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GIS‐based modelling of soil erosion processes using the modified‐MMF (MMMF) model in a large watershed having vast agro‐climatological differences 
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下载免费PDF全文 The present study demonstrates a spatially distributed application of a field‐scale annual soil loss model, the modified‐MMF (MMMF), to a large watershed using hydrological routing techniques, remote sensing data and geospatial technologies. In this study, the MMMF model is implemented after incorporating the corrections suggested in recent literature along with appropriate modifications of the model to suit the agro‐climatological conditions prevailing in most parts of India. Sensitivity analysis carried out through an Average Linear Sensitivity approach indicates that the model outputs are highly sensitive to soil moisture (MS), bulk density (BD), effective hydraulic depth (EHD), ground cover (GC) and settling velocity for clay (VSc). During calibration and validation, the performance evaluation statistics are mostly in the range of very good to satisfactory for both runoff and soil loss at the watershed outlet. Even spatial validation of the results of intermediate processes in the water phase and the sediment phase, although qualitative, seems to be reasonable and rational. Furthermore, the soil erosion severity analysis for different land‐uses existing in the watershed indicates that about 90% of the watershed area, especially that occupied by agricultural lands, is vulnerable to the long‐term effects of soil erosion. Copyright © 2018 John Wiley & Sons, Ltd. 相似文献
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This study presents a Geographic Information System (GIS)‐based distributed rainfall‐runoff model for simulating surface flows in small to large watersheds during isolated storm events. The model takes into account the amount of interception storage to be filled using a modified Merriam ( 1960 ) approach before estimating infiltration by the Smith and Parlange ( 1978 ) method. The mechanics of overland and channel flow are modelled by the kinematic wave approximation of the Saint Venant equations which are then numerically solved by the weighted four‐point implicit finite difference method. In this modelling the watershed was discretized into overland planes and channels using the algorithms proposed by Garbrecht and Martz ( 1999 ). The model code was first validated by comparing the model output with an analytical solution for a hypothetical plane. Then the model was tested in a medium‐sized semi‐forested watershed of Pathri Rao located in the Shivalik ranges of the Garhwal Himalayas, India. Initially, a local sensitivity analysis was performed to identify the parameters to which the model outputs like runoff volume, peak flow and time to peak flow are sensitive. Before going for model validation, calibration was performed using the Ordered‐Physics‐based Parameter Adjustment (OPPA) method. The proposed Physically Based Distributed (PBD) model was then evaluated both at the watershed outlet as well as at the internal gauging station, making this study a first of its kind in Indian watersheds. The results of performance evaluation indicate that the model has simulated the runoff hydrographs reasonably well within the watershed as well as at the watershed outlet with the same set of calibrated parameters. The model also simulates, realistically, the temporal variation of the spatial distribution of runoff over the watershed and the same has been illustrated graphically. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
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RAAJ Ramsankaran Umesh Chandra Kothyari Sanjay Kumar Ghosh Andreas Malcherek Krishnan Murugesan 《水文科学杂志》2013,58(4):872-891
Abstract A relatively simple process-oriented, physically-based distributed (PBD) hydrological model, the distributed runoff and erosion assessment model (DREAM), is described, and a validation study conducted in the semi-forested watershed of Pathri Rao, in the Garhwal Himalayas, India, is reported. DREAM takes account of watershed heterogeneity as reflected by land use, soil type, topography and rainfall, measured in the field or estimated through remote sensing, and generates estimates of runoff and sediment yield in spatial and temporal domains. The model is based on simultaneous solution of flow dynamics, based on kinematic wave theory, followed by solution of soil erosion dynamics. As the storm rainfall proceeds, the process of overland flow generation is dependent on the interception storage and infiltration rates. The components of the soil erosion model have been modified to provide better prediction of sediment flow rates and sediment yields. The validation study conducted to test the performance of the model in simulating soil erosion and sediment yield during different storm events monitored in the study watershed showed that the model outputs are satisfactory. Details of a sensitivity analysis, model calibration and the statistical evaluation of the results obtained are also presented and discussed. It is noteworthy that the distributed nature of the model combined with the use of geographical information system (GIS) techniques permits the computation and representation of the spatial distribution of sediment yield for simulated storm events, and a map of the spatial distribution of sediment yield for a simulated storm event is presented to highlight this capability. Citation Ramsankaran, R., Kothyari, U.C., Ghosh, S.K., Malcherek, A., and Murugesan, K., 2013. Physically-based distributed soil erosion and sediment yield model (DREAM) for simulating individual storm events. Hydrological Sciences Journal, 58 (4), 872–891. 相似文献
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Wei Su Zhong-Ping Sun Dao-Liang Li Raaj Ramsankaran Xiang Zhu Xiang-Yun Guo 《Journal of the Indian Society of Remote Sensing》2009,37(4):631-645
Vegetation condition monitoring has been done from 1975 to 2000 in the waste dump of Haizhou opencast coalmine area, China,
using remote sensing techniques with the objective of improving our understanding of the temporal and spatial variation of
vegetation recovery in the mining dump. Four historical vegetation indexes (NDVI, VF, soil brightness and vegetation greenness)
from two Landsat 2 MSS images and two Landsat 5 TM images are extracted and analyzed. For the purpose of comparison and analysis
two improved techniques such as normalization grading of change slope and image segmentation were used in this study. Based
on the results obtained through the above analysis two conclusions are derived: (1) vegetation recovery in the study area
is in an improved condition, (2) two remote sensing based vegetation indexes such as VF and NDVI are the optimal parameters
to monitor vegetation condition, which could be used as the indicators of land reclamation progress in the mining area. 相似文献
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