Abstract: As one of the primary inputs that drive watershed dynamics, the estimation of spatial variability of precipitation has been shown to be crucial for accurate distributed hydrologic modeling. In this study, a Geographic Information System program, which incorporates Nearest Neighborhood (NN), Inverse Distance Weighted (IDW), Simple Kriging (SK), Ordinary Kriging (OK), Simple Kriging with Local Means (SKlm), and Kriging with External Drift (KED), was developed to facilitate automatic spatial precipitation estimation. Elevation and spatial coordinate information were used as auxiliary variables in SKlm and KED methods. The above spatial interpolation methods were applied in the Luohe watershed with an area of 5,239 km2, which is located downstream of the Yellow River basin, for estimating 10 years’ (1991‐2000) daily spatial precipitation using 41 rain gauges. The results obtained in this study show that the spatial precipitation maps estimated by different interpolation methods have similar areal mean precipitation depth, but significantly different values of maximum precipitation, minimum precipitation, and coefficient of variation. The accuracy of the spatial precipitation estimated by different interpolation methods was evaluated using a correlation coefficient, Nash‐Sutcliffe efficiency, and relative mean absolute error. Compared with NN and IDW methods that are widely used in distributed hydrologic modeling systems, the geostatistical methods incorporated in this GIS program can provide more accurate spatial precipitation estimation. Overall, the SKlm_EL_X and KED_EL_X, which incorporate both elevation and spatial coordinate as auxiliary into SKlm and KED, respectively, obtained higher correlation coefficient and Nash‐Sutcliffe efficiency, and lower relative mean absolute error than other methods tested. The GIS program developed in this study can serve as an effective and efficient tool to implement advanced geostatistics methods that incorporate auxiliary information to improve spatial precipitation estimation for hydrologic models. 相似文献
We assessed the contamination levels of Mn, Zn, Cr, Cu, Ni, Pb, As and Hg and the risks posed by these potentially harmful elements in top-soils around a municipal solid waste incinerator (MSWI).We collected 20 soil samples, with an average pH of 8.1, and another fly ash sample emitted from the MSWI to investigate the concentrations of these elements in soils. We determined the concentrations of these elements by inductively coupled plasma–optical emission spectrometer (ICP-OES), except for Hg, which we measured by AF-610B atomic fluorescence spectrometer (AFS). We assessed the risks of these elements through the use of geoaccumulation index (Igeo), potential ecological risk index (RI), hazard quotient (HQi) and cancer risk (Riski). The results showed that concentrations of potentially harmful elements in soil were influenced by the wind direction, and the concentrations of most elements were higher in the area northwest of the MSWI, compared with the area southeast of the incinerator, with the exception of As; these results were in accordance with those results acquired from our contour maps. According to the Igeo values, some soil samples were clearly polluted by Hg emissions. However, the health risk assessment indicated that the concentrations of Hg and other elements in soil did not pose non-carcinogenic risks to the local populations. This was also the case for the carcinogenic risks posed by As, Cr, and Ni. The carcinogenic risk posed by As was higher, in the range 6.49 × 10–6–9.58 × 10–6, but this was still considered to be an acceptable level of risk.
