In the numerical simulation of groundwater flow, uncertainties often affect the precision of the simulation results. Stochastic and statistical approaches such as the Monte Carlo method, the Neumann expansion method and the Taylor series expansion, are commonly employed to estimate uncertainty in the final output. Based on the first-order interval perturbation method, a combination of the interval and perturbation methods is proposed as a viable alternative and compared to the well-known equal interval continuous sampling method (EICSM). The approach was realized using the GFModel (an unsaturated-saturated groundwater flow simulation model) program. This study exemplifies scenarios of three distinct interval parameters, namely, the hydraulic conductivities of six equal parts of the aquifer, their boundary head conditions, and several hydrogeological parameters (e.g. specific storativity and extraction rate of wells). The results show that the relative errors of deviation of the groundwater head extremums (RDGE) in the late stage of simulation are controlled within approximately ±5% when the changing rate of the hydrogeological parameter is no more than 0.2. From the viewpoint of the groundwater head extremums, the relative errors can be controlled within ±1.5%. The relative errors of the groundwater head variation are within approximately ±5% when the changing rate is no more than 0.2. The proposed method of this study is applicable to unsteady-state confined water flow systems.
The change in the zonal sea surface temperature gradient (ZSSTG) across the equatorial Pacific plays an important role in the global climate system. However, there has not yet been a consensual conclusion about the changing ZSSTG at either a short-term (from 20 to 90 years) or a long-term time scale (longer than 90 years) in the literature. In this study, the uncertainty of the trend in ZSSTG for different sub-periods since 1881 was examined using four interpolated datasets and four un-interpolated datasets. It was found that the trend in ZSSTG on the short-term time scale could be significantly influenced by internal variability such as the El Niño–Southern Oscillation and the Pacific Decadal Oscillation. On the long-term time scale, the sign of the ZSSTG trend depends on the dataset used. In particular, it was not possible to draw a uniform conclusion about the secular trends in ZSSTG in recent history, given the high sensitivity of the ZSSTG trends to the period, dataset, and regions used to calculate the trends. Our results imply that it may not be possible to detect the response of ZSSTG to global warming until a longer data record becomes available in the future. 相似文献
