Automated calibration applied to watershed‐scale flow simulations

Complexity in simulating the hydrological response in large watersheds over long times has prompted a significant need for procedures for automatic calibration. Such a procedure is implemented in the basin‐scale hydrological model (BSHM), a physically based distributed parameter watershed model. BSHM simulates the most important basin‐scale hydrological processes, such as overland flow, groundwater flow and stream–aquifer interaction in watersheds. Here, the emphasis is on estimating the groundwater parameters with water levels in wells and groundwater baseflows selected as the calibration targets. The best set of parameters is selected from within plausible ranges of parameters by adjusting the values of hydraulic conductivity, storativity, groundwater recharge and stream bed permeability. The baseflow is determined from stream flow hydrographs by using an empirical scheme validated using a chemical approach to hydrograph separation. Field studies determined that the specific conductance for components of the composite hydrograph were sufficiently unique to make the chemical approach feasible. The method was applied to the Big Darby Creek Watershed, Ohio. The parameter set selected for the groundwater system provides a good fit with the estimated baseflow and observed water well data. Copyright © 1999 John Wiley & Sons, Ltd.     

Effects of Interpolation Errors on the Analysis of DEMs

A suite of methods to interpolate a digital elevation model from a ground survey was evaluated with respect to precision and ability to maintain the shape of the original height data. This shape reliability was evaluated by comparing the spatial patterns of secondary terrain parameters derived from the interpolated elevation data. The best interpolation method for this study area was found to be a spline interpolation, which is somewhat contradictory to findings in the literature. The error and uncertainty found in the results for terrain analysis and modelling tools is important and sometimes distressingly high, even for some frequently used local or context operations on altitude. Positional operations, in which the output is determined more by the position in the topographic structure, seem to give more reliable results. Therefore, the results obtained by terrain analysis and spatial modelling need careful interpretation. © 1997 John Wiley & Sons, Ltd.     

THE SENSITIVITY OF TWO DISTRIBUTED NON-POINT SOURCE POLLUTION MODELS TO THE SPATIAL ARRANGEMENT OF THE LANDSCAPE

Distributed hydrological models are becoming increasingly complex with respect to spatial phenomena, and with the widespread availability of spatial data from GIS, this trend is likely to increase. In all such models the spatial arrangement of phenomena, such as soil properties and land-use categories is fundamental, and so the arrangement should have an influence on the model output. Testing for this influence we term spatial sensitivity analysis. Here, we report on the spatial sensitivity of two widely used models, AgNPS (agricultural non-point source pollution model) and ANSWERS (areal nonpoint source watershed environment response simulation). The input spatial data were subjected to spatially random mixing to varying degrees, such that the organized landscape became disorganized. The chemical discharge from AgNPS, and the sediment and water discharge from ANSWERS, are examined. In both cases most outputs exhibited little or no sensitivity to the spatial distribution of most input data. Only infiltration-related inputs produced large variations, but these changes were not in the sense that might have been predicted. Although the analytical methods used require further refinement, there must now be some doubt as to the validity of the models, and whether they repay their computational complexity. Furthermore, it is felt that spatial sensitivity analysis should become a fundamental part of the verification of all such models. © 1997 by John Wiley & Sons, Ltd.     

ASSESSMENT OF CLIMATE CHANGE AND FRESHWATER ECOSYSTEMS OF THE ROCKY MOUNTAINS,USA AND CANADA

The Rocky Mountains in the USA and Canada encompass the interior cordillera of western North America, from the southern Yukon to northern New Mexico. Annual weather patterns are cold in winter and mild in summer. Precipitation has high seasonal and interannual variation and may differ by an order of magnitude between geographically close locales, depending on slope, aspect and local climatic and orographic conditions. The region's hydrology is characterized by the accumulation of winter snow, spring snowmelt and autumnal baseflows. During the 2–3-month ‘spring runoff’ period, rivers frequently discharge > 70% of their annual water budget and have instantaneous discharges 10–100 times mean low flow. Complex weather patterns characterized by high spatial and temporal variability make predictions of future conditions tenuous. However, general patterns are identifiable; northern and western portions of the region are dominated by maritime weather patterns from the North Pacific, central areas and eastern slopes are dominated by continental air masses and southern portions receive seasonally variable atmospheric circulation from the Pacific and the Gulf of Mexico. Significant interannual variations occur in these general patterns, possibly related to ENSO (El Niño–Southern Oscillation) forcing. Changes in precipitation and temperature regimes or patterns have significant potential effects on the distribution and abundance of plants and animals. For example, elevation of the timber-line is principally a function of temperature. Palaeolimnological investigations have shown significant shifts in phyto- and zoo-plankton populations as alpine lakes shift between being above or below the timber-line. Likewise, streamside vegetation has a significant effect on stream ecosystem structure and function. Changes in stream temperature regimes result in significant changes in community composition as a consequence of bioenergetic factors. Stenothermic species could be extirpated as appropriate thermal criteria disappear. Warming temperatures may geographically isolate cold water stream fishes in increasingly confined headwaters. The heat budgets of large lakes may be affected resulting in a change of state between dimictic and warm monomictic character. Uncertainties associated with prediction are increased by the planting of fish in historically fishless, high mountain lakes and the introduction of non-native species of fishes and invertebrates into often previously simple food-webs of large valley bottom lakes and streams. Many of the streams and rivers suffer from the anthropogenic effects of abstraction and regulation. Likewise, many of the large lakes receive nutrient loads from a growing human population. We concluded that: (1) regional climate models are required to resolve adequately the complexities of the high gradient landscapes; (2) extensive wilderness preserves and national park lands, so prevalent in the Rocky Mountain Region, provide sensitive areas for differentiation of anthropogenic effects from climate effects; and (3) future research should encompass both short-term intensive studies and long-term monitoring studies developed within comprehensive experimental arrays of streams and lakes specifically designed to address the issue of anthropogenic versus climatic effects. © 1997 John Wiley & Sons, Ltd.     

MODELLING RUNOFF GENERATION ON SMALL AGRICULTURAL CATCHMENTS: CAN REAL WORLD RUNOFF RESPONSES BE CAPTURED?

This paper focuses on the problem of quantifying real world catchment response using a distributed model and discusses the ability of the model to capture that response. The rainfall–runoff responses of seven small agricultural catchments in the eastern wheatbelt region of south-western Australia are examined. The variability in runoff generation and the factors that contribute to that variability (i.e. rainfall intensity, soil properties and topography) are investigated to determine if their influence can be captured in a mathematical model. The spatially distributed rainfall–runoff model used in this study is based on the TOPMODEL concepts of Beven and Kirkby (1979), and simulates runoff generation by both the infiltration excess and saturation excess mechanisms. Simulations with the model revealed the highly complex nature of catchment response to rainfall events. Runoff generation was highly heterogeneous in both space and time, with the runoff response being governed by the spatial variability of soil properties and topography, and by the temporal variation in rainfall intensity. Although the model proved capable of simulating catchment response for many events, the investigation has demonstrated that not all aspects of the variability associated with agricultural catchments (particularly the effects of land management) can be captured using this relatively simple model. © 1997 by John Wiley & Sons, Ltd     

Hydrological runoff modelling by the use of remote sensing data with reference to the 1993–1994 and 1995 floods in the river Rhine catchment

In hydrological modelling of runoff processes, including water balance, various input data and parameters can be acquired or estimated by the use of remote sensing (RS) techniques.The acquisition and use of synoptic RS areal information rather than traditional point information is an important issue in hydrology. Hydrological models allow runoff/water balance in catchments to be calculated and flow routing within flow channels to be done. For runoff and water balance computations land use, soil moisture, detection of snow and ice, digital terrain models (DTM), as well as hydrometeorological information and discharge are important. For flow routing, water level information, geometric–topographic information such as cross-sections for normal and flood conditions, coefficient of roughness and velocity of flow and its cross-sectional distribution are required. In addition, water level information (lower and upper level) is needed for shipping and for design purposes. In the German part of the River Rhine catchment, several focus areas in the December 1993–January 1994 and January 1995 floods were covered with RS data [ERS-1 and airborne SAR, both C-band VV, passive microwave (18·7, 36·5, 89 GHz), TIR, UV, aerial photographs (b/w PAN, b/w NIR)], giving a good opportunity for a comparison of methods. Evaluation is still continuing. The importance of soil saturation for flood generation and, therefore, for flood monitoring, was shown on this occasion. The use of ERS SAR data for soil moisture estimation is currently being investigated by the Federal Institute of Hydrology. Also, the need for emergency schemes for data acquisition and easy, quick and affordable RS data dissemination was demonstrated. The assimilation of RS data with GIS information such as DTMs, including relevant topographic features like dams, which is omitted in currently available raster digital elevation models, is promising. RS altimetry techniques can be a step towards high resolution DTMs for hydrological purposes. Ground truth reference data are still needed. © 1997 John Wiley & Sons, Ltd.     

中国区域工业全要素生产率的空间计量经济分析

全要素生产率(TFP)是一个国家或地区经济增长质量和技术进步、管理效率提高的重要标志,正确、科学测算TFP对区域经济增长和技术进步及政策研究非常重要。运用空间统计和空间计量经济学的空间自相关Moran指数、空间滞后模型和空间误差模型方法,基于2003年中国大陆31个省、直辖市和自治区的工业企业统计数据,对中国大陆省级区域工业全要素生产率进行了空间计量经济测算分析。结果发现,空间统计与空间计量经济学模型在测算我国省域工业全要素生产率中具有较好效果,利用这种方法测算的2003年中国大陆31个区域全要素生产率的实证结果比较符合工业生产率发展实际;在影响我国省域工业生产率的因素中,工业资本投入是造成工业经济增长率在东中西部地区之间和各个省域之间存在巨大差异的主要原因;劳动生产率水平偏低是制约我国省域工业生产率提高的主要瓶颈因素;2003年我国省域工业生产率增长是由资本和技术共同推动的。     

LISEM: A SINGLE-EVENT,PHYSICALLY BASED HYDROLOGICAL AND SOIL EROSION MODEL FOR DRAINAGE BASINS. II: SENSITIVITY ANALYSIS,VALIDATION AND APPLICATION

A new hydrological and soil erosion model has been developed and tested: LISEM, the Limburg soil erosion model. The model uses physically based equations to describe interception, infiltration and soil water transport, storage in surface depressions, splash and flow detachment, transport capacity and overland and channel flow. From the validation results it is clear that, although the model has several advantages over other models, the results of LISEM 1.0 are far from perfect. Based on the sensitivity analysis and field observations, the main reasons for these differences seems to be the spatial and temporal variability of the soil hydraulic conductivity and the initial pressure head at the basin scale. Another reason for the differences between measured and simulated results is our lack or understanding of the theory of hydrological and soil erosion processes.     

Review of methods for the detection and estimation of trends with emphasis on water quality applications

Methods for the detection and estimation of trends which are suitable for the type of data sets available from water quality and atmospheric deposition monitoring programmes are considered. Parametric and non-parametric methods which are based on the assumption of monotonic trend and which account for seasonality through blocking on season are described. The topics included are heterogeneity of trend, missing data, covariates, censored data, serial dependence and multivariate extensions. The basis for the non-parametric methods being the method of choice for current large data sets of short to moderate length is reviewed. A more general definition of trend as the component of gradual change over time is consistent with another group of methods and some examples are given. Spatial temporal data sets and longer temporal records are also briefly considered. A broad overview of the topic of trend analysis is given, with technicalities left to the references cited. The necessity of defining what is meant by trend in the context of the design and objectives of the programme is emphasized, as is the need to model the variability in the data more generally.