Excel modelling of hydrological systems

This short paper describes the use of Excel spreadsheet Solver facility for deriving estimates in a solute mixing model equation with more than one unknown.     

Capabilities and limitations of detailed hillslope hydrological modelling

Hillslope hydrological modelling is considered to be of great importance for the understanding and quantification of hydrological processes in hilly or mountainous landscapes. In recent years a few comprehensive hydrological models have been developed at the hillslope scale which have resulted in an advanced representation of hillslope hydrological processes (including their interactions), and in some operational applications, such as in runoff and erosion studies at the field scale or lateral flow simulation in environmental and geotechnical engineering. An overview of the objectives of hillslope hydrological modelling is given, followed by a brief introduction of an exemplary comprehensive hillslope model, which stimulates a series of hydrological processes such as interception, evapotranspiration, infiltration into the soil matrix and into macropores, lateral and vertical subsurface soil water flow both in the matrix and preferential flow paths, surface runoff and channel discharge. Several examples of this model are presented and discussed in order to determine the model's capabilities and limitations. Finally, conclusions about the limitations of detailed hillslope modelling are drawn and an outlook on the future prospects of hydrological models on the hillslope scale is given.The model presented performed reasonable calculations of Hortonian surface runoff and subsequent erosion processes, given detailed information of initial soil water content and soil hydraulic conditions. The vertical and lateral soil moisture dynamics were also represented quite well. However, the given examples of model applications show that quite detailed climatic and soil data are required to obtain satisfactory results. The limitations of detailed hillslope hydrological modelling arise from different points: difficulties in the representations of certain processes (e.g. surface crusting, unsaturated–saturated soil moisture flow, macropore flow), problems of small‐scale variability, a general scarcity of detailed soil data, incomplete process parametrization and problems with the interdependent linkage of several hillslopes and channel–hillslope interactions. Copyright © 1999 John Wiley & Sons, Ltd.     

SWAT-based hydrological modelling of tropical land-use scenarios

Abstract

The Hulu Langat basin, a strategic watershed in Malaysia, has in recent decades been exposed to extensive changes in land-use and consequently hydrological conditions. In this work, the impact of Land Use and Cover Change (LUCC) on hydrological conditions (water discharge and sediment load) of the basin were investigated using the Soil and Water Assessment Tool (SWAT). Four land-use scenarios were defined for land-use change impact analysis, i.e. past, present (baseline), future and water conservation planning. The land-use maps, dated 1984, 1990, 1997 and 2002, were defined as the past scenarios for LUCC impact analysis. The present scenario was defined based on the 2006 land-use map. The 2020 land-use map was simulated using a cellular automata-Markov model and defined as the future scenario. Water conservation scenarios were produced based on guidelines published by Malaysia’s Department of Town and Country Planning and Department of Environment. Model calibration and uncertainty analysis was performed using the Sequential Uncertainty Fitting (SUFI-2) algorithm. The model robustness for water discharge simulation for the period 1997–2008 was good. However, due to uncertainties, mainly resulting from intense urban development in the basin, its robustness for sediment load simulation was only acceptable for the calibration period 1997–2004. The optimized model was run using different land-use maps over the periods 1997–2008 and 1997–2004 for water discharge and sediment load estimation, respectively. In comparison to the baseline scenario, SWAT simulation using the past and conservative scenarios showed significant reduction in monthly direct runoff and monthly sediment load, while SWAT simulation based on the future scenario showed significant increase in monthly direct runoff, monthly sediment load and groundwater recharge.

Editor D. Koutsoyiannis; Associate editor C. Perrin     

The problem of scaling in grid-related hydrological process modelling

This article shows some important scaling aspects that exist in hydrological process grid modelling with GIS, with respect to selecting the optimal grid width. Hydrologically relevant space parameter fields should often be regarded as self-similar fractals for which certain invariance characteristics are applied. These characteristics are especially important if there is an extensive change in the model grid width. The self-similarity generates simple scaling laws, which can be used for rescaling procedures. © 1997 John Wiley & Sons, Ltd.     

Distributed hydrological modelling using weather radar in gauged and ungauged basins

Distributed hydrological modelling using space–time estimates of rainfall from weather radar provides a natural approach to area-wide flood forecasting and warning at any location, whether gauged or ungauged. However, radar estimates of rainfall may lack consistent, quantitative accuracy. Also, the formulation of hydrological models in distributed form may be problematic due to process complexity and scaling issues. Here, the aim is to first explore ways of improving radar rainfall accuracy through combination with raingauge network data via integrated multiquadric methods. When the resulting gridded rainfall estimates are employed as input to hydrological models, the simulated river flows show marked improvements when compared to using radar data alone. Secondly, simple forms of physical–conceptual distributed hydrological model are considered, capable of exploiting spatial datasets on topography and, where necessary, land-cover, soil and geology properties. The simplest Grid-to-Grid model uses only digital terrain data to delineate flow pathways and to control runoff production, the latter by invoking a probability-distributed relation linking terrain slope to soil absorption capacity. Model performance is assessed over nested river basins in northwest England, employing a lumped model as a reference. When the distributed model is used with the gridded radar-based rainfall estimators, it shows particular benefits for forecasting at ungauged locations.     

An approach to measure parameter sensitivity in watershed hydrological modelling

Hydrological responses vary spatially and temporally according to watershed characteristics. In this study, the hydrological models that we developed earlier for the Little Miami River (LMR) and Las Vegas Wash (LVW) watersheds in the USA were used for detailed sensitivity analyses. To compare the relative sensitivities of the hydrological parameters of these two models, we used normalized root mean square error (NRMSE). By combining the NRMSE index with the flow duration curve analysis, we derived an approach to measure parameter sensitivities under different flow regimes. Results show that the parameters related to groundwater are highly sensitive in the LMR watershed, whereas the LVW watershed is primarily sensitive to near-surface and impervious parameters. The high and medium flows are more impacted by most of the parameters. The low flow regime was highly sensitive to groundwater-related parameters. Moreover, our approach is found to be useful in facilitating model development and calibration.

EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR S. Huang     

Evaluation of satellite-based rainfall products for hydrological modelling in Morocco

ABSTRACT

Several satellite-based precipitation estimates are becoming available at a global scale, providing new possibilities for water resources modelling, particularly in data-sparse regions and developing countries. This work provides a first validation of five different satellite-based precipitation products (TRMM-3B42 v6 and v7, RFE 2.0, PERSIANN-CDR, CMORPH1.0 version 0.x) in the 1785 km² Makhazine catchment (Morocco). Precipitation products are first compared against ground observations. Ten raingauges and four different interpolation methods (inverse distance, nearest neighbour, ordinary kriging and residual kriging with altitude) were used to compute a set of interpolated precipitation reference fields. Second, a parsimonious conceptual hydrological model is considered, with a simulation approach based on the random generation of model parameters drawn from existing parameter set libraries, to compare the different precipitation inputs. The results indicate that (1) all four interpolation methods, except the nearest neighbour approach, give similar and valid precipitation estimates at the catchment scale; (2) among the different satellite-based precipitation estimates verified, the TRMM-3B42 v7 product is the closest to observed precipitation, and (3) despite poor performance at the daily time step when used in the hydrological model, TRMM-3B42 v7 estimates are found adequate to reproduce monthly dynamics of discharge in the catchment. The results provide valuable perspectives for water resources modelling of data-scarce catchments with satellite-based rainfall data in this region.

Editor M.C. Acreman; Associate editor N. Verhoest     

Mitigating parameter bias in hydrological modelling due to uncertainty in covariates

The uncertainty in hydrological model covariates, if ignored, introduces systematic bias in the parameters estimated. We introduce here a method to determine the true value of parameters given uncertainty in model inputs. This method, known as simulation extrapolation (SIMEX) operates on the basis of an empirical relationship between parameters and the level of input noise (or uncertainty). The method starts by generating a series of alternate model inputs by artificially adding white noise in increasing multiples of the known error variance. The resulting parameter sets allow us to formulate an empirical relationship between their values and the level of noise present. SIMEX is based on theory that the trend in alternate parameters can be extrapolated back to the notional error free zone.

We illustrate the strength of SIMEX in improving skills of predictive models that use uncertain sea surface temperature anomaly (SSTA) data over the NINO3 region as predictor to the southern oscillation index (SOI), an alternate measure of the strength of the El Nino southern oscillation. Our hypothesis is that the higher magnitude of noise in the pre 1960 data period introduces bias to model parameters where SSTA is the input variable. The relatively error invariant southern oscillation index (SOI) is regressed over SSTA and calibrated using a subset of the series from 1900 to 1960. We validate the resulting models using the less erroneous 1960–2003 data period. Overall the application of SIMEX is found to reduce the residual predictive errors during the validation period.     

Application of satellite products and hydrological modelling for flood early warning

Floods have caused devastating impacts to the environment and society in Awash River Basin, Ethiopia. Since flooding events are frequent, this marks the need to develop tools for flood early warning. In this study, we propose a satellite based flood index to identify the runoff source areas that largely contribute to extreme runoff production and floods in the basin. Satellite based products used for development of the flood index are CMORPH (Climate Prediction Center MORPHing technique: 0.25^° by 0.25^°, daily) product for calculation of the Standard Precipitation Index (SPI) and a Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) for calculation of the Topographic Wetness Index (TWI). Other satellite products used in this study are for rainfall-runoff modelling to represent rainfall, potential evapotranspiration, vegetation cover and topography. Results of the study show that assessment of spatial and temporal rainfall variability by satellite products may well serve in flood early warning. Preliminary findings on effectiveness of the flood index developed in this study indicate that the index is well suited for flood early warning. The index combines SPI and TWI, and preliminary results illustrate the spatial distribution of likely runoff source areas that cause floods in flood prone areas.     

Selection between the generalized Pareto and kappa distributions in peaks-over-threshold hydrological frequency modelling

Hydrologists use the generalized Pareto (GP) distribution in peaks-over-threshold (POT) modelling of extremes. A model with similar uses is the two-parameter kappa (KAP) distribution. KAP has had fewer hydrological applications than GP, but some studies have shown it to merit wider use. The problem of choosing between GP and KAP arises quite often in frequency analyses. This study, by comparing some discrimination methods between these two models, aims to show which method(s) is (are) recommended. Three specific methods are considered: one uses the Anderson-Darling goodness-of-fit (GoF) statistic, another uses the ratio of maximized likelihood (closely related to the Akaike information criterion and the Bayesian information criterion), and the third employs a normality transformation followed by application of the Shapiro-Wilk statistic. We show this last method to be the most recommendable, due to its advantages with sizes typically encountered in hydrology. We apply the simulation results to some flood POT datasets.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR E. Volpi     

Identifying storm flow pathways in a rainforest catchment using hydrological and geochemical modelling

The hydrological model TOPMODEL is used to assess the water balance and describe flow paths for the 9·73 ha Lutz Creek Catchment in Central Panama. Monte Carlo results are evaluated based on their fit to the observed hydrograph, catchment‐averaged soil moisture and stream chemistry. TOPMODEL, with a direct‐flow mechanism that is intended to route water through rapid shallow‐soil flow, matched observed chemistry and discharge better than the basic version of TOPMODEL and provided a reasonable fit to observed soil moisture and wet‐season discharge at both 15‐min and daily time‐steps. The improvement of simulations with the implementation of a direct‐flow component indicates that a storm flow path not represented in the original version of TOPMODEL plays a primary role in the response of Lutz Creek Catchment. This flow path may be consistent with the active and abundant pipeflow that is observed or delayed saturation overland flow. The ‘best‐accepted’ simulations from 1991 to 1997 indicate that around 41% of precipitation becomes direct flow and around 10% is saturation overland flow. Other field observations are needed to constrain evaporative and groundwater losses in the model and to characterize chemical end‐members posited in this paper. Published in 2004 by John Wiley & Sons, Ltd.     

Distributed hydrological modelling of a heavily glaciated Alpine river basin

Abstract

A glacier submodel was successfully integrated into the distributed hydrological model WaSiM-ETH to simulate the discharge of a heavily glaciated drainage basin. The glacier submodel comprises a distributed temperature index model including solar radiation to simulate the melt rate of glaciated areas. Meltwater and rainfall are transformed into glacier discharge by using a linear reservoir approach. The model was tested on a high-alpine sub-basin of the Rhone basin (central Switzerland) of which 48% is glaciated. Continuous discharge simulations were performed for the period 1990–1996 and compared with hourly discharge observations. The pronounced daily and annual fluctuations in discharge were simulated well. The obtained efficiency criterion, R², exceeds 0.89 for all years. The good performance of the glacier submodel is also demonstrated by integrating it into the hydrological model PREVAH.     

Evaluating preprocessing methods of digital elevation models for hydrological modelling

With the introduction of high‐resolution digital elevation models, it is possible to use digital terrain analysis to extract small streams. In order to map streams correctly, it is necessary to remove errors and artificial sinks in the digital elevation models. This step is known as preprocessing and will allow water to move across a digital landscape. However, new challenges are introduced with increasing resolution because the effect of anthropogenic artefacts such as road embankments and bridges increases with increased resolution. These are problematic during the preprocessing step because they are elevated above the surrounding landscape and act as artificial dams. The aims of this study were to evaluate the effect of different preprocessing methods such as breaching and filling on digital elevation models with different resolutions (2, 4, 8, and 16 m) and to evaluate which preprocessing methods most accurately route water across road impoundments at actual culvert locations. A unique dataset with over 30,000 field‐mapped road culverts was used to assess the accuracy of stream networks derived from digital elevation models using different preprocessing methods. Our results showed that the accuracy of stream networks increases with increasing resolution. Breaching created the most accurate stream networks on all resolutions, whereas filling was the least accurate. Burning streams from the topographic map across roads from the topographic map increased the accuracy for all methods and resolutions. In addition, the impact in terms of change in area and absolute volume between original and preprocessed digital elevation models was smaller for breaching than for filling. With the appropriate methods, it is possible to extract accurate stream networks from high‐resolution digital elevation models with extensive road networks, thus providing forest managers with stream networks that can be used when planning operations in wet areas or areas near streams to prevent rutting, sediment transport, and mercury export.     

Capturing the essential spatial variability in distributed hydrological modelling: Infiltration parameters

Selecting the correct resolution in distributed hydrological modelling at the watershed scale is essential in reducing scale-related errors. The work presented herein uses information content (entropy) to identify the resolution which captures the essential variability, at the watershed scale, of the infiltration parameters in the Green and Ampt infiltration equation. A soil map of the Little Washita watershed in south-west Oklahoma, USA was used to investigate the effects of grid cell resolution on the distributed modelling of infiltration. Soil-derived parameters and infiltration exhibit decreased entropy as resolutions become coarser. This is reflected in a decrease in the maximum entropy value for the reclassified/derived parameters vis a vis the original data. Moreover, the entropy curve, when plotted against resolution, shows two distinct segments: a constant section where no entropy was lost with decreasing resolution and another part which is characterized by a sharp decrease in entropy after a critical resolution of 1209 m is reached. This methodology offers a technique for assessing the largest cell size that captures the spatial variability of infiltration parameters for a particular basin. A geographical information system (GIS) based rainfall-runoff model is used to simulate storm hydrographs using infiltration parameter maps at different resolutions as inputs. Model results up to the critical resolution are reproducible and errors are small. However, at resolutions beyond the critical resolution the results are erratic with large errors. A major finding of this study is that a large resolution (1209 m for this basin) yields reproducible model results. When modelling a river basin using a distributed model, the resolution (grid cell size) can drastically affect the model results and calibration. The error structure attributable to grid cell resolution using entropy as a spatial variability measure is shown.