterules .................................. 27 v CONTENTS vi 3.3.3 Infiltrationcalculation............................. 28 3.3.4 Runoffcalculation ............................... 32 3.3.5 Timevariationofsoilinfiltrability ...................... 35 3.3.6 Originofcomponentsdescribedinthissection . . . . . . . . . . . . . . . 36 3.4 Implementation..................................... 36 3.4.1 Simulationsystemdataandclasses...................... 36 3.4.2 Graphicdisplay................................. 38 3.4.3 Rainfalldataweatherstation ......................... 39 3.5 Datacollection ..................................... 39 3.5.1 Digitalelevationmodel ............................ 39 3.5.2 Rainfalleventdata............................... 40 3.5.3 Soilclassificationandinfiltrabilitydata ................... 41 3.6 Results.......................................... 41 3.6.1 Rainfallinfiltrationatthecelllevel...................... 43 3.6.2 Subwatershedcharacterisation ........................ 44 3.6.3 Subwatershedrainfalldynamics........................ 48 3.7 Discussion........................................ 53 3.7.1 Goodnessofthemodel............................. 53 3.7.2 Infiltration comparison unburned vs high wildfire terrain . . . . . . . . . . 54 3.7.3 Simulation study peak discharge values vs field studies . . . . . . . . . . . 55 4 Optimisation of land controls distribution 58 4.1 Scope .......................................... 58 4.2 GeneticAlgorithmsmetaheuristic........................... 59 4.2.1 Genetic Algorithms adapted for the optimisation system . . . . . . . . . . 59 4.3 Implementation..................................... 62 4.3.1 Landremediationcontrolsrepresentation . . . . . . . . . . . . . . . . . . 62 4.3.2 Datarepresentation .............................. 63 4.4 Optimisationsystemtuning.............................. 65 4.4.1 Selectionoperator ............................... 65 4.4.2 Crossoveroperator............................... 66 4.4.3 Mutationoperator ............................... 66 4.4.4 Populationsize................................. 67 4.5 Optimisationresultsanddiscussion.......................... 68 4.5.1 Rainfallinfiltrationmaximisation....................... 68 4.5.2 Rainfallrunoffminimisation.......................... 76 4.5.3 Spatialdistributionconvergence ....................... 78 4.5.4 Optimisationexecutionduration ....................... 80 4.6 Othermetaheuristics.................................. 81 5 Conclusions 83 List of Tables 2.1 Ecologicalmodellingapproaches. ........................... 14 3.1 Slope characterisation for the six selected cross points at the subwatershed. . . . 48 3.2 Comparison of catchment peak flows of different studies with similar soils, to this study. .......................................... 56 4.1 Comparison of tests with one and two chromosome partitions for crossover. . . . 66 4.2 Number of generations required by nine optimisation tests to reach a specific threshold......................................... 67 4.3 Fitness value obtained by three incremental infiltration maximisation tests with differentpopulationsize................................. 67 4.4 Execution duration for tests with different parameter values. . . . . . . . . . . . 81 vii List of Figures 3.1 Map for Bosque La Primavera and the western end of Guadalajara city in Jalisco, Mexico. ......................................... 22 3.2 Thezonearoundtheareaunderstudy......................... 22 3.3 TheareaunderstudyinBosqueLaPrimavera. ................... 23 3.4 BosqueLaPrimaveraoakandpinecoverinthedryseason. . . . . . . . . . . . . 24 3.5 ABosqueLaPrimaveralandscapeinthedryseason. . . . . . . . . . . . . . . . . 25 3.6 Rovingwindowonthe3Dmeshsurface. ....................... 26 3.7 Infiltration capacity time series and Horton equation exponential decay curves. . 30 3.8 Horton equation infiltration capacity decay curves and the rainfall profile repro- ducedforthesimulationstudy. ............................ 31 3.9 Cell–specific surface water at storm peak is shown for burned terrain. A DEM of asectionofLaPrimaveraForestisused........................ 42 3.10 Cell–specific cumulative infiltration at storm–end is shown for burned terrain. A DEMofLaPrimaveraForestisused.......................... 44 3.11 Infiltration rate determined by the simulation study for two surface cells. . . . . 45 3.12 The subwatershed whose rainfall dynamics are presented in this study. . . . . . . 46 3.13 The six different cross points selected to calculate the slope across the subwatershed. 47 3.14 Cell-specific cumulative infiltration is shown at storm end for unburned terrain andhighseveritywildfireaffectedterrain. ...................... 49 3.15 Thesimulationstudycumulativeprecipitation,cumulativeinfiltrationandminute– by–minuteoverlandflow................................. 49 3.16 Cumulative infiltration and overland flow are compared for unburned and high wildfireaffectedterrain. ................................ 49 3.17 Catchment outlet discharge volume is shown for ”El Coyote” subwatershed. . . . 50 3.18 The subwatershed cumulative outlet discharge for unburned and burned terrain. 51 3.19 Rainfall volume, infiltration volume, catchment outlet discharge, and catchment overlandflow,areshownforunburnedterrain. ................... 52 3.20 Rainfall volume, infiltration volume, catchment outlet discharge, and catchment overlandflow,areshownforburnedterrain ..................... 53 3.21 A distribution that includes I30 and the corresponding peak discharge volume for thisstudyandforfieldobservations. ......................... 56 viii LIST OF FIGURES ix 4.1 An illustration of a ditch aligned with the Y axis and a ditch in a diagonal position, intheDEMhorizontalplane. ............................. 63 4.2 A spatial distribution for 20 ditches obtained with crossover of 90 percent and mutationof15percent. ................................ 69 4.3 A spatial distribution for 20 ditches for a 10-chromosome population with cross breedingof90andmutationof30percent. ..................... 69 4.4 Land controls distributions obtained with crossover of 95 percent and mutation of15,10,and5percent................................. 71 4.5 Land controls distributions obtained with crossover probability of 90 percent and mutationof15,10,and5percent. .......................... 72 4.6 Land controls distributions obtained with crossover of 85 percent and mutation of15,10,and5percent................................. 73 4.7 Optimisation test with crossover of 90 percent and mutation of 50 percent. Ending conditionof100generationsofnofitnessimprovement.. . . . . . . . . . . . . . . 74 4.8 Optimisation results of 50-gen chromosomes tests with ending conditions of 35, 50, and 70 consecutive generations of no fitness improvement. . . . . . . . . . . . 75 4.9 For a 20-gene chromosome, optimisation test results with a population of 1,000 chromosomes....................................... 76 4.10 Infiltration maximisation versus runoff minimisation land controls spatial distri- butions.......................................... 77 4.11 Comparison of optimisation results with chromosome crossover performed with twopartitionsandonepartition. ........................... 78 4.12 Nearly identical land controls spatial distributions are produced on three runs of thesametest....................................... 79 | |
| dc.format | application/PDF | |
| dc.language.iso | eng | |
| dc.publisher | Biblioteca Digital wdg.biblio | |
| dc.publisher | Universidad de Guadalajara | |
| dc.rights.uri | https://www.riudg.udg.mx/info/politicas.jsp | |
| dc.subject | Forest Rainfall | |
| dc.title | Forest rainfall infiltration and runoff: A simulation and optimisation system. | |
| dc.type | Tesis de Doctorado | |
| dc.rights.holder | Universidad de Guadalajara | |
| dc.rights.holder | Vergara Blanco, Javier Eugenio | |
| dc.coverage | ZAPOPAN, JALISCO | |
| dc.type.conacyt | doctoralThesis | |
| dc.degree.name | DOCTORADO EN TECNOLOGIAS DE INFORMACION | |
| dc.degree.department | CUCEA | |
| dc.degree.grantor | Universidad de Guadalajara | |
| dc.degree.creator | DOCTOR EN TECNOLOGIAS DE INFORMACION | |
| dc.contributor.director | Leboeuf Pasquier, Jeròme | |
| Aparece en las colecciones: | CUCEA | |
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