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Agriculture is one of the most vulnerable sectors to changes in climate patterns. Moreover, climate change is a complex and interdisciplinary problem, where natural processes are closely intertwined with socio-economic aspects, especially in areas where human activities are widespread. Thus, when planning for natural resources management, it becomes essential to consider how storylines, attitudes and behaviours can influence the decision-making towards adaptation measures. In particular, when considering an agricultural system, farmers are key agents that cannot be neglected, as the decision to adapt or to change their agricultural practice is ultimately in the hands of the individuals. Understanding the reasoning behind farmer adaptation can help create a sounder framework to recognize farmers’ awareness and experiences regarding climate change, while reinforcing their resilience to face climate change scenarios. Consequently, finding patterns in attitudes and similarities between farmers is essential both to better share an overall picture of climate change effects and perspectives in a specific study area and to summarize the complex set of factors influencing farmers’ behaviours to facilitate their modelling. Different tools and methods have been provided by the literature in the last two decades to delve into farmers’ attitudes and perspectives regarding climate change. One of the most used tools are structured surveys, mainly due to their strongly case-specific nature and the capacity to synthesize climate change scenarios in a standardized way. Here, we provide an overview of the results obtained through a survey of 460 farmers from northern Italy about climate change risk awareness, perceived impacts, and adaptive capacity. In addition to a descriptive statistical analysis to delve into farmers’ profiles and farming characteristics, this triple-loop approach was analysed through Multiple Correspondence Analysis (MCA), an interesting data analysis technique that allows to highlight underlying structures in categorical data used to recap farmers’ behaviours and define the association between dependent and independent variables. The resulting factor map allows for the identification of those variables that most explain the variance in the dataset and expected similarities and differences between respondents. The obtained results show how certain variables describing the agricultural practice of the respondents, such as farm extension or the preferred irrigation method, are key driving factors in differentiating and grouping individuals’ behaviour. In general, farmers with the same modus operandi share similar behaviour with respect to other aspects of their activity (e.g., water source). Interestingly, and contradicting similar experiences from the literature, this pattern differs among farmers with comparable demographic background, requiring more attention to farmers’ heuristics. These results can be useful in multiple ways: from creating an informative picture of farmers’ attitudes and concerns regarding climate change in a certain area, to its application in profiling farmers to identify common demands and shared worries; from helping with the creation of customized policies at the regional scale from a bottom-up approach, to the implementation of farmers’ profiles into Agent-Based Models to reinforce the human dimension in decision-making processes.

Agricultural systems are adversely influenced by climate change through increased temperatures, change in run-off patterns and seasonality fluctuation. Farmers are, hence, a valuable source of first-hand observations of climate change as they may provide a deeper understanding of their manifestation and relevance. Farmers are aware of climate change impacts and promote adaptation measures such as changing crop varieties, adjusting planting dates, introducing agroforestry practices, and promoting soil and water conservation practices. However, some adaptation barriers persist such as the limited knowledge of potential adaptation strategies, high adaptation cost, or poor institutional support. Understanding why and how farmers aim to adapt to climate change is imperative to provide informed decisions to policy-makers and the first step to minimizing misconceptions or maladaptation practices. Consequently, drivers and influencing factors of farmers’ behavior toward climate change have received increasing attention in the last two decades. Social and behavioral sciences have investigated the influence of farmers’ experiences in increasing climate change adaptation capability and improving decision-making processes at the system level, concluding how local perceptions provide sufficient baseline information for understanding individual and collective exposure to climate risks and risk aversion patterns, an essential element for effective policy formulation and implementation. Traditional management approaches based on simple, linear growth optimization strategies, overseen by command-and-control policies, have proven inadequate for effective adaptation to climate change. Conversely, accurate bottom-up approaches focused on social learning can complement the system transformation by building collaborative problem solving. In this line, associative processing methods, such as interviews and surveys, have been discussed for their ability to delve into knowledge-based data and monitor the nature, significance, and influence of personal experience on climate change adaptation. Agent-Based Models (ABM) can include feedback between social and physical environments, define individuals’ narratives, and map the social network with agents’ interactions. This proposal aims at presenting a transdisciplinary approach that integrates survey data, with behavior and agrohydrological modelling in order to support policy-makers and managers to understand and re-think water management and climate change policies at the regional scale, which is essential to address climate change risks. From a system dynamics perspective, we characterize farmers’ risk aversion patterns and examine how ABMs can most effectively integrate these insights to increase robustness in decision-making processes while attending to farmers’ adaptive capacity. In the application to the case study of a large irrigated area in northern Italy, we surveyed 460 farmers to deepen a triple loop analysis on climate change awareness, perceived impacts, and adaptation measures and barriers. Statistics and computer-assisted data analysis were applied to gain insights from farmers’ profiles and risk perception. We included the profiles in an ABM coupled with a distributed agrohydrological model that covers the whole irrigated area. We expect farmers’ profiles influence agents’ risk perception and their ultimate decision on the adopted crop types and irrigation methods. Provisional results indicate that the approach can provide new insights across complexity in modelling farmers’ behavior and human adaptation to climate change and enrich the discussion about the gaps and benefits of including qualitative data in ABM.

Over the last decades, several new observation systems have been developed, tested, and implemented in dedicated experimental sites by research groups in many countries all around the World. The data collected at these high-level test sites have boosted research and collaborations providing the basis for new hypothesis testing, better process understanding and model improvements. In contrast, national and more operational ground monitoring networks are still largely based on traditional instruments. Moreover, the different networks and the data are not always well integrated, even at the regional level. For these reasons, the capability to monitor the main components of the hydrological cycle over large areas is still limited and the observation systems to support the management of the water resources and for environmental protections can be improved. By using soil moisture and snow water equivalent monitoring as examples, in this contribution we present and discuss challenges, results and opportunities in upgrading national weather stations and improving the service provided by the public environmental agencies. Specifically, the difficulties of implementing ground monitoring networks are first discussed. The opportunities provided by the development of new non invasive sensors based on cosmic-ray neutrons detection are then presented. The activities and the results conducted during the last years to move this technology further from research to operation are shown. The current uptake from a number of Italian environmental agencies is reported. The key components and current challenges for a successful implementation are finally discussed.

Agriculture is the main source of pressure on water resources, so accurate estimates of irrigation demands play a key role in sustainable water management. The INCIPIT (INtegrated Computer modeling and monitoring for Irrigation Planning in Italy) project (funded by Italian Min. Univ. and Research) aims to address the gaps between research and practical application in monitoring irrigation water use in six Italian regions [1]. It is designed to meet the requirements of sustainable water policies, such as the Water Framework Directive and the MIPAAF Ministry Decree, by providing accurate measurements and estimations of irrigated areas and water volumes. The project uses the ESA Sentinel-2 (S2) satellites as a valuable source of information to map irrigated areas and estimate distributed irrigation water requirements. This study presents the results of the IRRISAT methodology, the first Italian satellite-based irrigation advisory service [2], which was applied in the Campania region. The methodology uses a one-step approach, based on the Penman-Monteith equation, and is adjusted with canopy parameters from S2 data, to quantify irrigation water abstraction. Effective irrigated areas were assessed by using pre-existing maps, unsupervised clustering, and supervised machine learning algorithms applied to vegetation index data [3]. The results of the methodology for the irrigation seasons of 2019 and 2020 will be presented for seven Irrigation and Land Reclamation Consortiums, which vary in size, irrigation scheme, farm delivery, irrigation methods, and crop types. [1] INCIPIT Project, www.principit2017.it [2] Vuolo F., D’Urso G., De Michele C., Bianchi B., Cutting M.: Satellite-based irrigation advisory services: a common tool for different experiences from Europe to Australia”. Agricultural Water Management, Elsevier, vol. 147: 82-95; dx.doi.org/10.1016/j.agwat.2014.08.004 (2015). [3] Falanga Bolognesi S., Pasolli E., Belfiore O. R., De Michele C., D’Urso G.: Harmonized Landsat 8 and Sentinel-2 Time Series Data to Detect Irrigated Areas: An Application in Southern Italy". Remote Sensing, MDPI, vol.12, no. 8: 1275; doi.org/10.3390/rs12081275 (2020).

The effects of climate change on water availability affect the performance of surface irrigation, which is the oldest and most common method of water application to row crops worldwide. A paradigm shift towards strategies aimed at increasing flexibility of irrigation scheduling and improving the design and management of field layouts and irrigation practices should be explored to promote water savings at the farm scale. In this study, we investigate how adopting a more flexible irrigation scheduling and optimizing irrigation management variables and field layout it is possible to increase the efficiency of border irrigation and thus achieve water savings and improve quality of crop production. The analysis of the actual performance of border irrigation was carried out on two maize fields located in the Padana Plain (Northern Italy) in two years characterized by different rainfall patterns (i.e. 2021 and 2022). Based on this information, continuous monitoring of soil moisture status combined with the AquaCrop-OS agro-hydrological model was used to manage flexible irrigation scheduling over the experimental fields. While the optimization of irrigation management (flowrate per unit width and cutoff time) and field geometries (border width and slope) was studied using WinSRFR 5.1 USDA software, which was properly calibrated by measures of waterfront advance and recession. The results show that with flexible irrigation scheduling and proper irrigation management and field layout, significant water savings can be achieved. Specifically, in the case study, seasonal water savings of about 10% were obtained just by scheduling irrigation based on actual crop water needs in a very dry agricultural season, while water savings reached up to 60% in a wetter season. On average, an additional 7% of water savings was achieved over the agricultural season when the irrigation duration was correctly applied to each border of the experimental plots, while approximately 20% of water was saved when the border width was correctly designed based on inflow availability. These results provide useful information for improving the management of border irrigation in practice, both under current conditions and in the face of increasing freshwater scarcity in the future.

Achieving a good irrigation performance is not straightforward in border irrigation practices. This is almost always due to a lack of balance between natural factors (i.e. soil texture, infiltration characteristics), geometrical features (filed length, slope and border strip width) and management elements (flow rate and cut-off time). Such lack of balance makes it difficult to reach an optimal water depth across the field and a uniform intake opportunity time to satisfy crop water requirements at every point. In light of these concerns, studies investigating the current irrigation performance of border irrigated fields, and the potential improvements in irrigation managements are needed in order to better understand how we can keep this ancient but still crucial irrigation method alive. In this work, the results of an intensive monitoring campaign of more than ten border strip irrigation events carried out between the years 2021 and 2022 over two maize fields located in the Padana Plain (North Italy), are analyzed to understand the current performance level of this practice. Specifically, observed variables at the experimental sites included the actual flow rate, cut-off time and distance, advance and recession trajectories and water distribution uniformity, were investigated and their spatio-temporal variability discussed. Then, the IrriSurf2D model which is constituted by an integrated 2D hydrodynamic modelling framework intended to describe the dynamics of surface irrigation, was used for reproducing waterfront propagation under new irrigation management practices, i.e. different irrigation durations, flow rates and border layouts (slopes and border widths). Results show that microtopography, border width and antecedent moisture conditions before the irrigation intervention, plays a key role in the advancement of the waterfront along the longitudinal direction of the field and in the spatial variability of the water depth. A significant variability in time of advance and recession trajectories was observed over the experimental fields, whereas the distribution uniformity was generally consistent with literature standards. Additionally, the fields could be irrigated in considerably less time if the cut-off time is adjusted in according with the real flow rate and border layout. In general, the study has demonstrated a great potential to significantly improve irrigation performance by applying alternative field designs and operation strategies. These findings pave the way to define suitable guidelines for practical field irrigations with positive impacts in terms of water distribution uniformity and water saving.

The main goals of agro-hydrological models are to estimate water fluxes in the soil-plant-atmosphere continuum (SPAC) and to support management and planning of the water resource over specific areas (a field, a farm, an irrigation district, a river catchment, etc.). Hydrological models are ‘physically-based’ (e.g., SWAP, HYDRUS, FLOWS) if they rely on an accurate mathematical description of processes taking place in the physical system, or are ‘conceptual’ (e.g., SWAT/SWAT+, DSSAT, IDRAGRA) when they are based on a simplified schematization of the physical system and the processes involved. The Richards’ equation (Richards, 1931), modified to include root water extraction, is applied by physically-based models to compute soil water movements, requiring the knowledge of the soil water retention, θ(h), and unsaturated conductivity, K(θ), curves, and the use of quite complex and computationally demanding numerical schemes to be solved. On the contrary, conceptual models are based on a bucket/cascade bucket approach to describe water movement into the soil.Conceptual models are often applied for irrigation planning over large areas in a spatially distributed mode, since they require less data and a lower computational effort than physically-based models. However, when considering rice areas, the strong link between irrigation, soil characteristics and groundwater dynamics dictates the need of a rigorous way to compute soil water fluxes, from which the irrigation efficiency depends. This suggests the application of physically-based models or the development of a novel conceptual approach able to describe the effect of compacted soil layers and shallow groundwater conditions on the percolation/capillary rise dynamics.This work presents a simplified soil water balance model for rice areas based on the Darcy equation. This approach allows the quantification of vertical fluxes based on a limited number of data that can be retrieved from existent data sources (depth and thickness of the less conductive layer within the soil profile, saturated soil hydraulic conductivity of this layer, ponding water level inside the paddy field and depth of the groundwater table). The new approach was validated comparing the water fluxes obtained with those achieved through a semi-distributed/mechanistic agro-hydrological model based on SWAP (https://www.swap.alterra.nl/) applied to a pilot rice district of about 1.000 ha in northern Italy (San Giorgio di Lomellina, Pavia).This research was developed in the context of the MEDWATERICE (PRIMA Section2-2018) and RISWAGEST projects (Regione Lombardia, RDP 2014-20).

The present report summarizes the benefits of the eleven digital solutions demonstrated within DWC-WP2 in the form of fact sheets. The document aims to help cities and water utilities in finding appropriate solutions for their operational, environmental or public health deficits. The report is the final version which was submitted in Nov. 2022 after incorporating the recommendations and amendments by the EC.

Improving the management of irrigation schemes is a priority in the Mediterranean countries of the EU to achieve the objectives of the Water Framework Directive 2000/60EC. In the case of schemes based on open-channel networks for water conveyance and delivery, a limitation to the management efficiency is the huge number of gates that need to be controlled and regulated manually to adapt the flow to the actual irrigation water demand. Automated and coordinated gate regulation of large irrigation schemes has been successfully implemented in some areas of the world (e.g., NSW, Australia), but it implies huge public investments that are often unavailable. Opposite to this top–down approach, the Lombardy region (the largest irrigated region in the EU) has explored an approach based on funding small projects, which should demonstrate the potential of innovation in irrigation practice and foster the expansion of the most effective measures. In this paper, we analyze the effects of one of these projects, consisting in the substitution of a manual gate, controlling the supply of irrigation to a 150 ha irrigation district, with an automated, remotely controlled gate. Nine years of daily flow measurements at the district inlet, provided by the irrigation consortium that manages the gate, were compared with the rigid flow regulation that was applied when the inlet gate was manually regulated and with the irrigation water requirements simulated with a distributed agro-hydrological model widely used in the region for irrigation accounting and planning. The results show that the flexible regulation allowed by the new gate provided an average water saving of 12,000 m3/ha/year compared to the rigid regulation system. A further, though smaller, margin of improvement of 5000 m3/ha/year can be achieved with an optimal regulation that follows exactly the crop water requirements. A further interesting empirical evidence is that the simulation model fits very well the irrigation water requirements of the district using only easily accessible meteorological input data, without exploiting any information from ground or remote sensors to update soil moisture or crop developments during the season. This indicates that it could be effectively used, with very limited costs and effort, to support and improve the gate management. Finally, a preliminary economic analysis shows that the cost of the gate installation is sustainable, but the upscaling of this type of intervention to larger areas requires the support of public funding to cover approximately half of the cost of investment needed for the networking infrastructures.

Farmers’ adaptation to climate change is a two-step process that involves perceiving stressors and identifying impacts to respond to variability and changes through specific actions and strategies. Hence, successful adaptation depends on how well changing climate is perceived, either from a ‘bottom-up’ pathway –where farmers observe and identify changes through past experience–, or by using a ‘top-down’ pathway –where changes are identified through climate records. A gap between both pathways tends to be related to farmers’ misperception. For example, as life experiences influence perception, farmers who have been directly affected by extreme climatic events tend to report that the probability of such event happening again is relatively high. Furthermore, as perception is in part a subjective phenomenon, therefore, different farmers in the same locality might construct different perceptions of climate change impacts even though they experience the same weather patterns. Consequently, increased attention has been put on combining the ‘civic science’ of farmers’ perceptions with the ‘formal science’ from meteorological reports to identify the (in)consistency between perceived and observed data and how this affect farmers’ resilience when facing climate change impacts. This contribution provides a review comparing farmers’ perception and climate observations to address a twofold research question: 1) Which extreme events and compound risks are perceived by farmers in contrast with observed data? And 2) How do past experiences and social-learning influence farmers’ resilience and their adaptive capacity? We analyze a portfolio of 147 articles collected from Scopus library catalogue since 2000. The bibliometrics analysis was coupled with the systematic review to 103 articles selected from the original portfolio. Comparison between perceived and observed changes were focus on what was changing (onset, duration or cessation regarding temperature and rainfall patterns) and how it was changing (amount, frequency, intensity or inter-annual variability). Results will be useful for managers, developers, and policymakers of climate adaptation strategies to be more in tune with farmers’ understandings of when and how weather is changing. Furthermore, the review could generate recommendations for the design, formulation, and implementation of adaptation policies that are better tailored to farmers’ perception at local conditions, being more efficient and conducive to risk analysis when facing climate change.

The assessment of soil-water balance is associated with several challenges, such as the mitigation effects of droughts and flooding, particularly under climate change. Such alerting threat has pushed forward the efforts that the governments are doing to mitigate this risk. Aiming at contributing to better characterize the soil-water balance in small agricultural catchments, the European Union has launched a project of OPtimal strategies to retAIN and re-use water and nutrients across different soil-climatic regions in Europe (OPTAIN). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 862756. In the framework of this project, the Soil Water Assessment Tool Plus (SWAT+) model was applied to the Cherio river basin, located near the city of Milan, Northern Italy, to develop novel strategies for natural/small water retention measures (NSWRM). The topography of the basin is complex, in which the northern part of the basin is a mountainous area, while the middle and lower part is mainly covered by urban, forest, and agricultural areas. The digital elevation model, land uses, soils, river network, and a long dataset of observed meteorological variables from 2002 to 2020 were prepared and elaborated to satisfy the model requirements. The application of the SWAT+ model was done by delineating the watershed, mapping land use and soil and their associated parameters, and creating the Hydrologic Response Units (HRUs) that identify hydrological homogenous areas inside the basin. As a result, the SWAT+ was used to simulate the hydrological processes and a sensitivity analysis was performed to identify the sensitive parameters affecting the simulated discharge based on the Sobol method. Model calibration was then performed using the observed discharges recorded at a flow gauge close to the basin outlet. The results show that differences between the simulated and observed discharges are very significant and appear to be related to the insufficient quality of precipitation inputs, rather than to model limitations or poor parameter calibration. This returns to the role of the uncertainty associated with the temporal and spatial measurement of the precipitation even in small catchments when the hydromorphological characteristics are complex. The findings of this research can be used to have a better understanding of hydrological fluxes variability across the basin and to assess the proper NSWRM to improve the qualitative and quantitative management of water resources in the Cherio river basin.

Topographic depressions in Digital Elevation Models (DEMs) have been traditionally seen as a feature to be removed as no outward flow direction is available to route and accumulate flows. Therefore, to simplify hydrologic analysis for practical purposes, the common approach treated all depressions in DEMs as artefacts and completely removed them in DEMs’ data preprocessing prior to modelling. However, the effects of depression filling on both the geomorphic structure of the river network and surface runoff is still not clear. The use of two-dimensional (2D) hydrodynamic modeling to track inundation patterns has the potential to provide novel point of views on this issue. Specifically, there is no need to remove topographic depression from DEM, as performed in the use of traditional methods for the automatic extraction of river networks, so that their effects can be directly taken into account in simulated drainage patterns and in the associated hydrologic response. The novelty introduced in this work is the evaluation of the effects of DEM depression filling on both the structure of the net-points characterizing the simulated networks and the hydrologic response of the watersheds to simplified rainfall scenarios. The results highlight how important these effects might be in practical applications, providing new insights in the field of watershed-scale modeling.

The intensification of agricultural production is connected to the increased use of fertilizers, pesticides, irrigation water, and energy. Among all cropping systems, rice cultivation is considered to be one of the most significant sources of environmental harm due to the flooding conditions in which rice normally grows; at the same time, rice has important economic and social implications, especially in areas where it is a staple food. In the last 20 years, sustainable development of agricultural production has become a priority for scientific research and policy programs. Several studies proposed methodological frameworks to assess the impacts of different management practices adopted in agro-ecosystems and to identify strategies to mitigate the negative effects of agricultural intensification. Such methodologies are based on the use of particular indicators, which are increasingly seen as crucial tools in impact assessment studies and for decision making. This paper aims to review and analyze the most significant methodological frameworks developed to assess the sustainability of agricultural production systems, with a particular focus on rice cultivation. The analysis includes highlighting which dimensions of sustainability (economic, environmental, social, and governance) are covered by each method and identifying which indicators are used to describe the different dimensions. The spatial scale of the application of the indicators, their typology, the data needed for their implementation, and the criteria for formulating the overall sustainability judgment were then examined. The analysis highlighted the scarce availability of clear operational data for the calculation of the indicators and the often-limited involvement of stakeholders in the development and implementation of the methodologies. The exceptions to these limitations are represented by a few methodologies developed under the umbrella of important international organizations to promote sustainability and research efficiency in specific agricultural production systems, such as the SRP (sustainable rice platform) for rice. Finally, the analysis shows that there is a need to develop methodologies that are applicable not only to an individual farm or group of farms, but also at larger spatial scales (district, watershed, region), which are often those of greatest interest to decision makers.

Italy is Europe’s leading rice producer, with over half of the total production, almost totally concentrated in a large paddy rice area in the north-western part of the country, stretching across the border between the Lombardy and Piedmont regions in the Po river valley. In this area, rice irrigation has been traditionally carried out by wet seeding and continuous flooding. The introduction of alternative water-saving irrigation strategies could reduce water needs and environmental impacts; however, before extensively adopting them, their effects at both the field and irrigation district scales must be quantified.In the context of the MEDWATERICE project (PRIMA-Section2-2018), in the agricultural season 2019 an experimental platform was set-up in a location within the paddy area (Pavia province), to compare different irrigation strategies: wet seeding and traditional flooding (WFL), dry seeding and delayed flooding (DFL), and a ‘safe' wet seeding and alternated wetting and drying (AWD). Six plots of about 20 m x 80 m each were set-up, with two replicates for each irrigation option. One out of the two replicates was instrumented with: water inflow and outflow meters, piezometers, tensiometers, and water tubes for the irrigation management in the AWD plots. A soil survey was conducted before the agricultural season (EMI sensor and physico-chemical analysis of soil samples). Periodic measurements of crop biometric parameters were conducted. Nutrients (N, P, K) and two widely used pesticides (Clomazone, MCPA) were measured in irrigation water (inflow and outflow), groundwater, and porous cups installed at two soil depths (20 and 70 cm, above and below the plough pan). Finally, rice grain yields and quality (As and Cd in the grain) were determined. The experimental activity in the platform was carried out for two years (2019 and 2020), and an upscaling of the results at the irrigation district scale is foreseen in the project.Soil water balances at the field scale were computed through an approach integrating field measurements of irrigation flows and storages with hydrological modelling, to compare the three irrigation management strategies under similar soil conditions. Results for 2019 showed that DFL allowed a water saving of 10% compared to WFL, while a higher water saving (19%) was achieved with AWD, as expected. Rice grain yield was found to be comparable for all the investigated irrigation treatments. Also, the grain N content was not significantly affected by the water management strategy adopted: the highest values were obtained in WFL and AWD (1.4 N%), while the lowest in DFL (1.2 N%). Total As in grain was not significant for any of the irrigation strategies, but rice Cd level was statistically higher in AWD, although under the legal limits set in the EU even for baby food. As far as water quality is concerned, in surface water, soil solution and groundwater, concentrations for both herbicidesdid not reach significant values, even after treatments, except in limited cases that could depend on relevant concentrations already present in the irrigation inflow. Data for 2020 are under elaboration and first results will be illustrated during the conference.

Selecting the best irrigation management is required for improved use of water resources and for achieving sustainable crop productions. That selection implies accurate predictions of crop water requirement in response to meteorological variables and phenological stages. A plethora of irrigation models are reported to date in literature, many of which are based on three different approaches proposed by the FAO organization, the single and double crop coefficient methods and, the canopy-cover curve determination included in the AquaCrop model.The objective of this study is to compare irrigation needs and scheduling obtained by the three aforementioned approaches in the agricultural context of the Po River Plain (northern Italy). The first and the second approaches were simulated respectively by Sim1Kc and IdrAgra models, which implemented the algorithms and crop parameterizations reported in FAO paper 56 for a crop water requirement estimation. While the third approach was simulated by the open source version of AquaCrop software.Models were tested on a maize plot located in the lower-east part of Lombardy Po River Plain characterized by a humid sub-tropical climate, according Köppen classification. A single sandy-loam layer profile of medium-textured soil 1 m deep was considered for the simulation. Crop parameters values in Sim1Kc and AcquaCrop models were mutuated from the IdrAgra model, which is routinely applied in the region as the reference model for the assessment of crop water requirements.Actual evapotranspiration and irrigation needs were evaluated respectively in rainfed and irrigated simulations. These latter were performed replacing soil moisture at the field capacity when 70% of TAW was reached. Results achieved in three agrarian seasons characterized by low, medium and high rainfall volumes (from June to September) were compared (respectively the years 2009, 2002 and 2014 with about 41 mm, 116 mm and 152 mm of rainfall).The results show that in rainfed conditions, for each year, actual evapotranspiration simulated by the models were consistent with each other, with an average RMSE, calculated comparing the models in pairs, of about 1 mm over the season. Differences among the models were mainly observed in the first part of the season (respectively before the thirtieth day after the sowing) and for each year, probably caused by a still limited crop and root development, which highlights the differences in simulating water fluxes exchanges in soil-vegetation domain proposed by three modeling approaches.Concerning irrigations, IdrAgra and AquaCrop appear very consistent with each other in volumes and frequency, especially during mid-crop stages and in all years with a total irrigation volume of about 400, 300 and 180 mm and with 10, 12 and 8 irrigation interventions respectively in the years 2009, 2002 and 2014. Results of Sim1Kc were consistent with those obtained by the other models only in mid and end crop season, whereas no irrigations were suggested in the first part of the season.

In this article, an open channel flow resistance equation, deduced applying dimensional analysis and incomplete self-similarity condition for the flow velocity distribution, was tested using measurements carried out in a full-scale channel equipped with three types of riparian plants (Salix alba L., Salix caprea L. and Alnus glutinosa L.). In the experimental channel, having banks lined with boulders, the vegetation branches were anchored in a concrete bottom. For each species, the measurements were carried out with plants having different amounts of leaves, different plant density and plant area index. The relationship between the scale factor Γ of the velocity profile and the Froude number was separately calibrated by measurements carried out without and with vegetation. The component of Darcy-Weisbach friction factor corresponding to the riparian vegetation fv was calculated as the difference between the measured friction factor value (channel grain roughness + vegetation) and that calculated for the channel without vegetation in the same hydraulic conditions. Using these fv values, the relationship between the scale factor Γ and the Froude number was calibrated. In this last relationship, a scaling coefficient a varying with the investigated vegetation type was introduced. This coefficient, as expected, gives the highest friction factor values for vegetation having branches with leaves. The theoretical flow resistance law, coupled with the relationship for estimating the Γ function having a scaling coefficient different for each investigated vegetation type, allowed an accurate estimate of the Darcy-Weisbach friction factor (errors less than or equal to 20% for 82.6% of the investigated cases). Finally, for the investigated vegetation species that are characterized by a condition with few leaves or leafless, the scaling coefficient a resulted strongly related to the bending stiffness. This analysis demonstrated that the highest Darcy-Weisbach friction factors correspond to vegetation species characterized by the highest values of bending stiffness. The friction factor values calculated for this last condition are characterized by errors that were less than or equal to ±20% for 90.6% of cases.

Urbanization modifies the hydrologic cycle, resulting in increased runoff rates, volumes, and peak flows in the drainage network. In this paper, the implementation of green roofs as source control solutions for mitigating the impacts of urbanization is analysed at the urban catchment scale. The hydrologic-hydraulic response of a 2 km2 urban basin is investigated under various implementation scenarios and rainfall characteristics. In particular, a distributed hydrologic model is employed to assess the impact of 4 spatially homogeneous installations of green roofs (25%, 50%, 75%, 100% of roofs area converted) when forced by 6 storms differing in both duration and return period. In addition, a spatially heterogeneous configuration is tested, with green roofs concentrated where the drainage network is more prone to high degrees of filling. Results show that implementing green roofs at the urban watershed scale can be considered a valuable strategy to reduce both flow peak and volume in urban drainage networks, although the approach is more effective for frequent storms of smaller magnitude. In addition, it is found that the urban system may respond non-linearly to the extent of green roofs implementation in terms of peak flow reduction at the network outlet, and that non-linearity is mainly related to the network being close to its flow convey capability. Finally, planning redevelopment efforts on the basis of local insufficiencies in network convey capacity has the potential of increasing the effectiveness of Low Impact Development solutions.

Italy is the leading rice producer in Europe, accounting for more than half of the total high-quality production of this crop. Rice is traditionally grown in fields that remain flooded starting with crop establishment until close to harvest. The water management in rice areas requires a high level of labor because it is based on maintaining a predetermined water height in paddy fields and because the regulation of input and output flow is typically operated manually by the farmers. This study aims to evaluate the hydraulic, control and economical performances of the first automatic and remote-controlled system applied for traditional rice irrigation in Europe and tested in Italy during 2016 agricultural season. In particular, (i) the effects of automation on the water balance; (ii) the reliability of the irrigation system for a real-time control of flow regulation and water level management in the field and (iii) the economic viability of the investment are investigated. The results show that, despite the automatic system has not proven a decrease of water consumptions (ranging from 2000 to 3700 mm) or a significant increase of rice yield (of about 8 ton hectare−1), it has not revealed any mechanical malfunctioning during the irrigation season and it allows to drastically reduce the time spent by workers for water level control and flow regulation. Lastly, the price of the automatic irrigation system (ranging from 638 to 689 € hectare−1) appears to be in good agreement with respect to the willingness of farmers for innovation.

This research aims to evaluate the perceptions of and preferences for irrigation multifunctionality based on an analysis of stakeholder’ attitudes in a large irrigation system in Northern Italy, the Muzza canal. As the first artificial canal built in Northern Italy, this canal articulates a network of open earth canals that distribute water for irrigation, especially maize. The Stakeholder analysis approach and Governance model approach are applied. The collected data highlights: (1) each key stakeholder points of view regarding multifunctionality and ecosystem services, (2) the nature of conflicting attitudes regarding who and how the Muzza system is managed, and (3) the ability or inability to promote agreements among conflicting water demands. The results show how public administration is concerned about how to manage ecosystem services provided by irrigation practices, while private services are focused on how to guarantee the coexistence of consumptive and non-consumptive water uses, highlighting the persistent conflict between farming production and environmental protection. The rural community and civil society call for a debate about the future of irrigation multifunctionality in the Muzza system and the role of irrigation practices in landscape provision and management. In addition, the paper examines if multifunctionality is a characteristic or an objective of irrigation systems. These results can be used by researchers and relevant authorities to customize their interventions based on previous, well-structured knowledge of various stakeholders’ priorities.

The last decades have been characterized by an important development of viticulture in Italy, especially in Lombardy, where this sector is focusing on improving grapevine production, by enhancing quantity and, even more, quality. The increasing frequency of extreme meteorological events that has been observed in recent years has started raising concerns about the risks for grapevine quality and production, caused by summer heat waves and late spring frosts. The role of over-vine sprinklers in frost protection is well known; less so is their effect on heat stress protection. In fact, recent studies have shown that evaporation of sprayed water in the canopy layer during heat waves can reduce local air temperature through latent heat absorption by water evaporation. Moreover, in order to minimize the temperature-related stress, water spraying can be combined with the control of soil water content through drip irrigation, to lower soil temperature and enhance turgor maintenance.The ADAM project (http://www.adam-disaa.eu/IT/DEFAULT.ASP#) fits into this research framework. The objective of the project is to develop a multifunctional irrigation strategy combining controlled soil water content and protection from temperature-related stress conditions. An experimental activity has started in the 2019 season in a Chardonnay vineyard located in the Colli Morenici area (Lombardy, northern Italy). Four irrigation management strategies have been compared, namely: no irrigation (NI); farmer’s drip irrigation (IT); automated drip irrigation, based on tensiometer measurements (IG); automated drip plus over-vine micro-sprinkler irrigation based on tensiometer measurements, temperature measurements and short-term forecast (IS). In the latter case, irrigation is activated before heat wave occurrence, based on 5days-ahead temperature forecasts (with 3 h refresh period).At the end of the first year of experiment, we have obtained interesting preliminary results: while the first three strategies did not lead to significant differences in grape quality (in terms of sugars content, acidity and pH of musts), differences were found in all three parameters for the IS strategy. Specifically, pH and acidity are higher and sugars content is lower. Further analysis, including micro-vinification, are ongoing in order to assess the effects on wine quality. The experimental activity will continue in 2020 and 2021 with the aims of: collecting enough data to define a preliminary protocol for multi-functional irrigation management; assess the irrigation water requirements and the energy consumptions; test the effectiveness of VIS/NIR techniques for the quick measurement of crop conditions; verify the sustainability of the different strategies, both at the farm and district scale.

Water resources planning at the basin scale is the keystone to adaptation of water resources systems to socio-economic and climate changes. Simulation and optimization models can provide a useful support to the planning process. Besides including all significant processes, they need to incorporate the contribution of the relevant stakeholders from the early stages of their development, particularly in areas where multiple concurring uses of water resources occur and where surface water-groundwater interactions are important. This is the case of the plain of the Lombardy Region, Italy, where an ancient system of irrigation canals has been successfully used for centuries to supply huge amounts of water to a large irrigated area, which is also one of the most industrialized in Europe (Lombardy is one of the “Four Motors for Europe”, a transnational network of highly industrialized regions including Rhône-Alpes, Baden-Württemberg and Catalonia). Indeed, the Lombardy water resources have suffered recurrent crisis in the last years and a huge pressure has been raising on irrigation water use, which is by far the main consumptive use. We illustrate here an integrated approach to the analysis of different strategies of adaptation of irrigation systems to changing conditions, which accounts for the links between water use, crop production, energy consumption and hydrological conditions (as a proxy of the ecosystems quality). We will consider the case study of the Adda river basin, an 8,000 km2 basin including lake Como, where the requirements of hydropower production and irrigation supply need to strike a balance with lake tourism, flood protection and environment conservation.The approach is based on a combination of simulation models (of upstream sub-basin, lake and downstream sub-basin) and optimization model (of lake regulation policy) that allow assessing the effects of different climate and technological scenarios. The former scenarios were obtained downscaling the regional climate projections provided by the CORDEX project till 2100, while for the latter we focused on measures to increase the efficiency of irrigation systems, that emerged as priority from the discussions with the stakeholders. Specifically, we considered different degrees of reconversion of irrigation methods from surface irrigation to more efficient methods (sprinkler or drip). The effects of the reconversion, under different climate projections, were assessed by running simulations with the IdrAgra spatially distributed agro-hydrological model, which provided the estimated values of crop water use, groundwater recharge, return flows, as well as of crop production and energy consumption. The comparison of different reconversion intensities was carried out considering indicators for the satisfaction of crop water requirements, the energy consumption, the groundwater recharge, and the river hydrological regime. A number of remarks can be made from the analysis of the results, among which it clearly emerged that under the current trend of increasing temperature already at the mid of the century irrigation deficits and impacts on the river hydrological regime will be intolerable unless the irrigation system efficiency will increase significantly in vast portions of the study area. Finally, a preliminary estimate of the cost of interventions is provided.

In the Mediterranean basin, rice is cultivated over an area of 1,300,000 hectares. The most important rice-producing countries are Italy and Spain in Europe (72% of the EU production; 345,000 ha), and Egypt and Turkey among the extra-EU countries (almost totality of the production; 789,000 ha). Traditionally, rice is grown under continuous flooding; thus, it requires much more irrigation than non-ponded crops. The MEDWATERICE project (PRIMA-Section 2-2018; https://www.medwaterice.org/) aims at exploring sustainability of innovative rice irrigation management solutions, in order to reduce rice water consumption and environmental impacts, and to extend rice cultivation outside of traditional paddy areas to meet the escalating demand. Within the MEDWATERICE project, irrigation management options to address the main site-specific problems are being tested for each rice areas involved in the project (IT, ES, PT, EG, TR). Case studies are being conducted in pilot farms, with the involvement of Stake-Holder Panels (SHPs) in each country. Data collected at the farm level will be extrapolated to the irrigation district level, to support water management decisions and policies. Moreover, indicators for quantitative assessment of environmental, economic and social sustainability of the irrigation options will be defined.This work illustrates the first year of results for the Italian Case Study (Lomellina area, Pavia) at the pilot farm scale. This area is characterized by a growing water scarcity in drought years in many districts. Within the farm managed by the National Rice Research Center (CRR), in the agricultural season 2019 the experimentation was conducted in six plots of about 20 m x 80 m each, with two replicates for each of the following water regimes: i) water-seeded rice with continuous flooding (WFL), ii) dry-seeded rice with continuous flooding from the 3-4 leaf stage (DFL), and iii) water seeded-rice with alternate wetting and drying from fertilization at the tillering stage (AWD). One out of the two replicates of each treatment was instrumented with: water inflow and outflow meters, set of piezometers, set of tensiometers and water tubes for the irrigation management in the AWD plots. A soil survey was conducted before the agricultural season (EMI sensor and physico-chemical analysis of soil samples). Periodic measurements of crop biometric parameters (LAI, crop height, crop rooting depth) were performed. Moreover, nutrients (TN, NO3, PO4, K) and two widely used pesticides (Sirtaki – a.i. Clomazone; Tripion E – a.i. MCPA) were measured in irrigation water (inflow and outflow), groundwater, and porous cups installed at two soil depths (20 and 70 cm, above and below the plough pan). Finally, rice grain yields and quality (As and Cd in the grain) were determined. First results in terms of cumulative water balance components (rainfall, irrigation inflow and outflow, difference in soil and ponding water storage, evapotranspiration, net percolation), water application efficiency (evapotranspiration over net water input), and water productivity (grain production over net water input), will be presented and discussed. Results of a 1D Richard-equation-based numerical simulation model applied to generalize results obtained under the different irrigation regimes will be moreover illustrated.

The topographic survey of rural canal network is a crucial task to allow a sustainable irrigation management and planning in rural areas and, always more frequently, to control the interactions with urban areas (flood protection, in particular). However, to date, datasets of canal and ditch geomorphological characteristics, such as layout, cross-sections, slopes and canal bed characteristics, are almost completely absent, or unreliable. This work tests the use of four different data sources—two from remote sensing and two from ground survey—for detecting the geometrical characteristics of rural canals at increasingly high resolution, providing cross sections and slopes over a pilot study domain of about two hectares located in south Milan (Italy). Specifically, rural canal geometries were obtained from the processing of data from (i) a Lidar and a photogrammetric flight at different altitude (ii) a ground-fixed laser scanner and (iii) a GPS spot acquisition to complete surveys with a further level of detail. 3D models of the rural canals were obtained from the processing of the data of each of the three sources. Results of the comparison of the models are presented, focusing on canal cross sections, slope, and bed characteristics; moreover, the impact of these differences on the flow and storage capacity of the channels will be discussed and, finally, an assessment of the costs of data acquisition and processing is provided.

Among the commonly used plastic materials in geotechnical engineering, the most significant fraction consists in the geosynthetics. The use of these products involves environmental risks associated with their degradation. Hence, a strong interest in biodegradable polymers of natural origin has been increasing, for finding alternative materials with adequate mechanical properties for geotechnical and geo-environmental applications. The main aim of this study is to test a bio-based, biodegradable and eco-compatible polymer, able to replace polypropylene and other synthetic materials in the production of geosynthetics. For this purpose, Poly(lactic acid) or PLA, one of the most common bioplastic polymer material commonly used as filament for 3D printers, was investigated. The chemical structure of PLA was determined by 1H NMR and the optical purity determination by polarimetry. PLA filament was used to print samples of uniaxial and biaxial geogrid at 1:5 scale using a professional 3D printer. Subsequently, tensile tests were performed on the filament and on prototype geogrids. Tensile tests measured a maximum tensile resistance of 51.96 MPa for the filament and 12.96 kN/m for uniaxial geogrid prototypes. The mechanical properties of PLA were found to be comparable to petroleum derivatives. These results are encouraging and can support the utilization of PLA for innovative biodegradable geosynthetics production, which could represent an alternative to non-biodegradable products, particularly when used in combination with live plants. In view of practical applications, however, research is still needed to determine the degradation of their mechanical properties over time.

The spatial and temporal variability of droughts over the period 1951–2017 for a portion of Lombardy plain (Northern Italy) was reconstructed starting from a quality-checked and homogenized database of long precipitation and temperature station records covering the study region. The monthly meteorological series were interpolated over the period 1951–2017 onto a 30-arc second resolution grid covering the area by means of an anomaly-based procedure and the gridded fields were used to extract for each cell the series of two standardized drought indices: Standardized Precipitation Index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPEI). SPI and SPEI trend analyses were performed on annual and seasonal scales at both regional and grid-point levels. Theil-Sen test on SPI values highlighted a significant drying tendency (Mann-Kendall p-value

The Journal of Agricultural Engineering (JAE) celebrates with this issue the publication of its fiftieth volume. The Journal was founded in 1969, on the initiative of the Italian Society of Agricultural Engineering (AIIA) to publish the results of scientific and experimental acquisitions of the sector, noted the serious lack of adequate editorial venues for what was then called Genie Rural. Initially published in Italian under the name of Rivista di Ingegneria Agraria by the publisher Edagricole, it was one of the first sector journals in Europe and since 1970 it has always followed an annual periodicity, with each volume consisting of four issues printed quarterly, for a total of almost 1200 scientific papers published so far.

Exponentially growing water demands and increasingly uncertain hydrologic regimes due to changes in climate and land use are challenging the sustainability of agricultural water systems. Farmers must adapt their management strategies in order to secure food production and avoid crop failures. Investigating the potential for adaptation policies in agricultural systems requires accounting for their natural and human components, along with their reciprocal interactions. Yet this feedback is generally overlooked in the water resources systems literature. In this work, we contribute a novel modeling approach to study the coevolution of irrigated agriculture under changing climate, advancing the representation of the human component within agricultural systems by using normative meta-models to describe the behaviors of groups of farmers or institutional decisions. These behavioral models, validated against observational data, are then integrated into a coupled human-natural system simulation model to better represent both systems and their coevolution under future changing climate conditions, assuming the adoption of different policy adaptation options, such as cultivating less water demanding crops. The application to the pilot study of the Adda River basin in northern Italy shows that the dynamic coadaptation of water supply and demand allows farmers to avoid estimated potential losses of more than 10 M€/yr under projected climate changes, while unilateral adaptation of either the water supply or the demand are both demonstrated to be less effective. Results also show that the impact of the different policy options varies as function of drought intensity, with water demand adaptation outperforming water supply adaptation when drought conditions become more severe.