Ke-Chin Yen,
Department of Architecture and Urban Planning, Chung Hua University, 707, Sec 2, Wu-Fu Rd, Hsinchu City 30012, Taiwan ROC
dama@chu.edu.tw
ABSTRACT
Wetlands are natural buffer areas crucial to coastal environments, especially for island countries such as Taiwan in which land resources depend on wetlands for protection. However, the current regional management system for land use cannot effectively prevent damage to coastal wetlands. The significance of wetlands outweighs the consequences from restricting or controlling their utilization and development. A management system utilizing performance standard criteria based on sustainable managerial concepts will likely prove useful for sustaining conservation of wetland. The goal of this study is to establish criteria for performance standards for Taiwan’s coastal wetlands, and, by using the Grey Relation Analysis Model, develop a performance index for independence and availability that can serve as reference for future study.
Of the 22 index features of wetland environmental functionality that are determined based on the definition and functionality of wetlands, this study identified 7 index items for applicability and representative for coastal wetland performance management. Following screening, these indices employed in managing coastal wetland environments in which exist a high degree of uncertainty, extreme difficulty gathering data, ambiguous correlations among functionality indices, and vulnerable to the effects of subjective definitions.
Keyword: Coastal wetland, performance management, grey relational analysis model INTRODUCTION
As an island, Taiwan has approximately 11,846 hectares of wetlands. Therefore most coastal development is directly or indirectly related to wetlands. Wetland preservation is typically in conflict with development. Wetlands are natural buffer areas and their importance has been well recognized by many countries. Advanced countries, such as the US, Japan and the most European countries, have adopted sustainable management systems to protect their wetlands (Broll et al.
2002; Yamashita 1994), implementing different levels of wetland in accordance with wetland functions. However, in many years of development of west coastal wetland, it is mostly for external use of land, but seldom for management on inherent characteristics of land. The results in some environmental issues and creates many land ecological problems being overlooked.
Agenda 21, was adopted by the United Nations Conference on Environment and Development, its contents emphasized ecological land use and environmental planning and management (Chiau 1998). Taiwan’s current land management system is still based on traditional land classifications and zoning and cannot exert precise control over land use and fails to protect the environment.
The conventionally adopted system is particularly not applicable to resource management and preservation for sensitive areas such as waterfront and wetlands. Performance standards, which are substantial and flexible criteria for land resource utilization, accommodate public interests while prioritizing the carrying capacity of the land. The feature of performance standards is that land use plans and resource management measures are combined. To respect carrying capacity of environment and resources, performance standards are developed to control the negative effect of zoning and achieve the goal of coexistence of humans and their surrounding environment.
This study, which adopts the concept of sustainable management, attempts to establish the performance standard criteria for sustainable management of coastal wetlands. After examining issues related to wetland resources, indicators that can investigate performance management for different development activities were identified. Since wetland environments are complex and dynamic environmental systems, there are numerous obstacles to data collection. Thus, this study considers wetland performance management system as a grey system. Under the condition of small sample with uncertainty, grey relational analysis from grey system theory is used to select performance standard criteria for management of coastal wetlands. The method will increase the feasibility of the proposed research and reduce subjectivity in manual operation of information.
After the characteristics of the performance indicators are selected by independence, data accessibility and simple operation, these performance standard criteria are used as references to develop land use zoning for coast and help establish the method of research for wetland classification, assessment and quantification.
SELECTION MODEL —GREY RELATIONAL ANALYSIS
The grey system is a real-world system that can accommodate incomplete or uncertain information. A small sample with uncertainty can be described in the grey system (Deng 1989). Correlation grade is typically a relationship between two variables, functions, etc. Grey relational analysis assesses the relationship between factors (grey relational grade) to evaluate correlations among factors. Through such a correlation grade differentiation, the independence of factors can be identified.
The grey relational analysis model is an influence measurement model based on grey system theory which, in turn, is based on the following principles (Tzeng and Tsaur 1994): (1) the established model is a non-functional sequence model; (2) the calculation method is simple and easy; (3) there is no strict requirement for sample quantity; (4) sequence data for section characteristics do not require normal distribution with probability compliance; and, (5) the correlation grade among sample data can be analyzed and conclusions made without any conflict with qualitative analysis.
If
X
={ x
j |j
∈N }
is a grey relational factor set,x
0∈X
is a reference sequence,x
i∈X ( i
≠0)
is a comparative sequence, k is the number of samples (k =1,2,…,n), i is the number of indicators (i =1,2,…,m), thenx
i( ) k
represents the number for ith indicator and kth point andx
0( ) k
is the number of kth point for the reference indicator. Thus, the grey relational grade definition forx
i, with respect tox
0, isγ ( x ,
0x
i)
and the grey relational coefficient is
γ ( x
0( ) ( ) k
,x
ik )
. The more similarx and
ix are, the larger
0( x ,
0x
i)
γ
is. From each of the above assumptions, the equation for grey relational gradeγ ( x ,
0x
i)
can be derived as( ) ∑ ( )
=
= n
k
i
i x k x k
x n x
1 0
0 1 ( ), ( )
, γ
γ ,
( )
) ( ) ( max max )
( ) (
) ( ) ( max max )
( ) ( min min ) ( ), (
0 0
0 0
0 x k x k x k x k
k x k x k
x k x k
x k x
k i i i
k i i i
k i
i − + −
− +
= −
ς γ ς
This study, therefore, adopts the grey relational analysis model as its indicator selection method for coastal wetland performance indicators. For wetlands with complex environments, uncertainty of information and difficulty in data collection, this methodology can identify simply representative wetland indicators.
SELECTION OF COASTAL WETLAND PERFORMANCE MANAGEMENT INDICATOR
3-1 Initial Indicators
According to the elements comprising wetlands and their non-use functions, this study uses hydroperiod, soil structure and aquatic plants as the three natural wetland components to develop the wetland environmental function indicators (Mitsch and Gosselink l993).
1.Hydrology: Groundwater recharge(W1); Surface water inflow(W2); Assimilative capacity(W3); Tidal effect(W4); Water level(W5); Water flow velocity(W6); Self- purification(W7); Influent and effluent(W8);
Flood frequency(W9)
2.Soil structure: Salinity(W10); Water quality(W11); Water saturation period(W12); Soil porosity(W13);
Nutrient effectiveness(W14); Soil erosion(W15); Contaminant sediment(W16); Organic content(W17) 3.Plant ecology: Vascular plant type(W18); Aquatic plant density(W19); Plant energy flow(W20); Plant community structure(W21); Animal community structure(W22)
3-2 Grey Relational Grade Calculation and Sequencing 1.Calculation of grey relational grade
γ ( W ,
1W
i)
2.Grey relational grade
γ ( W ,
1W
i)
Sequencing3.Clustering of performance indicator: repeating steps 1 and 2 for grey relational grade calculations and sequencing obtains the indicator of comparative sequence result for each reference sequence. The comparative sequence indicators with similar sequencing are clustered as are those with high correlations.
Fig. 1 shows each reference sequence indicator in the same cluster as W1 and the comparative sequence indicator sequencing results. The six corresponding values in the normalized matrix to the reference sequence are plotted as a broken line. From Fig.1, the similarity among W1, W5, W8, W12, W16, and W20 is identified.
3-3 Selection of Representative Indicator
Following the calculation in Section 3-2 the 22 wetland environmental functional indicators are clustered into 7 categories. Then one indicator in each category is selected as the representative indicator by applying the principles of selection for a representative indicator with consideration of data availability, indicator controllability, minimization of indicator and repeating relationships among indicators. The 7 clusters is: 1.Water level(W1; W5; W8; W12; W16; W20); 2.Surface water inflow(W2; W4; W15); 3.Water quality(W7; W11); 4.Water flow velocity(W6; W10; W18); 5.Organic content(W9; W14; W17); 6.Soil porosity(W3; W13; W21; W22); 7.Aquatic plant density(W19).
CONCLUSION
Increasing urbanization is gradually destroying Taiwan’s western coastal wetlands. Most advanced countries recognize the importance of wetland preservation. If effective wetland management measures are not instituted, the roughly 20 remaining wetlands in Taiwan will likely disappear. This attempted to develop an effective wetland environmental management standard despite the lack of wetland environmental data and related research activities. Grey system theory was applied to identify a coastal wetland performance management indicator. Such representative indicators should provide a reference for further management system planning.
ACKNOWLEDGMENTS
The authors would like to thank the National Science Council of the Republic of China, Taiwan for financially supporting this research under Contract No. NSC 96-2415-H-216-007.
REFERENCES
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Chiau, W. Y. 1998. The role of religion in coastal resource management: The case of Kupo Island, Penghu (Pescadores), Taiwan. Coastal Management,26(1), 17-31.
Deng, J. L. 1989. Introduction to grey system theory. The Journal of Grey System, 1(1), 1-24.
Mitsch, W. J. and Gosselink,J. G. l993. Wetlands, New York: Van Nostran Reinhold.
0 . 0 0 0 0 . 0 5 0 0 . 1 0 0 0 . 1 5 0 0 . 2 0 0 0 . 2 5 0 0 . 3 0 0 0 . 3 5 0 0 . 4 0 0
1 2 3 4 5 6 7 8 9 1 0
k
x(k)
W 1 W 5 W 8 W 1 2 W 1 6 W 2 0
Figure 1 Broken Line for Indicators of W1, W5, W8, W12, W16, W20 in the Same Cluster
Tzeng, G. H. and Tsaur, S. H. 1994. The multiple criteria evaluation of grey relation model. The
Journal of Grey System, 6(3), 87-108.
Yamashita, K. 1994. The History of Wetland Conservation Movement in Japan, Tokyo:
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