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1.
Watershed scale hydrological and biogeochemical models rely on the correct spatial‐temporal prediction of processes governing water and contaminant movement. The Soil and Water Assessment Tool (SWAT) model, one of the most commonly used watershed scale models, uses the popular curve number (CN) method to determine the respective amounts of infiltration and surface runoff. Although appropriate for flood forecasting in temperate climates, the CN method has been shown to be less than ideal in many situations (e.g. monsoonal climates and areas dominated by variable source area hydrology). The CN model is based on the assumption that there is a unique relationship between the average moisture content and the CN for all hydrologic response units (HRUs), and that the moisture content distribution is similar for each runoff event, which is not the case in many regions. Presented here is a physically based water balance that was coded in the SWAT model to replace the CN method of runoff generation. To compare this new water balance SWAT (SWAT‐WB) to the original CN‐based SWAT (SWAT‐CN), two watersheds were initialized; one in the headwaters of the Blue Nile in Ethiopia and one in the Catskill Mountains of New York. In the Ethiopian watershed, streamflow predictions were better using SWAT‐WB than SWAT‐CN [Nash–Sutcliffe efficiencies (NSE) of 0·79 and 0·67, respectively]. In the temperate Catskills, SWAT‐WB and SWAT‐CN predictions were approximately equivalent (NSE > 0·70). The spatial distribution of runoff‐generating areas differed greatly between the two models, with SWAT‐WB reflecting the topographical controls imposed on the model. Results show that a water balance provides results equal to or better than the CN, but with a more physically based approach. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

2.
Z. X. Xu  J. P. Pang  C. M. Liu  J. Y. Li 《水文研究》2009,23(25):3619-3630
The Soil and Water Assessment Tool (SWAT) was used to simulate the transport of runoff and sediment into the Miyun Reservoir, Beijing in this study. The main objective was to validate the performance of SWAT and the feasibility of using this model as a simulator of runoff and sediment transport processes at a catchment scale in arid and semi‐arid area in North China, and related processes affecting water quantity and soil erosion in the catchment were simulated. The investigation was conducted using a 6‐year historical streamflow and sediment record from 1986 to 1991; the data from 1986 to 1988 was used for calibration and that from 1989 to 1991 for validation. The SWAT generally performs well and could accurately simulate both daily and monthly runoff and sediment yield. The simulated daily and monthly runoff matched the observed values satisfactorily, with a Nash‐Sutcliffe coefficient of greater than 0·6, 0·9 and a coefficient of determination 0·75, 0·9 at two outlet stations (Xiahui and Zhangjiafen stations) during calibration. These values were 0·6, 0·85 and 0·6, 0·9 during validation. For sediment simulation, the efficiency is lower than that for runoff. Even so, the Nash‐Sutcliffe coefficient and coefficient of determination were greater than 0·48 and 0·6 for monthly sediment yield during calibration, and these values were greater than 0·84 and 0·95 during validation. Sensitivity analysis shows that sensitive parameters for the simulation of discharge and sediment yield include curve number, base flow alpha factor, soil evaporation compensation factor, soil available water capacity, soil profile depth, surface flow lag time and channel re‐entrained linear parameter, etc. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

3.
Runoff estimations based on the standard USDA–NRCS curve number (CN) table without calibration have a tendency to give inaccurate results when the CN values are applied in South Korea which has many high slope watersheds and that has a continental monsoon climate. Particularly for the design flood estimation, accurately calibrated CN values are required because the estimated peak flow is very sensitive to the selection of CN. However, the lack of flood data makes it difficult to calibrate and assign runoff CNs to Korean watersheds. Even if sufficient data are available to estimate CN values, it is also difficult to obtain the direct flows by separating base flows from total runoff hydrographs due to the temporal irregularity of rainfall events and the resulting complex pattern of runoff. Therefore, an alternative method for estimating CNs needs to be developed to overcome these issues. The purpose of this study is to present a method for estimating runoff CNs using the soil and water assessment tool (SWAT) model which can take into account watershed heterogeneities such as climate conditions, land use and soil types. The proposed CN estimation method uses the simulated flow data by SWAT instead of using measured flow data. This method has advantages in estimating CN values spatially for each subbasin division considering watershed characteristics. The use of daily data can reduce the sensitivity to the abnormality that is commonly involved in flow data with a small time scale. The SWAT‐based CN estimation method, combined with the asymptotic CN method, was applied to the Chungju dam watershed in South Korea. A regression equation was then developed from this approach, which was used to estimate CN values that decrease exponentially as rainfall amounts increase and that converge to 60·6 and 79·4 without and with considering subsurface lateral flow, respectively. Furthermore, the CN values for the antecedent moisture conditions were determined using the probabilistic approach. The CN associated with the 50% probability for the Chungju dam watershed is 87·8 which can be taken to be representative of antecedent moisture condition (AMC) II. The CNI and CNIII associated with 90% and 10% probabilities are 78·9 and 94·1, respectively. The estimated CNII = 87·8 differs markedly from the geographic information system (GIS)‐based CN 65·0, which implies that the standard USDA–NRCS CN method should be calibrated to the studied area of interest. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

4.
Most semi‐distributed watershed water quality models divide the watershed into hydrologic response units (HRU) with no flow among them. This is problematic when watersheds are delineated to include variable source areas (VSAs) because it is the lateral flows from upslope areas to downslope areas that generate VSAs. Although hydrologic modellers have often successfully calibrated these types of models, there can still be considerable uncertainty in model results. In this paper, a topographic‐index‐based method is described and tested to distribute effective soil water holding capacity among HRUs, which can be subsequently adjusted using the watershed baseflow coefficient. The method is tested using a version of the Soil and Water Assessment Tool (SWAT) model that simulates VSA runoff and is applied to two watersheds: a New York State (NYS) watershed, and one in the head waters of the Blue Nile Basin (BNB) in Ethiopia. Daily streamflow predicted using effective soil water storage capacities based only on the topographic index were reassuringly accurate in both the NYS watershed (daily Nash Sutcliffe (E) = 0·73) and in the BNB (E = 0·70). Using the baseflow coefficient to adjust the effective soil water storage capacity only slightly improved streamflow predictions in NYS (E = 0·75) but substantially improved the BNB predictions (E = 0·80). By comparison, the standard SWAT model, which uses the traditional look‐up tables to determine a runoff curve number, performed considerably less accurately in un‐calibrated form (E = 0·51 for NYS and E = 0·45 for BNB), but improved substantially when explicitly calibrated to streamflow measurements (E = 0·76 for NYS and E = 0·67 for the BNB). The calibration method presented here provides a parsimonious, systematic approach to using established models in VSA watersheds that reduces the ambiguity inherent in model calibration. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

5.
The Soil Conservation Service curve number (CN) method is widely used for predicting direct runoff from rainfall. However, despite the extent of cultivation on hillslope areas, very few attempts have been made to incorporate a slope factor into the CN method. The objectives of this study were (1) to evaluate existing approaches integrating slope in the CN method, and (2) to develop an equation incorporating a slope factor into the CN method for application in the steep slope areas of the Loess Plateau of China. The dataset consisted of 11 years of rainfall and runoff measurements from two experimental sites with slopes ranging from 14 to 140%. The results indicated that the standard CN method underestimated large runoff events and overestimated small events. For our experimental conditions, the optimized and non‐optimized forms of the slope‐modified CN method of the Erosion Productivity Impact Calculator model improved runoff prediction for steep slopes, but large runoff events were still underestimated and small ones overpredicted. Based on relationships between slope and the observed and theoretical CN values, an equation was developed that better predicted runoff depths with an R2 of 0·822 and a linear regression slope of 0·807. This slope‐adjusted CN equation appears to be the most appropriate for runoff prediction in the steep areas of the Loess Plateau of China. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   

6.
Grazing is common in the foothills fescue grasslands and may influence the seasonal soil‐water patterns, which in turn determine range productivity. Hydrological modelling using the soil and water assessment tool (SWAT) is becoming widely adopted throughout North America especially for simulation of stream flow and runoff in small and large basins. Although applications of the SWAT model have been wide, little attention has been paid to the model's ability to simulate soil‐water patterns in small watersheds. Thus a daily profile of soil water was simulated with SWAT using data collected from the Stavely Range Sub‐station in the foothills of south‐western Alberta, Canada. Three small watersheds were established using a combination of natural and artificial barriers in 1996–97. The watersheds were subjected to no grazing (control), heavy grazing (2·4 animal unit months (AUM) per hectare) or very heavy grazing (4·8 AUM ha?1). Soil‐water measurements were conducted at four slope positions within each watershed (upper, middle, lower and 5 m close to the collector drain), every 2 weeks annually from 1998 to 2000 using a downhole CPN 503 neutron moisture meter. Calibration of the model was conducted using 1998 soil‐water data and resulted in Nash–Sutcliffe coefficient (EF or R2) and regression coefficient of determination (r2) values of 0·77 and 0·85, respectively. Model graphical and statistical evaluation was conducted using the soil‐water data collected in 1999 and 2000. During the evaluation period, soil water was simulated reasonably with an overall EF of 0·70, r2 of 0·72 and a root mean square error (RMSE) of 18·01. The model had a general tendency to overpredict soil water under relatively dry soil conditions, but to underpredict soil water under wet conditions. Sensitivity analysis indicated that absolute relative sensitivity indices of input parameters in soil‐water simulation were in the following order; available water capacity > bulk density > runoff curve number > fraction of field capacity (FFCB) > saturated hydraulic conductivity. Thus these data were critical inputs to ensure reasonable simulation of soil‐water patterns. Overall, the model performed satisfactorily in simulating soil‐water patterns in all three watersheds with a daily time‐step and indicates a great potential for monitoring soil‐water resources in small watersheds. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

7.
High‐resolution, spatially extensive climate grids can be useful in regional hydrologic applications. However, in regions where precipitation is dominated by snow, snowmelt models are often used to account for timing and magnitude of water delivery. We developed an empirical, nonlinear model to estimate 30‐year means of monthly snowpack and snowmelt throughout Oregon. Precipitation and temperature for the period 1971–2000, derived from 400‐m resolution PRISM data, and potential evapotranspiration (estimated from temperature and day length) drive the model. The model was calibrated using mean monthly data from 45 SNOTEL sites and accurately estimated snowpack at 25 validation sites: R2 = 0·76, Nash‐Sutcliffe Efficiency (NSE) = 0·80. Calibrating it with data from all 70 SNOTEL sites gave somewhat better results (R2 = 0·84, NSE = 0·85). We separately applied the model to SNOTEL stations located < 200 and ≥ 200 km from the Oregon coast, since they have different climatic conditions. The model performed equally well for both areas. We used the model to modify moisture surplus (precipitation minus potential evapotranspiration) to account for snowpack accumulation and snowmelt. The resulting values accurately reflect the shape and magnitude of runoff at a snow‐dominated basin, with low winter values and a June peak. Our findings suggest that the model is robust with respect to different climatic conditions, and that it can be used to estimate potential runoff in snow‐dominated basins. The model may allow high‐resolution, regional hydrologic comparisons to be made across basins that are differentially affected by snowpack, and may prove useful for investigating regional hydrologic response to climate change. Published in 2011 by John Wiley & Sons, Ltd.  相似文献   

8.
The C factor, representing the impact of plant and ground cover on soil loss, is one of the important factors of the Modified Universal Soil Loss Equation (MUSLE) in the Soil and Water Assessment Tool (SWAT) to model sediment yield. The daily update of C factors in SWAT was originally determined by land use types and plant growth cycles. This does not reflect the spatial variation of C values that exists within a large land use area. We present a new approach to integrate remotely sensed C factors into SWAT for highlighting the effect of detailed vegetative cover data on soil erosion and sediment yield. First, the C factor was estimated using the abundance of ground components extracted from remote sensing images. Then, the gridding data of the C factor were aggregated to hydrological response units (HRUs), instead of to land use units of SWAT. In the end, the C factor values in HRUs were integrated into SWAT to predict sediment yield by modifying the ysed subroutine. This substitution work not only increases the spatial variation of the C factor in SWAT, but also makes it possible to utilize other sources of C databases rather than those from the United States. The demonstration in the Dage basin shows that the modified SWAT produces reasonable results in water flow simulation and sediment yield prediction using remotely sensed C values. The Nash–Sutcliffe efficiency coefficient (ENS) and R2 for surface runoff range from 0·69 to 0·77 and 0·73 to 0·87, respectively. The coefficients ENS and R2 for sediment yield were generally above 0·70 and 0·60, respectively. The soil erosion risk map based on sediment yield prediction at the HRU level illustrates instructive details on spatial distribution of soil loss. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

9.
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.  相似文献   

10.
This study was conducted under the USDA‐Conservation Effects Assessment Project (CEAP) in the Cheney Lake watershed in south‐central Kansas. The Cheney Lake watershed has been identified as ‘impaired waters’ under Section 303(d) of the Federal Clean Water Act for sediments and total phosphorus. The USDA‐CEAP seeks to quantify environmental benefits of conservation programmes on water quality by monitoring and modelling. Two of the most widely used USDA watershed‐scale models are Annualized AGricultural Non‐Point Source (AnnAGNPS) and Soil and Water Assessment Tool (SWAT). The objectives of this study were to compare hydrology, sediment, and total phosphorus simulation results from AnnAGNPS and SWAT in separate calibration and validation watersheds. Models were calibrated in Red Rock Creek watershed and validated in Goose Creek watershed, both sub‐watersheds of the Cheney Lake watershed. Forty‐five months (January 1997 to September 2000) of monthly measured flow and water quality data were used to evaluate the two models. Both models generally provided from fair to very good correlation and model efficiency for simulating surface runoff and sediment yield during calibration and validation (correlation coefficient; R2, from 0·50 to 0·89, Nash Sutcliffe efficiency index, E, from 0·47 to 0·73, root mean square error, RMSE, from 0·25 to 0·45 m3 s?1 for flow, from 158 to 312 Mg for sediment yield). Total phosphorus predictions from calibration and validation of SWAT indicated good correlation and model efficiency (R2 from 0·60 to 0·70, E from 0·63 to 0·68) while total phosphorus predictions from validation of AnnAGNPS were from unsatisfactory to very good (R2 from 0·60 to 0·77, E from ? 2·38 to 0·32). The root mean square error–observations standard deviation ratio (RSR) was estimated as excellent (from 0·08 to 0·25) for the all model simulated parameters during the calibration and validation study. The percentage bias (PBIAS) of the model simulated parameters varied from unsatisfactory to excellent (from 128 to 3). This study determined SWAT to be the most appropriate model for this watershed based on calibration and validation results. Copyright © 2008 John Wiley & Sons, Ltd.  相似文献   

11.
The Soil Conservation Service curve number (CN) method commonly uses three discrete levels of soil antecedent moisture condition (AMC), defined by the 5‐day antecedent rainfall depth, to describe soil moisture prior to a runoff event. However, this way may not adequately represent soil water conditions of fields and watersheds in the Loess Plateau of China. The objectives of this study were: (1) to determine the effective soil moisture depth to which the CN is most related; (2) to evaluate a discrete and a linear relationship between AMC and soil moisture; and (3) to develop an equation between CN and soil moisture to predict runoff better for the climatic and soil conditions of the Loess Plateau of China. The dataset consisted of 10 years of rainfall, runoff and soil moisture measurements from four experimental plots cropped with millet, pasture and potatoes. Results indicate that the standard CN method underestimated runoff depths for 85 of the 98 observed plot‐runoff events, with a model efficiency E of only 0·243. For our experimental conditions, the discrete and linear approaches improved runoff estimation, but still underestimated most runoff events, with E values of 0·428 and 0·445 respectively. Based on the measured CN values and soil moisture values in the top 15 cm of the soil, a non‐linear equation was developed that predicted runoff better with an E value of 0·779. This modified CN equation was the most appropriate for runoff prediction in the study area, but may need adjustments for local conditions in the Loess Plateau of China. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   

12.
Ashok Mishra  S. Kar  V. P. Singh 《水文研究》2007,21(22):3035-3045
The Hydrologic Simulation Programme‐Fortran (HSPF), a hydrologic and water quality computer model, was employed for simulating runoff and sediment yield during the monsoon months (June–October) from a small watershed situated in a sub‐humid subtropical region of India. The model was calibrated using measured runoff and sediment yield data for the monsoon months of 1996 and was validated for the monsoon months of 2000 and 2001. During the calibration period, daily‐calibrated runoff had a Nash‐Sutcliffe efficiency (ENS) value of 0·68 and during the validation period it ranged from 0·44 to 0·67. For daily sediment yield ENS was 0·71 for the calibration period and it ranged from 0·68 to 0·90 for the validation period. Sensitivity analysis was performed to assess the impact of important watershed characteristics. The model parameters obtained in this study could serve as reference values for model application in similar climatic regions, with practical implications in watershed planning and management and designing best management practices. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

13.
Using a large set of rainfall–runoff data from 234 watersheds in the USA, a catchment area‐based evaluation of the modified version of the Mishra and Singh (2002a) model was performed. The model is based on the Soil Conservation Service Curve Number (SCS‐CN) methodology and incorporates the antecedent moisture in computation of direct surface runoff. Comparison with the existing SCS‐CN method showed that the modified version performed better than did the existing one on the data of all seven area‐based groups of watersheds ranging from 0·01 to 310·3 km2. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   

14.
Experimental research in the Ethiopian highlands found that saturation excess induced runoff and erosion are common in the sub‐humid conditions. Because most erosion simulation models applied in the highlands are based on infiltration excess, we, as an alternative, developed the Parameter Efficient Distributed (PED) model, which can simulate water and sediment fluxes in landscapes with saturation excess runoff. The PED model has previously only been tested at the outlet of a watershed and not for distributed runoff and sediment concentration within the watershed. In this study, we compare the distributed storm runoff and sediment concentration of the PED model against collected data in the 95‐ha Debre Mawi watershed and three of its nested sub‐watersheds for the 2010 and 2011 rainy seasons. In the PED model framework, the hydrology of the watershed is divided between infiltrating and runoff zones, with erosion only taking place from two surface runoff zones. Daily storm runoff and sediment concentration values, ranging from 0.5 to over 30 mm and from 0.1 to 35 g l?1, respectively, were well simulated. The Nash Sutcliffe efficiency values for the daily storm runoff for outlet and sub‐watersheds ranged from 0.66 to 0.82, and the Nash–Sutcliffe efficiency for daily sediment concentrations were greater than 0.78. Furthermore, the model uses realistic fractional areas for surface and subsurface flow contributions, for example between saturated areas (15%), degraded areas (30%) and permeable areas (55%) at the main outlet, while close similarity was found for the remaining hydrology and erosion parameter values. One exception occurred for the distinctly greater transport limited parameter at the actively gullying lower part of the watershed. The results suggest that the model based on saturation excess provides a good representation of the observed spatially distributed runoff and sediment concentrations within a watershed by modelling the bottom lands (as opposed to the uplands) as the dominant contributor of the runoff and sediment load. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   

15.
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.  相似文献   

16.
Many methods developed for calibration and validation of physically based distributed hydrological models are time consuming and computationally intensive. Only a small set of input parameters can be optimized, and the optimization often results in unrealistic values. In this study we adopted a multi‐variable and multi‐site approach to calibration and validation of the Soil Water Assessment Tool (SWAT) model for the Motueka catchment, making use of extensive field measurements. Not only were a number of hydrological processes (model components) in a catchment evaluated, but also a number of subcatchments were used in the calibration. The internal variables used were PET, annual water yield, daily streamflow, baseflow, and soil moisture. The study was conducted using an 11‐year historical flow record (1990–2000); 1990–94 was used for calibration and 1995–2000 for validation. SWAT generally predicted well the PET, water yield and daily streamflow. The predicted daily streamflow matched the observed values, with a Nash–Sutcliffe coefficient of 0·78 during calibration and 0·72 during validation. However, values for subcatchments ranged from 0·31 to 0·67 during calibration, and 0·36 to 0·52 during validation. The predicted soil moisture remained wet compared with the measurement. About 50% of the extra soil water storage predicted by the model can be ascribed to overprediction of precipitation; the remaining 50% discrepancy was likely to be a result of poor representation of soil properties. Hydrological compensations in the modelling results are derived from water balances in the various pathways and storage (evaporation, streamflow, surface runoff, soil moisture and groundwater) and the contributions to streamflow from different geographic areas (hill slopes, variable source areas, sub‐basins, and subcatchments). The use of an integrated multi‐variable and multi‐site method improved the model calibration and validation and highlighted the areas and hydrological processes requiring greater calibration effort. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   

17.
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.  相似文献   

18.
Because the traditional Soil Conservation Service curve‐number (SCS‐CN) approach continues to be used ubiquitously in water quality models, new application methods are needed that are consistent with variable source area (VSA) hydrological processes in the landscape. We developed and tested a distributed approach for applying the traditional SCS‐CN equation to watersheds where VSA hydrology is a dominant process. Predicting the location of source areas is important for watershed planning because restricting potentially polluting activities from runoff source areas is fundamental to controlling non‐point‐source pollution. The method presented here used the traditional SCS‐CN approach to predict runoff volume and spatial extent of saturated areas and a topographic index, like that used in TOPMODEL, to distribute runoff source areas through watersheds. The resulting distributed CN–VSA method was applied to two subwatersheds of the Delaware basin in the Catskill Mountains region of New York State and one watershed in south‐eastern Australia to produce runoff‐probability maps. Observed saturated area locations in the watersheds agreed with the distributed CN–VSA method. Results showed good agreement with those obtained from the previously validated soil moisture routing (SMR) model. When compared with the traditional SCS‐CN method, the distributed CN–VSA method predicted a similar total volume of runoff, but vastly different locations of runoff generation. Thus, the distributed CN–VSA approach provides a physically based method that is simple enough to be incorporated into water quality models, and other tools that currently use the traditional SCS–CN method, while still adhering to the principles of VSA hydrology. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

19.
Impact studies of catchment management in the developing world rarely include detailed hydrological components. Here, changes in the hydrological response of a 200‐ha catchment in north Ethiopia are investigated. The management included various soil and water conservation measures such as the construction of dry masonry stone bunds and check dams, the abandonment of post‐harvest grazing, and the establishment of woody vegetation. Measurements at the catchment outlet indicated a runoff depth of 5 mm or a runoff coefficient (RC) of 1·6% in the rainy season of 2006. Combined with runoff measurements at plot scale, this allowed calculating the runoff curve number (CN) for various land uses and land management techniques. The pre‐implementation runoff depth was then predicted using the CN values and a ponding adjustment factor, representing the abstraction of runoff induced by the 242 check dams in gullies. Using the 2006 rainfall depths, the runoff depth for the 2000 land management situation was predicted to be 26·5 mm (RC = 8%), in line with current RCs of nearby catchments. Monitoring of the ground water level indicated a rise after catchment management. The yearly rise in water table after the onset of the rains (ΔT) relative to the water surplus (WS) over the same period increased between 2002–2003 (ΔT/WS = 3·4) and 2006 (ΔT/WS >11·1). Emerging wells and irrigation are other indicators for improved water supply in the managed catchment. Cropped fields in the gullies indicate that farmers are less frightened for the destructive effects of flash floods. Due to increased soil water content, the crop growing period is prolonged. It can be concluded that this catchment management has resulted in a higher infiltration rate and a reduction of direct runoff volume by 81% which has had a positive influence on the catchment water balance. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

20.
This paper investigates the variation of the popular curve number (CN) values given in the National Engineering Hand Book–Section 4 (NEH‐4) of the Soil Conservation Service (SCS) with antecedent moisture condition (AMC) and soil type. Using the volumetric concept, involving soil, water, and air, a significant condensation of the NEH‐4 tables is achieved. This leads to a procedure for determination of CN for gauged as well as ungauged watersheds. The rainfall‐runoff events derived from daily data of four Indian watersheds exhibited a power relation between the potential maximum retention or CN and the 5‐day antecedent rainfall amount. Including this power relation, the SCS‐CN method was modified. This modification also eliminates the problem of sudden jumps from one AMC level to the other. The runoff values predicted using the modified method and the existing method utilizing the NEH‐4 AMC criteria yielded similar results. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   

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