排序方式： 共有59条查询结果，搜索用时 15 毫秒
41.
Predictive modeling of hydrological time series is essential for groundwater resource development and management. Here, we examined the comparative merits and demerits of three modern soft computing techniques, namely, artificial neural networks (ANN) optimized by scaled conjugate gradient (SCG) (ANN.SCG), Bayesian neural networks (BNN) optimized by SCG (BNN.SCG) with evidence approximation and adaptive neuro-fuzzy inference system (ANFIS) in the predictive modeling of groundwater level fluctuations. As a first step of our analysis, a sensitivity analysis was carried out using automatic relevance determination scheme to examine the relative influence of each of the hydro-meteorological attributes on groundwater level fluctuations. Secondly, the result of stability analysis was studied by perturbing the underlying data sets with different levels of correlated red noise. Finally, guided by the ensuing theoretical experiments, the above techniques were applied to model the groundwater level fluctuation time series of six wells from a hard rock area of Dindigul in Southern India. We used four standard quantitative statistical measures to compare the robustness of the different models. These measures are (1) root mean square error, (2) reduction of error, (3) index of agreement (IA), and (4) Pearson’s correlation coefficient (R). Based on the above analyses, it is found that the ANFIS model performed better in modeling noise-free data than the BNN.SCG and ANN.SCG models. However, modeling of hydrological time series correlated with significant amount of red noise, the BNN.SCG models performed better than both the ANFIS and ANN.SCG models. Hence, appropriate care should be taken for selecting suitable methodology for modeling the complex and noisy hydrological time series. These results may be used to constrain the model of groundwater level fluctuations, which would in turn, facilitate the development and implementation of more effective sustainable groundwater management and planning strategies in semi-arid hard rock area of Dindigul, Southern India and alike. 相似文献
42.
Saumen Maiti Gautam Gupta Vinit C. Erram Ram Krishna Tiwari 《Environmental Earth Sciences》2013,68(3):779-794
Modeling resistivity profiles, especially from hard rock areas, is of specific relevance for groundwater exploration. A method based on Bayesian neural network (BNN) theory using a Hybrid Monte Carlo (HMC) simulation scheme is applied to model and interpret direct current vertical electrical sounding measurements from 28 locations around the Malvan region, in the Sindhudurg district, southwest India. The modeling procedure revolves around optimizing the objective function using the HMC based sampling technique which is followed by updating each trajectory by integrating the Hamiltonian differential equations via a second order leapfrog discretization scheme. The inversion results suggest a high resistivity structure in the north-western part of the area, which correlates well with the presence of laterites. In the south-western part, a very high conductive zone is observed near the coast indicating an extensive influence of saltwater intrusion. Our results also show that the effect of intrusion of saline water diminishes from the south-western part to the north-eastern part of the region. Two dimensional modeling of four resistivity profiles shows that the groundwater flow is partly controlled by existing lineaments, fractures, and major joints. Groundwater occurs at a weathered/semi-weathered layer of laterite/clayey sand and the interface of overburden and crystalline basement. The presence of conduits is identified at a depth between 10 and 15 m along the Dhamapur–Kudal and Parule–Oros profiles, which seems to be potential zone for groundwater exploration. The NW–SE trending major lineaments and its criss-cross sections are indentified from the apparent and true resistivity surface map. The pseudo-section at different depths in the western part of the area, near Parule, shows extensive influence of saltwater intrusion and its impact reaching up to a depth of 50 m from the surface along the coastal area. Further, the deduced true electrical resistivity section against depth correlates well with available borehole lithology in the area. Present analyses suggest that HMC-based BNN method is robust for modeling resistivity data especially in hard rock terrains. These results are useful for interpreting fractures, major joints, and lineaments and crystalline basement rock and also for constraining the higher dimensional models. 相似文献
43.
N. C. Maiti 《Pure and Applied Geophysics》1978,116(1):198-211
The displacement produced in a semi-infinite, homogeneous, isotropic elastic medium by the application of shearing traction over a circular portion of the half-space has been evaluated in exact form by Cagniard's Technique (Cagniard, 1962;Gakenheimer andMiklowitz, 1969). 相似文献
44.
45.
Surface coal mining inevitably deforests the land, reduces carbon (C) pool and generates different land covers. To re-establish the ecosystem C pool, post-mining lands are often afforested with fast-growing trees. A field study was conducted in the 5-year-old unreclaimed dump and reclaimed coal mine dump to assess the changes in soil CO2 flux and compared with the reference forest site. Changes in soil organic carbon (SOC) and total nitrogen stocks were estimated in post-mining land. Soil CO2 flux was measured using close dynamic chamber method, and the influence of environmental variables on soil CO2 flux was determined. Woody biomass C and SOC stocks of the reference forest site were threefold higher than that of 5-year-old reclaimed site. The mean soil CO2 flux was highest in 5-year-old reclaimed dump (2.37 μmol CO2 m?2 s?1) and lowest in unreclaimed dump (0.21 μmol CO2 m?2 s?1). Soil CO2 flux was highly influenced by environmental variables, where soil temperature positively influenced the soil CO2 flux, while soil moisture, relative humidity and surface CO2 concentration negatively influenced the soil CO2 flux. Change in soil CO2 flux under different land cover depends on plant and soil characteristics and environmental variables. The study concluded that assessment of soil CO2 flux in post-mining land is important to estimate the potential of afforestation to combat increased emission of soil CO2 at regional and global scale. 相似文献
46.
The study aimed to assess the heavy metals(K, Ca, Ti, Cr, Mn, Fe, Ni, Cu, Zn, As, Pb, Sr, Zr) contamination in the soil of mine affected Singaran river basin and to analyse spatial variation in the contamination level considering 32 soil samples. Elemental analysis of soil samples has been performed through Energy Dispersive X-ray Analysis(EDX) to quantify the elemental concentration(mg kgà1). Heavy metal concentrations have been assessed through geo-accumulation index(Igeo) and enrichment factor(EF).Indices showed soils have moderate accumulation of most of the metals with moderate enrichment of Sr,Zr, Zn, Cu and Ni. Soil contamination level assessment has been carried out using indices like Contamination Factor(CF), degree of contamination(C_(deg)), modified degree of contamination(m C_(deg)) and Pollution Load Index(PLI). CF shows moderate to considerable contamination by Sr, Zr, Ca, Cu, Mn, Zn and Ni. Mean indices values(m C_(deg)and PLI for the entire basin are 3.38 and 2.23 respectively) show low to moderate level of soil contamination. These indices result have been mapped and analysed in GIS platform to get spatial variation of pollution level. Opencast mines dominate middle catchment area and so is comparatively contaminated. Sample sites 11, 18 and 25 evidenced high values of all indices of pollution load. From the ecological standpoint Ecological Risk Factor(Er) and Potential Ecological Risk Index(RI) have been estimated to assess regional threat to native soil environment and it shows low ecological risk potential. Analysis shows that mine dominated soil of the entire Singaran basin is less contaminated in all respect but tends to the moderate contamination level at the mid-catchment area,especially by Sr, Zr, Zn, Cu and Ni. 相似文献
47.
The Ganga River is one of the largest river systems in the world that has built extensive alluvial plains in northern India. The stretch of the Lower Ganga River is vulnerable to siltation because of: (a) the naturally low slope in the alluvial stretch; (b) the confluence of several highly sediment-charged rivers such as the Ghaghra, Gandak, and Kosi; and (c) the reduction in non-monsoon flows because of upstream abstractions of both surface and groundwater. Additionally, the Farakka barrage has impacted the morphology of the Ganga River significantly, both upstream and downstream of the barrage. Large-scale siltation in several reaches has reduced the channel capacity, leading to catastrophic floods in this region even at low discharges. This work has utilized historical remote sensing data and UAV surveys to reconstruct channel morphodynamics and compute sediment volumes accumulated in the channel belt along the Lower Ganga River between Buxar and Farakka. The work was carried out by dividing the total length of the river into four continuous stretches: (a) Buxar–Gandhighat (GW1, 160 km); (b) Gandhighat–Hathidah (GW2, 106 km); (c) Hathidah–Azmabad (GW3, 182 km); and (d) Azmabad–Farakka (GW4, 132 km). We document that major ‘hotspots’ of siltation have developed in several reaches of the Lower Ganga during the last four to five decades. Sediment budgeting using planform maps provides estimates of ‘extractable’ volumes of sediment in GW1, GW2, GW3, and GW4 as 656 ± 48, 706 ± 52, 876 ± 71, and 200 ± 85 Mm3, respectively. These estimates are considerably lower than those computed from the hydrological approach using observed suspended sediment load data, which assumes uniform sedimentation between two stations. Further, our approach provides reach-scale hotspots of aggradation and estimates of extractable sediment volumes, and this can be very useful for river managers to develop a strategic sediment management plan for the given stretch of the Ganga River. 相似文献
48.
Shoreline change analysis and prediction are important for integrated coastal zone management, and are conventionally performed by field and aerial surveys. This paper discusses an alternative cost-effective methodology involving satellite remote sensing images and statistics. Multi-date satellite images have been used to demarcate shoreline positions, from which shoreline change rates have been estimated using linear regression. Shoreline interpretation error, uncertainty in shoreline change rate, and cross-validation of the calculated past shorelines have been performed using the statistical methods, namely, Regression coefficient (R2) and Root Mean Square Error (RMSE). This study has been carried out along 113.5 km of coast adjoining Bay of Bengal in eastern India, over the time interval 1973 to 2003. The study area has been subdivided into seven littoral cells, and transects at uniform interval have been chosen within each cell. The past and future shoreline positions have been estimated over two time periods of short and long terms in three modes, viz., transect-wise, littoral cell-wise and regionally.The result shows that 39% of transects have uncertainties in shoreline change rate estimations, which are usually nearer to cell boundaries. On the other hand, 69% of transects exhibit lower RMSE values for the short-term period, indicating better agreement between the estimated and satellite based shoreline positions. It is also found that cells dominated by natural processes have lower RMSE, when considered for long term period, while cells affected by anthropogenic interventions show better agreement for the short-term period. However, on regional considerations, there is not much difference in the RMSE values for the two periods. Geomorphological evidence corroborates the results. The present study demonstrates that combined use of satellite imagery and statistical methods can be a reliable method for shoreline related studies. 相似文献
49.
E. Verdeny P. Masqu K. Maiti J. Garcia-Orellana J.M. Bruach C. Mahaffey C.R. Benitez-Nelson 《Deep Sea Research Part II: Topical Studies in Oceanography》2008,55(10-13):1461
Particle export from the upper waters of the oligotrophic ocean may play a crucial role in the global carbon cycle. Mesoscale eddies have been hypothesized to inject new nutrients into oligotrophic surface waters, thereby increasing new production and particle export in otherwise nutrient deficient regimes. The E-Flux Program was a large multidisciplinary project designed to investigate the physical, biological and biogeochemical characteristics of cold-core cyclonic eddies that form in the lee of the Hawaiian Islands. There, we investigated particle dynamics using 210Pb–210Po disequilibrium. Seawater samples for 210Pb and 210Po were collected both within (IN) and outside (OUT) of two cyclones, Noah and Opal, at different stages of their evolution as well as from the eddy generation region. Particulate carbon (PC), particulate nitrogen (PN) and biogenic silica (bSiO2) export fluxes were determined using water-column PC, PN, and bSiO2 inventories and the residence times of 210Po. PC and PN fluxes at 150 m ranged from 1.58±0.10 to 1.71±0.16 mmol C m−2 d−1 and 0.22±0.02 to 0.30±0.02 mmol N m−2 d−1 within Cyclones Opal and Noah. PC and PN fluxes at OUT stations sampled during both cruises were of similar magnitudes, 1.69±0.16 to 1.67±0.16 mmol C m−2 d−1 and 0.30±0.03 to 0.26±0.03 mmol N m−2 d−1. The bSiO2 fluxes within Cyclone Opal were 0.157±0.010 mmol Si m−2 d−1 versus 0.025±0.002 mmol Si m−2 d−1 at OUT stations. These results of minimal PC and PN export, but significant eddy-induced bSiO2 fluxes, agree very well with other studies that used a variety of direct and indirect methods. Thus, our results suggest that using elemental inventories and residence times of 210Po is another independent and robust method for determining particle export and should be investigated more fully. 相似文献
50.