The performance of the reformulated Gash's interception loss model in Mexico's northeastern temperate forests

The quantitative importance of rainfall interception loss and the performance of the reformulated Gash model were evaluated as a function of basal area in Mexico's northeastern temperate forest communities. A sensitivity analysis as well as an iterative search of parameters matched interception loss measurements and assessments and isolated coefficient values that drive the model performance. Set hypothesis was tested with a total of 73 rainfalls recorded on four forest stands with different canopy cover for model fitting (39) and validation (34). The reformulated Gash model predicted well rainfall interception loss because mean deviations between recorded and modelled interception loss as a function of gross rainfall, MD, were <2.6% and 5.3% for fitting and validating parameter data sets, respectively. Basal area was negatively related to the model performance, but maximum projected MD range values can be found in most interception loss studies, for example, <7% when basal area is <5 m² ha^?1. The wet canopy evaporation rate and the canopy storage coefficient drive interception loss and the iterative parameter search showed that high wet canopy evaporation rates were expected in these forests. These parameters must be further studied to physically explain drivers of high wet canopy evaporation rates. Copyright © 2012 John Wiley & Sons, Ltd.     

How to improve the representation of hydrological processes in SWAT for a lowland catchment – temporal analysis of parameter sensitivity and model performance

Model diagnostic analyses help to improve the understanding of hydrological processes and their representation in hydrological models. A detailed temporal analysis detects periods of poor model performance and model components with potential for model improvements, which cannot be found by analysing the whole discharge time series. In this study, we aim to improve the understanding of hydrological processes by investigating the temporal dynamics of parameter sensitivity and of model performance for the Soil and Water Assessment Tool model applied to the Treene lowland catchment in Northern Germany. The temporal analysis shows that the parameter sensitivity varies temporally with high sensitivity for three groundwater parameters (groundwater time delay, baseflow recession constant and aquifer fraction coefficient) and one evaporation parameter (soil evaporation compensation factor). Whereas the soil evaporation compensation factor dominates in baseflow and resaturation periods, groundwater time delay, baseflow recession constant and aquifer fraction coefficient are dominant in the peak and recession phases. The temporal analysis of model performance identifies three clusters with different model performances, which can be related to different phases of the hydrograph. The lowest performance, when comparing six performance measures, is detected for the baseflow cluster. A spatially distributed analysis for six hydrological stations within the Treene catchment shows similar results for all stations. The linkage of periods with poor model performance to the dominant model components in these phases and with the related hydrological processes shows that the groundwater module has the highest potential for improvement. This temporal diagnostic analysis enhances the understanding of the Soil and Water Assessment Tool model and of the dominant hydrological processes in the lowland catchment. Copyright © 2013 John Wiley & Sons, Ltd.     

Integrating the LISFLOOD‐FP 2D hydrodynamic model with the CAESAR model: implications for modelling landscape evolution

Landscape evolution models (LEMs) simulate the geomorphic development of river basins over long time periods and large space scales (100s–1000s of years, 100s of km²). Due to these scales they have been developed with simple steady flow models that enable long time steps (e.g. years) to be modelled, but not shorter term hydrodynamic effects (e.g. the passage of a flood wave). Nonsteady flow models that incorporate these hydrodynamic effects typically require far shorter time steps (seconds or less) and use more expensive numerical solutions hindering their inclusion in LEMs. The recently developed LISFLOOD‐FP simplified 2D flow model addresses this issue by solving a reduced form of the shallow water equations using a very simple numerical scheme, thus generating a significant increase in computational efficiency over previous hydrodynamic methods. This leads to potential convergence of computational cost between LEMs and hydrodynamic models, and presents an opportunity to combine such schemes. This paper outlines how two such models (the LEM CAESAR and the hydrodynamic model LISFLOOD‐FP) were merged to create the new CAESAR‐Lisflood model, and through a series of preliminary tests shows that using a hydrodynamic model to route flow in an LEM affords many advantages. The new model is fast, computationally efficient and has a stronger physical basis than a previous version of the CAESAR model. For the first time it allows hydrodynamic effects (tidal flows, lake filling, alluvial fans blocking valley floor) to be represented in an LEM, as well as producing noticeably different results to steady flow models. This suggests that the simplification of using steady flow in existing LEMs may bias their findings significantly. Copyright © 2013 John Wiley & Sons, Ltd.     

Sensitivity and uncertainty analysis of a sediment transport model: a global approach

Computerized sediment transport models are frequently employed to quantitatively simulate the movement of sediment materials in rivers. In spite of the deterministic nature of the models, the outputs are subject to uncertainty due to the inherent variability of many input parameters in time and in space, along with the lack of complete understanding of the involved processes. The commonly used first-order method for sensitivity and uncertainty analyses is to approximate a model by linear expansion at a selected point. Conclusions from the first-order method could be of limited use if the model responses drastically vary at different points in parameter space. To obtain the global sensitivity and uncertainty features of a sediment transport model over a larger input parameter space, the Latin hypercubic sampling technique along with regression procedures were employed. For the purpose of illustrating the methodologies, the computer model HEC2-SR was selected in this study. Through an example application, the results about the parameters sensitivity and uncertainty of water surface, bed elevation and sediment discharge were discussed.     

Temporal variation of over‐bank flooding of Wei River and its impact on a riparian wetland in Xi'an,China

Over‐bank flooding is one of the driving forces controlling ecological integrity of riparian wetlands. Indentifying natural over‐bank flooding regime and its temporal variations is crucial for developing conservation and restoration plans and making water resources management policies for these ecosystems. Along the midstream of the Wei River in Xi'an, China lies the Jingwei riparian wetland, which was well preserved until the 1970s. Based on historical record of hydrological and morphological data of the Wei River from 1951 to 2000, we analysed temporal variations of over‐bank flooding frequency, duration, and timing in this paper. The natural annual over‐bank flooding regime was identified as having an occurrence frequency of 2·2 times a year and average duration of 5·3 days; these flooding events typically occur between June and September with occasional occurrence in late spring and late autumn. Over‐bank flooding occurrence frequency and duration decreased significantly during the 1990s, seasonal events of over‐bank floods were changed through reduced flooding frequency during summer and disappearing flooding events in late spring and late autumn. Further investigations showed that reduced discharge in the Wei River was the principal cause for these changes in over‐bank flooding dynamics. Our analysis also showed that decreased discharge of the Wei River during the 1990s was attributed near equally to disturbances from human activities and decreased regional precipitation. Results from this study may help reestablish natural over‐bank flooding dynamics in order to ensure successful restoration of Jingwei riparian wetland. Copyright © 2010 John Wiley & Sons, Ltd.     

Hydrological modelling of the Chaohe Basin in China: Statistical model formulation and Bayesian inference

Calibration of hydrologic models is very difficult because of measurement errors in input and response, errors in model structure, and the large number of non-identifiable parameters of distributed models. The difficulties even increase in arid regions with high seasonal variation of precipitation, where the modelled residuals often exhibit high heteroscedasticity and autocorrelation. On the other hand, support of water management by hydrologic models is important in arid regions, particularly if there is increasing water demand due to urbanization. The use and assessment of model results for this purpose require a careful calibration and uncertainty analysis. Extending earlier work in this field, we developed a procedure to overcome (i) the problem of non-identifiability of distributed parameters by introducing aggregate parameters and using Bayesian inference, (ii) the problem of heteroscedasticity of errors by combining a Box–Cox transformation of results and data with seasonally dependent error variances, (iii) the problems of autocorrelated errors, missing data and outlier omission with a continuous-time autoregressive error model, and (iv) the problem of the seasonal variation of error correlations with seasonally dependent characteristic correlation times. The technique was tested with the calibration of the hydrologic sub-model of the Soil and Water Assessment Tool (SWAT) in the Chaohe Basin in North China. The results demonstrated the good performance of this approach to uncertainty analysis, particularly with respect to the fulfilment of statistical assumptions of the error model. A comparison with an independent error model and with error models that only considered a subset of the suggested techniques clearly showed the superiority of the approach based on all the features (i)–(iv) mentioned above.     

Hydrological system analysis and modelling of the Kara River basin (West Africa) using a lumped metric conceptual model

This paper discusses the analysis and modelling of the hydrological system of the basin of the Kara River, a transboundary river in Togo and Benin, as a necessary step towards sustainable water resources management. The methodological approach integrates the use of discharge parameters, flow duration curves and the lumped conceptual model IHACRES. A Sobol sensitivity analysis is performed and the model is calibrated by applying the shuffled complex evolution algorithm. Results show that discharge generation in three nested catchments of the basin is affected by landscape physical characteristics. The IHACRES model adequately simulates the rainfall–runoff dynamics in the basin with a mean modified Nash-Sutcliffe efficiency measure of 0.6. Modelling results indicate that parameters controlling rainfall transformation to effective rainfall are more sensitive than those routing the streamflow. This study provides insights into understanding the catchment’s hydrological system. Nevertheless, further investigations are required to better understand detailed runoff generation processes.

EDITOR M.C. Acreman; ASSOCIATE EDITOR N Verhoest     

Global sensitivity analyses for a complex hydrological model applied in an Alpine watershed

The increasing complexity of hydrological models results in a large number of parameters to be estimated. In order to better understand how these complex models work, efficient screening methods are required in order to identify the most important parameters. This is of particular importance for models that are used within an operational real‐time forecasting chain such as HQsim. The objectives of this investigation are to (i) identify the most sensitive parameters of the complex HQsim model applied in the Alpine Lech catchment and (ii) compare model parameter sensitivity rankings attained from three global sensitivity analysis techniques. The techniques presented are the (i) regional sensitivity analysis, (ii) Morris analysis and (iii) state‐dependent parameter modelling. The results indicate that parameters affecting snow melt as well as processes in the unsaturated soil zone reveal high significance in the analysed catchment. The snow melt parameters show clear temporal patterns in the sensitivity whereas most of the parameters affecting processes in the unsaturated soil zone do not vary in importance across the year. Overall, the maximum degree day factor (meltfunc_max) has been identified to play a key role within the HQsim model. Although the parameter sensitivity rankings are equivalent between methods for a number of parameters, for several key parameters differing results were obtained. An uncertainty analysis demonstrates that a parameter ranking attained from only one method is subjected to large uncertainty. Copyright © 2012 John Wiley & Sons, Ltd.     

Daily streamflow modelling and assessment based on the curve‐number technique

A cell‐based long‐term hydrological model (CELTHYM) that can be integrated with a geographical information system (GIS) was developed to predict continuous stream flow from small agricultural watersheds. The CELTHYM uses a cell‐by‐cell soil moisture balance approach. For surface runoff estimation, the curve number technique considering soil moisture on a daily basis was used, and release rate was used to estimate baseflow. Evapotranspiration was computed using the FAO modified Penman equation that considered land‐use‐based crop coefficients, soil moisture and the influence of topography on radiation. A rice paddy field water budget model was also adapted for the specific application of the model to East Asia. Model sensitivity analysis was conducted to obtain operational information about the model calibration parameters. The CELTHYM was calibrated and verified with measured runoff data from the WS#1 and WS#3 watersheds of the Seoul National University, Department of Agricultural Engineering, in Hwaseong County, Kyounggi Province, South Korea. The WS#1 watershed is comprised of about 35·4% rice paddy fields and 42·3% forest, whereas the WS#3 watershed is about 85·0% forest and 11·5% rice paddy fields. The CELTHYM was calibrated for the parameter release rate, K, and soil moisture storage coefficient, STC, and results were compared with the measured runoff data for 1986. The validation results for WS#1 considering all daily stream flow were poor with R², E² and RMSE having values of 0·40, ?6·63 and 9·69 (mm), respectively, but validation results for days without rainfall were statistically significant (R² = 0·66). Results for WS#3 showed good agreement with observed data for all days, and R², E² and RMSE were 0·92, 0·91 and 2·23 (mm), respectively, suggesting potential for CELTHYM application to other watersheds. The direct runoff and water balance components for watershed WS#1 with significant areas of paddy fields did not perform well, suggesting that additional study of these components is needed. Copyright © 2002 John Wiley & Sons, Ltd.     

Assessing the performance of a physically based hydrological model using a proxy‐catchment approach in an agricultural environment

Physically based models are useful frameworks for testing intervention strategies designed to reduce elevated sediment loads in agricultural catchments. Evaluating the success of these strategies depends on model accuracy, generally established by a calibration and evaluation process. In this contribution, the physically based SHETRAN model was assessed in two similar U.K. agricultural catchments. The model was calibrated on the Blackwater catchment (18 km²) and evaluated in the adjacent Kit Brook catchment (22 km²) using 4 years of 15 min discharge and suspended sediment flux data. Model sensitivity to changes in single and multiple combinations of parameters and sensitivity to changes in digital elevation model resolution were assessed. Model flow performance was reasonably accurate with a Nash–Sutcliffe efficiency coefficient of 0.78 in Blackwater and 0.60 in Kit Brook. In terms of event prediction, the mean of the absolute percentage of difference (μAbs_diff) between measured and simulated flow volume (Qv), peak discharge (Qp), sediment yield (Sy), and peak sediment flux (Sp) showed larger values in Kit Brook (48% [Qv], 66% [Qp], 298% [Sy], and 438% [Sp]) compared with the Blackwater catchment (30% [Qv], 41% [Qp], 106% [Sy], and 86% [Sp]). Results indicate that SHETRAN can produce reasonable flow prediction but performs less well in estimation of sediment flux, despite reasonably similar hydrosedimentary behaviour between catchments. The sensitivity index showed flow volume sensitive to saturated hydraulic conductivity and peak discharge to the Strickler coefficient; sediment yield was sensitive to the overland flow erodibility coefficient and peak sediment flux to raindrop/leaf soil erodibility coefficient. The multiparameter sensitivity analysis showed that different combinations of parameters produced similar model responses. Model sensitivity to grid resolution presented similar flow volumes for different digital elevation model resolutions, whereas event peak and duration (for both flow and sediment flux) were highly sensitive to changes in grid size.     

A two-stage sensitivity analysis for parameter identification and calibration of a physically-based distributed model in a river basin

Hydrological models demand large numbers of input parameters, which are to be optimally identified for better simulation of various hydrological processes. Identifying the most relevant parameters and their values using efficient sensitivity analysis methods helps to better understand model performance. In this study, the physically-based distributed model SHETRAN is used for hydrological simulation on the Netravathi River Basin in south India and the most important parameters are identified using the Morris screening method. Further, the influence of a particular model parameter on streamflow is quantified using local sensitivity analysis and optimal parameters are obtained for calibration of the SHETRAN model. The results demonstrate the capability of two-stage sensitivity analysis, combining qualitative and quantitative methods in the initial screening-out of insignificant model parameters, identifying parameter interactions and quantifying the contribution of each model parameter to the streamflow. The results of the sensitivity analysis simplified the calibration procedure of SHETRAN for the study area.     

Error analysis for the evaluation of model performance: rainfall–runoff event time series data

This paper provides a procedure for evaluating model performance where model predictions and observations are given as time series data. The procedure focuses on the analysis of error time series by graphing them, summarizing them, and predicting their variability through available information (recalibration). We analysed two rainfall–runoff events from the R‐5 data set, and evaluated 12 distinct model simulation scenarios for these events, of which 10 were conducted with the quasi‐physically‐based rainfall–runoff model (QPBRRM) and two with the integrated hydrology model (InHM). The QPBRRM simulation scenarios differ in their representation of saturated hydraulic conductivity. Two InHM simulation scenarios differ with respect to the inclusion of the roads at R‐5. The two models, QPBRRM and InHM, differ strongly in the complexity and number of processes included. For all model simulations we found that errors could be predicted fairly well to very well, based on model output, or based on smooth functions of lagged rainfall data. The errors remaining after recalibration are much more alike in terms of variability than those without recalibration. In this paper, recalibration is not meant to fix models, but merely as a diagnostic tool that exhibits the magnitude and direction of model errors and indicates whether these model errors are related to model inputs such as rainfall. Copyright © 2004 John Wiley & Sons, Ltd.     

Two‐dimensional physically based finite element runoff model for small agricultural watersheds: II. Model testing and field application

Mathematical models are useful analysis tools to understand problems in watersheds associated with runoff, and to find solutions through land use changes and best management practices. However, before a model is applied in the field, it must be tested and checked to ensure that the model represents the real world adequately. In this paper, a two‐dimensional physically based finite element runoff model ROMO2D has been verified and validated by comparing the model output with analytic solution under simplified conditions, published data, and field measurements. Calibration of the model was done manually through a multi‐objective calibration procedure, using observed field data. Before going for field validation/application of ROMO2D, analysis was carried out to determine the optimum number of finite elements into which the watershed should be discretized and the size of the time step. A sensitivity analysis of the model was performed using the observed values of watershed parameters. The model was applied to a 1·45 ha agricultural watershed located in the Shiwalik foothills (India) to simulate runoff. The results demonstrated the potential of the model to simulate runoff from small agricultural watersheds for individual storm events with reasonable accuracy. Copyright © 2008 John Wiley & Sons, Ltd.     

Sensitivity analysis of prior model probabilities and the value of prior knowledge in the assessment of conceptual model uncertainty in groundwater modelling

A key point in the application of multi‐model Bayesian averaging techniques to assess the predictive uncertainty in groundwater modelling applications is the definition of prior model probabilities, which reflect the prior perception about the plausibility of alternative models. In this work the influence of prior knowledge and prior model probabilities on posterior model probabilities, multi‐model predictions, and conceptual model uncertainty estimations is analysed. The sensitivity to prior model probabilities is assessed using an extensive numerical analysis in which the prior probability space of a set of plausible conceptualizations is discretized to obtain a large ensemble of possible combinations of prior model probabilities. Additionally, the value of prior knowledge about alternative models in reducing conceptual model uncertainty is assessed by considering three example knowledge states, expressed as quantitative relations among the alternative models. A constrained maximum entropy approach is used to find the set of prior model probabilities that correspond to the different prior knowledge states. For illustrative purposes, a three‐dimensional hypothetical setup approximated by seven alternative conceptual models is employed. Results show that posterior model probabilities, leading moments of the predictive distributions and estimations of conceptual model uncertainty are very sensitive to prior model probabilities, indicating the relevance of selecting proper prior probabilities. Additionally, including proper prior knowledge improves the predictive performance of the multi‐model approach, expressed by reductions of the multi‐model prediction variances by up to 60% compared with a non‐informative case. However, the ratio between‐model to total variance does not substantially decrease. This suggests that the contribution of conceptual model uncertainty to the total variance cannot be further reduced based only on prior knowledge about the plausibility of alternative models. These results advocate including proper prior knowledge about alternative conceptualizations in combination with extra conditioning data to further reduce conceptual model uncertainty in groundwater modelling predictions. Copyright © 2009 John Wiley & Sons, Ltd.     

Assessment of surface water resources and evapotranspiration in the Haihe River basin of China using SWAT model

Quantitative assessment of surface water resources (SWRs) and evapotranspiration (ET) is essential and significant for reasonably planning and managing water resources in the Haihe River basin which is facing severe water shortage. In this study, a distributed hydrological model of the Haihe River basin was constructed using the Soil and Water Assessment Tool, well considering the reservoirs and agricultural management practices for reasonable simulation. The crop parameters were independently calibrated with the observed crop data at six experimental stations. Then, sensitivity ranks of hydrological parameters were analysed, which suggested the important parameters used for calibration. The model was successfully calibrated using the monthly observed data of discharge in around 1970–1991 and actual ET (ET_a) in 2002–2004 for the mountainous area and Haihe plain, respectively. Meanwhile, good agreements between the simulated and statistical crop yields in 1985–2005 further verified the model's appropriateness. Finally, the calibrated model was used to assess SWRs and ET_a in time and space during 1961–2005. Results showed that the average annual natural SWRs and the ET_a were about 17.5 billion cubic metre and 542 mm, respectively, both with a slight downward trend. The spatial distributions of both SWRs and ET_a were significantly impacted by variations of precipitation and land use. Moreover, the reservoir in operation was the main factor for the noticeable decline of actual SWRs. In the Haihe plain, the ET_a with irrigation was increased by 46% compared with that under rainfed conditions. In addition, this study identified the regions with potential to improve the irrigation effects on water use. Copyright © 2012 John Wiley & Sons, Ltd.     

Application of a wind-driven hydrodynamic model for the quantification of transport in an open boundary canal-lakes system in sw Friesland,The Netherlands

The south western lake district is a part of the boezem, a system of interconnected lakes and canals in the province of Friesland. The lake district has open boundaries with the other part of the boezem system. However, discharges in the boundary canals are unknown. These discharges are needed for modelling the phosphorus dynamics in the study area. Incidental water flow measurements gave a good indication of the complex water transport in the study area, but continuous water flow recording was not possible. Consequently, discharges could not be measured directly. In order to quantify the discharges, the water transport in the area was modelled by the application of a detailed wind-driven hydrodynamic model. In the model hourly mean values of wind data and water levels at the boundary locations were used as forcing functions. Model tuning was done by comparing observed and computed water levels of three stations within the system. This approach is new in surface water systems in The Netherlands. Therefore, a sensitivity analysis was done and it was verified whether the model results were reliable.The sensitivity analysis showed that the sensitivity was low for modifications of the wind exponent value and rather high for the bottom roughness coefficient. Simulations with daily or weekly mean wind and water level data resulted in an undesirable loss of detail. The sensitivity for noise at the imposed water levels at the boundary locations was moderate. The calculated discharges were used as forcing functions for a chloride mass balance model. Calculated chloride concentrations coincided with measured concentrations in three lakes, during three periods. From this it was concluded that the discharges were reliable. The simulations also lead to the quantification of the water balance and water residence times in the lakes.     

基于WRF模式的青藏高原斜坡和平台加热影响亚洲夏季风的模拟研究

青藏高原大地形的热力强迫作用对亚洲夏季风的形成和发展具有重要的影响.本文利用较高分辨率的WRF区域模式,探讨了高原不同区域（斜坡和平台）的地形加热分别对南亚夏季风和东亚夏季风的影响.结果表明：高原南部喜马拉雅山脉的斜坡地形加热对其周围局地的环流形势和降水影响十分明显,是南亚夏季风北支分量形成和维持的主导因子,也是斜坡上气流爬坡和降水发生的必要条件.斜坡加热对东亚夏季风也有明显的增强作用,它不仅加强了中国东部低空西南季风环流,还会造成北部南下的异常干冷空气的响应.斜坡上的地形加热作用也是对流层高层暖中心位置维持在斜坡上空的一个重要原因.而高原平台加热对季风环流和降水的影响虽然没有喜马拉雅山脉斜坡加热那么显著,但是对南亚夏季风的影响范围更广,对经向哈得来环流影响更明显,能够调控高原以外更远处热带洋面上的西南季风环流.通过比较高原不同区域地形加热条件下的多种季风指数,进一步表明了高原地形加热对南亚和东亚夏季风均有增强作用,但是高原不同区域的地形加热对两类夏季风子系统又会产生不一样的影响.     

Evaluation of the Liu model for predicting rainfall interception in forests world‐wide

Simple but effective models are needed for the prediction of rainfall interception under a full range of environmental and management conditions. The Liu model was validated using data published in the literature and was compared with two leading models in the literature: the Rutter and the Gash models. The Liu model was tested against the Rutter model on a single‐storm basis with interception measurements observed from an old‐growth Douglas fir (Pseudotsuga menziesii) forest in Oregon, USA. Simulated results by the Liu model were close to the measurements and comparable to those predicted by the Rutter model. The Liu model was further tested against the Gash model on a multistorm basis. The Gash and Liu models successfully predicted long‐term interception losses from a broad range of 20 forests around the world. Results also indicated that both the Gash and the Liu models could be used to predict rainfall interception using daily rainfall data, although it was assumed in both models that there is only one storm per rain day. The sensitivity of the Liu model to stand storage capacity, canopy gap fraction and evaporation rate from wet canopy surface during rainfall was investigated. Results indicate that the Liu model has the simplest form, least data requirements and comparable accuracy for predicting rainfall interception as compared with the Rutter and the Gash models. Copyright © 2001 John Wiley & Sons, Ltd.     

Identifying advantages and drawbacks of two hydrological models based on a sensitivity analysis: a study in two Chilean watersheds

ABSTRACT

Hydrological modelling has undergone constant growth with the increase in information processing capabilities. Hydrological models have traditionally been used to study the effects of climate change on management and land-use changes and for water resources planning, among other purposes. The aim of this study was to determine and analyse the advantages of the HBV and HYMOD models, which are commonly used in hydrology on daily and monthly time scales. A regional sensitivity analysis was used to compare the processes that take on greater importance at different time scales in the two models. As a result, it was found that quick precipitation–runoff processes prove to be better represented in the HBV model, while slow, time-aggregated processes are better represented by the HYMOD model. This study confirms that both models are adequate for rain-dominated basins, such as those of the study area. Additionally, the HBV model proved to be more robust in comparison to HYMOD.