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This study aims to propose a framework for assessing climate change in Mediterranean data-sparse contexts. For that purpose, the 309-km2 Lebanese Nahr Ibrahim watershed, extending over 3% of Lebanon's surface, was chosen as a representative of the targeted settings. Generally, holistic climate change assessments encompass both climate trend analysis and future forecasting. According to the World Meteorological Organization, a continuous, homogenous, and uninterrupted climatic record for at least 30 years is needed to fulfill these tasks. Often, some Mediterranean watersheds lack such data and are hence characterized by climatic data scarcity. Such is the case of Lebanon where 30 years of wars have considerably disrupted the country's climatic record. In an effort to overcome this state of data scarcity, remote sensing–derived drought indicators were used to determine the climate's evolution during the last 28 years. For that purpose, several remote sensing indices were extracted from LANDSAT imageries for the period 1990–2018 at a 3-year interval, and were coupled to meteorological indicators. Forecasting was then performed using autoregressive integrated moving average (ARIMA) models. Meteorological indices showed increased variability of precipitations and aridity periods, while remote sensing indicators collectively revealed slight shifts towards increasing droughts. Projections using ARIMA models forecasted increases of 0.9 °C, 0.7 °C, and 0.8 °C for average, maximal, minimal temperatures, and an average 6 mm decrease of precipitations at the 95% confidence level for the year 2030. The presented approach can serve as a tool for proactive climate change mitigation or adaptation plans. [ABSTRACT FROM AUTHOR]

Ponds, as landscape features, are known to regulate climate. Since ponds proliferate or recede due to natural or anthropogenic factors, a variation of pond numbers implies a variation of their climatic effect. Accordingly, this study investigates the impact of ponds on the local climate of the French Claise watershed. The latter was chosen because it contains a pond dense zone and a pondless zone. This repartition makes the Claise an adequate context to reveal the climatic impact of ponds even in the same landscape. To study the pond-climate effect, the parallel evolution of pond numbers variation and subsequent climatic impact must be tracked. Therefore, the remote sensing-derived Normalized Difference Water Index (NDWI) was extracted from LANDSAT images with different acquisition dates to track changes in pond numbers with time. When compared with a pond map established from aerial photography interpretation, the LANDSAT NDWI map revealed an accuracy of 85.74% for pond count and 75% for pond spatial allocation. This validation showed that NDWI is suitable for mapping the proliferation of ponds through time. In order to study the parallel evolution of the climatic effect, the land surface temperature (LST) index was extracted for each LANDSAT map. LST maps revealed that as a result of pond number variation, surface temperatures varied accordingly. A comparison of air temperatures between the ponded zone and pondless zones also revealed that pond zones had lower air temperatures than their direct surroundings. Accordingly, ponds were shown to buffer local microclimates even within the same landscape. [ABSTRACT FROM AUTHOR]