Catchment Storage and its Influence on Summer Low Flows in Central European Mountainous Catchments

The objective of this study was to determine the role of spring catchment water storage on the evolution of low flows in central European mountainous catchments. The study analysed 58 catchments for which catchment storage, represented by snow, soil water and groundwater storages, was determined by the HBV hydrological model over a 35-year period. The spring catchment storage was related to several streamflow indices describing low flow periods using the mutual information criterion. The mean runoff in the summer and autumn periods was mostly related to rainfall sums from the respective season. The median relative contribution of rainfall to the total mutual information value was 48.4% in summer, and 44.2% in autumn period, respectively. The relative contribution of soil water and groundwater storages was approximately 25% for each of the components. In contrast, the minimum runoff, its duration and deficit runoff volume, were equally related to both catchment storage and seasonal rainfall, especially in the autumn period.

     

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.     

Data- and model-driven determination of flow pathways in the Piako catchment,New Zealand

Quantifying flow pathways within a larger catchment can help improve diffuse pollution management strategies across subcatchments. But, spatial quantification of flow pathway contributions to catchment stream flow is very limited, since it is challenging to physically separate water from different paths and very expensive to measure, especially for larger areas. To overcome this problem, a novel, combined data and modelling approach was employed to partition stream flow in the Piako catchment, New Zealand, which is a predominantly agricultural catchment with medium to high groundwater recharge potential. The approach comprised a digital filtering technique to separate baseflow from total stream flow, machine learning to predict a baseflow index (BFI) for all streams with Strahler 1st order and higher, and hydrological modelling to partition the flow into five flow components: surface runoff, interflow, tile drainage, shallow groundwater, and deep groundwater. The baseflow index scores corroborated the spatial distributions of the flow pathways modelled in 1st order catchments. Average depth to groundwater data matched well with BFI and Hydrological Predictions for the Environment (HYPE) modeled flow pathway partitioning results, with deeper water tables in areas of the catchment predicted to have greater baseflow or shallow and deep groundwater contributions to stream flow. Since direct quantification of flow pathways at catchment-scale is scarce, it is recommended to use soft data and expert knowledge to inform model parameterization and to constrain the model results. The approach developed here is applicable as a screening method in ungauged catchments.     

Modelling nitrate losses from agricultural activities on a national scale.

The Nitrogen Risk Assessment Model for Scotland (NIRAMS) has been developed as a screening tool for prediction of streamwater N concentrations draining from agricultural land in Scotland. The objective of the model is to be able to predict N concentrations for ungauged catchments, to fill gaps in monitoring data and provide guidance in relation to policy development. The model uses national land use, soils and meteorology data sets and has been developed within an ArcView GIS user interface. The model includes modules to calculate N inputs to the land, residual N remaining at the end of the growing season, weekly time-series of leached N and transport of N at the catchment scale. The N leaching and transport are. controlled by hydrological modules, including a national water balance model and a catchment scale transport model. Preliminary testing of NIRAMS has been carried out on eight Scottish catchments, diverse in terms of geographic location as well as land use. The model is capable of predicting the correct mean level of stream N concentrations, as well as the basic characteristics of seasonal variation. As such the model can be of value for providing estimates of N concentrations in ungauged areas.     

Low Flows Regionalization in North-Western Italy

Prediction of low flows in ungauged catchments is needed in many branches of water resources management, including water availability and river ecology studies. In this paper we analyze the regional variability of q ₉₅, i.e., the specific discharge that is exceeded 95% of the time, in North-Western Italy (Piemonte and Valle d’Aosta Regions). Multiple regressions with morphoclimatic catchment characteristics are applied in subregions obtained through four classification methods: Seasonality Indices (SI), Classification and Regression Trees (CRT), Residual Pattern Approach (RPA) and Weighted Cluster Analysis (WCA). All the classification methods separate the South-Eastern Apennine-Mediterranean area from the rest of the study domain (the Alps mountain range), even if they use different criteria to carry out this division (e.g., the percentage of forest, seasonality of low flows, combination of several parameters). In the Apennine-Mediterranean part of the area, low flows occur in summer with a long period of drought and are mainly due to dry climate, moderate snowpack storage and high evapotranspiration. In Alpine catchments low flows occur in winter and vary according to precipitation, elevation, interactions with aquifers and land cover. Within the Alpine mountain range the CRT algorithm identifies a number of small high-elevation catchments in which the intense drought period during winter has the soil freezing processes as the driving force. From a statistical point of view, the CRT model outperforms the models obtained by the other classification techniques in terms of explained variance (69%). Because of this, and given the meaningful hydrological interpretation of the results, we use the CRT model for the regionalization of q ₉₅ in Piemonte and Valle d’Aosta. Lastly, as operational procedure for future low flow regionalization studies, we suggest that more classification methods should be applied to assist the critical analysis of the results.     

Potential Improvement of the Parameter Identifiability in Ungauged Catchments

The objective of this study was to reduce the parameter uncertainty which has an effect on the identification of the relationship between the catchment characteristics and the catchment response dynamics in ungauged catchments. Model deficiencies influencing on the identification of the regional relationships were identified through analysing the non-stationarity nature under different climate conditions. An advanced calibration approach was proposed to improve the identification of the regional relationships, according to the deficiencies on model structure suitability for the different flow regime. This study demonstrated the refined calibration strategy can improve the identification of the relationships between the catchment characteristics and the calibrated model parameters for the dry period. In the assessment of model structure suitability to represent the non-stationary catchment response characteristics, there was a flow-dependent bias in the runoff simulations. In particular, over-prediction of the streamflow was dominant for the dry period. The poor model performance during the dry period was associated with the largely different impulse response estimates for the entire period and the dry period. Based on assessment of model deficiencies, the rainfall–runoff models were separately calibrated to different parts of the flow regime, and the calibrated models for the separated time series were used to establish the regional models of relevant parts of the flow regime (i.e. wet and dry periods). The effectiveness of the parameter values for the refined approach in regionalisation was evaluated through investigating the accuracy of predictions of the regional models. The regional models from the refined calibration approach clearly enhanced the hydrological behaviour for the dry period by improving the identification of the relationships between the catchment attributes and the catchment response dynamics representing the time constants in fitting recession parts of hydrograph (i.e. improving the parameter identifiability representing the different behaviour of the catchment) in regionalisation.     

全国小流域分布式单位线综合分析

基于全国小流域数据集,采用相关性分析和基于最小二乘法的多元回归非线性模型进行了小流域分布式单位线的综合分析,并以全国30个不同地形地貌类型区的中小流域为例开展了应用研究。研究表明:小流域不均匀系数、加权平均坡度反映了小流域汇流非均质分布特性,小流域属性与单位线特征值(洪峰流量、汇流时间和峰现时间)之间存在中度-强度相关关系;单位线洪峰流量、汇流时间和峰现时间最优公式型的均方根误差分别为0.14～0.75 m3/s、3.16～7.21 min和3.15～7.33 min,合格率分别为86%～100%、85%～100%和65%～100%,相关系数分别为0.93～0.99、0.89～0.99和0.83～0.98,构建的单位线特征值综合公式较好地反映了不同地形地貌类型区洪水集中度和汇集时间的差异性。研究可为缺资料地区中小流域暴雨洪水分析计算和山洪早期预报预警提供技术支撑。     

Comparing Three Hydrological Models for Flash Flood Simulations in 13 Humid and Semi-humid Mountainous Catchments

Flash flood disaster ranks top among all the natural hazards across the world due to its high frequency, severity and fatality. However, flash flood simulation is still challenging in small and medium-sized catchments with complex orography, flashy hydrological responses and poor observations. Three distributed hydrological models, i.e., TOPModel, HEC and CNFF, are selected to simulate flash floods in seven humid and six semi-humid catchments in China, with consideration of water balance (RER), peak flow rate (REQ) and its occurrence time (TP), hydrograph variation (SNSE) and model uncertainty. Influences of five catchment attributes are further investigated on individual model performances. All three models perform satisfactorily in humid catchments, but less satisfactorily in semi-humid catchments. Water balance is well obtained by CNFF, followed by HEC and TOPModel. Peak flow rate and its occurrence time are most accurately captured by CNFF and HEC, respectively. Hydrograph variations are well reproduced by HEC and CNFF. TOPModel performs well for picking peak flow and hydrograph variation in humid catchments. Uncertainty interval is narrowest for HEC with average relative interval length at 95% confidence level being 0.78?~?2.53. Most observations are bracketed by uncertainty intervals for TOPModel (64.79%?~?91.91% of total). Three model performance indices (i.e., RER, REQ, and SNSE) are mainly affected by drainage area and forest ratio across humid and semi-humid catchments, while TP performance is mainly affected by mean slope in humid catchments.

     

分布式单位线在河北雨洪模型中的应用

因河北雨洪模型的汇流计算方法难以用于无资料流域,其汇流参数难以获得且不宜移用,为此,将基于数字高程模型的分布式单位线用于河北雨洪模型,并对峪门口流域4场较大洪水过程进行了模拟。结果表明:4场洪水洪峰流量相对误差均<5%,峰现时间误差均<2 h,确定性系数均>0.85,模拟效果令人满意。河北雨洪模型与基于流域地形地貌特征的分布式单位线相结合,可解决无资料流域,特别是山丘地区中小流域的洪灾预警预报等问题。     

Characterization of natural and environmental flows in New Brunswick,Canada

A good understanding of the natural flow regime plays an important role in many hydrological studies. Also important in such studies is the quantification of environmental flows. This study focuses on flow metrics that best describe the natural flow regime and the hydrological characteristics for rivers in New Brunswick (Canada) as well as quantifying environment flows for these rivers. New Brunswick rivers have a mean annual flow (MAF) of approximately 23 L s^?1 km^?2, which is also reflective of the water availability. The frequency analysis showed that low flows (T = 2–50 years, where T is the recurrence interval) were all below the 10% MAF. Environmental flow methods based on the MAF and flow duration analysis (median flow) showed good regional regression equations. However, flow duration methods showed high variability especially at flows between Q₈₀ and Q₁₀₀. Flow targets based on the 25% MAF, Q₅₀ and 70% Q₅₀ were used to estimate environmental flows, particularly during low‐flow periods (winter and summer). Results showed that the 70% Q₅₀ method should be used with caution in summer as this method provided flows in the range of 15–16% of MAF. Other methods provided environmental flows higher than 15% MAF, thus, providing better flow protection for aquatic habitat. When comparing water availability for off‐stream use (river flow–environmental flow), different parts of New Brunswick were found to be deficient in flows (i.e., river flows less than environment flows—no extractable water) during the summer and winter low‐flow periods.     

Quantification of Expected Changes in Peak Flow Quantiles in Climate Change by Combining Continuous Hydrological Modelling with the Modified Curve Number Method

Climate projections point to modifications in the magnitude, frequency and timing of floods in the future. However, robust methodologies to quantify how climate change will modify the catchment response in flood events are required. Continuous hydrological modelling usually smooth magnitudes of extreme events. This paper proposes a methodology to improve the assessment of flood changes in the future driven by climate change. Climate change projections of the EURO-CORDEX programme obtained under the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) supplied are used. Four catchments located on the Douro River Basin have been considered as case studies. Precipitation and temperature projections have been bias corrected to reduce errors with observations in the control period (1971–2004). The HBV continuous hydrological simulation model has been used to simulate the soil moisture content on the day of occurrence of the maximum annual rainfalls in the four catchments. The modified curve number method has been utilized to obtain the changes expected in the future in flood magnitudes, considering the initial soil moisture contents estimated with the HBV model and the expected changes in annual maximum rainfalls. The methodology has been applied to the control period (1971–2004) to check the validity of the process. Then, the methodology has been applied to the future period (2011–2095), to quantify the changes expected in the future in flood magnitudes under climate change conditions. The combined use of the HBV continuous hydrological simulation with the modified curve number method improves the results provided by the HBV model. The proposed methodology allows a better characterization of the response of catchments in flood events. It also considers the expected variation in the antecedent moisture content in catchments in the future, driven by increasing temperatures and decreasing mean annual precipitations in the future. The results show that flood quantiles will increase in three of the four catchments considered.

     

Hydrological behaviour and water balance analysis for Xitiaoxi catchment of Taihu Basin

With the rapid social and economic development of the Taihu region, Taihu Lake now faces an increasingly severe eutrophication problem. Pollution from surrounding catchments contributes greatly to the eutrophication of water bodies in the region. Investigation of surface flow and associated mass transport for the Xitiaoxi catchment is of a significant degree of importance as the Xitiaoxi catchment is one of the major catchments within the Taihu region. A SWAT-based distributed hydrological model was established for the Xitiaoxi catchment. The model was calibrated and verified using hydrometeorological data from 1988 to 2001. The results indicate that the modeled daily and annual stream flow match the observed data both in the calibration period and the verification period, with a linear regression coefficient R2 and a coefficient e for modeled daily stream flow greater than 0.8 at Hengtangcun and Fanjiacun gauge stations. The results show that the runoff process in the Xitiaoxi catchment is affected both by rainfall and human activities （e.g., reservoirs and polder areas）. Moreover, the human activities weaken flood peaks more noticeably during rainstorms. The Water balance analysis reveals the percentages of precipitation made up by surface flow, evapotranspiration, groundwater recharge＇ and the change of soil storage, all of which are considered useful to the further understanding of the hydrological processes in the Xitiaoxi catchment. This study provides a good base for further studies in mass transport modeling and comparison of modeling results from similar hydrological models.     

Estimation of Clark’s Instantaneous Unit Hydrograph Parameters and Development of Direct Surface Runoff Hydrograph

We present a method to estimate Time of Concentration (T _c) and Storage Coefficient (R) to develop Clark’s Instantaneous Unit Hydrograph (CIUH). T _c is estimated from Time Area Diagram of the catchment and R is determined using optimization approach based on Downhill Simplex technique (code written in FORTRAN). Four different objective functions are used in optimization to determine R. The sum of least squares objective function is used in a novel way by relating it to slope of a linear regression best fit line drawn between observed and simulated peak discharge values to find R. Physical parameters (delineation, land slope, stream lengths and associated drainage areas) of the catchment are derived from SPOT satellite imageries of the basin using ERDAS: Arc GIS is used for geographic data processing. Ten randomly selected rainfall–runoff events are used for calibration and five for validation. Using CIUH, a Direct surface runoff hydrograph (DSRH) is developed. Kaha catchment (5,598 km²), part of Indus river system, located in semi-arid region of Pakistan and dominated by hill torrent flows is used to demonstrate the applicability of proposed approach. Model results during validation are very good with model efficiency of more than 95% and root mean square error of less than 6%. Impact of variation in model parameters T _c and R on DSRH is investigated. It is identified that DSRH is more sensitive to R compared to T _c. Relatively equal values of R and T _c reveal that shape of DSRH for a large catchment depends on both runoff diffusion and translation flow effects. The runoff diffusion effect is found to be dominant.     

Suspended sediment load estimation in an ungauged river in south‐eastern Australia

Soil erosion poses a significant threat to river health as well as the sustainability of soil resources. Management of this issue requires catchment‐specific data to be developed; however, many large catchments are poor in terms of hydrological and sediment transport data. Regional scale (thousands of square kilometres), computer‐based modelling methods are a way to generate such data. This study aims to apply the SedNet model to estimate a sediment budget for a 575 km², ungauged, agricultural catchment of south‐eastern Australia. The model results are then compared with field measured erosion rates for the catchment, in order to assess the sustainability of soil loss and redistribution across the catchment. SedNet estimated average suspended sediment concentrations between 70 and 120 mg/L, under conditions deemed most representative of the river. These model estimates were comparable with monitoring data, showing suspended sediment concentrations between 30 and 350 mg/L. It was found that soil loss and redistribution across the catchment is low; however, the estimated base sediment loads indicate that river health may be negatively impacted by this. SedNet accurately represented current catchment and river conditions and provided a reliable estimation of sediment yield, demonstrating the ability to estimate sediment loss and redistribution across data‐poor catchments using a multifaceted modelling approach. Methodologies, such as the one presented here, offer the ability to better assess the impacts of erosion on sediment loads to develop strategies to effectively manage excess suspended sediment.     

Sensitivity Analysis of the GIUH based Clark Model for a Catchment

For estimation of runoff response of an ungauged catchment resulting from a rainfall event, geomorphologicalinstantaneous unit hydrograph (GIUH) approach is getting popularbecause of its direct application to an ungauged catchment. Itavoids adoption of tedious methods of regionalization of unithydrograph; wherein, the historical rainfall-runoff data of anumber of gauged catchments are required to be analyzed. In thisstudy, the GIUH derived from geomorphological characteristics ofa catchment has been related to the parameters of Clark IUH modelfor deriving its complete shape. The DSRO hydrographs estimatedby the GIUH based Clark model have been compared with the DSROhydrographs computed by the Clark IUH model option of the HEC-1package and the Nash IUH model by employing some of the commonlyused error functions. Sensitivity analysis of the GIUH basedClark model has been conducted with the objective to identify thegeomorphological and other model parameters which are moresensitive in estimation of peak of unit hydrographs computed bythe GIUH based Clark model. So that these parameters may beevaluated with more precision for accurate estimation of floodhydrographs for the ungauged catchments.     

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.     

Development of Regional Flood Frequency Relationships Using L-moments for Middle Ganga Plains Subzone 1(f) of India

In this study, screening of the data has been carried out basedon the discordancy measure (D _i) in terms of the L-moments. Homogeneity of the region has been tested using the L-moments based heterogeneity measure, H. For computing the heterogeneity measure H, 500 simulations were carried out using the four parameter Kappa distribution. Based on this test, it has been observed that the data of 8 out of 11 bridge sites constitute ahomogeneous region. Hence, the data of these 8 sites have been used in this study. Catchment areas of these 8 sites vary from 32.89 to 447.76 km² and their mean annual peak floods varyfrom 24.29 to 555.21 m³ s^-1. Comparative regional floodfrequency analysis studies have been carried out using the various L-moments based frequency distributions viz. Extreme value (EV1), General extreme value (GEV), Logistic (LOS), Generalized logistic (GLO), Normal (NOR), Generalized normal (GNO), Uniform (UNF), Pearson Type-III (PE3), Exponential (EXP),Generalized Pareto (GPA), Kappa (KAP), and five parameter Wakeby(WAK). Based on the L-moment ratio diagram and Z _i ^dist –statistic criteria, GEV distribution has been identified as the robust distribution for the study area. For estimation of floods of various return periods for gauged catchments of the study area, regional flood frequency relationship has been developed using the L-moments based GEV distribution. Also, for estimation of floods of desiredreturn periods for ungauged catchments, regional flood frequencyrelationship has been developed by coupling the regional flood frequency relationship with the regional relationship between mean annual maximum peak flood and catchment area.     

Slackwater Sediments Record the Increase in Sub-daily Rain Flood due to Climate Change in a European Mediterranean Catchment

In this work we propose an original method to determine the magnitude of the discharge, the intensity of the precipitation and the duration of short-rain floods in small torrential basins (<?2000 km²), extending our earlier approach for long-rain floods in larger basins (Water 2016, 8, 526; Remote Sens. 2017, 9, 727). The studied areas are located in ungauged catchments with high erosion rates where torrents deposit slackwater sediments near the outlet of the basins. Such deposits and erosive morphologies allow us to analyse sub-daily extreme hydrological events by combining standard techniques in paleohydrology, the kinematic wave method and remote-sensed paleostage indicators. The formulation was correctly verified in extreme events through reliable gauge measurements and a high-resolution distributed hydrological model showing the accuracy of our calculations (10% ≤relative error ≤?22%). In catchments of the European Mediterranean region where the frequency and magnitude of short-rain floods are increasing (e.g. the Guadalquivir Basin), the main hydrological variables can thus be quantified post-event using the proposed approach. The outputs may serve to construct a new database for this kind of events complementary to the existing daily database for long-rain floods (>?24 h). The need is evident for safety designs of civil infrastructures and flood risk mitigation strategies in the current climate change scenario.

     

Regionalizing Flood Magnitudes using Landscape Structural Patterns of Catchments

Emerging as an important issue in the disciplines of landscape ecology and landscape hydrology which inspired it, defining the concept of landscape metrics in a hydrological context has become a challenge to both landscape planners and engineers. Accordingly, the present study addresses the relationships existing between flooding phenomena and landscape metrics (shape index, fractal dimension index, perimeter-area ratio, related circumscribing circle, and contiguity index) of land use/land cover, hydrological soil groups and geological permeability classes. A regionalization approach was adopted employing 39 select catchments (33—4800 km² in area, 0.47—21 m³ s^?1 in mean discharge), located within the southern basin of the Caspian Sea. These catchments were predominantly covered by forest (57.4%), while rangeland, farmland and urban areas accounted for 25.9%, 11.7%, and 1.6%, respectively. Class-level landscape structural metrics of land use/land cover, hydrological soil groups and geological permeability classes have then been served as inputs to stepwise multiple linear regression analysis in an attempt to explain the flood magnitudes. The regression models (0.69?≤?r² ≤?0.84) suggested that the catchments’ flood magnitude could explicitly be predicted using average measure of the shape and related circumscribing circle indices for the land use/land cover classes and those of hydrologic soil groups and geological permeability classes of the catchments. This indicated that regularity (vs. irregularity) of the landscape, pedoscape, and lithoscape, as represented by the shape index as well as the circumscribing circle index (for elongation and convolution), explained 69–84% of the variation in the flood magnitudes in the catchment.