An integrated groundwater/surface water hydrological model with a 1 km2 grid has been constructed for Denmark covering 43,000 km2. The model is composed of a relatively simple root zone component for estimating the net precipitation, a comprehensive three-dimensional groundwater component for estimating recharge to and hydraulic heads in different geological layers, and a river component for streamflow routing and calculating stream–aquifer interaction. The model was constructed on the basis of the MIKE SHE code and by utilising comprehensive national databases on geology, soil, topography, river systems, climate and hydrology. The present paper describes the modelling process for the 7330 km2 island of Sjælland with emphasis on the problems experienced in combining the classical paradigms of groundwater modelling, such as inverse modelling of steady-state conditions, and catchment modelling, focussing on dynamic conditions and discharge simulation. Three model versions with different assumptions on input data and parameter values were required until the performance of the final, according to pre-defined accuracy criteria, model was evaluated as being satisfactory. The paper highlights the methodological issues related to establishment of performance criteria, parameterisation and assessment of parameter values from field data, calibration and validation test schemes. Most of the parameter values were assessed directly from field data, while about 10 ‘free’ parameters were subject to calibration using a combination of inverse steady-state groundwater modelling and manual trial-and-error dynamic groundwater/surface water modelling. Emphasising the importance of tests against independent data, the validation schemes included combinations of split-sample tests (another period) and proxy-basin tests (another area). 相似文献
As surface exchange processes are highly non-linear and heterogeneous in space and time, it is important to know the appropriate scale for the reasonable prediction of these exchange processes. For example, the explicit representation of surface variability has been vital in predicting mesoscale weather events such as late-afternoon thunderstorms initiated by latent heat exchanges in mid-latitude regions of the continental United States. This study was undertaken to examine the effects of different spatial scales of input data on modeled fluxes, so as to better understand the resolution needed for accurate modeling. A statistical procedure was followed to select two cells from the Southern Great Plains 1997 hydrology experiment region, each 20 km×20 km, representing the most homogeneous and the most heterogeneous surface conditions (based on soil and vegetation) within the study region. The NOAH-OSU (Oregon State University) Land Surface Model (LSM) was employed to estimate surface energy fluxes. Three scales of study (200 m, 2 and 20 km) were considered in order to investigate the impacts of the aggregation of input data, especially soil and vegetation inputs, on the model output. Model results of net radiation and latent, sensible and ground heat fluxes were compared for the three scales. For the heterogeneous area, the model output at the 20-km resolution showed some differences when compared with the 200-m and 2-km resolutions. This was more pronounced in latent heat (12% decrease), sensible heat (22% increase), and ground heat flux (44% increase) estimation than in net radiation. The scaling effects were much less for the relatively homogeneous land area with 5% increase in sensible heat and 4% decrease in ground heat flux estimation. All of the model outputs for the 2- and 20-km resolutions were in close agreement. The results suggested that, for this study region, soils and vegetation input resolution of about 2 km should be chosen for realistic modeling of surface exchange processes. This resolution was sufficient to capture the effects of sub-grid scale heterogeneity, while avoiding the data and computational difficulties associated with higher spatial resolutions. 相似文献
Individual based simulations of population dynamics require the availability of growth models with adequate complexity. For this purpose a simple-to-use model (non-linear multiple regression approach) is presented describing somatic growth and reproduction of Daphnia as a function of time, temperature and food quantity. The model showed a good agreement with published observations of somatic growth (r2 = 0.954, n = 88) and egg production (r2 = 0.898, n = 35). Temperature is the main determinant of initial somatic growth and food concentration is the main determinant of maximal body length and clutch size. An individual based simulation was used to demonstrate the simultaneous effects of food and temperature on the population level. Evidently, both temperature and food supply affected the population growth rate but at food concentrations above approximately 0.4 mg Cl−1Scenedesmus acutus temperature appeared as the main determinant of population growth.
Four simulation examples are given to show the wide applicability of the model: (1) analysis of the correlation between population birth rate and somatic growth rate, (2) contribution of egg development time and delayed somatic growth to temperature-effects on population growth, (3) comparison of population birth rate in simulations with constant vs. decreasing size at maturity with declining food concentrations and (4) costs of diel vertical migration. Due to its plausible behaviour over a broad range of temperature (2–20 °C) and food conditions (0.1–4 mg Cl−1) the model can be used as a module for more detailed simulations of Daphnia population dynamics under realistic environmental conditions. 相似文献
In seismic analysis some assumptions are often made aboutthe data, e.g. stationarity and Gaussianity. This is not obvious for all realseismic data. Here, we use statistical tests for characterization of regionalseismic data. We apply tests for stationarity, symmetry, linearity, andtime-reversibility. In the analysis we use twelve regional seismic events inFennoscandia recorded with the seismic small-aperture arrays NORESS,ARCESS and FINESA at hypocentral distances in the range from 160 to1580 km. For the tests we use the regional phases Pn, secondary P, Sn and Lg-phases and the preceding noise. Two of the eventsare explosions, two are rockbursts and eight are earthquakes. Theperformance and possibilities of using statistical tests based on bispectra, asa complementary tool for conventional analysis of seismic phases isdemonstrated. The preceding noise recorded before the first onset of theP-wave for the twelve events is tested to be spatially stationarybetween each channel within each array and temporal stationary in 21consecutive time windows of 3.2 sec each. Also, the preceding noise issymmetric and linear. The seismic phases defined by the symmetry test asnon-Gaussian (not symmetric) are all linear. This means a linear model canbe used to characterize both the noise and the phases. The first P-phase for the two explosions is characterized as non-Gaussian at thethree arrays. For all 36 possibly first P-phase arrivals at the three arraystations, 23 are non-Gaussian. The second P-phase is non-Gaussian at13 of 36 data records, the S-phase at eleven of 36 and the Lg-phase at nine of 36. For all the four phases more than 32 of possible36 are time-reversible. 相似文献