A model for distributed GIUH‐based flow routing on natural and anthropogenic hillslopes

Attempts to reduce the number of parameters in distributed rainfall–runoff models have not yet resulted in a model that is accurate for both natural and anthropogenic hillslopes. We take on the challenge by proposing a distributed model for overland flow and channel flow based on a combination of a linear response time distribution and the hillslope geomorphologic instantaneous unit hydrograph (GIUH), which can be calculated with only a digital elevation model and a map with field boundaries and channel network as input. The spatial domain is subdivided into representative elementary hillslopes (REHs) for each of which we define geometric and flow velocity parameters and compute the GIUH. The catchment GIUH is given by the sum of all REH responses. While most distributed models only perform well on natural hillslopes, the advantage of our approach is that it can also be applied to modified hillslopes with for example a rectangular drainage network and terrace cultivation. Tests show that the REH‐GIUH approach performs better than classical routing functions (exponential and gamma). Simulations of four virtual hillslopes suggest that peak flow at the catchment outlet is directly related to drainage density. By combining the distributed flow routing model with a lumped‐parameter infiltration model, we were also able to demonstrate that terrace cultivation delays the response time and reduces peak flow in comparison to the same hillslope, but with a natural stream network. The REH‐GIUH approach is a first step in the process of coupling distributed hydrological models to erosion and water quality models at the REH (associated with agricultural management) and at the catchment scale (associated with the evaluation of the environmental impact of human activities). It furthermore provides a basis for the development of models for large catchments and urban or peri‐urban catchments. Copyright © 2013 John Wiley & Sons, Ltd.     

Perspectives in using a remotely sensed dryness index in distributed hydrological models at the river‐basin scale

In a previous study a spatially distributed hydrological model, based on the MIKE SHE code, was constructed and validated for the 375 000 km² Senegal River basin in West Africa. The model was constructed using spatial data on topography, soil types and vegetation characteristics together with time‐series of precipitation from 112 stations in the basin. The model was calibrated and validated based on river discharge data from nine stations in the basin for 11 years. Calibration and validation results suggested that the spatial resolution of the input data in parts of the area was not sufficient for a satisfactory evaluation of the modelling performance. The study further examined the spatial patterns in the model input and output, and it was found that particularly the spatial resolution of the precipitation input had a major impact on the model response. In an attempt to improve the model performance, this study examines a remotely sensed dryness index for its relationship to simulated soil moisture and evaporation for six days in the wet season 1990. The index is derived from observations of surface temperature and vegetation index as measured by the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor. The correlation results between the index and the simulation results are of mixed quality. A sensitivity analysis, conducted on both estimates, reveals significant uncertainties in both. The study suggests that the remotely sensed dryness index with its current use of NOAA AVHRR data does not offer information that leads to a better calibration or validation of the simulation model in a spatial sense. The method potentially may become more suitable with the use of the upcoming high‐resolution temporal Meteosat Second Generation data. Copyright © 2002 John Wiley & Sons, Ltd.     

Simulating saturation‐excess surface run‐off in a semi‐distributed hydrological model

The level of complexity, and the number of parameters, to include in a hydrological model is a relatively contentious issue in hydrological modelling. However, it can be argued that explicitly representing important run‐off generation processes can improve the practical value of a model's outputs. This paper explores the benefits of including a new function into an existing semi‐distributed hydrological model (the Pitman model) that is widely used in the sub‐Saharan Africa region. The new function was designed to represent saturation‐excess surface run‐off processes at subcatchment scales and was motivated by the evidence of dambo (low topography riparian areas) type features in many sub‐Saharan river basins. The results for uncertainty versions of the model, with and without the new function, were compared for 25 catchments, which were divided up into those where evidence of dambos exists and those where there is no such evidence. The results suggest that the new function certainly improves the model results for the catchments where dambos exist, but not in situations where saturation‐excess surface run‐off is not expected to occur. The overall conclusion is therefore that the addition of the new function is justified.     

Development of a distributed hydrological model to facilitate watershed management

To facilitate precise and cost-effective watershed management, a simple yet spatially and temporally distributed hydrological model (DHM-WM) was developed. The DHM-WM is based on the Mishra-Singh version of the curve number method, with several modifications: The spatial distribution of soil moisture was considered in moisture updating; the travel time of surface runoff was calculated on a grid cell basis for routing; a simple tile flow module was included as an option. The DHM-WM was tested on a tile-drained agricultural watershed in Indiana, USA. The model with the tile flow module performed well in the study area, providing a balanced water budget and reasonable flow partitioning. The daily coefficient of determination and Nash-Sutcliffe coefficient were 0.58 and 0.56, for the calibration period, and 0.63 and 0.62 for the validation period. The DHM-WM also provides detailed information about the source areas of flow components, the travel time and pathways of surface runoff.

EDITOR A. Castellarin; ASSOCIATE EDITOR F.-J. Chang     

Non‐stationary hydrological model parameters: a framework based on SOM‐B

The application of stationary parameters in conceptual hydrological models, even under changing boundary conditions, is a common yet unproven practice. This study investigates the impact of non‐stationary model parameters on model performance for different flow indices and time scales. Therefore, a Self‐Organizing Map based optimization approach, which links non‐stationary model parameters with climate indices, is presented and tested on seven meso‐scale catchments in northern Germany. The algorithm automatically groups sub‐periods with similar climate characteristics and allocates them to similar model parameter sets. The climate indices used for the classification of sub‐periods are based on (a) yearly means and (b) a moving average over the previous 61 days. Classification b supports the estimation of continuous non‐stationary parameters. The results show that (i) non‐stationary model parameters can improve the performance of hydrological models with an acceptable growth in parameter uncertainty; (ii) some model parameters are highly correlated to some climate indices; (iii) the model performance improves more for monthly means than yearly means; and (iv) in general low to medium flows improve more than high flows. It was further shown how the gained knowledge can be used to identify insufficiencies in the model structure. Copyright © 2015 John Wiley & Sons, Ltd.     

Sensitivity of soil parameters in unsaturated zone modelling and the relation between effective,laboratory and in situ estimates

Simulation of soil moisture content requires effective soil hydraulic parameters that are valid at the modelling scale. This study investigates how these parameters can be estimated by inverse modelling using soil moisture measurements at 25 locations at three different depths (at the surface, at 30 and 60 cm depth) on an 80 by 20 m hillslope. The study presents two global sensitivity analyses to investigate the sensitivity in simulated soil moisture content of the different hydraulic parameters used in a one‐dimensional unsaturated zone model based on Richards' equation. For estimation of the effective parameters the shuffled complex evolution algorithm is applied. These estimated parameters are compared to their measured laboratory and in situ equivalents. Soil hydraulic functions were estimated in the laboratory on 100 cm³ undisturbed soil cores collected at 115 locations situated in two horizons in three profile pits along the hillslope. Furthermore, in situ field saturated hydraulic conductivity was estimated at 120 locations using single‐ring pressure infiltrometer measurements. The sensitivity analysis of 13 soil physical parameters (saturated hydraulic conductivity (K_s), saturated moisture content (θ_s), residual moisture content (θ_r), inverse of the air‐entry value (α), van Genuchten shape parameter (n), Averjanov shape parameter (N) for both horizons, and depth (d) from surface to B horizon) in a two‐layer single column model showed that the parameter N is the least sensitive parameter. K_s of both horizons, θ_s of the A horizon and d were found to be the most sensitive parameters. Distributions over all locations of the effective parameters and the distributions of the estimated soil physical parameters from the undisturbed soil samples and the single‐ring pressure infiltrometer estimates were found significantly different at a 5% level for all parameters except for α of the A horizon and K_s and θ_s of the B horizon. Different reasons are discussed to explain these large differences. Copyright © 2004 John Wiley & Sons, Ltd.     

Year‐round estimation of soil moisture content using temporally variable soil hydraulic parameters

Soil moisture plays a key role in the hydrological cycle as it controls the flux of water between soil, vegetation, and atmosphere. This study is focused on a year‐round estimation of soil moisture in a forested mountain area using the bucket model approach. For this purpose, three different soil moisture models are utilised. The procedure is based on splitting the whole year into two complement periods (dormant and vegetation). Model parameters are allowed to vary between the two periods and also from year to year in the calibration procedure. Consequently, two sets of average model parameters corresponding to dormant and vegetation seasons are proposed. The process of splitting is strongly supported by the experimental data, and it enables us to variate saturated hydraulic conductivity and pore‐size characterisation. The use of the two different parameter sets significantly enhances the simulation of two (Teuling and Troch model and soil water balance model‐green–ampt [SWBM‐GA]) out of three models in the 6‐year period from 2009 to 2014. For these two models, the overall Nash‐Sutcliffe coefficient increased from 0.64 to 0.79 and from 0.55 to 0.80. The third model (the Laio approach) proved to be insensitive to parameter changes due to its insufficient drainage prediction. The variability of the warm and cold parameter sets between particular years is more pronounced in the warm periods. The cold periods exhibited approximately similar character during all 6 years.     

Application of semi‐distributed hydrological model for basin level water balance of the Ken basin of Central India

In the present study, a semi‐distributed hydrological model soil and water assessment tool (SWAT) has been employed for the Ken basin of Central India to predict the water balance. The entire basin was divided into ten sub basins comprising 107 hydrological response units on the basis of unique slope, soil and land cover classes using SWAT model. Sensitivity analysis of SWAT model was performed to examine the critical input variables of the study area. For Ken basin, curve number, available water capacity, soil depth, soil evaporation compensation factor and threshold depth of water in the shallow aquifer (GWQ_MN) were found to be the most sensitive parameters. Yearly and monthly calibration (1985–1996) and validation (1997–2009) were performed using the observed discharge data of the Banda site in the Ken basin. Performance evaluation of the model was carried out using coefficient of determination, Nash–Sutcliffe efficiency, root mean square error‐observations standard deviation ratio, percent bias and index of agreement criterion. It was found that SWAT model can be successfully applied for hydrological evaluation of the Ken basin, India. The water balance analysis was carried out to evaluate water balance of the Ken basin for 25 years (1985–2009). The water balance exhibited that the average annual rainfall in the Ken basin is about 1132 mm. In this, about 23% flows out as surface run‐off, 4% as groundwater flow and about 73% as evapotranspiration. Copyright © 2013 John Wiley & Sons, Ltd.     

Exploiting the use of physical information for the calibration of a lumped hydrological model

In hydrological modelling, the challenge is to identify an optimal strategy to exploit tools and available observations in order to enhance model reliability. The increasing availability of data promotes the use of new calibration techniques able to make use of additional information on river basins. In the present study, a lumped hydrological model—designed with the aim of utilizing remotely sensed data—is introduced and calibrated, adopting four different schemes that adopt, to varying extents, available physical information. The physically consistent conceptualization of the hydrological model used allowed development of a step by step calibration based on a combination of information, such as remotely sensed data describing snow cover, recession curves obtained from streamflow measurements, and time series of surface run‐off obtained with a baseflow mathematical filter applied to the streamflow time‐series. Results suggest that the use of physical information in the calibration procedure tends to increase model reliability with respect to approaches where the parameters are calibrated using an overall statistic based, considerably or exclusively, on streamflow data.     

Modelling the spatial variation in soil moisture at the landscape scale: an application to five areas of ecological interest in the UK

A simple conceptual hydrological model that explicitly includes the lateral movement of soil water and operates efficiently at the landscape scale is outlined. It is applied to five areas of ecological interest in the UK to provide distributed mean monthly soil moisture on a 50 m grid. As the model's driving variables—daily rainfall and potential evapotranspiration—are assumed constant over each of the tracts of land, the variability in soil moisture is due to different soil types and to topographic effects. Box plots of the mean monthly simulated soil moisture clearly show the spread of values occasioned by modelling the lateral water movement down the hillslope. The general magnitude of the results are compared with published data wherever possible and there is some discussion of the form of the curve used in the model to describe the attenuation of evapotranspiration with decreasing soil moisture. Copyright © 2000 John Wiley & Sons, Ltd.     

Alternative climate data sources for distributed hydrological modelling on a daily time step

Two major criteria in choosing climate data for use in hydrological modelling are the period of record of the data set and the proximity of the collection platform(s) to the basin under study. Conventional data sets are derived from weather stations; however, in many cases there are no weather stations sufficiently close to a basin to be representative of climate conditions in that basin. In addition, it is often the case either that the period of record for the weather station(s) does not cover the period of the proposed simulation or that there are gaps in the data. Therefore, the objectives of this study are to investigate alternative climate data sources for use in hydrological modelling and to develop a protocol for creating hydrological data sets that are spatially and temporally harmonized. The methods we used for constructing daily, spatially distributed, climatic data sets of precipitation, maximum and minimum temperature, wind speed, solar radiation, potential evapotranspiration, and relative humidity are described. The model used in this study was the Soil and Water Assessment Tool implemented on the Mimbres River Basin located in southwestern New Mexico, USA, for the period 2003–2006. Our hydrological simulations showed that two events in January and February 2005 were missed, while an event in August 2006 was well simulated. We have also investigated the usefulness of several other precipitation data sets and compared the simulation results. Copyright © 2010 John Wiley & Sons, Ltd.     

Observational and predictive uncertainties for multiple variables in a spatially distributed hydrological model

In this study, uncertainty in model input data (precipitation) and parameters is propagated through a physically based, spatially distributed hydrological model based on the MIKE SHE code. Precipitation uncertainty is accounted for using an ensemble of daily rainfall fields that incorporate four different sources of uncertainty, whereas parameter uncertainty is considered using Latin hypercube sampling. Model predictive uncertainty is assessed for multiple simulated hydrological variables (discharge, groundwater head, evapotranspiration, and soil moisture). Utilizing an extensive set of observational data, effective observational uncertainties for each hydrological variable are assessed. Considering not only model predictive uncertainty but also effective observational uncertainty leads to a notable increase in the number of instances, for which model simulation and observations are in good agreement (e.g., 47% vs. 91% for discharge and 0% vs. 98% for soil moisture). Effective observational uncertainty is in several cases larger than model predictive uncertainty. We conclude that the use of precipitation uncertainty with a realistic spatio‐temporal correlation structure, analyses of multiple variables with different spatial support, and the consideration of observational uncertainty are crucial for adequately evaluating the performance of physically based, spatially distributed hydrological models.     

Investigating the use of spatial discretization of hydrological processes in conceptual rainfall runoff modelling: a case study for the meso‐scale

In this study a simple modelling approach was applied to identify the need for spatial complexity in representing hydrological processes and their variability over different scales. A data set of 18 basins was used, ranging between 8 and 4011 km² in area, located in the Nahe basin (Germany), with daily discharge values for over 30 years. Two different parsimoniously structured models were applied in lumped as well as in spatially distributed according to two distribution classifications: (1) a simple classification based on the lithology expressed in three permeability types and (2) a more complex classification based on seven dominating runoff production processes. The objective of the study was to compare the performances of the models on a local and on a regional scale as well as between the models with a view to identifying the accuracy in capturing the spatial variability of the rainfall‐runoff relationships. It was shown that the presence of a specific basin characteristic or process of the distribution classification was not related with higher model performance; only a larger basin size promoted higher model performance. The results of this study also indicated that the permeability generally contained more useful information on the spatial heterogeneity of the hydrological behaviour of the natural system than did a more detailed classification on dominating runoff generation processes. Although model performance was slightly lower for the model that used permeability as a distribution classification, consistency in its parameter values was found, which was lacking with the more complex distribution classification. The latter distribution classification had a higher flexibility to optimize towards the variability of the runoff, which resulted in higher performance, however, process representation was applied inconsistently. Copyright © 2007 John Wiley & Sons, Ltd.     

Uncertainty quantization of meteorological input and model parameters for hydrological modelling using a Bayesian-based integrated approach

The traditional treatment of uncertainty in hydrological modelling primarily attributes it to model parameters, but rarely systematically considers meteorological input errors, especially in quantifying the impact of meteorological input errors on parameter uncertainty. This study developed a Bayesian-based integrated approach to quantitatively investigate uncertainties in meteorological inputs (precipitation and temperature) and model parameters as well as the variation in parameter uncertainty due to meteorological input errors. Additionally, we analysed the propagation from these uncertainties to runoff response in snowmelt and non-snowmelt periods. The applicability and advantages of this approach were presented by applying of the Soil and Water Assessment Tool to the Shitoukoumen Reservoir Catchment. Differential Evolution Adaptive Metropolis-Markov Chain Monte Carlo was applied for the straightforward Bayesian inference the uncertainties of meteorological inputs and model parameters. On this basis, multilevel factorial analysis technology was used to quantitatively investigate the specific impact of the model parameters' individual and interactive effects due to meteorological input errors. Finally, the impact of meteorological input errors and model parameter uncertainty on the model performance were analysed and quantified systematically. The results showed that the meteorological input errors could affect the random characteristics of multiple model parameters. Moreover, meteorological input errors could further affect the model parameters' effects on annual average runoff. Overall, the above results have significant implications in enhancing hydrological model to simulate/predict runoff and understanding hydrological processes during different periods.     

On the value of isotope-enabled hydrological model calibration

ABSTRACT

Calibration of hydrological models is challenging in high-latitude regions where hydrometric data are minimal. Process-based models are needed to predict future changes in water supply, yet often with high amounts of uncertainty, in part, from poor calibrations. We demonstrate the utility of stable isotopes (¹⁸O, ²H) as data employed for improving the amount and type of information available for model calibration using the isoWATFLOOD^TM model. We show that additional information added to calibration does not hurt model performance and can improve simulation of water volume. Isotope-enabled calibration improves long-term validation over traditional flow-only calibrated models and offers additional feedback on internal flowpaths and hydrological storages that can be useful for informing internal water distribution and model parameterization. The inclusion of isotope data in model calibration reduces the number of realistic parameter combinations, resulting in more constrained model parameter ranges and improved long-term simulation of large-scale water balance.     

Understanding the hydrological system dynamics of a glaciated alpine catchment in the Himalayan region using the J2000 hydrological model

This paper provides the results of hydrological modelling in a mesoscale glaciated alpine catchment of the Himalayan region. In the context of global climate change, the hydrological regime of an alpine mountain is likely to be affected, which might produce serious implications for downstream water availability. The main objective of this study was to understand the hydrological system dynamics of a glaciated catchment, the Dudh Kosi River basin, in Nepal, using the J2000 hydrological model and thereby understand how the rise in air temperature will affect the hydrological processes. The model is able to reproduce the overall hydrological dynamics quite well with an efficiency result of Nash–Sutcliffe (0.85), logarithm Nash–Sutcliffe (0.93) and coefficient of determination (0.85) for the study period. The average contribution from glacier areas to total streamflow is estimated to be 17%, and snowmelt (other than from glacier areas) accounts for another 17%. This indicates the significance of the snow and glacier runoff in the Himalayan region. The hypothetical rise in temperature scenarios at a rate of +2 and +4 °C indicated that the snowmelt process might be largely affected. An increase in snowmelt volume is noted during the premonsoon period, whereas the contribution during the monsoon season is significantly decreased. This occurs mainly because the rise in temperature will shift the snowline up to areas of higher altitude and thereby reduce the snow storage capacity of the basin. This indicates that the region is particularly vulnerable to global climate change and the associated risk of decreasing water availability to downstream areas. Under the assumed warming scenarios, it is likely that in the future, the river might shift from a ‘melt‐dominated river’ to a ‘rain‐dominated river’. The J2000 model should be considered a promising tool to better understand the hydrological dynamics in alpine mountain catchments of the Himalayan region. This understanding will be quite useful for further analysis of ‘what‐if scenarios’ in the context of global climate and land‐use changes and ultimately for sustainable Integrated Water Resources Management in the Himalayan region. Copyright © 2012 John Wiley & Sons, Ltd.     

Lumped parameter sensitivity analysis of a distributed hydrological model within tropical and temperate catchments

Parameter sensitivity of the Distributed Hydrology‐Soil‐Vegetation Model (DHSVM) was studied in two contrasting environments: (1) Pang Khum Experimental Watershed (PKEW) in tropical northern Thailand; and (2) Cedar River basin (CRB) in Washington State of the temperate US Pacific Northwest. The analysis shows that for both basins, the most sensitive soil parameters were porosity, lateral saturated hydraulic conductivity, and the exponential decrease rate of lateral saturated hydraulic conductivity with soil depth. The most sensitive vegetation parameters were leaf area index, vegetation height, vapour pressure deficit, minimum stomatal resistance (for both grassland and forest scenarios), hemisphere fractional coverage, overstory fractional coverage, and trunk space (for the forest scenario only). Parameter sensitivity was basin‐specific, with the humid, temperate CRB being more influenced by vegetation parameters, while tropical PKEW was more influenced by soil properties. Increases and decreases in parameter values resulted in opposite and unequal changes in bias and root mean square error (RMSE), indicating the non‐linearity of physical process represented in the hydrological model. Copyright © 2011 John Wiley & Sons, Ltd.     

Semi‐distributed flood runoff model at the subcontinental scale for southwestern Iran

Rainfall–runoff modelling, as a surface hydrological process, on large‐scale data‐poor basins is currently a major topic of investigation that requires the model parameters be identified by using basin physical characteristics rather than calibration. This paper describes the application of the TOPMODEL framework accompanied by a kinematic wave model to the Karun River sub‐basins in southwestern Iran with just one conceptual parameter for calibration. ISLSCP1, HYDRO1K and Reynolds data sets are presented in a geographical information system and used as data sources for meteorological information, hydrological features and soil characteristics of the study area respectively. The results show that although the model developed can adequately predict flood runoff in the catchment with only one calibrated parameter, it is suggested that the effect of surface reservoirs be considered in the proposed model. Copyright © 2007 John Wiley & Sons, Ltd.     

Assessment on the function of reservoirs for flood control during typhoon seasons based on a distributed hydrological model

A grid‐based distributed hydrological model, PDTank model, is used to simulate hydrological processes in the upper Tone River catchment. The Tone River catchment often suffers from heavy rainfall events during the typhoon seasons. The reservoirs located in the catchment play an important role in flood regulation. Through the coupling of the PDTank model and a reservoir module that combines the storage function and operation function, the PDTank model is used for flood forecasting in this study. By comparing the hydrographs simulated using gauging and radar rainfall data, it is found that the spatial variability of rainfall is an important factor for flood simulation and the accuracy of the hydrographs simulated using radar rainfall data is slightly improved. The simulation of the typhoon flood event numbered No. 9 shows that the reservoirs in the catchment attenuate the peak flood discharge by 423·3 m³/s and validates the potential applicability of the distributed hydrological model on the assessment of function of reservoirs for flood control during typhoon seasons. Copyright © 2011 John Wiley & Sons, Ltd.