Modal contribution and state space order selection in operational modal analysis

The estimation of modal parameters of a structure from ambient measurements has attracted the attention of many researchers in the last years. The procedure is now well established and the use of state space models, stochastic system identification methods and stabilization diagrams allows to identify the modes of the structure. In this paper the contribution of each identified mode to the measured vibration is discussed. This modal contribution is computed using the Kalman filter and it is an indicator of the importance of the modes. Also the variation of the modal contribution with the order of the model is studied. This analysis suggests selecting the order for the state space model as the order that includes the modes with higher contribution. The order obtained using this method is compared to those obtained using other well known methods, like Akaike criteria for time series or the singular values of the weighted projection matrix in the Stochastic Subspace Identification method. Finally, both simulated and measured vibration data are used to show the practicability of the derived technique. Finally, it is important to remark that the method can be used with any identification method working in the state space model.

Indicators of sustainability of agriculture and livestock in Spain - Indicadores de sostenibilidad de la agricultura y ganadería española

Sustainability is an adjective used to characterize agriculture according to the degree of fulfillment of goals. Those goals are related to agro-ecological, environmental and socio-economic dimensions. Sustainability is a dynamic and temporal character. In absolute terms there is not an ending value because it changes as its dimensions make it. Spain is one of the main agricultural countries of the European Union both in terms of crop land and value of productions. The object of this study is to present a methodology of sustainability account to be incorporated into national statistical and to assess their performance in the course of the years. For that reason the data sources used have been the statistics of the Department of Agriculture and from others database. We presented a set of indicators of sustainability and its evaluation in a time series of at least 30 years. The trend analysis offers the evolution of the numerical values of the indicators in terms of efficiency, physical units used for a unit of product or its value in euros. The analyzed crops have been: wheat, barley, maize, sunflower, sugar beet, wine grape, olive oil, citrus, melon and tomato. Physical indicators were: land, water, energy, erosion, soil organic matter, and carbon balance; socio-economic indicators were: agricultural final production, prices, income, employment and use of fertilizers. In general, all crops increased their productive efficiency, higher in irrigated than on dry land. Spanish agricultural carbon sequestration capacity has multiplied by five in the last seventy years, as a result of the increase in the productivity of crops, in terms of total biomass and the modification of the soil management techniques. Livestock sector presents data of pork, broilers and laying hen. Those showed an improvement in efficiency and economic indicators. Overall we can say that Spanish agriculture and livestock subsector have a tendency towards sustainability, being its main threats extreme meteorological factors and the instability of todays markets.

Analyzing climate change adaptation in the agriculture and water sectors: screening risks and opportunities.

As part of the Mediterranean area, the Guadiana basin in Spain is particularly exposed to increasing water stress due to climate change. Future warmer and drier climate will have negative implications for the sustainability of water resources and irrigation agriculture, the main socio- economic sector in the region. This paper illustrates a systematic analysis of climate change impacts and adaptation in the Guadiana basin based on a two-stage modeling approach. First, an integrated hydro-economic modeling framework was used to simulate the potential effects of regional climate change scenarios for the period 2000-2069. Second, a participatory multi-criteria technique, namely the Analytic Hierarchy Process (AHP), was applied to rank potential adaptation measures based on agreed criteria. Results show that, in the middle-long run and under severe climate change, reduced water availability, lower crop yields and increased irrigation demands might lead to water shortages, crop failure, and up to ten percent of income losses to irrigators. AHP results show how private farming adaptation measures, including improving irrigation efficiency and adjusting crop varieties, are preferred to public adaptation measures, such as building new dams. The integrated quantitative and qualitative methodology used in this research can be considered a socially-based valuable tool to support adaptation decision-making.

Probabilistic analysis of water availability for agriculture and associated crop net margins.

Rising water demands are difficult to meet in many regions of the world. In consequence, under meteorological adverse conditions, big economic losses in agriculture can take place. This paper aims to analyze the variability of water shortage in an irrigation district and the effect on farmer?s income. A probabilistic analysis of water availability for agriculture in the irrigation district is performed, through a supply-system simulation approach, considering stochastically generated series of stream-flows. Net margins associated to crop production are as well estimated depending on final water allocations. Net margins are calculated considering either single-crop farming, either a polyculture system. In a polyculture system, crop distribution and water redistribution are calculated through an optimization approach using the General Algebraic Modeling System (GAMS) for several scenarios of irrigation water availability. Expected net margins are obtained by crop and for the optimal crop and water distribution. The maximum expected margins are obtained for the optimal crop combination, followed by the alfalfa monoculture, maize, rice, wheat and finally barley. Water is distributed as follows, from biggest to smallest allocation: rice, alfalfa, maize, wheat and barley.

Climate Change, Water Scarcity in Agriculture and The Country-Level Economic Impacts. A Multimarket Analysis

Climate Change, Water Scarcity in Agriculture and the Country-Level Economic Impacts. A Multimarket Analysis. Abstract: Agriculture could be one of the most vulnerable economic sectors to the impacts of climate change in the coming decades. Considering the critical role that water plays for agricultural production, any shock in water availability will have great implications for agricultural production, land allocation, and agricultural prices. In this paper, an Agricultural Multimarket model is developed to analyze climate change impacts in developing countries, accounting for the uncertainty associated with the impacts of climate change. The model has a structure flexible enough to represent local conditions, resource availability, and market conditions. The results suggest different economic consequences of climate change depending on the specific activity, with many distributional effects across regions

Water, agriculture and ecosystem services in climate change vulnerable agricultural regions of Spain and Jordan

Irrigated agricultural landscapes generate a valuable set of ecosystem services, which are threatened by water scarcity in many aridand semi‐arid regions of the world. In the Mediterranean region, climate change is expected to decrease water availability through reduced precipitation and more frequent drought spells. At the same time, climate change, demographic and economic development and an agricultural sector highly dependent on irrigation, will raise water demand, increasing experienced water scarcity and affecting the provision of ecosystem services from water resources and agro-ecosystems. In this context, policy makers face the challenge of balancing the provision of different ecosystem services, including agricultural income and production and also water ecosystem protection.

Assessment of species diversity and state of "Stipa tenacissima" steppes

North African steppes are subjected to extreme degradation resulting in the reduction of their surface, genetic erosion of resources, and decrease in biodiversity. "Stipa tenacissima" steppes, which constitute one of the most representative vegetation types in the driest areas of the Mediterranean basin, are continuously degrading. With the aim of contributing to a better knowledge of the floristic composition and diagnosing the state of degradation of these steppes, we conducted a phytoecological analysis of 10 "S. tenacissima" sites in Tunisia. Floristic inventory compiled a systematic list of 46 vascular plant species belonging to 43 genera and 26 families. Species richness ranged from 4 to 18 species per 900 m2. Total vegetation cover was moderate and fluctuated between 22.8% and 49.9%. Our results revealed also a decreasing trend in species richness with increasing elevation (ρ = –0.585). Indeed, species richness was negatively correlated with slope (ρ = –0.19) and positively correlated with sand content (ρ = 0.262). Biological types were dominated by chamaephytes; this chamaephytization is due to the phenomenon of aridization and overgrazing. Moreover, the low species cover and the appearance of nonpalatable species highlighted the vulnerability of these steppes to degradation.

Effect of nano-Si2O and nano-Al2O3 on cement mortars for use in agriculture and livestock production

The effect of nano-silica, nano-alumina and binary combinations on surface hardness, resistance to abrasion and freeze-thaw cycle resistance in cement mortars was investigated. The Vickers hardness, the Los Angeles coefficient (LA) and the loss of mass in each of the freeze–thaw cycles to which the samples were subjected were measured. Four cement mortars CEM I 52.5R were prepared, one as control, and the other three with the additions: 5% nano-Si, 5% nano-Al and mix 2.5% n-Si and 2.5% n-Al. Mortars were tested at 7, 28 and 90 d of curing to determine compression strength, total porosity and pore distribution by mercury intrusion porosimetry (MIP) and the relationship between the CSH gel and Portlandite total by thermal gravimetric analysis (TGA). The capillary suction coefficient and an analysis by a scanning electron microscope (SEM) was made. There was a large increase in Vickers surface hardness for 5% n-Si mortar and a slight increase in resistance to abrasion. No significant difference was found between the mortars with nano-particles, whose LA was about 10.8, classifying them as materials with good resistance to abrasion. The microstructure shows that the addition of n-Si in mortars refines their porous matrix, increases the amount of hydrated gels and generates significant changes in both Portlandite and Ettringite. This produced a significant improvement in freeze–thaw cycle resistance. The effect of n-Al on mortar was null or negative with respect to freeze–thaw cycle resistance.

Drivers in adopting adaptation strategies to face increased water scarcity in agriculture. A case study in Doñana (Spain) and Makueni (Kenya)

La agricultura es uno de los sectores más afectados por el cambio climático. A pesar de haber demostrado a lo largo de la historia una gran capacidad para adaptarse a nuevas situaciones, hoy en día la agricultura se enfrenta a nuevos retos tales como satisfacer un elevado crecimiento en la demanda de alimentos, desarrollar una agricultura sostenible con el medio ambiente y reducir las emisiones de gases de efecto invernadero. El potencial de adaptación debe ser definido en un contexto que incluya el comportamiento humano, ya que éste juega un papel decisivo en la implementación final de las medidas. Por este motivo, y para desarrollar correctamente políticas que busquen influir en el comportamiento de los agricultores para fomentar la adaptación a estas nuevas condiciones, es necesario entender previamente los procesos de toma de decisiones a nivel individual o de explotación, así como los efectos de los factores que determinan las barreras o motivaciones de la implementación de medidas. Esta Tesis doctoral trata de profundizar en el análisis de factores que influyen en la toma de decisiones de los agricultores para adoptar estrategias de adaptación al cambio climático. Este trabajo revisa la literatura actual y desarrolla un marco metodológico a nivel local y regional. Dos casos de estudio a nivel local (Doñana, España y Makueni, Kenia) han sido llevados a cabo con el fin de explorar el comportamiento de los agricultores hacia la adaptación. Estos casos de estudio representan regiones con notables diferencias en climatología, impactos del cambio climático, barreras para la adaptación y niveles de desarrollo e influencia de las instituciones públicas y privadas en la agricultura. Mientras el caso de estudio de Doñana representa un ejemplo de problemas asociados al uso y escasez del agua donde se espera que se agraven en el futuro, el caso de estudio de Makueni ejemplifica una zona fuertemente amenazada por las predicciones de cambio climático, donde adicionalmente la falta de infraestructura y la tecnología juegan un papel crucial para la implementación de la adaptación. El caso de estudio a nivel regional trata de generalizar en África el comportamiento de los agricultores sobre la implementación de medidas. El marco metodológico que se ha seguido en este trabajo abarca una amplia gama de enfoques y métodos para la recolección y análisis de datos. Los métodos utilizados para la toma de datos incluyen la implementación de encuestas, entrevistas, talleres con grupos de interés, grupos focales de discusión, revisión de estudios previos y bases de datos públicas. Los métodos analíticos incluyen métodos estadísticos, análisis multi‐criterio para la toma de decisiones, modelos de optimización de uso del suelo y un índice compuesto calculado a través de indicadores. Los métodos estadísticos se han utilizado con el fin de evaluar la influencia de los factores socio‐económicos y psicológicos sobre la adopción de medidas de adaptación. Dentro de estos métodos se incluyen regresiones logísticas, análisis de componentes principales y modelos de ecuaciones estructurales. Mientras que el análisis multi‐criterio se ha utilizado con el fin de evaluar las opciones de adaptación de acuerdo a las opiniones de las diferentes partes interesadas, el modelo de optimización ha tenido como fin analizar la combinación óptima de medidas de adaptación. El índice compuesto se ha utilizado para evaluar a nivel regional la implementación de medidas de adaptación en África. En general, los resultados del estudio ponen de relieve la gran importancia de considerar diferentes escalas espaciales a la hora de evaluar la implementación de medidas de adaptación al cambio climático. El comportamiento de los agricultores es diferente entre lugares considerados a una escala local relativamente pequeña, por lo que la generalización de los patrones del comportamiento a escalas regionales o globales resulta relativamente compleja. Los resultados obtenidos han permitido identificar factores determinantes tanto socioeconómicos como psicológicos y calcular su efecto sobre la adopción de medidas de adaptación. Además han proporcionado una mejor comprensión del distinto papel que desempeñan los cinco tipos de capital (natural, físico, financiero, social y humano) en la implementación de estrategias de adaptación. Con este trabajo se proporciona información de gran interés en los procesos de desarrollo de políticas destinadas a mejorar el apoyo de la sociedad a tomar medidas contra el cambio climático. Por último, en el análisis a nivel regional se desarrolla un índice compuesto que muestra la probabilidad de adoptar medidas de adaptación en las regiones de África y se analizan las causas que determinan dicha probabilidad de adopción de medidas. ABSTRACT Agriculture is and will continue to be one of the sectors most affected by climate change. Despite having demonstrated throughout history a great ability to adapt, agriculture today faces new challenges such as meeting growing food demands, developing sustainable agriculture and reducing greenhouse gas emissions. Adaptation policies planned on global, regional or local scales are ultimately implemented in decision‐making processes at the farm or individual level so adaptation potentials have to be set within the context of individual behaviour and regional institutions. Policy instruments can play a formative role in the adoption of such policies by addressing incentives/disincentives that influence farmer’s behaviour. Hence understanding farm‐level decision‐making processes and the influence of determinants of adoption is crucial when designing policies aimed at fostering adoption. This thesis seeks to analyse the factors that influence decision‐making by farmers in relation to the uptake of adaptation options. This work reviews the current knowledge and develops a methodological framework at local and regional level. Whilst the case studies at the local level are conducted with the purpose of exploring farmer’s behaviour towards adaptation the case study at the regional level attempts to up‐scale and generalise theory on adoption of farmlevel adaptation options. The two case studies at the local level (Doñana, Spain and Makueni, Kenya) encompass areas with different; climates, impacts of climate change, adaptation constraints and limits, levels of development, institutional support for agriculture and influence from public and private institutions. Whilst the Doñana Case Study represents an area plagued with water‐usage issues, set to be aggravated further by climate change, Makueni Case study exemplifies an area decidedly threatened by climate change where a lack of infrastructure and technology plays a crucial role in the uptake of adaptation options. The proposed framework is based on a wide range of approaches for collecting and analysing data. The approaches used for data collection include the implementation of surveys, interviews, stakeholder workshops, focus group discussions, a review of previous case studies, and public databases. The analytical methods include statistical approaches, multi criteria analysis for decision‐making, land use optimisation models, and a composite index based on public databases. Statistical approaches are used to assess the influence of socio‐economic and psychological factors on the adoption or support for adaptation measures. The statistical approaches used are logistic regressions, principal component analysis and structural equation modelling. Whilst a multi criteria analysis approach is used to evaluate adaptation options according to the different perspectives of stakeholders, the optimisation model analyses the optimal combination of adaptation options. The composite index is developed to assess adoption of adaptation measures in Africa. Overall, the results of the study highlight the importance of considering various scales when assessing adoption of adaptation measures to climate change. As farmer’s behaviour varies at a local scale there is elevated complexity when generalising behavioural patterns for farmers at regional or global scales. The results identify and estimate the effect of most relevant socioeconomic and psychological factors that influence adoption of adaptation measures to climate change. They also provide a better understanding of the role of the five types of capital (natural, physical, financial, social, and human) on the uptake of farm‐level adaptation options. These assessments of determinants help to explain adoption of climate change measures and provide helpful information in order to design polices aimed at enhancing societal support for adaptation policies. Finally the analysis at the regional level develops a composite index which suggests the likelihood of the regions in Africa to adopt farm‐level adaptation measures and analyses the main causes of this likelihood of adoption.