IMPROVED RAINFALL/RUNOFF ESTIMATES USING REMOTELY SENSED SOIL MOISTURE1

ABSTRACT: Remotely sensed soil moisture data measured during the Southern Great Plains 1997 (SGP97) experiment in Oklahoma were used to characterize antecedent soil moisture conditions for the Soil Conservation Service (SCS) curve number method. The precipitation‐adjusted curve number and the soil moisture were strongly related (r²= 0.70). Remotely sensed soil moisture fields were used to adjust the curve numbers and the runoff estimates for five watersheds, in the Little Washita watershed; the results ranged from 2.8 km² to 601.6 km². The soil moisture data were applied at two spatial scales, a finer one (800 m) measuring spatial resolution and a coarser one (28 km). The root mean square error (RMSE) and the mean absolute error (MAE) of the runoff estimated by the standard SCS method was reduced by nearly 50 percent when the 800 m soil moisture data were used to adjust the curve number. The coarser scale soil moisture data also significantly reduced the error in the runoff predictions with 41 percent and 28 percent reductions in MAE and RMSE, respectively. The results suggest that remote sensing of soil moisture, when combined with the SCS method, can improve rainfall runoff predictions at a range of spatial scales.     

Runoff and soil loss from steep slopes treated with low cost bioengineering measures

Soil loss and surface runoff patterns were studied in erosion plots developed on manmade steep slopes (60 percent) over three years (1997–2000) in which rainfall ranged from 1338.4 to 1429.2 mm/year. Surface runoff and soil loss was examined under three different rainfall intensity classes. Runoff was mainly controlled by the rainfall distribution pattern on the seasonal scale. The soil loss was influenced by runoff during the first year. Both soil loss and runoff were reduced due to bioengineering measures in the first year irrespective of species planted. In the third year, combined effects of growth of grasses on protected plots, soil compaction and sediment exhaustion was noticed on runoff and soil loss. This was reflected by reduction in the runoff and soil loss from untreated and treated plots. In the high intensity class, reduction in runoff in treated plots was about 50 percent in three years and reduction in soil loss ranged between 94–95 percent in all plots. Physical treatment with brushwood structures was more efficient in erosion control in the low intensity class.     

A STRIP MODEL APPROACH TO PARAMETERIZE A COUPLED GREEN‐AMPT KINEMATIC WAVE MODEL1

ABSTRACT: Infiltration processes at the plot scale are often described and modeled using a single effective hydraulic conductivity (Kg) value. This can lead to errors in runoff and erosion prediction. An integrated field measurement and modeling study was conducted to evaluate: (1) the relationship among rainfall intensity, spatially variable soil and vegetation characteristics, and infiltration processes; and (2) how this relationship could be modeled using Green and Ampt and a spatially distributed hydrologic model. Experiments were conducted using a newly developed variable intensity rainfall simulator on 2 m by 6 m plots in a rangeland watershed in southeastern Arizona. Rainfall application rates varied between 50 and 200 mm/hr. Results of the rainfall simulator experiments showed that the observed hydrologic response changed with changes in rainfall intensity and that the response varied with antecedent moisture condition. A distributed process based hydrologic simulation model was used to model the plots at different levels of hydrologic complexity. The measurement and simulation model results show that the rainfall runoff relationship cannot be accurately described or modeled using a single Kg value at the plot scale. Multi‐plane model configurations with infiltration parameters based on soil and plot characteristics resulted in a significant improvement over single‐plane configurations.     

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.     

Inferring Hydrograph Components from Rainfall and Streamflow Records Using a Kriging Method-Based Linear Cascade Reservoir Model1

Cheng, Shin-jen, 2010. Inferring Hydrograph Components From Rainfall and Streamflow Records Using a Kriging Method-Based Linear Cascade Reservoir Model. Journal of the American Water Resources Association (JAWRA) 46(6):1171–1191. DOI: 10.1111/j.1752-1688.2010.00484.x Abstract: This study investigates the characteristics of hydrograph components in a Taiwan watershed to determine their shapes based on observations. Hydrographs were modeled by a conceptual model of three linear cascade reservoirs. Mean rainfall was calculated using the block Kriging method. The optimal parameters for 42 events from 1966-2008 were calibrated using an optimal algorithm. Rationality of generated runoffs was well compared with a trusty model. Model efficacy was verified using seven averaged parameters with 25 other events. Hydrograph components were characterized based on 42 calibration results. The following conclusions were obtained: (1) except for multipeak storms, a correlation between base time of the surface runoff and soil antecedent moisture is a decreasing power relationship; (2) a correlation between time lag of the surface flow and soil antecedent moisture for single-peak storms is an increasing power relationship; (3) for single-peak events, times to peak of hydrograph components are an increasing power correlation corresponding to the peak time of rainfall; (4) the peak flows of hydrograph components are linearly proportional to that of total runoff, and the peak ratio for the surface runoff to total runoff is approximately 78 and 13% for subsurface runoff to total runoff; and (5) the relationships of total discharges have direct ratios between hydrograph components and observations of total runoffs, and a surface runoff is 60 and 32% for a subsurface runoff.     

A REVISED VERSION OF PnET‐II TO SIMULATE THE HYDROLOGIC CYCLE IN SOUTHEASTERN FORESTED AREAS1

ABSTRACT: The PnET‐II model uses hydroclimatic data on maximum and minimum temperatures, precipitation, and solar radiation, together with vegetation and soil parameters, to produce estimates of net primary productivity, evapotranspiration (ET), and runoff on a monthly time step for forested areas. In this study, the PnET‐II model was employed to simulate the hydrologic cycle for 17 Southeastern eight‐digit hydrologic unit code (HUC) watersheds dominated by evergreen or deciduous tree species. Based on these control experiments, model biases were quantified and tentative revision schemes were introduced. Revisions included: (1) replacing the original single soil layer with three soil layers in the water balance routine; (2) introducing calibrating factors to rectify the phenomenon of overestimation of ET in spring and early summer months; (3) parameterizing proper values of growing degree days for trees located in different climate zones; and (4) adjusting the parameter of fast‐flow (overland flow) fraction based on antecedent moisture condition and precipitation intensity. The revised PnET‐II model, called PnET‐II3SL in this work, substantially improved runoff simulations for the 17 selected experimental sites, and therefore may offer a more powerful tool to address issues in water resources management.     

FOREST HYDROLOGY AND EXTREME RAINFALL FREQUENCY1

Extreme rainfall frequency analysis provides one means to predict, within certain limits of probability, the average time interval between the recurrences of storms of a specified duration and magnitude. This in turn furnishes the forest hydrologist a valuable tool for engineering design and runoff and erosion forecast. A modification in the application of the annual maximum and annual exceedance series analysis described by V. T. Chow can, for special purposes, lead to an even more useful estimate of extreme events on a seasonal basis. This can be particularly important on small forested headwater watersheds where the runoff response to extreme rainfall may vary considerably with seasonal changes in canopy cover and soil moisture characteristics. Although the application of data covering a relatively short period of record has produced some inconsistencies among the frequency diagrams, under certain circumstances for short-term recurrence interval forecast and for non-critical application the analysis of extreme rainfall frequency from less than 20 years data seems justified.     

A Multi‐Scale Soil Moisture Monitoring Strategy for California: Design and Validation

A multi‐scale soil moisture monitoring strategy for California was designed to inform water resource management. The proposed workflow classifies soil moisture response units (SMRUs) using publicly available datasets that represent soil, vegetation, climate, and hydrology variables, which control soil water storage. The SMRUs were classified, using principal component analysis and unsupervised K‐means clustering within a geographic information system, and validated, using summary statistics derived from measured soil moisture time series. Validation stations, located in the Sierra Nevada, include transect of sites that cross the rain‐to‐snow transition and a cluster of sites located at similar elevations in a snow‐dominated watershed. The SMRUs capture unique responses to varying climate conditions characterized by statistical measures of central tendency, dispersion, and extremes. A topographic position index and landform classification is the final step in the workflow to guide the optimal placement of soil moisture sensors at the local‐scale. The proposed workflow is highly flexible and can be implemented over a range of spatial scales and input datasets can be customized. Our approach captures a range of soil moisture responses to climate across California and can be used to design and optimize soil moisture monitoring strategies to support runoff forecasts for water supply management or to assess landscape conditions for forest and rangeland management.     

EVAPOTRANSPIRATION AND SOIL MOISTURE DYNAMICS ON A SEMIARID PONDEROSA PINE HILLSLOPE1

ABSTRACT: Detailed measurements of soil moisture and ET in semiarid forest environments have not been widely reported in the literature. In this study, soil moisture and water balance components were measured over a four‐year period on a semiarid ponderosa pine hillslope, with evapotranspiration (ET) determined as the residual of measured precipitation, runoff, and change in soil moisture storage. ET accounts for approximately 95 percent of the water budget and has a distinctly bimodal annual pattern, with peaks occurring after spring snowmelt and during the late summer monsoon season, periods that coincide with high soil moisture. Weekly growing season ET rates determined by the hillslope water balance are found to be invariably below calculated potential rates. Normalized ET rates are linearly correlated (r²= 0.62) with soil moisture; therefore, a simple linear relation is proposed. Growing season soil moisture dynamics were modeled based on this relation. Results are in fair agreement (r²= 0.63) with the observed soil moisture data over the four growing seasons; however, for two dry summers with little surface runoff, much better results (r² > 0.90) were obtained.     

The Effect of Water Harvesting Techniques on Runoff,Sedimentation, and Soil Properties

This study addressed the hydrological processes of runoff and sedimentation, soil moisture content, and properties under the effect of different water harvesting techniques (treatments). The study was conducted at three sites, representing environmental condition gradients, located in the southern part of the West Bank. For each treatment, the study evaluated soil chemical and physical properties, soil moisture at 30 cm depth, surface runoff and sedimentation at each site. Results showed that runoff is reduced by 65–85% and sedimentation by 58–69% in stone terraces and semi-circle bunds compared to the control at the semi-humid site. In addition, stone terraces and contour ridges significantly reduced the amount of total runoff by 80% and 73%, respectively, at the arid site. Soil moisture content was significantly increased by water harvesting techniques compared to the control in all treatments at the three study sites. In addition, the difference between the control and the water harvesting structures were higher in the arid and semi-arid areas than in the semi-humid area. Soil and water conservation, via utilization of water harvesting structures, is an effective principle for reducing the negative impact of high runoff intensity and subsequently increasing soil moisture storage from rainfall. Jessour systems in the valley and stone terraces were effective in increasing soil moisture storage, prolonging the growing season for natural vegetation, and decreasing the amount of supplemental irrigation required for growing fruit trees.     

SPATIAL VARIABILITY IN WATER‐BALANCE MODEL PERFORMANCE IN THE CONTERMINOUS UNITED STATES1

ABSTRACT: A monthly water‐balance (WB) model was tested in 44 river basins from diverse physiographic and climatic regions across the conterminous United States (U.S.). The WB model includes the concepts of climatic water supply and climatic water demand, seasonality in climatic water supply and demand, and soil‐moisture storage. Exhaustive search techniques were employed to determine the optimal set of precipitation and temperature stations, and the optimal set of WB model parameters to use for each basin. It was found that the WB model worked best for basins with: (1) a mean elevation less than 450 meters or greater than 2000 meters, and/or (2) monthly runoff that is greater than 5 millimeters (mm) more than 80 percent of the time. In a separate analysis, a multiple linear regression (MLR) was computed using the adjusted R‐square values obtained by comparing measured and estimated monthly runoff of the original 44 river basins as the dependent variable, and combinations of various independent variables [streamflow gauge latitude, longitude, and elevation; basin area, the long‐term mean and standard deviation of annual precipitation; temperature and runoff; and low‐flow statistics (i.e., the percentage of months with monthly runoff that is less than 5 mm)]. Results from the MLR study showed that the reliability of a WB model for application in a specific region can be estimated from mean basin elevation and the percentage of months with gauged runoff less than 5 mm. The MLR equations were subsequently used to estimate adjusted R‐square values for 1,646 gauging stations across the conterminous U.S. Results of this study indicate that WB models can be used reliably to estimate monthly runoff in the eastern U.S., mountainous areas of the western U.S., and the Pacific Northwest. Applications of monthly WB models in the central U.S. can lead to uncertain estimates of runoff.     

ESTIMATING RUNOFF VOLUMES FROM URBAN AREAS1

ABSTRACT: Estimations of runoff volumes from urban areas can be made by the equation Q = a A σ(P_e– b), where Q is the runoff volume, a is the part of the total area A Contributing to runoff, P_e is the rainfall amount for a single event, and b is the initial rainfall losses. For the evaluation of a and b, rainfall/runoff measurements were made in five areas of sizes between 0.035 km² and 1.450 km². By linear regression analysis of rainfall volumes versus runoff volumes, the initial rainfall losses were found to vary from 0.38 mm to 0.70 mm for the different areas. The parts of the areas contributing to runoff were found to be proportional to the impermeable parts of the mas. The equation is applicable in urban areas with well defined paved surfaces and roofs and with a negligible amount of runoff from permeable areas.     

Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.     

RUNOFF AND SEDIMENT YIELD UNDER GRAZING IN FOOTHILLS FESCUE GRASSLANDS OF ALBERTA1

ABSTRACT: Grazing can have a profound impact on infiltration and thus runoff and erosion. The objectives of this study were to quantify the effects of select grazing systems on rainfall and snowmelt induced runoff and sediment yield from sloped areas of the foothills fescue grasslands of Alberta, Canada. The effects of two grazing intensities (heavy and very heavy) for two durations (short duration and continuous throughout the growing season) were compared to an ungrazed control between June 1988 and April 1991. Runoff was measured using 1-rn² runoff frames and collection bucket systems. Sediment yields were then determined on samples from the collected runoff. Snowmelt was the dominant source of runoff. Snowmelt runoff was higher from the heavily grazed areas than from the very heavily grazed areas, due to the higher standing vegetation which accumulated snow in the former areas. Sediment yields as a result of snowmelt were generally low in all areas. Only a few summer storms caused runoff. Runoff volumes and sediment yields from summer rainstorms were low, due to low rainfall and to generally dry antecedent soil moisture conditions. The greatest risk of summer runoff, and thus sediment yield, appears to occur in August.     

EVALUATION OF EROSION CONTROL PRODUCTS WITH AND WITHOUT ADDED POLYACRYLAMIDE1

ABSTRACT: Polyacrylamide (PAM) has been demonstrated to greatly reduce erosion in furrow irrigation, but much less is known about its effectiveness on the much steeper slopes typical of construction sites. The purpose of this study was to determine if anionic PAM would enhance erosion control either alone on bare soil or in combination with four types of ground covers commonly used for grass establishment: straw, straw erosion control blanket (ECB), wood fiber, and mechanically bonded fiber matrix (MBFM). Tests were conducted under natural rainfall and vegetation on a 4 percent slope (bare soil, straw, ECB, and MBFM) or using a rainfall simulator (bare soil, straw, wood fiber, MBFM) on either 10 percent or 20 percent slope on three different soil substrates. All ground cover treatments were evaluated with and without PAM applied in solution at 19 kg/ha. The straw, ECB, and MBFM significantly reduced runoff volume, average turbidity, and total sediment lost over five rainfall events on the vegetated plots. The addition of PAM to ground covers only occasionally had significant effects on runoff parameters but did significantly increase vegetative coverage overall. The rainfall simulator tests produced similar results after four events, with the straw, wood fiber, and MBFM all having significantly lower turbidity than the bare soil. The PAM significantly reduced turbidity for both the first and second events but did not consistently improve runoff quality after multiple rainfall events for any ground cover‐soil combinations tested. Separate tests of PAM applied before or after straw did not indicate a clear advantage of either approach, but runoff turbidity was often significantly reduced with PAM, especially at the 20 percent slope. Turbidity reductions were attributed to flocculation of eroded sediment.     

RELIABILITY OF THE DESIGN STORM CONCEPT IN EVALUATING RUNOFF PEAK FLOW1

A comparative study was undertaken to evaluate peak runoff flow rates using (1) a continuous series of actual rainfall events and (2) design storms. The ILLUDAS computer model was used to simulate runoff over a catchment within the city of Montreal, Canada. A ten-year period, five-minute increment rainfall data base was used to derive peak flow frequency curves. Two types of design storms were analyzed: one derived from intensity duration frequency curves (Chicago type), the other from averaging actual rainfall patterns (Huff type). Antecedent soil moisture conditions were considered in the analyses. It was found that the probability distribution of runoff peak flow was sensitive to the choice of design storm pattern and to the antecedent soil moisture condition. A symmetrical, Chicago-type design storm with antecedent dry soil moisture produced a flow frequency curve similar to the one obtained from a series of historical rainfall events.     

Hydrology of small field plots used to study phosphorus runoff under simulated rainfall

Use of small plots and rainfall simulators to extrapolate trends in runoff water quality requires careful consideration of hydrologic process represented under such conditions. A modified version of the National Phosphorus Runoff Project (NPRP) protocol was used to assess the hydrology of paired 1 x 2 m plots established on two soils with contrasting hydrologic properties (somewhat poorly drained vs. well drained). Rain simulations (60 mm h(-1)) were conducted to generate 30 min of runoff. For the somewhat poorly drained soil, simulations were conducted in October and May to contrast dry conditions typically targeted by NPRP protocols with wet conditions generally associated with natural runoff. For the well-drained soil, only dry conditions (October) were evaluated. Under dry antecedent moisture conditions, an average of 64 mm of rainfall was applied to the somewhat poorly drained soil to generate 30 min of runoff, as opposed to 96 mm to the well-drained soil. At an extreme, differences in rainfall were equivalent to a 50-yr rainfall-return period. An absence of detectable spatial trends in surface soil moisture suggests uniformity of runoff processes within the plots. No differences in applied rainfall were evident between wet and dry antecedent conditions for the somewhat poorly drained soil. However, significant differences in runoff generation processes were observed in dissolved P concentrations between wet and dry conditions. As natural runoff from the somewhat poorly drained soil is largely under wet antecedent conditions, this study highlights the need for care in interpreting findings from generalized protocols that favor infiltration-excess runoff mechanisms.     

RUNOFF AND WATER QUALITY FROM THREE SOIL LANDFORM UNITS ON MANCOS SHALE1

ABSTRACT: Relative yields of water, sediment, and salt (as indexed by electrical conductivity) were determined using simulated rainfall plots on three soil landform units on Mancos shale in the Price River Basin, Utah. Final infiltration rates on residual shale derived soils were between 0.13 and 0.50 cm/hr. No runoff was generated on cracked soils derived from aeolian deposits. Suspended sediment concentrations and elehcal conductivities were 180 and 68 times greater, respectively, for a steep dissected Mancos shale upland than for a low relief shale pediment and recent alluvial surface. Riling accounted for approximately 80 percent of the sediment produced on the steep, dissected shale surface. Channel scow and soil creep also produced measurable mounts of sediment. A survey of sediment basins in steep, dissected shale up lands indicated that an average of 1.25 Mg/ha/year of sediment is produced by that landform unit Carefully designed and located basin plugs can be used effectively to trap sediment, water, and salt from dissected shale uplands.     

Calibration and Verification of SWMM for Low Impact Development

The Storm Water Management Model was used to simulate runoff and nutrient export from a low impact development (LID) watershed and a watershed using traditional runoff controls. Predictions were compared to observed values. Uncalibrated simulations underpredicted weekly runoff volume and average peak flow rates from the multiple subcatchment LID watershed by over 80%; the single subcatchment traditional watershed had better predictions. Saturated hydraulic conductivity, Manning's n for swales, and initial soil moisture deficit were sensitive parameters. After calibration, prediction of total weekly runoff volume for the LID and traditional watersheds improved to within 12 and 5% of observed values, respectively. For the validation period, predicted total weekly runoff volumes for the LID and traditional watersheds were within 6 and 2% of observed values, respectively. Water quality simulation was less successful, Nash–Sutcliffe coefficients >0.5 for both calibration and validation periods were only achieved for prediction of total nitrogen export from the LID watershed. Simulation of a 100‐year, 24‐h storm resulted in a runoff coefficient of 0.46 for the LID watershed and 0.59 for the traditional watershed. Results suggest either calibration is needed to improve predictions for LID watersheds or expanded look‐up tables for Green–Ampt infiltration parameter values that account for compaction of urban soil and antecedent conditions are needed.     

Time Series Analysis of Nebraska Daily Rainfall Data to Simulate Atrazine Runoff1

Abstract: Measured atrazine concentrations in Nebraska surface water have been shown to exceed water‐quality standards, posing risks to humans and to the ecosystem. To assess this risk, atrazine runoff was simulated at the field‐scale in Nebraska based on the pesticide component of the AGNPS model. This project’s objective was to determine the frequency that the atrazine concentration at the field outlet exceeded three different atrazine water‐quality criteria. The simulation was conducted for different farm management practices, soil moisture conditions, and five Nebraska topographic regions. If the criteria were exceeded, a risk to the drinking water consumer or freshwater aquatic life was hypothesized to exist. Three pesticide fate and transport processes were simulated with the model. Degradation was simulated using first‐order kinetics. Adsorption/desorption was modeled assuming a linear soil‐water partitioning coefficient. Advection (runoff) was based primarily on the USDA‐NRCS curve number method. Daily rainfall from the National Weather Service was used to compute the soil moisture conditions for the 1985‐2000 growing seasons. After each runoff event, the pesticide runoff concentration was compared with each of the three atrazine water‐quality criteria. The results show that environmental receptors (i.e., freshwater aquatic species) are exposed to unacceptable atrazine runoff concentrations in 20‐50% of the runoff events.