The role of remote sensing data for monitoring different parameters in the study of ecosystems has been increasing. Particularly the development of different indices has played a great role to study the properties of vegetation and vegetation dynamics in large countries. In addition to this, satellite rainfall estimate data has been used to study the pattern of precipitation in areas where station rain-gauge data is not available. The Normalized Difference Vegetation Index (NDVI) and rainfall estimates data from the National Oceanic and Atmospheric Administration (NOAA) satellites were used to investigate the spatio-tempotal pattern of precipitation and the response of vegetation to precipitation in Ethiopia from 1996 to 2008. The patterns were studied in different land cover classes using data from the Global Land Cover Network (GLCN). The spatial patternof NDVI and precipitation showed that vegetation responded directly to precipitation. The seasonal patterns showed that there was between 0 to 3 months lag between precipitationand vegetation. However it was not possible to draw conclusion regarding the annual trendsof precipitation and NDVI because of the nature of the NDVI data, which was produced using the 10 day maximum composite values.

Most of the working population in Ghana are farmers. It is of importance for them to know where and when precipitation will occur to prevent crop losses due to droughts and floodings. In order to have a sustainable agriculture, improved rainfall forecasts are needed. One way to do that is to enhance the initial conditions for the rainfall models. In the mid-latitudes, in-situ rainfall observations and radar data are used to monitor weather and measure rainfall. However, due to the lack of station data and the present absence of a radar network in West Africa, other rainfall estimates are needed as substitutes. The rainfall amount in convective systems, dominating in West Africa, is coupled to their vertical structure. Therefore, satellite measurements of cloud top temperatures and microwave scatter, as well as the number of lightning, can be used to estimate the amount of rainfall. In this report, derived rainfall estimates from satellites and the use of lightning data are analysed to see how well they estimate the actual rainfall amount. The satellite datasets used in this report are NOAA RFE2.0, NOAA ARC2, and the EUMETSAT MPE. The datasets were compared to in-situ measurements from GTS- and NGO collaborating observation stations in order to verify which satellite dataset that best estimates the rainfall or, alternatively, if a combination between two or all the datasets is a better approach. Lightning data from Vaisala GLD360 have been compared to GTS-station data and RFE2.0 to see if a relation between the number of lightning and rainfall amount could be found. It was also tested whether a combination between the satellite- and lightning data could be a better estimate than the two approaches separately. Rainfall estimates from RFE2.0 alone showed the best correlation to GTS- and the NGO collaborating station data. However, a difference in how well RFE2.0 estimated rainfall at GTS-stations compared to reference stations was seen. Comparing RFE2.0 to GTS-stations showed a better correlation, probably due to the use of these observations in the build up of RFE2.0. Even though RFE2.0 showed the best correlation compared to other datasets, satellite estimates showed in general poor skill in catching the actual rainfall amount, strongly underestimating heavy rainfall and somewhat overestimating lighter rainfall. This is probably due to the rather basic assumptions that the cloud top temperature is directly coupled to rain rate and also the poor temporal resolution of the polar orbiting satellites (carrying microwave sensors). Better instruments and algorithms need to be developed to be able to use satellite datasets as an alternative to rainfall measurements in West Africa. Furthermore, due to the lack of station data, only tentative results between GLD360 and GTS-stations could be made, showing a regime dependence. When further analysed to RFE2.0, a stronger temporal dependence, i.e. seasonal variation, rather than a spatial one was seen, especially during the build up of the monsoon. However, due to poor rainfall estimates from RFE2.0, no accurate rainfall-lightning relation could be made but trends regarding the relation were seen. The use of GLD360 showed to be an effective way to erase false precipitation from satellite estimates as well as locating the trajectory of convective cells. To be able to further analyse rainfall/lightning relation, more measurements of the true rainfall is needed from e.g. a radar. / Majoriteten av Ghanas befolkning arbetar inom jordbrukssektorn. Det är viktigt för jordbrukarna att veta när och var nederbörd kommer att falla för att deras skörd inte ska bli förstörd av till exempel torka eller översvämningar. Det behövs därför bättre nederbördsprognoser för ett hållbart jordbruk. Ett sätt att få mer noggranna prognoser är att förbättra initialvärden till nederbördsmodellerna. Vid de mellersta breddgraderna på norra halvklotet används nederbördsmätningar från in-situ stationer samt data från radarsystem som initialvärden, men på grund av få mätstationer och inget radarsystem i västra Afrika behövs alternativa nederbördsestimater. Nederbörden i västra Afrika domineras av konvektiva system, vars regnmängd är kopplad till dess vertikala struktur. Satellitmätningar av molntoppstemperaturen och mikrovågornas spridning och absorption, liksom antalet blixtar är också relaterat till molnets struktur och kan därför användas för att estimera nederbördsmängden. I den här rapporten analyserades nederbördsestimater från satellitdata samt användning av blixtdata för att undersöka hur bra metoderna är på att estimera den verkliga nederbördsmängden. Satellitdataseten som analyserades var NOAA RFE2.0, NOAA ARC2 och EUMETSAT MPE. Dataseten jämfördes med in-situ mätningar från GTS-stationer samt observationerfrån NGO-samarbetande jordbrukare för att verifiera vilket satellitdataset som ger det bästa nederbördsestimatet, alternativt att en kombination mellan två eller alla dataset ger det bästa estimatet. Vidare har blixtdata från Vaisala GLD360 jämförts med GTS-stationer och RFE2.0 för att se om antalet blixtar är relaterat till nederbördsmängden. Slutligen har det också undersökts om en kombination mellan satellit- och blixtdata är ett bättre än de två metoderna separat. Nederbördsestimater från RFE2.0 visade på bäst korrelation med både GTS- och NGO-stationer. En tydlig skillnad noterades dock i RFE2.0:s förmåga att estimera nederbörd vid jämförelse mellan de två stationsdataseten. En bättre korrelation mellan RFE2.0 och GTS-stationerna påvisades, troligen för att RFE2.0 använder dessa observationer i uppbyggnaden av datasetet. Även om RFE2.0 visade på bäst korrelation i jämförelse med ARC2 och MPE var samtliga satellitdataset dåliga på att estimera den verkliga nederbördsmängden. De underestimerar starkt stora mängder nederbörd samtidigt som de överestimerar små mängder. Anledningen är troligen det relativt enkla antagandet att molntoppstemperaturen är direkt kopplad till molnets regnmängd samt den dåliga tidsupplösningen på de polära satelliterna som är utrustade med mikrovågssensorer. För att satellitdataseten ska kunna användas som ett alternativt nederbördsestimat i Västafrika behövs bättre mätinstrument och algoritmer. Vid analysen mellan GLD360 och GTS-stationer kunde, på grund av för få stationsdata, endast övergripande resultat erhållas. Ett områdesberoende gick dock att urskilja som vid en ytterligare analys mellan GLD360 och RFE2.0 visade på ett större säsongsberoende, särskilt under uppbyggnaden av monsunperioden i april och maj. Eftersom RFE2.0 visade sig ha dåliga nederbördsestimat kunde ingen noggrann koppling hittas, utan resultatet visade på trender samt möjligheter att kunna använda blixtdata som ett alternativt nederbördsestimat. Till exempel visade det sig att GLD360 kunde användas som ett verktyg för att sålla bort falsk nederbörd från satellitestimat samt identifiera trajektorien för ett konvektivt system. För en djupare analys i att relatera blixtar och nederbörd i Västafrika krävs bättre tekniker för att estimera nederbörd eller fler in-situ observationer.

In most regions of the world, and particularly in developing countries, the possibility and reliability of hydrologic predictions is severely limited, because conventional measurement networks (e.g. rain and stream gauges) are either nonexistent or sparsely located. This study, therefore, investigates various systems methods and newly available data acquisition techniques to evaluate their potential for improving hydrologic predictions in poorly gaged and ungaged watersheds.Part One of this study explores the utility of satellite-remote-sensing-based rainfall estimates for watershed-scale hydrologic modeling at watersheds in the Southeastern U.S. The results indicate that satellite-based rainfall estimates may contain significant bias which varies with watershed size and location. This bias, of course, then propagates into the hydrologic model simulations. However, model performance in large basins can be significantly improved if short-term streamflow observations are available for model calibration.Part Two of this study deals with the fact that hydrologic predictions in poorly gauged/ungauged watersheds rely strongly on a priori estimates of the model parameters derived from observable watershed characteristics. Two different investigations of the reliability of a priori parameter estimates for the distributed HL-DHMS model were conducted. First, a multi-criteria penalty function framework was formulated to assess the degree of agreement between the information content (about model parameters) contained in the precipitation-streamflow observational data set and that given by the a priori parameter estimates. The calibration includes a novel approach to handling spatially distributed parameters and streamflow measurement errors. The results indicated the existence of a significant trade-off between the ability to maintain reasonable model performance while maintaining the parameters close to their a priori values. The analysis indicates those parameters responsible for this discrepancy so that corrective measures can be devised. Second, a diagnostic approach to model performance assessment was developed based on a hierarchical conceptualization of the major functions of any watershed system. "Signature measures" are proposed that effectively extract the information about various watershed functions contained in the streamflow observations. Manual and automated approaches to the diagnostic model evaluation were explored and were found to be valuable in constraining the range of parameter sets while maintaining conceptual consistency of the model.

Depuis le développement des mesures satellites de nombreuses missions spatiales sont dédiées au suivi de l'atmosphère et de la surface terrestre. Ces travaux de thèse s'inscrivent dans le cadre de la mission Megha-Tropiques dédiée au cycle de l'eau et de l'énergie en zone tropicale. L'objectif est d'évaluer le potentiel des estimations de précipitation par satellite pour des applications hydrologiques en zone tropicale. Les Tropiques réunissent les plus grands fleuves du globe, mais ne bénéficient pas de réseaux d'observation in-situ denses et continus permettant une gestion intégrée efficace de la ressource et des systèmes d'alertes. Les estimations des précipitations issues des systèmes d'observation satellite offrent une alternative pour ces bassins peu ou pas instrumentés et souvent exposés aux extrêmes climatiques. C'est le cas du fleuve Niger, qui a subi une grande variabilité climatique depuis les années 1950, mais aussi d'importants changements environnementaux et hydrologiques. Depuis les années 2000, le Niger moyen connaît une recrudescence des inondations pendant la période de crue Rouge (engendrée par ses affluents sahéliens pendant la mousson). A Niamey, des niveaux record de hauteur d'eau et de période d'inondation ont été enregistrés en 2003, 2010, 2012 et 2013, engendrant de nombreuses pertes humaines et matérielles. Ces travaux analysent l'influence du forçage pluviométrique sur les inondations liées à la crue Rouge à Niamey. Une gamme de produits pluviométriques (in situ et satellite) et la modélisation hydrologique (ISBA-TRIP) sont combinés pour étudier : (i) l'apport des produits satellite pour diagnostiquer la crue Rouge récente, (ii) l'impact des caractéristiques des produits et de leurs incertitudes sur les simulations et enfin (iii) l'évaluation du rôle des précipitations, face aux changements de conditions de surface, dans l'évolution de la crue Rouge à Niamey depuis les années 1950. L'étude a mis en évidence l'impact des caractéristiques des estimations des précipitations (cumul, intensité et distribution spatio-temporelle) sur la modélisation hydrologique et le potentiel des produits satellites pour le suivi des inondations. Les caractéristiques des précipitations se propageant dans la modélisation, la détection des inondations est plus efficace avec une approche relative à chaque produit plutôt qu'avec un seuil absolu. Ainsi des produits présentant des biais peuvent être envisagés pour la simulation hydrologique et la détection des inondations. Le nouveau produit TAPEER de la mission MT présente un fort potentiel hydrologique, en 2012 et pour la zone d'étude. D'autre part, l'étude de la propagation de l'erreur associée à ces précipitations a mis en évidence, la nécessité de déterminer la structure du champ d'erreur pour l'utilisation d'une telle information en hydrologie. Enfin la modélisation a été utilisée comme levier pour décomposer les sensibilités de la crue Rouge aux variations des précipitations et des conditions de surface. Pour simuler les changements hydrologiques entre les périodes 1953-1982 et 1983-2012, les changements d'occupation du sol et d'aire de drainage doivent être pris en compte. Puis les variations des précipitations peuvent expliquer les changements majeurs décennaux et annuels entre les années 1983 et 2012. / Since the development of satellite based remote sensing in the 1970s, many missions have been dedicated to monitoring the terrestrial atmosphere and surfaces. Some of these satellites are dedicated to the Tropics with specific orbits. Megha-Tropiques (MT) is devoted to the water and energy cycle in the tropical atmosphere and provides an enhanced sampling for rainfall estimation in the tropical region. This PhD work was initiated within MT hydro-meteorological activities, with the objective of assessing the hydrological potential of satellite rainfall products in the Tropics. The world most important rivers lay in tropical areas where the in situ observation networks are deficient. Alternative information is therefore needed for water resource management and alert systems. The present work focuses on the Niger River a basin which has undergone drastic climatic variations leading to disasters such as droughts and floods. Since 1950, the Niger has been through 3 main climatic periods: a wet period (1950-1960), a long and intense drought period (1970-1980) and since 1990 a partial recovery of the rainfall. These climatic variations and the anthropic pressure, have modified the hydrological behaviour of the basin. Since 2000, the middle Niger River has been hit by an increase of floods hazards during the so-called Red flood period. In Niamey city, the highest river levels and the longest flooded period were recorded in 2003, 2010, 2012 and 2013, leading to heavy casualties and property damage. This study combines hydrological modelling and a variety of rainfall estimation products (satellite and in-situ) to meet several objectives: (i) the simulation of the Niamey Red flood and the detection of floods (during the recent period 2000-2013) (ii) the study of the propagation of satellite rainfall errors in hydrological modelling (iii) the evaluation of the role of rainfall variability, and surface conditions, in the changes of the Red flood in Niamey since the 50s. The global model ISBA-TRIP, is run with a resolution of 0.5° and 3h, and several rainfall products were used as forcing. Products derived from gauges (KRIG, CPC), pure satellite products (TAPEER, 3B42RT, CMORPH, PERSIANN) and mixed satellite products adjusted by rain gauges (3B42v7, RFE2, PERSIANN-CDR). This work confirms the hydrological potential of satellite rainfall products and proposes an original approach to overcome their biases. It highlights the need for documenting the errors associated with the rainfall products and the error structure. Finally, the hydrological modelling results since the 1950s have given a new understanding of the relative role of rainfall and surface conditions in the drastic increase of flood risk in Niamey.