The vulnerability of regional agriculture regarding irrigation water from the Tagus-Segura transfer

Input–output tables provide a useful tool for analysing economic and environmental impacts, which has led to their extension beyond the national level to the regional level. The availability of the intermediate demand matrix allows for the extraction of income multipliers and employment multipliers to assess the environmental impacts of different economic activities. This can intuitively be expected to play an important role in economic growth and employment in many regions, and to allow for more precise policy decision-making and application in sustainable development strategies. Despite the relevance of these input-output tables at regional level, there is an almost total absence of official data in most countries. This has led to the development of regionalisation methodologies, among which are those based on the application of location quotients. In these methods, corrections are applied to the obtained variables that depend on the value given to certain unknown parameters. This paper use a proposal of a simple and efficient procedure for estimating these parameters from generally available information on road freight transport and goods imports from the rest of the world. Applying them to estimate the input-output matrix of the Region of Murcia (Spain) made it possible to measure the economic impact of the Tagus-Segura transfer and to assess the impact of a reduction in the volume of transferable water. A hybrid approach was applied to obtain the Bi-Regional Input-Output matrix, which combines pure non-survey methods with matrix-balancing methods. This study quantifies the total contribution (direct, indirect and induced) of the agricultural branches associated with the irrigation water of the Tagus-Segura transfer to the economic output of the Region of Murcia. In addition, it estimates that a 50 % reduction of the current transferable volume of water would reduce regional output, Gross Value Added and regional employment by 1.6 %, 1.5 % and 3.8 %, respectively.