Application of the SHE to catchments in India Part 2. Field experiments and simulation studies with the SHE on the Kolar subcatchment of the Narmada River

The results of SHE modelling of the 820 km² Kolar catchment in Madhya Pradesh, Central India are presented. The data collection, the associated field investigations, the calibration and the modelling results are discussed along with the assessment of model parameters. Based on the experiences obtained in this study from modelling and field experiments, the necessity of fieldwork and the hydrological realism of the final model representation of the basin are discussed.     

Spatial and temporal dynamics of stream water particulate and dissolved N, P and C forms along a catchment transect, NE Scotland

The dynamics of dissolved and particulate N, P and organic C were examined for field drains, through a headwater (4 km²), into a mesoscale stream (51 km²) and river (1844 km²) catchment. Distributions of N and P forms were similar in the agricultural headwater and field drains; annual P fluxes of particulate and dissolved forms were of equal magnitude, whilst N was dominated by NO₃–N. Across all scales organic P was an important, often dominant, component of the dissolved P. Temporal variation in nutrient concentrations and proportions was greatest in the headwater, where storms resulted in the generation of large concentrations of suspended particulate matter, particulate and dissolved P, particularly following dry periods. The data suggest that groundwater and minor point source inputs to the mesoscale catchment buffered the temporal variability in hydrochemistry relative to the headwater. Summer low flows were associated with large PO₄–P concentrations in the mesoscale catchment at a critical time of biological sensitivity. At the largest river catchment scale, organic forms of C, N and P dominated. Inorganic nutrient concentrations were kept small through dilution by runoff from upland areas and biological processes converted dissolved N and P to particulate forms. The different processes operating between the drain/headwater to the large river scale have implications for river basin management. Given the prevalence of organic and particulate P forms in our catchment transect, the bioavailability of these fractions needs to be better understood.     

An interactive multi-objective optimization framework for groundwater inverse modeling

The groundwater inverse problem of estimating heterogeneous groundwater model parameters (hydraulic conductivity in this case) given measurements of aquifer response (such as hydraulic heads) is known to be an ill-posed problem, with multiple parameter values giving similar fits to the aquifer response measurements. This problem is further exacerbated due to the lack of extensive data, typical of most real-world problems. In such cases, it is desirable to incorporate expert knowledge in the estimation process to generate more reasonable estimates. This work presents a novel interactive framework, called the ‘Interactive Multi-Objective Genetic Algorithm’ (IMOGA), to solve the groundwater inverse problem considering different sources of quantitative data as well as qualitative expert knowledge about the site. The IMOGA is unique in that it looks at groundwater model calibration as a multi-objective problem consisting of quantitative objectives – calibration error and regularization – and a ‘qualitative’ objective based on the preference of the geological expert for different spatial characteristics of the conductivity field. All these objectives are then included within a multi-objective genetic algorithm to find multiple solutions that represent the best combination of all quantitative and qualitative objectives. A hypothetical aquifer case-study (based on the test case presented by Freyberg [Freyberg DL. An exercise in ground-water model calibration and prediction. Ground Water 1988;26(3)], for which the ‘true’ parameter values are known, is used as a test case to demonstrate the applicability of this method. It is shown that using automated calibration techniques without using expert interaction leads to parameter values that are not consistent with site-knowledge. Adding expert interaction is shown to not only improve the plausibility of the estimated conductivity fields but also the predictive accuracy of the calibrated model.     

The impact of land use on stream water quality in Slovakia

In the first part of this paper, the impact of forestry, agriculture and urban activities on the quality of surface water is analysed. Daily data from 15 forest and agricultural experimental catchments of the Institute of Hydrology, Slovak Academy of Sciences are used. It is shown, that the nitrate concentrations in surface water have decreased in Slovakia since 1989 as a result of decreased use of inorganic nitrogen fertilisers (lower intensity of agricultural production in Slovakia owing to recent economic changes). The annual nitrate specific load varies from 5.90 to 110 kg ha⁻¹ year⁻¹, the annual sulphate load varied from 29.16 to 509.60 kg ha⁻¹ year⁻¹ and the annual phosphate load varied from 0.0098 to 0.0224 kg ha⁻¹ year⁻¹ during 1990–1992.

In the second part, a two-step method of three-component hydrograph separation of rain-, soil- and groundwater is proposed. The method is used in the Manelo-Gribov microbasin (O.95 km²) in Eastern Slovakia. The annual contribution of surface runoff in total runoff volume was 57.5%, the contribution of interflow runoff was 21.1%, and the contribution of groundwater was 21.4%, during the period from 1 August to 31 July 1992. A deterministic regression model for predicting daily nitrate concentrations from values of stream daily discharge and flow component data was developed. A set of 1421 modelled NO₃⁻¹ data was compared with the set of measured data.     

Groundwater in the wetlands of the Okavango Delta, Botswana, and its contribution to the structure and function of the ecosystem

The Okavango Delta of northern Botswana is a large (40,000 km²) alluvial fan located at the terminus of the Okavango River. The river discharges about 10 km³ of water onto the fan each year, augmented by about 6 km³ of rainfall, which sustains about 2500 km² of permanent wetland and up to 8000 km² of seasonal wetland. Interaction between this surface water and the groundwater strongly influences the structure and function of the wetland ecosystem. The climate is semi-arid, and only 2% of the water leaves as surface flow and probably very little as groundwater flow. The bulk of the water is lost to the atmosphere. The Okavango River also delivers about 170,000 tonnes of bedload sediment and about 360,000 tonnes of solutes to the Delta each year, most of which are deposited on the fan. Bedload is deposited in the proximal, permanent wetland, whilst much of the solute load is deposited in the seasonal wetland. Notwithstanding the high evapotranspirational loss, saline surface water is rare. Between 80 and 90% of the seasonal flood water infiltrates the ground, recharging the groundwater beneath the flood plains and the many islands on the flood plains. The remainder is lost by evaporation. This groundwater reservoir is transpired into the atmosphere by both aquatic vegetation on the flood plains and terrestrial vegetation on the islands, and the water table is steadily lowered following passage of the seasonal flood. Trees, which are almost exclusively confined to islands, are particularly important, as they lower the water table beneath islands relative to the surrounding wetlands. There is therefore a net flow of groundwater towards islands. Accumulation of dissolved salts in this groundwater leads to precipitation of solutes (mainly of silica and calcite) in the soils beneath island fringes and the islands grow by vertical expansion. Islands are thus an expression of the chemical sedimentation taking place on the fan. Sodium bicarbonate accumulates in the groundwater beneath island centres, and this impacts on the vegetation, leading ultimately to barren island interiors. Dense saline brine thus produced subsides under density-driven flow. This cycling of seasonal flood water through the groundwater reservoir thus plays a key role in creating and maintaining the biological and habitat diversity of the wetland, and inhibits the formation of saline surface water.     

Hydrological modelling for assessing spatio-temporal groundwater recharge variations in the water-stressed Amathole Water Supply System,Eastern Cape,South Africa

To increase the resilience of regional water supply systems in South Africa in the face of anticipated climatic changes and a constant increase in water demand, water supply sources require diversification. Many water-stressed metropolitan regions in South Africa depend largely on surface water to cover their water demand. While climatic and river discharge data is widely available in these regions, information on groundwater resources – which could support supply source diversification – is scarce. Groundwater recharge is a key parameter that is used to estimate groundwater amounts that can be sustainably exploited at a sub-watershed level. Therefore, the objective of this study was to develop a reliable hydrological modelling routine that enables the assessment of regional spatio-temporal variations of groundwater recharge to discern the most promising areas for groundwater development. Accordingly, we present a semi-distributed hydrological modelling approach that incorporates water balance routines coupled with baseflow modelling techniques to yield spatio-temporal variations of groundwater recharge on a regional level. The approach is demonstrated for the actively managed catchment areas of the Amathole Water Supply System situated in a semi-arid part of the Eastern Cape of South Africa. In the investigated study area, annual groundwater recharge exhibits a high spatio-temporal heterogeneity and is estimated to vary between ~0.5% and 8% of annual rainfall. Despite some uncertainties induced by limited data availability, calibration and validation of the model were found to be satisfactory and yielded model results similar to (point) data of annual groundwater recharge reported in earlier studies. Our approach is therefore found to derive crucial information for efficiently targeting more detailed groundwater exploration studies and could work as a blueprint for orientating groundwater potential exploration in similar environments.     

Isotope hydrological study of mean transit times in an alpine basin (Wimbachtal, Germany)

Measurements of tritium and ¹⁸O concentrations in precipitation and runoff were used to provide further insight into the groundwater storage properties of the Wimbachtal Valley, a catchment area of 33.4 km², extending between 636 and 2713 m a.s.l. in the Berchtesgaden Alps. The catchment includes three aquifer types: a dominant porous aquifer; a fractured dolomite; a karstic limestone aquifer. Employing a simple hydrological model, information about mean transit times of environmental tracers is derived for the groundwater runoff component and several karst springs from the application of the exponential and dispersion flow models to the isotopic input and output data. The mean transit times calculated from a dispersion model with transit times of 4.1 years for ¹⁸O and 4.2 years for tritium, which agree well, allow calculation of total (mobile + stagnant) groundwater storage volume, which is equivalent to 6.6 m of water depth. Direct runoff appears negligible as in many other cases.     

PSYCHIC – A process-based model of phosphorus and sediment transfers within agricultural catchments. Part 2. A preliminary evaluation

This paper describes the preliminary evaluation of the PSYCHIC catchment scale (Tier 1) model for predicting the mobilisation and delivery of phosphorus (P) and suspended sediment (SS) in the Hampshire Avon (1715 km²) and Herefordshire Wye (4017 km²) drainage basins, in the UK, using empirical data. Phosphorus and SS transfers to watercourses in the Wye were predicted to be greater than corresponding delivery in the Avon; SS, 249 vs 33 kg ha⁻¹ yr⁻¹; DP, 2.57 vs 1.26 kg ha⁻¹ yr⁻¹; PP, 2.20 vs 0.56 kg ha⁻¹ yr⁻¹. The spatial pattern of the predicted transfers was relatively uniform across the Wye drainage basin, whilst in the Avon, delivery to watercourses was largely confined to the river corridors and small areas of drained land. Statistical performance in relation to predicted exports of P and SS, using criteria for relative error (RE) and root mean square error (RMSE), reflected the potential shortcomings associated with using longer-term climate data for predicting shorter-term (2002–2004) catchment response and the need to refine calculations of point source contributions and to incorporate additional river basin processes such as channel bank erosion and in-stream geochemical processing. PSYCHIC is therefore best suited to characterising longer-term catchment response.     

A groundwater-based, objective-heuristic parameter optimisation method for a precipitation-runoff model and its application to a semi-arid basin

A hydrologic model calibration methodology that is based on groundwater data is developed and implemented using the US Geological Survey's precipitation-runoff modelling system (PRMS) and the modular modelling system (MMS), which performs automatic calibration of parameters. The developed methodology was tested in the Akrotiri basin, Cyprus. The necessity for the groundwater-based model calibration, rather than a typical runoff-based one, arose from the very intermittent character of the runoff in the Akrotiri basin, a case often met in semi-arid regions. Introducing a datum and converting groundwater storage to head made the observable groundwater level the calibration indicator. The modelling of the Akrotiri basin leads us to conclude that groundwater level is a useful indicator for hydrological model calibration that can be potentially used in other similar situations in the absence of river flow measurements. However, the option of an automatic calibration of the complex hydrologic model PRMS by MMS did not ensure a good outcome. On the other hand, automatic optimisation, combined with heuristic expert intervention, enabled achievement of good calibration and constitutes a valuable means for saving effort and improving modelling performance. To this end, results must be scrutinised, melding the viewpoint of physical sense with mathematical efficiency criteria. Thus optimised, PRMS achieved a low simulation error, good reproduction of the historic trend of the aquifer water level evolution and reasonable physical behaviour (good hydrologic balance, Reasonable match of aquifer level evolution, good estimation of mean natural recharge rate).     

基于GRACE的空间约束方法监测华北平原地下水储量变化

华北平原作为我国重要的工农业基地和政治经济中心,面临着严重的水资源危机.因此,开展对华北平原地下水储量变化的监测工作具有重要现实意义与科学价值.本文基于GRACE重力卫星的空间约束方法,研究了华北平原地下水储量变化的时空分布规律,并与地面水井实测与地下水模型结果进行了综合比较和分析.结果表明:2002-2014年,华北平原地下水存在明显的长期亏损,GRACE估计的亏损速率为-7.4±0.9 km~3·a~(-1),而地面水井资料估计的浅层地下水亏损速率为-1.2 km~3·a~1,对比两者之间的差异可以发现,华北平原的地下水亏损以深层地下水为主.2002-2008年,GRACE估计的华北平原地下水亏损速率为-5.3±2.2 km~3·a~(-1),这与华北平原两个地下水模型得到的平均亏损速率-5.4 km~3·a~(-1)十分吻合.通过华北平原区域地下水模型的独立验证,说明GRACE可以有效评估华北平原的地下水储量变化趋势.除了长期亏损的趋势项之外,华北平原地下水还存在明显的年际变化特征,并与该地区年降雨量变化特征一致.在降雨偏少的2002年、2005-2009年和2014年,华北平原地下水储量显著减少.在空间分布上,GRACE结果表明,华北平原的地下水储量减少主要发生在山前平原和中部平原区,这也与水井实测资料和区域地下水模型结果较为吻合.与GRACE和区域地下水模型相比,目前的全球水文模型仍无法准确估计华北平原地下水变化的空间分布和亏损速率.上述研究表明,GRACE提供了评估华北平原地下水储量变化的重要监测手段.     

CTBTO监测台站发展及其对朝鲜6次核试验的监测与分析

概述CTBTO监测系统及发展过程中对朝鲜6次核试验的爆炸记录、分析、判断、声明和应对措施。地震台阵/站是CTBTO监测系统的重要组成部分,随着核证地震台阵/站的不断增加,国际监测系统IMS对朝鲜核试验的定位误差椭圆面积逐渐缩小,从2006年的880 km²降低到2017年的110 km²。通过对朝鲜核爆炸事件的记录、分析和判断,证明了该系统的可靠性、技术能力及其设计价值,即接收和审查特定事件数据,并向禁核试签署国提供高质量数据信息,使其能够做出正确判断。     

Sensitivity analyses of a distributed catchment model to verify the model structure

Sensitivity analyses are valuable tools for identifying important model parameters, testing the model conceptualization, and improving the model structure. They help to apply the model efficiently and to enable a focussed planning of future research and field measurement. Two different methods were used for sensitivity analyses of the complex process-oriented model TAC^D (tracer aided catchment model, distributed) that was applied to the meso-scale Brugga basin (40 km²) and the sub-basin St Wilhelmer Talbach (15.2 km²). Five simulations periods were investigated: two summer events, two snow melt induced events and one summer low flow period. The model was applied using 400 different parameter sets, which were generated by Monte Carlo simulations using latin hypercube sampling. The regional sensitivity analysis (RSA) allowed determining the most significant parameters for the complete simulation periods using a graphical method. The results of the regression-based sensitivity analysis were more detailed and complex. The temporal variability of the simulation sensitivity could be observed continuously and the significance of the parameters could be determined in a quantitative way. A dependency of the simulation sensitivity on initial- and boundary conditions and the temporal and spatial variability of the sensitivity to some model parameters was revealed by the regression-based sensitivity analysis. Thus, the difficulty of transferring the results to different time periods or model applications in other catchments became obvious. The analysis of the temporal course of the simulation sensitivity to parameter values in conjunction with simulated and measured additional data sets (precipitation, temperature, reservoir volumes etc.) gave further insight into the internal model behaviour and demonstrated the plausibility of the model structure and process conceptionalizations.     

Hydrological modelling of Ethiopian catchments using limited data

The hydrological component of the soil and water assessment tool (SWAT) model is adapted for two Ethiopian catchments based on primary knowledge of the coherence spectrum between rainfall and stream flow data. Spectrum analysis using the available nearby climatic data is made to limit the temporal and spatial scales (inverse rate coefficients) subject to the calibration of compartmentalized runoff models. The exclusion of unwarranted time scales in the calibration implies that the model efficiency (r² values) decrease only moderately between calibration and validation, and the optimization is focused on warranted problems. On the basis of the available data for the two Ethiopian catchments, the implication is that only periods longer than about 50 days can be reliably evaluated in the model. The model structure of SWAT for the surface runoff and groundwater flow response is modified to make the time scales consistent with the results of the spectrum analysis. An optimization algorithm is developed to constrain and combine the model parameters with the spectrum analysis results. Copyright © 2009 John Wiley & Sons, Ltd.     

Impact of anticipated climate change on direct groundwater recharge in a humid tropical basin based on a simple conceptual model

A simple conceptual semi‐distributed modelling approach for assessing the impacts of climate change on direct groundwater recharge in a humid tropical river basin is investigated. The study area is the Chaliyar river basin in the state of Kerala, India. Many factors affecting future groundwater recharge include decrease or increase in precipitation and temperature regimes, coastal flooding, urbanization and changes in land use. The model is based on the water‐balance concept and links the atmospheric and hydrogeologic parameters to different hydrologic processes. It estimates daily water‐table fluctuation and is calibrated and validated using 10 years of data. Data for the first 6 years (2000 to 2005) is used for model calibration, and data for the remaining four years (2006 to 2009) is used for validation. For assessing the impact of predicted climate change on groundwater recharge during the period 2071–2100, temperature and precipitation data in two post climate change scenarios, A2 and B2, were predicted using the Regional Climate Model (RCM), PRECIS (Providing Regional Climates for Impact Studies). These data were then corrected for biases and used in a hydrologic model to predict groundwater recharge in the post climate change scenario. Due to lack of reliable data and proper knowledge as to the magnitude and extent of future climatic changes, it may not be possible to include all the possible effects quantitatively in groundwater recharge modelling. However, the study presents a scientific method to assess the impact of predicted climate change on groundwater recharge and would help engineers, hydrologists, administrators and planners to devise strategies for the efficient use as well as conservation of freshwater resources. Copyright © 2011 John Wiley & Sons, Ltd.     

Effect of single and multi-site calibration techniques on hydrological model performance,parameter estimation and predictive uncertainty: a case study in the Logone catchment,Lake Chad basin

Understanding hydrological processes at catchment scale through the use of hydrological model parameters is essential for enhancing water resource management. Given the difficulty of using lump parameters to calibrate distributed catchment hydrological models in spatially heterogeneous catchments, a multiple calibration technique was adopted to enhance model calibration in this study. Different calibration techniques were used to calibrate the Soil and Water Assessment Tool (SWAT) model at different locations along the Logone river channel. These were: single-site calibration (SSC); sequential calibration (SC); and simultaneous multi-site calibration (SMSC). Results indicate that it is possible to reveal differences in hydrological behavior between the upstream and downstream parts of the catchment using different parameter values. Using all calibration techniques, model performance indicators were mostly above the minimum threshold of 0.60 and 0.65 for Nash Sutcliff Efficiency (NSE) and coefficient of determination (R ²) respectively, at both daily and monthly time-steps. Model uncertainty analysis showed that more than 60% of observed streamflow values were bracketed within the 95% prediction uncertainty (95PPU) band after calibration and validation. Furthermore, results indicated that the SC technique out-performed the other two methods (SSC and SMSC). It was also observed that although the SMSC technique uses streamflow data from all gauging stations during calibration and validation, thereby taking into account the catchment spatial variability, the choice of each calibration method will depend on the application and spatial scale of implementation of the modelling results in the catchment.     

Inverse methods in hydrogeology: Evolution and recent trends

Parameter identification is an essential step in constructing a groundwater model. The process of recognizing model parameter values by conditioning on observed data of the state variable is referred to as the inverse problem. A series of inverse methods has been proposed to solve the inverse problem, ranging from trial-and-error manual calibration to the current complex automatic data assimilation algorithms. This paper does not attempt to be another overview paper on inverse models, but rather to analyze and track the evolution of the inverse methods over the last decades, mostly within the realm of hydrogeology, revealing their transformation, motivation and recent trends. Issues confronted by the inverse problem, such as dealing with multiGaussianity and whether or not to preserve the prior statistics are discussed.     

Parameter Estimation for Groundwater Models under Uncertain Irrigation Data

The success of modeling groundwater is strongly influenced by the accuracy of the model parameters that are used to characterize the subsurface system. However, the presence of uncertainty and possibly bias in groundwater model source/sink terms may lead to biased estimates of model parameters and model predictions when the standard regression‐based inverse modeling techniques are used. This study first quantifies the levels of bias in groundwater model parameters and predictions due to the presence of errors in irrigation data. Then, a new inverse modeling technique called input uncertainty weighted least‐squares (IUWLS) is presented for unbiased estimation of the parameters when pumping and other source/sink data are uncertain. The approach uses the concept of generalized least‐squares method with the weight of the objective function depending on the level of pumping uncertainty and iteratively adjusted during the parameter optimization process. We have conducted both analytical and numerical experiments, using irrigation pumping data from the Republican River Basin in Nebraska, to evaluate the performance of ordinary least‐squares (OLS) and IUWLS calibration methods under different levels of uncertainty of irrigation data and calibration conditions. The result from the OLS method shows the presence of statistically significant (p < 0.05) bias in estimated parameters and model predictions that persist despite calibrating the models to different calibration data and sample sizes. However, by directly accounting for the irrigation pumping uncertainties during the calibration procedures, the proposed IUWLS is able to minimize the bias effectively without adding significant computational burden to the calibration processes.     

Estimating River Conductance from Prior Information to Improve Surface‐Subsurface Model Calibration

Most groundwater models simulate stream‐aquifer interactions with a head‐dependent flux boundary condition based on a river conductance (CRIV). CRIV is usually calibrated with other parameters by history matching. However, the inverse problem of groundwater models is often ill‐posed and individual model parameters are likely to be poorly constrained. Ill‐posedness can be addressed by Tikhonov regularization with prior knowledge on parameter values. The difficulty with a lumped parameter like CRIV, which cannot be measured in the field, is to find suitable initial and regularization values. Several formulations have been proposed for the estimation of CRIV from physical parameters. However, these methods are either too simple to provide a reliable estimate of CRIV, or too complex to be easily implemented by groundwater modelers. This paper addresses the issue with a flexible and operational tool based on a 2D numerical model in a local vertical cross section, where the river conductance is computed from selected geometric and hydrodynamic parameters. Contrary to other approaches, the grid size of the regional model and the anisotropy of the aquifer hydraulic conductivity are also taken into account. A global sensitivity analysis indicates the strong sensitivity of CRIV to these parameters. This enhancement for the prior estimation of CRIV is a step forward for the calibration and uncertainty analysis of surface‐subsurface models. It is especially useful for modeling objectives that require CRIV to be well known such as conjunctive surface water‐groundwater use.     

Parameter identification and uncertainty analysis for simulating streamflow in a river basin of Eastern India

Uncertainty is inherent in modelling studies. However, the quantification of uncertainties associated with a model is a challenging task, and hence, such studies are somewhat limited. As distributed or semi‐distributed hydrological models are being increasingly used these days to simulate hydrological processes, it is vital that these models should be equipped with robust calibration and uncertainty analysis techniques. The goal of the present study was to calibrate and validate the Soil and Water Assessment Tool (SWAT) model for simulating streamflow in a river basin of Eastern India, and to evaluate the performance of salient optimization techniques in quantifying uncertainties. The SWAT model for the study basin was developed and calibrated using Parameter Solution (ParaSol), Sequential Uncertainty Fitting Algorithm (SUFI‐2) and Generalized Likelihood Uncertainty Estimation (GLUE) optimization techniques. The daily observed streamflow data from 1998 to 2003 were used for model calibration, and those for 2004–2005 were used for model validation. Modelling results indicated that all the three techniques invariably yield better results for the monthly time step than for the daily time step during both calibration and validation. The model performances for the daily streamflow simulation using ParaSol and SUFI‐2 during calibration are reasonably good with a Nash–Sutcliffe efficiency and mean absolute error (MAE) of 0.88 and 9.70 m³/s for ParaSol, and 0.86 and 10.07 m³/s for SUFI‐2, respectively. The simulation results of GLUE revealed that the model simulates daily streamflow during calibration with the highest accuracy in the case of GLUE (R² = 0.88, MAE = 9.56 m³/s and root mean square error = 19.70 m³/s). The results of uncertainty analyses by SUFI‐2 and GLUE were compared in terms of parameter uncertainty. It was found that SUFI‐2 is capable of estimating uncertainties in complex hydrological models like SWAT, but it warrants sound knowledge of the parameters and their effects on the model output. On the other hand, GLUE predicts more reliable uncertainty ranges (R‐factor = 0.52 for daily calibration and 0.48 for validation) compared to SUFI‐2 (R‐factor = 0.59 for daily calibration and 0.55 for validation), though it is computationally demanding. Although both SUFI‐2 and GLUE appear to be promising techniques for the uncertainty analysis of modelling results, more and more studies in this direction are required under varying agro‐climatic conditions for assessing their generic capability. Copyright © 2015 John Wiley & Sons, Ltd.     

Choosing an arbitrary calibration period for hydrologic models: How much does it influence water balance simulations?

The selection of calibration and validation time periods in hydrologic modelling is often done arbitrarily. Nonstationarity can lead to an optimal parameter set for one period which may not accurately simulate another. However, there is still much to be learned about the responses of hydrologic models to nonstationary conditions. We investigated how the selection of calibration and validation periods can influence water balance simulations. We calibrated Soil and Water Assessment Tool hydrologic models with observed streamflow for three United States watersheds (St. Joseph River of Indiana/Michigan, Escambia River of Florida/Alabama, and Cottonwood Creek of California), using time period splits for calibration/validation. We found that the choice of calibration period (with different patterns of observed streamflow, precipitation, and air temperature) influenced the parameter sets, leading to dissimilar simulations of water balance components. In the Cottonwood Creek watershed, simulations of 50-year mean January streamflow varied by 32%, because of lower winter precipitation and air temperature in earlier calibration periods on calibrated parameters, which impaired the ability for models calibrated to earlier periods to simulate later periods. Peaks of actual evapotranspiration for this watershed also shifted from April to May due to different parameter values depending on the calibration period's winter air temperatures. In the St. Joseph and Escambia River watersheds, adjustments of the runoff curve number parameter could vary by 10.7% and 20.8%, respectively, while 50-year mean monthly surface runoff simulations could vary by 23%–37% and 169%–209%, depending on the observed streamflow and precipitation of the chosen calibration period. It is imperative that calibration and validation time periods are chosen selectively instead of arbitrarily, for instance using change point detection methods, and that the calibration periods are appropriate for the goals of the study, considering possible broad effects of nonstationary time series on water balance simulations. It is also crucial that the hydrologic modelling community improves existing calibration and validation practices to better include nonstationary processes.