Spatial and Temporal Distribution of Groundwater Recharge in the West Bank Using Remote Sensing and GIS Techniques

Estimating groundwater recharge to aquifer systems is a very important element in assessing the water resources of the West Bank. Of particular interest is the sustainable yield of the aquifers. Previous studies have developed analytical recharge models that are based on the long-term annual rainfall data. These models have been shown to be inadequate and changes over shorter periods, e.g. monthly estimates, must be known in order to study the temporal distribution of recharge. The approach used in this research integrates data derived from satellite images (e.g. land cover, evapotranspiration, rainfall, and digital elevation model) with hydrogeological data in a Geographic Information System (GIS) model to identify and map the surface recharge areas. The Surface Energy Balance Algorithm for Land (SEBAL) is applied to time series of remote sensing MODerate Resolution Imaging Spectroradiometer (MODIS) level 3 data of reflectance and surface temperature measurements to estimate monthly evapotranspiration; precipitation is derived from the monthly data sets of the Tropical Rainfall Measuring Mission (TRMM); runoff is given assumed values of 0.75 mm month-1 and 0.4 mm month-1 for the months of January and February, respectively. Recharge is quantified from November until March by applying the water balance method where evapotranspiration estimates and runoff are subtracted from precipitation. Results show good agreement between data reported in the literature and remote sensing-based analysis. Empirical models that are based on long term rainfall measurements suggest recharge values between 800 and 836 MCM yr-1 while the remote sensing based model results estimate recharge to be 700 MCM yr-1. The Western, North-Eastern, and Eastern Aquifer Basins receive 30%, 23%, and 47% of the total calculated recharge while percentages available in the literature provide 49%, 22%, and 29%, respectively. Discrepancies are mainly due to lack of field data, the overestimation of actual evapotranspiration, and underestimation of TRMM precipitation values. The recharge map indicates that the most effective groundwater recharge zones are located in the north and west of the area that is characterised by thick and well developed soil deposits, heavy vegetation, and a sub-humid climate with the potential of significant recharge occurring during the wet season. Some areas in the east include concentration of drainage and stream flows which increase the ability of to recharge the groundwater system. The least effective areas are in the south and south-west region that is more arid with much less recharge, mainly due to its isolated thin soil deposits. A sensitivity analysis was carried out to demonstrate the impact of land cover change on groundwater and natural recharge. The assessment involved the use of land covers of 1994 and 2004 with the same fixed parameters of evapotranspiration, precipitation, drainage, slope, soil, and geology. Results show a decrease in high and intermediate high recharge areas from 40.25 km2 and 2462.25 km2 in year 1994 to 15.5 km2 and 1994 km2 in 2004, respectively. This illustrates the extent of land cover/land use change influence on recharge and calls for integrated plans and strategies to preserve recharge at least at its current rates

Balanço de energia com base no modelo S-SEBI sobre gramíneas em Barrax, Espanha e no bioma Pampa do sul do Brasil

No Brasil, existem seis biomas, sendo eles Amazônia, Mata Atlântica, Cerrado, Caatinga, Pantanal e Pampa. Cada bioma possui características únicas e importantes para a manutenção dos seus processos ecossistêmicos. Neste sentido, no bioma Pampa há uma dinâmica socioambiental que influencia a vegetação, o manejo agrícola e o modo de vida da população local. Este bioma é único no mundo porque traz na vegetação rasteira sua fonte de biomassa e energia como em nenhum outro ecossistema, seus campos nativos são os responsáveis pela conservação e preservação dos recursos hídricos, da fauna silvestre e da biodiversidade. A supressão da vegetação nativa deste bioma para a monocultura de grãos compromete a manutenção da biodiversidade e gera impactos nos recursos naturais, alterando as suas condições ambientais, a disponibilidade de água e a temperatura de superfície. Além disso, as mudanças climáticas têm modificado os componentes do Balanço de Energia (BE). Em relação ao balanço energético este bioma tem, no estado do Rio Grande do Sul, a mesma importância climática que as florestas em regiões tropicais, já que cobre 63% do Estado e possui influência nas dinâmicas atmosféricas. Sendo assim, o objetivo deste trabalho é avaliar as particularidades ambientais do BE e do cálculo de evapotranspiração (ET) no bioma Pampa. A ET é a responsável pelas interações da biosfera- atmosfera-hidrosfera. Estas interações se dão por utilizar energia eletromagnética para a formação de vapor d’água a partir da transpiração vegetal e da evaporação da água. O uso do Sensoriamento Remoto tem sido eficaz nas estimativas de fluxo de calor sensível e fluxo de calor latente por diferentes métodos, porém a aplicação de forma operacional, a heterogeneidade da superfície e a influência da temperatura de superfície (Ts) são desafios deste trabalho. O modelo S-SEBI para recuperação de dados de ET foi avaliado no bioma Pampa e em Barrax, um sítio de validação localizado no mediterrâneo espanhol. O modelo demonstrou ser eficaz em vegetação campestre, além de ser menos dependente da Ts em relação a outros modelos reportados na literatura. Os resultados deste trabalho visam contribuir para a geração de melhor qualidade de dados de ET em futuras análises de mudanças de uso do solo, mudanças climáticas e gestão dos recursos hídricos para todo o bioma Pampa.In Brazil, there are six biomes, namely the Amazon, Atlantic Forest, Cerrado, Caatinga, Pantanal, and Pampa. Each biome has unique and important characteristics for the maintenance of the ecosystemic processes of each environment. In this sense, in the Pampa biome there is a socio-environmental dynamic that influences the vegetation, agricultural management, and the way of life of the local population. This biome is unique in the world because it brings in its undergrowth vegetation its source of biomass and energy like no other ecosystem; its native grasslands are responsible for the conservation and preservation of water resources, wildlife, and biodiversity. The suppression of the native vegetation of this biome for the monoculture of grains compromises the maintenance of biodiversity and generates impacts on natural resources, altering the environmental conditions of the ecosystem, water availability, and surface temperature. In addition, climate change has modified the components of the Energy Balance (EB). In relation to the energy balance, in the state of Rio Grande do Sul, this biome has the same climatic importance as the forests in tropical regions, since it covers 63% of the state and influences the atmospheric dynamics. Therefore, the objective of this work is to evaluate the environmental particularities of BE and the calculation of evapotranspiration (ET) in the Pampa biome. ET is responsible for biosphere-atmosphere-hydrosphere interactions. These interactions occur by using electromagnetic energy for the formation of water vapor from plant transpiration and water evaporation. The use of Remote Sensing has been effective in estimating sensible heat flux and latent heat flux by different methods, but the application in an operational way, the heterogeneity of the surface and the influence of the surface temperature (Ts) are challenges of this work. The S-SEBI model for ET data retrieval was evaluated in the Pampa biome and in Barrax, a validation site located in the Spanish Mediterranean. The model proved to be effective in grassland vegetation, and is less dependent on Ts compared to other models reported in the literature. The results of this work aim to contribute to the generation of better quality ET data in future analyses of land use change, climate change, and water resource management for the entire Pampa biome

Estimation of regional evaporation under different weather conditions from satellite and meteorological data: a case study in the Naivasha Basin, Kenya

Existing remote sensing algorithms used to estimate evaporation from remotely sensed data differ in the way they describe the spatial variations of input parameters. An evaluation of the impact of spatially varying input parameters on distributed surface fluxes showed that the vertical near surface air temperature difference and frictional velocity were the most critical parameters. Most remote sensing algorithms treat air temperature as spatially constant indicating that they are less suitable for the calculation of distributed evaporation in heterogeneous catchments.The temporal variability of the evaporative fractionΛat the daily and seasonal time frames was investigated with field data obtained at two experimental sites. For general weather conditions the values of the midday (12.00 to 13.00 hrs) evaporative fractionΛ mid compared well with the averaged day time evaporative fractionΛ day . A good relationship was obtained between daytime evaporation estimated fromΛ mid and evaporation measured by the Bowen ratio surface energy balance method. Less satisfactory evaporation results were obtained using morning (9.00 to 10.00 hrs) evaporation fractionΛ mor . The seasonal evolution ofΛ day was observed to be gradual. To capture the seasonal evolution ofΛ day it would be sufficient to measureΛ day approximately every 10 days. Moreover, it was shown that the inter-annual variability of the 10-day averageΛcould be reliably estimated from standard weather data.To monitor the temporal evolution of daily evaporation over a season, evaporation has to be estimated between consecutive clear days with satellite images being available. Two methods to predict daily evaporation on days without satellite images due to cloud cover are presented. Field data acquired at two sites were used to test these methods. The first method consists of the application of the Penman-Monteith equation and Jarvis-Stewart model with standard weather data and the assumption of gradual soil moisture changes between consecutive clear days. With this method evaporation could be accurately predicted for up-to 5 continuous days with no satellite images. The second method is a simplified approach involving the use of a constantΛbetween cloud free days with measured evaporation. This approach did not give satisfactory results in predicting evaporation on individual days. However, the total evaporation of a 7-day time span was equally good for both methods.Five NOAA AVHRR satellite images were used to produce daily evaporation maps of the Naivasha basin for 15 continuous days with intermittent cloud cover by using the Penman-Monteith equation coupled with the Jarvis-Stewart model as well as the evaporative fraction method. The evaporation maps were validated with field data and overall good agreement was obtained. This demonstrated that remote sensing methods can be extended for practical use under all weather conditions to map both the spatial patterns as well as the temporal evolution of evaporation in catchments and river basins. The methods of predicting evaporation can be applied at different time scales. Users can select the appropriate time scales depending on their needs. The implementation of the Penman-Monteith equation and Jarvis-Stewart model requires a land cover classification of the catchment to assign land cover dependent coefficients in the Jarvis-Stewart model. At each land cover type standard weather data has to be measured.</p

Ecohydrology in water-limited environment using quantitative remote sensing - the Heihe River basin (China) case

Water-limited environments exist on all continents of the globe and they cover more than 30% of the Earth’s land surface. The eco-environments of these regions tend to be fragile and they are changing in a dramatic way through processes like land desertification, shrinking of oases, groundwater depletion, and soil erosion. These are either human induced or results of a changing climate. Implications of these changes for both the regional hydrologic cycle and the vegetation have been documented. Since these changes occur over a wide range of scales in space and time, remote sensing methods are needed to monitor the land surface characteristics, to observe changes in vegetation and hydrological states, and to compare these with predictions from hydrological models. It is widely accepted that remote sensing methods offer the ability to acquire spatially continuous measurements over large areas. Remote sensing can also help to visualize complex processes because the spatial data can be captured regularly over time. China is one of several countries with large arid and semi-arid areas. The Heihe River basin, situated in the arid inland of northwestern China, is one of the areas severely affected by ecoenvironmental degradation and recovery. The problem of the degraded environment is due to overexploitation of surface and ground water leading to shrinking of oases, including the decline and death of natural vegetation, and the lowering of the groundwater table. Exhaustive (over-)use of water resources is the main cause of land degradation in the lower reaches of the basin, called the Ejina oasis. The whole Heihe River basin is therefore selected as study area in this thesis to analyze the long-term eco-environmental changes. What happens in this river basin is likely to have a growing influence on regional hydrological cycles, even affecting human life. Effective management of eco-environmental problems in this critical zone of water-limited conditions will provide scientific evidence for protecting and improving the eco-environment in these Chinese northwestern arid regions, eventually resulting in land improvement. Studies on quantifying the relationship between the vegetation and the water resources are a critical step in developing an ecohydrological approach to resources management in order to minimize environmental degradation. Remote sensing measurements can help us to better understand the effects of changes in water management on hydrological processes and their subsequent feedback to the eco-environment at the regional scale. Remote sensing methods can also provide information to quantify heterogeneity and change at a large scale. Therefore, the main objective of this thesis is to develop a methodology for the quantitative assessment of eco-environmental changes at a large scale in arid regions by integrating remote sensing methods in ecohydrological approaches. Chapter 1 outlines the significance of quantitative assessment of eco-environmental changes using remote sensing methods and applying them for ecohydrology in northwestern China, resulting in the specific research objectives of this thesis. Chapter 2 quantifies both the vertical and horizontal distribution of vegetation in the Qilian Mountains area, representing the upper reaches of the Heihe River basin, based on MODIS NDVI images from the year 2000 - 2006. Our analysis reveals that elevation and aspect are two important impact factors for the vertical distribution of vegetation in a mountainous area. The NDVI increases with the elevation and reaches a maximum value at a certain elevation threshold, and then decreases as the elevation increases beyond this threshold. The optimal vegetation growth is on the shady side of the mountains because of less evapotranspiration. The best combination of temperature and precipitation is assessed providing good conditions for vegetation growth. Chapter 3 presents an efficient method to estimate the regional annual evapotranspiration (ET) based on the SEBS algorithm (Surface Energy Balance System) in the Zhangye basin, representing the middle reaches of the Heihe River basin. The method proposed is a combination of the daily SEBS results and data collected by meteorological stations. The result shows that the annual ET increased gradually during the period 1990-2004 and the main impact factor on the long-term increase of annual ET was the vegetation change. The accuracy of the ET result is validated using a water balance for the whole watershed and the validation reveals that the SEBS algorithm can be used to effectively estimate annual ET in the Zhangye basin. Chapter 4 establishes the quantitative relationship between the runoff of the Heihe River and the long-term vegetation change of the Ejina oasis, located in the lower reaches of the Heihe River. In this part, two time periods are distinguished corresponding to before and after the implementation of a new water allocation scheme in the Heihe River basin. The GIMMS NDVI and MODIS NDVI data sets are used to quantify the long-term change of the oasis vegetation in the first period 1989-2002 and the second period 2000-2006, respectively. The vegetation change shows a decreasing trend from 1989 to 2002 and an increasing trend between 2000 and 2006. Good relation between the runoff of the river and the vegetation growth are found at both stages and the time lag of the observed hysteresis effect of the runoff of the river on the oasis vegetation is one year. In addition, the yearly smallest water amount which sustains the demand of the eco-environment of the Ejina area is estimated to be 4×108 m3 based on MODIS images. Chapter 5 explores a method to quantify the effect of the groundwater depth on the vegetation growth in the year 2000 in the oasis area by combining MODIS NDVI with groundwater observation data. The result demonstrates that the groundwater depth suitable for vegetation growth in this region ranges from 2.8 to 5 m, depending on species composition. Hardly any vegetation growth occurs when the groundwater depth is below 5 m because the rooting depth of the occurring species is limited and cannot maintain adequate water supplies to their canopies when the water depth is below 5 m. The situation changes after implementation of the new water allocation scheme since 2000. The mean NDVI increased and the annual conversion of bare land into vegetated land is about 38 km2 per year during the period 2000 – 2008. It reflects a potential recovery of the eco-environment of the Ejina area. Chapter 6 comprises the main conclusions and the outlook for possible improvements in future research. The main contribution of this study is the successful integration of remote sensing with ecohydrology in quantifying the relationship between water resources and vegetation occurrence at large scale. It provides a methodology to evaluate the long-term vegetation change and the water resources impact using remote sensing data in water-limited areas. The approach of vegetation dynamics, runoff and groundwater impacts presented in this thesis serves as a sound foundation for predicting the effects of future environmental changes. <br/

Improved Modeling of Evapotranspiration using Satellite Remote Sensing at Varying Spatial and Temporal Scales

The overall objective of the dissertation was to improve the spatial and temporal representation and retrieval accuracy of evapotranspiration (ET) using satellite imagery. Specifically, (1) aiming at improving the spatial representation of daily net radiation (Rn,24) under rugged terrains, a new algorithm, which accounts for terrain effects on available shortwave radiation throughout a day and utilizes four observations of Moderate-resolution Imaging Spectroradiometer (MODIS)-based land surface temperature retrievals to simulate daily net longwave radiation, was developed. The algorithm appears to be capable of capturing heterogeneity in Rn,24 at watershed scales. (2) Most satellite-based ET models are constrained to work under cloud-free conditions. To address this deficiency, an approach of integrating a satellite-based model with a large-scale feedback model was proposed to generate ET time series for all days. Results show that the ET time series estimates can exhibit complementary features between the potential ET and the actual ET at watershed scales. (3) For improving the operability of Two-source Energy Balance (TSEB) which requires computing resistance networks and tuning the Priestley-Taylor parameter involved, a new Two-source Trapezoid Model for ET (TTME) based on deriving theoretical boundaries of evaporative fraction (EF) and the concept of soil surface moisture availability isopleths was developed. It was applied to the Soil Moisture and Atmosphere Coupling Experiment (SMACEX) site in central Iowa, U.S., on three Landsat TM/ETM imagery acquisition dates in 2002. Results show the EF and latent heat flux (LE) estimates with a mean absolute percentage difference (MAPD) of 6.7 percent and 8.7 percent, respectively, relative to eddy covariance tower-based measurements after forcing closure by the Bowen ratio technique. (4) The domain and resolution dependencies of the Surface Energy Balance Algorithm for Land (SEBAL) and the triangle model were systematically investigated. Derivation of theoretical boundaries of EF for the two models could effectively constrain errors/uncertainties arising from these dependencies. (5) A Modified SEBAL (M-SEBAL) was consequently proposed, in which subjectivity involved in the selection of extreme pixels by the operator is eliminated. The performance of M-SEBAL at the SMACEX site is reasonably well, showing EF and LE estimates with an MAPD of 6.3 percent and 8.9 percent, respectively

Comparison of Three Operative Models for Estimating the Surface Water Deficit Using ASTER Reflective and Thermal Data

24 pages, 4 figures, 4 tables.-- Special Issue "Remote Sensing of Natural Resources and the Environment".Three operative models with minimum input data requirements for estimating the partition of available surface energy into sensible and latent heat flux using ASTER data have been evaluated in a semiarid area in SE Spain. The non-evaporative fraction (NEF) is proposed as an indicator of the surface water deficit. The best results were achieved with NEF estimated using the "Simplified relationship" for unstable conditions (NEF_Seguin) and with the S-SEBI (Simplified Surface Energy Balance Index) model corrected for atmospheric conditions (NEF_S-SEBIt,) which both produced equivalent results. However, results with a third model, NEF_Carlson, that estimates the exchange coefficient for sensible heat transfer from NDVI, were unrealistic for sites with scarce vegetation cover. These results are very promising for an operative monitoring of the surface water deficit, as validation with field data shows reasonable errors, within those reported in the literature (RMSE were 0.18 and 0.11 for the NEF, and 29.12 Wm-2 and 25.97 Wm-2 for sensible heat flux, with the Seguin and S-SEBIt models, respectively).This study received financial support from several different research projects: the integrated EU project, DeSurvey (A Surveillance System for Assessing and Monitoring of Desertification) (ref.: FP6- 00.950, Contract nº. 003950), the PROBASE (ref.: CGL2006-11619/HID) and CANOA (ref.: CGL2004-04919-C02-01/HID) projects funded by the Spanish Ministry of Education and Science; and the BACAEMA ('Balance de carbono y de agua en ecosistemas de matorral mediterráneo en Andalucía: Efecto del cambio climático', RNM-332) and CAMBIO ('Efectos del cambio global sobre la biodiversidad y el funcionamiento ecosistémico mediante la identificación de áreas sensibles y de referencia en el SE ibérico', RNM 1280) projects funded by the Junta de Andalucía (Andalusian Regional Government).Peer reviewe

Calibração automática do modelo de estimativa de evapotranspiração por sensoriamento remoto (SEBAL)

A evapotranspiração (ET) desempenha um papel fundamental no no ciclo hidrológico, e no ciclo de carbono. A identificação da quantidade de água evapotranspirada é de fundamental importância em diversas áreas tais como gerenciamento dos recursos hídricos, agricultura e clima. Mesmo assim a ET superficial ainda é um dos processos menos compreendidos do ciclo hidrológico. Tradicionalmente pode ser obtida a partir de medições pontuais, mas em função da heterogeneidade da superfície e da não-linearidade do processo, essas medidas não podem ser extrapoladas diretamente para escalas regionais uma vez que não são representativas de áreas maiores. Métodos que utilizam de dados de sensoriamento remoto para estimativa de evapotranspiração, se apresentam como uma alternativa para superar essa limitação. O modelo SEBAL (Surface Energy Balance Algorithm for Land) foi desenvolvido para estimar o fluxo de calor latente (LE) e ET com base no resíduo do balanço de energia a partir da utilização de imagens termais, multiespectrais e dados meteorológicos auxiliares e utiliza um processo de calibração interna que requer a escolha de dois pontos da imagem (pixels âncoras) que representem condições extremas em termos de temperatura e umidade. Originalmente a seleção dos pixels extremos para a calibração interna do algoritmo SEBAL é realizada manualmente pelo operador. Entretanto, Allen et al. (2013) propôs que a escolha dos pixels âncora fosse realizada a partir de porcentagens de extremos das imagens de NDVI e Ts. Neste contexto, o objetivo do presente trabalho consistiu em (1) analisar critérios envolvidos no processo de escolha automática dos pixels âncora, (2) analisar a sensibilidade do algoritmo quanto a área de domínio e (3) quanto as variáveis de entrada e intermediárias do modelo. Para isso foram utilizadas 12 imagens multiespectrais dos satélites LANDSAT 5 e 8, abrangendo a localização de uma torre da Rede SULFLUX instalada em Cachoeira do Sul (RS), com medições micrometeorologicas e de vórtices turbulentos. Os resultados mostraram que o algoritmo é sensível principalmente à dT e Rn para LE instantâneo e à dT para ET diária, com maior acurácia à medida que se aumentou a área de domínio do modelo. O grupo de porcentagens para escolha automática dos pixels âncora que apresentou melhores resultados de LE instantâneo foi com NDVI frio=5%; Ts frio=0,01%; NDVI quente=10%; Ts quente=0,01%, enquanto que para ET-diária foi com NDVI frio=5%; Ts frio=0,1%; NDVI quente=10%; Ts quente=0,1%, com raiz do erro médio quadrático (RMEQ) de 52 e 15%, respectivamente.Evapotranspiration (ET) plays a key role in the hydrological and carbon cycle. The identification of the amount of evapotranspirated water is of fundamental importance in several areas such as water resources management, agriculture and climate. Nevertheless, ET is still one of the least understood processes of the hydrological cycle. Traditionally it can be obtained from local measurements, however depending on surface heterogeneity and due to non-linear processes, these measurements can not be extrapolated directly to regional scales since they are not representative over larger areas. Methods using remote sensing data to estimate ET are presented as an alternative to overcome this limitation. SEBAL (Surface Energy Balance Algorithm for Land) algorithm was developed to estimate latent heat flux (LE) and daily ET based on energy balance relying on thermal and multispectral images and ancillary meteorological data. The algorithm uses an internal calibration that requires the choice of two pixels that represent extreme conditions in terms of temperature and humidity. Originally the selection of extreme pixels for the internal calibration of the SEBAL algorithm is performed manually. However, Allen et al. (2013) proposed an automated method to select these pixels based on percentiles of NDVI and surface temperature. In this context, the objective of the present work was to (1) analyze the criteria involved in the automatic selection process of the anchor pixels, (2) analyze the sensitivity of the algorithm in the domain area and (3) model variables. For this, 12 multispectral images of the LANDSAT 5 and 8 satellites were selected, covering the location of a SULFUX eddy covariance tower installed in Cachoeira do Sul (RS). The results showed that the algorithm is sensitive mainly to dT and Rn for instantaneous LE and to dT for daily ET, with greater accuracy as the domain area of the model was increased. The group of percentages for automatic selection of the anchor pixels that presented the best results of instantaneous LE was with cold NDVI = 5%; Cold Ts = 0.01%; NDVI hot = 10%; Hot ts = 0.01%, whereas for ET-daily it was cold NDVI = 5%; Cold Ts = 0.1%; NDVI hot = 10%; Hot Ts = 0.1%, root mean square error (RMEQ) of 52 and 15%, respectively

Impacts of climate variability and drought on surface water resources in sub-saharan africa using remote sensing: A review

Climate variability and recurrent droughts have caused remarkable strain on water resources in most regions across the globe, with the arid and semi-arid areas being the hardest hit. The impacts have been notable on surface water resources, which are already under threat from massive abstractions due to increased demand, as well as poor conservation and unsustainable land management practices. Drought and climate variability, as well as their associated impacts on water resources, have gained increased attention in recent decades as nations seek to enhance mitigation and adaptation mechanisms. Although the use of satellite technologies has, of late, gained prominence in generating timely and spatially explicit information on drought and climate variability impacts across different regions, they are somewhat hampered by difficulties in detecting drought evolution due to its complex nature, varying scales, the magnitude of its occurrence, and inherent data gaps

ENVIRONMENTAL SECURITY AND SEASONAL VARIABILITY:REMOTE SENSING AND MODELING APPLICATION FOR THE MONITORING OF SAHELIAN NATURAL RESOURCES

Il lavoro sviluppato in questa Tesi si \ue8 incentrato sullo studio dei sistemi pascolivi delle regioni del Sahel, Africa Occidentale, tramite tecniche e strumenti del telerilevamento satellitare. L\u2019area oggetto di studio \ue8 una fascia di savana semi-arida, rappresentate la zona di transizione tra il Sahara a nord e le foreste del golfo di Guinea a sud. La regione \ue8 caratterizzata da ana marcata stagionalit\ue0, con una breve stagione umida (da Giugno ad Ottobre) in cui concentra gran parte delle produzione di biomassa vegetale e di conseguenza la produzione di derrate alimentari, seguita da una lunga stagione secca (Novembre-Maggio). A seconda della distanza dal Sahara le precipitazioni medie annuali vanno dai 150 mm annui ai 500, con elevata variabilit\ue0 tra le annate. In questo sistema cos\uec mutevole la pastorizia transumante \ue8 l\u2019attivit\ue0 antropica che meglio si adattata alle dinamiche stagionali. Difatti le uniche fonti di cibo sono date dalla pastorizia e, ove possibile, da agricoltura di sussistenza di specie molto rustiche come il Miglio (Pennisetum glaucum). Nonostante questi adattamenti la regione ha subito una serie di crisi umanitarie a partire dagli anni 70\u2019 del secolo scorso, causate da un brusco calo delle precipitazioni annuali. Il fenomeno climatico \ue8 risultato essere dovuto ad anomalie di temperature dell\u2019oceano Atlantico, similmente al fenomeno de El Ni\uf1o. Nonostante le piogge siano in lenta ripresa dall\u2019inizio degli anni 90\u2019, ricorrenti crisi umanitarie continuano ad interessare l\u2019area (l\u2019ultima nel 2010), motivo per cui le strategie da adottare per incrementare la sicurezza alimentare dell\u2019area rimangono questioni dibattute. In particolare, essendo il Sahel un\u2019area marginale a ridosso di una zona iper-arida, non vi sono gli estremi per attuare due comuni strategie di food security, l\u2019incremento delle aree coltivate e l\u2019intensificazione delle produzioni. In questo contesto, in cui strategie top-down sono inefficaci o dannose, \ue8 il monitoraggio del territorio che riveste un ruolo cruciale. In particolare in un\u2019area semi-naturale vasta come quella Saheliana, gli strumenti del telerilevamento satellitare sono strategici grazie alla loro capacit\ue0 di fornire dati spazializzati ed ad elevata risoluzione temporale. Scopo del lavoro \ue8 stato quello di contribuire a due aspetti del monitoraggio delle risorse naturali: lo studio di serie storiche di dati satellitari per individuare zone sottoposte a cronico degrado e studiare parametri correlati allo sviluppo della biomassa vegetale ad al suo stato idrico. Mentre il primo lavoro vuole dare informazioni utili alla pianificazione della gestione delle risorse naturali, il secondo vuole fornire informazioni in grado di fotografare in tempo reale l\u2019andamento della stagione corrente. La prima parte del lavoro ha riguardo il confronto sull\u2019intera Africa Occidentale tra il 1998 e il 2009) dei i trend delle cumulate stagionali di NDVI come proxy dello sviluppo vegetazionale, e delle precipitazioni in quanto variabile climatiche guida. I risultati hanno confermato che larga parte del territorio saheliano ha visto queste due variabili come perfettamente concordi durante il decennio passato. Tuttavia sono state evidenziate aree in cui i trend di produzione vegetale non sono spiegati dalle piogge. Aree in cui le produzioni sono aumentate nonostante la sostanziale stabilit\ue0 delle precipitazioni (Anomalous Greening, AG) risultano pi\uf9 frequenti nelle aree pi\uf9 meridionali dell\u2019Africa Occidentale ove \ue8 preponderante l\u2019attivit\ue0 agricola (West Sudanian savannah, 46% degli AG rilevati), mentre zone localizzate di anomalo decremento dell\u2019NDVI (Anomalous Degradation, AD) sono state rilevate nelle zone pi\uf9 aride del Sahel (Sahelian Acacia savannah, 59% degli AD rilevati). La analisi condotte a scala pi\uf9 di dettaglio con immagini ad alta risoluzione (30 m) hanno mostrato come queste anomalie si correlino ad usi e coperture del suolo differenti, con l\u2019AG in aree agricole l\u2019AD in aree marginali ove \ue8 praticabile unicamente la pastorizia. Due casi particolari di AG hanno mostrato eventi particolarmente drammatici in Chad e in Sudan. Entrambi i fenomeni sono risultati, da remoto, in un incremento dello sviluppo vegetazionale non legato alle piogge, dovuto al ritiro delle acque del lago Chad ed all\u2019abbandono delle terre di pascolo a seguito del conflitto del Darfur (2005-2006). I risultati sino a qui ottenuti permettono di sviluppare una mappatura tematica di aree localizzate soggette a cronico degrado, evidenziando in un sistema semi-naturale largamente legato alle precipitazioni zone in cui altre variabili vanno ad incidere sullo sviluppo vegetazionale. Queste possono essere approfondite dagli esperi locali, in modo da verificare se una popolazione rurale in continua crescita demografia sia incidendo sulla capacit\ue0 di carico dell\u2019ecosistema. La seconda parte del lavoro si \ue8 concentrata sullo stima dello stress idrico e della biomassa, due variabili fondamentali nel monitoraggio delle risorse naturali e pascolive in aree semi-aride. Serie temporali di frazione evapotraspirativa (EF) a bassa risoluzione sono state ottenute grazie alla relazione tra albedo e temperature superficiale. L\u2019EF \ue8 una componente del bilancio energetico ed \ue8 strettamente correlata con la disponibilit\ue0 idrica per la pianta. Le stime risultano avere dinamiche spaziotemporali coerenti con quelle che sono le dinamiche ecologiche della regione (piogge, fase vegetativa etc.) . Inoltre, l\u2019EF \ue8 risultata altamente correlata con flussi energetici misurati a terra da una stazione eddy covariance in Niger (r2 > 0.7). Il metodo implementato \ue8 di sicura utilit\ue0 per la stima dello stress idrico su vaste aree come quella Saheliana, frequentemente interessata da siccit\ue0 e piogge scarse. Stime di produzioni di biomassa sono state ottenute dal prodotto operativo satellitare Dry Matter Productivity (DMP) basato su di un modello di Light Use Efficiency (LUE). Le stime satellitari sono state valutate grazie al confronto con dati di produzione di biomassa pascoliva in 46 siti di misura in Niger lungo 10 anni (2000-2009). Le stime da remoto riportano valori di biomassa (kg/ha) in linea con le produzioni medie annuali dell\u2019area, tra i 200 kg/ha (aree iper-aride in annate sfavorevoli) e i 2000 kg/ha (pascoli altamente produttivi). Tuttavia le correlazioni coi dati di campo risultano basse (r2<0.3), ed il lavoro propone due approcci per incrementare l\u2019accuratezza del modello satellitare. La prima consiste nell\u2019integrazione dell\u2019EF come fattore di efficienza di disponibilit\ue0 idrica, attualmente non considerata dal DMP. L\u2019EF ha permesso di incrementare la capacit\ue0 del modello di LUE di spiegare la variabilit\ue0 dei dati di campo, specialmente su quei siti ove \ue8 pi\uf9 marcata la carenza idrica. Inoltre \ue8 stato verificato che il modello pu\uf2 incrementare la sua accuratezza nel caso in cui diverse Radiation Use Efficency (RUE) siano considerate, e seconda delle differenti coperture vegetali presenti al suolo. Le biomasse di queste \u201cunit\ue0 ecologiche\u201d presentano correlazioni staticamente differenti con le stime satellitari, e si differenziano tra di loro per la loro produttivit\ue0 media (max NDVI) e la loro fenologia (inizio della stagione, SoS). In conclusione, una stima satellitare di biomassa corretta per la disponibilit\ue0 idrica e l\u2019efficienza d\u2019uso della radiazione da parte delle diverse specie vegetali, una volta prodotta operativamente potr\ue0 fornire indicazioni sulla capacit\ue0 di carico dei pascoli nel corso della stagione, permettendo, se necessario, di produrre tempestive indicazioni sulle aree soggette a criticit\ue0.The research thesis here discussed focused on the Sahelian semi-arid rangeland, a region characterized by strong rainfall seasonality, with few dry months followed by a long dry season. In that area rangeland vegetation and human livelihoods of pastoralism and rainfed crop relies on this peculiar climatic condition. Unfavorable years whit poor or erratic rain results in reducing food supply from agropastoral activities possibly creating food insecurity condition. The work conducted address to main aspects of natural resources monitoring: long term study to identify critical condition that require further analysis to assess potential unbalanced human activities and near real time production of herbaceous biomass relate parameters to support on-going season early warning. In order to achieve the first goal satellite time-series of vegetation index and estimated rainfall were exploited (1998-2009) to identify areas where the two variables have opposite trends. These areas of anomalous hot spots highlight situations where the trend in the development of vegetation is locally driven by other factors mainly linked to human activity, rather than climatic driving force. In the humid regions of the southern part of the study area an increase of NDVI was observed even in conditions where rainfall remained stable (i.e. no significant trend), or even decreased (anomalous greening). These patches of increased NDVI are associated to crop land and savannah land cover classes. A number of hot spots of anomalous conditions along the boundary between the Sahelian and the Sahelian-Sudanian zones were analyzed in details using multi-temporal Landsat TM/ETM+ images and a more detailed analysis was conducted on a test area in Niger analyzing the anomalies in terms in changes of land cover and land use through years. The analysis of changes occurred between pairs of images acquired over the same area confirmed at local scale the trends of land degradation or recovery identified at the coarser resolution of 1km. It is important to underline that these anomalous situations are driven by local causes. Anomalous greening occurring north of Lake Chad is indicative of a critical environmental situation: the shrinking of Lake Chad has uncovered new lands colonized by new agricultural fields. On the contrary, small pockets anomalous degradation have been identified mainly in the Northern part of the study area, in the belt from West Mali to the Chad-Sudan border, which is well-known as fragile zone, where increasing population and human activity (rainfed agriculture, pastoralism and wood exploitation) are in instable equilibrium. Their strong dependence on climatic conditions determines frequent humanitarian crises due to food shortage. In Niger anomalous greening corresponds to the intensification of cropping in a fertile floodplain, whereas in Western Sudan it is associated to the abandonment of agro-pastoral land as a consequence of Darfur conflict. In areas where anomalous vegetation degradation is observed, the demographic framework and associated increase of the exploitation of environmental resources provide the general framework but are not sufficient to explain the local patterns. This result would be a support for natural resources exploitation planning, highlighting local chronic rangeland condition that need detailed analysis to identify causes and specific strategies to compensate the negative effect. The second part of the thesis focused on the estimation of two crucial variables in rangeland monitoring, the water availability for vegetation and the biomass production. Time series of evaporative fraction (EF), strongly linked to the vegetation water status and able to increase the performances of biomass estimation , were estimated from low resolution satellite data exploiting the albedo vs. land surface temperature relation. EF satellite derived resulted highly correlated to flux tower evapotranspiration (ET) measurements. In order to monitoring regional biomass the reliability of an operational LUE based product called Dry Matter Productivity (DMP) was evaluated in Niger rangeland thanks to ground biomass measurements on 46 sites over 10 years. In order to improve this useful biomass prediction at large scales the contribution of EF as a water stress efficiency in DMP algorithm was tested. Moreover the DMP performances were analyzed in relation to different ecological units, homogeneous in terms of vegetation cover and vegetation seasonal behaviour. Results suggest and discuss feasible LUE modelling improvement over the Sahel, taking into account satellite estimation of water availability and different radiation use efficiency for distinct plant communities. In conclusion, satellite biomass estimation corrected by water availability and including eco-types radiation use efficiency, once operationally produced and validated, could provide the necessary information for i) the creation of near real time bulletin of ongoing season and ii) if the case, the identification potential critical situation occurrence due to food shortage