Estimation of baseflow recession constants

Hydrograph recession constants are required in rainfall-runoff models, baseflow augmentation studies, geohydrologic investigations and in regional low-flow studies. The recession portion of a streamflow hydrograph is shown to be either an autoregressive process or an integrated moving average process, depending upon the structure of the assumed model errors. Six different estimators of the baseflow recession constant are derived and tested using thousands of hydrograph recessions available at twenty-three sites in Massachusetts, U.S. When hydrograph recessions are treated as an autoregressive process, unconditional least squares or maximum likelihood estimators of the baseflow recession constant are shown to exhibit significant downward bias due to the short lengths of hydrograph recessions. The precision of estimated of hydrograph recession constants is shown to depend heavily upon assumptions regarding the structure of the model errors. In general, regression procedures for estimating hydrograph recession parameters are generally preferred to the time-series alternatives. An evaluation of the physical significance of estimates of the baseflow recession constant is provided by comparing regional regression models which relate low-flow statistics to three independent variables: drainage area, basin slope and the baseflow recession constant. As anticipated, approximately unbiased estimators of the baseflow recession constant provide significant information regarding the geohydrologic response of watersheds.     

Case study evaluation of the geomorphologic instantaneous unit hydrograph

Several issues related to the probabilistic and hydraulic structure of the geomorphologic instantaneous unit hydrograph (GIUH) are addressed. These issues are: (1) accuracy of the geomorphologic expressions of the probabilities of surface runoff movement in a watershed, (2) identifying, for a given storm, a representative time-average velocity for surface runoff, (3) estimation of this velocity for the ungauged watersheds and effect of velocity estimation errors on the GIUH predictability, and (4) suitability of incorporating a linear expression for infiltration in the GIUH as well as the estimation problem of the infiltration coefficient and its effect on the reliability of predicted hydrographs. These issues are analyzed through application of the GIUH for two gauged watersheds in the southwestern region of Saudi Arabia. Twelve storm events are used in the analysis and the results are presented.Irrigation and Hydraulics Department, Faculty of Engineering, Cairo University, Giza Egypt.     

生成日径流资料的散粒噪声模型

描述时间连续日径流过程散粒噪声过程是非正态随机模型。本文对G.weiss提出的单散粒噪声模型中的涨水退水曲线的形式改用为Γ-分布的密度函数表示,推导出改进后的散粒噪声模型的一、二阶矩的计算公式和以日平均流量资料为依据的离散序列的一、二阶矩的递推公式。并用物理-统计相结合的方法估计有关模型参数,改进拟合程度。本文还对weiss提出的单散粒噪声综合数据的生成方法上做了修正。最后通过潮白河密云水库等站的日平均径流资料说明这模型的应用。     

Risk Assessment for a Proposed Groundwater Abstraction Scheme in Strathmore, North-East Scotland: a Modelling Approach

The Lower Old Red Sandstones in northern Strathmore have favourable hydrogeological conditions for ground-water development. A scheme was proposed to abstract water in the north Esk catchment in order to augment water supplies to local villages, and a production borehole was drilled into the Edzell Sandstones to give a design yield of 2420 m³/d. However, this scheme has been abandoned because of concern that the abstraction would significantly reduce the flow in a nearby stream which is an important salmonid fishery.
This study demonstrates the potential value of using a stream-aquifer numerical model in an environmental risk assessment for the proposed scheme.     

基于多层神经元网络的随机自适应径流预报模型

针对水文系统的非线性特性，提出了一种基于多层神经元网络的自适应径流预报模型，并对其预报机理进行了分析。该预报模型由两个同构的多层神经元网络－训练网络和预报网络实现，实例验证了本文方法的有效性。从而为解决水文系统的径流预报提供了一条可行的途径。     

Effects of climate change and anthropogenic activities on runoff change of the Weihe River basin,Northwest China

The Weihe River has experienced a significant runoff decline in the past few decades, but the detailed and systematic analysis of different sub-regions of the Weihe River basin (WRB) for a long time is insufficient. Based on the data of five hydrological stations from 1957 to 2018, this study investigated the variation of annual runoff both in the whole Weihe River basin (WWRB) and its sub-regions: the upper, middle, and lower reaches of the Weihe River (URWR, MRWR, LRWR, respectively), the Jing River basin (JRB), and the Beiluo River basin (BLRB). Moreover, the contribution of climate change and anthropogenic activities on runoff change was quantified by double mass curve (DMC) and hydrological sensitivity analysis (HSA) methods. The results showed that runoff of the URWR, MRWR, JRB, BLRB, and WWRB showed significant downward trends, and with the change-point years of 1993, 1990, 1996, 1994, and 1993, respectively. Both results of DMC and HSA showed that anthropogenic activities were the main factors for runoff reduction. The contribution of human activities was largest in the JRB and BLRB, whereas lowest in the MRWR. Over the study period, land use has changed significantly in the basin, mainly manifested in the reduction of farmland, and the increase of construction land and grassland, indicating that intense anthropogenic activities have taken place. Moreover, the total water consumption of the WWRB increased evidently, which exacerbated the contradiction between supply and demand of water resources. The results of HSA showed that runoff was more sensitive to precipitation than to E_p. Precipitation reduced the runoff, while E_p increased runoff in the basin. The results of this study are helpful for understanding the regional hydrological situation in more detail, and can act as a reference for formulating reasonable water resources allocation schemes.     

Automated streamflow measurements in high-elevation Alpine catchments

Salt dilution is a well-established streamflow measurement method in creeks, which works particularly well downstream of turbulent flow sections as the mixing of the salt tracer is enhanced. Usually, salt dilution measurements are performed manually, which considerably limits the observations of rare peak flow events. These events are particularly important for constructing robust rating curves and avoiding large uncertainties in the extrapolation of streamflow values. An additional challenge is the variability of the river cross section, especially after larger discharge events, leading to nonstationary rating curves. Therefore, discharge measurements well distributed over time are needed to construct a reliable streamflow–water level relationship and to detect changes caused by erosion and deposition processes. To overcome these two issues, we used an automated streamflow measuring systems at three different sites with contrasting hydrological and hydraulic characteristics in the Alps. This system allowed us to measure discharge at nearly maximum flow of the observation period (2020–2021) at all three sites and to detect abrupt changes in the rating curve by performing event-based salt injections. The uncertainty in the measurements was quantified, and the streamflow was compared with official gauging stations in the same catchment. Based on a very large dataset of almost 300 measurements, we were able to evaluate the reliability of the system and identify the primary sources of uncertainty in the experimental setup. One key aspect was the site selection for the downstream electrical conductivity sensors, as measurement location strongly controls the signal-to-noise ratio in the recorded breakthrough curves.