青藏高原东南部径流特征的空间规律及控制因子研究

采用青藏高原东南部的水文气象资料,对比分析了该地区23个(区间)流域的年径流深、集中度与集中期、基流系数、退水系数等径流特征及其空间分布规律,并进一步研究了这些径流特征的控制因子。结果表明:该地区径流特征的空间分布规律为年径流深从东南(700~1 300 mm)向西北(<400 mm)递减,而集中度则呈相反的空间格局(从<0.44增加到>0.59);退水系数及基流系数,在低海拔地区随高程增大而增大(分别为0.55~0.69、0.51~0.73),但在高海拔地区则随高程增大而减小(0.74~0.42、0.79~0.63)。本研究发现,青藏东南径流特征空间规律的控制因子,具有显著的区域分异:在低海拔流域(平均高程<3 000 m),降水是径流特征的主要影响因子;而在高海拔流域(平均高程>3 000 m),仅径流深和集中度受降水控制,其他特征则主要受温度、冻土、地形等条件的共同影响。可见,由于青藏高原东南部降水和冻土对气候变化敏感,该地区水资源时空分布格局将面临很大的不确定性,对此应予以充分重视。     

Streamflow alteration and habitat ramifications for a threatened fish species in the Central United States

In the Central United States, the Arkansas darter (Etheostoma cragini) is listed as a threatened fish species by the State of Kansas. Survival of the darter is threatened by loss of habitat caused by changing streamflow conditions, in particular flow depletion. Future management of darter populations and habitats requires an understanding of streamflow conditions and how those conditions may have changed over time in response to natural and anthropogenic factors. In Kansas, streamflow alteration was assessed at 9 U.S. Geological Survey streamgages in 6 priority basins with no pronounced long‐term trends in precipitation. The assessment was based on a comparison of observed (O) and predicted expected (E) reference conditions for 29 flow metrics. The O/E results indicated a likely or possible diminished flow condition in 2 basins; the primary cause of which is groundwater‐level declines resulting from groundwater pumping for irrigated agriculture. In these 2 basins, habitat characteristics adversely affected by flow depletion may include stream connectivity, pools, and water temperature. The other 4 basins were minimally affected, or unaffected, by flow depletion and therefore may provide the best opportunity for preservation of darter habitat. Through the O/E analysis, anthropogenic streamflow alteration was quantified and the results will enable better‐informed decisions pertaining to the future management of darters in Kansas.     

The Sanaga discharge at the Edea Catchment outlet (Cameroon): An example of hydrologic responses of a tropical rain‐fed river system to changes in precipitation and groundwater inputs and to flow regulation

The Sanaga River is one of Sub‐Saharan Africa's largest and greatly regulated rivers. Available flow data for this hydrosystem largely cover the pre‐ and post‐regulation periods. From comparisons between unregulated (hypothetical) and observed scenarios, it has been possible to separate and to quantify hydro‐climatic (groundwater + rainfall) change effects from anthropogenic impacts (especially dam‐related alterations). To appreciate shifts in the river regime, discontinuity detection tests and the IHA model were applied to discharge data series reflecting average and extreme flow conditions, respectively. Results obtained principally from the Hubert segmentation method reveal that a major discontinuity occurred in 1970–1971 separating a surplus phase between 1945–1946 and 1969–1970, and a deficient and much contrasted one, from 1971/1972. This implies that the Sanaga catchment is dominantly affected by hydro‐climatic changes. However, wide land cover/land use changes experienced here since 1988 have resulted in an increase in surface runoff. Additional quickflows linked to these changes may have partly compensated for the substantial decline in the dry season rainfall and groundwater inputs observed from this date. Although at the monthly scale, dam‐related impacts on average flows increase with stage of regulation, the seasonal variability of the river regime remains generally unaffected. A comparison of the IHA statistics, calculated from unregulated and observed streamflow data, show that hydrologic shifts occurring in maximum and minimum discharges are mostly significant from 1971/1972 and are mainly due to the action of dams. Minimum flows appear, however, widely impacted, thus reflecting the prime objective assigned to the existing reservoirs, constructed to supplement flows for hydroelectricity production during the dry season. Copyright © 2010 John Wiley & Sons, Ltd.     

基于Vine Copula的短期径流预报不确定性分析

定量分析短期径流预报序列的不确定性特征,对于提高水库短期运行计划的可靠性具有重要意义。针对常用多元椭圆Copula或阿基米德Copula难以有效刻画短期径流预报不确定性特征的问题,本文引入了Vine Copula对不同径流量级及不同预见期下预报不确定性进行定量评估,进而分析了先验信息对于后续时段预报不确定性的影响。以雅砻江流域锦西水库为例进行验证,结果表明：相较于传统多元Copula函数,Vine Copula构建的相对预报误差联合分布均能通过假设检验且拟合效果最好,模拟结果的统计量与实测数据相差较小;通过利用调度期内已经发生的相对预报误差信息,可以有效减小后续时段相对预报误差期望值及90%置信水平分位距,降低预报的不确定性。     

Extreme value analysis of streamflow time series in Poyang Lake Basin, China

Extreme meteorological and hydrological events may cause major disasters and heavy social and economic losses.Therefore,more and more studies have focused on extreme hydro-meteorological events in various climates and geographic regions.Based on nearly 50 years of observed records of the Poyang Lake Basin,the occurrence and changing trends of extreme streamflow indices,including the annual maximum flow,annual peak-over-threshold flows,and low flows,were analyzed for ten hydrological stations.The results indicate that most annual maximum flows occurred from April to July,highly attributed to the Southeast Asian summer monsoons,whereas the annual minimum flows were concentrated between January and February.As for the low flow indices (the annual minimum flow,annual minimum 7-d flow,and annual minimum 30-d flow),a significant increasing trend was detected in most parts of the Poyang Lake Basin.The trends illustrate the potential effects of climate change and human activities on the hydrological cycle over the Poyang Lake Basin.     

Monthly Joint Operations for the Nakdong Multi-reservoir System in Korea

Abstract

This study applies a state-of-art optimization technique, SSDP/ESP (Sampling Stochastic Dynamic Programming with Ensemble Streamflow Prediction), to derive a monthly joint operating policy for the Nakdong multi-reservoir system in Korea. A rainfall-runoff model, SSARR (Streamflow Synthesis And Reservoir Regulation), is linked to the SSDP/ESP model to provide ESP scenarios for runoff during the next month in the Nakdong River basin. The primary advantage of the SSDP/ESP is that it updates the derived operating policy as new ESP forecasts become available. Another SSDP model that employs historical runoff scenarios (SSDP/Hist) is also developed. The main difference between the two SSDP models is that SSDP/Hist is an off-line model whereas the SSDP/ESP is on-line. The developed operating policies are tested with a simulation model using an object-oriented simulation software, STELLA. The simulation results show that SSDP/ESP is superior to SSDP/Hist with respect to the water supply criterion, although both models perform similarly with respect to the hydroelectric energy production criterion.     

Development of PCA-based cluster quantile regression (PCA-CQR) framework for streamflow prediction: Application to the Xiangxi river watershed,China

In this study, a PCA-based cluster quantile regression (PCA-CQR) method was proposed through integrating principal component analysis and quantile regression approaches into a stepwise cluster analysis framework. In detail, the principal component analysis was adopted to overcome the multicollinearity among the explanatory variables, while the quantile regression approach was used to provide probabilistic information in prediction. The proposed PCA-CQR method can effectively capture discrete and nonlinear relationships between explanatory and response variables. The applicability of PCA-CQR was demonstrated by a case study of monthly streamflow prediction in the Xiangxi River, China. The nonlinearity between the hydro-meteorological variables and the streamflow measurements was characterized through the measure of maximal information coefficient (MIC), which demonstrated the need of the proposed PCA-CQR method. The results showed that the previous monthly streamflow and precipitation, as well as potential evapotranspiration in current month posed significant nonlinear impacts on the streamflow in current month. Three components could well reflect the total variance of the input variables. Comparison between traditional SCA and PCA-CQR showed that the proposed approach could provide more accurate predictions than traditional SCA methods. Moreover, probabilistic forecasts could be provided by PCA-CQR, and the 90% predictive intervals could well bracket the observations in both calibration and validation periods. Also, sensitivity analysis was performed to identify the impacts of the control parameters in PCA-CQR on the performance of the proposed model. The results showed the proposed PCA-CQR improved the robustness of traditional SCA. Finally, comparison among PCA-CQR, GRNN and MLR also showed the effectiveness of the proposed method.     

基于人工神经网络的河川径流实时预报研究

将人工神经网络技术应用于河川径流实时预报，建立起河川径流实时预报的BP网络模型，并针对经典BP算法所存在的缺陷，采用共轭梯度优化和误差反向传播训练算法，使得所建立的BP网络模型的收敛性大为改善，消除和避免了实际应用中可能出现的局部优化问题．利用西大洋水库1975～1995年的入库径流系列资料，对所建立的BP网络模型进行训练和检验，同时探讨了网络结构对网络模型预报结果的影响．通过大量的实际应用和对比分析，表明BP网络模型比HG分析模型和相关图法更优越、更具有实际推广和应用价值．     

An ARMA-type section model for average ten-day streamflow synthesis

Most of the rivers in Taiwan are short and run on a steep slope due to the island's topography. Because of the weak correlations of streamflow in time and the occurrence of extreme events such as typhoons, classical autoregressive-moving average (ARMA) models have difficulties in forecasting and synthesizing the average 10-day streamflow in Taiwan. In this study, the synthesis of the average 10-day streamflow of the Tanshui River in Taiwan is accomplished by a section model. The model divides the year-round streamflow records into several sections according to their distinguishable patterns, and each section is modeled by a separate ARMA model. For parameter control, a heuristic grouping procedure, based on statistical inference of the random noise part, is used to separate a year into a minimum number of sections. The section separation procedure follows the general precipitation pattern in a year. The case study results indicate high statistical agreement between synthesized series and historical records. Additionally, a new procedure, extended autocorrelation function (EACF), is introduced and applied in this study to assist in model identification.     

滇池入流径流模型

本文以松华坝、滇池两站模型为例，叙述了双变量模型的基本原理，建立了随机模型，模拟生成了径流系列，为滇池的水量及水质模拟模型提供了入流资料。