This study focuses on the development of two GIS-based approaches that are used jointly to evaluate the groundwater resources associated with granular aquifers in shield environments. The first approach is a multi-criteria analysis (MCA) using an analytical hierarchic process (AHP) based on geological and hydrogeological data for ranking the probability of finding readily available groundwater resources in a specific territory. The second approach relies on GIS-based geometric calculations that were developed for evaluating the extent and volume of aquifers. The approaches are applied on a 100?×?100 m grid in a 185,000-km2 area corresponding to watersheds of the James Bay area in Quebec, Canada. The MCA-AHP approach revealed that the unconfined granular aquifers that present the highest aquifer potential (AP) are sparsely distributed and mostly associated with glaciofluvial formations such as the Harricana and Sakami moraines. The geometric calculations approach allowed for estimating that the total volume of groundwater stored in the unconfined granular aquifers reaches approximately 40 km3. When used jointly, the two approaches reveal that the shallow unconfined aquifers that require increased groundwater protection account for approximately 5% of the territory. In areas of confined granular aquifers, the highest APs are located in river valleys and lowlands. A sensitivity analysis conducted on the MCA-AHP approach revealed that the grid size does not significantly affect the results. Therefore, the approach was expanded northward, to a 490,000-km2 territory reaching the Ungava Bay area. The proposed method could be adapted and applied in other shield areas.
A methodology for groundwater evaluation has been developed by the combined use of numerical model and spatial modeling using GIS. The developed methodology has been applied on the sub-basin of the Banganga River, India. Initially, the groundwater potential zones have been delineated by spatial modeling. Different thematic maps of the basin like geology, geomorphology, soil, drainage, slope factor and landuse/landcover have been used to identify the groundwater potential zones. Further, the groundwater flow model for the study area has been developed in the MODFLOW. The groundwater flow vector map has been developed and superimposed on the potential zone map to validate the results of spatial modeling. Finally, the different scenarios have been conceptualized by varying the discharge of the wells and purposing the location for new rainwater harvesting structures. Results reveal that increasing the discharge of the wells in the potential zones put less stress on the aquifer. The suggested locations of rainwater harvesting structures also help to reduce the overall decline of groundwater in the area. The hydrological and spatial modeling presented in this study is highly useful for the evaluation of groundwater resources and for deciding the location of rainwater harvesting structures in semi-arid regions. 相似文献
Water Resources - Predicting the Suspended Sediment Load (SSL) of the river is a very significant and challenging task. Being a non-linearity in the SSL data, it requires a non-linear method to get... 相似文献
One of the aims of sewer networks is the protection of population against floods and the reduction of pollution rejected to the receiving water during rainy events. To meet these goals, managers have to equip the sewer networks with and to set up real-time control systems. Unfortunately, a component fault (leading to intolerable behaviour of the system) or sensor fault (deteriorating the process view and disturbing the local automatism) makes the sewer network supervision delicate. In order to ensure an adequate flow management during rainy events it is essential to set up procedures capable of detecting and diagnosing these anomalies.
This article introduces a real-time fault detection method, applicable to sewer networks, for the follow-up of rainy events. This method consists in comparing the sensor response with a forecast of this response. This forecast is provided by a model and more precisely by a state estimator: a Kalman filter. This Kalman filter provides not only a flow estimate but also an entity called ‘innovation’. In order to detect abnormal operations within the network, this innovation is analysed with the binary sequential probability ratio test of Wald. Moreover, by crossing available information on several nodes of the network, a diagnosis of the detected anomalies is carried out. This method provided encouraging results during the analysis of several rains, on the sewer network of Seine-Saint-Denis County, France. 相似文献
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