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This paper considers what we know about the potential for disinformation in hydrological data when used for the evaluation of hydrological models. This will generally arise from epistemic uncertainties associated with hydrological observations, particularly from nonstationary or extrapolated rating curves for discharges, and poor rainfall and snowmelt information when interpolated over basin areas. Approaches based on information theory are not well suited to consideration of such epistemic uncertainties in model evaluation and an alternative approach based on setting limits of acceptability independent of any model runs is suggested. This allows for both the rejection of all models tried, and for acceptability of models across different model structures and parameter sets. The paper concludes with some suggestions for future research on defining disinformative data for both point and spatial observables, studying model failures, and defining new observations with a view to having the greatest impact on reducing model uncertainties. [ABSTRACT FROM AUTHOR]

Calibration and regionalization are two key tasks in hydrological modelling, and the availability of increased data and computing resources has enhanced our ability to complete these tasks. This paper addresses both tasks, i.e. (i) it proposes novel model structure-based calibration strategies with the goal to improve estimation of high streamflows, and (ii) it explores the association of soil hydraulic properties with optimal parameters to estimate streamflows in ungauged catchments. Both tasks are demonstrated by employing a conceptual hydrological model, Sacramento Soil Moisture Accounting (SAC-SMA), on multiple catchments in the Narmada River Basin. The initial calibrated model exhibited good model performance, with high flows being underestimated. Seven calibration strategies via revising parameter space are explored, and improvement in high flow performance is observed at nine out of 12 catchments. Estimated streamflows based on soil hydraulic parameters demonstrate regionalization potential. The results indicate successful application of the proposed methods which are transferable to other basins. [ABSTRACT FROM AUTHOR]

Natural streamflow data is required in many hydrological applications. However, many basins are located in data-scarce regions or are impacted by human construction and activities. In this paper, we explore three machine learning algorithms, namely artificial neural networks, random forest and light gradient boosting machine, to simultaneously estimate all the parameters of the coupled modèle du Génie Rural à 4 paramètres Journaliers (GR4J) and snow accounting routine called CemaNeige model. A database of 675 basins in the USA and Quebec is used to train and test ensembles. After using the estimated parameters in GR4J, the resulting naturalized streamflow series are compared with those obtained by the established drainage area ratio and spatial proximity transfer methods in 11 test basins. The results indicate that the machine learning algorithms outperform the drainage area ratio and spatial proximity transfer methods. Among machine learning algorithms, random forests obtain lower (better) continuous ranked probability scores than the other methods for 10 out of 11 test basins. [ABSTRACT FROM AUTHOR]

The Iberian Peninsula is a climate change hotspot, where the temperature is increasing faster than the global annual mean surface temperature, with the largest reduction of precipitation. Consequently, freshwater availability is expected to decrease substantially. In this context, freshwater systems are especially vulnerable in terms of meeting the water demands and ecosystem requirements we know today. In this paper, we present an extension of the eco-engineering decision scaling (EEDS) method to explore trade-offs in agricultural and ecologic metrics at the catchment scale across a range of unknown future hydrological and climate states. The extended EEDS method evaluates current water resource management rules focusing on agricultural and ecologic objectives, identifies climate hazards that make the system fail and assesses climate risk in three time horizons for the design of adaptation measures. The case study is the Serpis River basin, Spain, where 72% of available water is used for agricultural purposes. [ABSTRACT FROM AUTHOR]

Rainfall is considered a major input in designing stormwater management measures, especially for any low-impact development (LID) control design. With the impact of climate change, rainfall frequency and its patterns are changing continuously. Quantification of these changes and their impact on the performance of LID design becomes crucial. This paper presents a methodology to quantify the change in rainfall patterns using the Coupled Model Intercomparison Project 5 (CMIP5) climate model and to select the most feasible LID for a catchment with haphazard development. Interconnected decentralization-based LID controls are evaluated with the objective of emulating a pre-urbanized scenario. The overall analyses indicated that green roof (GR) followed by infiltration trenches (IT), rooftop disconnection (RTD), and permeable pavement (PP) showed better performance. Furthermore, a combination of IT, PP, and RTD accomplishes better efficiency for extreme rainfall events. Implementation of the most feasible combination will provide the additional benefit of water recycle and reuse. [ABSTRACT FROM AUTHOR]

This paper investigates how hydrological drought affected suspended sediment yield (SSY) in the Mediterranean Ofanto River basin, southern Italy, and in its five sub-basins from 1951 to 1989. The Standardized Precipitation Evaporation Index over a scale of 12 months (SPEI12) has been used to compute the hydrological drought in the investigated span of time. SPEI12, mean and maximum monthly discharge (Qmean and Qmax), monthly rainfall erosivity, monthly simple daily intensity index and monthly SSY were used to assess the relationships between dry/wet cycles, streamflow and SSY through the Pearson correlation matrix. Qmean and Qmax are significantly correlated with SSY, while SPEI12 and rainfall intensity do not show good correlation with SSY. Furthermore, from the overall analyses it emerges that sediment yield estimations were higher mainly during the wet period following a period of drought or during a drought period. [ABSTRACT FROM AUTHOR]

This paper presents a numerical test problem that was used as the basis for ranking the river basin management models that participated in a tender for a World Bank-funded project in India. The problem is deterministic, and it involves a set of constraints and management objectives that were of interest to the Narmada Control Authority. The test problem had five reservoirs, seven off-stream and four on-stream water demands, steady-state inflows based on a 10-daily time step over a period of nine years, and relatively simple reservoir operating rules. The paper describes the problem and discusses the solutions that were obtained from various vendors. The principal finding is that simulation models should not be used to solve optimization problems. The paper also highlights the importance of establishing benchmarks as an important tool for model evaluation. Input data and the current benchmark solution are available for download. [ABSTRACT FROM AUTHOR]

This review paper focuses on the question of what will happen to the future water resource system of Grand Renaissance Dam of Ethiopia based on the projected hydrology of the Upper Blue Nile River basin. For this, the hydrological extremes, the baseline hydrological trends, and projected hydrological extremes of the Upper Blue Nile River basin were reviewed from various published and unpublished sources. Changes in the future hydrology of the Upper Blue Nile River basin due to climate change or any other natural or manmade modification of the river basin deserve concerted attention in the future water resources system of the Grand Renaissance Dam of Ethiopia, because the water resources of the dam mainly depend on the water potential nature of the Upper Blue Nile River basin. [ABSTRACT FROM AUTHOR]

In the present paper, we propose a new approach for monthly streamflow prediction based on the extreme learning machine (ELM) and the metaheuristic bat algorithm (Bat-ELM). The performance of the Bat-ELM was compared to that of ELM, support vector regression (SVR), Gaussian process regression (GPR), multilayer perceptron neural network (MLPNN), and generalized regression neural network (GRNN). The proposed models were applied using data from three hydrometric stations located in the Cheliff Basin, Algeria. The results showed that the Bat-ELM was more satisfactory than the standalone models. The Bat-ELM achieved the highest numerical performance with correlation coefficient and Nash-Sutcliffe efficiency ranging from 0.927 to 0.973 and from 0.846 to 0.944, respectively, much higher than the respective values obtained using the MLPNN, GRNN, SVR, GPR and ELM approaches. The obtained results demonstrate that the Bat-ELM is an interesting alternative algorithm for predicting high and extreme streamflow. [ABSTRACT FROM AUTHOR]

Assessment of the spatial and temporal distribution of surface water balance (SWB) components for a river basin having complex topography with limited observed data is challenging. This paper focused on estimating the spatial-temporal variability of long-term average monthly, seasonal, and annual SWB components using the modified Water Energy Transfer between Soil, Plants, and Atmosphere in Steady State (WetSpass-M) physically based hydrological model in Ethiopia's data-scarce Omo River basin. Further, the model output was used for estimating the spatial variation of the average monthly crop water deficit. A sensitivity analysis was performed on the global and local parameters of the model for analysing the relative variation in the SWB components. It was found that actual evapotranspiration (AET) and interception are insensitive to average rainfall intensity while surface runoff is highly sensitive. The variation of SWB under different combinations of land-use/land cover (LU/LC) and soil type indicates that SWB types such as surface runoff, AET, and interception are influenced more by LU/LC than by soil type. [ABSTRACT FROM AUTHOR]

This paper proposes runoff models based on machine learning to estimate daily streamflows in Oued Sebaou watershed, a Mediterranean coastal basin located in northern Algeria. Therefore, we applied random forest (RF), artificial neural networks (ANN – under different training algorithms), and locally weighted linear regression (LWLR) using as input combinations of current and past rainfall amounts and previous values of streamflow. We selected streamflow and rainfall records to calibrate and validate the stated approaches. We used root mean square error (RMSE) and correlation coefficient (R) to evaluate the accuracy of the models. Analyses of the results show that RF provided the best outcomes for both training (RMSE = 4.7458 and R = 0.9834) and validation (RMSE = 2.3617 and R = 0.9719). The ANN calibrated with the Levenberg-Marquardt algorithm presented the second-best result, outperforming its counterparts and LWLR. [ABSTRACT FROM AUTHOR]

This paper presents an evaluation of the parameter sensitivity of a process-based model at the global scale using large-sample data. The analysis was carried out using the HYdrological Prediction of the Environment (HYPE) model, for which soil and snow parameters were evaluated using 187 river flow gauges spread worldwide. As a result, 6 out of 12 soil parameters and 7 out of 10 snow parameters were found to be sensitive. Taking advantage of the global dataset, an additional analysis was used to investigate links between catchment characteristics and parameter sensitivity. Different patterns of sensitivity were observed for different Köppen climate classes, which indicates that parameter regionalization would benefit from calibration based on climate zones. This numerical sensitivity method was compared with the judgement of a set of expert HYPE modellers to understand how numerical results compare with modellers' experience. [ABSTRACT FROM AUTHOR]

This paper focuses on the development of a robust accurate streamflow prediction model by balancing the abilities of exploitation and exploration to find the best parameters of a machine learning model. To do so, the simulated annealing (SA) algorithm is integrated with the mayfly optimization algorithm (MOA) as SAMOA to determine the optimal hyper-parameters of support vector regression (SVR) to overcome the exploration weakness of the MOA method. The proposed method is compared with the classical SVR and hybrid SVR-MOA. To examine the accuracy of the selected methods, monthly hydroclimatic data from Jhelum River Basin is used to predict the monthly streamflow on the basis of RMSE, MAE, NSE, and R2 indices. Test results show that the SVR-SAMOA outperformed the SVR-MOA and SVR models. SVR-SAMOA reduced the prediction errors of the SVR-MOA and SVR models by decreasing the RMSE and the MSE from 21.4% to 14.7% and from 21.7% to 15.1%, respectively, in the test stage. [ABSTRACT FROM AUTHOR]

This paper analyses decadal climate phenomena and the phases of the Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO), and assesses the climate–water–energy nexus at the reservoir system of the São Francisco River Basin (SFRB), Brazil. This study brings a non-traditional approach focused on the link between climatic patterns and hydrological processes and their social-economic consequences, such as their effect on energy production. The methodology used data from the precipitation, natural streamflow, and AMO and PDO series. These variables were evaluated by wavelet transform analysis (WTA), flow duration curve (FDC), streamflow that is equalled or exceed ed 90% of the time (Q90), the reliability index (RI) for different demands and the hydropower generated. The results suggest that the WTA for the SFRB was more significant on the inter-annual scale, and the period with opposite phases of AMO(−) and PDO(+) showed the highest values of FDC, Q90, RI and hydropower generated simulated for the SFRB. [ABSTRACT FROM AUTHOR]

Socio-hydrology has recently garnered attention as a promising research paradigm among hydrologists. In this paper, we argue that viewing the socio-hydrological systems as a network of causal factors can assist in these efforts by revealing emergent properties of socio-hydrological systems. These factors, which are neither actors nor affiliations but symbolic representations of miscellaneous phenomena, represent the key variables affecting socio-hydrological system behaviour. Despite being crucial for understanding system dynamics, these factors are not captured by most equations of coupled human–water coevolutionary models. To demonstrate our method, we use qualitative case study research to analyse the Jaguaribe Basin in Ceará State-Brazil as a network of factors, i.e. mental conceptions, and representations of water resource management experts. We show that most results are unsurprising, exhibiting expected causal relationships. However, there was at least one unexpected result, which showed that the variable "conflict" was the single most sensitive variable to systemic evolution. [ABSTRACT FROM AUTHOR]

This paper presents a hybrid approach for stormwater runoff modelling and pollutant load estimation in a hilly catchment. The stormwater runoff hydrograph was simulated by developing a conceptual hybrid model (HM) using transfer function. Model parameters were estimated by non-linear optimization. The simulated runoff hydrographs showed an excellent match with the observed data. Next, a relationship was developed between runoff and pollutant load and the developed relationship was used for estimation of pollutant load. A novelty of this hybrid approach is that it could bring out a generic HM. By using the derived model, the pollutant load was successfully predicted from simulated runoff (R2 > 0.75) by considering rainfall as the only input. In addition, assessment, characterization and analysis of the first flush of urban runoff also form part of the study. The HM was tested and validated by applying it to 25 storm events monitored during two monsoon seasons in the Nainital Lake catchment (approx. 1900 m a.m.s.l.), India. [ABSTRACT FROM AUTHOR]

This paper investigates conventional and soft-computing methods for the estimation of suspended sediment concentration (SSC) and load (SSL) in rivers. Frequently used methods of sediment rate curve (SRC) and multi-nonlinear regression, and soft-computing methods of multi-layer perceptron, multi-linear regression and adaptive neuro-fuzzy inference system are implemented using various hydrological and hydraulic parameters for the Little Kickapoo Creek Watershed, Illinois, USA. All methods performed equally well in the estimation of SSL, without any noticeable outperformance from any from the methods. However, the application of soft-computing methods decreased SSC estimation errors considerably as compared to the results of SRC. The results are significant in the way they reconcile traditionally used hydrological parameters into the soft-computing methods. Overall, soft-computing methods are recommended for the estimation of SSC in rivers because of their reasonably better performance and ease of implementation. [ABSTRACT FROM AUTHOR]

Water from the alluvium of ephemeral rivers in Zimbabwe is increasingly being used. These alluvial aquifers are recharged annually from infiltrating floodwater. Nonetheless, the size of this water resource is not without limit and an understanding of the hydrological processes of an alluvial aquifer is required for its sustainable management. This paper presents the development of a water balance model, which estimates the water level in an alluvial aquifer recharged by surface flow and rainfall, while allowing for abstraction, evaporation and other losses. The model is coupled with a watershed model, which generates inflows from upland catchment areas and tributaries. Climate, hydrological, land cover and geomorphological data were collected as inputs to both models as well as observed flow and water levels for model calibration and validation. The sand river model was found to be good at simulating the observed water level and was most sensitive to porosity and seepage. [ABSTRACT FROM AUTHOR]

Current estimations of sediment transport at the watershed scale are limited by the difficulty of accurately simulating the sediment transfer along the main stem. The typical approach to simulating watershed sediment transport involves the adoption of hydrologic sediment routing schemes that do not fully capture the contribution and timing of side tributaries, and the inclusion of a simplified channel geometry that does not include its hydraulic feedback. In this paper, we present the results of a coupled hydrologic-hydraulic model of sediment transport applied to a small watershed of Iowa. The model was developed to simulate both the hydrologic network and non-equilibrium sediment transport that occur during a flood. The model results highlight the importance of including side tributaries in order to capture a realistic duration of shear stress that ultimately affects sediment transport. Comparisons with bank erosion measurements indicate that the presented approach is also promising to estimate sediment sources along the main stem. [ABSTRACT FROM AUTHOR]

Determining the catchment design peak flow is crucial in hydrological practice. In this paper, the conceptual rainfall–runoff model EBA4SUB (Event-Based Approach for Small and Ungauged Basins) was applied in six catchments in Iran. The aims were to test EBA4SUB in reconstructing runoff hydrographs for the investigated case studies and to provide a suitable alternative for the review and updating of design peak flow estimation in Iran. The EBA4SUB output was compared with previous studies on selected catchments. The results show, for all case studies, a large variability in the peak flow values; the EBA4SUB model gave flow values similar to the other methodologies. The EBA4SUB model can be recommended for the following reasons: (i) it minimizes the subjectivity of the modeller. (ii) its modules are based on state-of-the-art procedures, which have been appropriately optimized for ungauged basins; and (iii) it furnishes the whole design flood hydrograph. [ABSTRACT FROM AUTHOR]

The objective of this paper is to understand how the natural dynamics of a time-varying catchment, i.e. the rainfall pattern, transforms the random component of rainfall and how this transformation influences the river discharge. To this end, this paper develops a rainfall–runoff modelling approach that aims to capture the multiple sources and types of uncertainty in a single framework. The main assumption is that hydrological systems are nonlinear dynamical systems which can be described by stochastic differential equations (SDE). The dynamics of the system is based on the least action principle (LAP) as derived from Noether’s theorem. The inflow process is considered as a sum of deterministic and random components. Using data from the Ouémé River basin (Benin, West Africa), the basic properties for the random component are considered and the triple relationship between the structure of the inflowing rainfall, the corresponding SDE that describes the river basin and the associated Fokker-Planck equations (FPE) is analysed.EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR D. Gerten [ABSTRACT FROM PUBLISHER]

Long-term data (2003-2015) on meltwater chemistry, mass balance and discharge of a benchmark glacier (Chhota Shigri Glacier, India) were studied to determine any association between these variables. To infer the factors governing the alteration of chemical weathering processes in glacierized basins, multi-annual records of the hydrochemical indices (Ca2++Mg2+/Na++K+) and the C-ratio were also examined. A succession of negative mass balance years has resulted in a decline in solute concentrations in the runoff, as discharge has increased. The (Ca2++Mg2+/Na++K+) and C-ratio are highest during periods of negative annual mass balance, when the spatial extent of the channelized drainage system increases. Conversely, these ratios are lowest in positive mass balance years, when the spatial extent of the channelized drainage system decreases, and chemical weathering in the distributed drainage system becomes more dominant. This paper is the first to show the inter-annual linkages between meltwater chemistry, mass balance and discharge for a valley glacier. [ABSTRACT FROM AUTHOR]

The ability of hydrological models to deal with changing conditions should not be taken for granted: it is an unfortunate but well-known problem of hydrology that the model structure and/or parameters optimized for certain conditions may not be transferable in time. Consequently, it is essential that, for application under changing conditions (e.g. in climate change impact studies), models be thoroughly assessed for their extrapolation capacity using adequate protocols. This editorial provides an overview of the Special Issue ofHydrological Sciences Journalcompiled after a workshop on this theme held during the General Assembly of the International Association of Hydrological Sciences (IAHS) in Gothenburg (Sweden) in 2013. The Workshop participants had been invited to apply a calibration and evaluation protocol to their own models on a given set of changing basins. The results show that this protocol is an appropriate and instructive way of assessing the suitability of hydrological models to be applied under changing conditions. This special issue also includes papers following alternative testing methodologies, as well as an opinion paper on the definition of non-stationarity. [ABSTRACT FROM AUTHOR]

This paper introduces a Special Issue ofHydrological Sciences Journalcontaining 10 research papers which present current applications of the Soil and Water Assessment Tool (SWAT) for water resources assessment. First, an overview of selected, recently published papers with application of SWAT is given. The papers address the following topics: nutrients and related best management practices (BMPs); sediments and related BMPs; impoundment and wetlands; irrigation; bioenergy crops; climate change impact; and land-use change impacts. Then, papers from this Special Issue are briefly described, covering the themes: surface runoff and sediments; nonpoint-source pollution; surface water and groundwater; impacts of climate and land-use change; and large-scale SWAT applications. The presented model applications of SWAT were conducted across a variety of spatial scales, physiographic regions and climatic zones. This collection of papers demonstrates that applications of SWAT for water resources assessment are growing in number and cover drainage basins in many regions worldwide.Editor M. Acreman; Associate editor Xi Chen [ABSTRACT FROM AUTHOR]

This paper investigates the transferability of calibrated HBV model parameters under stable and contrasting conditions in terms of flood seasonality and flood generating processes (FGP) in five Norwegian catchments with mixed snowmelt/rainfall regimes. We apply a series of generalized (differential) split-sample tests using a 6-year moving window over (i) the entire runoff observation periods, and (ii) two subsets of runoff observations distinguished by the seasonal occurrence of annual maximum floods during either spring or autumn. The results indicate a general model performance loss due to the transfer of calibrated parameters to independent validation periods of −5 to −17%, on average. However, there is no indication that contrasting flood seasonality exacerbates performance losses, which contradicts the assumption that optimized parameter sets for snowmelt-dominated floods (during spring) perform particularly poorly on validation periods with rainfall-dominated floods (during autumn) and vice versa. [ABSTRACT FROM AUTHOR]

Spatial and seasonal variations of curve number (CN) and initial abstraction ratio (λ) in a watershed can result in inaccurate runoff volume estimations when using the US Natural Resources Conservation Service (SCS-CN) method with constant values for these parameters. In this paper, parameters of CN and λ are considered as calibration parameters and the sensitivity of estimated runoff to these parameters using the SCS-CN method is scrutinized. To incorporate the uncertainty associated with CN and λ, fuzzy linear regression (FLR) is applied to derive the relationships of CN and λ with rainfall depth (P) by employing a large dataset of storm events from four watersheds in Iran. Results indicate that the proposed approach provides more accuracy in estimation of runoff volume compared to the SCS method with constant values of CN and λ, and gives a straightforward technique for evaluating the hydrological effects of CN, λ, and P on runoff volume. [ABSTRACT FROM AUTHOR]

A constrained total water-use policy has been implemented to maintain sustainable water supply in some water shortage areas. Managing a constrained water-use quota (T) in water allocation is a challenging goal. This paper proposes a new framework for water allocation under total water-use constraint by utilizing the concept of the Newsboy model, commonly used in operations management and applied economics, and applying it to the Dongjiang River Basin, South China. This framework considersTas a state variable of the objective function, rather than simply dealing with it as a constraint of multi-objective analysis. Using this framework, it is revealed how different schemes ofTplay out in water allocation, and water-use warning is provided for each sector and water governor in water resources management. [ABSTRACT FROM PUBLISHER]

The estimation of missing rainfall data is an important problem for data analysis and modelling studies in hydrology. This paper develops a Bayesian method to address missing rainfall estimation from runoff measurements based on a pre-calibrated conceptual rainfall–runoff model. The Bayesian method assigns posterior probability of rainfall estimates proportional to the likelihood function of measured runoff flows and prior rainfall information, which is presented by uniform distributions in the absence of rainfall data. The likelihood function of measured runoff can be determined via the test of different residual error models in the calibration phase. The application of this method to a French urban catchment indicates that the proposed Bayesian method is able to assess missing rainfall and its uncertainty based only on runoff measurements, which provides an alternative to the reverse model for missing rainfall estimates. [ABSTRACT FROM AUTHOR]

This paper presents a novel method to estimate flow duration curves (FDCs) for ungauged catchments with permanent flow. It is based on a dataset of 521 catchments located throughout France. The method consists in a three-step procedure called the Quantile Solidarity (QS) approach. First, a regression-based model is built to estimate FDCs in ungauged catchments, linking each flow quantile independently to physical descriptors. The second step involves imposing the continuity of the regression-based model parameters along the quantiles (hence quantile solidarity) to obtain a large reduction in the number of parameters used to estimate the FDC. The last step consists in spatially interpolating the model residuals to further improve the performance of the FDC estimation. The QS approach yields a robust and parsimonious FDC estimation without any loss in simulation efficiency and ensures strictly monotonic FDCs. [ABSTRACT FROM AUTHOR]

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 [ABSTRACT FROM AUTHOR]

This paper presents a neural network model capable of catchment-wide simultaneous prediction of river stages at multiple gauging stations. Thirteen meteorological parameters are considered in the input, which includes rainfall, temperature, mean relative humidity and evaporation. The NARX model is trained with a representative set of hourly data, with optimal time delay for both the input and output. The network trained using 120-day data is able to produce simulations that are in excellent agreement with field observations. We show that for application with one-step-ahead predictions, the loss in network performance is marginal. Inclusion of additional tidal observations does not improve predictions, suggesting that the river stage stations under consideration are not sensitive to tidal backwater effects despite the claim commonly made.EDITOR D. Koutsoyiannis ASSOCIATE EDITOR F. Pappenberger [ABSTRACT FROM PUBLISHER]

The southern coast of the Caspian Sea in northern Iran is bordered by a mountain range with forested catchments which are susceptible to droughts and floods. This paper examines possible changes to runoff patterns from one of these catchments in response to climate change scenarios. The HEC-HMS rainfall–runoff model was used with downscaled future rainfall and temperature data from 13 global circulation models, and meteorological and hydrometrical data from the Casilian (or “Kassilian”) Catchment. Annual and seasonal predictions of runoff change for three future emissions scenarios were obtained, which suggest significantly higher spring rainfall with increased risk of flooding and significantly lower summer rainfall leading to a higher probability of drought. Flash floods arising from extreme rainfall may become more frequent, occurring at any time of year. These findings indicate a need for strategic planning of water resource management and mitigation measures for increasing flood hazards.EDITOR M.C. Acreman ASSOCIATE EDITOR not assigned [ABSTRACT FROM PUBLISHER]

This paper presents an analysis of three common hydrological regionalization methods (multiple linear regression, spatial proximity and physical similarity) in a virtual-world setting, using a 15 km resolution regional climate model to eliminate uncertainty due to measurement errors and missing data. It was found that in many cases the best donor is neither the most similar nor the closest watershed to the ungauged site, indicating a need for better hydrologically relevant catchment descriptors. Results show that using the closest donors yields satisfactory results only if they share similar characteristics with the ungauged basin, confirming that the proximity method is a good proxy only if there is reason to believe that the basins are physically similar. It was also shown that the ability to predict whether a method will succeed or fail is limited by the quality of catchment descriptors and the inherent probabilistic nature of the problem. A method to determine whether a regionalization method will fail or succeed based on the ungauged catchment’s characteristics failed to recognize a successful candidate 20% of the time, whereas it incorrectly classified a poor candidate in 30% of cases. The results indicate that there are unknown properties or processes that contribute to the hydrological behaviour of ungauged basins.EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR F. Pappenberger [ABSTRACT FROM PUBLISHER]

This paper analyses the composition of surface water and shallow groundwater in the Grande River basin, North-Central Chile, using this information to characterize water interactions. Chemical and isotopic data for surface water and groundwater (7 and 6 sampling locations, respectively) were obtained from three sampling campaigns performed in March-April (autumn), August-September (late winter) and December (early summer) 2012. Precipitation samples were also collected. Data was processed using spatial distribution charts, Piper and Stiff diagrams, and multivariate analysis. In general, the results for each method converge on a high degree of connectivity between surface water and shallow groundwater in the study area. Furthermore, approximately a 10% of groundwater contribution to the surface flow discharge was estimated for a particular reach. This multi-method approach was useful for the characterization of surface water-groundwater interactions in the Grande River basin, and may become a suitable and replicable scheme for studies in arid and semi-arid basins facing similar water management challenges. [ABSTRACT FROM AUTHOR]

Somalia has frequently been affected by droughts, famines and water-related humanitarian crises. Water is scarce and the only perennial streams, the Juba and Shabelle rivers, are trans-boundary with river flows mainly originating from the Ethiopian highlands. In both riparian countries water demands are projected to increase. This paper reveals the impact of rising regional water abstractions on stream flows by illustrating sectoral demands and joining them into scenarios of medium and high population and economic growth. These scenarios are associated to the time horizons of 2035 and 2055, respectively. The scenarios disclose alarming trends especially for the Shabelle River: in the medium and high growth scenarios, water demands surpass the available river flows by 200 and 3500 hm3, respectively. The calculated deficits partly derive from conflicting assumptions about river flows by the two main riparian countries, an obstacle to any integrated planning efforts and sustained regional development.EDITOR Z.W. Kundzewicz; ASSOCIATE EDITOR F. Hattermann [ABSTRACT FROM AUTHOR]

We greatly enjoyed reading the paper by Liu et al., which is both timely and rich in insight, as it discusses the challenges in operationalizing the water-energy-food security (WEF) nexus. The nexus approach is gaining increasing attention, both in research and in policy documents, as reflected in the number and content of published documents in the past years and highlighted by the authors. [ABSTRACT FROM AUTHOR]

The estimation of drought at certain temporal and spatial scales is useful for research on climate change and global warming. Greece is often affected by droughts, which are widespread spatially and temporally due to the complex topography. Within the Greek territory, various complex microclimates are created, linked with the spatial variances in drought phenomena. In this paper an estimation of drought in the Sperchios River basin was conducted using the Aridity Index (AI). Additionally, a seasonal analysis of drought was performed. Meteorological data from the Hellenic National Meteorological Service (HNMS) were used as inputs for the AI equation. Spatial interpolation of AI for the Sperchios River basin was performed using a kriging method by the application of ArcGIS 9.3. In order to produce required input data, several models (EmPEst, RayMan) and techniques (linear regression, interpolation) were combined. Finally, the meteorological data series were randomly separated into two periods and AI was estimated for these sub-periods, in order to test the effectiveness of the drought index used. The results indicate that the conditions prevailing in the area are humid, mostly affected by increased rainfall occurring in the mountainous section of the basin. Broadly, the humid environment in the upstream of Sperchios River prevents drought occurring in the lowlands of Sperchios River valley. Nevertheless, some differentiation appeared during the summer period, to which special attention needs to be given in order to prevent drought conditions.Editor Z. W. Kundzewicz Associate editor not assigned [ABSTRACT FROM AUTHOR]

The objective of this paper is to analyse, for the Senegal River basin, the evolution of four classes of daily precipitation, the number of rainy days and the duration of the rainy season. The approach is to apply statistical tests of homogeneity to the series of annual rainfall over the period 1950–1998 to detect abrupt changes and to characterize the evolution of these six variables on each side of the change dates. The time series present an abrupt change (break) between 1966 and 1970. Deficits of rainy days in the period after the break compared to before vary between 6.2% at Kédougou and 38.6% at Saint Louis. The class of rain of more than 50 mm (P4) has the largest deficit, ranging from 14.8% at Mamou station to 66.6% at Nioro du Sahel.Editeur Z. W. Kundzewicz; Edithur Associé E. Gargouri [ABSTRACT FROM AUTHOR]

This paper explores the use of entropy-based measures in catchment hydrology, and provides an importance-weighted numerical descriptor of the flow–duration curve. Although entropy theory is being applied in a wide spectrum of areas (including environmental and water resources), artefacts arising from the discrete, under-sampled and uncertain nature of hydrological data are rarely acknowledged, and have not been adequately explored. Here, we examine challenges to extracting hydrologically meaningful entropy measures from a flow signal; the effect of binning resolution on calculation of entropy is investigated, along with artefacts caused by (1) emphasis of information theoretic measures towards flow ranges having more data (statistically dominant information), and (2) effects of discharge measurement truncation errors. We introduce an importance-weighted entropy-based measure to counter the tendency of common binning approaches to over-emphasise information contained in the low flows which dominate the record. The measure uses a novel binning method, and overcomes artefacts due to data resolution and under-sampling. Our analysis reveals a fundamental problem with the extraction of information at high flows, due to the lack of statistically significant samples in this range. By separating the flow–duration curve into segments, our approach constrains the computed entropy to better respect distributional properties over the data range. When used as an objective function for model calibration, this approach constrains high flow predictions, as well as the commonly used Nash-Sutcliffe efficiency, but provides much better predictions of low flow behaviour.Editor Z.W. KundzewiczAssociate editor Not assigned [ABSTRACT FROM AUTHOR]

The honey-bees mating programming (HBMP) algorithm is introduced as a novel tool for predicting suspended sediment concentration for the Mad River catchment near Arcata, USA. The paper also applies gene expression programming (GEP) as a comparison and shows that these two approaches can the produce transparent, nonlinear relationships between the independent and dependent variables. Some modifications have been made to the HBMP algorithm to improve its capability and efficiency. The results achieved from this method and GEP are compared with two different sediment rating curves based on regression techniques. The findings show that the results from both the HBMP and GEP methods are promising and outperform the results obtained from the sediment rating curves.Editor D. Koutsoyiannis; Associate editor L. See [ABSTRACT FROM AUTHOR]

A significant decrease in mean river flow as well as shifts in flood regimes have been reported at several locations along the River Niger. These changes are the combined effect of persistent droughts, damming and increased consumption of water. Moreover, it is believed that climate change will impact on the hydrological regime of the river in the next decades and exacerbate existing problems. While decision makers and stakeholders are aware of these issues, it is hard for them to figure out what actions should be taken without a quantitative estimate of future changes. In this paper, a Soil and Water Assessment Tool (SWAT) model of the Niger River watershed at Koulikoro was successfully calibrated, then forced with the climate time series of variable length generated by nine regional climate models (RCMs) from the AMMA-ENSEMBLES experiment. The RCMs were run under the SRES A1B emissions scenario. A combination of quantile-quantile transformation and nearest-neighbour search was used to correct biases in the distributions of RCM outputs. Streamflow time series were generated for the 2026–2050 period (all nine RCMs), and for the 2051–2075 and 2076–2100 periods (three out of nine RCMs) based on the availability of RCM simulations. It was found that the quantile-quantile transformation improved the simulation of both precipitation extremes and ratio of monthly dry days/wet days. All RCMs predicted an increase in temperature and solar radiation, and a decrease in average annual relative humidity in all three future periods relative to the 1981–1989 period, but there was no consensus among them about the direction of change of annual average wind speed, precipitation and streamflow. When all model projections were averaged, mean annual precipitation was projected to decrease, while the total precipitation in the flood season (August, September, October) increased, driving the mean annual flow up by 6.9% (2026–2050), 0.9% (2051–2075) and 5.6% (2076–2100). At-test showed that changes in multi-model annual mean flow and annual maximum monthly flow between all four periods were not statistically significant at the 95% confidence level. [ABSTRACT FROM PUBLISHER]

The first objective of this paper is to analyse the trends and change points in the hydroclimatic time series of five representative sub-catchments of the Macta basin, which lies in western Algeria. The second objective is to quantify the role of climate on the trends observed in annual flow time series. This is achieved using hydrological modelling at the multi-annual time step using the Schreiber formulation. The results showed no significant trends on annual rainfall in the 1975–2005 period, a significant increase of temperature and different flow responses to the latter, depending on the catchment considered. Two out of five catchments considered presented a significant flow decrease in the 1975–2005 period with a change point at the beginning of the 1990s. Modelling results suggest that the increase of air temperature is not the sole factor explaining the decrease of annual flow time series in these two catchments. [ABSTRACT FROM AUTHOR]

This paper aims at revisiting the use of non-dimensional representations for catchment change and model robustness analysis. As well as being helpful for catchment classification according to hydroclimatic conditions, the Turc-Budyko representation enables visualization of temporal changes in these conditions and/or modification of the hydrological behaviour of the catchment. This brings a new perspective to hydrological analysis, different from the classical time series plots, which helps when interpreting catchment functioning with respect to hydroclimatic constraints. These tools do not require statistical analyses of observed series and are therefore very simple to implement. Four case studies are considered here to illustrate the use of theQ/P = f(P/Ep) graph. When combined with the inter-annual Turc-Mezentsev formula, this visual framework enables anticipation of potential difficulties for models based on the same hypotheses, solely using the analysis of observed data. [ABSTRACT FROM AUTHOR]

This paper quantifies the impacts of bushfire and climate variability on streamflow from three southeast Australian catchments where bushfires occurred in February 1983. Three hydrological models (AWRA-L, Xinanjiang and GR4J) were first calibrated against streamflow data from the pre-bushfire period and then used to simulate runoff for the post-bushfire period with the calibrated parameters. The difference in simulated streamflow between pre- and post-bushfire periods provides an estimate of the impact of climate variability on streamflow. The impact of bushfire on streamflow is quantified by removing the climate variability impact from the difference in mean annual observed streamflow between post- and pre-bushfire periods. For the first 15 years after the 1983 bushfires, the results from hydrological models for the three catchments indicate that there is a substantial increase in streamflow; this is attributed to initial decreases in evapotranspiration and soil infiltration rates resulting from the fires, followed by logging activity. After 15 years, streamflow dynamics are more heavily influenced by climate effects, although some impact from fire and logging regeneration may still occur. The results show that hydrological models provide reasonably consistent estimates of bushfire and climate impacts on streamflow for the three catchments. The models can be used to quantify relative contributions of forest disturbance (bushfire, logging and other forest management) and climate variability. The results presented can also help forest managers understand the relationship between bushfire and climate variability impacts on water yield in the context of climate variability. [ABSTRACT FROM AUTHOR]

This paper focuses on a regionalization attempt to partly solve data limitation problems in statistical analysis of high flows to derive discharge–duration–frequency (QDF) relationships. The analysis is based on 24 selected catchments in the Lake Victoria Basin (LVB) in East Africa. Characteristics of the theoretical QDF relationships were parameterized to capture their slopes of extreme value distributions (evd), tail behaviour and scaling measures. To enable QDF estimates to be obtained for ungauged catchments, interdependence relationships between the QDF parameters were identified, and regional regression models were developed to explain the regional difference in these parameters from physiographic characteristics. In validation of the regression models, from the lowest (5 years) to the highest (25 years) return periods considered, the percentage bias in the QDF estimates ranged from –2% for the 5-year return period to 27% for 25-year return period.Editor D. Koutsoyiannis [ABSTRACT FROM AUTHOR]

Available data from nearby gauging stations can provide a great source of hydrometric information that is potentially transferable to an ungauged site. Furthermore, streamflow measurements may even be available for the ungauged site. This paper explores the potential of four distance-based regionalization methods to simulate daily hydrographs at almost ungauged pollution-control sites. Two methods use only the hydrological information provided by neighbouring catchments; the other two are new regionalization methods parameterized with a limited number of streamflow data available at the site of interest. Based on a network of 149 streamgauges and 21 pollution-control sites located in the Upper Rhine-Meuse area, the comparative assessment demonstrates the benefit of making available point streamflow measurements at the location of interest for improving quantitative streamflow prediction. The advantage is moderate for the prediction of flow types (stormflow, recession flow, baseflow) and pulse shape (duration of rising limb and falling limb). Editor Z.W. Kundzewicz; Associate editor A. Viglione [ABSTRACT FROM AUTHOR]

Large errors in peak discharge estimates at catchment scales can be ascribed to errors in the estimation of catchment response time. The time parameters most frequently used to express catchment response time are the time of concentration (TC), lag time (TL) and time to peak (TP). This paper presents a review of the time parameter estimation methods used internationally, with selected comparisons in medium and large catchments in the C5 secondary drainage region in South Africa. The comparison of different time parameter estimation methods with recommended methods used in South Africa confirmed that the application of empirical methods, with no local correction factors, beyond their original developmental regions, must be avoided. TheTCis recognized as the most frequently used time parameter, followed byTL. In acknowledging this, as well as the basic assumptions of the approximationsTL = 0.6TCandTC≈TP, along with the similarity between the definitions of theTPand the conceptualTC, it was evident that the latter two time parameters should be further investigated to develop an alternative approach to estimate representative response times that result in improved estimates of peak discharge at these catchment scales.Editor Z.W. Kundzewicz; Associate editor Qiang Zhang [ABSTRACT FROM AUTHOR]

We thank van Emmerik et al. for their discussion of our opinion paper. We do not fully agree that publication of negative results will be very effective in promoting experimental hydrology. Instead, we think that experimental hydrology is considered to be more risky than modelling studies because of difficulties in publishing inconclusive results and the potential for failure. [ABSTRACT FROM AUTHOR]