Supporting land use change modelling with automated monitoring of land use dynamics in the La Plata River Basin.

2008

Biophysical indicators based on satellite images in an irrigated area at the São Francisco River Basin, Brazil.

The Jaíba Irrigated Perimeter is a large irrigated agriculturearea, located in the region Forest Jaíba between the SãoFrancisco and Verde Grande rivers, in the Brazilian semi-arid region. In 2014, irrigators thisthe region face losses in theinterruption of new plantings in irrigated areas due to water scarcity. The objective ofthis study is combine the modelto estimate the Monteith BIO with the SAFER algorithm in the case of obtaining ET, to analyze the dynamics of naturalvegetation and irrigated crops in water scarcity period. For application of the model are necessary data frommeteorological stations and satellite images. Were used 23satellite images of MODIS withspatial resolution of 250mand temporal 16 days, of 2014 year. For analyze the results,we used central pivots irrigation mask of Minas Geraisstate, Brazil. In areas with irrigated agriculture with central pivot, the mean values of BIO over the year 2014 were88.96 kg.ha-1.d-1. The highest values occurred between April 23 and May 8, with BIO 139 kg.ha-1.d-1. For areas withnatural vegetation, the average BIO was 88.34 kg.ha-1.d-1with lower values in September. Estimates of ET varied withthe lowest values of ET observedin natural vegetation 1,91±1,22 mm.d-1and the highest values in irrigated area isobserved 3,51±0,97 mm.d-1. Results of this study can assist in monitoring of river basins, contributing to themanagement irrigated agriculture, with the trend of scarcity of water resources and increasing conflicts for the wateruse.

Energy balances in sugar cane, coffee and natural vegetation in the northeastern side of the São Paulo state, Brazil

Under land and climate change scenarios, agriculture has experienced water competitions among other sectors in the São Paulo state, Brazil. On the one hand, in several occasions, in the northeastern side of this state, nowadays sugar-cane is expanding, while coffee plantations are losing space. On the other hand, both crops have replaced the natural vegetation composed by Savannah and Atlantic Coastal Forest species. Under this dynamic situation, geosciences are valuable tools for evaluating the large-scale energy and mass exchanges between these diffe rent agro-ecosystems and the lower atmosphere. For quantification of the energy balance components in these mixed agro-ecosystems, the bands 1 and 2 from the MODIS product MOD13Q1 we re used throughout SA FER (Surface Algorithm for Evapotranspiration Retrieving) algorithm, which was applied together with a net of 12 automatic weather stations, during the year 2015 in the main sugar cane and coffee growing regions, located at the no rtheastern side of the state. The fraction of the global solar radiation (R G ) transformed into net radiation (Rn) was 52% for sugar cane and 53% for both, coffee and natural vegetation. The respective annual fractions of Rn used as λ E were 0.68, 0.87 and 0.77, while for the sensible heat (H) fluxes they were 0.27, 0.07 and 0.16. From April to July, heat advection raised λ E values above Rn promoting negative H, however these effects were much and less strong in coffee and sugar cane crop s, respectively. The smallest daily Rn fraction for all agro-ecosystems was for the soil heat flux (G), with averages of 5%, 6% and 7% in sugar cane, coffee and natural vegetation. From the energy balance analyses, we could conclude that, sugar-cane crop presented lower annual water consumption than that for coffee crop , what can be seen as an advantage in situations of water scarcity. However, the replacement of natural vegetation by su gar cane can contribute for warming th e environment, while when this occur with coffee crop there was noticed co oling conditions. The large scale modeling satisfactory results confirm the suitability of using MODIS products togeth er with weather stations to study the energy balance components in mixed agro-ecosystems under land-use and climate change conditions.

Water and sediments geochemistry and elemental fluxes on a Large Dam: case study of Ridracoli reservoir.

Since the study of Large Dam Reservoirs is of worldwide interest, in this PhD project we investigated the Ridracoli reservoir, one of the main water supply in Emilia-Romagna (north-eastern Italy). This work aims to characterize waters and sediments to better understand their composition, interactions and any process that occurs, for a better geochemical and environmental knowledge of the area. Physical and chemical analyses on the water column have shown an alternation of stratification and mixing of water in the reservoir’s water body due to seasonal variations in temperature and density. In particular, it was observed the establishment, in late summer, of anoxic conditions at the bottom, which in turn affects the concentration and mobility of some elements of concern (e.g. Fe and Mn) for the water quality. Sediments within the reservoir and from surrounding areas were analysed for organic matter, total inorganic composition and grain size, assessing the inter-element relationship, grain size, geological background and damming influences on their chemistry, through descriptive statistics, Principal Component Analysis and Cluster Analysis. The reservoir’s area was also investigated by pseudo total composition (Aqua Regia digestion), degree of elements extractability, and enrichment factors, then analysed and compared to limits by law and literature. Sediment cores, interstitial waters, and benthic chamber data from the bottom were of great interest due to organic matter degradation, early diagenesis, mineral formation at water-sediment interface and observed flows. Finally, leaching test and extraction procedures, of environmental interest, showed peculiar partitioning, both regarding spatial and in-depth distribution, and the absence of pollution. Collectively, our results are useful for the comprehension of processes that occur in water and sediments of Ridracoli reservoir, providing important knowledges on the site that could be relevant for the management of the resource and the planning of future interventions.

Sviluppo e validazione di mappe di copertura nevosa per lo studio della variabilità del manto nevoso in Emilia Romagna nel periodo 2000-2020

Il telerilevamento satellitare costituisce una delle tecniche di osservazione maggiormente efficace nel monitoraggio e nello studio dell'estensione del manto nevoso. Il manto ricopre un ruolo di estrema importanza quale risorsa idrica per gli ecosistemi e per le applicazioni agricole e industriali. Inoltre, è un indicatore climatologico in un contesto di cambiamenti climatici regionali e globali. In questo senso, la copertura nevosa è da considerarsi come una importante risorsa economica e sociale. Lo scopo della presente tesi è di produrre mappe di copertura nevosa giornaliere per la stima dell'estensione del manto nevoso della regione Emilia-Romagna e di analizzare la sua variabilità spazio-temporale nel periodo 2000-2020. Le mappe sono state sviluppate sulla base dei prodotti di neve, M*D10A1, del sensore MODIS, che consistono in mappe di classificazione della copertura in funzione dell'indice NDSI. Inizialmente, è stato costruito un albero decisionale con criteri a soglia multipla in grado di rielaborare la classificazione della superficie del sensore e produrre mappe di copertura nevosa sulla base di tre classi: neve, no-neve e nube. L'accuratezza delle mappe è stata validata tramite test statistici effettuati confrontandole con i dati di altezza del manto nevoso in situ di 24 stazioni meteorologiche, per il periodo di compresenza dei dati 2000-2012. I risultati della procedura di validazione hanno mostrato come, in generale, vi sia buon accordo tra il dato satellitare e la rispettiva osservazione al suolo, soprattutto nei pressi di stazioni lontane da vegetazione sempreverde e/o di ambiente urbano. Infine, è stata valutata la variabilità climatologica dell'estensione del manto nevoso tramite l'elaborazione degli indici di neve SCF, SCD e diversi indici SCA. L'attenzione è stata particolarmente focalizzata sugli indici di massima estensione invernale del manto, del valore mediano e del numero di giorni con estensione superiore al 39.5% della regione.