Scaling Effects in Spatial Multi-Criteria Decision Aggregation in Integrated River Basin Management

Rania Taha,Jörg Dietrich,Alexandra Dehnhardt,Jesko Hirschfeld

doi:10.3390/w11020355

Abstract

For river basin management plans (RBMPs), measures are aggregated from smaller spatial units (e.g., water bodies) to the catchment or basin scale. River basin management plans measures in integrated management are evaluated using multiple criteria, e.g., ecological and socio-economiccriteria, etc. Therefore, aggregation often combines spatial analysis and multi-criteria decision analysis (MCDA). Herein, we investigate: (1) the effect of applying different aggregation pathways on the outcome of the RBMP using the technique for order of preference by similarity to ideal solution (TOPSIS) as an MCDA method, (2) the scaling effects considering water body, sub-catchment, and river basin scales, and (3) the effect of using global and local criteria weighing on the final ranking of alternatives. We propose two approaches to aggregate ranks for the entire basin: using non-dominated alternatives only and using a normalized TOPSIS relative closeness value. The results show no variation in the final non-dominated alternative for both aggregation pathways. However, we note rank reversal among the dominated alternatives. These results suggest that scaling effects need to be considered in spatial MCDA.

Highlights

The complexity of decision making has been recognized in a number of fields including water resources management, which is typically guided by more than one objective and by multiple stakeholders [1,2]
In fields involving spatial planning, Multi-criteria decision analysis (MCDA) can be combined with geographic information systems (GIS) [5]
We perform this investigation on three different spatial scales: the water body, sub-catchment, and river basin scales; As means of reflecting spatial variations onto criteria ranges, we further investigate the effect of applying the Range Sensitivity Principle (RSP) within the water body and sub-catchment scales; To allow the comparison of the results for the two pathways, we propose two approaches to aggregate rankings for the entire basin: (1) only using the non-dominated decision alternatives, (2) using the performance values of all alternatives

Summary

Introduction

The complexity of decision making has been recognized in a number of fields including water resources management, which is typically guided by more than one objective and by multiple stakeholders [1,2]. Multi-criteria decision analysis (MCDA)— known as multi-criteria decision making (MCDM), or multi-criteria analysis (MCA)—is “an evaluation method, which ranks or scores the performance of decision options against multiple criteria” [3]. It aims to improve the process of decision making through increasing its transparency, accountability, and auditability, and to introduce an analytically robust selection process, which is based on a better understanding of the trade-offs between the alternatives. Spatial MCDA is used in water policy evaluation, strategic planning, and infrastructure selection among other fields [1].

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