Areal Nonpoint Source Watershed Environment Response Simulation Research Articles

Development of Sub-Daily Erosion and Sediment Transport Algorithms for SWAT

New Soil and Water Assessment Tool (SWAT) algorithms for simulation of stormwater best management practices (BMPs) such as detention basins, wet ponds, sedimentation filtration ponds, and retention irrigation systems are under development for modeling small/urban watersheds. Modeling stormwater BMPs often requires time steps as small as minutes to realistically capture the instantaneous flow and sediment load coming from upland areas. SWAT2005 uses the Modified Universal Soil Loss Equation (MUSLE) for modeling upland erosion and sediment load. The MUSLE model is an empirical soil loss equation, which was formulated based on field observations rather than theoretically derived relationships to predict long-term average soil loss. This article presents modified physically based erosion models in SWAT for seamless modeling of erosion processes with the recently developed sub-hourly flow models. In the new algorithms, splash erosion is calculated based on the kinetic energy delivered by raindrops, adapted from the European Soil Erosion Model, and overland flow erosion is estimated using a physically based equation adapted from the Areal Nonpoint-Source Watershed Environment Response Simulation (ANSWERS) model. The Yang model and the Brownlie model were also modified for in-stream sediment routing. The SWAT model with the modified sub-daily sediment algorithms was calibrated and validated each for a one-year period at 15 min intervals with measured data from the USDA-ARS Riesel watersheds in Texas. Results show that SWAT with the sub-daily algorithms performed as well or better in terms of sediment yield prediction than SWAT with the current daily output structure. In addition, SWAT (sub-daily) was able to adequately represent the timing, peak, and duration of sediment transport events. Thus, this initial evaluation indicates that the new sub-daily flow and sediment structure in SWAT is a promising tool for water quality assessment studies in small watersheds or urban watersheds where sub-daily process are so important to quantify.

Simulating Watershed Outlet Sediment Concentration using the ANSWERS Model by applying Two Sediment Transport Capacity Equations

Soil erosion is one of the major sources of environmental deterioration and has many impacts on soil and water resources quality. Scientists generally use computational models to simulate the amount of sediment yield from watersheds. One of the leading equations used in these models is the overland flow sediment transport capacity. Owing to the lack of such equations, the streamflow equations have been used widely instead. Some of these equations relatively resulted good estimations of runoff flow sediment concentration. In this study the Areal Non point Source Watershed Environment Response Simulation (ANSWERS) model code was changed and the original equation of the model replaced with a new equation. Although the new equation underestimates sediment concentration, the original model resulted in closer agreement between observed and simulated sediment concentration in different rainfall events. Results of this study suggested that adding some components considering fine particles of soil such as silt and clay to the new and original equations, may improve the accuracy of prediction of sediment concentration by the ANSWERS model. Although, both equations revealed that tend to underestimate sediment concentration; however, the original equation overestimated sediment concentration whenever the runoff coefficient exceeded 0·3 under relatively moderate rainfall intensity. Furthermore, the results showed that soil moisture conditions, rainfall depth and rainfall intensity affect underestimation or overestimation of the model; and initial soil moisture is a key factor in simulation of sediment concentration. Wet and dry soil conditions caused overestimation and underestimation of sediment concentration for the original model, respectively. Nevertheless, no specific erosion model is available now which can simulate sediment yield accurately.

Hydrological studies for small watershed in India using the ANSWERS model

A study was undertaken with the objective of investigating the performance of the physically based distributed parameter Areal Non point Source Watershed Environment Response Simulation (ANSWERS) model for a 16.13 km 2 small watershed in eastern India by using digital elevation model (DEM), GIS and remote sensing techniques for automatic extraction of the model input parameters. The model was calibrated by using sixteen storms of 1993 and 1994 and validated with fifteen storms of 1995 and 1996. For calibration storms, the model simulates surface runoff, peak flow and sediment yield with average per cent deviation (Dv) equal to −9.32, 1.24 and −3.04 and coefficient of efficiency (E) equal to 0.964, 0.881 and 0.884 respectively. For validation storms, the model simulates surface runoff, peak flow and sediment yield with average per cent Dv as −8.13, −2.25 and −1.63 and E as 0.991, 0.741 and 0.965 respectively. During model calibration and validation the peaks of the simulated hydrographs for majority of the storms were found to occur after the peaks of the observed hydrographs. The statistical comparisons indicate that the model simulates runoff, peak flow and sediment yield well for most of the storms with Dv less than 15% from the observed values and average value of E greater than 0.80. The model calibration and validation results indicate that the ANSWERS can be successfully used for simulating the watershed response under varying soil moisture and watershed conditions. The study reveals the suitability of the ANSWERS model application for the other Indian watersheds of similar hydro-geological characteristics.

Field Evaluation of Selected Soil Erosion Models for Catchment Management in Indonesia

Three models, viz., areal non-point source watershed environment response simulation (ANSWERS), universal soil loss equation (USLE) and adapted universal soil loss equation (AUSLE) are evaluated for their performance under the field conditions of the Riam Kanan catchment in South Kalimantan province of Indonesia. While ANSWERS is evaluated for its accuracy to predict both runoff and soil loss, USLE and AUSLE are evaluated for soil loss only. The study was carried out in the context of sedimentation concerns for the Muhammad Nur Reservoir—an important source of drinking and irrigation water supply for the catchment. The models are evaluated using field data collected under four different land uses and during 2 years of field experiments. The land uses considered are cropland with minimum tillage, cropland with conventional tillage, grassland and areas reforested with rubber trees. The ANSWERS model in general has a tendency to overpredict runoff values. The ANSWERS model also was relatively better for predicting soil loss followed by the AUSLE and USLE models. Overall, the ANSWERS model proved superior for predicting soil loss in the Riam Kanan catchment. However, given that the AUSLE model produced sufficiently reliable results and is relatively easy to use, the AUSLE model would also appear to be a useful tool for predicting soil erosion in the catchment.

Soil loss predictions with three erosion simulation models

Quantification of soil loss is one of the greatest challenges in natural resources and environmental planning. Computer simulation models are becoming increasingly popular in predicting soil loss for various land use and management practices. In this study, three soil erosion prediction models — the Water Erosion Prediction Project (WEPP), the Erosion Productivity Impact Calculator (EPIC), and the Areal Nonpoint Source Watershed Environment Response Simulation (ANSWERS) were used for simulating soil loss and testing the capability of the models in predicting soil losses for three different tillage systems (ridge-till, chisel-plow, and no-till). For each model, the most sensitive model parameters were calibrated using measured soil erosion data. After calibration, models were run and predicted soil loss values were compared with the measured soil loss values. The measured soil erosion data were collected from an erosion experiment field of Kansas State University at Ottawa (Kansas), USA. Field experiments were conducted from 1995 to 1997 on small plots to measure runoff and soil losses under all three tillage systems. All three models were evaluated on the basis of individual event, total yearly, and mean event-based soil loss predictions. Results showed that all the three models performed reasonably well and the predicted soil looses were within the range of measured values. For ridge-till and chisel-plow systems, WEPP and ANSWERS gave better predictions than those by EPIC model. For no-till system, WEPP and EPIC predictions were better than those by ANSWERS. The overall results indicate that WEPP predictions were better than those by the other two models in most of the cases, and it can be used with reasonable degree of confidence for soil loss quantification for all the three tillage systems.

Vegetation influence on runoff and sediment yield in the Andes region: observation and modelling

The Precordillera of the Andes Mountains (Mendoza, Argentina) is prone to severe flash floods, caused by heavy rainfall events of short duration and high intensities. Two catchments were instrumented in order to study the rainfall–runoff process and soil management impact on runoff and/or sediment yield. In the first catchment (Divisadero Largo, DL, 5.47 km 2), characterized by a large heterogeneity of surface geology, a data set of about 50 rainfall–runoff events covering the 1983–1994 period was available. Vegetation cover changed significantly after the catchment was enclosed in 1989–1990. This change was successfully mapped using Landsat TM image analysis. The second catchment (Cuenca Aluvional Piloto, CAP, 35 ha), the soil of which was homogeneous, was instrumented in 1992 for total runoff and sediment yield measurements. Three small plots of 3×10 m 2 (bare soil, 42 and 60% vegetation cover) and three sub catchments (2–4.5 ha) were delimited with different average vegetation cover. Data analysis showed the difficulty in relating runoff volume and sediment yield to simple descriptors of the catchments such as the average slope and/or the average vegetation cover. The DL and CAP catchments were modelled using the Areal Non Point Source Watershed Environment Response Simulation (ANSWERS) model with contrasting results. Good agreement between model and observation could be achieved after calibration on the 3×10 m 2 plots, but the model failed to correctly reproduce runoff on the three 2–4.5 ha CAP sub-catchments using the values calibrated on the small plots. Better results were obtained on the larger and heterogeneous DL basin, where surface geology variations and rainfall variability seemed to be the most influential factors. In this case, no sensitivity to vegetation coverage changes, induced when enclosing the catchment, was found. On the other hand, the model proved sensitive to differences in vegetation cover at smaller scales when the geology was homogeneous.

Distributed parameter hydrology model (ANSWERS) applied to a range of catchment scales using rainfall simulator data. III. Application to a spatially complex catchment

The areal non-point source watershed environment response simulation (ANSWERS) model, modified to include Green and Ampt infiltration, was tested using measured runoff from a 9.6-ha spatially variable grassland catchment in the semi-arid tropics in Central Queensland. A description of the development of the modified ANSWERS model and testing with runoff from relatively uniform, cultivated catchments is given in earlier papers in this series. Important infiltration parameter values were derived from 1-m2 rainfall simulator plots. Functions describing change in soil infiltration capacity with increasing pasture cover were included in ANSWERS. Other parameter values describing infiltration, catchment topography and surface conditions were measured directly, estimated from tabulated sources or modelled with the Grasp model. Runoff at the catchment outlet was well predicted for cover conditions that varied from bare to heavy cover. Runoff from sub-catchments with varying areas, soil types and infiltration capacities was also well predicted. Runoff from high intensity rainfall events was more accurately predicted than from low intensity events. Using the application and parameterisation methods described in this paper, the modified ANSWERS model could be used to predict runoff from spatially complex catchments without optimisation of parameter values against measured runoff.

THE SENSITIVITY OF TWO DISTRIBUTED NON-POINT SOURCE POLLUTION MODELS TO THE SPATIAL ARRANGEMENT OF THE LANDSCAPE

Distributed hydrological models are becoming increasingly complex with respect to spatial phenomena, and with the widespread availability of spatial data from GIS, this trend is likely to increase. In all such models the spatial arrangement of phenomena, such as soil properties and land-use categories is fundamental, and so the arrangement should have an influence on the model output. Testing for this influence we term spatial sensitivity analysis. Here, we report on the spatial sensitivity of two widely used models, AgNPS (agricultural non-point source pollution model) and ANSWERS (areal nonpoint source watershed environment response simulation). The input spatial data were subjected to spatially random mixing to varying degrees, such that the organized landscape became disorganized. The chemical discharge from AgNPS, and the sediment and water discharge from ANSWERS, are examined. In both cases most outputs exhibited little or no sensitivity to the spatial distribution of most input data. Only infiltration-related inputs produced large variations, but these changes were not in the sense that might have been predicted. Although the analytical methods used require further refinement, there must now be some doubt as to the validity of the models, and whether they repay their computational complexity. Furthermore, it is felt that spatial sensitivity analysis should become a fundamental part of the verification of all such models. © 1997 by John Wiley & Sons, Ltd.

HYDROLOGIC RESPONSES OF AN AGRICULTURAL WATERSHED TO VARIOUS HYDROLOGIC AND MANAGEMENT CONDITIONS1

ABSTRACT: The hydrologic responses from an agricultural watershed in southeast Nebraska were investigated under an array of physiographic, hydrologic, meteorologic, and management conditions. For analytical purposes, the hydrologic responses were narrowed to include only runoff and sediment yield. The study was performed by utilizing the ANSWERS (Areal Nonpoint Source Watershed Environment Response Simulation) hydrologic‐simulation model. Results of this study indicate that, generally, nonstructural (agronomic) Best Management Practices (BMPs) have a more significant impact in controlling erosion and nonpoint‐source pollution than structurally oriented BMPs. The percentage of reduction in average soil loss as a result of changing tilage systems from conventional to chisel plow was in the mid‐40s. The corresponding percentages of reduction in sediment yield from the watershed under minimum tillage and no‐till systems were in the mid‐60s and mid‐80s, respectively. The impact of these management strategies on runoff varied considerably. That is primarily based on the watershed's antecedent soil moisture condition, land use, and the growth stage of crops. Generally, an intense, short, thunderstorm type of rainfall event had more relative impact on runoff, and therefore sediment yield than a long, gentle, and steady event.

ANSWERS: A Model for Watershed Planning

ABSTRACT IN recent years, a greatly increased emphasis has been placed on improving and maintaining the quality of our national water resources. Agencies and individuals from the various levels of government, industry and private life are seeking information concerning the ef-fects that land use, management, and conservation prac-tices or structures might have on the quality and quantity of water from both agricultural and non-agricultural watersheds. ANSWERS (Areal Nonpoint Source Watershed En-vironment Response Simulation) was developed in an ef-fort to supply the desired information described above for primarily agricultural watersheds. The overall struc-ture consists of a hydrologic model, a sediment detachment/transport model and several routing com-ponents necessary to describe the movement of water in overland, subsurface and channel flow phases. ANSWERS, unlike many large-scale watershed model structures, uses distributed (rather than lumped) parameters and is event (rather than long-term) oriented. These operational features generally yield a better understanding of the hydrologic and water quality interactions involved in a watershed by allowing the user to physically describe those processes both spatially and temporally. The purpose of this report is to present the operational concepts, the basic mathematical model used in ANSWERS, general data needs and user considerations. In addition, the potential utility of ANSWERS as a plan-ning tool is demonstrated by simulating several manage-ment alternatives for a primarily agricultural watershed in northeastern Indiana subjected to several different precipitation events.