STREAMFLOW MODELING OF UPPER INDUS RIVER CATCHMENTS1

ABSTRACT: The streamflows of three tributaries, Siran, Haro, and Soan in the upper Indus River catchment in Pakistan were simulated using SSARR and Tank Models. Channel characteristics of the main Indus River were also determined using the two models. The basin characteristics were derived by trial and error method and were verified using the data for the period 1964–1970. Comparison of the two model performances showed that low flows were better reproduced by SSARR while the high flows were simulated with equal accuracy by both the models.     

APPLICATION OF THE DR3M WATERSHED MODEL ON A SMALL URBAN BASIN1

ABSTRACT: Data collected at a 79-acre urban watershed in Albuquerque, New Mexico, were used to calibrate and verify the Distributed Routing Rainfall-Runoff Model, a parametric watershed model. Standard errors of estimate for the 38 calibration storms were 33 percent and 38 percent, respectively, for volumes and peaks; and for the 46 verification storms were 29 percent and 37 percent, respectively, for volumes and peaks. Correlation coefficients for peaks were 0.8 and 0.95, respectively, for calibration and verification storms.     

Using SWAT to Model Streamflow in Two River Basins With Ground and Satellite Precipitation Data1

Abstract: Both ground rain gauge and remotely sensed precipitation (Next Generation Weather Radar – NEXRAD Stage III) data have been used to support spatially distributed hydrological modeling. This study is unique in that it utilizes and compares the performance of National Weather Service (NWS) rain gauge, NEXRAD Stage III, and Tropical Rainfall Measurement Mission (TRMM) 3B42 (Version 6) data for the hydrological modeling of the Middle Nueces River Watershed in South Texas and Middle Rio Grande Watershed in South Texas and northern Mexico. The hydrologic model chosen for this study is the Soil and Water Assessment Tool (SWAT), which is a comprehensive, physical‐based tool that models watershed hydrology and water quality within stream reaches. Minor adjustments to selected model parameters were applied to make parameter values more realistic based on results from previous studies. In both watersheds, NEXRAD Stage III data yields results with low mass balance error between simulated and actual streamflow (±13%) and high monthly Nash‐Sutcliffe efficiency coefficients (NS > 0.60) for both calibration (July 1, 2003 to December 31, 2006) and validation (2007) periods. In the Middle Rio Grande Watershed NEXRAD Stage III data also yield robust daily results (time averaged over a three‐day period) with NS values of (0.60‐0.88). TRMM 3B42 data generate simulations for the Middle Rio Grande Watershed of variable qualtiy (MBE = +13 to ?16%; NS = 0.38‐0.94; RMSE = 0.07‐0.65), but greatly overestimates streamflow during the calibration period in the Middle Nueces Watershed. During the calibration period use of NWS rain gauge data does not generate acceptable simulations in both watersheds. Significantly, our study is the first to successfully demonstrate the utility of satellite‐estimated precipitation (TRMM 3B42) in supporting hydrologic modeling with SWAT; thereby, potentially extending the realm (between 50°N and 50°S) where remotely sensed precipitation data can support hydrologic modeling outside of regions that have modern, ground‐based radar networks (i.e., much of the third world).     

Role of rainfall intensity and hydrology in nutrient transport via surface runoff

Loss of soil nutrients in runoff accelerates eutrophication of surface waters. This study evaluated P and N in surface runoff in relation to rainfall intensity and hydrology for two soils along a single hillslope. Experiments were initiated on 1- by 2-m plots at foot-slope (6%) and mid-slope (30%) positions within an alfalfa (Medicago sativa L.)-orchardgrass (Dactylis glomerata L.) field. Rain simulations (2.9 and 7.0 cm h(-1)) were conducted under wet (spring) and dry (late-summer) conditions. Elevated, antecedent soil moisture at the foot-slope during the spring resulted in less rain required to generate runoff and greater runoff volumes, compared with runoff from the well-drained mid-slope in spring and at both landscape positions in late summer. Phosphorus in runoff was primarily in dissolved reactive form (DRP averaged 71% of total P), with DRP concentrations from the two soils corresponding with soil test P levels. Nitrogen in runoff was mainly nitrate (NO3-N averaged 77% of total N). Site hydrology, not chemistry, was primarily responsible for variations in mass N and P losses with landscape position. Larger runoff volumes from the foot-slope produced higher losses of total P (0.08 kg ha(-1)) and N (1.35 kg ha(-1)) than did runoff from the mid-slope (0.05 total P kg ha(-1); 0.48 kg N ha(-1)), particularly under wet, spring-time conditions. Nutrient losses were significantly greater under the high intensity rainfall due to larger runoff volumes. Results affirm the critical source area concept for both N and P: both nutrient availability and hydrology in combination control nutrient loss.     

EPIC tile flow and nitrate loss predictions for three Minnesota cropping systems

Subsurface tile drains are a key source of nitrate N (NO3-N) losses to streams in parts of the north central USA. In this study, the Erosion Productivity Impact Calculator (EPIC) model was evaluated by comparing measured vs. predicted tile flow, tile NO3-N loss, soil profile residual NO3-N, crop N uptake, and yield, using 4 yr of data collected at a site near Lamberton, MN, for three crop rotations: continuous corn (Zea mays L.) or CC, corn-soybean [Glycine max (L.) Merr.] or CS, and continuous alfalfa (Medicago sativa L.) or CA. Initially, EPIC was run using standard Soil Conservation Service (SCS) runoff curve numbers (CN2) for CC and CS; monthly variations were accurately tracked for tile flow (r2 = 0.86 and 0.90) and NO3-N loss (r2 = 0.69 and 0.52). However, average annual CC and CS tile flows were underpredicted by -32 and -34%, and corresponding annual NO3-N losses were underpredicted by -11 and -52%. Predicted average annual tile flows and NO3-N losses generally improved following calibration of the CN2; tile flow underpredictions were -9 and - 12%, whereas NO3-N losses were 0.6 and -54%. Adjusting a N parameter further improved predicted CS NO3-N losses. Predicted monthly tile flows and NO3-N losses for the CA simulation compared poorly with observed values (r2 values of 0.27 and 0.19); the annual drainage volumes and N losses were of similar magnitude to those measured. Overall, EPIC replicated the relative impacts of the three cropping systems on N fate.     

MODELING A CONCRETE BLOCK IRRIGATION DIVERSION SYSTEM1

ABSTRACT: Concrete block irrigation diversion systems have been proposed as alternatives to permanent dams of concrete or rock or temporary gravel berms. Permanent dams can cause stream channel instability, bank erosion, sediment pollution, ice flow blockage, and safety problems for recreational floating craft. Temporary berms can require substantial streambed disturbance and can promote sediment pollution, stream bank instability, and bank erosion. A design procedure was developed based on a model of the hydraulic performance of concrete block diversion systems. The procedure was used to model a site on the Gallatin River in Montana. The method relies on HEC-RAS (Hydrologic Engineering Center -River Analysis System) software combined with analytical techniques in an iterative scheme. The hydraulic performance of different diversion configurations (the existing heavy-rock diversion system, concrete blocks oriented parallel to flow, and concrete blocks oriented diagonally) was assessed using the model under a range of flow rates. The minimum diversion dimensions (length, number, and size of blocks) that maintained block stability while diverting the requisite flow were determined for each model run. At the Gallatin River site, the block system oriented parallel to flow required less diversion material than the diagonal orientation. The recommended diversion length was 51.8 m (170 ft). Trapezoidal blocks with a top width of 20.3 cm (8 in), a height of 45.7 cm (18 in), and side slopes of 2 vertical to 1 horizontal were specified. This configuration minimizes the total block mass, diverts the required flow, and has a factor of safety of 2.0 against block displacement.     

VERIFICATION OF THE RHEA-OROGRAPHIC-PRECIPITATION MODEL1

ABSTRACT: Observed April 1 snowpack accumulations within and near the Gunnison River basin in southwestern Colorado are compared with simulations from the Rhea-orographic-precipitation model to determine if the model simulates reliable magnitudes and temporal and spatial variability in winter precipitation for the basin. Twenty simulations of the Rhea model were performed using‘optimal’parameter sets determined for 10-kilometer (km) grids (10-km by 10-km grid cells) through stochastic calibration. Comparisons of Rhea-model simulations of winter precipitation with April 1 snowpack accumulations at 32 snowcourse stations were performed for the years 1972–1990. For most stations and most years the Rhea model reliably simulates the temporal and spatial variability in April 1 snowpack accumulations. However, in general, the Rhea-model underestimates April 1 snowpack accumulations in the Gunnison River basin area, and the underestimation is greatest for locations that receive the largest amount of snow. A significant portion of the error in Rhea-model simulations is due to the calibration of the Rhea model using gauge-catch precipitation measurements which can be as much as 50 percent below actual snowfall accumulations. Additional error in the Rhea-model simulations is a result of the comparison of gridded precipitation values to observed values measured at points.     

CLIMATE VARIABILITY AND FLOOD FREQUENCY ESTIMATION FOR THE UPPER MISSISSIPPI AND LOWER MISSOURI RIVERS1

ABSTRACT: This paper considers the distribution of flood flows in the Upper Mississippi, Lower Missouri, and Illinois Rivers and their relationship to climatic indices. Global climate patterns including El Niño/Southern Oscillation, the Pacific Decadal Oscillation, and the North Atlantic Oscillation explained very little of the variations in flow peaks. However, large and statistically significant upward trends were found in many gauge records along the Upper Mississippi and Missouri Rivers: at Hermann on the Missouri River above the confluence with the Mississippi (p = 2 percent), at Hannibal on the Mississippi River (p < 0.1 percent), at Meredosia on the Illinois River (p = 0.7 percent), and at St. Louis on the Mississippi below the confluence of all three rivers (p = 1 percent). This challenges the traditional assumption that flood series are independent and identically distributed random variables and suggests that flood risk changes over time.     

REGULATED RIVER MODELING FOR CLIMATE CHANGE IMPACT ASSESSMENT: THE MISSOURI RIVER1

ABSTRACT: The Great Plains of the United States, drained primanly by the Missouri River, are very sensitive to shifts in climate. The six main stem dams on the Missouri River control more than one‐half of the nearly 1.5 million square kilometer basin and can store three times the annual inflow from upstream. The dams are operated by the U.S. Army Corps of Engineers using a Master Manual that describes system priorities and benefits. The complex operational rules were incorporated into the Soil and Water Assessment Tool computer model (SWAT). SWAT is a distributed parameter rainfall‐runoff model capable of simulating the transpiration suppression effects of CO₂ enrichment. The new reservoir algorithms were calibrated using a 25‐year long historic record of basin climate and discharge records. Results demonstrate that it is possible to incorporate the operation of a highly regulated river system into a complex rainfall‐runoff model. The algorithms were then tested using extreme climate scenarios indicative of a prolonged drought, a short drought, and a ten percent increase in basin‐wide precipitation. It is apparent that the rules for operating the reservoirs will likely require modification if, for example, upper‐basin precipitation were to increase only ten percent under changed climate conditions.     

Parameter Uncertainty Reduction for SWAT Using Grace,Streamflow, and Groundwater Table Data for Lower Missouri River Basin1

Abstract: This study incorporates the newly available Gravity Recovery and Climate Experiment (GRACE) water storage data and water table data from well logs to reduce parameter uncertainty in Soil and Water Assessment Tool (SWAT) calibration using a SUFI2 (sequential uncertainty fitting) framework for the Lower Missouri River Basin. Model evaluations are performed in multiple stages using a multiobjective function consisting of multisite streamflow and GRACE water storage data as well as a groundwater component. Results show that (1) a model calibrated with both streamflow and GRACE data simultaneously can maintain the water balance for the whole basin, but may improperly partition surface flow and base flow. Additional inclusion of the groundwater constraint can significantly improve the model performance in groundwater hydrological processes. In our case, the estimation of specific yield of shallow aquifers has been increased to 10^?2 from previous much underestimated level (<10^?3). (2) The daily streamflow data are needed to confine the parameters related to water flow in channels such as the Manning’s coefficient, which are less sensitive to the monthly simulations. (3) Parameters are nonuniformly sensitive for different goal variables, and thus, proper specification of a prior distribution of parameters may be the key factor for global optimization algorithms to obtain stable and realistic model performance.     

基于MIKE 21的汾河水库挟沙水流水质数值模拟研究

为了揭示悬浮泥沙(SSC)对水库水质的影响规律,对汾河水库进行样品收集和长期水质监测,采用水动力模型与泥沙转移和富营养化模型相结合的方法,将这三者关联耦合,并通过实测数据对模型进行参数率定和验证,分析含沙水和不含沙水中总氮(TN)、总磷(TP)、叶绿素a(Chla)、溶解氧(DO)四项指标,得出两者对水质造成的影响。结果表明:SSC对TN、TP的去除作用明显,对Chla、DO浓度分布影响较小,并计算了污染物的释放量以及贡献率,得出TP的负荷仅为16.47t,而贡献率高达25.25%。因此在汾河的污染控制方面应侧重削减磷,进而改善汾河地区的污染现状。     

基于MIKE 21的汾河水库挟沙水流水质数值模拟研究

为了揭示悬浮泥沙(SSC)对水库水质的影响规律,对汾河水库进行样品收集和长期水质监测,采用水动力模型与泥沙转移和富营养化模型相结合的方法,将这三者关联耦合,并通过实测数据对模型进行参数率定和验证,分析含沙水和不含沙水中总氮(TN)、总磷(TP)、叶绿素a(Chla)、溶解氧(DO)四项指标,得出两者对水质造成的影响。结果表明:SSC对TN、TP的去除作用明显,对Chla、DO浓度分布影响较小,并计算了污染物的释放量以及贡献率,得出TP的负荷仅为16.47t,而贡献率高达25.25%。因此在汾河的污染控制方面应侧重削减磷,进而改善汾河地区的污染现状。     

Modeled Summer Background Concentration of Nutrients and Suspended Sediment in the Mid‐Continent (USA) Great Rivers1

Angradi, Ted R., David W. Bolgrien, Matt A. Starry, and Brian H. Hill, 2012. Modeled Summer Background Concentration of Nutrients and Suspended Sediment in the Mid‐Continent (USA) Great Rivers. Journal of the American Water Resources Association (JAWRA) 48(5): 1054‐1070. DOI: 10.1111/j.1752‐1688.2012.00669.x Abstract: We used regression models to predict summer background concentration of total nitrogen (N), total phosphorus (P), and total suspended solids (TSS), in the mid‐continent great rivers: the Upper Mississippi, the Lower Missouri, and the Ohio. From multiple linear regressions of water quality indicators with land use and other stressor variables, we determined the concentration of the indicators when the predictor variables were all set to zero — the y‐intercept. Except for total P on the Upper Mississippi River, we could predict background concentration using regression models. Predicted background concentration of total N was about the same on the Upper Mississippi and Lower Missouri Rivers (430 μg l^?1), which was lower than percentile‐based values, but was similar to concentrations derived from the response of sestonic chlorophyll a to great river total N concentration. Background concentration of total P on the Lower Missouri (65 μg l^?1) was also lower than published and percentile‐based concentrations. Background TSS concentration was higher on the Lower Missouri (40 mg l^?1) than the other rivers. Background TSS concentration on the Upper Mississippi (16 mg l^?1) was below a threshold (30 mg l^?1) designed to protect aquatic vegetation. Our model‐predicted concentrations for the great rivers are an attempt to estimate background concentrations for water quality indicators independent from thresholds based on percentiles or derived from stressor‐response relationships.     

Impact of Watershed Subdivision and Soil Data Resolution on SWAT Model Calibration and Parameter Uncertainty1

Abstract: Impact of watershed subdivision and soil data resolution on Soil Water Assessment Tool (SWAT) model calibration and parameter uncertainty is investigated by creating 24 different watershed model configurations for two study areas in northern Indiana. SWAT autocalibration tool is used to calibrate 14 parameters for simulating seven years of daily streamflow records. Calibrated parameter sets are found to be different for all 24 watershed configurations, however in terms of calibrated model output, their effect is minimal. In some cases, autocalibration is followed by manual calibration to correct for low flows, which were underestimated during autocalibration. In addition to normal validation using four years of streamflow data for each calibrated parameter set, cross‐validation (using a calibrated parameter set from one model configuration to validate observations using another configuration) is performed to investigate the effect of different model configurations on streamflow prediction. Results show that streamflow output during cross‐validation is not affected, thus highlighting the non‐unique nature of calibrated parameters in hydrologic modeling. Finally, parameter uncertainty is investigated by extracting good parameter sets during the autocalibration process. Parameter uncertainty analysis suggests that significant parameters show very narrow range of uncertainty across different watershed configurations compared with nonsignificant parameters. Results from recalibration of some configurations using only six significant parameters were comparable to that from calibration using 14 parameters, suggesting that including fewer significant parameters could reduce the uncertainty arising from model parameters, and also expedite the calibration process.     

Nutrient Sources and Transport in the Missouri River Basin,with Emphasis on the Effects of Irrigation and Reservoirs1

Brown, Juliane B., Lori A. Sprague, and Jean A. Dupree, 2011. Nutrient Sources and Transport in the Missouri River Basin, With Emphasis on the Effects of Irrigation and Reservoirs. Journal of the American Water Resources Association (JAWRA) 47(5):1034‐1060. DOI: 10.1111/j.1752‐1688.2011.00584.x Abstract: SPAtially Referenced Regressions On Watershed attributes (SPARROW) models were used to relate instream nutrient loads to sources and factors influencing the transport of nutrients in the Missouri River Basin. Agricultural inputs from fertilizer and manure were the largest nutrient sources throughout a large part of the basin, although atmospheric and urban inputs were important sources in some areas. Sediment mobilized from stream channels was a source of phosphorus in medium and larger streams. Irrigation on agricultural land was estimated to decrease the nitrogen load reaching the Mississippi River by as much as 17%, likely as a result of increased anoxia and denitrification in the soil zone. Approximately 16% of the nitrogen load and 33% of the phosphorus load that would have otherwise reached the Mississippi River was retained in reservoirs and lakes throughout the basin. Nearly half of the total attenuation occurred in the eight largest water bodies. Unlike the other major tributary basins, nearly the entire instream nutrient load leaving the outlet of the Platte and Kansas River subbasins reached the Mississippi River. Most of the larger reservoirs and lakes in the Platte River subbasin are upstream of the major sources, whereas in the Kansas River subbasin, most of the source inputs are in the southeast part of the subbasin where characteristics of the area and proximity to the Missouri River facilitate delivery of nutrients to the Mississippi River.     

硫磺沟煤矿3#井矿井水处理措施分析

硫磺沟煤矿紧邻头屯河，多年以来煤矿矿井水未做任何处理直接排入头屯河，已经对头屯河造成了污染。本文根据硫磺沟煤矿3^#井矿井水涌水量、水质情况及处理后所排入水体的标准要求，确定矿井水处理工艺、主要处理构筑物及技术参数，以使矿井水达标排放，减轻对头屯河水的污染。     

The Ability of Urban Residential Lawns to Disconnect Impervious Area from Municipal Sewer Systems1

Abstract: Runoff from urban catchments depends largely on the amount of impervious surface and the connectivity of these surfaces to the storm sewer drainage system. In residential areas, pervious lawns can be used to help manage stormwater runoff by intercepting and infiltrating runoff from impervious surfaces. The goal of this research was to develop and evaluate a simple method for estimating the reduction in stormwater runoff that results when runoff from an impervious surface (e.g., rooftop) is directed onto a pervious surface (e.g., lawn). Fifty‐two stormwater runoff reduction tests were conducted on six residential lawns in Madison, Wisconsin during the summer of 2004. An infiltration‐loss model that requires inputs of steady‐state infiltration rate, abstraction (defined here as surface storage, vegetation interception and cumulative total infiltration minus steady‐state infiltration during the period prior to steady‐state), and inundated area was evaluated using experimental data. The most accurate results were obtained using the observed steady‐state infiltration rates and inundated areas for each test, combined with a constant abstraction for all tests [root mean squared (RMS) difference = 1.0 cm]. A second case utilized lawn‐averaged steady‐state infiltration rates, a regression estimate of inundated area based on flow‐path length, and lawn‐specific abstractions based on infiltration rate (RMS difference = 2.2 cm). In practice, infiltration rates will likely be determined using double‐ring infiltration measurements (RMS difference = 3.1 cm) or soil texture (RMS difference = 5.7 cm). A generalized form of the model is presented and used to estimate annual stormwater runoff volume reductions for Madison. Results indicate the usefulness of urban lawns as a stormwater management practice and could be used to improve urban runoff models that incorporate indirectly connected impervious areas.     

Hydrologic Calibration and Validation of SWAT in a Snow‐Dominated Rocky Mountain Watershed,Montana, U.S.A.1

Abstract: The Soil and Water Assessment Tool (SWAT) has been applied successfully in temperate environments but little is known about its performance in the snow‐dominated, forested, mountainous watersheds that provide much of the water supply in western North America. To address this knowledge gap, we configured SWAT to simulate the streamflow of Tenderfoot Creek (TCSWAT). Located in central Montana, TCSWAT represents a high‐elevation watershed with ～85% coniferous forest cover where more than 70% of the annual precipitation falls as snow, and runoff comes primarily from spring snowmelt. Model calibration using four years of measured daily streamflow, temperature, and precipitation data resulted in a relative error (RE) of 2% for annual water yield estimates, and mean paired deviations (Dv) of 36 and 31% and Nash‐Sutcliffe (NS) efficiencies of 0.90 and 0.86 for monthly and daily streamflow, respectively. Model validation was conducted using an additional four years of data and the performance was similar to the calibration period, with RE of 4% for annual water yields, Dv of 43% and 32%, and NS efficiencies of 0.90 and 0.76 for monthly and daily streamflow, respectively. An objective, regression‐based model invalidation procedure also indicated that the model was validated for the overall simulation period. Seasonally, SWAT performed well during the spring and early summer snowmelt runoff period, but was a poor predictor of late summer and winter base flow. The calibrated model was most sensitive to snowmelt parameters, followed in decreasing order of influence by the surface runoff lag, ground water, soil, and SCS Curve Number parameter sets. Model sensitivity to the surface runoff lag parameter reflected the influence of frozen soils on runoff processes. Results indicated that SWAT can provide reasonable predictions of annual, monthly, and daily streamflow from forested montane watersheds, but further model refinements could improve representation of snowmelt runoff processes and performance during the base flow period in this environment.     

Applications of Explicitly Incorporated/Post‐Processing Measurement Uncertainty in Watershed Modeling

In the field of watershed modeling, the impact of measurement uncertainty (MU) on calibration results indicates the potential issue of inaccurate model predictions. It is important to note that MU refers to the uncertainty in measured data such as flow and nutrient values that are used to evaluate model outputs. The calculation of error statistics assuming measured data are deterministic may not be appropriate as has been frequently stated in literature. Although MU can affect model calibration results, it is rarely incorporated in modeling practice. MU can be incorporated in two schemes: explicitly incorporated (MU‐EI) during model calibration and post‐processed (MU‐PP) after calibration is completed. In this study, both schemes are implemented in a case study of the Arroyo Colorado Watershed, Texas. Unexpectedly, no substantial differences were observed between each scheme for flow predictions. Although MU did not cause dramatic differences in most sediment and NH₄‐N predictions, error statistics were affected in cases with MU greater than 50%, especially for sediment and NH₄‐N. Therefore, it is concluded that MU may not exert a significant impact on model predictions until certain threshold is reached. This study demonstrates that high levels of uncertainty in measured calibration/validation data significantly affect parameter estimation, especially in the auto‐calibration process.     

A CRITICAL APPROACH TO THE CALIBRATION OF A WATERSHED MODEL1

ABSTRACT: A complex watershed-scale water quality simulation model, the Hydrological Simulation Program-FORTRAN (HSPF) model, was calibrated for a 16 km² catchment. The simulation step size was 0.33 hours with predicted and recorded hydrologic flows compared on an annual and monthly basis during a total calibration period of four years. Unguided numerical optimization when applied alone did not yield a model parameter set with acceptable predictive capability; instead, it was necessary to apply a critical process that included sensitivity analysis, numerical optimization, and testing of derived model parameter sets to evaluate their performance for periods other than those for which they were determined. Using this critical calibration process, the model was proven to have significant predictive capability. Numerical optimization is an aid for model calibration, but it must not be used blindly.