COMPARISON OF PROCESS‐BASED AND ARTIFICIAL NEURAL NETWORK APPROACHES FOR STREAMFLOW MODELING IN AN AGRICULTURAL WATERSHED1

ABSTRACT: The performance of the Soil and Water Assessment Tool (SWAT) and artificial neural network (ANN) models in simulating hydrologic response was assessed in an agricultural watershed in southeastern Pennsylvania. All of the performance evaluation measures including Nash‐Sutcliffe coefficient of efficiency (E) and coefficient of determination (R²) suggest that the ANN monthly predictions were closer to the observed flows than the monthly predictions from the SWAT model. More specifically, monthly streamflow E and R² were 0.54 and 0.57, respectively, for the SWAT model calibration period, and 0.71 and 0.75, respectively, for the ANN model training period. For the validation period, these values were ?0.17 and 0.34 for the SWAT and 0.43 and 0.45 for the ANN model. SWAT model performance was affected by snowmelt events during winter months and by the model's inability to adequately simulate base flows. Even though this and other studies using ANN models suggest that these models provide a viable alternative approach for hydrologic and water quality modeling, ANN models in their current form are not spatially distributed watershed modeling systems. However, considering the promising performance of the simple ANN model, this study suggests that the ANN approach warrants further development to explicitly address the spatial distribution of hydrologic/water quality processes within watersheds.     

EFFECTS OF STATSGO AND SSURGO AS INPUTS ON SWAT MODEL'S SNOWMELT SIMULATION1

ABSTRACT: Soil data comprise a basic input of SWAT (Soil and Water Assessment Tool) for a watershed application. For watersheds where site specific soil data are unavailable, the two U.S. Department of Agriculture (USDA) soil databases, the State Soil Geographic (STATSGO) and Soil Survey Geographic (SSURGO) databases, may be the best alternatives. Although it has been noted that SWAT models using the STATSGO and SSURGO data may give different simulation results for water, sediment, and agricultural chemical yields, information is scarce on the effects of using these two databases in predicting streamflows that are predominantly generated from melting snow in spring. The objective of this study was to assess the effects of using STATSGO versus SSURGO as an input for the SWAT model's simulation of the streamflows in the upper 45 percent of the Elm River watershed in eastern North Dakota. Designating the model as SWAT‐STATSGO when the STATSGO data were used and SWAT‐SSURGO when the SSURGO data were used, SWAT‐STATSGO and SWAT‐SSURGO were separately calibrated and validated using the observed daily streamflows. The results indicated that SWAT‐SSURGO provided an overall better prediction of the discharges than SWAT‐STATSGO, although both did a good and comparable job of predicting the high streamflows. However, SWAT‐STATSGO predicted the low streamflows more accurately and had a slightly better performance during the validation period. In addition, the discrepancies between the discharges predicted by these two SWAT models tended to be larger at upstream locations than at those farther downstream within the study area.     

Estimation of Cumulative Frequency Distribution for Carbon Monoxide Concentration from Wind-Speed Data, in Buenos Aires (Argentina)

In this article we apply and test a methodology to estimate cumulative frequency distribution for air pollutant concentration from wind-speed data. We use the inverse relationship after Simpson et al. (Atmospheric Environment, 19, 75–82, 1985) between the opposing percentile values in the statistical distributions for air pollutant concentrations and wind-speed data. This relationship is valid, irrespective of the statistical distributions of both variables, if an inverse relationship between them is also applicable. The available data are five years of 8-h average carbon monoxide concentration and 8-h mean wind-speed, observed in Buenos Aires (Argentina). The performance of the obtained empirical expressions in estimating cumulative frequency distributions for 8-h CO is statistically evaluated. The results show that it is possible to obtain an acceptable cumulative frequency distribution for 8-h CO concentration at the site if the cumulative frequency distribution for wind-speed is known. Q–Q plots show a good agreement between estimated and observed values. From our data, the mean relative error of the estimations was found to be as much as 8.0%.     

Potential and Shortcomings of Numerical Weather Prediction Models in Providing Meteorological Data for Urban Air Pollution Forecasting

The last decade progress in numericalweather prediction (NWP) modelling and studies of urbanatmospheric processes for providing meteorological data forurban air pollution forecasting is analysed on examples ofseveral European meteorological centres. Modern nested NWP models are utilising land-use databasesdown to 1 km resolution or finer, and are approaching thenecessary horizontal and vertical resolution suitable forcity scale. The recent scientific developments in the fieldof urban atmospheric physics and the growing availabilityof high-resolution urban surface characteristics datapromise further improvements of the capability of NWPmodels for this aim. A strategy to improve NWP data forthe urban air pollution forecasting is suggested.     

Protozooplankton in the Deep Oligotrophic Traunsee (Austria) Influenced by Discharges of Soda and Salt Industries

Traunsee is a deep oligotrophic lake in Austria characterised by an artificial enrichment of chloride in the hypolimnion (up to 170 mg L^-1) caused by waste disposal of soda and salt industries. Protists were collected monthly over one year, observed alive and after Quantitative Protargol Staining (ciliates) or via epifluorescence microscopy (heterotrophic flagellates). Three sites within the lake (0–40 m depths) were compared to deeper water layers from 60–160 m depths where chloride concentrations and conductivity were increased. In addition, we observed the protozooplankton of two neighbouring lakes, i.e. reference systems, during one sampling occasion. In Traunsee the abundance of ciliates was low (200–36 600 cells L^-1) in contrast to high species diversity (at least 60 different species; H_S = 2.6) throughout the year. The main pelagic species in terms of abundance were small oligotrichs and prostomatids like Rimostrombidium brachykinetum/hyalinum, Balanion planctonicum and Urotricha spp. throughout the investigation period. Among free-living heterotrophic flagellates, which occurred at densities of 40–2800 cells mL^-1, small morphotypes dominated in the pelagial. No differences at the community level between the three lakes could be observed and pelagic ciliates and flagellates seemed not to be affected by increased chloride concentrations or by enhanced conductivity.     

绵阳市大气降水pH值时空分布及酸雨成因研究

通过对绵阳市9个测点1998－1999年大气降水监测数据的统计分析，并结合历史数据，对大气降水pH值的时空分布及酸雨成因进行了研究。结果表明：绵阳市大气降水酸化严重，除主要受本地区大气污染影响外，还受大气中、长距离输送的影响。     

Modeling the relationships between land use and land cover on private lands in the Upper Midwest, USA

This paper presents an approach to modeling land-cover change as a function of land-use change. We argue that, in order to model the link between socio-economic change and changes in forest cover in a region that is experiencing residential and recreational development and agricultural abandonment, land-use and land-cover change need to be represented as separate processes. Forest-cover change is represented here using two transition probabilities that were calculated from Landsat imagery and that, taken together, describe a Markov transition matrix between forest and non-forest over a 10-year period. Using a three-date land-use data set, compiled and interpreted from digitized parcel boundaries, and scanned aerial photography for 136 sites (c. 2500 ha) sampled from the Upper Midwest, USA, we test functional relationships between forest-cover transition probabilities, standardized to represent changes over a decade, and land-use conditions and changes within sample sites. Regression models indicated that about 60% of the variation in the average forest-cover transition probabilities (i.e. from forest to non-forest and vice versa) can be predicted using three variables: amount of agricultural land use in a site; amount of developed land use; and the amount of area increasing in development. In further analysis, time lags were evaluated, showing that agricultural abandonment had a relatively strong time-lag effect but development did not. We demonstrate an approach to using forest-cover transition probabilities to develop spatially-constrained simulations of forest-cover change. Because the simulations are based on transition probabilities that are indexed to a particular time and place, the simulations are improved over previous applications of Markov transition models. This modeling approach can be used to predict forest-cover changes as a result of socio-economic change, by linking to models that predict land-use change on the basis of exogenous human-induced drivers.     

陕西大暴雨时空分布特征及减灾对策

通过对陕西１９５７～１９９８年共４２年９７个测站的逐日降水量中大暴雨资料进行时间和空间尺度分析，总结归纳出陕西灾害性大暴雨的天气气候基本特征和规律性，并提出相应的减灾对策。     

COUPLING OF NONPARAMETRIC FREQUENCY AND L-MOMENT ANALYSES FOR MIXED DISTRIBUTION IDENTIFICATION 1

ABSTRACT: Both L-moment and nonparametric frequency analyses were performed on a series of annual maximum floods from New Brunswick, Canada. The L-moment analysis concluded that the data were generated from a unimodal Generalized Extreme Value (GEV) distribution. However, the nonparametric frequency analysis indicated that a majority of stations followed nonunimodal mixed distributions since peak flows occur during different seasons and are the result of different generating mechanisms. The coupling of L-moment and nonparametric analyses facilitates mixed distribution identification. Thus, the nonparametric method helps in identifying underlying probability distribution, especially when samples arise from mixed distributions.     

内蒙古赤峰地区草麻黄资源的分布及利用

本文论述了内蒙古赤峰地区草麻黄的分布和生态特性。草麻黄从东南至西北受气温和降水等因素的影响,在东南部丘陵沙地干草原区集中分布;在中部低山丘陵干草原区呈零星分布,在西北部山地草甸草原区无分布。草麻黄对干旱的环境条件适应能力强,具有耐干旱、耐沙湿、耐高温、耐寒、耐贫瘠和不耐水湿等生态特性。本文对如何保护与合理利用草麻黄资源,提出了建议。