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Linker R.,Technion - Israel Institute of Technology | Ioslovich I.,Technion - Israel Institute of Technology | Sylaios G.,Democritus University of Thrace | Plauborg F.,University of Aarhus | Battilani A.,Consorzio di Bonifica di Secondo Grado per Il Canale Emiliano Romagnolo CER
Agricultural Water Management | Year: 2016

Water shortage is the main limiting factor for agricultural productivity in many countries and improving water use efficiency in agriculture has been the focus of numerous studies. The usual approach to limit water consumption in agriculture is to apply water quotas and in such a situation farmers should use an irrigation schedule that maximizes the yield and abides to the quota constraints. In contrast to the widespread use of irrigation scheduling based on agronomy practices, irrigation scheduling may be considered as a constrained optimization problem. When drip irrigation is used, the decision variables are the irrigation amounts for each day of the season. The objective function is the expected yield calculated with the use of a model. In the present work we solved this optimization problem for three crops modeled by the model AquaCrop. This optimization problem is non-trivial due to the non-smooth behavior of the objective function and the fact that it involves multiple integer variables. We developed an optimization scheme for generating sub-optimal irrigation schedules that take implicitly into account the response of the crop to water stress, and used these as initial guesses for a full optimization of daily irrigation. Performing this optimization with various values of water quotas produced the function that expresses the relationship between water quota and yield. © 2015 Elsevier B.V.. Source

Munaretto S.,VU University Amsterdam | Battilani A.,Consorzio di Bonifica di Secondo Grado per Il Canale Emiliano Romagnolo CER
Water Policy | Year: 2014

Irrigation is an essential element of agricultural production whose absence would create great economic hardship in many regions of the global South. Yet irrigated agriculture uses 70% of global fresh water withdrawals, putting major pressure on global water resources. Whilst much research has focused on technological solutions to improve irrigation efficiency, irrigation water governance arrangements remain poorly investigated. This paper examines the irrigation water governance arrangements in place in the Canale Emiliano Romagnolo (CER) district in Italy. The objective is to understand key factors driving or hindering irrigation efficiency, and to identify context-relevant policy-making dynamics that could enable greater efficiency. The analysis is conducted following the Policy Arrangement Approach, which describes a policy domain in terms of actors, rules, resources and discourses, and identifies opportunities for change in the interplay of these dimensions. Findings suggest that the existing governance arrangements have led to improvements in irrigation efficiency over the past decades in the CER district. Key factors of this performance include public financial investment in research and farm modernization, the existence of local capacity building and social capital, and the presence of a public-private organization with capacity to raise resources and to generate and transfer knowledge to both policy-makers and farmers. © 2014 IWA Publishing. Source

Battilani A.,Consorzio di Bonifica di Secondo Grado per Il Canale Emiliano Romagnolo CER | Steiner M.,Eawag - Swiss Federal Institute of Aquatic Science and Technology | Andersen M.,Grundfos A S | Back S.N.,Grundfos A S | And 8 more authors.
Agricultural Water Management | Year: 2010

The EU project SAFIR aimed to help farmers solve problems related to the use of low quality water for irrigation in a context of increasing scarcity of conventional freshwater resources. New decentralised water treatment devices (prototypes) were developed to allow a safe direct or indirect reuse of wastewater produced by small communities/industries or the use of polluted surface water. Water treatment technologies were coupled with irrigation strategies and technologies to obtain a flexible, easy to use, integrated management of the system. The challenge is to apply new strategies and technologies which allow using the lowest irrigation water quality without harming food safety or yield and fruit or derivatives quality. This study presents the results of prototype testing of a small-scale compact pressurized membrane bioreactor and of a modular field treatment system including commercial gravel filters and heavy-metal specific adsorption materials. Decentralised compact pressurised membrane biobooster (MBR), was able to remove up to 99.99% of the inlet Escherichia coli and 98.52% of total coliforms. E. coli was completely removed from irrigation water in 53% of the samples by the last MBR prototype version. In 2008, 100% of samples fulfilled WHO standards (1989) and Global Gap requirement for faecal contamination. MBR removed from inlet flow in the average 82% of arsenic, 82% of cadmium, 97% of chromium, 93% of copper and 99% of lead. Boron and manganese were not removed from permeate. The field treatment system (FTS) proved to be effective against faecal contamination when applied with its complete set up including UV treatment. The sole gravel filter and heavy metal removal device (HMR) cannot provide sufficient and steadily treatment for microbial contamination. Nevertheless, gravel filter can remove up to 60% of E. coli but the removal process was not stable nor predictable. FTS removed 76% of arsenic, 80% of cadmium and copper, 88% of chromium and lead, and up to 97% of zinc. Like the MBR, boron and manganese were not removed from the irrigation water. Gravel filter directly fed with secondary treated wastewater was found able to remove 41% of arsenic, 36% of cadmium and lead, 48% of chromium and 46% of copper. The residual heavy metals concentration after the gravel filter was further reduced by the HMR: 35% for arsenic, 22% for cadmium, 25% for chromium, 33% for copper and 53% for lead. © 2010 Elsevier B.V. Source

Afzal M.,UK Center for Ecology and Hydrology | Afzal M.,University of Reading | Battilani A.,Consorzio di Bonifica di Secondo Grado per Il Canale Emiliano Romagnolo CER | Solimando D.,Consorzio di Bonifica di Secondo Grado per Il Canale Emiliano Romagnolo CER | Ragab R.,UK Center for Ecology and Hydrology
Agricultural Water Management | Year: 2016

The aim of this study was to investigate the effects of two different irrigation strategies, regulated deficit irrigation, RDI and partial root drying, PRD using surface freshwater (SW) and brackish treated waste water (TWW) for maize and potato crops. The SALTMED model has been applied using the field measurements of two cropping seasons 2013 and 2014 at the Canale Emiliano Romagnolo, CER's experimental farm located in Mezzolara di Budrio (Bologna, Italy). In 2013, PRD irrigated potato received 17% less irrigation water than RDI but produced nearly the same yield as under RDI. The water productivity, on average, was 11% higher for PRD compared with RDI. For maize 2014 season, the PRD strategy received almost 15% less irrigation water, but produced a yield only 6% lower than that of RDI and gave equal water productivity to RDI. Given that the two strategies received the same amount of rainfall the results favour the PRD over RDI. Had the site not received above average rainfall (258 mm in 2013 and 259 mm during the 2014 growing seasons), PRD might have produced higher yield and water productivity than RDI.In terms of model simulations, overall, the model showed a strong relationship between the observed and the simulated soil moisture and salinity profiles, total dry mater and final yields. This illustrates SALTMED model's ability to simulate the dry matter and yield of C3 and C4 crops as well as to simulate different water qualities and different water application strategies. Therefore, the model can run with "what if" scenarios depicting several water qualities, crops and irrigation systems and strategies without the need to try them all in the field. This will reduce costs of labour and investment. © 2016 Elsevier B.V. Source

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