CRIDE: A Case Study in Multi-Criteria Analysis for Decision-Making Support in Rainwater Harvesting

Abstract

This paper aims to develop a multi-criteria decision analysis (MCDA) tool for rainwater harvesting (RWH) on a university campus in Bogota, Colombia. The specific type of MCDA our research proposes is known as CRIDE (multi-CRIteria DEcision support tool), which allows us to study various methods of RWH. In order to account for uncertainties such as the variability of expert opinions and imprecision stemming from the different criteria required, we have designed this tool to incorporate ELECTRE II and the Monte Carlo method. For this case study we apply a methodology that evaluates the performance of six RWH scenarios. These six input scenarios emerged from an ideal one, wherein all rainwater throughout the campus is successfully harvested and treated until potable. From there, reality sets in: the other five scenarios are varying degrees of deviance from the ideal one, both in terms of water quantity and quality. In regard to collection and treatment we used sustainable urban drainage systems (SUDS). As for the evaluation of each of the scenarios, we outline eight criteria, which include hydraulic performance, compatibility with the University's Master Plan and financial aspects. Our research concludes that CRIDE as a means of support during the decision-making process generates a complete view of possible solutions, in addition to ranking these solutions. The CRIDE-based approach allows for the proposal of a methodology that evaluates the relevance of an established criteria set, using robustness, redundancy and sensitivity.

Developing GIS-based water poverty and rainwater harvesting suitability maps for domestic use in the Dead Sea region (West Bank, Palestine)

“…RWH is the process of collecting and storing rainwater in order to be used afterwards for different uses among which is the domestic one (Gould and Nissen-Petersen, 1999). It is considered an ancient technology dating back to biblical times and was practiced in Palestine and Greece 4000 years ago (Critchley et al, 1991).…”

Towards a Constructed Wetland/Reservoir- Tank System for Rainwater Harvesting in an Experimental Catchment in Colombia

“…This scenario consists of the runoff collection on nine basins (Figure 3) (basins number 1, 2, 3, 4, 5, 9, 10, 11 and 12) with quality for non-potables uses (floor cleaning, sanitary discharge, and landscape irrigation) using SUDS such as: basins, bioretention gardens, permeable paving, and constructed wetlands [59] for the collection and treatment of rainwater [56]. The results were reported to the PRO of the University, and they decided to design and construct scenario number five, beginning with the RWH of one of the nine basins (basin number 2).…”

“…In this place it was projected the collection of stormwater runoff from the parking building (3,776 m 2 ), the soccer field, and the areas that surround it (14,816 m 2 ). Source: [56].…”

“…The weight of each criteria was defined by a survey conducted by four PRO leaders of the University and five experts on water management. The scenarios were evaluated with the set of criteria defined, in order to construct the decision matrix with minimum, average, and maximum assessments [56].…”

Organizational performance evaluation in intangible criteria: a model based on knowledge management and innovation management

“…As the Innovative organizational culture To observe if the organizational culture is focused on innovation KPI 17 Partnership with universities Represent the degree of involvement with universities and research centers determination of weights W y , according to Eq. (5), it was proposed to use standard techniques to faithfully represent the preference of the decision maker, such as Swing Weighting and Simple Attribute Rating Technique (SMART), based on the assumptions of Guitouni and Martel (1998), Clemen and Reilly (2001) and Poyhonen and Hamalainen (2001), so that the first, laid down by Edwards (1971), performs this process by the direct decreasing order of importance for each one of them, for which is usually assigned for the worst placed a value of 10 and, from this, values are listed increasingly, according to the degree of discrepancy in the existing behavior between them (Figueira, Greco, & Ehrgott, 2005;Galarza-Molina et al, 2015). As for the technique named Swing Weighting, the logic of value assignment occurs in reverse, starting from the same ordering system, identifying which has greater relevance, adopting the value 100 and performing this same process to the remaining as far as reaching a value able to resume the less relevant item in relation to the hierarchical system level in question, as the difference found in each range is set again according to the characteristics of both (Gomes & Gomes, 2012),…”