MODELING TRANSIENT pH DEPRESSIONS IN COASTAL STREAMS OF BRITISH COLUMBIA USING NEURAL NETWORKS1

ABSTRACT: Transient events in water chemistry in small coastal watersheds, particularly pH depressions, are largely driven by inputs of precipitation. While the response of each watershed depends upon both the nature of the precipitation event and the season of the year, how the response changes over time can provide insight into landscape changes. Neural network models for an urban watershed and a rural‐suburban watershed were developed in an attempt to detect changes in system response resulting from changes in the landscape. Separate models for describing pH depressions for wet season and dry season conditions were developed for a seven year period at each watershed. The neural network models allowed separation of the effects of precipitation variations and changes in watershed response. The ability to detect trends in pH depression magnitudes was improved by analyzing neural network residuals rather than the raw data. Examination of sensitivity plots of the models indicated how the neural networks were affected by different inputs. There were large differences in effects between seasons in the rural‐suburban watershed whereas effects in the urban watershed were consistent between seasons. During the study period, the urban watershed showed no change in pH depression response, while the rural‐suburban watershed showed a significant increase in the magnitude of pH depressions, likely the result of increased urbanization.     

APPLICATION OF GREY MODEL TOWARD RUNOFF FORECASTING1

ABSTRACT: A reliable forecasting model is essential in real‐time flood forecasting for reducing natural damage. Efforts to develop a real‐time forecasting model over the past two decades have been numerous. This work applies the Grey model to forecast rainfall and runoff owing to the model's relative ability to predict the future using a small amount of historical data. Such a model significantly differs from the stochastic and deterministic models developed previously. Ten historical storm events from two catchment areas in northern Taiwan are selected to calibrate and verify the model. Results in this study demonstrate that the proposed models can reasonably forecast runoff one to four hours ahead, if the Grey error prediction method is further used to update the output of the model.     

降雨随历时变化标度性质的探讨

降雨公式是水文计算的基本依据之一，也是工程师和水文学家十分关心的问题。长期以来水文中采用的降雨公式是基于大量降雨资料而建立起来的经验公式，多年的实践表明该公式能客观地反映降雨特性，计算结果符合实际，但是对该公式的理论基础却不太清楚。着眼于降雨在时间上的自相似性，将标度理论应用于降雨时间尺度问题，对降雨强度随历时变化的标度性质进行了研究，探讨了降雨公式的理论基础。由标度理论阐述了降雨标度性质（标度不变性）在时间尺度上的意义，并用此理论研究了成都望江楼站的降雨资料，计算了该站不同历时下降雨强度的各阶矩和变差系数，研究的结果表明，在一定的时间尺度范围内，降雨强度随历时变化确实具有多标度性质。最后由降雨强度随历时变化的标度性质推导出降雨公式，说明了降雨公式是降雨在时间尺度上标度特性的表示。     

MODIFIED SMEMAX TRANSFORMATION FOR FREQUENCY ANALYSIS1

ABSTRACT: SMEMAX is a transformation technique suggested by Bethalmy to transform random hydrological series to a near normal series. This paper puts forward an alternative simpler form of the SMEMAX transformation. The modified SMEMAX transformation avoids use of trigonometric functions and the transformed variables range from 0 to 100.     

APPLICABILITY OF THE GREEN AND AMPT INFILTRATION EQUATION TO RANGELANDS1

ABSTRACT: The objective of this study was to investigate the use of Green and Ampt infiltration equation parameters (determined by least squares fitting of field infiltration data or predicted from soil texture properties) to characterize infiltration on spatially varying rangeland sites. It was found that a least squares regression approach reduces the physically based parameters in the Green and Ampt to empirical coefficients since negative coefficients are obtained, particularly on plots with low infiltration rates. Green and Ampt parameters predicted from soil texture data describe infiltration rates less than 3 cm/hr. The applicability of these Green and Ampt parameters appears limited to sites with lower infiltration rates. Results indicate that soil texture predictive triangles, developed to describe infiltration on agricultural soils, need revision to adequately describe infiltration patterns on rangelands.     

FOREST HYDROLOGY AND EXTREME RAINFALL FREQUENCY1

Extreme rainfall frequency analysis provides one means to predict, within certain limits of probability, the average time interval between the recurrences of storms of a specified duration and magnitude. This in turn furnishes the forest hydrologist a valuable tool for engineering design and runoff and erosion forecast. A modification in the application of the annual maximum and annual exceedance series analysis described by V. T. Chow can, for special purposes, lead to an even more useful estimate of extreme events on a seasonal basis. This can be particularly important on small forested headwater watersheds where the runoff response to extreme rainfall may vary considerably with seasonal changes in canopy cover and soil moisture characteristics. Although the application of data covering a relatively short period of record has produced some inconsistencies among the frequency diagrams, under certain circumstances for short-term recurrence interval forecast and for non-critical application the analysis of extreme rainfall frequency from less than 20 years data seems justified.     

AN EVALUATION OF FLOOD FREQUENCY ESTIMATES BASED ON RAINFALL/RUNOFF MODELING1

ABSTRACT: An evaluation of flood frequency estimates simulated from a rainfall/runoff model is based on (1) computation of the equivalent years of record for regional estimating equations based on 50 small stream sites in Oklahoma and (2) computation of the bias for synthetic flood estimates as compared to observed estimates at 97 small stream sites with at least 20 years of record in eight eastern states. Because of the high intercorrelation of synthetic flood estimates between watersheds, little or no regional (spatial) information may be added to the network as a result of the modeling activity. The equivalent years of record for the regional estimating equations based totally on synthetic flood discharges is shown to be considerably less than the length of rainfall record used to simulate the runoff. Furthermore, the flood estimates from the rainfall/runoff model consistently underestimate the flood discharges based on observed record, particularly for the larger floods. Depending on the way bias is computed, the synthetic estimate of the 100-year flood discharge varies from 11 to 29 percent less than the value based on observed record. In addition, the correlation between observed and synthetic flood frequency estimates at the same site is also investigated. The degree of correlation between these estimates appears to vary with recurrence interval. Unless the correlation between these two estimates is known, it is not possible to compute a weighted estimate with minimum variance.     

北京市清河水体非点源污染特征

为揭示城市水体非点源污染特征,以北京市清河流域为研究对象,于2013年8月—2014年12月对流域不同河段河水、雨水、降雨前后河水、降雨径流以及不同下垫面（居民区、商业区、绿地、街道、农田）的土壤或降尘中主要污染物进行了采样分析.结果表明:清河水体污染严重,大部分污染物浓度均超过GB 3838—2002《地表水环境质量标准》的V类标准,营养盐浓度甚至超过GB 18918—2002《城镇污水处理厂污染物排放标准》一级A排放标准.河水主要污染物浓度远高于雨水污染物浓度,长期来看,受雨水影响较小.丰水期河水ρ（TDP）（TDP为溶解性总磷）显著高于枯水期和平水期,而丰水期ρ（TDN）（TDN为溶解性总氮）却低于枯水期和平水期（P < 0.05）,ρ（COD_Mn）和ρ（NH₄+-N）在3个水期没有显著差异.与降雨前相比,降雨后河水ρ（TDN）显著降低,ρ（TDP）却显著升高（P < 0.05）,ρ（COD_Mn）、ρ（NH₄+-N）在降雨前后没有显著差异.研究显示,清河流域的降雨径流增加了河水外源磷输入,磷的初期冲刷效应最为显著,且水体磷的非点源特征明显,而氮主要来源于生活污水排放,受非点源影响较小,清河水体COD_Mn、NH₄+-N则同时受点源和非点源的影响.      

洱海西部雨季地表径流氮磷污染特征及受土地利用类型的影响

云南高原平坝区地表径流是湖泊氮、磷的主要来源之一.为研究高原平坝区雨季地表径流氮、磷污染特征及受土地利用类型的影响,调查了洱海西部平坝区雨季的径流氮、磷形态特征,并结合遥感影像空间分析与SPSS等统计分析,从汇水区尺度和缓冲区尺度上研究土地利用类型与地表径流水质的关系.结果表明:①研究区雨季地表径流氮、磷质量浓度较高,ρ（TP）为0.16~0.77 mg/L,且以DIP（溶解性无机磷）为主（63.01%）;ρ（TN）为1.75~14.86 mg/L,且以NO₃--N为主（78.15%）.②汇水区尺度上城镇用地对ρ（TP）影响突出.环湖农村居民点对ρ（NH₄+-N）影响突出,耕地中的高施肥种植区对ρ（TN）、ρ（NO₃--N）影响突出;③在缓冲区500、1 000和2 000 m尺度下,随缓冲区距离增加,土地利用类型对地表径流水质的影响减小.研究显示,城镇用地与高施肥种植区对洱海西部雨季地表径流氮、磷质量浓度影响最大,土地利用类型随缓冲区距离增加对水质的影响逐渐减小.