Estimating source regions for snowmelt runoff in a Rocky Mountain basin: tests of a data‐based conceptual modeling approach

In many mountain basins, river discharge measurements are located far away from runoff source areas. This study tests whether a basic snowmelt runoff conceptual model can be used to estimate relative contributions of different elevation zones to basin‐scale discharge in the Cache la Poudre, a snowmelt‐dominated Rocky Mountain river. Model tests evaluate scenarios that vary model configuration, input variables, and parameter values to determine how these factors affect discharge simulation and the distribution of runoff generation with elevation. Results show that the model simulates basin discharge well (NSCE and R >0.90) when input precipitation and temperature are distributed with different lapse rates, with a rain‐snow threshold parameter between 0 and 3.3 °C, and with a melt rate parameter between 2 and 4 mm °C^?1 d^?1 because these variables and parameters can have compensating interactions with each other and with the runoff coefficient parameter. Only the hydrograph recession parameter can be uniquely defined with this model structure. These non‐unique model scenarios with different configurations, input variables, and parameter values all indicate that the majority of basin discharge comes from elevations above 2900 m, or less than 25% of the basin total area, with a steep increase in runoff generation above 2600 m. However, the simulations produce unrealistically low runoff ratios for elevations above 3000 m, highlighting the need for additional measurements of snow and discharge at under‐sampled elevations to evaluate the accuracy of simulated snow and runoff patterns. Copyright © 2013 John Wiley & Sons, Ltd.     

Geospatially based distributed rainfall‐runoff modelling for simulation of internal and outlet responses in a semi‐forested lower Himalayan watershed

This study presents a Geographic Information System (GIS)‐based distributed rainfall‐runoff model for simulating surface flows in small to large watersheds during isolated storm events. The model takes into account the amount of interception storage to be filled using a modified Merriam ( 1960 ) approach before estimating infiltration by the Smith and Parlange ( 1978 ) method. The mechanics of overland and channel flow are modelled by the kinematic wave approximation of the Saint Venant equations which are then numerically solved by the weighted four‐point implicit finite difference method. In this modelling the watershed was discretized into overland planes and channels using the algorithms proposed by Garbrecht and Martz ( 1999 ). The model code was first validated by comparing the model output with an analytical solution for a hypothetical plane. Then the model was tested in a medium‐sized semi‐forested watershed of Pathri Rao located in the Shivalik ranges of the Garhwal Himalayas, India. Initially, a local sensitivity analysis was performed to identify the parameters to which the model outputs like runoff volume, peak flow and time to peak flow are sensitive. Before going for model validation, calibration was performed using the Ordered‐Physics‐based Parameter Adjustment (OPPA) method. The proposed Physically Based Distributed (PBD) model was then evaluated both at the watershed outlet as well as at the internal gauging station, making this study a first of its kind in Indian watersheds. The results of performance evaluation indicate that the model has simulated the runoff hydrographs reasonably well within the watershed as well as at the watershed outlet with the same set of calibrated parameters. The model also simulates, realistically, the temporal variation of the spatial distribution of runoff over the watershed and the same has been illustrated graphically. Copyright © 2011 John Wiley & Sons, Ltd.     

The hydrological behaviour of urban streets: long‐term observations and modelling of runoff losses and rainfall–runoff transformation

Runoff on impervious surfaces (roads, roofs, etc.) raises a number of environmental and road safety‐related problems. The primary objective of this research effort is to improve our knowledge of the hydrological behaviour of impervious urban surfaces in order to better assess runoff on these surfaces and its subsequent consequences. This article will focus on two street stretches studied over a 38‐month period. Measurements of rainfall and runoff discharge on these stretches have made it possible to estimate runoff losses as well as to constitute a database for modelling purposes. On the basis of these data, two models have been used, one simple the other more detailed and physically based. For both models, runoff discharges at a 3‐min time step are well reproduced, although runoff coefficients and runoff losses are still poorly estimated. Detailed analyses of experimental data and model output, however, indicate that runoff losses could be quite high on such ‘impervious surfaces’ (between 30 and 40% of total rainfall, depending on the street stretch) and that these losses are mainly because of evaporation and infiltration inside the road structure. Copyright © 2011 John Wiley & Sons, Ltd.     

One‐ and two‐dimensional modelling of overland flow in semiarid shrubland,Jornada basin,New Mexico

Two distributed parameter models, a one‐dimensional (1D) model and a two‐dimensional (2D) model, are developed to simulate overland flow in two small semiarid shrubland watersheds in the Jornada basin, southern New Mexico. The models are event‐based and represent each watershed by an array of 1‐m² cells, in which the cell size is approximately equal to the average area of the shrubs. Each model uses only six parameters, for which values are obtained from field surveys and rainfall simulation experiments. In the 1D model, flow volumes through a fixed network are computed by a simple finite‐difference solution to the 1D kinematic wave equation. In the 2D model, flow directions and volumes are computed by a second‐order predictor–corrector finite‐difference solution to the 2D kinematic wave equation, in which flow routing is implicit and may vary in response to flow conditions. The models are compared in terms of the runoff hydrograph and the spatial distribution of runoff. The simulation results suggest that both the 1D and the 2D models have much to offer as tools for the large‐scale study of overland flow. Because it is based on a fixed flow network, the 1D model is better suited to the study of runoff due to individual rainfall events, whereas the 2D model may, with further development, be used to study both runoff and erosion during multiple rainfall events in which the dynamic nature of the terrain becomes an important consideration. Copyright © 2006 John Wiley & Sons, Ltd.     

Rainfall‐runoff modelling using artificial neural networks: comparison of network types

Growing interest in the use of artificial neural networks (ANNs) in rainfall‐runoff modelling has suggested certain issues that are still not addressed properly. One such concern is the use of network type, as theoretical studies on a multi‐layer perceptron (MLP) with a sigmoid transfer function enlightens certain limitations for its use. Alternatively, there is a strong belief in the general ANN user community that a radial basis function (RBF) network performs better than an MLP, as the former bases its nonlinearities on the training data set. This argument is not yet substantiated by applications in hydrology. This paper presents a comprehensive evaluation of the performance of MLP‐ and RBF‐type neural network models developed for rainfall‐runoff modelling of two Indian river basins. The performance of both the MLP and RBF network models were comprehensively evaluated in terms of their generalization properties, predicted hydrograph characteristics, and predictive uncertainty. The results of the study indicate that the choice of the network type certainly has an impact on the model prediction accuracy. The study suggests that both the networks have merits and limitations. For instance, the MLP requires a long trial‐and‐error procedure to fix the optimal number of hidden nodes, whereas for an RBF the structure of the network can be fixed using an appropriate training algorithm. However, a judgment on which is superior is not clearly possible from this study. Copyright © 2004 John Wiley & Sons, Ltd.     

Macroscale hydrological modelling approach for study of large scale hydrologic impacts under climate change in Indian river basins

In climate‐change studies, a macroscale hydrologic model (MHM) operating over large scales can be an important tool in developing consistent hydrological variability estimates over large basins. MHMs, which can operate at coarse grid resolutions of about 1° latitude by longitude, have been used previously to study climate change impacts on the hydrology of continental scale or global river basins. They can provide a connection between global atmospheric models and water resource systems on large spatial scales and long timescales. In this study, the variable infiltration capacity (VIC) MHM is used to study large scale hydrologic impacts of climate change for Indian river basins. Large‐scale changes in runoff, evapotranspiration and soil moisture for India, as well as station‐scale changes in discharges for three major river basins with distinct climatic and geographic characteristics are examined in this study. Climate model projections for meteorological variables (precipitation, temperature and wind speed) from three general circulation models (GCMs) and three emissions scenarios are used to drive the VIC MHM. GCM projections are first interpolated to a 1° by 1° hydrologic model grid and then bias‐corrected using a quantile–quantile mapping. The VIC model is able to reproduce observed statistics for discharges in the Ganga, Narmada and Krishna basins reasonably well, even at the coarse grid resolution employed using a calibration period for years 1965–1970 and testing period from 1971–1973/1974. An increasing trend is projected for summer monsoon surface runoff, evapotranspiration and soil moisture in most central Indian river basins, whereas a decrease in runoff and soil moisture is projected for some regions in southern India, with important differences arising from GCM and scenario variability. Discharge statistics show increases in mid‐flow and low flow at Farakka station on Ganga River, increased high flows at Jamtara station upstream of Narmada, and increased high, mid‐flow and low flow for Vijayawada station on Krishna River in the future. Copyright © 2013 John Wiley & Sons, Ltd.     

Tritium balance in macro‐scale river basins analysed through distributed hydrological modelling

The recession of bomb tritium in river discharge of large basins indicates a contribution of slowly moving water. For an appropriate interpretation it is necessary to consider different runoff components (e.g. direct runoff and ground water components) and varying residence times of tritium in these components. The spatially distributed catchment model (tracer aided catchment model, distributed; TAC^D) and a tritium balance model (TRIBIL) were combined to model process‐based tritium balances in a large German river basin (Weser 46 240 km²) and seven embedded sub‐basins. The hydrological model (monthly time step, 2 × 2 km²) estimated the three major runoff components: direct runoff, fast‐moving and slow‐moving ground water for the period of 1950 to 1999. The model incorporated topography, land use, geomorphology, geology and hydro‐meteorological data. The results for the different basins indicated a contribution of direct runoff of 30–50% and varying amounts for fast and slow ground water components. Combining these results with the TRIBIL model allowed us to estimate the residence time of the components. Mean residence times of 8 to 14 years were found for the fast ground water component, 21 to 93 years for the slow ground water component and 14 to 50 years for an overall mean residence time within these basins. Balance calculations for the Weser basin indicate an over‐estimation of loss of tritium through evapotranspiration (more than 60%) and decay (10%). About 28% were carried in stream‐flow where direct runoff contributed about 12% and ground water runoff 13% in relation to precipitation input over the studied 50‐year period. Neighbouring basins and nuclear power plants contributed about 1% each over this time period. Copyright © 2007 John Wiley & Sons, Ltd.     

基于微分响应的流域产流分单元修正方法

为考虑洪水预报误差的空间变化,提出一种基于微分响应的流域产流分单元修正方法.该方法建立了各单元流域产流与流域出口流量之间的微分响应关系,采用正则化最小二乘法结合逐步迫近进行反演求解,将产流误差估计量分配给相应单元流域实现流域产流分单元修正.将构建的方法应用于大坡岭流域和七里街流域进行新安江模型产流修正,比较分析了流域产流分单元修正、流域面平均产流修正和自回归修正的效果.结果表明：流域产流分单元修正效果优于流域面平均产流修正;随着预见期的增大,产流微分响应修正效果优于自回归修正.该方法通过汇流系统将流域出口断面流量信息进行分解用于修正各单元流域产流,有利于提高实时洪水预报精度.     

Selecting best mapping strategies for storm runoff modeling in a mountainous semi‐arid area

Accurate runoff and soil erosion modeling is constrained by data availability, particularly for physically based models such as OpenLISEM that are data demanding, as the processes are calculated on a cell‐by‐cell basis. The first decision when using such models is to select mapping units that best reflect the spatial variability of the soil and hydraulic properties in the catchment. In environments with limited data, available maps are usually generic, with large units that may lump together the values of the soil properties, affecting the spatial patterns of the predictions and output values in the outlet. Conversely, the output results may be equally acceptable, following the principle of equifinality. To studyhow the mapping method selected affects the model outputs, four types of input maps with different degrees of complexity were created: average values allocated to general soil map units (ASG1), average values allocated to detailed map units (ASG2), values interpolated by ordinary kriging (OK) and interpolated by kriging with external drift (KED). The study area was Ribeira Seca, a 90 km² catchment located in Santiago Island, Cape Verde (West Africa), a semi‐arid country subject to scarce but extreme rainfall during the short tropical summer monsoon. To evaluate the influence of rainfall on runoff and erosion, two storm events with different intensity and duration were considered. OK and KED inputs produced similar results, with the latter being closer to the observed hydrographs. The highest soil losses were obtained with KED (43 ton ha^{? 1} for the strongest event). To improve the results of soil loss predictions, higher accurate spatial information on the processes is needed; however, spatial information of input soil properties alone is not enough in complex landscapes. The results demonstrate the importance of selecting the appropriate mapping strategy to obtain reliable runoff and erosion estimates. Copyright © 2013 John Wiley & Sons, Ltd.     

Season‐based rainfall–runoff modelling using the probability‐distributed model (PDM) for large basins in southeastern Brazil

Southeastern Brazil is characterized by seasonal rainfall variability. This can have a great social, economic, and environmental impact due to both excessive and deficient water availability. During 2014 and 2015, the region experienced one of the most severe droughts since 1960. The resulting water crisis has seriously affected water supply to the metropolitan region of São Paulo and hydroelectric power generation throughout the entire country. This research considered the upstream basins of the southeastern Brazilian reservoirs Cantareira (2,279 km²; water supply) and Emborcação (29,076 km²), Três Marias (51,576 km²), Furnas (52,197 km²), and Mascarenhas (71,649 km²; hydropower) for hydrological modelling. It made the first attempt at configuring a season‐based probability‐distributed model (PDM‐CEMADEN) for simulating different hydrological processes during wet and dry seasons. The model successfully reproduced the intra‐annual and interannual variability of the upstream inflows during 1985–2015. The performance of the model was very satisfactory not only during the wet, dry, and transitional seasons separately but also during the whole period. The best performance was obtained for the upstream basin of Furnas, as it had the highest quality daily precipitation and potential evapotranspiration data. The Nash–Sutcliffe efficiency and logarithmic Nash–Sutcliffe efficiency were 0.92 and 0.93 for the calibration period 1984–2001, 0.87 and 0.88 for the validation period 2001–2010, and 0.93 and 0.90 for the validation period 2010–2015, respectively. Results indicated that during the wet season, the upstream basins have a larger capacity and variation of soil water storage, a larger soil water conductivity, and quicker surface water flow than during the dry season. The added complexity of configuring a season‐based PDM‐CEMADEN relative to the traditional model is well justified by its capacity to better reproduce initial conditions for hydrological forecasting and prediction. The PDM‐CEMADEN is a simple, efficient, and easy‐to‐use model, and it will facilitate early decision making and implement adaptation measures relating to disaster prevention for reservoirs with large‐sized upstream basins.     

Temporal trends of hydro‐climatic variables and runoff response to climatic variability and vegetation changes in the Yiluo River basin,China

The Yiluo River is the largest tributary for the middle and lower reaches of the Yellow River below Sanmenxia Dam. Changes of the hydrological processes in the Yiluo River basin, influenced by the climatic variability and human activities, can directly affect ecological integrity in the lower reach of the Yellow River. Understanding the impact of the climatic variability and human activities on the hydrological processes in the Yiluo River basin is especially important to maintain the ecosystem integrity and sustain the society development in the lower reach of the Yellow River basin. In this study, the temporal trends of annual precipitation, air temperature, reference evapotranspiration (ET₀) and runoff during 1961–2000 in the Yiluo River basin were explored by the Mann‐Kendall method (M‐K method), Yamamoto method and linear fitted model. The impacts of the climatic variability and vegetation changes on the annual runoff were discussed by the empirical model and simple water balance model and their contribution to change of annual runoff have been estimated. Results indicated that (i) significant upwards trend for air temperature and significant downwards trend both for precipitation and ET₀ were detected by the M‐K method at 95% confidence level. And the consistent trends were obtained by the linear fitted model; (ii) the abrupt change started from 1987 detected by the M‐K method and Yamamoto method, and so the annual runoff during 1961–2000 was divided into two periods: baseline period (1961–1986) and changeable period (1987–2000); and (iii) the vegetation changes were the main cause for change of annual runoff from baseline period to changeable period, and climatic variability contributed a little to the change of annual runoff of the Yiluo River. Copyright © 2009 John Wiley & Sons, Ltd.     

Distributed rainfall‐runoff modelling for flood frequency estimation and flood forecasting

Nowadays, in the scientific literature many rainfall‐runoff (RR) models are available ranging from simpler ones, with a limited number of parameters, to highly complex ones, with many parameters. Therefore, the selection of the best structure and parameterisation for a model is not straightforward as it is dependent on a number of factors: climatic conditions, catchment characteristics, temporal and spatial resolution, model objectives, etc. In this study, the structure of a continuous semi‐distributed RR model, named MISDc (‘Modello Idrologico Semi‐Distribuito in continuo’) developed for flood simulation in the Upper Tiber River (central Italy) is presented. Most notably, the methodology employed to detect the more relevant processes involved in the modelling of high floods, and hence, to build the model structure and its parameters, is developed. For this purpose, an intense activity of monitoring soil moisture and runoff in experimental catchments was carried out allowing to derive a parsimonious and reliable continuous RR model operating at an hourly (or smaller) time scale. Specifically, in order to determine the catchment hydrological response, the important role of the antecedent wetness conditions is emphasized. The application of MISDc both for design flood estimation and for flood forecasting is reported here demonstrating its reliability and also its computational efficiency, another important factor in hydrological practice. As far as the flood forecasting applications are concerned, only the accuracy of the model in reproducing discharge hydrographs by assuming rainfall correctly known throughout the event is investigated indepth. In particular, the MISDc has been implemented in the framework of Civil Protection activities for the Upper Tiber River basin. Copyright © 2011 John Wiley & Sons, Ltd.     

Simulating pan‐Arctic runoff with a macro‐scale terrestrial water balance model

A terrestrial hydrological model, developed to simulate the high‐latitude water cycle, is described, along with comparisons with observed data across the pan‐Arctic drainage basin. Gridded fields of plant rooting depth, soil characteristics (texture, organic content), vegetation, and daily time series of precipitation and air temperature provide the primary inputs used to derive simulated runoff at a grid resolution of 25 km across the pan‐Arctic. The pan‐Arctic water balance model (P/WBM) includes a simple scheme for simulating daily changes in soil frozen and liquid water amounts, with the thaw–freeze model (TFM) driven by air temperature, modelled soil moisture content, and physiographic data. Climate time series (precipitation and air temperature) are from the National Centers for Environmental Prediction (NCEP) reanalysis project for the period 1980–2001. P/WBM‐generated maximum summer active‐layer thickness estimates differ from a set of observed data by an average of 12 cm at 27 sites in Alaska, with many of the differences within the variability (1σ) seen in field samples. Simulated long‐term annual runoffs are in the range 100 to 400 mm year^?1. The highest runoffs are found across northeastern Canada, southern Alaska, and Norway, and lower estimates are noted along the highest latitudes of the terrestrial Arctic in North America and Asia. Good agreement exists between simulated and observed long‐term seasonal (winter, spring, summer–fall) runoff to the ten Arctic sea basins (r = 0·84). Model water budgets are most sensitive to changes in precipitation and air temperature, whereas less affect is noted when other model parameters are altered. Increasing daily precipitation by 25% amplifies annual runoff by 50 to 80% for the largest Arctic drainage basins. Ignoring soil ice by eliminating the TFM sub‐model leads to runoffs that are 7 to 27% lower than the control run. The results of these model sensitivity experiments, along with other uncertainties in both observed validation data and model inputs, emphasize the need to develop improved spatial data sets of key geophysical quantities (particularly climate time series) to estimate terrestrial Arctic hydrological budgets better. Copyright © 2003 John Wiley & Sons, Ltd.     

Effects of the catchment runoff coefficient on the performance of TOPMODEL in rainfall–runoff modelling

Effects of the catchment runoff coefficient on the performance of TOPMODEL in simulating catchment rainfall–runoff relationships are investigated in this paper, with an aim to improve TOPMODEL's simulation efficiency in catchments with a low runoff coefficient. Application of TOPMODEL in the semi‐arid Yihe catchment, with an area of 2623 km² in the Yellow River basin of China, produced a Nash–Sutcliffe model efficiency of about 80%. To investigate how the catchment runoff coefficient affects the performance of TOPMODEL, the whole observed discharge series of the Yihe catchment is multiplied with a larger‐than‐unity scale factor to obtain an amplified discharge series. Then TOPMODEL is used to simulate the amplified discharge series given the original rainfall and evaporation data. For a set of different scale factors, TOPMODEL efficiency is plotted against the corresponding catchment runoff coefficient and it is found that the efficiency of TOPMODEL increases with the increasing catchment runoff coefficient before reaching a peak (e.g. about 90%); after the peak, however, the efficiency of TOPMODEL decreases with the increasing catchment runoff coefficient. Based on this finding, an approach called the discharge amplification method is proposed to enhance the simulation efficiency of TOPMODEL in rainfall–runoff modelling in catchments with a low runoff coefficient. Copyright © 2004 John Wiley & Sons, Ltd.     

Multiple modes of storm runoff generation in a North Carolina coastal plain watershed

The results of field measurements conducted in a small (19·37 ha) agricultural watershed on the North Carolina coastal plain during the summer of 1996 are presented. The objective of the study was to develop a more complete understanding of basin response in the region with respect to stormflow generation and, in particular, to identify the processes that determine storm runoff and the conditions under which such processes occur. Twenty‐four storm events were monitored, including two tropical storm systems and two hurricanes. The data demonstrate considerable spatial and temporal heterogeneity in runoff generation within the watershed. Surface flowpaths, in the form of Hortonian overland flow and saturation overland flow, were found to be the dominant runoff processes during the storm events measured. The hillslope flowpaths had the same response time as the basin streamflow, but significantly shorter time of rise and lag times. The importance of Hortonian flow in a basin with sandy, permeable soils, as well as the rapid stormflow response in a low‐relief area with a humid climate, was contrary to expectations. This, coupled with the contingency of runoff response, suggests that it may be difficult to generalize about runoff generation mechanisms in broad terms, and that a synoptic approach may be more appropriate. Copyright © 2006 John Wiley & Sons, Ltd.     

A rainfall‐runoff model parameterized from GIS and runoff data

A guiding principle in hydrological modelling should be to keep the number of calibration parameters to a minimum. A reduced number of parameters to be calibrated, while maintaining the accuracy and detail required by modern hydrological models, will reduce parameter and model structure uncertainty and improve model diagnostics. In this study, the dynamics of runoff are derived from the distribution of distances from points in the catchments to the nearest stream. This distribution is unique for each catchment and can be determined from a geographical information system. The distribution of distances, will, when a celerity of (subsurface) flow is introduced, provide a distribution of travel times, or a unit hydrograph (UH). For spatially varying levels of saturation deficit, we have different celerities and, hence, different UHs. Runoff is derived from the superposition of the different UHs. This study shows how celerities can be estimated if we assume that recession events represent the combined UHs for different levels of saturation deficit. A new soil moisture routine which estimates saturated and unsaturated volumes of subsurface water and with only one parameter to calibrate is included in the new model. The performance of the new model is compared with that of the Swedish HBV model and is found to perform equally well for eight Norwegian catchments although the number of parameters to be calibrated in the module concerning soil moisture and runoff dynamics is reduced from seven in the HBV model to one in the new model. It is also shown that the new model has a more realistic representation of the subsurface hydrology. Copyright © 2013 John Wiley & Sons, Ltd.     

Green‐Ampt Curve‐Number mixed procedure as an empirical tool for rainfall–runoff modelling in small and ungauged basins

The Soil Conservation Service Curve Number (SCS‐CN) method is a popular rainfall–runoff model that is widely used to estimate direct runoff from small and ungauged basins. The SCS‐CN is a simple and valuable approach to quantify the total streamflow volume generated by storm rainfall, but its use is not appropriate for estimating the sub‐daily incremental rainfall excess. To overcome this drawback, we propose to include the Green‐Ampt (GA) infiltration model into a mixed procedure, which is referred to as Curve Number for Green‐Ampt (CN4GA), aiming to distribute in time the information provided by the SCS‐CN method. For a given storm, the computed SCS‐CN total net rainfall amount is employed to calibrate the soil hydraulic conductivity parameter of the GA model. The proposed procedure is evaluated by analysing 100 rainfall–runoff events that were observed in four small catchments of varying size. CN4GA appears to provide encouraging results for predicting the net rainfall peak and duration values and has shown, at least for the test cases considered in this study, better agreement with the observed hydrographs than the classic SCS‐CN method. Copyright © 2012 John Wiley & Sons, Ltd.