Predicting phosphorus dynamics in complex terrains using a variable source area hydrology model

Phosphorus (P) loss from agricultural watersheds has long been a critical water quality problem, the control of which has been the focus of considerable research and investment. Preventing P loss depends on accurately representing the hydrological and chemical processes governing P mobilization and transport. The Soil and Water Assessment Tool (SWAT) is a watershed model commonly used to predict run‐off and non‐point source pollution transport. SWAT simulates run‐off employing either the curve number (CN) or the Green and Ampt methods, both assume infiltration‐excess run‐off, although shallow soils underlain by a restricting layer commonly generate saturation‐excess run‐off from variable source areas (VSA). In this study, we compared traditional SWAT with a re‐conceptualized version, SWAT‐VSA, that represents VSA hydrology, in a complex agricultural watershed in east central Pennsylvania. The objectives of this research were to provide further evidence of SWAT‐VSA's integrated and distributed predictive capabilities against measured surface run‐off and stream P loads and to highlight the model's ability to drive sub‐field management of P. Thus, we relied on a detailed field management database to parameterize the models. SWAT and SWAT‐VSA predicted discharge similarly well (daily Nash–Sutcliffe efficiencies of 0.61 and 0.66, respectively), but SWAT‐VSA outperformed SWAT in predicting P export from the watershed. SWAT estimated lower P loss (0.0–0.25 kg ha^?1) from agricultural fields than SWAT‐VSA (0.0–1.0+ kg ha^?1), which also identified critical source areas – those areas generating large run‐off and P losses at the sub‐field level. These results support the use of SWAT‐VSA in predicting watershed‐scale P losses and identifying critical source areas of P loss in landscapes with VSA hydrology. Copyright © 2014 John Wiley & Sons, Ltd.     

Improvement and comparison of the rainfall–runoff methods in SWAT at the monsoonal watershed of Baocun,Eastern China

ABSTRACT

A new physics-based rainfall–runoff method of the Soil and Water Assessment Tool (SWAT) was developed, which integrates a water balance (WB) approach with the variable source area (WB-VSA). This approach was further compared with four methods—soil-water-dependent curve number (CN-Soil), evaporation-dependent curve number (CN-ET), Green and Ampt equation (G&A) and WB—in a monsoonal watershed, Eastern China. The regional sensitivity analysis shows that volumetric efficiency coefficient (VE) with river discharges is sensitive to the most parameters of all approaches. The results of model calibration against VE demonstrate that WB-VSA is the most accurate owing to its reflection of the spatial variation of runoff generation as affected by topography and soil properties. Other methods can also mimic baseflow well, but the G&A and CN-ET simulate floods much worse than the saturation excess runoff approaches (WB-VSA, WB and CN-Soil). Meanwhile, CN-Soil as an empirical method fails to simulate groundwater levels. By contrast, WB-VSA captures them best.

Editor M.C. Acreman; Associate editor S. Kanae     

Development of a soil moisture‐based distributed hydrologic model for determining hydrologically based critical source areas

A simple grid cell‐based distributed hydrologic model was developed to provide spatial information on hydrologic components for determining hydrologically based critical source areas. The model represents the critical process (soil moisture variation) to run‐off generation accounting for both local and global water balance. In this way, it simulates both infiltration excess run‐off and saturation excess run‐off. The model was tested by multisite and multivariable evaluation on the 50‐km² Little River Experimental Watershed I in Georgia, U.S. and 2 smaller nested subwatersheds. Water balance, hydrograph, and soil moisture were simulated and compared to observed data. For streamflow calibration, the daily Nash‐Sutcliffe coefficient was 0.78 at the watershed outlet and 0.56 and 0.75 at the 2 nested subwatersheds. For the validation period, the Nash‐Sutcliffe coefficients were 0.79 at the watershed outlet and 0.85 and 0.83 at the 2 subwatersheds. The per cent bias was less than 15% for all sites. For soil moisture, the model also predicted the rising and declining trends at 4 of the 5 measurement sites. The spatial distribution of surface run‐off simulated by the model was mainly controlled by local characteristics (precipitation, soil properties, and land cover) on dry days and by global watershed characteristics (relative position within the watershed and hydrologic connectivity) on wet days when saturation excess run‐off was simulated. The spatial details of run‐off generation and travel time along flow paths provided by the model are helpful for watershed managers to further identify critical source areas of non‐point source pollution and develop best management practices.     

Dynamics of stormflow generation—A hillslope‐scale field study in east‐central Pennsylvania,USA

A 40 m × 20 m mowed, grass hillslope adjacent to a headwater stream within a 26‐ha watershed in east‐central Pennsylvania, USA, was instrumented to identify and map the extent and dynamics of surface saturation (areas with the water table at the surface) and surface runoff source areas. Rainfall, stream flow and surface runoff from the hillslope were recorded at 5‐min intervals from 11 August to 22 November 1998, and 13 April to 12 November 1999. The dynamics of the water table (0 to 45 cm depth from the soil surface) and the occurrence of surface runoff source areas across the hillslope were recorded using specially designed subsurface saturation and surface runoff sensors, respectively. Detailed data analyses for two rainfall events that occurred in August (57·7 mm in 150 min) and September (83·6 mm in 1265 min) 1999, illustrated the spatial and temporal dynamics of surface saturation and surface runoff source areas. Temporal data analyses showed the necessity to measure the hillslope dynamics at time intervals comparable to that of rainfall measurements. Both infiltration excess surface runoff (runoff caused when rainfall intensity exceeds soil infiltration capacity) and saturation excess surface runoff (runoff caused when soil moisture storage capacity is exceeded) source areas were recorded during these rainfall events. The August rainfall event was primarily an infiltration excess surface runoff event, whereas the September rainfall event produced both infiltration excess and saturation excess surface runoff. Occurrence and disappearance of infiltration excess surface runoff source areas during the rainfall events appeared scattered across the hillslope. Analysis of surface saturation and surface runoff data showed that not all surface saturation areas produced surface runoff that reached the stream. Emergence of subsurface flow to the surface during the post‐rainfall periods appeared to be a major flow process dominating the hillslope after the August rainfall event. Copyright © 2002 John Wiley & Sons, Ltd.     

Identifying and linking source areas of flow and P transport in dairy‐grazed headwater catchments,North Island,New Zealand

We examined the applicability of the critical‐source area (CSA) concept to the dairy‐grazed 192‐ha Upper Toenepi catchment and its 8·7‐ha Kiwitahi sub‐catchment, New Zealand. We evaluated if phosphorus (P) transport from land into stream is dominated by saturation‐excess (SE) and infiltration‐excess (IE) runoff during stormflow and by sub‐surface (<1·5 m depth) flows during baseflow. We measured stream flow and shallow groundwater levels, collected monthly stream, tile drain (TDA) and groundwater samples, and flow‐proportional stream samples from the Kiwitahi sub‐catchment, and determined their dissolved reactive phosphorus (DRP) and total phosphorus (TP) concentrations. In the Kiwitahi sub‐catchment, during storm events, IE contributions were significant. Contributions from SE appeared significant in the Upper Toenepi catchment. However, in both catchments, sub‐surface contributions dominated stormflow and baseflow periods. Absence of water table at the surface and the water table gradient towards the stream indicated that P transport during events was not limited to surface runoff. The dynamics of the groundwater table and the occurrence of SE areas were influenced by proximity to the stream and hillslope positions. Baseflow accounted for 42% of the annual flow in the Kiwitahi sub‐catchment, and contributed 37 and 52% to the DRP and TP loads, respectively. The P transport during baseflow appeared equally important as P losses from CSAs during stormflow. The close resemblance in P levels between groundwater and stream samples during baseflow demonstrates the importance of shallow groundwater for stream flow. In the Upper Toenepi catchment, contributions from effluent ponds (EFFs) dominated P loads. Management strategies should focus on controlling P release from EFFs, and on decreasing Olsen P concentrations in soil to minimize leaching of P via sub‐surface flow to streams. Research is needed to quantify the role of sub‐surface flow as well as to expand management strategies to minimize P transfers during stormflow and baseflow conditions. Copyright © 2010 John Wiley & Sons, Ltd.     

Predicting saturation‐excess runoff distribution with a lumped hillslope model: SWAT‐HS

Saturation‐excess runoff is the major runoff mechanism in humid well‐vegetated areas where infiltration rates often exceed rainfall intensity. Although the Soil and Water Assessment Tool (SWAT) is one of the most widely used models, it predicts runoff based mainly on soil and land use characteristics, and is implicitly an infiltration‐excess runoff type of model. Previous attempts to incorporate the saturation‐excess runoff mechanism in SWAT fell short due to the inability to distribute water from one hydrological response unit to another. This paper introduces a modified version of SWAT, referred to as SWAT‐Hillslope (SWAT‐HS). This modification improves the simulation of saturation‐excess runoff by redefining hydrological response units based on wetness classes and by introducing a surface aquifer with the ability to route interflow from “drier” to “wetter” wetness classes. Mathematically, the surface aquifer is a nonlinear reservoir that generates rapid subsurface stormflow as the water table in the surface aquifer rises. The SWAT‐HS model was tested in the Town Brook watershed in the upper reaches of the West Branch Delaware River in the Catskill region of New York, USA. SWAT‐HS predicted discharge well with a Nash‐Sutcliffe Efficiency of 0.68 and 0.87 for daily and monthly time steps. Compared to the original SWAT model, SWAT‐HS predicted less surface runoff and groundwater flow and more lateral flow. The saturated areas predicted by SWAT‐HS were concentrated in locations with a high topographic index and were in agreement with field observations. With the incorporation of topographic characteristics and the addition of the surface aquifer, SWAT‐HS improved streamflow simulation and gave a good representation of saturated areas on the dates that measurements were available. SWAT‐HS is expected to improve water quality model predictions where the location of the surface runoff matters.     

A statistically based runoff‐yield model coupling infiltration excess and saturation excess mechanisms

A statistically based runoff‐yield model is proposed in this paper. The model considers spatial heterogeneities of rainfall, soil infiltration capacity and soil water storage capacity that are main factors controlling runoff‐yield process. It assumes that the spatial variation of rainfall intensity at each time step can be characterized by a probability density function, which is estimated by matching the hyetograph through goodness‐of‐fit measure, whereas the spatial heterogeneities of soil infiltration capacity and soil water storage capacity are described by parabola‐type functions. Surface runoff is calculated according to infiltration excess mechanism; the statistical distribution of surface runoff rate can be deduced with the joint distribution of rainfall intensity and soil infiltration rate, thus obtaining a quasi‐analytical solution for surface runoff. Based on saturation excess mechanism, the groundwater flow (flows below the ground are collectively referred to as groundwater flow) is calculated by infiltration and the probability distribution of soil water storage capacity. Consequently, the total runoff is composed of infiltration excess and saturation excess runoff components. As an example, this model is applied to flood event simulation in Dongwan catchment, a semi‐humid region and a tributary of Yellow River in China. It indicates that the proposed runoff‐yield model could achieve acceptable accuracy. Copyright © 2011 John Wiley & Sons, Ltd.     

A GIS‐based variable source area hydrology model

Effective control of nonpoint source pollution from contaminants transported by runoff requires information about the source areas of surface runoff. Variable source hydrology is widely recognized by hydrologists, yet few methods exist for identifying the saturated areas that generate most runoff in humid regions. The Soil Moisture Routing model is a daily water balance model that simulates the hydrology for watersheds with shallow sloping soils. The model combines elevation, soil, and land use data within the geographic information system GRASS, and predicts the spatial distribution of soil moisture, evapotranspiration, saturation‐excess overland flow (i.e., surface runoff), and interflow throughout a watershed. The model was applied to a 170 hectare watershed in the Catskills region of New York State and observed stream flow hydrographs and soil moisture measurements were compared to model predictions. Stream flow prediction during non‐winter periods generally agreed with measured flow resulting in an average r² of 0·73, a standard error of 0·01 m³/s, and an average Nash‐Sutcliffe efficiency R² of 0·62. Soil moisture predictions showed trends similar to observations with errors on the order of the standard error of measurements. The model results were most accurate for non‐winter conditions. The model is currently used for making management decisions for reducing non‐point source pollution from manure spread fields in the Catskill watersheds which supply New York City's drinking water. Copyright © 1999 John Wiley & Sons, Ltd.     

Climate change impact assessment of a river basin using CMIP5 climate models and the VIC hydrological model

Climate change has significant impacts on water availability in larger river basins. The present study evaluates the possible impacts of projected future daily rainfall (2011–2099) on the hydrology of a major river basin in peninsular India, the Godavari River Basin, (GRB), under RCP4.5 and RCP8.5 scenarios. The study highlights a criteria-based approach for selecting the CMIP5 GCMs, based on their fidelity in simulating the Indian Summer Monsoon rainfall. The nonparametric kernel regression based statistical downscaling model is employed to project future daily rainfall and the variable infiltration capacity (VIC) macroscale hydrological model is used for hydrological simulations. The results indicate an increase in future rainfall without significant change in the spatial pattern of hydrological variables in the GRB. The climate-change-induced projected hydrological changes provide a crucial input to define water resource policies in the GRB. This methodology can be adopted for the climate change impacts assessment of larger river basins worldwide.     

Improving the spatial representation of soil properties and hydrology using topographically derived initialization processes in the SWAT model

Topography exerts critical controls on many hydrologic, geomorphologic and biophysical processes. However, many watershed modelling systems use topographic data only to define basin boundaries and stream channels, neglecting opportunities to account for topographic controls on processes such as soil genesis, soil moisture distributions and hydrological response. Here, we demonstrate a method that uses topographic data to adjust spatial soil morphologic and hydrologic attributes: texture, depth to the C‐horizon, saturated conductivity, bulk density, porosity and the water capacities at field (33 kpa) and wilting point (1500 kpa) tensions. As a proof of concept and initial performance test, the values of the topographically adjusted soil parameters and those from the Soil Survey Geographic Database (SSURGO; available at 1 : 20 000 scale) were compared with measured soil pedon pit data in the Grasslands Soil and Water Research Lab watershed in Riesel, TX. The topographically adjusted soils were better correlated with the pit measurements than were the SSURGO values. We then incorporated the topographically adjusted soils into an initialization of the Soil and Water Assessment Tool model for 15 Riesel research watersheds to investigate how changes in soil properties influence modelled hydrological responses at the field scale. The results showed that the topographically adjusted soils produced better runoff predictions in 50% of the fields, with the SSURGO soils performing better in the remainder. In addition, the a priori adjusted soils result in fewer calibrated model parameters. These results indicate that adjusting soil properties based on topography can result in more accurate soil characterization and, in some cases, improve model performance. Copyright © 2016 John Wiley & Sons, Ltd.     

A non-linear perturbation model considering catchment wetness and its application in river flow forecasting

A non-linear perturbation model for river flow forecasting is developed, based on consideration of catchment wetness using an antecedent precipitation index (API). Catchment seasonality, of the form accounted for in the linear perturbation model (the LPM), and non-linear behaviour both in the runoff generation mechanism and in the flow routing processes are represented by a constrained non-linear model, the NLPM-API. A total of ten catchments, across a range of climatic conditions and catchment area magnitudes, located in China and in other countries, were selected for testing daily rainfall-runoff forecasting with this model. It was found that the NLPM-API model was significantly more efficient than the original linear perturbation model (the LPM). However, restriction of explicit non-linearity to the runoff generation process, in the simpler LMP-API form of the model, did not produce a significantly lower value of the efficiency in flood forecasting, in terms of the model efficiency index R².