The effects of new 2030 scenario: Reduction of short-circuit power and widening of voltage dips

In Italy, 80% of PV installations are at MV and LV levels, which makes it particularly challenging to control them from the national dispatch centre; this leads to an increase of the reverse power flow in the primary and secondary substations, increasing pressure on the existing measuring and protection systems and on voltage control. The National Strategic Plan, approved on November 10 th , 2017 by the Ministry of Economic Development and the Ministry of the Environment, has launched an ambitious challenge, e.g., phasing-out of coal and the increase of electricity from renewable sources: more than 55% by 2030 of gross final consumption. The power system must be able to withstand unplanned events and manage their impacts on the network, thus reducing the risk of cascading effects and maintaining suitable quality of supply. During operation with a high percentage of RES connected to the network through inverters, the system is weaker (lower short circuit power) and, with currently adopted controls, less able to react to emerging faults. With the increase of PV installations, also due to reduction of rotating synchronous machines connected to transmission grid, there is lower Short-circuit-Power available and therefore voltage dips generated at transmission level have larger impact (c.g. area impacting supply quality widens hundreds of kilometers away from the event). This paper summarizes the main challenges in terms of impacting supply quality for the Italian Power system in a new scenario with more than 50% RES by 2030 of gross final consumption and suggests some computation procedures to investigate the phenomenon

HERASE: monitorare l’erosione del suolo nelle Alpi con tecniche Geomatiche

In Italia ci sono circa 4 milioni di ettari di terreno agricolo e forestale a rischio di erosione o frana e recenti stime del Ministero dell’Ambiente (2013) indicano che sarebbero necessari 40 miliardi di Euro per ridurre il rischio dovuto alla perdita di suolo sul territorio nazionale. Il progetto Hydrogeological modeling for Erosion Risk Assessment from SpacE (HERASE), finanziato da Fondazione Cariplo (Grant Nr.2016-0768), affronta questo tema nel bacino camuno del fiume Oglio, un’area alpina dell’Italia settentrionale. Scopo di HERASE è mettere a punto una metodologia di analisi basato sul Revised Universal Soil Loss Equation (RUSLE), reso dinamico dall’uso di mappe di copertura del suolo multi-temporali, per evidenziare le zone potenzialmente soggette a fenomeni erosivi e le dinamiche dei cambiamenti del territorio capaci di influenzarne l’entità. Misure in situ di erosione realizzate con un simulatore di pioggia permetteranno la caratterizzazione idrologica di zone rappresentative e la taratura del modello. Infine, le previsioni restituite dai modelli climatici saranno utilizzate per delineare possibili scenari di rischio futuro, in un contesto che vede il territorio montano, e quello alpino in particolare, soggetto a sempre più evidenti cambiamenti climatici. Il presente lavoro riporta alcuni risultati preliminari del progetto HERASE ottenuti sul sotto-bacino del torrente Arcanello (circa 21 km2), dove la stima preliminare dell’erosione è pari a 7,61 [t ha-1 a-1]. Tale risultato è concorde con il valore medio annuo a livello nazionale

Impact of climate change on agricultural productivity and food security in the Himalayas: A case study in Nepal

The paradigmatic Dudh Koshi basin laid at the toe of Mt. Everest is largely visited by tourists every year, and yet agricultural productivity and food security therein are at stake under climate change. Agricultural yield in the area recently decreased, and the question arose whether cropping at higher altitudes may help adaptation. We investigated here the present, and future (until 2100) patterns of productivity of three main rain-fed crops in the catchment (wheat Triticum L., rice Oryza L., and maize Zea Mais L.). We explored food security using a nutritional index, given by the ratio of the caloric content from our target cereals, to daily caloric demand. We preliminary investigated whether vertical extension of the cropped area may increase food security. We did so by (i) mapping crops area using remote sensing, (ii) setting up the agronomic model Poly-Crop, (iii) feeding Poly-Crop with downscaled outputs from global climate models, and (iv) projecting vertical land occupation for cropping, population projections, and nutritional requirements. We estimated crop yield and food security at half century (2040–2050), and end of century (2090–2100), against a control run decade CR (2003−2013), under constant land use, and projected land occupation. On average, specific wheat yield would decrease against CR by −25% (rice −42%, maize −46%) at 2100, with largely yearly variability for unchanged land use scenario. Under modified land use scenario, wheat yield would decrease by −38%, while rice and maize yield would improve, maize very slightly (−22%, and −45%, against CR) in response to occupation of higher altitudes than now. Our food security index would decrease under all scenarios (111% in 2010, 49% on average at 2050, under a population peak, and 51% at 2100), and become more variable, however with potential for adaptation by colonization of higher lands (75%, 62%, at 2050, 2100). Very large expansion of one cereal (i.e. maize), may make food security more unstable, as mostly depending on erratic yield of that cereal only

Future scenarios of soil erosion in the Alps under climate change and land cover transformations simulated with automatic machine learning

Erosion is one of the major threats listed in the Soil Thematic Strategy of the European Commission and the Alps are one of the most vulnerable ecosystems, with one of the highest erosion rates of the whole European Union. This is the first study investigating the future scenarios of soil erosion in Val Camonica and Lake Iseo, which is one of the largest valleys of the central Italian Alps, considering both climate change and land cover transformations. Simulations were done with the Dynamic Revised Universal Soil Loss Equation (D-RUSLE) model, which is able to account also for snow cover and land cover dynamics simulated with automatic machine learning. Results confirm that land cover projections, usually ignored in these studies, might have a significant impact on the estimates of future soil erosion. Our scenario analysis for 2100 shows that if the mean annual precipitation does not change significantly and temperature increases no more than 1.5–2.0 °C, then the erosion rate will decrease by 67% for about half of the study area. At the other extreme, if the mean annual precipitation increases by more than 8% and the temperature increases by more than 4.0 °C, then about three-quarters of the study area increases the erosion rate by 92%. What clearly emerges from the study is that regions with higher erosion anomalies (positive and negative) are expected to expand in the future, and their patterns will be modulated by future land transformations

D-RUSLE: a dynamic model to estimate potential soil erosion with satellite time series in the Italian Alps

Soil erosion is addressed as one of the main hydrogeological risks in the European Union. Since the average annual soil loss rate exceeds the annual average formation rate, soil is considered as a non-renewable resource. Besides, human activities, human-induced forces and climate change have further accelerated the erosion processes. Therefore, understanding soil erosion spatial and temporal trends could provide important information for supporting government land-use policies and strategies for its reduction. This paper describes the Dynamic Revised Universal Soil Loss Equation (D-RUSLE) model, a modified version of the well-known RUSLE model. The RUSLE model formulation was modified to include variations in rainfall erosivity and land-cover to provide more accurate estimates of the potential soil erosion in the Italian Alps. Specifically, the modelling of snow occurrence and the inclusion of Earth Observation data allow dynamic estimation of both spatial and temporal land-cover changes. Results obtained in Val Camonica (Italy) show that RUSLE model tends to overestimate erosion rates in Autumn/Winter because not considering snow cover and vegetation dynamics. The assimilation of satellite-derived information in D-RUSLE allows a better representation of soil erosion forcing, thus proving a more accurate erosion estimate for supporting government land-use policies and strategies for reducing this phenomenon

Large plot erosion simulations on Alpine area

We propose an experimental setup to measure soil erosion and related it with sediment transport using rainfall simulator on a large plots experimental area. Experiments were carried out in fulfilment of the HERASE project, aimed at investigating the seasonal variations of soil erosion in the Oglio basin, an Alpine and Pre-alpine watershed with an area of about 1800 km2, and maximum elevation of 3.538m a.s.l. Namely some rainfall simulation experiments were carried out to assess water erosion under three different scenarios, on in situ plots having same soil and slope, but with different soil coverage and initial moisture condition. In particular, two experiments were carried out on a grassland plot covering an area of 144m2, one considering an undisturbed initial soil moisture condition and the other on a wet soil. The third experiment plot, having the same soil and slope of the previous, and covering an area of 72m2, was set up in the pine forest underwood area. The duration of the three experiments were respectively of 18 minutes, 30 minutes and 30minutes and rainfall intensity was set equal to 70mm/h, accordingly to a 200 return period storm. The plots were properly designed to ensure a correct as possible measure of surface runoff, and transported sediments were collected at 1 minute steps. Suspended sediment, and particle size analysis were carried out ex-post. Our results show a different behaviour of the two analysed plots, in terms of runoff generation and sediment transport. The runoff peak on grassland ranged from 0.018l/s for the undisturbed condition, to 0.09l/s with wet initial condition, while the peak in sediment transport, slowly delayed with respect to the runoff peak, was 1,7 times bigger in wet conditions. In the third experiment, peak runoff was 0.9l/s (10 times bigger than the peak runoff on wet grassland), and constant until the end of simulated rainfall, and took five minutes to run out (concentration time). The analysis on sediment shows an initial slush, where pine needles composed the majority of sediment. Then, after the sediment reached the peak of 350mg/s after about 9 minutes from the beginning of the experiment, it decreased rapidly to an almost constant value of 50mg/s. Interpretations on experiment results with different formulations and a comparison with similar analyses carried out in the Alpine area of Italy are proposed

Analisi di sensitività nella stima dell’erosione di suolo nelle Alpi con misure in situ e serie temporali Landsat

Questo lavoro si inserisce nell’ambito del progetto Hydrogeological modeling for Erosion Risk Assessment from SpacE (HERASE) finanziato da Fondazione Cariplo (Grant Nr.2016-0768) e che ha l’obiettivo di mettere a punto un modello per la stima dell’erosione dei suoli nel bacino alpino del fiume Oglio (~1800 km2). La metodologia di analisi è basata sul noto modello Revised Universal Soil Loss Equation (RUSLE), che stima l’erosione media annua in funzione di capacità erosiva delle precipitazioni, topografia, pedologia e copertura e uso dei suoli. In questa ricerca si propone un metodo alternativo per la stima dell’erosività della precipitazione in funzione della dinamica nivale e si rende dinamica la stima del parametro di copertura del suolo legandolo all’indice NDVI ricavato da una serie multi-temporale d’immagini Landsat (5, 7 e 8). L’analisi di sensitività all’effetto delle variazioni inter- ed intra-annuali di precipitazione e copertura/uso del suolo rispetto alla formulazione tradizionale del modello RUSLE è stata integrata valutando due diverse formulazioni per i parametri topografico e pedologico. I risultati evidenziano che l’approccio proposto permette di identificare le aree maggiormente esposte al rischio erosione. Inoltre, descrivendo in modo più accurato la dinamica del fenomeno, è potenzialmente in grado di restituirne stime più precise