With agricultural activities being the main driver of freshwater consumption worldwide, a simplified but robust approach providing local scale, real-time crop water demand estimations could meet the needs of both water managers and farmers, especially under rapidly changing climate. We investigated the effectiveness of Benfratello’s water balance and of Melisenda’s aridity index at classifying the Mediterranean climate of the Capitanata agricultural district (Southern Italy), based on the existing and future (RCP 4.5 and RCP 8.5) climatic and agricultural water demands quantified with Thornthwaite’s approach and the FAO56 procedure, respectively. The results showed an increase in aridity under RCP 8.5 when determined with Thornthwaite’s approach, while in case of FAO56 procedure the crop selection seemed to partly compensate the future water demand. The use of Benfratello’s method and of Melisenda’s index proved able at unveiling meaningful aspects of the capability of the crop choice at mitigating the effects of local aridity.

Mediterranean coastal areas are prone and increasingly exposed to hydrological stress driven by water scarcity, climate change, increasing agricultural pressure, groundwater exploitation, and water quality degradation. These drivers manifest differently across regions but often result in common challenges and issues such as salinization, saltwater intrusion, and competition between agricultural and domestic or industrial water uses, thus impacting water management in irrigation districts. In this context, the AI4Water PRIMA project investigates hydrological issues and water management challenges in four Mediterranean coastal irrigation districts and aims to apply Artificial Intelligence optimization and prediction techniques to improve water management. The four study areas are the Ras Jebel Coastal area (Tunisia), the Coastal Constantinois and Seybouse Basins (Algeria), the Capitanata Irrigation District (Italy), and the Nile Delta Basin (Egypt). Although these areas are all located in the Mediterranean region, they differ in population (from 50 thousands up to 3.5 million people), hydrogeological characteristics, water sources, irrigation practices, and water management policies. This contribution, after introducing the AI4Water project, presents a preliminary comparison of the main hydrological and irrigation issues in the selected case studies, with a broader Mediterranean perspective. The comparison highlights both shared vulnerabilities and site-specific drivers of hydrological stress, emphasizing the need for context-dependent management strategies. By framing the different case studies within a common perspective, the project provides a basis for cross-district comparison and discussion, supporting the development of adaptive and transferable water management approaches for Mediterranean coastal systems. This comparative approach is intended to stimulate discussion and critical feedback from the scientific community working on similar or related case studies.

Glaciers are dynamic systems of snow and ice that accumulate and melt, producing a wide range of sounds associated with morphodynamic and hydrological processes, such as their deformation and movement, melting and refreezing cycles, and ice collapse. The USIE (Un Suono In Estinzione) project leverages sound analysis to investigate Alpine glacier evolution and to raise awareness of climate change impacts. Through a multidisciplinary approach, the project aims to advance scientific research in alpine glacier hydrology while creating artistic performances and installations, both relying on the same dataset of recorded sounds. Such approach can be classified as STEAM, as it integrates Scientific research, Technology, Engineering, Art, and Mathematics, incorporating into the classical STEM aspect, typical of classical hydrological and cryospheric sciences, the perceptual and emotional dimensions typical of sound arts. Between 2021 and 2023, over 14’000 hours of acoustic data were collected on the Adamello Glacier using five bioacoustic recorders, suitable for long-term outdoor deployment, placed in strategic locations, such as crevasses and meltwater streams. For the same years, a spatially distributed energy and mass balance model (the PDSLIM model) has been used to compute surface melting and runoff at the sound recorders locations. In order to capture the daily variability of surface melting, the model requires hourly temporal resolution meteorological input data. Here, we show how the acoustic monitoring can be used for the validation of the PDSLIM surface melting model. We show how the sound pressure level daily variability reveals insights about timing of snow and ice melting cycles and the hydrological response of the glacier, highlighting seasonal and daily patterns. Through this innovative approach, we investigate the potential of acoustics as a complementary tool for advancing cryospheric and hydrological science while emotionally communicating the critical conditions of alpine glaciers.

Several optimisation models have been applied for optimising reservoir operations throughout the past decades. However, due to the limitations of each approach, the complexity of the system, and the conflict of combining purposes, reservoir operation evaluation and improvement remain classical. In this study, we apply a Genetic Algorithm model to generate a trade-off curve that presents alternative optimal strategies for the Hoa Binh reservoir in Vietnam. The study focuses on two goals: downstream water demand in the Red River Delta (RRD) and hydropower production in the dry season. Even though water availability in RRD is projected to be more plentiful until the mid-century, drought duration and intensity are also expected to increase. Thus, developing effective operation rules during the dry season is crucial for water security and the regional economy. The findings indicate that an optimised regulation can be developed to close the imbalance between water supply and demand while maintaining a high rate of energy generation. The optimisation criteria will also preliminarily consider the impact of the sediment transport reduction induced by trapping sediments generated by reservoirs: the enhanced erosion capacity of more clear streamflow water causes scouring of the riverbed, thus requiring more water release to meet the irrigation demand at the intake of the irrigation channels. In the future, reservoir management policies might also need to integrate the geomorphological changes induced by climatic and anthropic factors.

In this paper, the second longest time series of daily hydrometric levels and streamflow for an Italian river, Adige, in the Italian Alps, also one of the longest worldwide and unpublished so far, is reconstructed and analyzed. Daily streamflow prior to 1923, when the official mean daily discharge was first published, is estimated based on daily water levels collected since January 1862, cross-section geometry, discharge, and surface velocity measurements at the hydrometric station of Trento. The main objective of this paper is the identification, attribution, and quantification of the impact of natural and anthropic factors on changes in streamflow in a mountain region with marked orographic and climatic gradients. The resulting 161-year-long time series, until December 2022, for this 9763 km2 catchment is firstly analyzed in search of trends and their statistical significance, spectral properties at different time scales and periods, changes in the monthly regime prior to and after the constructions of reservoirs. The observed -1.0 mm year-1 slope of the annual streamflow linear trendline is statistically significant and indicates a decline of -1.4% per decade of available streamflow in the river, similar to the one observed in nearby basins. The spectral analysis conducted with the wavelet transform indicates that a sudden change of spectral properties and trends of daily streamflow occurred inside the pre- and post-reservoir construction period and can be explained also as a result of a more environment-oriented legislation. A wavelet coherence spectrum between streamflow and teleconnection indices indicates the existence of a significant coherence with the Atlantic Multidecadal Oscillation only. The comparison with estimated actual reference evapotranspiration losses and temperature points out that the observed temperature increase is not sufficient to explain the observed hydrological losses, being precipitation almost constant over the observation period. The observed increase of 86 mm of hydrological losses over the last century is explained in terms of water withdrawals for agricultural, civil, and industrial needs (38 mm), enhanced evapotranspiration due to temperature increase (30 mm), expanded artificial lakes' surface (1 mm), the residual of 17 mm being attributed to land-use changes with afforestation.

Water resource management in hydrological systems, particularly those involving reservoirs, is complex due to their dynamic and interconnected nature. Traditional approaches often struggle to adapt to changing conditions, resulting in suboptimal utilization and limited resilience to unexpected scenarios. This research investigates the application of AI-driven planning to enhance adaptive management strategies for such systems. This study focuses on the development and simulation of models capturing the dynamics and constraints of reservoir-based hydrological systems. These models can also be employed by automated planners to simulate system behavior. The approach is illustrated through a case study on Vietnam’s Red River Basin, demonstrating its feasibility and effectiveness. The results highlight the potential of AI planning to efficiently navigate decision spaces and derive robust management policies.

High Mountain Asia (HMA), including the Hindu Kush-Karakoram Himalayas (HKH) is one of the world's key "water towers", with the resources supporting hundreds of millions of people. Currently, this region is experiencing significant demographic and socio-economic growth. Reliable hydrological projections of the future supply of water resources are essential, given the likelihood that water resources demand will continue to increase. In this study, CORDEX South Asia (CORDEX-WAS44) regional climate models (RCMs) and the Physically Based Distributed Snow Land and Ice Model, that was calibrated with hourly meteorological data and daily runoff over eight years of monitoring period, are employed in the Naltar catchment located in the Hunza river basin, Upper Indus Basin, Pakistan to project glacio-hydrological regimes in the future climate. For each of the CORDEX-WAS44 simulations, climate change signals for near future (2040-2059) and far future (2080-2099) under three Representative Concentration Pathways (RCPs) namely RCP2.6, RCP4.5, and RCP8.5 are presented with respect to the corresponding present climate (1991-2010). Results show overall significant increases in mean temperature between (+0.9 to + 6.0 degrees C, depending upon the scenario) and total precipitation (+6 to + 29 %) from April to September by the end of the century for RCP2.6, RCP4.5, and RCP8.5. The projected simulations of energy and mass balance indicate that snow and ice melt rate will increase consistently in both future periods with an earlier timing of the snowmelt as it appears in June in the near future (2040-2059) and in May in the far future (2080-2099) under the high emission scenario (RCP8.5). The increase in temperature, precipitation and winter snowpack changes are also expected to have a substantial impact on the hydrological regime in the Naltar catchment, with a peak flow occurring one to two months earlier and a total by 2090 and a decrease of total runoff in the monsoon season by -3 to -24 % in the near and far future, respectively, under RCP 8.5 scenario and more neutral changes (-2 to + 3 %) according to RCP 4.5. Based on these results and the discussion above, water availability in the Naltar catchment will be uncertain by the end of the century.

The Adamello Glacier, a rare example of a summit glacier in the Italian Alps, is undergoing profound transformations since the beginning of the century, with a substantial reduction in its surface area. Between 1995 and 2009, the net surface mass balance displayed an average decrease of -1439 mm w.e. per year. We analyze the retreat of the Adamello Glacier through diverse prospectives, discussing trends and variability in in-situ observations and remotely sensed images, and modelling its mass balance in the current and future climate. Firstly, we show the areal retreat of the glacierized area studied by means of satellite images (Landsat), obtaining an areal retreat of 11% every decade since 2007. Secondly, we present the timeseries of temperature and precipitation measured at nearby high elevation meteorological stations. Significant increasing trends are found in temperature, especially in the summer period (+0.8°C every decade since 1996). Accumulation variability and trends are also discussed, drawing insights from snow water equivalent measurements systematically collected since 1967, revealing concerning spring trends with a 5-6% decrease in water equivalent every decade on April 1, and no significant trends in winter. Thirdly, by means of the Physical based Distributed Snow Land and Ice Model (PDSLIM), validated by ablation measurements collected in August 2023, we compute the distributed surface mass balance of the Adamello glacier for the period 2010-2023, obtaining an average net mass balance of -2170 mm w.e., significantly larger than in the period 1995-2009. Finally, in order to assess the future evolution of the glacier, we make use of regional climate models (RCMs) simulations of the future climate conditions developed in the framework of the CORDEX experiment for different emission scenarios. Our results highlight the critical conditions the Adamello Glacier is experiencing nowadays, quantifying the surface mass balance in the current climate, and estimate its expected behavior by the end of the century considering different emission scenarios.

A climatology of snow water equivalent (SWE) based on data collected at 240 gauging sites was performed for the Italian Alps over the 1967–2020 period, when Enel routinely conducted snow depth and density measurements with homogeneous methods. Six hydrological sub-regions were investigated spanning from the eastern Alps to the western Alps at altitudes ranging from 1000 to 3000 m a.s.l. Measurements were conducted at fixed dates at the beginning of each month from 1 February to 1 June and on 15 April. To our knowledge, this is the most comprehensive and homogeneous dataset of measured snow depth and density for the Italian Alps. Significant decreasing trends over the years at all fixed dates and elevation classes were identified for both snow depth, equal to −0.12 ± 0.06 m per decade, and snow water equivalent, equal to −51 ± 37 mm per decade, on average in the six macro-basins we selected. The analysis of bulk snow density data showed a temporal evolution along the snow accumulation and melt season, but no altitudinal trends were found. A Moving Average and Running Trend Analysis (MARTA triangles), combined with a Pettitt's test change-point detection, highlighted a decreasing change of snow climatology occurring around the end of the 1980s. The comparison with winter temperature and precipitation data from the HISTALP dataset identified a major role played by temperature on the long-term decrease and changing points of snow depth and SWE with respect to precipitation, mainly responsible for its variability. Correlation with climatic indexes indicates significant negative values of the Pearson correlation coefficient with winter North Atlantic Oscillation (NAO) and positive values with winter Western Mediterranean Oscillation (WeMO) for some areas and elevation classes. Results of this climatology are synthesized in a temporal polynomial model that is useful for climatological studies and water resources management in mountain areas.

The research aims to investigate the spatiotemporal changes in water balance components and distinguish the relative impacts of climatic data and land-use on groundwater levels in northeastern Iran. This investigation employs the WetSpass-M model to estimate water balance and the Mann-Kendall test alongside Sen's slope estimator to evaluate the trend. The study also assesses mean annual water balance components, considering diverse combinations of land use and soil. The findings offer a hydrological insight revealing that 14% of precipitation results in runoff, 29% of that recharging the aquifer; the remaining portion is lost through evapotranspiration. The trends in precipitation and simulated water components are not significant but a significant downward trend in groundwater is observed beyond a specific point in time. Based on this outcome, as well as the analysis of land-use changes, it was speculated that human activities in this fast-developing region might be implicated in the decline in groundwater levels. Analysis of water balance components in various soil and land-use combinations indicates that evapotranspiration exhibits greater variability within the land-cover class, while recharge is more influenced by soil texture. These findings enhance our understanding of identifying potential sites for artificial recharge and determining sustainable groundwater withdrawals based on spatiotemporal recharge patterns.

Energy balance distributed modelling in High Mountain Asia (HMA) is important to examine glaciological and hydrological processes and assess changes in streamflow in the current and future climate. In this study, the Physically based Distributed Snow Land and Ice Model (PDSLIM) using detailed observed meteorological data at hourly scale is employed to simulate the hydrological response of the Naltar catchment, 242.62 km2 in size, (in the Karakoram region in Pakistan to simulate its glaciers' mass balance as well as daily runoff. The results exhibited overall satisfactory performance in terms of coefficient of determination (R2 = 0.96) and Nash-Sutcliffe Efficiency (NSE=0.95) modelled against satellite-based snow cover areas, for internal model verification, in eight years. The results of runoff simulations compared for external model verification, with observed daily discharge resulted in NSE 0.90 and 0.89 for calibration and validation period respectively. Flow composition analysis revealed that the streamflow regime of Naltar catchment is composed to 40 % by glacier runoff, 42 % by subsurface runoff and 18 % by surface runoff. The eight year mean value of net mass balance exhibited a slightly negative mass balance (-0.810 +/- 0.31 m w.e. a(-1)) less pronounced than that observed globally in several continental glaciers distinct from the Greenland and Antarctic ice sheets in the current climate. It seems that the 'Karakoram anomaly', i.e. the balanced to slightly positive glacier budgets observed in the region in the recent decades, a unique dynamics worldwide, has a moderate impact in the central Karakoram. Overall, the distributed energy-balance model PDSLIM, so far tested in the Alps, results to be a suitable tool to estimate energy and mass balance in the glacierized catchments of Karakoram and Himalaya and to better understand snow and ice melt runoff dynamics and floods in highly complex and glacierized mountain basins in the current and, in our research perspective, in the future climate.

Maggioni S., Astolfi A., Baroni C., Carton A., Casarotto C., Colosio P., Degani A., Ferrari C., Lendvai A., Smiraglia C., Tedesco M. Ranzi R., Un Suono In Estinzione (USIE): a STEAM project for capturing and preserving the sounds of glaciers. (IT ISSN 0391-9838, 2024). Glaciers are dynamic systems of snow and ice that accumulate and melt, producing a wide range of sounds associated with morphodynamic and hydrological processes, such as their deformation and movement, melting and refreezing cycles, and ice collapse. The USIE (Un Suono In Estinzione) project leverages sound analysis to investigate Alpine glacier evolution and to raise awareness of climate change impacts. Through a multidisciplinary approach, the project aims to advance scientific research in alpine glacier hydrology while creating artistic performances and installations, both relying on the same dataset of recorded sounds. Such an approach can be classified as STEAM, as it integrates Scientific research, Technology, Engineering, Art, and Mathematics, incorporating into the classical STEM aspect, typical of classical hydrological and cryospheric sciences, the perceptual and emotional dimensions typical of sound arts. Between 2021 and 2023, over 14,000 hours of acoustic data were collected on the Adamello Glacier using five bioacoustic recorders, suitable for long-term outdoor deployment, placed in strategic locations, such as crevasses and meltwater streams. For the same years, the spatially distributed energy and mass balance Physically based Distributed Snow Land and Ice Model (PDSLIM) model has been used to compute surface melting and runoff at the sound recorders' locations. In order to capture the daily variability of surface melting, the model requires hourly temporal resolution meteorological input data. Here, we show how acoustic monitoring can be used for the calibration and validation of the surface melting model. We show how the sound pressure daily variability reveals insights about timing and amplitude of snow and ice melting cycles and the hydrological response of the glacier, highlighting seasonal and daily patterns. Through this innovative approach, we investigate the potential of acoustics as a complementary tool for advancing cryospheric and hydrological science while emotionally communicating the critical conditions of alpine glaciers.

<p>Reservoir operation is a complicated problem to cope with regarding the complexities and the conflicts among the different stakeholders interest. The study presents the set of operating policies for a multi-purpose reservoir, case study of Hoa Binh reservoir, Viet Nam, focusing on two main objectives: Hydropower and Irrigation demand in the dry season, when the other main target, i.e. the flood control, is less crucial. In addition, another environmental objective under consideration for the dry season is the discharge needed to limit the salinity intrusion into the Red river delta surface water. This is a somehow novel objective to be taken into account when climate change scenarios, observed and projected sea level rise and saline intrusion are considered. The weight of this objective compared to the other ones can be set according to the policy adopted. The study is based on an evolutionary algorithm, namely Genetic Algorithm (GA) to find a Pareto optimal set under different scenarios. The results offer more flexible policies where the reservoir operator may see the trade-off between objectives to decide which is more suitable with the instant interest. Finally, it is shown that the GA model is promising to improve the performance of reservoir operation compared to strict regulations, which are now applied.</p>

In recent years, saltwater intrusion in river estuaries has become more severe and frequent worldwide. The common reasons lie in increasing freshwater withdrawal, river flow regulation and sea level rise due to global warming. In particular, the Red River Delta in northern Vietnam is facing a strong population growth worsening the pressure on freshwater resources for drinking water and irrigation needs. During the dry season, increasing conflicts and constraints in freshwater availability have already been experienced. Adverse combinations of river flow regulations and high sea levels lead to severe upstream propagations of salinity. This study takes advantage of a statistical characterization of discharges released from Hoa Binh reservoir and observed at Son Tay station, the main river flow control upstream of the river delta, along with downscaled and updated sea level rise scenarios to estimate the future extents of saltwater intrusion under different options of water release from reservoirs in the dry season. To do so, a 1D hydraulic model of the river delta network was implemented using MIKE11 software. The hydraulic and the quality modules were calibrated and validated with respect to the present scenario by using water stages and salinity concentrations observed in estuary branches. Sea level rise projections for 2050 and 2100 referred to RCP4.5 and RCP8.5 AR5 emission scenarios were then considered. Results show that river flow regulation can provide an effective mitigation measure. A 20-30% increase in the discharge released from the Son Tay station would be beneficial to push downstream the saltwater intrusion in the main Red River branch during the dry season. For instance, in 2050 the 1%0 salt concentration front is expected to be pushed back at least 6 km when the exceeding probability of the discharge released by Son Tay station decreases from 95% to 25%.

<p>Benfratello's Contribution to the study of the water balance of an agricultural soil (<em>Contributo allo studio del bilancio idrologico del terreno agrario</em>) was firstly published in 1961. The paper provides a practical conceptual and lumped method to determine the irrigation deficit in agricultural districts, and it generalizes previous Thornthwaite (1948) and Thornthwaite and Mather (1955) water balances thanks to the application of the dimensionless approach introduced by De Varennes e Mendonça (1958). Since then, it has been used in many areas in Southern Italy. It is our opinion that, due to its simplicity and to the small number of required parameters, Benfratello's method could be regarded to as an effective tool to assess the effects of climatic, landuse and anthropogenic changes on the soil water balance and on the irrigation deficit.</p> <p>In previous contributions we presented (i) a GIS—based application of Benfratello's method to the case study of the semiarid Capitanata plane (4550 km<sup>2</sup>), one of the most important agricultural districts in Italy, and (ii) a theoretical development of the method that allows to simply estimate in closed form the uncertainity of the calculated irrigation deficit, once known the interannual variability of the required climatic variables (air temperature and precipitation). In this contribution we present the results obtained by applying the GIS—based Benfratello framework to estimate the irrigation deficit and its uncertainty of the Capitanata plane case study under different climate change scenarios.</p> <p>The scenarios were generated with the following procedure: (i) combination of different GCMs (CNRM-CM5, CMCC-CM and IPSL-CM5A-MR) with the IPCC RCP4.5 and RCP8.5 scenarios as well as with historical data, (ii) statistical downscaling of the obtained models to estimate future time series of air temperature and precipitation for the meteorological stations of interest in the considered case study and (iii) spatial interpolation with ordinary kriging. The obtained maps were then used as input data for the already developed GIS—based application of Benfratello's method.</p>

<p>Due to the changing climate, rapid development, and population growth, the current management of water resources is expected to be critically affected. The majority of reservoirs are multipurpose including water supply, flood control, hydropower production, etc., and often involve several competing interests. Most of the current reservoir management practices are ineffective, outdated, and highly subjective. Therefore, it is necessary to re-evaluate the current management rules for optimizing the objectives, reduction of water stress, and mitigation of climate change impacts.</p><p>Lake Como is a regulated lake in Northern Italy and the third largest lake, receiving water from the upper Adda River and controlled downstream by the “Olginate” regulation dam. The regulation dam has been constructed to manage the release according to irrigation and hydropower demand. In addition, it regulates the water level in the Lake within a certain threshold (i.e., upper, and lower bounds), to prevent flooding in the town of Como and to allow navigation and for environmental reasons.</p><p>This research mainly focuses on optimizing two conflicting objectives, the satisfaction of irrigation demand which is parametrized by α (the ratio between the actual release and the agricultural demand), and upstream flood regulation in the city of Como parametrized by β (the ratio between the actual active storage and the reference storage). Considering the characteristics of the reservoir and the targeted objectives, an optimal operating strategy has been developed by adopting a deterministic Revised Min-Max (RMM) approach. It focuses on the determination of the minimum water level required to satisfy the irrigation demand and the maximum water level to avoid flooding for a specified value of α and β. This approach is based on simulating the continuity equation for a set of 71 years of inflow and outflow time series, from 1946 (the operation of the Olginate dam began) to 2016. besides, the outflow time series was used to simulate the current management policy and historical efficiency of the system in terms of α and β.</p><p>Out of the several feasible solutions (combinations of α and β), we are interested in efficient (Pareto optimal) solutions, where there are no other solutions that can improve either α and/or β. We evaluate three possible management strategies depending on the storage condition and the feasible solutions with different combinations of α and β through a trade-off analysis. The first tends to approach historical average levels (BAUL: Business As Usual Level); the second approaches the historical average releases (BAUR: Business As Usual Release); the third one allows to modulate of the releases with the parameter delta (0< δ <1), which tends to satisfy irrigation demand (δ=0) or flood control (δ=1). In summary, this study shows that the current operating rule can be substantially improved with respect to both objectives, with an improvement of 19% in terms of irrigation demand satisfaction and 69% in terms of flood control.</p>

We apply a methodology to identify and count records (events of unprecedented intensity) in daily precipitation time series to two sets of data: (1) different observational and reanalysis products for recent decades and (2) twenty‐first century projections (RCP8.5 and RCP2.6 scenarios) completed with two regional climate models driven by three global climate models over nine continental‐scale domains. Comparison of the detected (or actual) number of records with the corresponding number theoretically expected in stationary climate conditions (or “reference” number of records) provides indications of trends in daily precipitation extremes, as expected in a changing climate. In particular, we measure deviations from stationary conditions using the ratio of actual to reference records (RAtR) as a basic metric. We find that the observational products provide mixed indications of precipitation record trends across regions, while in the reanalysis products and the model simulations for the historical period the RAtR value shows a prevailing increasing trend with time over most continents. The RAtR shows a consistent and pronounced increase in all RCP8.5 continental‐scale projections, when sustained warming occurs throughout the 21st century, while smaller to no significant trends are found in the RCP2.6 scenario, when the warming stabilizes after about mid‐21st century. These results are indicative of an increase in precipitation extremes with global warming as measured by the higher number of local precipitation events of unprecedented intensity compared to what expected in stationary climate conditions, although a marked variability of this response is found across different regions. Our method can have useful applications in detection and attribution of hydroclimatic extremes and in impact and vulnerability assessment studies.

This study presents monitoring data of a debris flow event in the Central Italian Alps. The debris flow occurred on August 16, 2021 in the Blè basin (Val Camonica valley, Lombardia Region) and was recorded by a monitoring station installed just few weeks before. The monitoring system was deployed to document the hydrologic response of the catchment to rainfall, and was designed to be lightweight, relatively cheap, and easy to deploy in the field. To this purpose, we combined video cameras with geophysical sensors (geophones and infrasound) and optimized the power supply system. The data recorded during the event allowed to identify the triggering rainfall, document the flow behaviour, and estimate surface flow velocity and flow rate using Particle Image Velocimetry algorithms. Moreover, the seismic signal generated by the debris flow revealed a peculiar frequency spectrum compared to regular streamflow. These results show that even a relatively simple monitoring system may provide valuable data on real debris flow events.

This work presents a novel, spatially distributed, GIS-based application of Benfratello's conceptual method to estimate the climatic water deficit and the irrigation deficit at the field and basin scales. Explicit analytical relationships are obtained to define the deficit uncertainty on the basis of the interannual variability of temperature and precipitation. With this model, we aim at proposing a rather simple and effective tool to deal with the complicated issues of assessing the soil water balance, determining the irrigation deficit and managing the water resources in semiarid agricultural environments, in the context of climatic, land-use and anthropogenic changes. In order to test this new application, the model was applied to estimate the irrigation deficit of the Bonifica della Capitanata consortium in the Apulia region, one of the most important agricultural districts in Southern Italy and in the whole Mediterranean area, in four different historical land-use scenarios. The first results of the application seem encouraging, as by using a limited amount of parameters we estimated an irrigation demand which is in agreement with the irrigation volumes erogated by the consortium. The different land-use cases are discussed in the light of an application of the Budyko curve.

Energy budget-based distributed modelling in High Mountain Asia (HMA) is important to examine glaciological-hydrological regimes and compute flow rates in current and projected scenarios. Trends in ablation of snow and glaciers retreat depend upon snow and ice reserves, meteorological parameters and geographical features which vary across sub-basin in HMA. In this study, the Physical Based Distributed Snow Land and Ice Model (PDSLIM, Ranzi and Rosso, 1991; Ranzi et al., 2010; Grossi et al., 2013) is employed for the Naltar catchment (catchment area of 261.70 km(2), with 45 km(2) glacierized) located in the Hunza river basin (Karakorum, Pakistan) to simulate snow and glacier melt progression as well as daily runoff. The overall objective is to verify the feasibility of this modelling system to assess the impact of climate and land use change scenarios. Another objective is also to address the so called "Karakorum anomaly" in glaciers' dynamics, as some glaciers exhibited advances in the last period. The accuracy of the model in simulating distributed snow cover is crosschecked using MODIS and LANDSAT based snow cover areas both at temporal and spatial scale. The results exhibited overall satisfactory performance of coefficient of determination (R-2.) = 0.97 and Nash-Sutcliffe Efficiency (NSE) = 0.96 of model against satellite-based snow cover area for all simulated melting periods. Downstream daily runoff measurement at the outlet of Naltar catchment at Naltar Bala station was used as a reference of comparison for simulated summer streamflow. Runoff simulations revealed good agreement with observed discharge with NSE of 0.88 and 0.90 for calibration and validation period respectively. The increasing runoff volume in late spring and early summer is associated with rising rate of temperature, as no significant precipitation changes have been recorded. However, net simulated runoff volume computed by PDSLIM was in reasonable agreement and only 4% higher than mean observed runoff volume with mean absolute percentage error (MAPE) of 8%. Flow composition analysis revealed snow-glacier melt runoff provides the largest contribution to river discharge. Overall, PDSLIM, so far tested in the Alps, showed to perform well also for snow- and glacier-dynamics in the glacierized catchments of HMA. The hydrological response to projected climate scenarios is currently being investigated.