Bio-based and Applied Economics 10(2): 109-122, 2021 | e-ISSN 2280-6172 | DOI: 10.36253/bae-9545 B i o - b a s e d a n d A p p l i e d E c o n o m i c s BAE Copyright: © 2021 R. Zucaro, V. Manganiello, R. Lorenzetti, M. Ferrigno. Open access, article published by Firenze University Press under CC-BY-4.0 License. Firenze University Press | www.fupress.com/bae Citation: R. Zucaro, V. Manganiello, R. Lorenzetti, M. Ferrigno (2021). Applica- tion of Multi-Criteria Analysis select- ing the most effective Climate change adaptation measures and investments in the Italian context. Bio-based and Applied Economics 10(2): 109-122. doi: 10.36253/bae-9545 Received: July 30, 2020 Accepted: June 23, 2021 Published: October 28, 2021 Data Availability Statement: All rel- evant data are within the paper and its Supporting Information files. Competing Interests: The Author(s) declare(s) no conflict of interest. Editor: Meri Raggi, Fabio Bartolini. ORCID RZ: 0000-0001-9386-7612 VM: 0000-0003-0348-6600 RL: 0000-0003-3346-0874 MF: 0000-0002-5347-0984 Application of Multi-Criteria Analysis selecting the most effective Climate change adaptation measures and investments in the Italian context Raffaella Zucaro, Veronica Manganiello, Romina Lorenzetti*, Marianna Ferrigno Council for Agricultural Research and Economics - Research Centre for Agricultural Poli- cies and Bioeconomy (CREA-PB), Via Po 14, 00198 Roma, RM, Italy. E-mail: raffaella.zucaro@crea.gov.it, veronica.manganiello@crea.gov.it, romina.lorenzet- ti@crea.gov.it, marianna.ferrigno@crea.gov.it. *Corresponding Author: romina.lorenzetti@crea.gov.it Abstract. In the context of climate change, one of the EU’s major political efforts focus on water management. Public investment is carried out considering several drivers, from economic development to demographics, climate, and pollutants. Meanwhile, the need for evaluation methods is also increasing, so their development has grown in recent years. Among these, Multi-Criteria Analysis methodologies (MCA) have taken on great importance. This work aims to demonstrate the usefulness of MCA in addressing crucial environmental issues, such as the use of water resources for agri- cultural and food production. The document presents an application of MCA for the ranking and selection of projects to be financed under the Italian National Plan on Water Resources. The Plan is part of the national initiatives planned for the adaptation of the agricultural sector to climate change. The selection criteria have been identified following a participatory approach, and to respond to both the challenge of climate change and the limited availability of funds. MCA is used to select the best projects to be financed with the available amount. The Italian experience confirms the effective- ness of MCA and highlights how the involvement of both decision makers and stake- holders is necessary for a successful application of MCA to environmental issues. Keywords: drought risk, water management, investment database, reservoirs, climate change. 1. INTRODUCTION In recent decades, climate change has caused worrying drought events across Europe, even in Countries where past meteorological drought had been rare. This situation has led EU Member States to monitor the availability of and need for water, to provide timely alerts in the event of drought and iden- tify possible actions to undertake in the event of a crisis. Recent studies car- ried out on the Italian territory have shown a growing climate heterogeneity due to climate change (Zucaro, 2017; ISPRA, 2018). In the past, drought events http://creativecommons.org/licenses/by/4.0/legalcode 110 Bio-based and Applied Economics 10(2): 109-122, 2021 | e-ISSN 2280-6172 | DOI: 10.36253/bae-9545 Raffaella Zucaro et al. were mainly concentrated in the Southern Regions and Islands, while, in the last 20 years, Central and Northern Italy have also suffered from recurrent droughts. The agricultural sector is the most exposed to the effects of climate change (Mahato, 2014), there is there- fore a need for targeted investments increasing the preparedness to face extreme events. As f loods and droughts affect both the quantity and quality of water, they contribute to environmental degradation and loss of ecosystem services. Thus, all Member States (MSs), including Italy, are implementing adaptation and miti- gation measures. International institutions, and in par- ticular the European Union (EU) are steering their poli- cies and economies towards long-term sustainability. In recent years, there has been a crescendo in the political narrative aimed at promoting climate change adaptation and mitigation. Several actions have been proposed to implement these policies, namely: enhancing knowledge in the field of climate change adaptation and mitigation policies (EU Adaptation Strategy, European Commis- sion, 2013); managing water risks and disasters; ensur- ing good water governance and sustainable investment for water services (OECD, 2015, ODEC 2016); encourag- ing the sustainable use of water for agriculture and the introduction of priority actions for the adaptation of agriculture to climate change (FAO – WASAG Global Framework for Action to Cope with Water Scarcity in Agriculture); taking account of climate adaptation in public and private investments (European Green Deal, European Commission, 2019). Several measures, singly or in combination, can be taken to cope with drought risk in agriculture, climate change adaptation, and sustainable water management. These include regulatory measures, risk management measures, water governance, research and innovation, and structural measures. There is no single decisive action, but the most effective one or a combination of them should be taken. Public investment in water dis- tribution infrastructure allows for greater and more constant availability of water for irrigation and great- er efficiency in water use, by reducing water abstrac- tions, introducing instruments for water metering, and increasing the use of non-conventional water. These investments can also contribute to achieving the objec- tives of the Water Framework Directive (WFD, 2000/60/ EC) of ensuring the availability of quality water for the needs of people and the environment. This is possible through the improvement of the ecological quality of water bodies and the conservation and restoration of areas of naturalistic interest (e.g. Nature 2000 sites). At the European level, specific funds have been allo- cated to finance irrigation investments as a response to the water crises of 2003 and 2007. These investments aimed to increase water storage and irrigation efficiency, through the modernization of existing assets, the build- ing of new reservoirs, and the recovery and improve- ment of existing ones. To decrease the dependency on conventional sources and reduce withdrawals from natu- ral water bodies, the promotion of the reuse of treated wastewater for irrigation purpose is also pursued. In Italy, with the aim of ensuring the integrated management of water resources, a steering commit- tee has been set up to coordinate the various adminis- trations responsible for water: the Steering Committee addressing investments in cross-sectoral investments, responding to the recommendations of the European Commission communication “Addressing the challenge of water scarcity and drought in the European Union” (COM, 2007) 414 final). Following this strategy, in 2017 the Italian Govern- ment financed the “National Plan of interventions in the Water Sector” (Budget Law 2018, December 27, 2017, No. 205). The National Plan was finalized to modernize and complete the national water distribution network (including the irrigation network) and to build new res- ervoirs. The National Plan also foresaw the adoption of an Extraordinary Plan, consisting in the implementation of urgent interventions against drought, with a focus on multipurpose reservoirs. At the River Basin scale, reservoirs are considered as effective climate change adaptation measures, espe- cially where natural water availability is highly vari- able throughout the year. In fact, they retain water to be released during periods of scarcity, thus sustaining irri- gated agriculture and increasing the availability of water for irrigation (Biemans, 2011). In addition, reservoirs have ecological and recreational functions, ranging from the conservation of protected migratory species (Mas- cara, 2010) and biodiversity (Deacon, 2018, Croce, 2015), to cultural and recreational purposes. That is why some of them are now defined as natural conservation areas. The case study shows the procedure followed by the Council for Agricultural Research and Economics (CREA), on behalf of the Italian Ministry of Agriculture (Mipaaf ), in selecting interventions to help the agricul- tural sector adapt to climate change. The interventions were selected according to the objectives of the Extraor- dinary Plan applying a Multi-Criteria Analysis (MCA). MCA is a non-monetary method of ranking and prior- itizing the characteristics of the projects submitted for funding. The paper aims to present the feasibility and useful- ness of MCA in identifying the most effective project proposals in the field of water, stating that this method 111Application of Multi-Criteria Analysis selecting the most effective Climate change adaptation measures and investments in the Italian context Bio-based and Applied Economics 10(2): 109-122, 2021 | e-ISSN 2280-6172 | DOI: 10.36253/bae-9545 can allow the inclusion of different disciplines in a sin- gle evaluation frame. In addition, MSs need appropri- ate methods to assess ex ante effectiveness of investment projects, including their potential impacts on natural resource protection. The Italian experience can therefore be extended to other countries. 2. DATA AND RESEARCH METHODOLOGY 2.1 Multi-Criteria Analysis Multi-Criteria Analysis (MCA) was selected as a method for classifying and selecting projects, as it allowed consideration of the different priority elements according to the requirements by the funder, and the needs in term of adaptation to climate. MCA was consid- ered the appropriate method as it allowed several specific agricultural and environmental conditions to be applied (Figueira et al., 2005). This facilitates the achievement of increased efficiency and sustainability in the use of natu- ral resources in line with the EU guidelines. Several papers have been published over the last 30 years on the empirical applications of MCA to a range of nature conservation topics, including: conservation pri- ority and planning; management and zoning of protect- ed areas; forest management and restoration; mapping of biodiversity, naturalness, and wilderness. Many referenc- es can be found in several reviews, such as: Mendoza et al. (1986); Romero and Rehman (1987); Tarp and Helles (1995); Hayashi (2000); Kangas et al. (2001); Steiguer et al. (2003); Mendoza and Martins (2006). A recent and extensive review of the applications of Multi-Criteria Decision Analysis was carried out by Adem Esmail and Geneletti, (2017), based on 86 papers and dealing with empirical applications in nature and biodiversity conservation. Decision-making in envi- ronmental management requires more and more com- parison alternatives to achieve multiple and compet- ing goals. Indeed, many of the following objectives must often be considered: ensuring a sufficient quantity of water for both people’s needs and the environment (Water Framework Directive – implementation of the Water Framework Directive), economic development, addressing the challenges posed by demographic change, climate change, and emerging pollutants. The public administrations responsible for determining and evalu- ating strategic choices need systems and/or selection cri- teria that are as objective as possible and not influenced by endogenous factors. This problem is particularly acute when it comes to public funding. In this context, Multi-Criteria Methodologies have become important because they provide valuable help in choosing between alternatives, especially since the clas- sic economic and monetary surveys do not represent the plurality of aspects that these problems present (Skoniec- zny et al, 2005). Compared to monetary methods based on welfare economy principles (Cost- Benefit Analysis, CBA), non-monetary methods that also consider natural resources and are based on decision theory are an alter- native when assessing the effectiveness of the interven- tions. While CBA is mainly applied to project evaluation to improve a specific environmental service, non-mone- tary methods such as MCA are used for issues related to territorial and environmental assessment and planning, as they can also evaluate qualitative information. Cur- rently, several books deal with Multi-Criteria method- ologies as applied to natural resources management (e.g. Zeleny, 1984; Yoon and Hwang, 1995; Malczewski, 1999; Belton and Stewart, 2002). Basically, MCA is applied with the following typical steps: 1. Structuring of the problem and the decision-making network. 2. Data acquisition and processing. 3. Normalization (linear normalizations or Value and Utility functions). 4. Criteria and weight allocation. 5. Calculation and sorting of alternatives (e.g. with outranking methods; graphic methods; scoring methods). 6. Results. 7. Sensitivity analysis (optional). The next paragraph describes how these steps were applied to the case study. 2.2. Applied methodology In this study, the listed steps of the Multi-Criteria Analysis were slightly reformulated, as follows. 1. Structuring of the problem and the decision-mak- ing network. There are many MCA approaches that differ in terms of computational complexity, level of stakehold- er engagement and time and data requirements. To protect the agricultural sector against drought events, policymakers identified structural measures, concerning infrastructure interventions on multipurpose reservoirs for water collection during rain periods and water saving interventions. A specific fund has been set up to these objectives, governed by specific rules. Water management operates within an interdiscipli- nary framework that seeks to ensure the protection of resources (Cugusi and Plaisant, 2019; Dir. 2000/60/EC; Dlgs 152/1999; Autonomous Region of Sardinia, 2005), and requires the integration of ecological, economic, 112 Bio-based and Applied Economics 10(2): 109-122, 2021 | e-ISSN 2280-6172 | DOI: 10.36253/bae-9545 Raffaella Zucaro et al. and socio-political elements of different territorial scales. Therefore, all the institutions responsible for water man- agement (Ministries of Agriculture, Environment, Infra- structure, Regions and River Basin District Authorities (RBDAs)), Local Agencies for irrigation Water Manage- ment (LAWMs), and stakeholders were involved in the decision-making network of this case study. The involve- ment of the stakeholders was a selling point in the meth- odology adopted by the CREA. 2. Data acquisition and processing. For the collection of data useful for the analysis, the CREA, Mipaaf, and Regions with the support of the LAWMs, identified the infrastructure priorities to be financed through national and EU resources. All information was stored and man- aged by DANIA, the National Database of Investments for Irrigation and the Environment (http://dania.crea. gov.it/). It was implemented by the CREA for Mipaaf, for the collection of structural and financial information on financed and programmed projects. Information about investments were provided by Regions and by SIGRIAN, the National Information System for Water Resources Management in Agriculture (https://sigrian.crea.gov.it) managed by the CREA (Mipaaf, 2015). SIGRIAN con- tains data from the Italian national irrigation system and is the national reference database for the collection of data on water used for irrigation on a national scale. In this work, SIGRIAN was used to collect information on the use of water resources and the extent of the irri- gated area affected by the projects for the estimation of the catchment area. Starting from DANIA information, MCA was applied to identify a series of projects to be financed up to the amount of 80 million euros, allocated by the Extraordinary Plan. 3 - 4. Criteria and weight allocation and normali- zation. The criteria and their weights, as well as related attributes and scores were defined in compliance with the requirements and objectives of the financing instru- ment, by a technical committee of experts through focus group discussions. The focus group involved representa- tives of the aforementioned institutions, in the appli- cation of a participatory approach. Through debates between the actors of the technical committee, shared choices were developed. The participatory approach minimized decision makers’ subjectivity in weight and score allocation, which is a very important and delicate step. Indeed, it can influence the final order of alterna- tives and, therefore, significant involvement is appropri- ate. Within the Technical Committee, the criteria were defined in accordance with the objective and priority of the Fund. Once the criteria were decided, several pos- sible attributes for each criterion were defined. At first, the normalization step was bypassed in this case study. Since the main aim of normalization in MCA is to make quantities comparable, this was achieved by using nomi- nal attribute quantities, to which scores must then be assigned. The different attributes of the criteria were sorted according to their compliance with the selection aims. The weight of the criteria and the score of the attributes were assigned at the same time. Applying a monotoni- cally linear utility function, a discrete scoring scale was adopted, with a step of 1, in all the criteria. In a descend- ing way, a maximum score was assigned to its best attrib- ute and a lower score was assigned to the other attributes, according to the preferences of the technical committee, and with reference to the selection goals. In this way, the weight of a given criterion coincides with the high- est score assumed by its best attribute. Attribute scores ranged from 0-1 to 0-4, while the weights assigned to the criteria ranged from 1 to 4. With this operative choice, the discretions and uncertainties implied in weights were shifted to the definition of scores. For this reason, the technical committee verified that the highest score of each attribute truly represented the weight that the indi- vidual criterion should have had compared to the others. 5. - 6. Calculation and sorting of alternatives and examination of results. The ranking of alternatives, namely the projects, was achieved by applying a scoring method as a type of aggregation. The scoring method classified the alternatives by assigning a numerical eval- uation for each of the attributes considered; the scores obtained for each criterion were summarized in a “sum- mary indicator” which aimed to represent the effective- ness of the proposal in achieving the objectives of the Fund. The number of projects financed was the maxi- mum obtainable on the basis of the defined budget allo- cated by the Budget law. The direct assignation of a value to the attribute and the use of a linear aggregation meth- od with scores simply added together, have made the method used for the evaluation of the proposal clearer to the potential beneficiary. Consequently, even the self- assessment required in the submission phase of the pro- jects was more feasible. Self-assessment was introduced because the RBDA was called upon to prioritise propos- als, mainly based on the declared information. 7. Sensitivity analysis. The shared approach gave a certain degree of robustness, as the steps of criteria and weight allocation were based on the expert judgment of the technical committee. The order of importance of cri- teria and attributes was considered clear and objective, as it was shared among all the stakeholders. Neverthe- less, in this study sensitivity analysis was carried out to verify the stability of the results, testing some changes in the weight of criteria (Skonieczny G. et al. 2005). New 113Application of Multi-Criteria Analysis selecting the most effective Climate change adaptation measures and investments in the Italian context Bio-based and Applied Economics 10(2): 109-122, 2021 | e-ISSN 2280-6172 | DOI: 10.36253/bae-9545 weights were allocated to the criteria in compliance with the aims and rules of the Fund and without upsetting the priorities established by the technical committee. To perform sensitivity analysis, as first step, the attribute scores were normalized to the maximum value that each attribute could assume (maximum row normali- zation), so that all the attribute scores are between 1 and 0. Then, Weighted Linear Combination (WLC) was used (Malczewski and Rinner, 2015) for the aggregation. Fol- lowing equation 1, the normalized value of attribute score (xi) was multiplied for the tested weights (wi), and the new summary indicators (S) were returned for each alternative. (1) The new rankings of the alternatives, given from the different tested weight assignments, were compared with the original ranking by means of the Spearman’s rank correlation coefficient, that is a non-parametric measure of rank correlation, following equation 2 (Clef, 2013): (2) where i = paired score, x and y are the ranks, and x-bar and y-bar are the mean ranks. The analysis of the results was carried out taking into account that the Spearman correlation between two variables is high when obser- vations have a similar rank, up to a correlation of 1 for identical ranks. 3. RESULTS AND DISCUSSION This section describes the detailed application and results of each step described above. 3.1 Structuring of the problem and of the decision-making network The case study concerned the application of MCA when selecting infrastructure interventions to facilitate adaptation of the agricultural sector to climate change. The financial instrument identified was the Extraor- dinary Plan as part of National Plan of interventions in the water sector. It was introduced by the Budget Law 2018 to finance urgent interventions concerning: prefer- entially executive projects (the final phase of the project was also accepted); multipurpose reservoirs; water sav- ing in agricultural and household use. The decision-making network identified included the competent Ministries of Infrastructure (MIT), Envi- ronment (MATTM) and Agriculture (Mipaaf ), the 7 RBDAs, the 21 Regions and Autonomous Provinces, and the LAWMs. According to Italian legislation, the Regions are responsible for irrigation water management and recla- mation, while the LAWMs, reclamation and irrigation consortia, and land improvement consortia are territo- rial authorities and actuators of the interventions. 3.2 Data acquisition and processing - the Database At the time of the study, DANIA included 894 irri- gation infrastructure projects, representing almost 6 billion euros. Information was collected in the database for each project for their evaluation, in accordance with the established criteria. The stored data were acquired in collaboration with Regions and processed with iden- tification data (title, actuators, etc.), technical features of projects (project objective and type, project stage, etc.), intervention cost, vulnerability of the intervention area to drought and hydrogeological risk, regional priority of intervention (1-high, 2-medium, and 3-low). Starting with the stored projects, a first selection was made before applying the MCA according to the follow- ing eligibility criteria, in line with the Budget Law objec- tives and in the framework of financing fund rules: • project stage = executive (because quickly imple- mentable); • type of intervention = interventions on multipur- pose reservoirs and water saving interventions in agriculture; • regional priority of intervention = level 1 (urgent interventions). A dataset of 55 projects was identified on the entire national territory, representing a total amount of almost 360 million euros. The RBDAs were asked to give priori- ty to projects in this dataset, to which MCA was applied. 3.3 Criteria and their attributes Some of the adopted criteria related to technical elements and aims of projects, while others referred to effectiveness, in compliance with the aim and priority of the Fund, as established in Law 205/2017. As mentioned, the Extraordinary Plan dealt with multipurpose reservoir (irrigation and household) and the priority water saving objectives. More in detail, the Plan includes a) completion of interventions concern- ing large existing dams or unfinished dams; b) recovery and expansion of the reservoir capacity, waterproofing of large dams and safety of the main water derivations for significant river basins in seismic areas classified in 114 Bio-based and Applied Economics 10(2): 109-122, 2021 | e-ISSN 2280-6172 | DOI: 10.36253/bae-9545 Raffaella Zucaro et al. zones 1 and 2 and at high hydrogeological risk. As a result, the following project criteria were identified: • Water resource use. Multiple uses were favoured over exclusive ones. • Site sensitivity in terms of seismicity and hydrogeo- logical instability. Great importance was given to the presence of these hazards. One of the priority objec- tives was identified as safety in seismic areas (clas- sified in zones 1 and 2) and in areas of high hydro- geological risk. The technical committee decided to assign more importance to areas at seismic risk than to the landslide. Therefore, the same value was asso- ciated with the presence of hydrogeological risk and the presence of the lower class of seismic risk (fourth class). Increasing importance was given to other seismic classes, because of the growing risk. • Catchment area in Equivalent Inhabitants – EI (giv- en 40 Equivalent Inhabitants –per irrigated hectare). This criterion intended to indicate the impact of the project on the territory in term of users of financing (population or agricultural areas). Three classes were created for this continuous variable (EI > 500,000; 300,000 ≤ EI ≤ 500,000; EI < 300,000), both based on expert assessment, and on assessments based on the DANIA dataset. In addition, it was necessary to provide a unique criterion for household, irrigation, and multiple interventions. Thus, the irrigated area was returned to the EI, with a conversion criterion of 40 EI per hectare of irrigated surface. • Project stage. The attributes represented the possible status of the project. The Extraordinary Plan focused on the final and executive level. • Project objectives. This criterion aimed to select pro- jects compliant with fund objectives. So, comple- tion of existing dams and the recovery or extension of the reservoir capacity were among the priority objectives. In addition to these, a third class was cre- ated for projects aimed at the improvement of the derivation efficiency. • Project type. This criterion integrated the techni- cal information agreed in the previous one, detail- ing the specific type of intervention. The following attributes were identified: Securing; Extraordinary maintenance; Completion; New intervention. • Co-financing. This was considered a reward element by the Technical Committee to promote Public-Pri- vate partnership. • Possibility of subdivision into lots. This was consid- ered a reward element by the Technical Commit- tee, since it made it possible to assess the multiple financing of a project, even with different funding sources at different times. In addition, three effectiveness criteria were identi- fied, as follows. • Project effectiveness (ratio of the intervention cost to the number of equivalent inhabitants corresponding to the irrigated area covered by the project: project cost (€)/EI). The criterion was described in 3 class- es, namely < 25€/EI, >=25 €/EI <50 €/EI, >=50€/EI. They were created according to the evaluation by experts, also through the DANIA. • Territorial effectiveness. This reflected a classifica- tion of the Italian Regions in relation to the per- centage of their regional territory under risk of desertification; according to the scientific reference available for the national scale (Ceccarelli et al., 2006), 3 classes were adopted, namely: >40% very sensitive danger (Basilicata, Marche, Molise, Pug- lia, Sicily and Sardinia); > 40% moderately sensi- tive danger (Abruzzo, Campania, Emilia-Romagna, Lazio, Piedmont, Tuscany, Umbria and Veneto); lit- tle sensitive (other Regions). • District priority. This was the assessment provided by the RBDA on the effectiveness of the project, in the context of the specific River Basin Management Plans. This criterion was considered by the Tech- nical Committee to be the most important of the effectiveness criteria, as it was evaluated through expert assessment by each RBDA and summarised several environmental aspects. In particular, each RBDA established their priority based on the infor- mation listed above and considering the objectives of the Water Framework Directive (2000/60/EC) and the main issues in the National Plan. For the estima- tion of District priority, the factors considered were: - consistency with another District Plans; - criticality of the intervention area, such as the hydraulic risk level; hydro-morphological aspects; environmental pressures; - expected benefits in terms of pressure reduction on water bodies; - expected benefits in terms of improving the water balance at river basin level. The level of effectiveness dealing with the strategic environmental feature, was described with four attrib- utes: Strategic, Relevant, Important, Required. 3.4 Weight and score allocation The weights assigned to the criteria are shown in Table 1. The criteria with the highest weight were: dis- trict priority, seismicity degree, project type, and pro- ject stage (weight 4). They were of equal importance and were followed by water resource use, project objective, 115Application of Multi-Criteria Analysis selecting the most effective Climate change adaptation measures and investments in the Italian context Bio-based and Applied Economics 10(2): 109-122, 2021 | e-ISSN 2280-6172 | DOI: 10.36253/bae-9545 catchment area, and project effectiveness, each with a weight of 3. For an easier understanding of the order of the criteria, a matrix was developed (Table 2). The attributes assigned to each criterion and their scores are shown in Table 3. The normalization of the score is also reported because it was used to perform sensitivity analysis. Although the Project stage was used to enter the selection, it was included in the MCA criteria. The cri- terion cannot affect the MCA result in any way since each alternative evaluated had the same score. However, it was decided to keep it in the process because the same method was adopted by the MIT, on another group of projects to be financed with the same Fund. Unlike Mip- aaf, the MIT did not choose to focus only on executive projects. Therefore, it was necessary to maintain the cri- terion in order to make the results of the two selection processes comparable. 3.5 Calculation and sorting of alternatives and selection of the projects The summary indicator returned from the sum of the scores obtained from each project. It represented the effectiveness of the intervention proposal to meet the objective of the Fund. Based on the defined budget allo- cated by the Budget law, 10 projects were financed in the amount of almost 80 million euros (fig. 1 and table 4), all with a summary indicator of 22 to 26. The 10 projects financed were in 7 Regions (Veneto, Lombardy, Emilia-Romagna, Tuscany, Abruzzo, Sicily, and Sardinia) and were implemented by 8 LAWMs. Fig- ure 1 shows the location of the LAWM which received funding. Table 1. Criteria and their assigned weights . Criterion Weight ID Name Project criteria 1 Water resource use 3 2.1 Site sensitivity - seismicity 4 2.2 Site sensitivity - hydrogeological instability 1 3 Project objectives 3 4 Catchment area 3 5 Co-financing 1 6 Project type 4 7 Possibility subdivision in lots 1 8 Project stage 4 Effectiveness criteria 9 Project effectiveness (ratio cost/ equivalent inhabitants) 3 10 Territorial effectiveness 2 11 District priority 4 TOTAL 12   33 Table 2. Criteria order: Score matrix. Criteria Si te s en si tiv ity - hy dr og eo lo gi ca l in st ab ili ty C o- fin an ci ng Po ss ib ili ty su bd iv is io n in lo ts Te rr ito ri al eff ec tiv en es s Pr oj ec t e ffe ct iv en es s W at er r es ou rc e us e Pr oj ec t o bj ec tiv es B as in u se rs D is tr ic t p ri or ity Si te s en si tiv ity - se is m ic ity Pr oj ec t t yp e Pr oj ec t s ta ge Site sensitivity - hydrogeological instability 1 1 1 0.5 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 Co-financing 1 1 1 0.5 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 Possibility subdivision in lots 1 1 1 0.5 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 Territorial effectiveness 2 2 2 1 0.7 0.7 0.7 0.7 0.5 0.5 0.5 0.5 Project effectiveness 3 3 3 2 1 1 1 1 0.8 0.8 0.8 0.8 Water resource use 3 3 3 3 1 1 1 1 0.8 0.8 0.8 0.8 Project objectives 3 3 3 4 1 1 1 1 0.8 0.8 0.8 0.8 Basin users 3 3 3 5 1 1 1 1 0.8 0.8 0.8 0.8 District priority 4 4 4 6 1.3 1.3 1.3 1.3 1 1 1 1 Site sensitivity - seismicity 4 4 4 7 1.3 1.3 1.3 1.3 1 1 1 1 Project type 4 4 4 8 1.3 1.3 1.3 1.3 1 1 1 1 Project stage 4 4 4 9 1.3 1.3 1.3 1.3 1 1 1 1 116 Bio-based and Applied Economics 10(2): 109-122, 2021 | e-ISSN 2280-6172 | DOI: 10.36253/bae-9545 Raffaella Zucaro et al. Among the financed projects, 2 of them concerned the increase in storage capacity to improve the availabil- ity of water for agriculture; the remaining projects con- cerned improving the efficiency of the main irrigation supply networks in order to achieve better efficiency in water use and water saving in agriculture. Under the same Plan, other projects were selected by the Ministry of Infrastructure using the same methodol- ogy for a total of 30 projects for about 250 million euros. Table 3. Attributes and their scores. Row max normalization refers to normalization carried out before sensitivity analysis. Criterion Attribute Row max normalizationID Name Name Score 1 Water resource use Irrigation and household 3 1.00 Household 2 0.67 Irrigation 1 0.33 2.1 Site sensitivity - seismicity Seismic zone 1 4 1.00 Seismic zone 2 3 0.75 Seismic zone 3 2 0.50 Seismic zone 4 1 0.25 2.2 Site sensitivity - hydrogeological instability Yes 1 1.00 No 0 0.00 3 Project objectives Completing of existing dams or unfinished dams 3 1.00 Recovery or extension of the reservoir’ capacity 2 0.70 Improvement of the derivation’ efficiency 1 0.30 4 Catchment area EI > 500.000 3 1.00 300.000 ≤ EI ≤ 500.000 2 0.70 EI < 300.000 1 0.30 5 Co-financing Yes 1 1.00 No 0 0.00 6 Project type Securing 4 1.00 Extraordinary maintenance 3 0.75 Completion 2 0.50 New intervention 1 0.25 7 Possibility of subdivision in lots Yes 1 1.00 No 0 0.00 8 Project stage Executive project 4 1.00 Final authorizing project 3 0.75 Definitive technical project 2 0.50 Feasibility project 0 0.25 9 Project effectiveness < 25€/EI 3 1.00 >=25 €/EI <50 €/EI 2 0.70 >=50€/EI 1 0.30 10 Territorial effectiveness > 40% very sensitive danger (Basilicata, Marche, Molise, Puglia, Sicily, and Sardinia) 2 1.00 > 40% moderately sensitive danger (Abruzzo, Campania, Emilia- Romagna, Lazio, Piedmont, Tuscany, Umbria, and Veneto) 1 0.50 little sensitive (other Regions) 0 0.00 11 District priority Strategic 4 1.00 Relevant 3 0.75 Important 2 0.50 Required 1 0.25 117Application of Multi-Criteria Analysis selecting the most effective Climate change adaptation measures and investments in the Italian context Bio-based and Applied Economics 10(2): 109-122, 2021 | e-ISSN 2280-6172 | DOI: 10.36253/bae-9545 3.6 Sensitivity analysis Two other assumptions of weight allocation to the criteria were tested to apply sensitivity analyses within this study. Both were designed to follow the aims and rules of the Fund, but by making changes in the order of criteria However, the new assignations were made with- out a profound distortion of the priorities expressed by the Technical Committee. In these new assignations, the correlation between the priorities expressed in the relevant law and the crite- ria that best represented them was considered. The decision of the Technical Committee was amended to stress the weight of the criteria in two ways. Firstly, the importance was increased for criteria provid- ing for the effects on the environment and community (e.g. number of people involved, mitigation of deserti- fication, District priority, etc.), and the importance was decreased for criteria providing for the feasibility prop- erties of the project (such as cost-efficiency ratio, possi- bility subdivision in lots, etc.) (R2). Then, the opposite point of view was applied (R3). In R2, the most important criteria were established to be the District priority, the basin users, the seismicity of the site, the territorial effectiveness, and the project stage (weight 4), followed by the project objectives and project type (weight 3). They all described some aspect of the effect of the intervention, except for the project stage. The latter criterion had no effect on the final rank- ing of alternatives, but it could not be deleted or modi- fied, as explained above (see paragraph 3.3). The lower Table 4. List of scores awarded to selected projects for each criterion: evaluation matrix. Project Criteria su m m ar y In di ca to r Po si tio n W at er r es ou rc e us e Pr oj ec t ob je ct iv es C at ch m en t a re a C o- fin an ci ng Pr oj ec t t yp e. Po ss ib ili ty su bd iv is io n in lo ts Pr oj ec t s ta ge Pr oj ec t eff ec tiv en es s Si te s en si tiv ity - se is m ic ity Si te s en si tiv ity - hy dr og eo lo gi ca l in st ab ili ty Te rr ito ri al eff ec tiv en es s D is tr ic t p ri or ity 1 3 1 3 0 4 1 4 3 2 1 1 3 26 2 3 2 1 0 4 1 4 3 1 1 1 3 24 3 3 2 1 0 4 0 4 3 1 1 1 3 23 4 1 1 3 0 3 1 4 3 1 0 2 4 23 5 1 1 3 0 3 1 4 3 1 0 2 4 23 6 3 1 1 0 3 1 4 1 3 1 1 4 23 7 1 1 3 0 3 1 4 3 2 0 1 3 22 8 3 1 3 0 3 1 4 3 1 0 0 3 22 9 1 1 1 0 4 0 4 3 3 0 1 4 22 10 1 1 1 0 3 1 4 1 3 1 2 4 22 Figure 1. Maps of the Italian LAWMs. The blue polygons indicate the LAWMs that had their projects funded under the Extraordinary Plans from Mipaaf (author’s extrapolation of SIGRIAN data). 118 Bio-based and Applied Economics 10(2): 109-122, 2021 | e-ISSN 2280-6172 | DOI: 10.36253/bae-9545 Raffaella Zucaro et al. weights were for project properties, such as co-financing, the possibility of subdivision in lots (weight 0.5), water resource use (weight 1), project effectiveness, project type, and hydrogeological instability of the site (weight 2). The Technical Committee associated with the latter criterion the same weight as class 4 in seismic risk. In this way, seismic risk was emphasized more than hydro- geological risk, compared to the priorities expressed by the legislation, where priority was given to interventions in seismic area 1 or 2 and those affected by hydrogeolog- ical risk. In R2, the same trend was maintained but the presence of hydrogeological instability was associated with the same weight as the seismic risk class 3, shorten- ing the distances between the two criteria. On the contrary, in R3, the most important criteria were established as project effectiveness, project type, and project stage (weight 4), followed by water resource use, and the criteria on the effects (project objectives, basin users, site seismicity, District priority) (weight 3). The burden of co-financing and of the possibility of sub- division in lots were increased to 2. The lowest weights were placed on hydrogeological instability of the site and territorial effectiveness (weight 1). Table 5 and Figure 2 summarize the weights adopt- ed in the two tests in relation to those chosen by the Technical Committee (R1). New summary indicators resulting for each alterna- tive were obtained by multiplying the tested weights of the criteria by the normalized attributes score (see table 4). Then, as result of the aggregation with the scoring method, the alternatives were sorted according to R2 and R3. Table 6 shows the comparison of these alterna- tive rankings for the first 10 projects. In both of the cases examined, two of the projects selected by the Techni- cal Committee were not included in the top 10 ranking. Nevertheless, the comparison of the results for all 55 cas- es, by Spearman test (fig. 3), showed that there was a sig- nificant and strong correlation between the ranking per- formed based on R2 and R3 and the ranking performed on the basis of the assignment of the original weights (R1) (respectively 0.920 and 0.940, p-level<0,001, n=55). The results still showed a significant correlation when the Spearman test was calculated only on the top ten posi- tions (respectively 0.641 and 0.681, p-level<0,05, n=10). 3.7 Discussions Looking at the adopted approach, the involvement of all stakeholders was a strength in the methodology. Firstly, it ensured competence in all the involved dis- ciplinary areas. In particular, the involvement of the RBDAs was very important as they are key players in water management and protection. Secondly, it ensured a high level of objectivity in the definition of criteria and weights. Indeed, the multidisciplinary Technical Committee allowed for setting criteria, attributes, and scores, including the objectives and constraints imposed by the financial instrument, and shared weight distribu- tion between decision-makers was achieved. Finally, this approach facilitated the acceptance of results obtained by the stakeholders embodied by the Regions. The absence of traditional normalization and the assignment of a predefined score to attributes represented Table 5. Weights of the criteria according to the two tests (*criteria mostly linked to the definitions given in the reference law), compared to those assigned by the Technical Committee. Main semantic area Criteria R1 Weight in tested hypothesis R2 R3 Project properties *Water resource use 3 2 3 Project properties Co-financing 1 0.5 2 Project properties Possibility subdivision in lots 1 0.5 2 Project properties *Project stage 4 4 4 Project properties Project effectiveness 3 2 4 Project properties / effects Project type 4 3 4 Effects / Project properties *Project objectives 3 3 3 Effects *Basin users 3 4 3 Effects *Site sensitivity - seismicity 4 4 3 Effects *Site sensitivity - hydrogeological instability 1 2 1 Effects Territorial effectiveness 2 4 1 Effects *District priority 4 4 3 Total weight 33 33 33 119Application of Multi-Criteria Analysis selecting the most effective Climate change adaptation measures and investments in the Italian context Bio-based and Applied Economics 10(2): 109-122, 2021 | e-ISSN 2280-6172 | DOI: 10.36253/bae-9545 a practical advantage: the method was easy for all parties involved to understand, making them even more confi- dent in the results of the application. This was important for the self-assessment that stakeholders had to carry out when submitting their project, and for the RBDAs, which had to express their priority mainly based on the infor- mation included in the self-assessment. In addition, two elements could make the methodol- ogy suitable for financing projects by means of a call for proposals. The first one consists of the direct assignment of the score to the attributes to facilitate the self-assess- ment. The second is the production of a definitive rank- ing of the proposals, without comparison with other test rankings, coming from sensitivity analysis (e.g. Skoniec- zny et al. 2005). In fact, sensitivity analysis is not suit- able for funding guided by calls for proposals, because in these cases the scores of the attributes and/or weights of the criteria must necessarily be unequivocal, defined, and published a priori. However, sensitivity analysis was applied to this study to verify the stability of the results when the weights of the criteria were changed. The results showed a good correlation between the ranking made on the two test hypotheses and that applied by the Technical Com- mittee. The differences between the rankings were not significant. However, the small variations imposed on the weights of the test criteria during sensitivity analy- sis are worth noting. Surely this choice influenced the results of the sensitivity analysis, overestimating the quality of the results. On the other hand, if there were a profound variation in weight assignations, this would have resulted in choices that overturned the very strict and detailed rules and priorities of the Fund. Overall, the study seemed to confirm that the allo- cation of the weights through a technical committee and the involvement of stakeholders achieved adequate solid- ity of the results. The analysis of the results also suggests that this solidity is higher when the regulation behind 0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 *D es ign le ve l Pr oje ct typ e Pr oje ct eff ec tiv en es s *W at er re so ur ce s u se Co -fin an cin g Po ssi bil ity of lo ts *P ro jec t o bje cti ve s *B as in us er s *S ite Se ism ici ty *S ite hy dr og eo log ica l… Te rri to ria l e ffe cti ve ne ss *D ist ric t p rio ri t y W EI G H T O F CR IT ER IO N R1 R2 R3 Figure 2. Graphic representation of the different weights of the criteria between the two tests and the assignment of the Technical Commit- tee (*criteria mostly linked to the definitions reported in the reference law). Table 6. The first 10 alternatives sorted by the summary indicator, obtained for R1 (the choices of the Technical Committee), R2, and R3 (the letters of the alphabet symbolize the alternatives, i.e. the projects). Ranking of the alternatives (first 10 positions) by R1 adoption (technical committee) by R2 adoption by R3 adoption A A A B D B C E H D L D E B E F F C G C G H Q F I G N L R O 120 Bio-based and Applied Economics 10(2): 109-122, 2021 | e-ISSN 2280-6172 | DOI: 10.36253/bae-9545 Raffaella Zucaro et al. the selection gives precise and detailed rules. This should reduce the discretion exercised by the Technical Com- mittee. 4. MAIN CONCLUSIONS Public infrastructure investments in water distribu- tion networks are part of a broader framework of pos- sible interventions (regulatory, risk management, invest- ments, etc.) to cope with and adapt to climate change. Recently, the European Green Deal Strategy also highlighted how climate change will continue to create significant stress in Europe despite mitigation efforts. Hence, the consideration of climate adaptation in public and private investments is an essential topic. The MCA method proved to be a very useful tool for choosing between different investment alternatives. When it is well-designed, it allows for the inclusion of different quantitative and qualitative criteria that can be measured in a single evaluation process. This has also made it possible to weight these criteria according to the priorities assigned by decision makers. However, the MCA procedure is articulated and complex, due to the need to develop an approach that represents the multiplicity of objectives. There is a risk that the results achieved will be strongly influenced by subjective choices made at some of the various stag- es. This can be a critical point. That is why sensitivity analysis should be applied. However, in some cases like those presented, a profound change in weight allocation for testing robustness is limited by the need to respect the priorities and constraints imposed by the related regulation. That is why decision maker and stakeholder involvement are even more necessary to achieve realistic and acceptable results. During t he applicat ion of t he met hodolog y described, certain strengths and weaknesses came to light. One of the main strengths was the participatory approach used to identify the decision-making network (Ministries and RBDAs) and stakeholders (Regions and LAWMs). The main weakness lies in the fact that the weights adopted can only be controlled ex-post, shifting the variation to weights to compare the results obtained. The methodology applied has the advantage of being applicable in the future also in the case of funding based on calls for proposals, for which the scores of the attrib- utes and/or the weights of the criteria must be defined and published a priori. The ex-post sensitivity analysis, carried out by modifying the weights with due regard for the priorities and limitations of the Fund, confirmed the solidity of the classification on the total number of cases. This solidity seems to be favoured precisely by the presence of accurate rules and priorities of the fund, which reduce the margin of discretion entrusted to the technical committee. MCA is a useful informative support for policy deci- sions, but it is important to keep in mind that it is not an “automatic” method for land management. ACKNOWLEDGEMENT The authors would like to thank Luca Adolfo Folino and Adriano Battilani for their help and cooperation in revising the English. 8 10 12 14 16 18 20 22 24 26 28 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 su m m ar y in di ca to r ALTERNATIVE ORDINATION BY TECHNICAL COMMITTEE R1 R 2 R 3 Figure 3. 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In: European Water 60: 313- 318 (ISSN 1105-7580) https://sigrian.crea.gov.it http://dania.crea.gov.it/ Volume 10, Issue 2 - 2021 Firenze University Press Mediterranean agriculture facing climate change: Challenges and policies Filippo Arfini The long-term fortunes of territories as a route for agri-food policies: evidence from Geographical Indications Cristina Vaquero-Piñeiro Application of Multi-Criteria Analysis selecting the most effective Climate change adaptation measures and investments in the Italian context Raffaella Zucaro, Veronica Manganiello, Romina Lorenzetti*, Marianna Ferrigno Climate changes and new productive dynamics in the global wine sector Emilia Lamonaca*, Fabio Gaetano Santeramo, Antonio Seccia A systematic review of attributes used in choice experiments for agri-environmental contracts Nidhi Raina*, Matteo Zavalloni, Stefano Targetti, Riccardo D’Alberto, Meri Raggi, Davide Viaggi The effect of farmer attitudes on openness to land transactions: evidence for Ireland Cathal Geoghegan*, Anne Kinsella, Cathal O’Donoghue