Predicting runoff in ungauged catchments by using Xinanjiang model with MODIS leaf area index

Vegetation processes are seldom considered in lumped conceptual rainfall–runoff (RR) models although they have significant impacts on runoff via the control of evapotranspiration. This paper incorporates the remotely-sensed the moderate resolution imaging spectrometer mounted on the polar-orbiting terra satellite-leaf area index (MODIS-LAI) data into Xinanjiang rainfall–runoff model and assesses the model performance on 210 catchments in south-east Australia. The results show that the inclusion of LAI data improves both the model calibration results as well as the daily runoff prediction in ungauged catchments. It is likely that more significant improvements to the model structure to integrate the remotely-sensed vegetation and other data can further reduce the uncertainty in runoff prediction in ungauged catchments.     

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.     

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.     

A process-based,distributed hydrologic model based on a large-scale method for surface–subsurface coupling

Process-based watershed models are useful tools for understanding the impacts of natural and anthropogenic influences on water resources and for predicting water and solute fluxes exported from watersheds to receiving water bodies. The applicability of process-based hydrologic models has been previously limited to small catchments and short time frames. Computational demands, especially the solution to the three-dimensional subsurface flow domain, continue to pose significant constraints. This paper documents the mathematical development, numerical testing and the initial application of a new distributed hydrologic model PAWS (Process-based Adaptive Watershed Simulator). The model solves the governing equations for the major hydrologic processes efficiently so that large scale applications become relevant. PAWS evaluates the integrated hydrologic response of the surface–subsurface system using a novel non-iterative method that couples runoff and groundwater flow to vadose zone processes approximating the 3D Richards equation. The method is computationally efficient and produces physically consistent solutions. All flow components have been independently verified using analytical solutions and experimental data where applicable. The model is applied to a medium-sized watershed in Michigan (1169 km²) achieving high performance metrics in terms of streamflow prediction at two gages during the calibration and verification periods. PAWS uses public databases as input and possesses full capability to interact with GIS datasets. Future papers will describe applications to other watersheds and the development and application of fate and transport modules.     

Water balance modeling over variable time scales based on the Budyko framework – Model development and testing

Partitioning of precipitation into evapotranspiration and runoff is controlled by climate and catchment characteristics. The degree of control exerted by these factors varies with the spatial and temporal scales of processes modeled. The Budyko framework or the “limits” concept was used to model water balance at four temporal scales (mean annual, annual, monthly and daily). The method represents a top-down approach to hydrologic modeling and is expected to achieve parsimony of model parameters. Daily precipitation, potential evapotranspiration, and streamflow from 265 catchments in Australia were used. On a mean annual basis, the index of dryness defined as the ratio of potential evapotranspiration to precipitation was confirmed to be a dominant factor in determining the water balance with one model parameter. Analysis of the data, however, suggested increased model complexity is necessary on finer time scale such as monthly. In response, the Budyko framework for mean annual water balance was extended to include additional factors and this resulted in a parsimonious lumped conceptual model on shorter-time scale. The model was calibrated and tested against measured streamflow at variable time scales and showed promising results. The strengths of the model are consistent water balance relationships across different time scales, and model parsimony and robustness. As result, the model has the potential to be used to predict streamflow for ungauged catchments.     

Application of linear and nonlinear techniques in river flow forecasting in the Kilombero River basin,Tanzania / Application de techniques linéaires et non-linéaires à la prévision des débits dans le bassin de la Rivière Kilombero,en Tanzanie

Abstract

Modelling of the rainfall–runoff transformation process and routing of river flows in the Kilombero River basin and its five sub-catchments within the Rufiji River basin in Tanzania was undertaken using three system (black-box) models—a simple linear model, a linear perturbation model and a linear varying gain factor model—in their linear transfer function forms. A lumped conceptual model—the soil moisture accounting and routing model—was also applied to the sub-catchments and the basin. The HEC-HMS model, which is a distributed model, was applied only to the entire Kilombero River basin. River discharge, rainfall and potential evaporation data were used as inputs to the appropriate models and it was observed that sometimes the system models performed better than complex hydrological models, especially in large catchments, illustrating the usefulness of using simple black-box models in datascarce situations.     

Regionalization of hydrologic parameters of Nash mode

hydrologic models are important tools to estimate runoff from a catchment. Identification of broad based parameters of a hydrologic model for development of direct runoff hydrograph is a key issue for the modelers. Optimization and regionalization of hydrologic parameters for application of Nash’s model is investigated in this paper. Six catchments dominated by hill torrent flows were selected for this purpose. Fifty seven rainfall events were used for regionalization of parameters and about 55 events were used for validation of the results. The hydrologic parameters of the Nash Model, number of linear cascades (N) and storage coefficient (k) were determined using optimization based upon Downhill Simplex method. The data was collected by field measurements and from Water and Power Development Authority (WAPDA) Pakistan. The physical parameters of the catchments were derived from the satellite images of the watersheds with the help of ERDAS software. The performance of the model was assessed by the model efficiency. It is concluded that the conceptual Nash model can simulate direct runoff hydrograph using regional hydrologic parameters with model efficiency of 67%.     

A distributed approach for estimating catchment evapotranspiration: comparison of the combination equation and the complementary relationship approaches

In large river basins, there may be considerable variations in both climate and land use across the region. The evapotranspiration that occurs over a basin may be drastically different from one part of the region to another. The potential influence of these variations in evapotranspiration estimated for the catchment is weakened by using a spatially based distributed hydrological model in such a study. Areal evapotranspiration is estimated by means of approaches requiring only meteorological data: the combination equation (CE) model and the complementary relationship approach—the complementary relationship areal evapotranspiration (CRAE) and advection–aridity (AA) models. The capability of three models to estimate the evapotranspiration of catchments with complex topography and land‐use classification is investigated, and the models are applied to two catchments with different characteristics and scales for several representative years. Daily, monthly, and annual evapotranspiration are estimated with different accuracy. The result shows that the modified CE model may underestimate the evapotranspiration in some cases. The CRAE and AA models seem to be two kinds of effective alternatives for estimating catchment evapotranspiration. Copyright © 2003 John Wiley & Sons, Ltd.     

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     

Diagnostic evaluation of multiple hypotheses of hydrological behaviour in a limits‐of‐acceptability framework for 24 UK catchments

Testing competing conceptual model hypotheses in hydrology is complicated by uncertainties from a wide range of sources, which result in multiple simulations that explain catchment behaviour. In this study, the limits of acceptability uncertainty analysis approach used to discriminate between 78 competing hypotheses in the Framework for Understanding Structural Errors for 24 catchments in the UK. During model evaluation, we test the model's ability to represent observed catchment dynamics and processes by defining key hydrologic signatures and time step‐based metrics from the observed discharge time series. We explicitly account for uncertainty in the evaluation data by constructing uncertainty bounds from errors in the stage‐discharge rating curve relationship. Our study revealed large differences in model performance both between catchments and depending on the type of diagnostic used to constrain the simulations. Model performance varied with catchment characteristics and was best in wet catchments with a simple rainfall‐runoff relationship. The analysis showed that the value of different diagnostics in constraining catchment response and discriminating between competing conceptual hypotheses varies according to catchment characteristics. The information content held within water balance signatures was found to better capture catchment dynamics in chalk catchments, where catchment behaviour is predominantly controlled by seasonal and annual changes in rainfall, whereas the information content in the flow‐duration curve and time‐step performance metrics was able to better capture the dynamics of rainfall‐driven catchments. We also investigate the effect of model structure on model performance and demonstrate its (in)significance in reproducing catchment dynamics for different catchments. Copyright © 2013 John Wiley & Sons, Ltd.     

Regional regression models for hydro‐climate change impact assessment

Hydro‐climatic impacts in water resources systems are typically assessed by forcing a hydrologic model with outputs from general circulation models (GCMs) or regional climate models. The challenges of this approach include maintaining a consistent energy budget between climate and hydrologic models and also properly calibrating and verifying the hydrologic models. Subjective choices of loss, flow routing, snowmelt and evapotranspiration computation methods also increase watershed modelling uncertainty and thus complicate impact assessment. An alternative approach, particularly appealing for ungauged basins or locations where record lengths are short, is to predict selected streamflow quantiles directly from meteorological variable output from climate models using regional regression models that also include physical basin characteristics. In this study, regional regression models are developed for the western Great Lakes states using ordinary least squares and weighted least squares techniques applied to selected Great Lakes watersheds. Model inputs include readily available downscaled GCM outputs from the Coupled Model Intercomparison Project Phase 3. The model results provide insights to potential model weaknesses, including comparatively low runoff predictions from continuous simulation models that estimate potential evapotranspiration using temperature proxy information and comparatively high runoff projections from regression models that do not include temperature as an explanatory variable. Copyright © 2014 John Wiley & Sons, Ltd.     

Catchment properties,function, and conceptual model representation: is there a correspondence?

This study investigates the possible correspondence between catchment structure, as represented by perceptual hydrological models developed from fieldwork investigations, and mathematical model structures, selected on the basis of reproducing observed catchment hydrographs. Three Luxembourgish headwater catchments are considered, where previous fieldwork suggested distinct flow‐generating mechanisms and hydrological dynamics. A set of lumped conceptual model structures are hypothesized and implemented using the SUPERFLEX framework. Following parameter calibration, the model performance is examined in terms of predictive accuracy, quantification of uncertainty, and the ability to reproduce the flow–duration curve signature. Our key research question is whether differences in the performance of the conceptual model structures can be interpreted based on the dominant catchment processes suggested from fieldwork investigations. For example, we propose that the permeable bedrock and the presence of multiple aquifers in the Huewelerbach catchment may explain the superior performance of model structures with storage elements connected in parallel. Conversely, model structures with serial connections perform better in the Weierbach and Wollefsbach catchments, which are characterized by impermeable bedrock and dominated by lateral flow. The presence of threshold dynamics in the Weierbach and Wollefsbach catchments may favour nonlinear models, while the smoother dynamics of the larger Huewelerbach catchment were suitably reproduced by linear models. It is also shown how hydrologically distinct processes can be effectively described by the same mathematical model components. Major research questions are reviewed, including the correspondence between hydrological processes at different levels of scale and how best to synthesize the experimentalist's and modeller's perspectives. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

Compared performance of a conceptual and a mechanistic hydrologic models of a green roof

In order to investigate the hydrologic response of a green roof system within the urban environment, a monitoring campaign is carried out at the green roof site of the University of Genova (Italy). Experimental data confirm that the green roof is able to significantly mitigate the generation of runoff with median values of retained volume and peak reduction, respectively, equal to 94 and 98%. A conceptual linear reservoir and a simple mechanistic (Hydrus‐1D) models are implemented to simulate the hydrologic behaviour of the system; each model is calibrated and validated based on experimental data collected at the green roof site. The hydrographs simulated with both hydrologic models reproduce with acceptable matching capabilities the experimental measurements, as confirmed by the Nash‐Sutcliffe Efficiency index generally greater than 0·60. Although the relative percentage differences evaluated for the selected hydrograph variables (the total effluent volume, the peak flow rate and the hydrograph centroid) demonstrate that the mechanistic model is more accurate, prediction errors of the conceptual model are generally limited when compared with the observed hydrologic performance. Results of the present comparison are useful in supporting conceptual model selection in case the hydrologic response is addressed for hydrologic performance assessment. Copyright © 2011 John Wiley & Sons, Ltd.     

Alteration of hydrologic indicators for Korean catchments under CMIP5 climate projections

The change of hydrological regimes may cause impacts on human and natural system. Therefore, investigation of hydrologic alteration induced by climate change is essential for preparing timely proper adaptation to the changes. This study employed 24 climate projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) under Representative Concentration Pathway (RCP) 4.5 scenario. The climate projections were downscaled at a station‐spacing for seven Korean catchments by a statistical downscaling method that preserves a long‐term trend in climate projections. Using an ensemble of future hydrologic projections simulated by three conceptual rainfall‐runoff models (GR4J, IHACRES, and Sacramento models), we calculated Hydrologic Alteration Factors (HAFs) to investigate degrees of variations in Indicators of Hydrologic Alteration (IHAs) derived from the hydrologic projections. The results showed that the seven catchments had similar trend in terms of the HAFs for the 24 IHAs. Given that more frequent severe floods and droughts were projected over Korean catchments, sound water supply strategies are definitely required to adapt to the alteration of streamflow. A wide range of HAFs between rainfall‐runoff models for each catchment was detected by large variations in the magnitude of HAFs with the hydrologic models and the difference could be the hydrologic prediction uncertainty. There were no‐consistent tendency in the order of HAFs between the hydrologic models. In addition, we found that the alterations of hydrologic regimes by climate change are smaller as the size of catchment is larger. Copyright © 2016 John Wiley & Sons, Ltd.     

How do potential evapotranspiration formulas influence hydrological projections?

ABSTRACT

This paper evaluates the sensitivity of hydrological projections to the choice of potential evapotranspiration formulas on two natural sub-catchments, in Canada and Germany. Twenty-four equations, representing a large range of options, are applied for calibration over the whole observation time series and for future conditions. The modelling chain is composed of dynamically downscaled climatic projections and a 20-member (ensemble) hydrological model, along with a snow module. The roots of the sensitivity and its propagation within the hydrological chain are evaluated to show influences on climate change impact conclusions. Results show large differences between the 24 simulated potential evapotranspiration time series. However, these discrepancies only moderately affect the calibration efficiency of hydrological models as a result of adaptation of parameters. Choice of formula influences hydrological projections and climate change conclusions for both catchments in terms of simulated and projected values, and also in the magnitude of changes during important dynamic periods such as spring and autumn high flows and summer low flows. Spread of the hydrological response is lower for the combinational formulas than for temperature-based or radiation-based equations. All the results reveal the importance of testing a large spectrum of potential evapotranspiration formulas in a decision-making context, such as water resources management.     

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.     

On the prediction of the Toce alpine basin floods with distributed hydrologic models

With the objective of improving flood predictions, in recent years sophisticated continuous hydrologic models that include complex land‐surface sub‐models have been developed. This has produced a significant increase in parameterization; consequently, applications of distributed models to ungauged basins lacking specific data from field campaigns may become redundant. The objective of this paper is to produce a parsimonious and robust distributed hydrologic model for flood predictions in Italian alpine basins. Application is made to the Toce basin (area 1534 km²). The Toce basin was a case study of the RAPHAEL European Union research project, during which a comprehensive set of hydrologic, meteorological and physiographic data were collected, including the hydrologic analysis of the 1996–1997 period. Two major floods occurred during this period. We compare the FEST04 event model (which computes rainfall abstraction and antecedent soil moisture conditions through the simple Soil Conservation Service curve number method) and two continuous hydrologic models, SDM and TDM (which differ in soil water balance scheme, and base flow and runoff generation computations). The simple FEST04 event model demonstrated good performance in the prediction of the 1997 flood, but shows limits in the prediction of the long and moderate 1996 flood. More robust predictions are obtained with the parsimonious SDM continuous hydrologic model, which uses a simple one‐layer soil water balance model and an infiltration excess mechanism for runoff generation, and demonstrates good performance in both long‐term runoff modelling and flood predictions. Instead, the use of a more sophisticated continuous hydrologic model, the TDM, that simulates soil moisture dynamics in two layers of soil, and computes runoff and base flow using some TOPMODEL concepts, does not seem to be advantageous for this alpine basin. Copyright © 2006 John Wiley & Sons, Ltd.     

Modelling of wildfire impacts on catchment hydrology applied to two case studies

We used a conceptual modelling approach on two western Canadian mountainous catchments that were burned in separate wildfires in 2003 to explore the potential of using modelling approaches to generalize post‐wildfire catchment hydrology in cases where pre‐wildfire hydrologic data were present or absent. The Fishtrap Creek case study (McLure fire, British Columbia) had a single gauged catchment with both pre‐fire and post‐fire data, whereas the Lost Creek case study (Lost Ck. fire, Alberta) had several instrumented burned and reference catchments providing streamflows and climate data only for the post‐wildfire period. Wildfire impacts on catchment hydrology were assessed by comparing pre‐wildfire and post‐wildfire model calibrated parameter sets for Fishtrap Creek (Fishtrap Ck.) and the calibrated parameters of two burned (South York Ck. and Lynx Ck.) and two unburned (Star Ck. and North York Ck.) catchments for Lost Ck. Model predicted streamflows for burned catchments were compared with unburned catchments (pre‐fire in the case of Fishtrap Ck. and unburned in the case of the Lost Ck.). Similarly, model predicted streamflows from unburned catchments were compared with burned catchments (post‐fire in the case of Fishtrap Ck. and burned in the case of the Lost Ck.). For Fishtrap Ck., different model parameters and streamflow behaviour were observed for pre‐wildfire and post‐wildfire conditions. However, the burned and unburned model results from the Lost Ck. wildfire did not show differing streamflow responses to the wildfire. We found that this hydrological modelling approach is suitable where pre‐wildfire and post‐wildfire data are available but may provide limited additional insights where pre‐disturbance hydrologic data are unavailable. This may in part be because the conceptual modelling approach does not represent the physical catchment processes, whereas a physically based model may still provide insights into catchment hydrological response in these situations. Copyright © 2015 John Wiley & Sons, Ltd.