Informations et ressources scientifiques
sur le développement des zones arides et semi-arides

Accueil du site → Doctorat → États-Unis → 1988 → Storm runoff forecasting model incorporating spatial data

University of Arizona (1988)

Storm runoff forecasting model incorporating spatial data

Karnieli, Arnon

Titre : Storm runoff forecasting model incorporating spatial data .

Auteur : Karnieli, Arnon

Université de soutenance : University of Arizona

Grade : Doctor of Philosophy (PhD) 1988

Résumé
This study is concerned with design forecasting of storm hydrographs with emphasis on runoff volume and peak discharge. The objective of the study was to develop, calibrate and test a method for forecasting storm runoff from small semi-arid watersheds using an available prediction model. In order to turn the selected prediction model into a forecasting model an objective procedure in terms of an API-type model was developed for evaluating the soil moisture deficit in the upper soil layer at the beginning of each storm. Distinction was made between the physically-based parameters and the other fitting parameters. The rainfall excess calculation was computed by solving the Green and Ampt equation for unsteady rainfall conditions using the physically-based parameters. For the physically-based parameters a geographic information system was developed in order to account for the variability in time and space of the input data and the watershed characteristics and to coregister parameters on a common basis. The fitting parameters were used to calibrate the model on one subwatershed in the Walnut Gulch Experimental Watershed while the physically-based parameters remained constant. Two objective functions were selected for the optimization procedure. These functions expressed the goodness of fit between the calculated hydrograph volume and peak discharge and the observed volume and peak discharge. Linear relationships between the effective matric potential parameter and the two objective functions obtained from the sensitivity analyses made it possible to develop a bilinear interpolation algorithm to minimize, simultaneously, the difference between the calculated and observed volume and peak discharge. The prediction mode of the model was tested both on different storm events on the same subwatershed and on another subwatershed with satisfactory results. In the prediction mode the effective matric potential parameter was allowed to vary from storm to storm, however, in the forecasting mode these values were obtained from the API model. Relatively poor results were obtained in testing the forecasting mode on another subwatershed. These errors were able to be corrected by changing the channel losses fitting parameters.

Mots clés : Hydrology. ; Runoff – Arizona – Tombstone Region – Forecasting. ; Rain and rainfall

Présentation

Version intégrale (7,83 Mb)

Page publiée le 3 juin 2013, mise à jour le 29 décembre 2016