Estimation of Parameters of a Conceptual Water Balance Model for Ungauged Catchments

The problem of parameter estimation constitutes the largest obstacle to successful application of conceptual catchment models in ungauged catchments. This paper investigates the usefulness of a conceptual water balance model for simulating river flow from catchments covering a wide variety of climatic and physiographic areas. The model is a 6-parameter water balance model which was applied to 26 seasonally snow covered catchments in central Sweden. The model was calibrated on a group of catchments and the calibrated parameter values related to physical catchment indices. The relationships were tested by comparing observed and simulated runoff records from 4 catchments that were not contained in the regression analysis. The results show that the model can be satisfactorily applied to ungauged basins in the study region. In order to test the physical relevance of the model to a wider set of conditions, the model was modified by excluding the snow routine part. The resulting model and the same technique were tested on 24 catchments taken from northern Belgium. The verification results were found to be satisfactory.     

Rating Curve Development at Ungauged River Sites using Variable Parameter Muskingum Discharge Routing Method

A physically based simplified discharge routing method, namely, the variable parameter Muskingum discharge-hydrograph (VPMD) routing method, having the capability of estimating the stage hydrographs simultaneously in channels with floodplains is presented herein. The upstream discharge hydrograph is routed using this VPMD method in different two-stage symmetrical trapezoidal compound cross section channel reaches. The performance of the VPMD method is evaluated by numerical experiments using the benchmark MIKE11 hydrodynamic model and the field data of the Tiber River in central Italy. The proposed method is capable of accurately routing the discharge hydrographs, corresponding stage hydrographs and synthesizing the normal rating curves at any downstream ungauged river site which is not affected by any downstream effects. This study can be helpful for various planning and management of river water resources in both the diagnostic and prognostic modes.     

无资料流域水文预报(PUB计划)研究进展

无资料流域水文预报,简称为PUB(Predictions in Ungaugecl Basins),从2003年7月开始成为国际水文科学学会新的国际水文十年计划主题．文中首先简述了PUB计划的主要研究内容,然后回顾了国际和国内已有的PUB研究进展,最后展望了对水文学发展有重要意义的几个PUB前沿研究,包括不确定性研究、对水循环各个环节因素的预报和对无资料流域水文过程的预报。     

SCS-CN Based Quantification of Potential of Rooftop Catchments and Computation of ASRC for Rainwater Harvesting

Rooftop rainwater harvesting, among other options, play a central role in addressing water security and reducing impacts on the environment. The storm or annual storm runoff coefficient (RC/ASRC) play a significant role in quantification of potential of rooftop catchments for rainwater harvesting, however, these are usually selected from generic lists available in literature. This study explores methodology/procedures based on one of the most popular and versatile hydrological model, Soil Conservation Service Curve Number (SCS-CN) (SCS 1986) and its variants, i.e., Hawkins SCS-CN (HSCS-CN) model (Hawkins et al. 2001), Michel SCS-CN (MSCS-CN) model (Michel et al. Water Resour Res 41:W02011, 2005), and Storm Water Management Model-Annual Storm Runoff Coefficient (SWMM-ASRC) (Heaney et al. 1976) and compares their performance with Central Ground Board (CGWB) (CGWB 2000) approach. It has been found that for the same amount of rainfall and same rooftop catchment area, the MSCS-CN model yields highest rooftop runoff followed by SWMM-ASRC?>?HSCS-CN?>?SCS-CN?>?CGWB. However, the SCS-CN model has close resemblance with CGWB approach followed by HSCS-CN model, SWMM-ASRC, and MSCS-CN model. ASRCs were developed using these models and it was found that MSCS-CN model has the highest value of ASRC (= 0.944) followed by SWMM-ASRC approach (=0.900), HSCS-CN model (=0.830), SCS-CN model (=0.801), and CGWB approach (=0.800). The versatility of these models lies to the fact that CN values (according to rooftop catchment characteristics) would yield rooftop runoff and therefore ASRC values based on sound hydrological perception and not just on the empiricism. The models have inherent capability to incorporate the major factors responsible for runoff production from rooftop/urban, i.e., surface characteristics, initial abstraction, and antecedent dry weather period (ADWP) for the catchments and would be better a tool for quantification rather than just using empirical runoff coefficients for the purpose.     

Regional Models for the Estimation of Streamflow Series in Ungauged Basins

The assessment of water resources in a region usually must cope with a general lack of data, both in time (short observed series) as well as in space (ungauged basins). Such a lack of data is generally overcome by combining rainfall–runoff models with regionalization techniques in order to transfer information to sites without or with short available observed series. The present paper aims to analyze applicability and limitations of two regionalization procedures for estimating the parameters of simple rainfall–runoff models respectively based on a “two-step” and on a “one-step” approach, for the estimation of monthly streamflow series in ungauged basins. In particular, an application to a Sicilian river basin of multiple regression equations according to a “two-step” and a “one-step” approaches and of a “one-step” approach based on neural networks is reported. For the investigated region, results indicate that models based on the “one-step” approach appear to be robust and adequate for estimating the streamflows in ungauged basins.     

Identifiability analysis in conceptual sewer modelling

For a sufficient calibration of an environmental model not only parameter sensitivity but also parameter identifiability is an important issue. In identifiability analysis it is possible to analyse whether changes in one parameter can be compensated by appropriate changes of the other ones within a given uncertainty range. Parameter identifiability is conditional to the information content of the calibration data and consequently conditional to a certain measurement layout (i.e. types of measurements, number and location of measurement sites, temporal resolution of measurements etc.). Hence the influence of number and location of measurement sites on the number of identifiable parameters can be investigated. In the present study identifiability analysis is applied to a conceptual model of a combined sewer system aiming to predict the combined sewer overflow emissions. Different measurement layouts are tested and it can be shown that only 13 of the most sensitive catchment areas (represented by the model parameter 'effective impervious area') can be identified when overflow measurements of the 20 highest overflows and the runoff to the waste water treatment plant are used for calibration. The main advantage of this method is very low computational costs as the number of required model runs equals the total number of model parameters. Hence, this method is a valuable tool when analysing large models with a long runtime and many parameters.     

东深供水改造工程水泵参数的选择

莲湖、旗岭和金湖供水泵站所采用的水泵填补了国内空白，在目前世界同类型水泵中处于领先地位，在选择水泵的过程中，其中一项重要工作是水泵参数的选择，比转速是水泵主要性能指标．在此介绍水泵比转速选择过程及所涉及的方方面面，目的是为该工程选择出一流的水泵．     

新型汇流计算方法及其在缺资料地区的应用

熵法、矩法推求纳什汇流参数需要完整的水文资料,在缺资料地区难以使用,故引入新型汇流计算方法,不依赖水文资料,利用Arc GIS软件,由流域地貌特征推求纳什汇流参数,进而获得时段单位线。选取湿润地区沙埠和半湿润地区马渡王两个流域,应用新型汇流计算方法进行次洪模拟研究,取得了良好效果,克服了熵法、矩法和其他参数优化方法对资料需求较高的不足,为缺资料地区汇流计算提供了新的方法。     

西藏稀缺资料地区洪峰流量推求

洪峰流量是水利工程规划设计、工程建设和运营管理的重要依据,对水利工程的投资规模和安全运行有着重要的意义。西藏地区主要水文测站实测洪峰流量(Instantaneous Peak Flow,简称:IPF)资料稀缺,而按水位计算整编的日径流资料(Mean Daily Flow,简称:MDF)相对较多。通过构建实测资料时段的洪峰流量与对应日平均流量间的函数关系,基于长序列的日径流资料估算洪峰流量,延长洪峰流量序列,为设计洪水提供数据支撑。研究结果表明:(1)西藏地区主要水文测站IPF～MDF函数关系稳定,利用这种函数关系由实测MDF推求的IPF误差均在10%以内,且延长后的IPF序列频率分析计算结果更加合理;(2)对于实测MDF序列缺乏的测站,可以通过气象资料驱动HIMS系统水文模块(Hydro Informatic Modeling Systerm)拓展MDF序列,在此基础上推求IPF序列。基于HIMS系统水文模块对西藏三条典型河流(年楚河、拉萨河和尼洋河)的日径流序列进行了模拟,结果表明,模型对日径流整体过程与高流量值的模拟效果均良好。进而利用模型延长的MDF序列以及构建的IPF～MDF函数关系拓展了西藏三条典型河流2000年-2010年间的IPF序列。     

Estimating the Ungauged Natural Flow Regimes for Environmental Flow Management

Regime-based approach recently becomes an important strategy while considering aquatic ecosystems in environmental flow management. The key element for supporting this strategy is long streamflow data which is usually not available for determining natural flow regimes. This study uses a back-propagation network to estimate ungauged natural flow regimes. A set of the upper reaches of Taiwan’s 42 flow stations with non-human control streamflow and at least 20 years daily flow data is used to quantify the natural flow regimes using 31 Indicators of Hydrologic Alteration (IHA). Watershed geomorphologic characteristic factors and rainfall parameters are used to classify homogeneous flow regime areas. The results show that there are three types of flow regimes from the flow stations, and each group of indicators in the IHA has different correlations with different geomorphologic characteristic factors and rainfall parameters. The results of using an artificial neural network model to estimate IHA show that the group average percent error fell from 21 % to 8 % and the average correlation coefficient was over 0.7, indicating that the model presented in this study is able to accurately estimate the natural flow regime in ungauged stations. Instead of predicting daily streamflow, this study estimates indicator values for ease of ecological water resources management.     

Estimation of Design Flood Hydrograph for an Ungauged Watershed

Based on the physiographical features of the studied watershed of 102.5 km² in northern Ontario and the meteorological data of one nearby climatic station, through the combination of the regionalization of flood and the HEC-1 modeling, this article presents an approach that may be used to determine the desired peak flows for the ungauged watershed. The empirical equations used to determine the desired peak flows were developed by the Cumming Cockburn Ltd. (CCL) who has carried out the studies on flood regionalization by using flow data at 380 gauging stations in Ontario. CCL has proposed four methods to estimate peak flows, namely 1) regression method describing multiple linear relationships between flood flow and related parameters; 2) index flood frequency curve; 3) regional flood frequency curve and 4) isoline map for unit peak flow. The desired peak flows for studied watershed determined by CCL methods were used to calibrate the HEC-1 model for the rainfall-runoff simulation for this watershed which consists of 15 subwatersheds. Through slight adjustment in the CN number used in the HEC-1 model, the calibrated HEC-1 model could be used for rainfall-runoff simulation for this ungauged watershed. This approach could be recommended for hydrological design and watershed management for ungauged watersheds provided the analyses of flood regionalization could be conducted. In addition, comparing to the Bavaria forest region, Germany, some questions have been discussed in this article.     

基于地貌瞬时单位线的缺资料小流域水文预报

为使水文预报结果具有更高的精度,在地貌瞬时单位线通用公式的基础上,将面雨量的不均匀性反映到面积率上,从而对初始概率作了适当的调整。另外,考虑坡面汇流相对于河道汇流具有一定程度的滞时,将坡地作为特殊的河流引入地貌瞬时单位线,保持了地貌瞬时单位线计算结构的一致性。应用结果表明:改进的地貌瞬时单位线的平均误差为6.02%,而未改进的地貌瞬时单位线的误差为14.70%。     

Identifiability analysis of the CSTR river water quality model.

Conceptual river water quality models are widely known to lack identifiability. The causes for that can be due to model structure errors, observational errors and less frequent samplings. Although significant efforts have been directed towards better identification of river water quality models, it is not clear whether a given model is structurally identifiable. Information is also limited regarding the contribution of different unidentifiability sources. Taking the widely applied CSTR river water quality model as an example, this paper presents a theoretical proof that the CSTR model is indeed structurally identifiable. Its uncertainty is thus dominantly from observational errors and less frequent samplings. Given the current monitoring accuracy and sampling frequency, the unidentifiability from sampling frequency is found to be more significant than that from observational errors. It is also noted that there is a crucial sampling frequency between 0.1 and 1 day, over which the simulated river system could be represented by different illusions and the model application could be far less reliable.     

Performance of a Monthly Streamflow Prediction Model for Ungauged Watersheds in Spain

Climate change, drought and the world??s growing population are increasing the demand for water which in turn requires improved water resources management. The sustainable management of a watershed requires a thorough knowledge of its water resources, including monthly streamflow. Spain is home to a large number of ungauged watersheds, the streamflows of which are often unknown. Chavez et al. (2007) reported a model for predicting monthly streamflow in ungauged watersheds that was validated for use in areas of tropical climate in Central America and a dry area in South America. This work reports an attempt to assess the performance of this model for eventual use with ungauged watersheds in Spain, using data for a number of watersheds for which gauging data were available. The proposed model took into account physical characteristics such us the soil infiltration rate, the slope of the terrain, plant fractional cover, the monthly moisture adequacy index, and the leaf area index. Comparisons of model-predicted monthly streamflows and those actually measured showed the Chavez et al. model unable to make reliable predictions for Spanish watersheds in its current form. A new approach has been developed considering only smaller watersheds in Spanish conditions, changing parameters in the original model. These parameters have been calibrated and validated, reaching adequate adjustment of results.     

Estimation of Peak Flood Discharges at Ungauged Sites Across Turkey

The reliable forecasting of the peak flood discharge at river basins is a common problem, and it becomes more complicated when there is inadequate recorded data. The statistical methods commonly used for the estimation of peak flood discharges are generally considered to be inadequate because of the complexity of this problem. Recently, genetic programming (GP) which is a branch of soft computing methods has attracted the attention of the hydrologists. In this study, gene-expression programming (GEP) and linear genetic programming (LGP), which are extensions to GP, in addition to logistic regression (LR) were employed in order to forecast peak flood discharges. The study covered 543 ungauged sites across Turkey. Drainage area, elevation, latitude, longitude, and return period were used as the inputs while the peak flood discharge was the output. Model comparison results revealed that GEP predicted the peak flood discharges with R ²?=?57.4?% correlation, LGP with 56?% and LR model with 42.3?%, respectively. The peak flood discharges in all river basins can now be determined using the single equation provided by the GEP model.     

棱锥体结构对弯道水流的改善与布置参数优化研究

河道的弯道段设置相应的护岸工程,可规避复杂横向水流对河岸稳定性产生的影响.文章通过模型试验,探讨了在河流弯道段设置棱锥体对改善流态的作用.结果显示,在弯道设置三棱锥体可提高水面均匀度和水面横比降,显著改善弯道流态,具有一定的工程应用价值,增加椎体的设置数量对改善水面流态更为有利.     

Simulating Future Groundwater Recharge in Coastal and Inland Catchments

Groundwater is a primary source of drinking water in the Mediterranean, however, climate variability in conjunction with mismanagement renders it vulnerable to depletion. Spatiotemporal studies of groundwater recharge are the basis to develop strategies against this phenomenon. In this study, groundwater recharge was spatiotemporally quantified using the Soil and Water Assessment Tool (SWAT) in one coastal and one inland hydrological basin in Greece. A double calibration/validation (CV) procedure using streamflow data and MODIS ET was conducted for the inland basin of Mouriki, whereas only ET values were used in the coastal basin of Anthemountas. Calibration and simulation recharge were accurate in both sites according to statistical indicators and previous studies. In Mouriki basin, mean recharge and runoff were estimated as 16% and 9%, respectively. In Anthemountas basin recharge to the shallow aquifer and surface runoff were estimated as 12% and 16%, respectively. According to the predicted RCP 4.5 and 8.5 scenarios, significant variations in groundwater recharge are predicted in the coastal zone for the period 2020–2040 with average annual recharges decreasing by 30% (RCP 4.5) and 25% (RCP 8.5). Variations in groundwater recharge in the inland catchment of Mouriki were insignificant for the simulated period. Anthemountas basin was characterized by higher runoff rates. Groundwater management in coastal aquifers should include detailed monitoring of hydrological parameters, reinforced groundwater recharge during winter and reduced groundwater abstraction during summer depending on the spatiotemporal distribution of groundwater recharge.

     

基于灵敏度计算的电力系统参数可辨识性分析

对于简单电力系统建模中参数可辨识性问题,以往采用解析方法可以进行分析。但对于大规模电力系统,解析方法难以进行。文中发现了电力系统参数的可辨识性与灵敏度之间的关系。提出先根据灵敏度的相位来判断参数能否唯一辨识,再根据灵敏度的大小来选择可辨识的重点参数,最后采用蚁群算法优化重点参数。通过算例分析,证明了上述方法的可行性。     

Regionalization of Tank Model Using Landscape Metrics of Catchments

To address the challenges inherent in accessing spatiotemporal hydrological data, water resources professionals have developed various regionalization tools. The present study examines the possibility that changes in landscape metrics including mean shape index, mean perimeter-area ratio, mean patch size and patch density of land use/ land cover could result in variations in the optimized parameters of the conceptual rainfall-runoff Tank model. Data from 30 catchments that are geographically distributed in Germany was used to develop the procedure. Regression analysis-based modeling indicated that four out of twelve model parameters (r²?≥?0.40) can be explained by changes in catchment geometrics along with a set of landscape metrics of land use/land cover. They include: coefficient of infiltration flow (r²?=?0.48, p?<?0.03), intermediate flow (r²?=?0.77, p?<?0.02), water storage level for sub-surface flow (r²?=?0.57, p?<?0.05) and water storage level for intermediate flow (r²?=?0.85, p?<?0.01). Despite developing fairly reliable regression models, uncertainty analysis also revealed that uncertainty induced unreliability of the regionalized models is of significant importance.