Error analysis for the evaluation of model performance: rainfall–runoff event summary variables

This paper provides a procedure for the evaluation of model performance for rainfall–runoff event summary variables, such as total discharge or peak runoff. The procedure is based on the analysis of model errors, defined as the differences between observed values and values predicted by a simulation model. Model errors can (i) indicate whether and where the model can be improved, (ii) be used to measure the performance of a model, and (iii) be used to compare model simulations. In this paper, both statistical and graphical methods are used to characterize model errors. We explore model recalibration by relating model errors to the model predictions, and to external, independent variables. The R‐5 catchment data sets that we used in this study include summary variables for 72 rainfall–runoff events. The simulations used in this study were previously conducted with the quasi‐physically based rainfall–runoff model QPBRRM for 11 different characterizations of the R‐5 catchment, each with increasing information or a refined spatial discretization of the overland flow planes. This paper is about proposing model diagnostics and not about procedures for using diagnostics for model modification. Copyright © 2007 John Wiley & Sons, Ltd.     

Further testing of the Integrated Hydrology Model (InHM): event‐based simulations for a small rangeland catchment located near Chickasha,Oklahoma

In the paper that is the foundation for this study, VanderKwaak and Loague (2001. Water Resources Research 37 : 999–1013) reported a demonstration of a fully coupled comprehensive physics‐based hydrologic‐response model, InHM (Integrated Hydrology Model), for two rainfall‐runoff events from the small rangeland catchment known as R‐5. The InHM simulations reported herein address (in three phases) limitations in the VanderKwaak and Loague (2001. Water Resources Research 37 : 999–1013) simulations. In Phase I, a new finite‐element mesh was selected to represent R‐5. In Phase II, with the new mesh in place, evaporation was considered for the R‐5 events. In Phase III, with the new mesh in place and evaporation considered, the geology of R‐5 was approximated. Each phase, compared with the results reported by VanderKwaak and Loague (2001. Water Resources Research 37 : 999–1013), shows a change in the simulated near‐surface response. The performance of InHM for 15 R‐5 events is also reported herein. The results from two stages of model calibration are presented. The uncertainty in initial soil‐water content estimates for event‐based simulation is shown to be a major limitation for physics‐based models. The performance of InHM, relative to past event‐based simulation efforts with a quasi‐physically based rainfall‐runoff model, is better for both peak stormflow and the time to peak stormflow, but worse for stormflow depth. The InHM simulations reported here set the stage for continuous simulation of near‐surface response for the R‐5 catchment with InHM. Copyright © 2004 John Wiley & Sons, Ltd.     

Dependence of model-based extreme flood estimation on the calibration period: case study of the Kamp River (Austria)

Abstract

The Kamp River is a particularly interesting case study for testing flood frequency estimation methods, since it experienced a major flood in August 2002. Here, the Kamp catchment is studied in order to quantify the influence of such a remarkable flood event on the calibration of a rainfall–runoff model, in particular when it is used in a stochastic simulation method for flood estimation, by performing numerous rainfall–runoff model calibrations (based on split-sample and bootstrap tests). The results confirmed the usefulness of the multi-period and bootstrap testing schemes for identifying the dependence of model performance and flood estimates on the information contained in the calibration period. The August 2002 event appears to play a dominating role for the Kamp River, since the presence or absence of the event within the calibration sub-periods strongly influences the rainfall–runoff model calibration and the extreme flood estimations that are based on the calibrated model.     

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.     

A modelling approach to assessing variations of total suspended solids (tss) mass fluxes during storm events

Connections between the catchment hydrology and accumulation, washoff and transport of pollutants in wet weather greatly affect the management of urban drainage and its wet‐weather effluents. In recent years, the concept of the first flush has gained on prominence and was further developed for analyzing the interaction between the hydrology and transport of runoff pollutants. One of the most important definitions of the first flush can be derived from the analysis of the m(v) curves (i.e. the curves in which the normalized cumulative pollutant mass is plotted vs the normalized cumulative runoff volume). Indeed the m(v) curves, indicating the distribution of pollutant mass versus volume in wet‐weather flow (WWF) discharges, are commonly used for comparing pollutant discharges for different rainfall events and catchments. In this study, the m(v) curves were used to define the concepts of flow‐limited and mass‐limited WWF events. These two different behaviours have been analysed for rainfall/runoff events observed in the urbanized part of the Liguori catchment in Cosenza (Italy). In order to advance the understanding of the intra‐event variability of m(v) curves, the mathematical rainfall/runoff model Storm Water Management Model of the US Environmental Protection Agency (SWMM) was calibrated for eight observed rainfall/runoff events and the differences between observed and simulated m(v) curves were analysed. The results showed a good correlation between the observed and simulated m(v) curves, and this finding offers further benefits in SWMM model calibration. Copyright © 2013 John Wiley & Sons, Ltd.     

Process controls on the statistical flood moments ‐ a data based analysis

In this paper, the controls of different indicators on the statistical moments (i.e. mean annual flood (MAF), coefficient of variation (CV) and skewness (CS)) of the maximum annual flood records of 459 Austrian catchments are analysed. The process controls are analysed in terms of the correlation of the flood moments within five hydrologically homogeneous regions to two different types of indicators. Indicators of the first type are static catchment attributes, which are associated with long‐term observations such as mean annual precipitation, the base flow index, and the percentage of catchment area covered by a geological unit or soil type. Indicators of the second type are dynamic catchment attributes that are associated with the event scale. Indicators of this type used in the study are event runoff coefficients and antecedent rainfall. The results indicate that MAF and CV are strongly correlated with indicators characterising the hydro‐climatic conditions of the catchments, such as mean annual precipitation, long‐term evaporation and the base flow index. For the catchments analysed, the flood moments are not significantly correlated with static catchment attributes representing runoff generation, such as geology, soil types, land use and the SCS curve number. Indicators of runoff generation that do have significant predictive power for flood moments are dynamic catchment attributes such as the mean event runoff coefficients and mean antecedent rainfall. The correlation analysis indicates that flood runoff is, on average, more strongly controlled by the catchment moisture state than by event rainfall. Copyright © 2008 John Wiley & Sons, Ltd.     

Exploring effects of rainfall intensity and duration on soil erosion at the catchment scale using openLISEM: Prado catchment,SE Spain

In semi‐arid areas, high‐intensity rainfall events are often held responsible for the main part of soil erosion. Long‐term landscape evolution models usually use average annual rainfall as input, making the evaluation of single events impossible. Event‐based soil erosion models are better suited for this purpose but cannot be used to simulate longer timescales and are usually applied to plots or small catchments. In this study, the openLISEM event‐based erosion model was applied to the medium‐sized (～50 km²) Prado catchment in SE Spain. Our aim was to (i) test the model's performance for medium‐sized catchments, (ii) test the ability to simulate four selected typical Mediterranean rainfall events of different magnitude and (iii) explore the relative contribution of these different storms to soil erosion using scenarios of future climate variability. Results show that because of large differences in the hydrologic response between storms of different magnitudes, each event needed to be calibrated separately. The relation between rainfall event characteristics and the calibration factors might help in determining optimal calibration values if event characteristics are known. Calibration of the model features some drawbacks for large catchments due to spatial variability in K_sat values. Scenario calculations show that although ～50% of soil erosion occurs as a result of high frequency, low‐intensity rainfall events, large‐magnitude, low‐frequency events potentially contribute significantly to total soil erosion. The results illustrate the need to incorporate temporal variability in rainfall magnitude–frequency distributions in landscape evolution models. Copyright © 2011 John Wiley & Sons, Ltd.     

Storm runoff response to rainfall pattern,magnitude and urbanization in a developing urban catchment

This study explored the hydrological impacts of urbanization, rainfall pattern and magnitude in a developing catchment. The Stormwater Management Model was parameterized, calibrated and validated in three development phases, which had the same catchment area (12.3 ha) but different land use intensities. The model calibration and validation by using sub‐hourly hydro‐meteorological data demonstrated a good performance of the model in predicting stormwater runoff in the different development phases. Based on the results, a threshold between minor and major rainfall events was identified and conservatively determined to be about 17.5 mm in depth. Direct runoff for minor storm events has a linear relationship with rainfall; however, events with a rainfall depth greater than the threshold yield a rainfall–runoff regression line with a clearly steeper slope. The difference in urban runoff generation between minor and major rainfall events diminishes with the increase of imperviousness. Urbanization leads to an increase in the production of stormwater runoff, but during infrequent major storms, the runoff contribution from pervious surfaces reduces the runoff changes owing to urbanization. Rainfall pattern exerts an important effect on urban runoff, which is reflected in pervious runoff. With the same magnitude, prolonged rainfall events with unvarying low intensity yield the smallest peak flow and the smallest total runoff, yet rainfall events with high peak intensity produce the largest runoff volume. These results demonstrate the different roles of impervious and pervious surfaces in runoff generation, and how runoff responds to rainstorms in urban catchments depends on hyetograph and event magnitude. Furthermore, the study provides a scientific basis of the design guideline sustainable urban drainage systems, which are still arbitrary in many countries. Copyright © 2015 John Wiley & Sons, Ltd.     

Improving runoff prediction using agronomical information in a cropped,loess covered catchment

Predicting runoff hot spots and hot‐moments within a headwater crop‐catchment is of the utmost importance to reduce adverse effects on aquatic ecosystems by adapting land use management to control runoff. Reliable predictions of runoff patterns during a crop growing season remain challenging. This is mainly due to the large spatial and temporal variations of topsoil hydraulic properties controlled by complex interactions between weather, growing vegetation, and cropping operations. This interaction can significantly modify runoff patterns and few process‐based models can integrate this evolution of topsoil properties during a crop growing season at the catchment scale. Therefore, the purpose of this study was to better constrain the event‐based hydrological model Limburg Soil Erosion Model by incorporating temporal constraints for input topsoil properties during a crop growing season (LISEM). The results of the temporal constraint strategy (TCS) were compared with a classical event per event calibration strategy (EES) using multi‐scale runoff information (from plot to catchment). The EES and TCS approaches were applied in a loess catchment of 47 ha located 30 km northeast of Strasbourg (Alsace, France). A slight decrease of the Nash–Sutcliffe efficiency criterion on runoff discharge for TCS compared to EES was counterbalanced by a clear improvement of the spatial runoff patterns within the catchment. This study showed that limited agronomical and climatic information added during the calibration step improved the spatial runoff predictions of an event‐based model. Reliable prediction of runoff source, connectivity, and dynamics can then be derived and discussed with stakeholders to identify runoff hot spots and hot‐moments for subsequent land use and crop management modifications.     

Seasonal rainfall–runoff relationships in a lowland forested watershed in the southeastern USA

Hydrological processes of lowland watersheds of the southern USA are not well understood compared to a hilly landscape due to their unique topography, soil compositions, and climate. This study describes the seasonal relationships between rainfall patterns and runoff (sum of storm flow and base flow) using 13 years (1964–1976) of rainfall and stream flow data for a low‐gradient, third‐order forested watershed. It was hypothesized that runoff–rainfall ratios (R/P) are smaller during the dry periods (summer and fall) and greater during the wet periods (winter and spring). We found a large seasonal variability in event R/P potentially due to differences in forest evapotranspiration that affected seasonal soil moisture conditions. Linear regression analysis results revealed a significant relationship between rainfall and runoff for wet (r² = 0·68; p < 0·01) and dry (r² = 0·19; p = 0·02) periods. Rainfall‐runoff relationships based on a 5‐day antecedent precipitation index (API) showed significant (r² = 0·39; p < 0·01) correspondence for wet but not (r² = 0·02; p = 0·56) for dry conditions. The same was true for rainfall‐runoff relationships based on 30‐day API (r² = 0·39; p < 0·01 for wet and r² = 0·00; p = 0·79 for dry). Stepwise regression analyses suggested that runoff was controlled mainly by rainfall amount and initial soil moisture conditions as represented by the initial flow rate of a storm event. Mean event R/P were higher for the wet period (R/P = 0·33), and the wet antecedent soil moisture condition based on 5‐day (R/P = 0·25) and 30‐day (R/P = 0·26) prior API than those for the dry period conditions. This study suggests that soil water status, i.e. antecedent soil moisture and groundwater table level, is important besides the rainfall to seasonal runoff generation in the coastal plain region with shallow soil argillic horizons. Copyright © 2011 John Wiley & Sons, Ltd.     

Reservoir rainfall‐runoff geomorphological model. II: analysis,calibration and validation

The model presented in the complementary document entitled, Reservoir rainfall‐runoff geomorphological model I: parameter application and analysis is analysed, calibrated and validated in this paper. The accuracy of simulated hydrographs is analysed by means of the efficiency defined by Nash and Sutcliffe. The sensitivity of the influence of five parameters on the behaviour of the model developed is analysed. Two different calibration and validation processes of Reservoir rainfall‐runoff geomorphological model are performed in Aixola watershed. Twelve events have been selected for calibrations and 25 for validations. With the first calibration and validation process, the model parameters are set by assigning the medians' values of the distributions obtained by means of the optimum results. The second process is performed by calibrating the most determinant parameter in the adjustment, which is the one that indicates the proportion of infiltrated water that is retained and does not flow; this is done with an empirical formulation depending on the event characteristics. Subsequently, the obtained results are validated. This last process has achieved very good adjustments in both calibrated and validated events. Copyright © 2012 John Wiley & Sons, Ltd.     

Assessment of the adequacy of the regional relationships between catchment attributes and catchment response dynamics,calibrated by a multi‐objective approach

This study aimed to evaluate the effectiveness of the regionalization method on the basis of a combination of a parsimonious model structure and a multi‐objective calibration technique. For this study, 12 gauged catchments in the Republic of Korea were used. The parsimonious model structure, requiring minimal input data, was used to avoid adverse effects arising from model complexity, over‐parameterization and data requirements. The IHACRES rainfall‐runoff model was applied to represent the dynamic response characteristics of catchments in Korea. A multi‐objective approach was adopted to reduce the predictive uncertainty arising from the calibration of a rainfall‐runoff model, by increasing the amount of information retrieved from the available data. The regional relationships (or models) between the model parameters and the catchment attributes were established via a multiple regression approach, incorporating correlation analysis and stepwise regression on linear and logarithmic scales. The impacts of the parameters, calibrated by the multi‐objective approach, on the adequacy of regional relationships were assessed by comparison with impacts obtained by the single‐objective approach. The regional relationships were well defined, despite limited available data. The drainage area, the effective soil depth, the mean catchment slope and the catchment gradient appeared to be the main factors for describing the hydrologic response characteristics in the areas studied. The overall model performance of the regional models based on the multi‐objective approach was good, producing reasonable results for high and low flows and for the overall water balance, simultaneously. The regional models based on the single‐objective approach yielded accurate predictions in high flows but showed limited predictive capability for low flows and the overall water balance. This was due to the optimal model parameter estimates when using a single‐objective measure. The parameters calibrated by the single‐objective approach decreased the predictability of the regional models. Copyright © 2013 John Wiley & Sons, Ltd.     

Rainfall‐runoff modelling using artificial neural networks technique: a Blue Nile catchment case study

A rainfall‐runoff model based on an artificial neural network (ANN) is presented for the Blue Nile catchment. The best geometry of the ANN rainfall‐runoff model in terms of number of hidden layers and nodes is identified through a sensitivity analysis. The Blue Nile catchment (about 300 000 km²) in the Nile basin is selected here as a case study. The catchment is classified into seven subcatchments, and the mean areal precipitation over those subcatchments is computed as a main input to the ANN model. The available daily data (1992–99) are divided into two sets for model calibration (1992–96) and for validation (1997–99). The results of the ANN model are compared with one of physical distributed rainfall‐runoff models that apply hydraulic and hydrologic fundamental equations in a grid base. The results over the case study area and the comparative analysis with the physically based distributed model show that the ANN technique has great potential in simulating the rainfall‐runoff process adequately. Because the available record used in the calibration of the ANN model is too short, the ANN model is biased compared with the distributed model, especially for high flows. Copyright © 2005 John Wiley & Sons, Ltd.     

Rainfall–runoff modelling of ephemeral streams in the Valencia region (eastern Spain)

This paper presents preliminary results from the application of a transfer‐function rainfall–runoff model to ephemeral streams in Mediterranean Spain. Flow simulations have been conducted for two small catchments (Carraixet and Poyo basins), located in close proximity to one another yet with significantly different geological characteristics. Analysis of flow simulations for a number of high‐flow events has revealed the dominant influence of the rainfall on the catchment response, particularly for high‐rainfall events. Particular success has been attained modelling the highest magnitude events in both catchments and for all events in the faster responding (Poyo) catchment. In order to investigate the viability of the model for forecasting floods in ungauged catchments, additional investigations have been conducted by calibrating the model for one catchment (donor catchment) and then applying it to another (receptor catchment). The results indicate that this can be successful when either the donor catchment is a fast response catchment or when the model is calibrated using a high‐magnitude event in the donor catchment, providing that the modelled receptor catchment event is of a lower magnitude. Copyright © 2002 John Wiley & Sons, Ltd.     

Water balance estimation under the challenge of data scarcity in a hyperarid to Mediterranean region

Water budget analyses are important for the evaluation of the water resources in semiarid and arid regions. The lack of observed data is the major obstacle for hydrological modelling in arid regions. The aim of this study is the analysis and calculation of the natural water resources of the Western Dead Sea subsurface catchment, one which is highly sensitive to rainfall resulting in highly variable temporal and spatial groundwater recharge. We focus on the subsurface catchment and subsequently apply the findings to a large‐scale groundwater flow model to estimate the groundwater discharge to the Dead Sea. We apply a semidistributed hydrological model (J2000g), originally developed for the Mediterranean, to the hyperarid region of the Western Dead Sea catchment, where runoff data and meteorological records are sparsely available. The challenge is to simulate the water budget, where the localized nature of extreme rainstorms together with sparse runoff data results in few observed runoff and recharge events. To overcome the scarcity of climate input data, we enhance the database with mean monthly rainfall data. The rainfall data of 2 satellites are shown to be unsuitable to fill the missing rainfall data due to underrepresentation of the steep hydrological gradient and temporal resolution. Hydrological models need to be calibrated against measured values; hence, the absence of adequate data can be problematic. Therefore, our calibration approach is based on a nested strategy of diverse observations. We calculate a direct surface runoff of the Western Dead Sea surface area (1,801 km²) of 3.4 mm/a and an average recharge (36.7 mm/a) for the 3,816 km² subsurface drainage basin of the Cretaceous aquifer system.     

Coupling the Xinanjiang model to a kinematic flow model based on digital drainage networks for flood forecasting

The Xinanjiang model, which is a conceptual rainfall‐runoff model and has been successfully and widely applied in humid and semi‐humid regions in China, is coupled by the physically based kinematic wave method based on a digital drainage network. The kinematic wave Xinanjiang model (KWXAJ) uses topography and land use data to simulate runoff and overland flow routing. For the modelling, the catchment is subdivided into numerous hillslopes and consists of a raster grid of flow vectors that define the water flow directions. The Xinanjiang model simulates the runoff yield in each grid cell, and the kinematic wave approach is then applied to a ranked raster network. The grid‐based rainfall‐runoff model was applied to simulate basin‐scale water discharge from an 805‐km² catchment of the Huaihe River, China. Rainfall and discharge records were available for the years 1984, 1985, 1987, 1998 and 1999. Eight flood events were used to calibrate the model's parameters and three other flood events were used to validate the grid‐based rainfall‐runoff model. A Manning's roughness via a linear flood depth relationship was suggested in this paper for improving flood forecasting. The calibration and validation results show that this model works well. A sensitivity analysis was further performed to evaluate the variation of topography (hillslopes) and land use parameters on catchment discharge. Copyright © 2009 John Wiley & Sons, Ltd.     

Spatial and temporal variability of the hydrological response in a small Mediterranean research catchment (Vallcebre,Eastern Pyrenees)

This paper analyses the spatial and temporal variability of the hydrological response in a small Mediterranean catchment (Cal Rodó). The first part of the analysis focuses on the rainfall–runoff relationship at seasonal and monthly scale, using an 8‐year data set. Then, using storm‐flow volume and coefficient, the temporal variability of the rainfall–runoff relationship and its relationship with several hydrological variables are analysed at the event scale from hydrographs observed over a 3‐year period. Finally, the spatial non‐linearity of the hydrological response is examined by comparing the Cal Rodó hydrological response with the Can Vila sub‐catchment response at the event scale. Results show that, on a seasonal and monthly scale, there is no simple relationship between rainfall and runoff depths, and that evapotranspiration is a factor that introduced some non‐linearity in the rainfall–runoff relationship. The analysis of monthly values also reveals the existence of a threshold in the relationship between rainfall and runoff depths, denoting a more contrasted hydrological response than the one usually observed in humid catchments. At the event scale, the storm‐flow coefficient has a clear seasonal pattern with an alternance between a wet period, when the catchment is hydrologically responsive, and a dry summer period, when the catchment is much less reactive to any rainfall. The relationship between the storm‐flow coefficient and rainfall depth, rainfall maximum intensity and base‐flow shows that observed correlations are the same as those observed for humid conditions, even if correlation coefficients are notably lower. Comparison with the Can Vila sub‐catchment highlights the spatial heterogeneity of the rainfall‐runoff relationship at the small catchment scale. Although interpretation in terms of runoff processes remains delicate, heterogeneities between the two catchments seem to be related to changes in the ratio between infiltration excess and saturation processes in runoff formation. Copyright © 2007 John Wiley & Sons, Ltd.     

An analysis of the impact of spatial variability in rainfall on runoff and sediment predictions from a distributed model

This paper investigates the effect of introducing spatially varying rainfall fields to a hydrological model simulating runoff and erosion. Pairs of model simulations were run using either spatially uniform (i.e. spatially averaged) or spatially varying rainfall fields on a 500‐m grid. The hydrological model used was a simplified version of Thales which enabled runoff generation processes to be isolated from hillslope averaging processes. Both saturation excess and infiltration excess generation mechanisms were considered, as simplifications of actual hillslope processes. A 5‐year average recurrence interval synthetic rainfall event typical of temperate climates (Melbourne, Australia) was used. The erosion model was based on the WEPP interrill equation, modified to allow nonlinear terms relating the erosion rate to rainfall or runoff‐squared. The model results were extracted at different scales to investigate whether the effects of spatially varying rainfall were scale dependent. A series of statistical metrics were developed to assess the variability due to introducing the spatially varying rainfall field. At the catchment (approximately 150 km²) scale, it was found that particularly for saturation excess runoff, model predictions of runoff were insensitive to the spatial resolution of the rainfall data. Generally, erosion processes at smaller sub‐catchment scales, particularly when the sediment generation equation had non linearity, were more sensitive to spatial rainfall variability. Introducing runon infiltration reduced the total runoff and sediment yield at all scales, and this process was also most sensitive to the rainfall resolution. Copyright © 2011 John Wiley & Sons, Ltd.     

Hydrological processes of a closed catchment‐lake system in a semi‐arid Mediterranean environment

Data collected in 4 years of field observations were used in conjunction with continuous simulation models to study, at the small‐basin scale, the water balance of a closed catchment‐lake system in a semi‐arid Mediterranean environment. The open water evaporation was computed with the Penman equation, using the data set collected in the middle of the lake. The surface runoff was partly measured at the main tributary and partly simulated using a distributed, catchment, hydrological model, calibrated with the observed discharge. The simplified structure of the developed modelling mainly concerns soil moisture dynamics and bedrock hydraulics, whereas the flow components are physically based. The calibration produced high efficiency coefficients and showed that surface runoff is greatly affected by soil water percolation into fractured bedrock. The bedrock reduces the storm‐flow peaks and the interflow and has important multi‐year effects on the annual runoff coefficients. The net subsurface outflow from the lake was calculated as the residual of the lake water balance. It was almost constant in the dry seasons and increased in the wet seasons, because of the moistening of the unsaturated soil. During the years of observation, rainfall 30% higher than average caused abundant runoff and a continuous rise in the lake water levels. The analysis allows to predict that, in years with lower than the average rainfall, runoff will be drastically reduced and will not be able to compensate for negative balance between precipitation and lake evaporation. Such highly unsteady situations, with great fluctuations in lake levels, are typical of closed catchment‐lake systems in the semi‐arid Mediterranean environment. Copyright © 2012 John Wiley & Sons, Ltd.     

Evaluating and modelling the hydrological and erosive behaviour of an olive orchard microcatchment under no‐tillage with bare soil in Spain

Despite the high risk of erosion in olive orchards located in mountainous areas in Spain, little research has been carried out to account for the complexity and interaction of the natural processes of runoff and soil erosion on the catchment scale or small catchment scale. In this study, a microcatchment of 6·7 ha in a mountainous area under no‐tillage farming with bare soil was set up to record runoff and sediment. Soil erosion and runoff patterns were monitored over a two‐year period. Totally, 22 events were observed. The data were analysed, and then used to calibrate the AnnAGNPS model, which allowed us to complete the data period and describe the hydrological and erosive behaviour on a monthly and annual basis. A high variability in catchment responses was observed, due to differences in the storms and to the effect of the surface soil moisture content. Maximum intensities of 10 and 30 min determined the final runoff values while the total sediment loads were dependent on the rainfall depth. The impact of management on the reduction of porosity can explain the relationship between runoff and intensity in the microcatchment. However, the impact of the spatial scale meant that the transport of sediment required substantial rainfall depths to ensure a continuous flow from the hillslopes. The results of the calibration (E >0·60 and r >0·75) on the event and monthly scale confirmed the applicability of AnnAGNPS to predict runoff and erosion in the microcatchment. The predicted average runoff coefficient was 3·3% for the study period and the total average sediment loads, 1·3 Mg/ha/yr. Despite these low values, the model simulation showed that much larger runoff coefficients and soil losses can be expected for periods with several consecutive years in which the annual rainfall depth was over 500 mm. The use of cover is recommended to prevent the high levels of erosion associated with these conditions. Copyright © 2009 John Wiley & Sons, Ltd.