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Abstract Analyzing intra-annual stream flow can reveal the main causes for runoff changes and the contributions of climate variability and human activities. For this purpose, the Mann–Kendall and cumulative rank difference (CRD) tests, and the double mass curve method, were applied to a time series of hydro-meteorological variables from 1971 to 2010 in the Tajan River basin in Iran. Results indicated that runoff changes in the wet and dry seasons after 1999 had significant respective decreasing and increasing trends, at the 0.01 confidence level, due to dam construction. In the pre-dam period (1991–1998), the results of the double mass curve method showed that climate variability and human activities contributed 57.76% and 42.24%, respectively, to the runoff decrease during the wet season. For the post-dam period (1999–2010), climate variability and anthropogenic activities contributed 24.68% and 75.32%, respectively, to the wet season runoff decrease of 116.55 mm. On the other hand, in the same period during the dry season, climate variability contributed −30.68% and human activities contributed 130.68% to the runoff increase of 41.45 mm. It is evident that runoff changes in both wet and dry seasons were mainly due to human activities associated with dam construction to meet water supply demands for agriculture.
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Large-scale flood risk assessment is essential in supporting national and global policies, emergency operations and land-use management. The present study proposes a cost-efficient method for the large-scale mapping of direct economic flood damage in data-scarce environments. The proposed framework consists of three main stages: (i) deriving a water depth map through a geomorphic method based on a supervised linear binary classification; (ii) generating an exposure land-use map developed from multi-spectral Landsat 8 satellite images using a machine-learning classification algorithm; and (iii) performing a flood damage assessment using a GIS tool, based on the vulnerability (depth–damage) curves method. The proposed integrated method was applied over the entire country of Romania (including minor order basins) for a 100-year return time at 30-m resolution. The results showed how the description of flood risk may especially benefit from the ability of the proposed cost-efficient model to carry out large-scale analyses in data-scarce environments. This approach may help in performing and updating risk assessments and management, taking into account the temporal and spatial changes in hazard, exposure, and vulnerability.