Effects of Urbanization Factors on Model Parameters

Cheng, Shin-jen; Lee, Cheng-feng; Lee, Ju-huang

doi:10.1007/s11269-009-9471-9

Cited by 23 publications

(12 citation statements)

References 35 publications

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“…This study concerns the applicability of urbanization variables for regular variations of hydrographic parameters. Previous research showed that changes related to urbanization in watershed divisions may be associated with imperviousness or population density (Cheng et al 2010). Relationships may exist between model parameters and urbanization variables.…”

Section: Correlativity Of Parameter Behaviour and Urbanization Variablesmentioning

confidence: 99%

Effects of urbanization variables on model parameters for watershed divisions

Chen

Chuang

Cheng

2014

Hydrological Sciences Journal

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A semi-distributed model with a parallel connection was applied to examine the effects of urbanization variables. Data were obtained from watershed divisions that were characterized by various degrees of urbanization. The mean rainfall was calculated using the kriging method. The model inputs were obtained by subtracting mean rainfall from Ф-index values, based on the spatially uniform loss assumption. Regression analysis was applied to determine the relationship between the parameters of 64 calibrations and urbanization variables among the divisions. The results showed that overland parameters produced more consistent change in response to imperviousness than to population. Conversely, the channel parameter was unaffected by changes in urbanization. The verification results of 46 cases showed that power linkage was a potential option for linking division parameters with the corresponding imperviousness based on four evaluation criteria. The changes in imperviousness on overland parameters show the hydrological effects of division urbanizations.

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Section: Correlativity Of Parameter Behaviour and Urbanization Variablesmentioning

confidence: 99%

Effects of urbanization variables on model parameters for watershed divisions

Chen

Chuang

Cheng

2014

Hydrological Sciences Journal

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“…There are several schemes for estimating average rainfall values from raingauge data, including the inverse distance method (Maidment 1993), Thiessen polygon method, height-balanced polygon method, and block Kriging method (Delhomme 1978;Isaaks and Srivastava 1989;Cheng and Wang 2002;Cheng et al 2008b;Huang et al 2008a;Huang et al 2008b;Cheng et al 2010;Cheng 2010b, c). These methods often assign weights to raingauge observations using weighted mean by related observations, and then obtain mean rainfall estimations for specific areas.…”

Section: Introductionmentioning

confidence: 99%

Effects of Raingauge Distribution on Estimation Accuracy of Areal Rainfall

Cheng

Wen

et al. 2011

Water Resour Manage

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Rainfall analysis is important to managing water resources. Mean rainfall is usually used to calculate the spatial rainfall status of a region and is the input into various rainfall-runoff models. However, this method relies on an adequate raingauge network. This study identifies the effects of raingauge distribution based on estimation results of areal rainfall using the Thiessen polygon and block Kriging methods. Twelve rainfall events with complete data from 14 raingauges were selected to complete the goal of this study. The block Kriging method in this study uses a dimensionless semivariogram to obtain hourly semivariograms based on a standardized rainfall depth. The power semivariogram model was used to describe the temporal-spatial variation of rainfall. The analytical process in this study uses raingauge weight and rainfall volume as evaluation criteria. All raingauges were in turn removed from the original raingauge network. The effects of removing each raingauge were compared with computations using all raingauges. Comparison results indicate that (1) the block Kriging method can accurately describe rainfall processes in terms of the spatiotemporal structure of a semivariogram. (2) the block Kriging method is better than the Thiessen polygon method at obtaining exact mean rainfall, and (3) the effects of different raingauge distributions on a mean hyetograph warrant further investigation.

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“…An increase in impermeable surfaces connected to a waterway will increase peak stream flows and the risk for flooding or channel erosion. The problems created by impervious cover and subsequent runoff are well-documented and go straight to the center of issues of land use change, urban sprawl, and impacts on the environment and urban riparian ecology (Morse et al 2003;Walsh 2000;Cheng et al 2009). …”

Section: Introductionmentioning

confidence: 99%

A Smart Market for Impervious Cover

Raffensperger

Cochrane

2010

Water Resour Manage

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When farmland or undeveloped ground is covered over, runoff can cause environmental damage and flood risk. Policymakers want to compare the economic improvement of new development to the costs produced by the associated environmental impacts. In this paper, we propose a smart market in impervious cover. A smart market is a periodic auction which is cleared by an optimization model, a linear program (LP) in this case. The LP constraint coefficients come from a hydrological model. The LP objective coefficients come from users' bids. To operate the auction, local government would appoint an auction manager, who would be responsible for maintaining the hydrological model and the LP, for operating the auction, and for maintaining the desired environmental standards. At regular intervals, the auction manager would accept bids over the internet, solve the corresponding LP, and announce the results. By LP duality, the smart market prices impervious cover at the opportunity cost to society, adjusted for location, the sensitivity of environmental features, and the incremental value of the development as indicated by bids. This design uses relevant hydrological information, and accepts community input on the desired environmental standards (avoiding the tragedy of the commons). The auction creates incentives to remove impervious cover, especially near environmentally sensitive areas. The proposed system nearly eliminates transaction costs associated with trading development rights.

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Effects of Urbanization Factors on Model Parameters

Cited by 23 publications

References 35 publications

Effects of urbanization variables on model parameters for watershed divisions

Effects of urbanization variables on model parameters for watershed divisions

Effects of Raingauge Distribution on Estimation Accuracy of Areal Rainfall

A Smart Market for Impervious Cover

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