A physically based distributed subsurface–surface flow dynamics model for forested mountainous catchments

This study was designed to develop a physically based hydrological model to describe the hydrological processes within forested mountainous river basins. The model describes the relationships between hydrological fluxes and catchment characteristics that are influenced by topography and land cover. Hydrological processes representative of temperate basins in steep terrain that are incorporated in the model include intercepted rainfall, evaporation, transpiration, infiltration into macropores, partitioning between preferential flow and soil matrix flow, percolation, capillary rise, surface flow (saturation‐excess and return flow), subsurface flow (preferential subsurface flow and baseflow) and spatial water‐table dynamics. The soil–vegetation–atmosphere transfer scheme used was the single‐layer Penman–Monteith model, although a two‐layer model was also provided. The catchment characteristics include topography (elevation, topographic indices), slope and contributing area, where a digital elevation model provided flow direction on the steepest gradient flow path. The hydrological fluxes and catchment characteristics are modelled based on the variable source‐area concept, which defines the dynamics of the watershed response. Flow generated on land for each sub‐basin is routed to the river channel by a kinematic wave model. In the river channel, the combined flows from sub‐basins are routed by the Muskingum–Cunge model to the river outlet; these comprise inputs to the river downstream. The model was applied to the Hikimi river basin in Japan. Spatial decadal values of the normalized difference vegetation index and leaf area index were used for the yearly simulations. Results were satisfactory, as indicated by model efficiency criteria, and analysis showed that the rainfall input is not representative of the orographic lifting induced rainfall in the mountainous Hikimi river basin. Also, a simple representation of the effects of preferential flow within the soil matrix flow has a slight significance for soil moisture status, but is insignificant for river flow estimations. Copyright © 2005 John Wiley & Sons, Ltd.     

Including spatial distribution in a data‐driven rainfall‐runoff model to improve reservoir inflow forecasting in Taiwan

Multi‐step ahead inflow forecasting has a critical role to play in reservoir operation and management in Taiwan during typhoons as statutory legislation requires a minimum of 3‐h warning to be issued before any reservoir releases are made. However, the complex spatial and temporal heterogeneity of typhoon rainfall, coupled with a remote and mountainous physiographic context, makes the development of real‐time rainfall‐runoff models that can accurately predict reservoir inflow several hours ahead of time challenging. Consequently, there is an urgent, operational requirement for models that can enhance reservoir inflow prediction at forecast horizons of more than 3 h. In this paper, we develop a novel semi‐distributed, data‐driven, rainfall‐runoff model for the Shihmen catchment, north Taiwan. A suite of Adaptive Network‐based Fuzzy Inference System solutions is created using various combinations of autoregressive, spatially lumped radar and point‐based rain gauge predictors. Different levels of spatially aggregated radar‐derived rainfall data are used to generate 4, 8 and 12 sub‐catchment input drivers. In general, the semi‐distributed radar rainfall models outperform their less complex counterparts in predictions of reservoir inflow at lead times greater than 3 h. Performance is found to be optimal when spatial aggregation is restricted to four sub‐catchments, with up to 30% improvements in the performance over lumped and point‐based models being evident at 5‐h lead times. The potential benefits of applying semi‐distributed, data‐driven models in reservoir inflow modelling specifically, and hydrological modelling more generally, are thus demonstrated. Copyright © 2012 John Wiley & Sons, Ltd.     

Regional differences in hydrological response to canopy interception schemes in a land surface model

Two different canopy interception schemes are applied to the parameterization of the hydrological processes in the Community Land Model version 3. One scheme treats rainfall and canopy water storage as spatially uniform within each model grid cell, and the other scheme considers sub‐grid variability of rainfall and water storage in the parameterization of canopy hydrological processes. The hydrological responses to differences between these two schemes in different regions are studied. It is found that the impact of the sub‐grid variability in the tropical regions is generally greater than the extra‐tropical regions. However, such impact can't be negligible for the extra‐tropical regions. Soil water in the total 3.4 m soil depth increases by 3% for Central‐South Europe, and vegetation temperature increases by 0.14 °C for Southeastern United States if the regional averages are considered. The magnitude of the impact is greater if the analysis focuses on the specific grid cells in these regions. The impact is tightly correlated with rainfall amount and vegetation density. The correlation coefficient between such impact and rainfall amount and vegetation density varies with regions and hydrological variables, with the largest value of 0.92 for interception loss in Amazonia. Our results indicate that the impact of the sub‐grid variability on hydrological processes in the extra‐tropical areas is also important, although rainfall amount and vegetation density in these areas are not as high as in the tropical areas. Copyright © 2013 John Wiley & Sons, Ltd.     

Gypsies in the palace: experimentalist's view on the use of 3‐D physics‐based simulation of hillslope hydrological response

As a fundamental unit of the landscape, hillslopes are studied for their retention and release of water and nutrients across a wide range of ecosystems. The understanding of these near‐surface processes is relevant to issues of runoff generation, groundwater–surface water interactions, catchment export of nutrients, dissolved organic carbon, contaminants (e.g. mercury) and ultimately surface water health. We develop a 3‐D physics‐based representation of the Panola Mountain Research Watershed experimental hillslope using the TOUGH2 sub‐surface flow and transport simulator. A recent investigation of sub‐surface flow within this experimental hillslope has generated important knowledge of threshold rainfall‐runoff response and its relation to patterns of transient water table development. This work has identified components of the 3‐D sub‐surface, such as bedrock topography, that contribute to changing connectivity in saturated zones and the generation of sub‐surface stormflow. Here, we test the ability of a 3‐D hillslope model (both calibrated and uncalibrated) to simulate forested hillslope rainfall‐runoff response and internal transient sub‐surface stormflow dynamics. We also provide a transparent illustration of physics‐based model development, issues of parameterization, examples of model rejection and usefulness of data types (e.g. runoff, mean soil moisture and transient water table depth) to the model enterprise. Our simulations show the inability of an uncalibrated model based on laboratory and field characterization of soil properties and topography to successfully simulate the integrated hydrological response or the distributed water table within the soil profile. Although not an uncommon result, the failure of the field‐based characterized model to represent system behaviour is an important challenge that continues to vex scientists at many scales. We focus our attention particularly on examining the influence of bedrock permeability, soil anisotropy and drainable porosity on the development of patterns of transient groundwater and sub‐surface flow. Internal dynamics of transient water table development prove to be essential in determining appropriate model parameterization. Copyright © 2010 John Wiley & Sons, Ltd.     

Fuzzy computing based rainfall–runoff model for real time flood forecasting

This paper analyses the skills of fuzzy computing based rainfall–runoff model in real time flood forecasting. The potential of fuzzy computing has been demonstrated by developing a model for forecasting the river flow of Narmada basin in India. This work has demonstrated that fuzzy models can take advantage of their capability to simulate the unknown relationships between a set of relevant hydrological data such as rainfall and river flow. Many combinations of input variables were presented to the model with varying structures as a sensitivity study to verify the conclusions about the coherence between precipitation, upstream runoff and total watershed runoff. The most appropriate set of input variables was determined, and the study suggests that the river flow of Narmada behaves more like an autoregressive process. As the precipitation is weighted only a little by the model, the last time‐steps of measured runoff are dominating the forecast. Thus a forecast based on expected rainfall becomes very inaccurate. Although good results for one‐step‐ahead forecasts are received, the accuracy deteriorates as the lead time increases. Using the one‐step‐ahead forecast model recursively to predict flows at higher lead time, however, produces better results as opposed to different independent fuzzy models to forecast flows at various lead times. Copyright © 2004 John Wiley & Sons, Ltd.     

Multi‐decadal variability of drought risk,eastern Australia

A number of previous studies have identified changes in the climate occurring on decadal to multi‐decadal time‐scales. Recent studies also have revealed multi‐decadal variability in the modulation of the magnitude of El Niño–Southern Oscillation (ENSO) impacts on rainfall and stream flow in Australia and other areas. This study investigates multi‐decadal variability of drought risk by analysing the performance of a water storage reservoir in New South Wales, Australia, during different climate epochs defined using the Inter‐decadal Pacific Oscillation (IPO) index. The performance of the reservoir is also analysed under three adaptive management techniques and these are compared with the reservoir performance using the current ‘reactive’ management practices. The results indicate that IPO modulation of both the magnitude and frequency of ENSO events has the effect of reducing and elevating drought risk on multi‐decadal time‐scales. The results also confirm that adaptive reservoir management techniques, based on ENSO forecasts, can improve drought security and become significantly more important during dry climate epochs. These results have marked implications for improving drought security for water storage reservoirs. Copyright © 2004 John Wiley & Sons, Ltd.     

The droughts of 1996–1997 and 2004–2005 in Amazonia: hydrological response in the river main‐stem

Severe hydrological droughts in the Amazon have generally been associated with strong El Niño events. More than 100 years of stage record at Manaus harbour confirms that minimum water levels generally coincide with intense warming in the tropical Pacific sea waters. During 2005, however, the Amazon experienced a severe drought which was not associated with an El Niño event. Unless what usually occurs during strong El Niño events, when negative rainfall anomalies usually affect central and eastern Amazon drainage basin; rainfall deficiencies in the drought of 2005 were spatially constrained to the west and southwest of the basin. In spite of this, discharge stations at the main‐stem recorded minimum water levels as low as those observed during the basin‐wide 1996–1997 El Niño‐related drought. The analysis of river discharges along the main‐stem and major tributaries during the drought of 2004–2005 revealed that the recession on major tributaries began almost simultaneously. This was not the case in the 1996–1997 drought, when above‐normal contribution of some tributaries for a short period during high water was crucial to partially counterbalance high discharge deficits of the other tributaries. Since time‐lagged contributions of major tributaries are fundamental to damp the extremes in the main‐stem, an almost coincident recession in almost all tributaries caused a rapid decrease in water discharges during the 2005 event. Copyright © 2010 John Wiley & Sons, Ltd.     

Validation of a full hydrodynamic model for large‐scale hydrologic modelling in the Amazon

A key aspect of large river basins partially neglected in large‐scale hydrological models is river hydrodynamics. Large‐scale hydrologic models normally simulate river hydrodynamics using simplified models that do not represent aspects such as backwater effects and flood inundation, key factors for some of the largest rivers of the world, such as the Amazon. In a previous paper, we have described a large‐scale hydrodynamic approach resultant from an improvement of the MGB‐IPH hydrological model. It uses full Saint Venant equations, a simple storage model for flood inundation and GIS‐based algorithms to extract model parameters from digital elevation models. In the present paper, we evaluate this model in the Solimões River basin. Discharge results were validated using 18 stream gauges showing that the model is accurate. It represents the large delay and attenuation of flood waves in the Solimões basin, while simplified models, represented here by Muskingum Cunge, provide hydrographs are wrongly noisy and in advance. Validation against 35 stream gauges shows that the model is able to simulate observed water levels with accuracy, representing their amplitude of variation and timing. The model performs better in large rivers, and errors concentrate in small rivers possibly due to uncertainty in river geometry. The validation of flood extent results using remote sensing estimates also shows that the model accuracy is comparable to other flood inundation modelling studies. Results show that (i) river‐floodplain water exchange and storage, and (ii) backwater effects play an important role for the Amazon River basin hydrodynamics. Copyright © 2011 John Wiley & Sons, Ltd.     

A simple rainfall–runoff model based on hydrological units applied to the Teba catchment (south‐east Spain)

A hydrological model (YWB, yearly water balance) has been developed to model the daily rainfall–runoff relationship of the 202 km² Teba river catchment, located in semi‐arid south‐eastern Spain. The period of available data (1976–1993) includes some very rainy years with intensive storms (responsible for flooding parts of the town of Malaga) and also some very dry years. The YWB model is in essence a simple tank model in which the catchment is subdivided into a limited number of meaningful hydrological units. Instead of generating per unit surface runoff resulting from infiltration excess, runoff has been made the result of storage excess. Actual evapotranspiration is obtained by means of curves, included in the software, representing the relationship between the ratio of actual to potential evapotranspiration as a function of soil moisture content for three soil texture classes. The total runoff generated is split between base flow and surface runoff according to a given baseflow index. The two components are routed separately and subsequently joined. A large number of sequential years can be processed, and the results of each year are summarized by a water balance table and a daily based rainfall runoff time series. An attempt has been made to restrict the amount of input data to the minimum. Interactive manual calibration is advocated in order to allow better incorporation of field evidence and the experience of the model user. Field observations allowed for an approximate calibration at the hydrological unit level. Copyright © 2001 John Wiley & Sons, Ltd.     

Hydrological Outlook UK: an operational streamflow and groundwater level forecasting system at monthly to seasonal time scales

This paper describes the development of the first operational seasonal hydrological forecasting service for the UK, the Hydrological Outlook UK (HOUK). Since June 2013, this service has delivered monthly forecasts of streamflow and groundwater levels, with an emphasis on forecasting hydrological conditions over the next three months, accompanied by outlooks over longer time horizons. This system is based on three complementary approaches combined to produce the outlooks: (i) national-scale modelling of streamflow and groundwater levels based on dynamic seasonal rainfall forecasts, (ii) catchment-scale modelling where streamflow and groundwater level models are driven by historical meteorological forcings (i.e. the Ensemble Streamflow Prediction, ESP, approach), and (iii) a catchment-scale statistical method based on persistence and historical analogues. This paper provides the background to the Hydrological Outlook, describes the various component methods in detail and then considers the impact and usefulness of the product. As an example of a multi-method, operational seasonal hydrological forecasting system, it is hoped that this overview provides useful information and context for other forecasting initiatives around the world.     

Response of hydrological processes to land‐cover and climate changes in Kejie watershed,south‐west China

Land‐cover/climate changes and their impacts on hydrological processes are of widespread concern and a great challenge to researchers and policy makers. Kejie Watershed in the Salween River Basin in Yunnan, south‐west China, has been reforested extensively during the past two decades. In terms of climate change, there has been a marked increase in temperature. The impact of these changes on hydrological processes required investigation: hence, this paper assesses aspects of changes in land cover and climate. The response of hydrological processes to land‐cover/climate changes was examined using the Soil and Water Assessment Tool (SWAT) and impacts of single factor, land‐use/climate change on hydrological processes were differentiated. Land‐cover maps revealed extensive reforestation at the expense of grassland, cropland, and barren land. A significant monotonic trend and noticeable changes had occurred in annual temperature over the long term. Long‐term changes in annual rainfall and streamflow were weak; and changes in monthly rainfall (May, June, July, and September) were apparent. Hydrological simulations showed that the impact of climate change on surface water, baseflow, and streamflow was offset by the impact of land‐cover change. Seasonal variation in streamflow was influenced by seasonal variation in rainfall. The earlier onset of monsoon and the variability of rainfall resulted in extreme monthly streamflow. Land‐cover change played a dominant role in mean annual values; seasonal variation in surface water and streamflow was influenced mainly by seasonal variation in rainfall; and land‐cover change played a regulating role in this. Surface water is more sensitive to land‐cover change and climate change: an increase in surface water in September and May due to increased rainfall was offset by a decrease in surface water due to land‐cover change. A decrease in baseflow caused by changes in rainfall and temperature was offset by an increase in baseflow due to land‐cover change. Copyright © 2009 John Wiley & Sons, Ltd.     

Simulating saturation‐excess surface run‐off in a semi‐distributed hydrological model

The level of complexity, and the number of parameters, to include in a hydrological model is a relatively contentious issue in hydrological modelling. However, it can be argued that explicitly representing important run‐off generation processes can improve the practical value of a model's outputs. This paper explores the benefits of including a new function into an existing semi‐distributed hydrological model (the Pitman model) that is widely used in the sub‐Saharan Africa region. The new function was designed to represent saturation‐excess surface run‐off processes at subcatchment scales and was motivated by the evidence of dambo (low topography riparian areas) type features in many sub‐Saharan river basins. The results for uncertainty versions of the model, with and without the new function, were compared for 25 catchments, which were divided up into those where evidence of dambos exists and those where there is no such evidence. The results suggest that the new function certainly improves the model results for the catchments where dambos exist, but not in situations where saturation‐excess surface run‐off is not expected to occur. The overall conclusion is therefore that the addition of the new function is justified.     

A review of continental scale hydrological models and their suitability for drought forecasting in (sub-Saharan) Africa

The aim of this review is to provide a basis for selecting a suitable hydrological model, or combination of models, for hydrological drought forecasting in Africa at different temporal and spatial scales; for example short and medium range (1–10 days or monthly) forecasts at medium to large river basin scales or seasonal forecasts at the Pan-African scale. Several global hydrological models are currently available with different levels of complexity and data requirements. However, most of these models are likely to fail to properly represent the water balance components that are particularly relevant in arid and semi-arid basins in sub-Saharan Africa. This review critically looks at weaknesses and strengths in the representation of different hydrological processes and fluxes of each model. The major criteria used for assessing the suitability of the models are (1) the representation of the processes that are most relevant for simulating drought conditions, such as interception, evaporation, surface water-groundwater interactions in wetland areas and flood plains and soil moisture dynamics; (2) the capability of the model to be downscaled from a continental scale to a large river basin scale model; and (3) the applicability of the model to be used operationally for drought early warning, given the data availability of the region. This review provides a framework for selecting models for hydrological drought forecasting, conditional on spatial scale, data availability and end-user forecast requirements. Among 16 well known hydrological and land surface models selected for this review, PCR-GLOBWB, GWAVA, HTESSEL, LISFLOOD and SWAT show higher potential and suitability for hydrological drought forecasting in Africa based on the criteria used in this evaluation.     

Retrieving Groundwater Depletion and Drought in the Tigris‐Euphrates Basin Between 2003 and 2015

Quantitative estimates of the groundwater depletion and droughts in the Tigris‐Euphrates Basin (TEB) can be useful for sustainably managing its water resources. Here, data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are used to infer the monthly changes in the total water storage of the TEB from January 2003 to December 2015. Additionally, the data of altimetry and output from land surface models are used to remove the contributions from lake water changes and other hydrological factors to obtain the total groundwater depletion (TGWD), human‐driven groundwater depletion (HGWD), and climate‐driven groundwater depletion. We conclude that an alarming rate of decrease in the total water storage and the loss of TGWD have an “accelerating” trend, as the trend during 2007 to 2015 was 3.6 times that during 2003 to 2006. Moreover, the HGWD is 116.09 Gt, which accounts for 98% of the TGWD. Finally, the total storage deficit index (TSDI) is derived from the GRACE data to characterize the drought of the TEB. The results show that TSDI agrees well with the actual drought rather than the Palmer drought severity index (PDSI) and that the TEB has been undergoing a severe drought since September 2007 according to both the TSDI and PDSI. The research in this study provides an effective and unique method for understanding the hydrological processes and sustainable use of water resources in regions or countries with little data, which is essential for more efficient, sustainable, and cross‐boundary cooperative water resource management.     

The cold rain‐on‐snow event of June 2013 in the Canadian Rockies — characteristics and diagnosis

The June 2013 flood in the Canadian Rockies featured rain‐on‐snow (ROS) runoff generation at alpine elevations that contributed to the high streamflows observed during the event. Such a mid‐summer ROS event has not been diagnosed in detail, and a diagnosis may help to understand future high discharge‐producing hydrometeorological events in mountainous cold regions. The alpine hydrology of the flood was simulated using a physically based model created with the modular cold regions hydrological modelling platform. The event was distinctive in that, although at first, relatively warm rain fell onto existing snowdrifts inducing ROS melt; the rainfall turned to snowfall as the air mass cooled and so increased snowcover and snowpacks in alpine regions, which then melted rapidly from ground heat fluxes in the latter part of the event. Melt rates of existing snowpacks were substantially lower during the ROS than during the relatively sunny periods preceding and following the event as a result of low wind speeds, cloud cover and cool temperatures. However, at the basin scale, melt volumes increased during the event as a result of increased snowcover from the fresh snowfall and consequent large ground heat contributions to melt energy, causing snowmelt to enhance rainfall–runoff by one fifth. Flow pathways also shifted during the event from relatively slow sub‐surface flow prior to the flood to an even contribution from sub‐surface and fast overland flow during and immediately after the event. This early summer, high precipitation ROS event was distinctive for the impact of decreased solar irradiance in suppressing melt rates, the contribution of ground heat flux to basin scale snowmelt after precipitation turned to snowfall, the transition from slow sub‐surface to fast overland flow runoff as the sub‐surface storage saturated and streamflow volumes that exceeded precipitation. These distinctions show that summer, mountain ROS events should be considered quite distinct from winter ROS and can be important contributors to catastrophic events. Copyright © 2016 John Wiley & Sons, Ltd.     

The data‐driven approach as an operational real‐time flood forecasting model

Accurate water level forecasts are essential for flood warning. This study adopts a data‐driven approach based on the adaptive network–based fuzzy inference system (ANFIS) to forecast the daily water levels of the Lower Mekong River at Pakse, Lao People's Democratic Republic. ANFIS is a hybrid system combining fuzzy inference system and artificial neural networks. Five ANFIS models were developed to provide water level forecasts from 1 to 5 days ahead, respectively. The results show that although ANFIS forecasts of water levels up to three lead days satisfied the benchmark, four‐ and five‐lead‐day forecasts were only slightly better in performance compared with the currently adopted operational model. This limitation is imposed by the auto‐ and cross‐correlations of the water level time series. Output updating procedures based on the autoregressive (AR) and recursive AR (RAR) models were used to enhance ANFIS model outputs. The RAR model performed better than the AR model. In addition, a partial recursive procedure that reduced the number of recursive steps when applying the AR or the RAR model for multi‐step‐ahead error prediction was superior to the fully recursive procedure. The RAR‐based partial recursive updating procedure significantly improved three‐, four‐ and five‐lead‐day forecasts. Our study further shows that for long lead times, ANFIS model errors are dominated by lag time errors. Although the ANFIS model with the RAR‐based partial recursive updating procedure provided the best results, this method was able to reduce the lag time errors significantly for the falling limbs only. Improvements for the rising limbs were modest. Copyright © 2011 John Wiley & Sons, Ltd.     

A hydrologic routing model suitable for climate‐scale simulations of arctic rivers: application to the Mackenzie River Basin

In this study, the Hillslope River Routing (HRR) model was modified for arctic river basin applications and used to route surface and subsurface run‐off from the Community Land Model (CLM) in the Mackenzie River Basin (MRB) for the period 2000–2004. The HRR modelling framework performs lateral surface and subsurface run‐off routing from hillslopes and channel/floodplain routing. The HRR model was modified here to include a variable subsurface active layer thickness (ALT; permafrost) to enable subsurface water to resurface, a distributed surface storage component to store and attenuate the rapid generation of snowmelt water, compound hillslopes to account for the low relief near rivers and floodplains, and reservoir routing to complete the total surface and subsurface water storage accounting. To illustrate the new HRR model components, a case study is presented for the MRB. The basin is discretized into 5077 sub‐basins based on a drainage network derived from the global digital elevation model (DEM) developed from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor on board NASA's Terra satellite and river widths extracted from LandSat images. The median hillslope land area is 68.5 km² with a flow length of 2.8 km. Gridded CLM surface and subsurface run‐offs are remapped to the HRR model's irregular sub‐basins. The role of each new model component is quantified in terms of peak annual streamflow (magnitude and timing) at select locations and basin‐wide total water storage anomalies. The role of distributed surface storage is shown to attenuate the relatively rapid generation of snowmelt water, impact the annual peak hydrograph (reduced peaks by >30% and detailed peak by >20 days), and account for 20% of the monthly total water storage anomalies averaged over the year and ranging from 14 to 25% (?10 to 30 mm) throughout the year. Although additional research is needed to dynamically link spatially distributed ALT to HRR, the role of ALT is shown to be important. A basin‐wide, uniform 1 m ALT impacts the annual peak hydrograph (reduced peaks by 9% and detailed peak by 8 days) and trends in total water storage anomalies. Copyright © 2014 John Wiley & Sons, Ltd.     

Simulating and predicting river discharge time series using a wavelet‐neural network hybrid modelling approach

Accurate simulation and prediction of the dynamic behaviour of a river discharge over any time interval is essential for good watershed management. It is difficult to capture the high‐frequency characteristics of a river discharge using traditional time series linear and nonlinear model approaches. Therefore, this study developed a wavelet‐neural network (WNN) hybrid modelling approach for the predication of river discharge using monthly time series data. A discrete wavelet multiresolution method was employed to decompose the time series data of river discharge into sub‐series with low (approximation) and high (details) frequency, and these sub‐series were then used as input data for the artificial neural network (ANN). WNN models with different wavelet decomposition levels were employed to predict river discharge 48 months ahead of time. Comparison of results from the WNN models with those of the ANN models alone indicated that WNN models performed a more accurate prediction. Copyright © 2011 John Wiley & Sons, Ltd.     

The importance of surface controls on overland flow connectivity in semi‐arid environments: results from a numerical experimental approach

In semi‐arid environments, the characteristics of the land surface determine how rainfall is transformed into surface runoff and influences how this runoff moves from the hillslopes into river channels. Whether or not water reaches the river channel is determined by the hydrological connectivity. This paper uses a numerical experiment‐based approach to systematically assess the effects of slope length, gradient, flow path convergence, infiltration rates and vegetation patterns on the generation and connectivity of runoff. The experiments were performed with the Connectivity of Runoff Model, 2D version distributed, physically based, hydrological model. The experiments presented are set within a semi‐arid environment, characteristic of south‐eastern Spain, which is subject to low frequency high rainfall intensity storm events. As a result, the dominant hydrological processes are infiltration excess runoff generation and surface flow dynamics. The results from the modelling experiments demonstrate that three surface factors are important in determining the form of the discharge hydrograph: the slope length, the slope gradient and the infiltration characteristics at the hillslope‐channel connection. These factors are all related to the time required for generated runoff to reach an efficient flow channel, because once in this channel, the transmission losses significantly decrease. Because these factors are distributed across the landscape, they have a fundamental role in controlling the landscape hydrological response to storm events. Copyright © 2013 John Wiley & Sons, Ltd.     

Thresholds for run‐off generation in a drained closed depression

Hydrological threshold behaviour has been observed across hillslopes and catchments with varying characteristics. Few studies, however, have evaluated rainfall–run‐off response in areas dominated by agricultural land use and artificial subsurface drainage. Hydrograph analysis was used to identify distinct hydrological events over a 9‐year period and examine rainfall characteristics, dynamic water storage, and surface and subsurface run‐off generation in a drained and farmed closed depression in north‐eastern Indiana, USA. Results showed that both surface flow and subsurface tile flow displayed a threshold relationship with the sum of rainfall amount and soil moisture deficit (SMD). Neither surface flow nor subsurface tile flow was observed unless rainfall amount exceeded the SMD. Timing of subsurface tile flow relative to soil moisture response on the shoulder slope of the depression indicated that the formation and drainage of perched water tables on depression hillslopes were likely the main mechanism that produced subsurface connectivity. Surface flow generation was delayed compared with subsurface tile flow during rainfall events due to differences in soil water storage along depression hillslopes and run‐off generation mechanisms. These findings highlight the substantial impact of subsurface tile drainage on the hydrology of closed depressions; the bottom of the depression, the wettest area prior to drainage installation, becomes the driest part of the depression after installation of subsurface drainage. Rapid connectivity of localized subsurface saturation zones during rainfall events is also greatly enhanced because of subsurface drainage. Thus, less fill is required to generate substantial spill. Understanding hydrologic processes in drained and farmed closed depressions is a critical first step in developing improved water and nutrient management strategies in this landscape.