Special Section on Ecohydrology—Editorial

Abstract

This paper makes use of a water balance study of a mountainous area with a wide range of average annual rainfall in an arid and semiarid region to illustrate the development of both a statistical model of daily rainfall and a rainfall-runoff model. The models are appropriate for these conditions and may be relevant to similar areas. Comparisons of mean rainfall and runoff at the arid end of the scale suggest that runoff coefficients do not conform to common assumptions.     

Application of the Takagi–Sugeno fuzzy system for combination forecasting of river flow in semiarid mountain regions

Because of high spatial heterogeneity and the degree of uncertainty about hydrological processes in large‐scale catchments of semiarid mountain areas, satisfactory forecasting of daily discharge is seldom available using a single model in many practical cases. In this paper the Takagi–Sugeno fuzzy system (TS) and the simple average method (SAM) are applied to combine forecasts of three individual models, namely, the simple linear model (SLM), the seasonally based linear perturbation model (LPM) and the nearest neighbour linear perturbation model (NNLPM) for modelling daily discharge, and the performance of modelling results is compared in five catchments of semiarid areas. It is found that the TS combination model gives good predictions. The results confirm that better prediction accuracy can be obtained by combining the forecasts of different models with the Takagi–Sugeno fuzzy system in semi‐arid mountain areas. Copyright © 2009 John Wiley & Sons, Ltd.     

Stability of model performance and parameter values on two catchments facing changes in climatic conditions

Abstract

Hydrological models are often used for studying the hydrological effects of climate change; however, the stability of model performance and parameter values under changing climate conditions has seldom been evaluated and compared. In this study, three widely-used rainfall–runoff models, namely the SimHYD model, the HBV model and the Xin’anjiang model, are evaluated on two catchments subject to changing climate conditions. Evaluation is carried out with respect to the stability in their performance and parameter values in different calibration periods. The results show that (a) stability of model performance and parameter values depends on model structure as well as the climate of catchments, and the models with higher performance scores are more stable in changing conditions; (b) all the tested models perform better on a humid catchment than on an arid catchment; (c) parameter values are also more stable on a humid catchment than on an arid catchment; and (d) the differences in stability among models are somewhat larger in terms of model efficiency than in model parameter values.     

Simulating temporal variability in catchment response using a monthly rainfall–runoff model

Abstract

Temporal variability can result from shifts in climate, or from changes in the runoff response due to land- or water-use changes, and represents a potential source of uncertainty in calibrating hydrological models. Parameter values were determined using Monte Carlo parameter sampling methods for a monthly rainfall–runoff model (Pitman model) for different sub-periods on four catchments, with different types and degrees of temporal variability, in Australia and Africa. For some catchments, parameters were not dependent upon the sub-period used and fell within expected ranges given the relatively high degree of model equifinality. In other catchments, dependencies can be identified that are associated with signals contained within the sub-periods. While the Pitman model is relatively robust in the face of temporal variability, it is concluded that better simulations will always be obtained from calibration data that include signals representing the total variability in climate, land-use change and catchment responses.     

Spatial disaggregation and intensity correction of TRMM-based rainfall time series for hydrological applications in dryland catchments

Abstract

A novel approach is presented for combining spatial and temporal detail from newly available TRMM-based data sets to derive hourly rainfall intensities at 1-km spatial resolution for hydrological modelling applications. Time series of rainfall intensities derived from 3-hourly 0.25° TRMM 3B42 data are merged with a 1-km gridded rainfall climatology based on TRMM 2B31 data to account for the sub-grid spatial distribution of rainfall intensities within coarse-scale 0.25° grid cells. The method is implemented for two dryland catchments in Tunisia and Senegal, and validated against gauge data. The outcomes of the validation show that the spatially disaggregated and intensity corrected TRMM time series more closely approximate ground-based measurements than non-corrected data. The method introduced here enables the generation of rainfall intensity time series with realistic temporal and spatial detail for dynamic modelling of runoff and infiltration processes that are especially important to water resource management in arid regions.

Editor D. Koutsoyiannis

Citation Tarnavsky, E., Mulligan, M. and Husak, G., 2012. Spatial disaggregation and intensity correction of TRMM-based rainfall time series for hydrological applications in dryland catchments. Hydrological Sciences Journal, 57 (2), 248–264.     

Water balance estimation under the challenge of data scarcity in a hyperarid to Mediterranean region

Water budget analyses are important for the evaluation of the water resources in semiarid and arid regions. The lack of observed data is the major obstacle for hydrological modelling in arid regions. The aim of this study is the analysis and calculation of the natural water resources of the Western Dead Sea subsurface catchment, one which is highly sensitive to rainfall resulting in highly variable temporal and spatial groundwater recharge. We focus on the subsurface catchment and subsequently apply the findings to a large‐scale groundwater flow model to estimate the groundwater discharge to the Dead Sea. We apply a semidistributed hydrological model (J2000g), originally developed for the Mediterranean, to the hyperarid region of the Western Dead Sea catchment, where runoff data and meteorological records are sparsely available. The challenge is to simulate the water budget, where the localized nature of extreme rainstorms together with sparse runoff data results in few observed runoff and recharge events. To overcome the scarcity of climate input data, we enhance the database with mean monthly rainfall data. The rainfall data of 2 satellites are shown to be unsuitable to fill the missing rainfall data due to underrepresentation of the steep hydrological gradient and temporal resolution. Hydrological models need to be calibrated against measured values; hence, the absence of adequate data can be problematic. Therefore, our calibration approach is based on a nested strategy of diverse observations. We calculate a direct surface runoff of the Western Dead Sea surface area (1,801 km²) of 3.4 mm/a and an average recharge (36.7 mm/a) for the 3,816 km² subsurface drainage basin of the Cretaceous aquifer system.     

Temporal patterns and controls on runoff magnitude and solution chemistry of urban catchments in the semiarid southwestern United States

Urban expansion and the scarcity of water supplies in arid and semiarid regions have increased the importance of urban runoff to localized water resources. However, urban catchment responses to precipitation are poorly understood in semiarid regions where intense rainfall often results in large runoff events during the short summer monsoon season. To evaluate how urban runoff quantity and quality respond to rainfall magnitude and timing, we collected stream stage data and runoff samples throughout the 2007 and 2008 summer monsoons from four ephemeral drainages in Tucson, Arizona. Antecedent rainfall explained 20% to 30% of discharge (mm) and runoff ratio in the least impervious (22%) catchment but was not statistically related to hydrologic responses at more impervious sites. Regression models indicated that rainfall depth, imperviousness and their combined effect control discharge and runoff ratios (p < 0.01, r² = 0.91 and 0.75, respectively). In contrast, runoff quality did not vary with imperviousness or catchment size. Rainfall depth and duration, time since antecedent rainfall and event and cumulative discharge controlled runoff hydrochemistry and resulted in five specific solute response patterns: (i) strong event and seasonal solute mobilization (solute flush), (ii) event chemostasis and strong seasonal flush, (iii) event chemostasis and weak seasonal flush, (iv) event and seasonal chemostasis and (v) late seasonal flush. Our results indicate that hydrologic responses of semiarid catchments are controlled by rainfall partitioning at the event scale, whereas wetting magnitude, frequency and timing alter solute stores readily available for transport and control temporal runoff quality. Copyright © 2012 John Wiley & Sons, Ltd.     

Application of a rainfall-runoff model to three catchments in Iraq

Abstract

The capability of the Surface inFiltration Baseflow (SFB) conceptual rainfall-runoff model to simulate streamflow for three catchments selected from northern Iraq is investigated. These catchments differ in their climatic regimes and physical characteristics. Three versions of the model were tested: the original three-parameter model (SFB), the modified five-parameter model (SFB-5), and the modified six-parameter model (SFB-6). The available daily precipitation, potential evapotranspiration and runoff data were used in conjunction with a simulated annealing (SA) optimization technique to calibrate the various versions of the SFB model. A simple sensitivity analysis was then carried out to determine the relative importance of the model parameters. The study indicated that use of the original three parameter model was not adequate to simulate monthly streamflow in the selected catchments. The modified version (SFB-5) provided better runoff simulation than the original SFB model; overall a 19% increase was observed in the coefficient of determination (R²) between simulated and observed monthly runoff. The SFB-5 model performed with varying degrees of success among the catchments. The model performance in the validation stage was reasonable and comparable to that of the calibration stage. The sensitivity analysis of the SFB model for arid catchments revealed that the baseflow parameter (B) was the most sensitive one, while the S and F parameters were less sensitive than the B parameter.     

Comparison of an artificial neural network and a conceptual rainfall–runoff model in the simulation of ephemeral streamflow

ABSTRACT

The rainfall–runoff process is governed by parameters that can seldom be measured directly for use with distributed models, but are rather inferred by expert judgment and calibrated against historical records. Here, a comparison is made between a conceptual model (CM) and an artificial neural network (ANN) for their ability to efficiently model complex hydrological processes. The Sacramento soil moisture accounting model (SAC-SMA) is calibrated using a scheme based on genetic algorithms and an input delay neural network (IDNN) is trained for variable delays and hidden layer neurons which are thoroughly discussed. The models are tested for 15 ephemeral catchments in Crete, Greece, using monthly rainfall, streamflow and potential evapotranspiration input. SAC-SMA performs well for most basins and acceptably for the entire sample with R² of 0.59–0.92, while scoring better for high than low flows. For the entire dataset, the IDNN improves simulation fit to R² of 0.70–0.96 and performs better for high flows while being outmatched in low flows. Results show that the ANN models can be superior to the conventional CMs, as parameter sensitivity is unclear, but CMs may be more robust in extrapolating beyond historical record limits and scenario building.

EDITOR M.C. Acreman; ASSOCIATE EDITOR not assigned     

The relationship between runoff rate and lag time and the effects of surface treatments at the plot scale

Abstract

The manner in which both the seasonal and regional variations in storm duration, intensity and inter-storm period manifest in the runoff response of agricultural water supply catchments is investigated. High-resolution rainfall data were analysed for a network of 17 raingauges located across the semiarid (200–500 mm year^?1) agricultural districts of southwest Western Australia. Seasonal variations in mean storm duration, mean rainfall intensity and mean inter-storm period were modelled using simple periodic functions whose parameters were then also regressed with geographic and climatic indices to create spatial fields for each of these statistics. Based on these mean values, a continuous rainfall time series can be synthesized for any location within the region, with the rainfall depth within each storm being downscaled to 5-min time steps using a bounded random cascade model. Runoff from six different catchment surface treatments (“engineered” catchments) was simulated using a conceptual water-balance model, validated using rainfall—runoff data from an experimental field site. The expected yield of the various catchment types at any other location within the study region is then simulated using the above rainfall—runoff model and synthetic rainfall and potential evaporation time series under a range of climatic settings representative of regional climate variation. The resulting coupled model can be used to estimate the catchment area required to yield an acceptable volume of runoff for any location and dam capacity, at a specified reliability level, thus providing a tool for water resource managers to design engineered catchments for water supply. Although the model presented is specific for Western Australia's southwest region, the methodology itself is applicable to other locations.     

Contribution to hydrological modelling of small Amazonian catchments: application of rainfall–runoff models to simulate flow duration curves

Abstract

The objective of this study is to analyse three rainfall–runoff hydrological models applied in two small catchments in the Amazon region to simulate flow duration curves (FDCs). The simple linear model (SLM) considers the rainfall–runoff process as an input–output time-invariant system. However, the rainfall–runoff process is nonlinear; thus, a modification is applied to the SLM based on the residual relationship between the simulated and observed discharges, generating the modified linear model (MLM). In the third model (SVM), the nonlinearity due to infiltration and evapotranspiration is incorporated into the system through the sigmoid variable gain factor. The performance criteria adopted were a distance metric (δ) and the Nash-Sutcliffe coefficient (R²) determined between simulated and observed flows. The good results of the models, mainly the MLM and SVM, showed that they could be applied to simulate FDCs in small catchments in the Amazon region.

Editor D. Koutsoyiannis; Associate editor A. Montanari

Citation Blanco, C.J.C., Santos, S.S.M., Quintas, M.C., Vinagre, M.V.A., and Mesquita, A.L.A., 2013. Contribution to hydrological modelling of small Amazonian catchments: application of rainfall–runoff models to simulate flow duration curves. Hydrological Sciences Journal, 58 (7), 1–11.     

Testing the applicability of a kinematic wave-based distributed hydrological model in two climatically contrasting catchments

Abstract

Steep mountainous areas account for 70% of all river catchments in Japan. To predict river discharge for the mountainous catchments, many studies have applied distributed hydrological models based on a kinematic wave approximation with surface and subsurface flow components (DHM-KWSS). These models reproduce observed river discharge of catchments in Japan well; however, the applicability of a DHM-KWSS to catchments with different geographical and climatic conditions has not been sufficiently examined. This research applied a DHM-KWSS to two river basins that have different climatic conditions from basins in Japan to examine the transferability of the DHM-KWSS model structure. Our results show that the DHM-KWSS model structure explained flow regimes for a wet river basin as well as a large flood event in an arid basin; however, it was unable to explain long-term flow regimes for the arid basin case study.     

AN EVALUATION OF ACTUAL EVAPOTRANSPIRATION IN TROPICAL EAST AFRICA

Monthly actual evapotranspiration (AET) for four humid catchments in Kenya, East Africa was evaluated using the Morton and Grindley models. The area of each catchment was less then 100 km² and all catchments lie around the equator. Three of the catchments are chiefly vegetated with pasture, annual and perennial crops, whereas one is largely under forest. The AET estimates from the aforementioned models were compared with those based on a water balance analysis. A total of 34 data years for daily rainfall and run off for all the catchments were used for analysis. The results indicated that both models tended to overestimate AET in relation to the water balance-based values. The Grindley model (AET_G) overestimated such that the estimates were either equal or close to the Penman potential evapotranspiration (PET) values in all the catchments. The Morton model (AET_M) performed better, and AET estimates by this method, although marginally higher, were closer to the water balance-based estimates. The overall overprediction by the Grindley model on a monthly basis was of the order of 32% whereas by the Morton model it was only 8%. Although the mean values from the Morton model are only 8% higher than the water balance values on a monthly basis, values of the RMSE (root mean square error) range between 25 and 47 mm. The additional merit of the Morton model lies in its ability to provide estimates of AET based solely on meteorological data, which are readily available in Kenya, East Africa. © 1997 by John Wiley & Sons, Ltd.     

Sensitivity of hydrological models to uncertainty in rainfall input

Abstract

Different approaches used in hydrological modelling are compared in terms of the way each one takes the rainfall data into account. We examine the errors associated with accounting for rainfall variability, whether in hydrological modelling (distributed vs lumped models) or in computing catchment rainfall, as well as the impact of each approach on the representativeness of the parameters it uses. The database consists of 1859 rainfall events, distributed on 500 basins, located in the southeast of France with areas ranging from 6.2 to 2851 km². The study uses as reference the hydrographs computed by a distributed hydrological model from radar rainfall. This allows us to compare and to test the effects of various simplifications to the process when taking rainfall information (complete rain field vs sampled rainfall) and rainfall–runoff modelling (lumped vs distributed) into account. The results appear to show that, in general, the sampling effect can lead to errors in discharge at the outlet that are as great as, or even greater than, those one would get with a fully lumped approach. We found that small catchments are more sensitive to the uncertainties in catchment rainfall input generated by sampling rainfall data as seen through a raingauge network. Conversely, the larger catchments are more sensitive to uncertainties generated when the spatial variability of rainfall events is not taken into account. These uncertainties can be compensated for relatively easily by recalibrating the parameters of the hydrological model, although such recalibrations cause the parameter in question to completely lose physical meaning.

Citation Arnaud, P., Lavabre, J., Fouchier, C., Diss, S. & Javelle, P. (2011) Sensitivity of hydrological models to uncertainty of rainfall input. Hydrol. Sci. J. 56(3), 397–410.     

Artificial neural networks for daily rainfall—runoff modelling

Abstract

The application of artificial neural network (ANN) methodology for modelling daily flows during monsoon flood events for a large size catchment of the Narmada River in Madhya Pradesh (India) is presented. The spatial variation of rainfall is accounted for by subdividing the catchment and treating the average rainfall of each subcatchment as a parallel and separate lumped input to the model. A linear multiple-input single-output (MISO) model coupled with the ANN is shown to provide a better representation of the rainfall-runoff relationship in such large size catchments compared with linear and nonlinear MISO models. The present model provides a systematic approach for runoff estimation and represents improvement in prediction accuracy over the other models studied herein.     

Comparison of different structures for a monthly water yield model in seasonally snow-covered mountainous watersheds of Iran

Abstract

This paper attempts to search for a suitable structure of a monthly water yield model applicable for seasonally snow-covered mountainous catchments located in a semiarid area. In this respect several model structures based on a soil water balance concept were compared. The main distinction between the different structures was made by the inclusion of either a linear or a nonlinear transformation element for the conversion of overland flow or baseflow into total runoff. A combined water balance model having two main elements, a soil storage element generating excess water, and a transformation element conceptualized by a linear storage-discharge relationship, was found to be the most accurate.     

G) Personalia

Abstract

This paper proposes a framework for identifying the parameters of a lumped routing model in small to medium sized catchments where lateral inflows can be large but poorly defined. In a first step, a priori estimates of the parameters are made based on topography, aerial photographs, flood marks and field surveys. In a second step, runoff data are analysed of reservoir release events and convective events where no rainfall in the direct catchments occurred. In a third step the routing model is calibrated to the results of hydrodynamic models for scenarios of different magnitudes. In a fourth step, these pieces of information are combined, allowing for soft expert judgement to be incorporated. In a fifth step, the routing parameters are fine tuned to observed flood events where lateral inflows are estimated by a rainfall—runoff model. The framework is illustrated by the Kamp flood forecasting system in Austria that has been in operational use since 2006.     

Prediction of climate change effects on the runoff regime of a forested catchment in northern Iran

ABSTRACT

The southern coast of the Caspian Sea in northern Iran is bordered by a mountain range with forested catchments which are susceptible to droughts and floods. This paper examines possible changes to runoff patterns from one of these catchments in response to climate change scenarios. The HEC-HMS rainfall–runoff model was used with downscaled future rainfall and temperature data from 13 global circulation models, and meteorological and hydrometrical data from the Casilian (or “Kassilian”) Catchment. Annual and seasonal predictions of runoff change for three future emissions scenarios were obtained, which suggest significantly higher spring rainfall with increased risk of flooding and significantly lower summer rainfall leading to a higher probability of drought. Flash floods arising from extreme rainfall may become more frequent, occurring at any time of year. These findings indicate a need for strategic planning of water resource management and mitigation measures for increasing flood hazards.

EDITOR M.C. Acreman ASSOCIATE EDITOR not assigned     

Understanding the role of hydrologic model structures on evapotranspiration-driven sensitivity

ABSTRACT

Most conceptual hydrological models do not treat vegetation as a dynamic component. This study focuses on understanding the impact of model structural complexity on the sensitivity of hydrologic models to potential evapotranspiration forcing data. To achieve this, two classes of hydrologic models are examined: (1) lumped, conceptual rainfall–runoff models and (2) eco-hydrologic models. A sample of 57 US catchments, covering eight eco-regions, included in the MOPEX dataset is used. While streamflow simulation performance in complex models did not exhibit increased sensitivity to PET, actual evapotranspiration simulation performance showed greater sensitivity in energy-limited catchments. This analysis warns against using over-simplistic PET estimations in energy-limited catchments for eco-hydrologic models and for more complex conceptual hydrologic models. This is particularly true for streamflow-only calibrations that commonly fail to properly constrain physically based parameters. Ultimately, these results have the potential to inform data collection and model selection efforts to yield the greatest benefit.