Drinking water security is a life safety issue as an adequate supply of safe water is essential for economic, social and sanitary reasons. Damage to any element of a water system, as well as corruption of resource quality, may have significant effects on the population it serves and on all other dependent resources and activities. As well as an analysis of the reliability of water distribution systems in ordinary conditions, it is also crucial to assess system vulnerability in the event of natural disasters and of malicious or accidental anthropogenic acts. The present work summarizes the initial results of research activities that are underway with the intention of developing a vulnerability assessment methodology for drinking water infrastructures subject to hazardous events. The main aim of the work was therefore to provide decision makers with an effective operational tool which could support them mainly to increase risk awareness and preparedness and, possibly, to ease emergency management. The proposed tool is based on Bayesian Belief Networks (BBN), a probabilistic methodology which has demonstrated outstanding potential to integrate a range of sources of knowledge, a great flexibility and the ability to handle in a mathematically sound way uncertainty due to data scarcity and/or limited knowledge of the system to be managed. The tool was implemented to analyze the vulnerability of two of the most important water supply systems in the Apulia region (southern Italy) which have been damaged in the past by natural hazards. As well as being useful for testing and improving the predictive capabilities of the methodology and for possibly modifying its structure and features, the case studies have also helped to underline its strengths and weaknesses. Particularly, the experiences carried out demonstrated how the

The safety of drinking water infrastructures is fundamental for economic, social and sanitary reasons, andshould be guaranteed both during ordinary service and in case of emergencies. Besides verifying and preventingdeterioration and ageing, the response of the system to extreme events should be also carefully analyzed. As a matterof fact, depending on the level of preparedness that water system authorities have adopted, the restoration of systemfunctionality may require days, weeks, or even months.Water supply systems are vulnerable towards several hazardous events, which can be mainly classified asnatural (such as earthquakes, hurricanes, volcanic eruptions, landslides, fires...) or anthropic (both intentional andaccidental, such as pollution, operational mistakes, black-outs etc.). Referring to the potential consequences of suchevents on the system, physical damages consisting in breakage or malfunctioning of one or more elements of thenetwork, should be distinguished from water contamination.A research activity is being developed by the Water Research Institute of the National Research Council(Istituto di Ricerca sulle Acque del Consiglio Nazionale delle Ricerche IRSA-CNR), supported by the ItalianDepartment of Civil Protection (Dipartimento della Protezione Civile - DPC), with the aim of defining a strategicDecision Support System (DSS) for efficient and coherent decision-making in case of threats involving drinkingwater infrastructures. The DSS is based on Bayesian Belief Networks (BBNs), a semi-quantitative probabilistic toolparticularly useful for managing emergency situations, characterized by time shortness and information uncertainty.It should be mainly used for detecting potential shortcomings of the system during emergencies, but also for helpingwater authorities in defining priorities of action, even with reference to ordinary management procedures.In the following, the methodological approach adopted is firstly presented, with specific reference to the mainfeatures of BBNs. Then, the structure of the methodology is described in synthesis. At last, the applicability of thetool is discussed, referring to a couple of real case studies developed with the cooperation of Acquedotto PuglieseS.p.A., an Italian water authority.

In this paper a new data assimilation technique is proposed which is based on the ensemble Kalman filter (EnKF). Such a technique will be effective if few observations of a dynamical system are available and a large model error occurs. The idea is to acquire a fine grid of synthetic observations in two steps: (1) first we interpolate the real observations with suitable polynomial curves; (2) then we estimate the relative measurement errors by means of Brownian bridges.This technique has been tested on the Richards' equation, which governs the water flow in unsaturated soils, where a large model error has been introduced by solving the Richards' equation by means of an explicit numerical scheme. The application of this technique to some synthetic experiments has shown improvements with respect to the classical ensemble Kalman filter, in particular for problems with a large model error.

Using reliable stochastic or deterministic methods, it is possible to rearrange an existing network by eliminating, adding or moving monitoring locations producing the optimal arrangement among any possible. In this paper, some spatial optimization methods have been selected as more effective among those reported in literature and implemented into a software M-Sanos able to carry out a complete redesign of an existing monitoring network. Both stochastic and deterministic methods have been embedded in the software with the option of choosing, case by case, the most suitable with regard to the available information. Finally, an application to the existing regional groundwater level monitoring network of the aquifer of Tavoliere located in Apulia (south Italy) is presented.

Artificial recharge is used to increase the availability of groundwaterstorage and reduce saltwater intrusion in coastal aquifers, where pumpingand droughts have severely impaired groundwater quality. Theimplementation of optimal recharge methods requires knowledge ofphysical, chemical, and biological phenomena involving water andwastewater filtration in the subsoil, together with engineering aspectsrelated to plant design and maintenance operations. This study uses anovel Decision Support System (DSS), which includes soil aquifertreatment (SAT) evaluation, to design an artificial recharge plant. The DSShelps users make strategic decisions on selecting the most appropriaterecharge methods and water treatment technologies at specific sites. Thiswill enable the recovery of safe water using managed aquifer recharge(MAR) practices, and result in reduced recharge costs. The DSS was builtusing an artificial intelligence technique and knowledge-based technology,related to both quantitative and qualitative aspects of water supply forartificial recharge. The DSS software was implemented using rules basedon the cumulative experience of wastewater treatment plant engineersand groundwater modeling. Appropriate model flow simulations wereperformed in porous and fractured coastal aquifers to evaluate thesuitability of this technique for enhancing the integrated water resourcesmanagement approach. Results obtained from the AQUASTRESSintegrated project and DRINKADRIA IPA CBC suggest the most effectivestrategies for wastewater treatments prior to recharge at specific sites.

Here some issues are studied, related to the numerical solution of Richards' equation in a one dimensional spatial domain by a technique based on the Transversal Method of Lines (TMoL). The core idea of TMoL approach is to semi-discretize the time derivative of Richards' equation: afterward a system of second order differential equations in the space variable is derived as an initial value problem.The computational framework of this method requires both Dirichlet and Neumann boundary conditions at the top of the column. The practical motivation for choosing such a condition is argued. We will show that, with the choice of the aforementioned initial conditions, our TMoL approach brings to solutions comparable with the ones obtained by the classical Methods of Lines (hereafter referred to as MoL) with corresponding standard boundary conditions: in particular, an appropriate norm is introduced for effectively comparing numerical tests obtained by MoL and TMoL approach and a sensitivity analysis between the two methods is performed by means of a mass balance point of view. A further algorithm is introduced for deducing in a self-sustaining way the gradient boundary condition on top in the TMoL context.

The aim of this research is to assess a technique to retrieve actual evapotranspiration (ET) maps from remote sensing images by the combination of two different procedures. The first one, known as triangle method, computes the evapotranspiration fraction (EF) defined as the ratio LE/Rn, where Rn is the net radiation at the surface and LE is the latent heat flux. LE is directly proportional to ET. In order to retrieve LE, and consequently the surface evapotranspiration, a second procedure computes the net radiation of the investigated area. Therefore, by inversion, it is possible to obtain an estimate of the ET. The validation of these variables, net radiation and evapotranspiration derived from MODIS data, has been undertaken on the Capitanata area, Southern Italy, by comparison of model results with in-situ measurements provided by the Consorzio per la Bonifica della Capitanata di Foggia. © 2012 IEEE.

The paper presents the preliminary results of a scientific initiative aiming at the definition and implementation of innovative management options to mitigate the environmental impacts of groundwater pumping in coastal aquifers. In fact seawater intrusion in such aquifers is very often caused by the over-exploitation of groundwater mainly due to the increasing water demand in the agricultural sector in the last decades in most semiarid or arid countries of the world. Consequently, the sustainable management of groundwater under the principles of transparent and efficient water use has highlighted the issue of measuring and accounting the water volumes withdrawn from the groundwater. The objective of the research activity is the design of an innovative monitoring system for sustainable groundwater exploitation. Such an ambitious target requires an accurate analysis of existent and potential stakeholders' conflicts. These conflicts are crucial for the implementation of strategies and activities by the different institutions that are involved in the management of water resources. Therefore, a central role in the development of the project is the stakeholder involvement, with particular emphasis on conflict assessment. In this work, conflicts analysis has concerned both the acceptability of groundwater protection measures and the feasibility of groundwater monitoring strategies.

In many arid and semi-arid regions agriculture is the main user of GW, causing problems with the quantity and quality of water, but there are few institutional policies and regulations governing sustainable GW exploitation. The authors suggest an integrated methodology for enabling local GW management, capable of combining the need for GW protection with socio-economic and behavioural determinants of GW use. In the proposed tool, integration is reinforced by the inclusion of multiple stakeholders, and the use of Bayesian Belief Networks (BBN) to simulate and explore these stakeholders' attitude to GW exploitation and their responses to the introduction of new protection policies. BBNs and hydrological system properties are integrated in a GIS-based decision support system - GeSAP - which can elaborate and analyse scenarios concerning the pressure on GW due to exploitation for irrigation, and the effectiveness of protection policies, taking into account the level of consensus. In addition, the GIS interface makes it possible to spatialize the information and to investigate model results.The paper presents the results of an experimental application of the GeSAP tool to support GW planning and management in the Apulia Region (Southern Italy). To evaluate the actual usability of the GeSAP tool, case study applications were performed involving the main experts in GW protection and the regional decision-makers. Results showed that GeSAP can simulate farmers' behaviour concerning the selection of water sources for irrigation, allowing evaluation of the effectiveness of a wide range of strategies which impact water demand and consumption.

In this study, we report the adopted methodology which has allowed us to map surface water thermal anomalies and, consequently, to identify and locate coastal inflows in the Bari province coasts and Mar Piccolo sea (Taranto), the latter part of the National Priority List site identified by the National Program of Environmental Remediation and Restoration.

The local downscaling of rainfall predictions provided by climate models is crucial for the assessment of climate change impacts on most ecological processes related to the land/water cycle, such as vegetation dynamics, soil-bacteria activity, and ecological response of water-bodies. In this study, we present a methodology to analyze the predictive performance of a Regional Climate Model (RCM) with regard to daily rainfall fields. A comparison between statistical properties of rainfall observations and model control simulations was performed through a robust and meaningful representation of the precipitation process. Our objectives were, first, to evaluate RCM bias data at basin-scale against daily rainfall records coming from a rain gauge network, and then to propose a simple framework to investigate possible alterations of the daily rainfall occurrence and intensity under climate change by way of a stochastic model suitable to investigate both ordinary regimes and extreme climate events.The RCM adopted for the the study region produced a general underestimation of mean storm intensity for all seasons in the control run. From the bias analysis at daily scale, the RCM has shown a good capability to simulate the occurrence of wet periods being able to reproduce the winter storm systems, but a poor capability to simulate the need to operate a correction of the climate model output to obtain more realistic input data to be used in impact studies at the local scale. A further result of the adopted bias correction was the significant reduction of the effects of climate change on daily rainfall statistics corresponding to rainfall features much closer to the historical data than in the raw RCM output data.

Water resource management is often characterized by conflicts, as a result of the heterogeneity ofinterests associated with a shared resource. Many water conflicts arise on a global scale and, in particular,an increasing level of conflicts can be observed in the Mediterranean basin, characterized by waterscarcity. In the present work, in order to assist the conflict analysis process, and thus outline a propergroundwater management, stakeholders were involved in the process and suitable tools were used ina Mediterranean area (the Apulia region, in Italy). In particular, this paper seeks to elicit and structurefarmers' mental models influencing their decision over the main water source for irrigation. The morecrucial groundwater is for farmers' objectives, the more controversial is the groundwater protectionstrategy. Bayesian Belief Networks were developed to simulate farmers' behavior with regard togroundwater management and to assess the impacts of protection strategy. These results have been usedto calculate the conflict degree in the study area, derived from the introduction of policies for thereduction of groundwater exploitation for irrigation purposes. The less acceptable the policy is, the morelikely it is that conflict will develop between farmers and the Regional Authority. The results of conflictanalysis were also used to contribute to the debate concerning potential conflict mitigation measures.The approach adopted in this work has been discussed with a number of experts in groundwatermanagement policies and irrigation management, and its main strengths and weaknesses have beenidentified. Increasing awareness of the existence of potential conflicts and the need to deal with themcan be seen as an interesting initial shift in the Apulia region's water management regime, which is stillgrounded in merely technical approaches.

Electrical resistivitymethods arewidely used for environmental applications, and they are particularly useful for thecharacterization and monitoring of sites where the presence of contamination requires a thorough understandingof the location and movement of water, that can act as a carrier of solutes. One such application is landfill studies,where the strong electrical contrasts between waste, leachate and surrounding formations make electrical methodsa nearly ideal tool for investigation. In spite of the advantages, however, electrical investigation of landfills posesalso challenges, both logistical and interpretational. This paper presents the results of a study conducted on adismissed landfill, close to the city of Corigliano d'Otranto, in the Apulia region (Southern Italy). The landfill is locatedin an abandoned quarry, that was subsequently re-utilized about thirty years ago as a site for urban waste disposal.The waste was thought to be more than 20 m thick, and the landfill bottom was expected to be confinedwith an HDPE (high-density poli-ethylene) liner. During the digging operations performed to build a nearby newlandfill, leachate was found, triggering an in-depth investigation including also non-invasivemethods. The principalgoal was to verify whether the leachate is indeed confined, and to what extent, by the HDPE liner.We performedboth surface electrical resistivity tomography (ERT) and mise-à-la-masse (MALM) surveys, facing the severe challengesposed by the rugged terrain of the abandoned quarry complex. A conductive body, probably associated withleachate,was found as deep as 40 mbelowthe current landfill surface i.e. at a depth much larger than the expected20 mthickness of waste. Given the logistical difficulties that limit the geometry of acquisition,we utilized syntheticforward modeling in order to confirm/dismiss interpretational hypotheses emerging from the ERT and MALM results.This integration between measurements and modeling helped narrow the alternative interpretations andstrengthened the confidence in results, confirming the effectiveness of non-invasive methods in landfill investigationand the importance of modeling in the interpretation of geophysical results.

Soil organic carbon (SOC) plays an important role in soil quality definition. In fact, soil organic matter (SOM) decline is one of the most relevant land degradation processes [1]. Therefore, an innovative methodology able to monitoring this soil property, collecting data more rapidly and economically, is needed. In this regard, remote sensing technique can open new scenarios of research. In particular, few studies have shown the capability to accurately determine SOC contents from airborne-hyperspectral sensors [2], [3], [4]. With this work we demonstrate that is possible to evaluate the Soil Organic Carbon in a test site in Apulia Region, Italy, through hyperspectral measurements by the airborne sensor CASI 1500, achieving very promising results.

Disasters impacts on urban environment are the result of interactions among natural and human systems, which are intimately linked each other. What is more, cities are directly dependent on infrastructures providing essential services (Lifeline Systems, LS). The operation of LS in ordinary conditions as well as after disasters is crucial. Among the LS, drinking water supply deserves a critical role for citizens.The present work summarizes some preliminary activities related to an ongoing EU funded research project. The main aim of the paper is to define a System Dynamic Model (SDM) to assess the evolution of resilience of a drinking water supply system in case of natural disasters, with particular attention to the role of both 'structural' and 'non-structural' parameters. Reflections are carried out on L'Aquila (Italy) case study, since drinking water infrastructures were significantly stressed during the 2009 earthquake, causing a limited functionality in the aftermath of the event. Furthermore, the reallocation of citizens in temporary shelters determined a change in the demand pattern, requiring a dynamic adaptation of the infrastructure. Based on an innovative approach to resilience, the model was developed also to simulate different emergency management scenarios, corresponding to different disaster management strategies.

The best fit of tide-gauge measurements of two monitoring stations, located along Puglia coast (Southern Italy), provided local sea level rise (LSLR) rate of 8.8 mm/y during 2000-2014 years. This local rate matches 21st and 22nd century projections of the rate of mean global sea level rise, which includes ocean thermal expansion, glaciers, polar caps, Greenland and Antarctica's ice sheets melting, and by including changes in soil water storage. Under the assumption that this sea rise rate will remain constant, an increasing of seawater intrusion will be produced into the Puglia and others Mediterranean coastal aquifers. Model simulations have been applied to the Ostuni (Puglia) groundwater in order to quantify seawater encroachment in fractured coastal aquifers due to LSLR. The model implemented the Ghyben-Herzberg's equation of freshwater/saltwater sharp interface in order to determine the amount of the decrease in groundwater discharge due to the maximum LSLR during 22nd century. Since model results have foreseen an impressive depletion (over 16%) of groundwater discharge, MAR actions have been tested to prevent the seawater intrusion. The study has confirmed the suitability of MAR for enhancing the integrated water resources availability by reducing future groundwater depletions. MAR recovered 80 L/s of groundwater as a new source of water supply during summer at the Ostuni area. Therefore, MAR can be a useful measure to mitigate the impact of climate change on coastal aquifers as a direct measure, due to reducing salt water intrusion, and as an indirect one, due to increasing water resource.

The present work summarizes the theoretical development process and the preliminary results of a research activity oriented to the definition of a Decision Support System (DSS) to be used for managing drinking water systems exposed to different hazard classes. The core of such DSS is a probabilistic vulnerability assessment tool based on Bayesian Belief Networks, mainly developed integrating expert knowledge and literature information. This vulnerability assessment tool proved able to define a reliable map of vulnerability levels for complex and interconnected infrastructures, thus helping decision-makers in the selection of the optimal strategies to respond to emergencies. The DSS is based also on the implementation of hydraulic models, both for gravity and pressurized water mains, which should provide information regarding the changes in the hydraulic behavior of the network due to a specific event or an action. A case study is described, confirming the potentialities of the proposed tool.

The Alimini water system, located in south eastern part of Italy, named Salento peninsula, is constituted from two connected coastal lakes, Alimini Piccolo and Alimini Grande. Specifically, Alimini Piccolo is a small freshwater body, directly fed by rainfall and by shallow porous aquifer through of several springs. From '50s Alimini Piccolo provides the surrounding area with water for agriculture and domestic use. In June 2013, IRSA-CNR started a study concerning the quali-quantitative characterization of the hydrogeological system feeding the Alimini Piccolo, in order to investigate the potential for additional exploiting of the lake as a resource for drinking water. For the purpose, a monitoring system has been set up for an entire hydrological year. Continuous measurements of water level, electrical conductivity and temperature, such as quantitative and qualitative monitoring monthly campaigns both in groundwater and in the lake have been carried out. In order to support the above mentioned surveys, Electrical Resistivity Tomography (ERT) has been carried out to identify geological structures and hydrogeological features, to better understand the system feeding the Alimini Piccolo and to set the boundary conditions of the hydrological model useful to represent the water balance of the lake.

The increasing concentration of CO2 and other radiative activetrace gases in the atmosphere is causing tropospherictemperatures to rise. Changes in other climatic featuressuch as precipitation, cloudiness, humidity, and windinessare likely to follow changes in temperature. Such changescould have deep implications for hydrologic processes in generaland for water availability to sustain both rain-fed andirrigated agriculture, in particular.Evapotranspiration (ET) is the compound term describingthe physical processes of water transfer into the atmosphereby evaporation from soil and transpiration through vegetation;ET constitutes an important component of hydrologicalbalance particularly in semi-arid and sub-humid climates.Evapotranspiration is determined by various mathematicalmodels using climatic factors such as temperature, radiation,humidity, and wind speed, while its direct measurement isseldom available in experimental fields.A relatively new technology using on remote sensing to retrieveland surface parameters such as surface temperature,albedo and vegetation indices - which are indispensable to remotelysensed ET models - is adopted here to map regional,meso- and macro-scale patterns of ET at the earth's surfacein a globally consistent and economically feasible manner.The aim of our research is to assess a technique to retrieveET maps from remote sensing images by the combination oftwo different procedures. The first one, known as trianglemethod, computes the evapotranspiration fraction (EF) de-fined as the ratio LE/Rn, where Rn is the net radiation atthe surface and LE is the latent heat flux. LE is directly proportionalto ET. In order to retrieve LE, and consequentlythe surface evapotranspiration, a second procedure computesthe net radiation of the investigated area. Therefore, by inversion,it is possible to obtain an estimate of the ET.The validation of these variables, the net radiation and ofthe evapotranspiration derived from MODIS data, has beenundertaken on the Capitanata area, Southern Italy, by comparisonof model results with in-situ measurements providedby the Consorzio per la Bonifica della Capitanata di Foggia.

Water resources management is often characterized by conflicts in many arid and semi-arid regions, where agriculture is the main user of groundwater (GW). Conflicts could arise among different decision-makers and stakeholders. Moreover, different policies can interact each other hampering or facilitating their implementation and effectiveness. This contribution describes a new implementation of GeSAP, an integrated modelling tool for enabling local GW management by combining the need for GW protection with socio-economic and behavioural determinants of GW use. GeSAP is based on the involvement of multiple stakeholders and the use of Bayesian Belief Networks (BBN) to simulate and explore their attitude relative to GW exploitation and their responses to the introduction of new protection and agricultural policies. In this work, GeSAP was implemented in the area of the Capitanata Irrigation Users Organization, located in the Apulia region (southern Italy). It was used to simulate the reactions of the main stakeholders involved in GW protection policy implementation and to assess the policy's effectiveness in terms of actual reduction of GW exploitation. Furthermore, the interactions between the GW protection policy and the coming reform of the Common Agricultural Policy (CAP) was investigated. The results of the application proved the capability of the GeSAP tool to assess the actual effectiveness of GW protection policy by investigating how far this policy could be considered acceptable by farmers. In addition, this study demonstrates how the effectiveness of the GW protection policy could be affected by the interaction with the CAP reform. The latter could strongly impact the balance between water demand and availability with the effect of ifying the positive synergy between CAP and GW protection policy. Although water management issues are not explicitly mentioned among the main scopes of the CAP, this work clearly demonstrates the impact that such policy could have on farmers' decisions on water use

This study was conducted on an irrigated area of southern Italy to analyze the current operation of a large-scale irrigation delivery system and the effects of the operation procedures on crop irrigation management and aquifer salinity increase. The area is characterized by relatively high levels of groundwater salinity in the summer that are probably due to intensive groundwater pumping by farmers during periods of peak irrigation demand, with the resulting seawater intrusion. Two alternative delivery schedules, namely the rotation delivery schedule and the flexible delivery schedule, referred to as RDS and FDS, respectively, were simulated using a soil-water balance model under different combinations of crop, soil and climatic conditions. The first set of simulations concerned the farm irrigation management constrained by the rotational delivery used by the local water management organization. The second scenario simulated the farm irrigation schedule most commonly used by growers in the area for maximizing crop yields. Based on crop irrigation management under RDS and FDS, two alternative operational scenarios were also developed at the scheme level and then compared for evaluation. Winter and summer salinity maps of the aquifer were developed by interpolating salinity measurements of the groundwater samples collected during the 2006 irrigation season. From these maps, a close relationship can be inferred among delivery schedule, aquifer exploitation and salinity increase, which justifies the need for implementing FDS that might reduce the groundwater demand for irrigation.

Empirical investigations in scientific literature have highlighted the differences between stakeholders' perceptions on the severity of a given drought phenomenon and on results out of scientific - technical evaluations. This means that there can be several perceptions over the phenomenon as well as different scientific models to be used in order to assess the drought's severity which itself does not consider such differences. Facing a drought phenomenon, stakeholders adopt different rnental models to assess its severity, taking into account additional elements, other than just water availability and climatic conditions. At turn, this could have a strong negative impact on the effectiveness of strategies for drought mitigation. In fact, if mitigation actions were selected without considering stakeholders' perceptions over the drought, then, the actions themselves would be considered as unsatisfactory by the stakeholders or, even worst, not acceptable at ali. If the degree of acceptability was low, then stakeholders would strongly hamper the implementation of mitigation actions. Therefore, an in depth analysis of potential conflicts and the definition of effective negotiation strategies should be useful. By this perspective, we propose a methodology based on a Fuzzy Cognitive Map (FCM) to support the elicitation and the analysis of stakeholders' perceptions over the drought and the analysis of potential conflicts. The method has been applied to a drought management process in the area nearby the Trasimeno Lake (located in the Region of Umbria) in order to analyze potential conflict.

In this study, we report the adopted methodology used in GRASS, a free open-source GIS software, which has allowed us to map surface water thermal anomalies and, consequently, to identify and locate coastal inflows in the Mar Piccolo sea (Taranto) part of the National Priority List site identified by the National Program of Environmental Remediation and Restoration. An ongoing work, where to apply the same procedure, is being carried out on Bari province coast and effimeral streams.

L'IRSA-CNR ha svolto attività di ricerca per la definizione di una metodologia di stima della vulnerabilità delle infrastrutture di approvvigionamento idropotabile, esposti a eventi calamitosi, nell'ambito di un Accordo quadro con il Dipartimento Nazionale della Protezione Civile. Tale stima viene effettuata in maniera probabilistica con una modellistica basata sulle reti Bayesiane (BBNs), in funzione delle caratteristiche strutturali, ambientali ed operative degli elementi. La metodologia si traduce in un sistema di supporto alle decisioni (DSS) capace di integrare e gestire le informazioni disponibili, per fornire ai decisori indicazioni sulle procedure da adottare nella gestione di reti acquedottistiche in emergenza. Nell'ambito del DSS è stato realizzato il tool G-Net, che aggiunge la componente GIS con la duplice funzione di elaborare i dati di input per il modello di vulnerabilità (gestito dal sw Netica(TM)) e di visualizzare i risultati in termini di cartografia. È stato sviluppato in Python in modalità loosely-coupled con Netica, per fornire una dimensione spaziale al DSS e migliorarne l'efficacia. La preparazione dei dati di input del modello prevede una caratterizzazione completa degli elementi dell'infrastruttura, ottenuta mediante analisi spaziale utilizzando interfacce personalizzate che ne automatizzano la procedura. G-Net è stato testato in vari casi di studio esposti a calamità (ad es. L'Aquila).

La conoscenza della quantità di carbonio organico nel suolo (SOM - Soil Organic Matter) puòessere di notevole aiuto nel pianificare le attività per la gestione sostenibile dei sistemi agricolifinalizzate sia all'aumento della produttività sia alla riduzione del rischio di degrado ambientale(processi di desertificazione). Negli ultimi anni pertanto, sono state messe a punto diversemetodologie per il monitoraggio di questo parametro. Tra queste la spettroscopia nel visibile evicino infrarosso, a scala di laboratorio, di campo e da remoto, si è rivelata uno strumentoparticolarmente efficace anche in relazione alle analisi chimiche tradizionali.In questo lavoro, tramite acquisizioni iperspettrali da aereo effettuate con il sensore CASI 1500, èstata valutata l'efficacia del telerilevamento nel monitoraggio del SOM. A tal fine due sorvoli hannopermesso di ottenere immagini pre e post trattamento di un sito degradato (con ridotto contenuto diSOM) in provincia di Taranto, arricchito in sostanza organica (spandimento di compost).Contestualmente ai sorvoli, sono state effettuate misure radiometriche al terreno e sono statiprelevati campioni di suolo successivamente analizzati in laboratorio per il contenuto in SOM.Dalla correlazione tra le analisi chimiche, la radiometria di campo e la classificazione delleimmagini è stata prodotta una mappa tematica che rappresenta la distribuzione della concentrazionedi SOM nel sito di indagine. I risultati preliminari sono incoraggianti e mostrano una rispostasignificativa dello metodologia utilizzata nel rilevare carbonio organico nel suolo, suggerendo chele tecniche di telerilevamento possono rappresentare uno strumento e adeguato per il monitoraggiodel SOM rapido ed efficace su scala locale.

The aim of this paper is to explore the effects and linkages between snow cover areas, distribution, probability and measured water discharge along east Mediterranean coastal watershed using moderate-resolution satellite images (MODIS-Terra). The Nahr Ibrahim River is a typical Lebanese watershed with an area of 326 km2 stretching between the sea and mountainous terrain to the east. The largest snow cover often exists in January-February with snow-free conditions between June and November. Image analysis enabled to analyze the temporal variability of the mean and maximum monthly areas of snow cover between 2000 and 2013. Snow cover dynamics were compared with the discharge from main springs (Afqa and Rouaiss) feeding the river and the probability of snow cover was estimated. The mean monthly snow cover, snow melting rates and springs discharge were found to be in direct relationship. In addition, the measured water discharge at the river mouth was found to be higher than the discharge of the two main feeding springs. This indicates a contribution of groundwater to the stream flow, which is again in direct connection with snow melting at the upper bordering slopes and probably from neighboring watersheds.Considering the characteristics of the mountainous rocks (i.e. Sinkholes, fissured and karstified limestone), the pedo-climatic and land cover conditions affect the hydrological regime which is directly responding to the area and temporal distribution of snow cover, which appears after two months from snowing events. This is reflected on water productivity and related disciplines (Agricultural yield, floods). This study highlights the potential of satellite snow detection over thewatershed to estimate snow cover duration curve, forecast the stream flow regime and volume for better water management and flood risk preparedness.

The role of monitoring is changing due to the increasing awareness of complexity and uncertainty in environmental resources management. Monitoring systems are required to support critical reflection about the effectiveness of actions toward the achievement of management objectives. To this aim, monitoring should be based on a strong integrated and multi-scale approach. Monitoring costs could be prohibitive if the monitoring is only based on traditional scientific methods of measurements. To deal with these issues, the design of an innovative monitoring system should be based on the integration between different sources of knowledge and information. In this work the usability of local knowledge to support environmental monitoring is investigated. A multi-step participatory monitoring design process has been implemented aiming to design a program for soil salinity monitoring in the lower Amudarya river basin in Uzbekistan. Although there is an increasing awareness of the importance of stakeholders being involved in decision processes, the current socio - cultural and institutional context is not favourable to the participatory approach. The choice of method to be implemented in this work was influenced by such conditions. The analysis of the lessons learned from the experiences gained in this project revealed some important clues concerning the development of a locally-based monitoring program. These lessons can be subdivided according to three fundamental issues: the long term involvement of local community members in monitoring activities, the acceptance of locally-based monitoring systems by decision makers, and the reliability of monitoring information.

Water, a precious and valuable natural resource in the Middle East, is a limiting factor for its development. The possible climate alterations likely to impact the Region with increasing global air temperatures and changing in precipitation patterns would lead to a sensible modification of hydrological processes at regional and local scales. Analyzing the potential impacts of climatic changes is an important step toward adaptation and mitigation especially for countries with vulnerable water resources. The objective of this study is to develop basin scale climate change scenarios (CCS) for a coastal watershed in Lebanon, Nahr Ibrahim watershed (NIW), which is representative of the snow-melt dominated watersheds located in Mount Lebanon (the so called water tower of the Middle East). This is the main objective of the biennial research programme 2012-2013 for "Modelling Water Balance Using Remotely Sensed Data" funded under the Scientific Cooperation between the National Research Council of Italy (CNR) and the National Council for Scientific Research of Lebanon (CNRS-L). To this end the regional climate model PRECIS (Providing Regional Climates for Impact Studies) developed by Hadley Centre of U.K. was adopted as a dynamic downscaling of a global climate model (GCM) thus providing spatially detailed projections and scenarios of future climate over the area of interest at a resolution of about 25x25 km. Daily simulations for precipitation (P), maximum and minimum temperature (Tmax, Tmin) from PRECIS were adopted to evaluate the impact of climate change on the water balance of the NIW by taking into account the time series for the recent past (1980-2000), the present (2001-2011), the near future (2012-2032) and the distant future (2080-2098) and comparing them with the available climate observations in order to assess the possible future variation in precipitation and temperature. The available stations' observations were also used to derive monthly regressions between climate and topographic elevations to be adopted as a simple interpolation tool to estimate the spatial distribution of T and P in NIW. Changes in climate variables resulted significant for the near future only for T while in the distant future, both P and T showed respectively remarkable decrease and increase. These alterations will correspond to a decrease in snow-covered area and anticipated snow-melt thus altering the water balance of NIW both in terms of mean values and variability. To simulate the impacts on stream flow regimes, basin scale CCS were coupled with a conceptual water balance model named NIWaB that was previously developed and calibrated. A consistent module of the model was developed to capture the space-time dynamics of the snow cover and snowmelt contribution. Such computations allowed to assess the possible climate change impacts on the hydrological signature of NIW which resulted strongly influenced by a shorter snowy period and a consequent enhanced seasonality

Within the recent EU Water Framework Directive and the modification introduced into national water-related legislation, monitoring assumes great importance in the frame of territorial managerial activities. Recently, a number of public environmental agencies have invested resources in planning improvements to existing monitoring networks. In effect, many reasons justify having a monitoring network that is optimally arranged in the territory of interest. In fact, modest or sparse coverage of the monitored area or redundancies and clustering of monitoring locations often make it impossible to provide the manager with sufficient knowledge for decision-making processes. The above mentioned are typical cases requiring optimal redesign of the whole network; fortunately, using appropriate stochastic or deterministic methods, it is possible to rearrange the existing network by eliminating, adding, or moving monitoring locations and producing the optimal arrangement with regard to specific managerial objectives. This paper describes a new software application, MSANOS, containing some spatial optimization methods selected as the most effective among those reported in literature. In the following, it is shown that MSANOS is actually able to carry out a complete redesign of an existing monitoring network in either the addition or the reduction sense. Both model-based and design-based objective functions have been embedded in the software with the option of choosing, case by case, the most suitable with regard to the available information and the managerial optimization objectives. Finally, two applications for testing the goodness of an existing monitoring network and the optimal reduction of an existing groundwater-level monitoring network of the aquifer of Tavoliere located in Apulia (South Italy), constrained to limit the information loss, are presented.

Within recent WFD and the modification introduced into national water related legislation, monitoring assumes great importance in the frame of territorial managerial activities. Recently, a number of public environmental agencies invested resources in planning improvements on existing monitoring networks. A lot of reasons justify the optimal redesign of a monitoring network. In fact, a modest or sparse coverage of the monitored area or redundancies and clustering of monitoring locations often make impossible to provide the manager with a sufficient knowledge for decision-making processes. These are typical cases requiring an optimal redesign of the whole network; particular emphasis shall be devoted to quality groundwater monitoring network. Using reliable stochastic or deterministic methods, it is possible to rearrange the existing network by eliminating, adding or moving monitoring locations producing the most uniform arrangement among any possible. In this paper, some spatial optimization methods have been selected as more effective among those reported in literature and implemented in a software able to carry out a complete redesign of an existing monitoring network. Both stochastic and deterministic methods have been embedded in the software with the option of choosing, case by case, the most suitable with regard to the available information. Finally, an application to the existing regional groundwater level monitoring network of the aquifer of Tavoliere located in Apulia (South Italy) is presented.

The infiltration process into the soil is generally modeled by the Richards' partial differential equation (PDE). Inthis paper a new approach for modeling the infiltration process through the interface of two different soils isproposed, where the interface is seen as a discontinuity surface defined by suitable state variables. Thus, theoriginal 1D Richards' PDE, enriched by a particular choice of the boundary conditions, is first approximated bymeans of a time semidiscretization, that is by means of the transversal method of lines (TMOL). In such a way asequence of discontinuous initial value problems, described by a sequence of second order differential systems inthe space variable, is derived. Then, Filippov theory on discontinuous dynamical systems may be applied inorder to study the relevant dynamics of the problem. The numerical integration of the semidiscretized differ-ential system will be performed by using a one-step method, which employs an event driven procedure to locatethe discontinuity surface and to adequately change the vector field.

Here a numerical technique based on the method of lines (MoL) for solving Richards' equation is presented. The Richards' equation deals with modeling infiltration of water into the unsaturated zone. By means of any kind of observations, some values of the state variable are assumed to be available at certain time points, in order to "correct" the numerical solution in the light of these observations. This is done by means of ensemble Kalman filter (EnKF), that is a data assimilation technique based on a Monte Carlo approach. Advantages of this approach are discussed, in the light of existing bibliography.

Modern intensive agriculture justified by the need to support the food requirement of an always growing population, because of the heavy use of agrochemicals, has revealed in many cases to be responsible for surface and groundwater pollution. In this paper, the problems of water and, in particular of groundwater pollution from agricultural nitrates are dealt, with reference to a sub-basin, located in southern Portugal, of river Guadiana, where olive groves and winter wheat are the most common crops. The study area suffers problems related to water availability from one year to another and, for this reason many reservoirs were recently built in the area. In the last few years the resulting greater water availability is causing a shift towards modern intensive agricultural production methods with a consequent, possible water quality deterioration. This is the reason why some BMP scenarios, aimed at reducing the impacts of agriculture on groundwater have been adjusted and their effect in terms of kg/ha of leached NO3 have been estimated using the simulation model GLEAMS. The irrigation water consumption referred to each scenario was also calculated. The load of leached nitrates and the water consumption from the whole area, with reference to each scenario were then merged within a unique synthetic index that summarizes in one number the suitability of that scenario at reducing both nitrate leaching and water consumption.Among the most interesting conclusions is the fact that, in the hypothesis of optimal agricultural management, modern intensive olive grove not always results to be responsible for a higher NO3 leaching in comparison to the traditional ones and could, for this reason, be considered in itself a way to perform a sustainable agriculture.