Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-09T02:15:38.629Z Has data issue: false hasContentIssue false

11 - Stochastic precipitation-runoff modeling for water yield from a semi-arid forested watershed

Published online by Cambridge University Press:  18 January 2010

Janos J. Bogardi
Affiliation:
Division of Water Sciences, UNESCO, Paris
Zbigniew W. Kundzewicz
Affiliation:
Research Centre of Agricultural and Forest Environment, Polish Academy of Sciences
Get access

Summary

ABSTRACT

A stochastic precipitation-runoff modeling approach is used to estimate water yield from a particular forested watershed in North Central Arizona. The procedure uses selected theoretical probability distribution functions and a random number generator to describe and simulate various precipitation characteristics, such as storm depth, duration, and time between storm events. The spatial characteristics of precipitation events are described in terms of their orographic and areal distribution patterns while temporal distributions are expressed in terms of daily events in the watershed. The generated precipitation events are used as input into a precipitation-runoff model to estimate water yield from a particular forested watershed. The method uses geographic information systems (GIS) to subdivide the study watershed into cells assumed to be homogenous with respect to watershed characteristics, such as elevation, aspect, slope, overstory density, and soil type. The total water yield is the accumulated surface runoff generated at the watershed outlet. The outcome is the development of an improved model for estimating water yield which takes into consideration uncertainty, as well as temporal and spatial watershed characteristics. This method is useful not only for providing water resources managers with a good estimate of the amount of water yield, but also for determining the reliability or failure of a source to meet desired downstream water demands.

INTRODUCTION

This chapter is concerned with the development of an appropriate precipitation-runoff model for estimating water yield from a semi-arid forested watershed. This involves combining a stochastic precipitation model and a deterministic runoff model. The first one is selected to capture the inherently uncertain characteristics of precipitation, while the latter is chosen to simplify an otherwise complex surface runoff estimation method.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2002

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×