CLIMATE-CHANGE IMPACTS ON RIVER FLOWS IN BRITAIN: THE UKCIPO2 SCENARIOS

This paper describes the implications of the UKCIPO2 climate-change scenarios for river flows in Britain, focusing on mean monthly runoff and Q95 (i.e. the flow which is exceeded for 95% of the time). By the 2020s. mean summer flows will be about 30% lower than the 1961–1990 mean and Q95 will be reduced by approximately 25%. Percentage reductions are particularly large in southern and eastern England. Mean winter flows are modestly increased, with the greatest increases in the north and west. Reductions in the recharge season result in lower flows in groundwater-dominated catchments throughout the year. The climate-change signal is larger than natural multi-decadal variability - even by the 2020s. This natural variability can add +/- 5% to the changes in Q95 due to climate change.
Changes resulting from the UKCIPO2 scenarios are (a) more extreme during summer than those resulting from earlier climate-change scenarios, showing considerably greater flow reductions, and (b) at the drier end of the range in changes arising from the application of scenarios based on other coarser-resolution climate models.     

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.     

基于集合卡尔曼滤波的变化环境下渭河流域日径流模拟

流域水文模型是研究水文规律和模拟水文过程的主要工具,而流域气候和下垫面条件的变化给径流的准确模拟带来了新的挑战。以渭河华县水文站以上流域为例,采用智能优化算法(SCE-UA)对HyMOD模型首先进行参数优选,并针对传统"捆绑率定"策略模拟效果不佳的实际情况,将集合卡尔曼滤波(EnKF)数据同化方法分别应用于HyMOD模型的状态变量更新、参数更新及状态—参数的同时更新,并在渭河流域近50年的日径流模拟中进行了效果检验。结果表明,状态—参数的双EnKF策略获得了最满意的效果,模拟精度比传统模型率定方法有显著提升。     

PREDICTING ECOLOGICAL FLOW REGIME AT UNGAGED SITES: A COMPARISON OF METHODS

Nineteen ecologically relevant streamflow characteristics were estimated using published rainfall–runoff and regional regression models for six sites with observed daily streamflow records in Kentucky. The regional regression model produced median estimates closer to the observed median for all but two characteristics. The variability of predictions from both models was generally less than the observed variability. The variability of the predictions from the rainfall–runoff model was greater than that from the regional regression model for all but three characteristics. Eight characteristics predicted by the rainfall–runoff model display positive or negative bias across all six sites; biases are not as pronounced for the regional regression model. Results suggest that a rainfall–runoff model calibrated on a single characteristic is less likely to perform well as a predictor of a range of other characteristics (flow regime) when compared with a regional regression model calibrated individually on multiple characteristics used to represent the flow regime. Poor model performance may misrepresent hydrologic conditions, potentially distorting the perceived risk of ecological degradation. Without prior selection of streamflow characteristics, targeted calibration, and error quantification, the widespread application of general hydrologic models to ecological flow studies is problematic. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.     

基于EnKS和SWAT模型的闽江流域径流数据同化

地表水文过程中观测变量对状态变量的响应存在时间滞后性,为提高径流数据同化的精度,以闽江流域为研究区,基于集合卡尔曼平滑器（EnKS）和SWAT模型,构建径流数据同化方案,并与集合卡尔曼滤波（EnKF）方法进行对比,评价不同同化模型的精度,分析数据同化对不同径流分量的影响。结果表明：EnKS最优时间窗口长度在不同水文周期、流域存在差异;考虑水文模型的时间滞后性可以有效提高模型的同化精度,对比EnKF方法,EnKS方法的纳什效率系数(NSE)在七里街、沙县、竹岐3个站点上分别提升了0.03、0.12、0.03,均方根误差(RMSE)分别减小了7.43%、26.81%、4.25%;数据同化方法对不同径流分量的改进程度存在空间异质性和时间异质性,在高渗透率土壤和陡坡区域EnKS方法能使壤中流获得更显著的改进,丰水期EnKS方法对地表径流的改进较枯水期更明显。     

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.     

干旱内陆河流域月径流的神经网络模拟

针对干旱内陆河流域地表径流形成、消耗的特点,采用1956~2003年的水文气象、灌溉用水等资料建立了用于模拟出山口月径流量、下游径流月径流量的分布式神经网络(ANN)模型。模型的输入为各子流域及中游本月降水、潜在蒸发蒸腾量、上月降水、潜在蒸发蒸腾量、中游灌溉面积、灌溉定额,输出为月径流量.检验结果表明,本文所建立的分布式ANN模型可以有效模拟干旱内陆河流域月径流,模型用于模拟子流域出山口径流的误差为0.18×107~0.42×107m3,用于模拟下游径流的误差为0.52×107m3.与单一ANN相比,尽管分布式ANN的输入不需实测出山口径流,但模型的精度没有明显减小.分布式ANN为研究干旱内陆河流域气候变化及农业活动对地表径流过程的影响提供了有效的工具.     

变化环境下东北半干旱地区径流演变规律分析——以洮儿河流域为例

受气候变化和人类活动影响,众多河流的径流量发生了改变,深入解析历史径流变化成因并探究未来径流演变趋势,是流域水资源科学管理的必然需求。本文以洮儿河流域为研究区,基于SWAT模型定量揭示历史径流变化原因,并结合未来气候情景,探究未来径流演变趋势。结果表明：洮儿河流域历史年均气温呈显著上升趋势,降水、径流均呈现一定下降趋势;气候变化和人类活动分别是洮儿河流域上游和下游径流变化的主要成因。在未来BCC-CSM2-MR（CMIP6）气候模式下,三种不同排放情景的未来期年均径流量相比于基准期变化-10.14% ~ 16.86%,未来水资源利用将面临更大挑战。研究成果可为深入理解流域历史径流变化成因及未来水资源演变趋势提供科学依据,为流域水资源规划和管理提供决策支持。     

Capability of TMPA products to simulate streamflow in upper Yellow and Yangtze River basins on Tibetan Plateau

Due to the high elevation, complex terrain, severe weather, and inaccessibility, direct meteorological observations do not exist over large portions of the Tibetan Plateau, especially the western part of it. Satellite rainfall estimates have been very important sources for precipitation information, particularly in rain gauge-sparse regions. In this study, Tropical Rainfall Measuring Mission （TRMM） Multi-satellite Precipitation Analysis （TMPA） products 3B42, RTV5V6, and RTV7 were evaluated for their applicability to the upper Yellow and Yangtze River basins on the Tibetan Plateau. Moreover, the capability of the TMPA products to simulate streamflow was also investigated using the Variable Infiltration Capacity （VIC） semi-distributed hydrological model. Results show that 3B42 performs better than RTVSV6 and RTV7, based on verification of the China Meteorological Administration （CMA） observational precipitation data. RTVSV6 can roughly capture the spatial precipitation pattern but overestimation exists throughout the entire study region. The anticipated improvements of RTV7 relative to RTVSV6 have not been realized in this study. Our results suggest that RTV7 significantly overestimates the precipitation over the two river basins, though it can capture the seasonal cycle features of precipitation. 3B42 shows the best performance in streamflow simulation of the abovementioned satellite products. Although involved in gauge adjustment at a monthly scale, 3B42 is capable of daily streamflow simulation. RTV5V6 and RTV7 have no capability to simulate streamflow in the upper Yellow and Yangtze River basins.     

中国年径流频率分布及统计特征区域规律分析

基于全国514个水文站1956~2000年的年径流资料,采用线性矩比例图和线性矩-矩对比图分析了P-Ⅲ型分布、对数正态(LN)分布拟合我国多年平均年径流系列的情况,并利用强局部加权回归曲线(LOWESS)平滑散点数据进行分布函数拟合判断,表明P-Ⅲ分布对我国年径流资料适用性较好。基于此,对全国年径流统计特征和区域规律进行研究,建立了南北分区径流量(深)、流域面积、标准差、离散系数之间的经验关系,为水资源规划及合理开发利用提供了依据。