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E:\FOX Backup\Working Disk\Thesis HARI THESE présentée devant l’Université de Nice - Sophia Antipolis en vue de l’obtention du DIPLÔME DE DOCTORAT (arrêté ministériel du 30 mars 1992) Spécialité : Géographie par Hari Gobinda ROY Long term prediction of soil erosion (1950-2025) in a Mediterranean context of rapid urban growth and land cover change Evolution de l’évolution de l’occupation du sol (1950-2025) et impacts sur l’érosion du sol dans un bassin versant méditerranéen Soutenue le 15 septembre 2016 Membres du Jury : Pr Pierre CARREGA Examinateur Pr Dennis FOX Directeur Pr Catherine MERING Rapporteur Pr Laurent RIEUTORT Rapporteur Pr Yves BAUDOUIN Examinateur UMR ESPACE 7300 CNRS Equipe Gestion et Valorisation de l’Environnement Université de Nice – Sophia Antipolis, 98 Blvd Edouard Herriot, 06204 Nice ABSTRACT The European Mediterranean coastal area has experienced widespread land cover change since 1950 because of rapid urban growth and expansion of tourism. Urban sprawl and other land cover changes occurred due to post-war economic conditions, population migration, and increased tourism. Land cover change has occurred through the interaction of environmental and socio-economic factors, including population growth, urban sprawl, industrial development, and environmental policies. In addition, rapid expansion of tourism during the last six decades has caused significant socioeconomic changes driving land cover change in Euro-Mediterranean areas. Mediterranean countries from Spain to Greece experienced strong urban growth from the 1970’s onwards, and a moderate growth rate is projected to continue into the future. Land cover change can result in environmental changes such as water pollution and soil degradation. Several previous studies have shown that Mediterranean vineyards are particularly vulnerable to soil erosion because of high rainfall intensity and the fact that vineyards are commonly located on steeper slopes and the soil is kept bare during most of the cultivation period (November to April) when precipitation is at its highest. To date, few Euro-Mediterranean studies of land cover change explicitly explore spatial constraints on land cover change patterns. Many modeling tools have been developed to explore and evaluate future land cover change possibilities, and time scales have varied greatly from one study to another. Most LUCC models relate change to physical and socio-economic factors in a grid of cells. The main objective of this thesis is to predict long-term soil erosion evolution in a Mediterranean context of rapid urban growth and land use change at the catchment scale. In order to achieve this, the following specific aims have been formulated: (i) to analyze the spatial dynamics of land cover change from 1950 to 2008; (ii) to compare the impact of historical time periods on land cover prediction using different time scales; (iii) to test the impacts of spatial extent and cell size on LUCC modeling; and (iv) to predict the impact of land cover change on soil erosion for 2025. The study area of approximately 235 km² is situated in the Var, a department located in southeastern France near the Gulf of St. Tropez. The western and higher part of the watershed, i consisting of about 70% of the catchment, is mostly pine and oak forest; the topography is uneven with the highest elevation at about 650 m. The eastern and lower part of the catchment is a gently sloping alluvial plain. The catchment area is characterized by a Mediterranean climate with hot, dry summers and cooler, rainy winters. Land cover maps were screen-digitized from digital orthorectified aerial photographs (1950, 1982, 2003, 2008, & 2011) purchased from the Institut Géographique National. In order to determine past land cover change patterns, surfaces were classified into five land cover categories based on visual interpretation, namely forest, vineyard, grassland, urban, and suburban. To analyze the spatial dynamics of past land cover change and create a model to predict future land cover change, surfaces were simplified into four categories, namely forest, vineyard, grassland, and built area. (Urban and suburban areas were combined into built area due to their small amount of coverage compared to other land cover categories.) Finally, soil erosion was predicted for the vineyard category. The aerial photographs from 1950 were the first high-quality post-Second World War photographs available when the area was still largely rural. An intermediate date of 1982 was selected between 1950 and the most recent photographs. Aerial photographs from 1982 represent land cover conditions at the beginning of rapid urban sprawl. Cell size of all digitized maps was changed from 1 m to 25 m to make land cover layers compatible with the 25 m DEM used for the creation of topographic and distance variables. Land cover change was analyzed using the Land Change Modeler (LCM) and CROSSTAB modules of IDRISI (Eastman, 2012). Explanatory variables were selected through Cramer’s coefficient. Land cover maps for 2011 were predicted using three different time scales, namely 1950-1982, 1982-2003, and 2003-2008. These predictions were then compared to the actual digitized land cover map from 2011 to evaluate model accuracy. Major topographic and distance variables were identified including the following: slope, altitude, distance from roads, distance from built area in initial year, and distance from streams. In addition, three constraints and incentives-- forest to built area, vineyard to built area, and grassland to built area-- were included in the prediction process. These were created from the Plan Local d’Urbanisme (PLU) and the Schéma de Cohérence Territoriale (SCOT). Kappa index and confusion matrix were used to evaluate the model’s accuracy. LCM of IDRISI was used to predict land cover in 2011. ii LCC dynamics, both in terms of absolute and relative change, were first analyzed using intensity analysis. Then land cover was predicted for 2011 for large (79.1 km²) and small (36.6 km²) windows using cell sizes of 25 m, 50 m, 100 m. Spatial resolution effects were also analyzed by upscaling from 25 m to 50 m and 100 m and then downscaling back to 25 m. Here spatial extent is equivalent to increasing the proportional area of a dormant category. Two spatial extents (36.6 km² and 79.1 km²) and three resolutions (25 m, 50 m and 100 m) were tested. The 50 m and 100 m resolutions were downscaled back to 25 m. Land cover maps dated from 1950, 1982, 2003 and 2011, and LCM was used to predict 2011 cover. Finally, RUSLE was used to predict soil erosion for different years: 1950, 1982, 2003, 2011, and 2025 (predicted). This study found that land cover changes were concentrated mainly in the alluvial plain and adjoining foothills. Forest remained the dominant land cover in the catchment, changing only slightly from around 86% to 85% in 1950-2008. However, forested areas underwent significant swapping with vineyard and grassland areas. The catchment experienced a marked decrease in vineyard (-28%) and a substantial increase in grassland (about +50%). Urban and suburban areas remained a minor component of the catchment (about 3%), but showed a dramatic relative increase (more than 20 times initial cover). Built areas grew at the expense of vineyards, and grassland also increased on former vineyards. Losses in vineyard were offset in part by growth of vineyard on previously forested foothills close to the alluvial plain. This finding differs from other Mediterranean studies that have shown agriculture (i.e. vineyard cultivation), in the face of urban pressure, moving to steeper marginal slopes, while abandoning fertile plain soils to grassland and forest. Topography (altitude, slope) and distance variables (from roads, streams, built area, and the sea) strongly influenced land cover change dynamics in the catchment between 1950 and 2008. Vineyard located near streams was converted mainly to grassland. Built areas were strongly dependent on roads and former built areas for expansion but expanded little near streams due to flooding risks. Finally, the rate of change was greater during the latter part of the study (1982-2008) than in the earlier period (1950-1982). Kappa index and confusion matrix were used to evaluate the model’s accuracy. Altitude, slope, and distance from roads had the greatest impact on land cover changes among all variables tested. Good to perfect level of spatial agreement and perfect level of quantitative agreement were observed in long to short time scale simulations. Kappa indices (Kquantity = 0.99 and Klocation iii = 0.90) and confusion matrices were good for intermediate and best for short time scale. The results indicate that shorter time scales produce better predictions. Time scale effects have strong interactions with specific land cover dynamics; for example, stable land cover categories are easier to predict than rapidly changing ones, and overall quantity is easier to predict than specific location over longer time periods. Spatial extent had a major impact on land cover change dynamics as absolute and relative values of gains/losses were inverted when dormant category increased. It also improved Cramer’s V values (1.3 to 1.5 times greater) and disagreement values artificially improved (twice as good) in change prediction; this resulted from an increase in the number of correctly classified persistent cells. Upscaling/downscaling revealed that coarser cell sizes lose considerable predictive power (1.5 to 2 times greater allocation errors), despite validation statistics. In future studies, dormant category area should be minimized and upscaling/downscaling should be done if data are modeled at coarser resolutions than original cell size. Land use changes were found to have a significant impact on soil erosion rates in different years. Between 1950 and 2003, soil erosion prone areas increased in the eastern and central parts of the study area; there was decreased soil erosion in the north and western parts of the catchment due a shift from vineyard to built area in the alluvial plain area.
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