Baseflow separation in a small watershed in New Brunswick,Canada, using a recursive digital filter calibrated with the conductivity mass balance method

Baseflow separation is important for obtaining critical parameters for hydrological models. As measuring the baseflow component directly is difficult, various analytical and empirical baseflow separation methods have been developed and tested. The recursive digital filter (RDF) method is commonly used for baseflow separation due to its simplicity and low data requirement. However, parameters used in the RDF method are often determined arbitrarily, resulting in high uncertainty of the estimated baseflow rate. A more accurate method is the conductivity mass balance (CMB) method, which is established based on the differences in physical processes between baseflow and surface runoff. In this research, the output of the CMB method was used to calibrate the parameters of an RDF model, and the calibrated RDF model was used to estimate monthly, seasonal and annual baseflow rate and baseflow index for the past 19 years using streamflow discharge records. The characteristics of the baseflow hydrographs were found to be consistent with the hydrological and hydrogeological conditions of the research area. Research results indicated that the accuracy of the RDF model has been greatly enhanced after being calibrated with the CMB method so that the RDF model can provide more reliable baseflow separation results for a long‐term study. Copyright © 2012 John Wiley & Sons, Ltd.     

Hydrograph separation using tracers and digital filters to quantify runoff components in a semi‐arid mesoscale catchment

Chemical hydrograph separation using electrical conductivity and digital filters is applied to quantify runoff components in the 1,640 km² semi‐arid Kaap River catchment and its subcatchments in South Africa. A rich data set of weekly to monthly water quality data ranging from 1978 to 2012 (450 to 940 samples per site) was analysed at 4 sampling locations in the catchment. The data were routinely collected by South Africa's national Department of Water and Sanitation, using standard sampling procedures. Chemical hydrograph separation using electrical conductivity (EC) as a tracer was used as reference and a recursive digital filter was then calibrated for the catchment. Results of the two‐component hydrograph separation indicate the dominance of baseflow in the low flow regime, with a contribution of about 90% of total flow; however, during the wet season, baseflow accounts for 50% of total flow. The digital filter parameters were very sensitive and required calibration, using chemical hydrograph separation as a reference. Calibrated baseflow estimates ranged from 40% of total flow at the catchment outlet to 70% in the tributaries. The study demonstrates that routinely monitored water quality data, especially EC, can be used as a meaningful tracer, which could also aid in the calibration of a digital filter method and reduce uncertainty of estimated flow components. This information enhances our understanding of how baseflow is generated and contributed to streamflow throughout the year, which can aid in quantification of environmental flows, as well as to better parameterize hydrological models used for water resources planning and management. Baseflow estimates can also be useful for groundwater and water quality management.     

Effects of initial soil water content and saturated hydraulic conductivity variability on small watershed runoff simulation using LISEM

Abstract

Soil water content (θ) and saturated hydraulic conductivity (K_s) vary in space. The objective of this study was to examine the effects of initial soil water content (θ_i) and K_s variability on runoff simulations using the LImburg Soil Erosion Model (LISEM) in a small watershed in the Chinese Loess Plateau, based on model parameters derived from intensive measurements. The results showed that the total discharge (TD) and peak discharge (PD) were underestimated when the variability of θ_i and K_s was partially considered or completely ignored compared with those when the variability was fully considered. Time to peak (TP) was less affected by the spatial variability compared to TD and PD. Except for TP in some cases, significant differences were found in all hydrological variables (TD, PD and TP) between the cases in which spatial variability of θ_i or K_s was fully considered and those in which spatial variability was partially considered or completely ignored. Furthermore, runoff simulations were affected more strongly by K_s variability than by θ_i variability. The degree of spatial variability influences on runoff simulations was related to the rainfall pattern and θ_i. Greater rainfall depth and instantaneous rainfall intensity corresponded to a smaller influence of the spatial variability. Stronger effects of the θ_i variability on runoff simulation were found in wetter soils, while stronger effects of the K_s variability were found in drier soils. For accurate runoff simulation, the θ_i variability can be completely ignored in cases of a 1-h duration storm with a return period greater than 10 years, while K_s variability should be fully considered even in the case of a 1-h duration storm with a return period of 20 years.

Editor D. Koutsoyiannis; Associate editor A. Fiori     

Runoff modelling at two field slopes: use of in situ measurements of air permeability to characterize spatial variability of saturated hydraulic conductivity

The time required at a field site to obtain a few measurements of saturated hydraulic conductivity (K_s) will allow for many measurements of soil air permeability (k_a). This study investigates if k_a measured in situ (k_{a, in situ}) can be a substitute for measurement of K_s in relation to infiltration and surface runoff modelling. Measurements of k_{a, in situ} were carried out in two small agricultural catchments. A spatial correlation of the log‐transformed values existed having a range of approximately 100 m. A predictive relationship between K_s and k_a measured on 100‐cm³ soil samples in the laboratory was derived for one of the field slopes and showed good agreement with an earlier suggested predictive K_s–k_a relationship. In situ measurements of K_s and k_a suggested that the predictive relationships also could be used at larger scale. The K_s–k_a relationships together with the k_{a, in situ} data were applied in a distributed surface runoff (DSR) model, simulating a high‐intensity rainfall event. The DSR simulation results were highly dependent on whether the geometric average of k_{a, in situ} or kriged values of k_{a, in situ} was used as model input. When increasing the resolution of K_s in the DSR model, a limit of 30–40 m was found for both field slopes. Below this limit, the simulated runoff and hydrograph peaks were independent of resolution scale. If only a few randomly chosen values of K_s were used to represent the spatial variation within the field slope, very large deviations in repeated DSR simulation results were obtained, both with respect to peak height and hydrograph shape. In contrast, when using many predicted K_s values based on a K_s–k_a relationship and measured k_{a, in situ} data, the DSR model generally captured the correct hydrograph shape although simulations were sensitive to the chosen K_s–k_a relationship. As massive measurement efforts normally will be required to obtain a satisfactory representation of the spatial variability in K_s, the use of k_{a, in situ} to assess spatial variability in K_s appears a promising alternative. Copyright © 2004 John Wiley & Sons, Ltd.     

Statistical analysis of the effects on overland flow of spatial variability in soil hydraulic conductivity / Analyse statistique des effets de la variabilité spatiale de la conductivité hydraulique du sol sur l'écoulement de surface

Abstract

The effects of spatial variation of the saturated hydraulic conductivity (K _s ) of the soil on the variation of overland flow were tested by analysing 2000 synthetic rainfall—runoff events, all generated from real, observed rainfall events but with runoff modelled by a two-dimensional distributed model using different spatially variable K _s fields in a small (12 ha) agricultural catchment. The purpose is to determine the influence of spatial variation in K _s on runoff generation. The statistical measures used to describe the variation in the generated K _s were its coefficient of variation and correlation length. Both of these had two levels of typical values obtained from field measurements in other studies. The storms were analysed at a general event level, first using simple graphical and statistical methods and then using analysis of variance (ANOVA). The observed scale of the spatial variation of K _s does cause statistically significant variation in overland flow. The graphical analysis showed that the first flow peak in a multi-event storm had the largest variation and that differences were greater in the rising part of the hydrograph than in its recession. The greatest variation in overland flow was produced by the combination of the greater coefficient of variation and the longer correlation lengths. The smallest variation in overland flow was produced by the combination of the smaller coefficient of variation and the shorter correlation lengths. ANOVA showed that the coefficient of variation and correlation length alone did not explain all the variation of the total flow. ANOVA was not very useful due to the many restrictive assumptions that were not satisfied by the nature of the data and therefore analysis methods with less restrictive assumptions need to be tested.     

Infiltration and runoff generation processes in fire‐affected soils

Post‐wildfire runoff was investigated by combining field measurements and modelling of infiltration into fire‐affected soils to predict time‐to‐start of runoff and peak runoff rate at the plot scale (1 m²). Time series of soil‐water content, rainfall and runoff were measured on a hillslope burned by the 2010 Fourmile Canyon Fire west of Boulder, Colorado during cyclonic and convective rainstorms in the spring and summer of 2011. Some of the field measurements and measured soil physical properties were used to calibrate a one‐dimensional post‐wildfire numerical model, which was then used as a ‘virtual instrument’ to provide estimates of the saturated hydraulic conductivity and high‐resolution (1 mm) estimates of the soil‐water profile and water fluxes within the unsaturated zone. Field and model estimates of the wetting‐front depth indicated that post‐wildfire infiltration was on average confined to shallow depths less than 30 mm. Model estimates of the effective saturated hydraulic conductivity, K_s, near the soil surface ranged from 0.1 to 5.2 mm h^?1. Because of the relatively small values of K_s, the time‐to‐start of runoff (measured from the start of rainfall), t_p, was found to depend only on the initial soil‐water saturation deficit (predicted by the model) and a measured characteristic of the rainfall profile (referred to as the average rainfall acceleration, equal to the initial rate of change in rainfall intensity). An analytical model was developed from the combined results and explained 92–97% of the variance of t_p, and the numerical infiltration model explained 74–91% of the variance of the peak runoff rates. These results are from one burned site, but they strongly suggest that t_p in fire‐affected soils (which often have low values of K_s) is probably controlled more by the storm profile and the initial soil‐water saturation deficit than by soil hydraulic properties. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.     

A new baseflow separation method based on analytical solutions of the Horton infiltration capacity curve

The separation of baseflow is an important issue in hydrology. The objective of this paper is to develop a new baseflow separation method based on the Horton infiltration capacity curve. For this purpose, the mathematical expressions of three parameters for the Horton infiltration capacity curve were derived in terms of rainfall and runoff data, and the lag time of the effective rainfall in the unsaturated zone and the groundwater flow routing equation are also presented. With these equations, the baseflow hydrographs at the outlet of the basin can be separated. The flow chart of the proposed method for baseflow hydrograph separation is given. Three recent baseflow separation methods, i.e. digital filter, non‐linear reservoir and the Boussinesq equation, were chosen as parallel schemes to compare with the proposed method. Rainfall‐runoff data from four watersheds located in different climatic regions in China were selected and used as case studies. Test and application results indicate that the proposed baseflow hydrograph separation method is in accordance with the hydrological physical process. The proposed method is comparable with current available methods and reduces some of the subjective aspects for the rising limb of the baseflow hydrograph, and it is useful for unit hydrograph analysis and for the study of the rainfall‐runoff relationship. Copyright © 2006 John Wiley & Sons, Ltd.     

Estimation of baseflow nitrate loads by a recursive tracing source algorithm in a rainy agricultural watershed

Baseflow has become an important source of nitrate nonpoint source pollution in many intensive agricultural watersheds. Uncertainties in baseflow nutrient load separation are caused by the effects of hydrometeorological factors on both baseflow recession and baseflow nutrient load recession. These uncertainties have not been addressed well in the existing separating algorithms, which are based on simple baseflow rate–load relationships. In the present study, a recursive tracing source algorithm (RTSA) was developed based on a nonlinear reservoir algorithm and hydrometeorology-corrected baseflow nutrient load recession parameter. This approach was used to reduce the uncertainty of baseflow nitrate load estimation caused by variations in different load recessions under varying climate conditions. RTSA validation in a typical rainy agricultural watershed yielded Nash–Sutcliffe efficiency, root mean square error-observation standard deviation ratio, and R² values of 0.91, 0.30, and 0.91, respectively. The baseflow nitrate–nitrogen (N─NO₃^–) loads from 2003 to 2012 in the Changle River watershed of eastern China were estimated with the RTSA. The results indicated that baseflow nitrate export accounted for 62.0% of the mean total annual N─NO₃^– loads (18.0 kg/ha). The total baseflow N─NO₃^– export was highest in spring (3.6 kg/ha), followed by summer (3.2 kg/ha), winter (2.3 kg/ha), and autumn (2.1 kg/ha). The contribution of baseflow to total nitrate in the stream decreased in the order of winter (69.88%) >spring (66.59%) >autumn (60.36%) >summer (54.04%). The monthly baseflow N─NO₃^– loads and flow-weighted concentrations greatly increased during the research period (Mann–Kendall test, Z_s > 2.56, p < .01). Without proper countermeasures, baseflow nitrate may represent a serious long-term risk for water surfaces in the future.     

Performance of methods for estimating the time of concentration in a watershed of a tropical region

The time of concentration (T_c) is a fundamental parameter in the design of hydrological projects for watersheds. In this study a graphical methodology is described for estimating T_c in a watershed, and this is applied to 17 rainfall–runoff events from a rural watershed located near the capital city of Mato Grosso do Sul State, in the Brazilian Cerrado. The T_c values obtained through the graphical method were compared to T_c values estimated using 20 equations from various references. The equations were selected by considering those that were not developed using data for urban watersheds, and the results of the graphical method were compared to those derived by applying the equations to sub-basin data. The graphical method was reliable in determining T_c, and Ventura’s equation was found to present the best performance for a rural watershed in a tropical climate region.     

Parameter sensitivity of automated baseflow separation for snowmelt‐dominated watersheds and new filtering procedure for determining end of snowmelt period

Automation in baseflow separation procedures allowed fast and convenient baseflow and baseflow index (BF and BFI) estimation for studies including multiple watersheds and covering large spatio‐temporal scales. While most of the existing algorithms are developed and tested extensively for rainfall‐ and baseflow‐dominated systems, little attention is paid on their suitability for snowmelt‐dominated systems. Current publishing practice in regional‐scale studies is to omit BF and BFI uncertainty evaluation or sensitivity analysis. Instead, “standard” and “previously recommended” parameterizations are transferred from rainfall/BF to snowmelt‐dominated systems. We believe that this practice should be abandoned. First, we demonstrate explicitly that the three most popular heuristic automated BF separation methods—Lyne–Hollick and Eckhardt recursive digital filters, and the U.K. Institute of Hydrology smoothed minima method—produce a wide range of annual BF and BFI estimates due to parameter sensitivity during the annual snowmelt period. Then, we propose a solution for cases when BF and BFI calibration is not possible, namely excluding the snowmelt‐dominated period from the analysis. We developed an automated filtering procedure, which divides the hydrograph into pre‐snowbelt, post‐snowmelt, and snowmelt periods. The filter was tested successfully on 218 continuous water years of daily streamflow data for four snowmelt‐dominated headwater watersheds located in Wyoming (60–837 km²). The post‐snowmelt BF and BFI metric can be used for characterizing summer low‐flows for snowmelt‐dominated systems. Our results show that post‐snowmelt BF and BFI sensitivity to filter parameterization is reduced compared with the sensitivity of annual BF and BFI and is similar to the sensitivity levels for rainfall/baseflow systems.     

Geomorphic controls on the physical and hydrologic properties of soils in a valley floor

The distribution of soil hydraulic and physical properties strongly influences runoff processes in landscapes. Although much work has been done to quantify and predict the properties of hillslope soils, far less is known about the distribution of soil properties in valley floors. A technique that links the estimation and distribution of soil hydraulic properties in valleys, with easily identified geomorphic features, was developed along a 2 km length of a valley at Brooks Creek in New South Wales, Australia. Soil physical and hydraulic property data were collected across a set of floodplain and fan features within the valley and analysed statistically to determine if soil properties varied significantly between geomorphic features and stratigraphic layers. The results show that the depth‐averaged saturated hydraulic conductivity, K_s, of the soil varies significantly with landform: fan units have K_g values that are twice that of floodplains and colluvial toeslope deposits have K_s values four times higher than floodplains. Given the notorious variability of K_s values in space, the strong statistical separation of soil properties by landform, backed up by strong separation of soil particle size by landform, suggests a way forward in understanding the distribution of soil properties in valleys and their influence on catchment hydrology. Copyright © 2000 John Wiley & Sons, Ltd.     

Rainfall—runoff response,event-based runoff coefficients and hydrograph separation

Abstract

Event-based runoff coefficients can provide information on watershed response. They are useful for catchment comparison to understand how different landscapes “filter” rainfall into event-based runoff and to explain the observed differences with catchment characteristics and related runoff mechanisms. However, the big drawback of this important parameter is the lack of a standard hydrograph separation method preceding its calculation. Event-based runoff coefficients determined with four well-established separation methods, as well as a newly developed separation method, are compared and are shown to differ considerably. This signifies that runoff coefficients reported in the literature often convey less information than required to allow for catchment classification. The new separation technique (constant-k method) is based on the theory of linear storage. Its advantages are that it is theoretically based in determining the end point of an event and that it can also be applied to events with multiple peaks. Furthermore, it is shown that event-based runoff coefficients in combination with simple statistical models improve our understanding of rainfall—runoff response of catchments with sparse data.     

Testing the Universal Soil Loss Equation‐MB equation in plots in Central and South Italy

Planning soil conservation strategies requires predictive techniques at event scale because a large percentage of soil loss over a long‐time period is due to relatively few large storms. Considering runoff is expected to improve soil loss predictions and allows relation of the process‐oriented approach with the empirical one, furthermore, the effects of detachment and transport on soil erosion processes can be distinguished by a runoff component. In this paper, the empirical model USLE‐MB (USLE‐M based), including a rainfall‐runoff erosivity factor in which the event rainfall erosivity index EI₃₀ of the Universal Soil Loss Equation (USLE) multiplies the runoff coefficient Q_R raised to an exponent b₁ > 1 is tested by the measurements carried out for the Masse (10 plots) and Sparacia (22 plots) experimental stations in Italy. For the Masse experimental station, an exponent b₁ > 1 was also estimated by tests carried out by a nozzle‐type rainfall simulator. For each experimental site in fallow conditions, the effect of the sample size of the plot soil loss measurements on the estimate of the b₁ coefficient was also studied by the extraction of a fixed number N of randomly obtained pairs of the normalized soil loss and runoff coefficient. The analysis showed that the variability of b₁ with N is low and that 350 pairs are sufficient to obtain a stable estimate of b₁. A total of 1,262 soil loss data were used to parameterize the model both locally and considering the two sites simultaneously. The b₁ exponent varied between the two sites (1.298–1.520), but using a common exponent (1.386) was possible. Using a common b₁ exponent for the two experimental areas increases the practical interest for the model and allows the estimation of a baseline component of the soil erodibility factor, which is representative of the at‐site soil intrinsic and quasi‐static properties. Development of a single USLE‐MB model appears possible, and sampling other sites is advisable to develop a single USLE‐MB model for general use.     

Comparing hydraulic properties of different forest floors

The forest floor plays an important role in runoff rate, soil erosion and soil infiltration capacity by protecting mineral soils from the direct impact of falling raindrops. Forest floor consists of different kinds of litter with different hydraulic properties. In this study, the inverse method was used to estimate the hydraulic properties of three kinds of forest floor (broad‐leaved, needle‐leaved and mixed‐stand) at three replications in a completely random design. Forest floor samples were collected from the Gilan Province, Iran. The samples were piled up to make long columns 40.88 cm high with an inner diameter of 18.1 cm. Artificial rainfall experiments were conducted on top of the columns, and free drainage from the bottom of the columns was measured in the laboratory. Saturated hydraulic conductivity (K_s), saturated water content and water retention curve parameters (van Genuchten equation) were estimated by the inverse method. The results showed that the K_s of needle‐leaved samples differed significantly (p < 0.05) from those of broad‐leaved and mixed‐stand samples, whereas the latter two did not differ in this regard. No significant differences emerged in the water retention function parameters of van Genuchten (θ_r, β and α) in the three forest floor samples. The saturated water content of mixed‐stand samples was significantly different (p < 0.05) from that of broad‐leaved and needle‐leaved treatments with the latter two samples showing no significant difference. The good agreement between simulated and observed free drainage for all forest floor samples in the validation period indicates that the estimated hydraulic properties efficiently characterize the unsaturated water flow in the forest floor. Copyright © 2013 John Wiley & Sons, Ltd.     

How to construct recursive digital filters for baseflow separation

Recursive digital filtering of hydrographs is a baseflow separation method that can easily be automated and has been recommended for providing reproducible results. In the past, different formulations of the most simple filter type, the so‐called one‐parameter filter, have been proposed. In this paper, a theoretical framework is developed for filter algorithms that were constructed under the assumption that the outflow from an aquifer is linearly proportional to its storage. It is shown that these one‐parameter filters describing an exponential baseflow recession are all special cases of a two‐parameter filter whose equation is specified. Its parameters are the recession constant—which can be objectively determined by a recession analysis—and BFI_max, the maximum value of the baseflow index that can be modelled by the algorithm. This introduces a subjective element into the baseflow calculation, since BFI_max is not measurable. A preliminary analysis based on the results of conventional separation techniques shows that it might be possible to find typical BFI_max values for classes of catchments that can be unequivocally distinguished by their hydrological and hydrogeological characteristics. Copyright © 2004 John Wiley & Sons, Ltd.     

In situ measurements of soil saturated hydraulic conductivity: Assessment of reliability through rainfall–runoff experiments

The saturated hydraulic conductivity, K_s, is a soil property that has a key role in the partitioning of rainfall into surface runoff and infiltration. The commonly used instruments and methods for in situ measurements of K_s have frequently provided conflicting results. Comparison of K_s estimates obtained by three classical devices—namely, the double ring infiltrometer (DRI), the Guelph version of the constant‐head well permeameter (GUELPH‐CHP) and the CSIRO version of the tension permeameter (CSIRO‐TP) is presented. A distinguishing feature in this study is the use of steady deep flow rates, obtained from controlled rainfall–runoff experiments, as benchmark values of K_s at local and field‐plot scales, thereby enabling an assessment of these methods in reliably reproducing repeatable values and in their capability of determining plot‐scale variation of K_s. We find that the DRI grossly overestimates K_s, the GUELPH‐CHP gives conflicting estimates of K_s with substantial overestimation in laboratory experiments and underestimation at the plot scale, whereas the CSIRO‐TP yields average K_s values with significant errors of 24% in the plot scale experiment and 66% in laboratory experiments. Although the DRI would likely yield a better estimate of the nature of variability than the GUELPH‐CHP and CSIRO‐TP, a separate calibration may be warranted to correct for the overestimation of K_s values. The reasons for such discrepancies within and between the measurement methods are not yet fully understood and serve as motivation for future work to better characterize the uncertainty associated with individual measurements of K_s using these methods and the characterization of field scale variability from multiple local measurements.     

Impact of forest degradation on streamflow regime and runoff response to rainfall in the Garhwal Himalaya,Northwest India

Baseflows have declined for decades in the Lesser Himalaya but the causes are still debated. This paper compares variations in streamflow response over three years for two similar headwater catchments in northwest India with largely undisturbed (Arnigad) and highly degraded (Bansigad) oak forest. Hydrograph analysis suggested no catchment leakage, thereby allowing meaningful comparisons. The mean annual runoff coefficient for Arnigad was 54% (range 44–61%) against 62% (53–69%) at Bansigad. Despite greater total runoff Q_t (by 250 mm year^–1), baseflow at Bansigad ceased by March, but was perennial at Arnigad (making up 90% of Q_t vs. 51% at Bansigad). Arnigad storm flows, Q_s, were modest (8–11% of Q_t) and occurred mostly during monsoons (78–98%), while Q_s at Bansigad was 49% of Q_t and occurred also during post-monsoon seasons. Our results underscore the importance of maintaining soil water retention capacity after forest removal to maintain baseflow levels.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR D. Gerten     

Predicting physical equations of soil detachment by simulated concentrated flow in Ultisols (subtropical China)

Soil detachment in concentrated flow is due to the dislodging of soil particles from the soil matrix by surface runoff. Both aggregate stability and shear strength of the topsoil reflect the erosion resistance of soil to concentrated runoff, and are important input parameters in predicting soil detachment models. This study was conducted to develop a formula to predict soil detachment rate in concentrated flow by using the aggregate stability index (As), root density (R_d) and saturated soil strength (σ_s) in the subtropical Ultisols region of China. The detachment rates of undisturbed topsoil samples collected from eight cultivated soil plots were measured in a 3.8 m long, 0.2 m wide hydraulic flume under five different flow shear stresses (τ = 4.54, 9.38, 15.01, 17.49 and 22.54 Pa). The results indicated that the stability index (As) was well related with soil detachment rate, particularly for results obtained with high flow shear stress (22.54 Pa), and the stability index (As) has a good linear relationship with concentrated flow erodibility factors (K_c). There was a positive linear relationship between saturated soil strength (σ_s) and critical flow shear stress (τ_c) for different soils. A significant negative exponential relationship between erodibility factors (K_c) and root density (R_d) was detected. This study yielded two prediction equations that allowed comparison of their efficiency in assessing soil detachment rate in concentrated flow. The equation including the root density (R_d) may have a better correlation coefficient (R² = 0.95). It was concluded that the formula based on the stability index (As), saturated soil strength (σ_s) and root density (R_d) has the potential to improve methodology for assessing soil detachment rate in concentrated flow for the subtropical Chinese Ultisols. Copyright © 2012 John Wiley & Sons, Ltd.     

Persistence of road runoff generation in a logged catchment in Peninsular Malaysia

Measurements of saturated hydraulic conductivity (K_s) and diagnostic model simulations show that all types of logging road/trail in the 14·4 ha Bukit Tarek Experimental Catchment 3 (BTEC3) generate substantial Horton overland flow (HOF) during most storms, regardless of design and level of trafficking. Near‐surface K_s(0–0·05 m) on the main logging road, skid trails and newly constructed logging terraces was less than 1, 2 and 34 mm h^?1, respectively. Near‐surface K_s on an abandoned skid trail in an adjacent basin was higher (62 mm h^?1), owing to the development of a thin organic‐rich layer on the running surface over the past 40 years. Saturated hydraulic conductivity measured at 0·25 m below the surface of all roads was not different (all <6 mm h^?1) and corresponded to the K_s of the adjacent hillslope subsoil, as most roads were excavated into the regolith more than 0·5–1 m. After 40 years, only limited recovery in near‐surface K_s occurred on the abandoned skid trail. This road generated HOF after the storage capacity of the upper near‐surface layer was exceeded during events larger than about 20 mm. Thus, excavation into low‐K_s substrate had a greater influence on the persistence of surface runoff production than did surface compaction by machinery during construction and subsequent use during logging operations. Overland flow on BTEC3 roads was also augmented by the interception of shallow subsurface flow traveling along the soil–saprolite/bedrock interface and return flow emerging from the cutbank through shallow biogenic pipes. The most feasible strategy for reducing long‐term road‐related impacts in BTEC3 is limiting the depth of excavation and designing a more efficient road network, including minimizing the length and connectivity of roads and skid trails. Copyright © 2007 John Wiley & Sons, Ltd.     

Sensitivity of soil parameters in unsaturated zone modelling and the relation between effective,laboratory and in situ estimates

Simulation of soil moisture content requires effective soil hydraulic parameters that are valid at the modelling scale. This study investigates how these parameters can be estimated by inverse modelling using soil moisture measurements at 25 locations at three different depths (at the surface, at 30 and 60 cm depth) on an 80 by 20 m hillslope. The study presents two global sensitivity analyses to investigate the sensitivity in simulated soil moisture content of the different hydraulic parameters used in a one‐dimensional unsaturated zone model based on Richards' equation. For estimation of the effective parameters the shuffled complex evolution algorithm is applied. These estimated parameters are compared to their measured laboratory and in situ equivalents. Soil hydraulic functions were estimated in the laboratory on 100 cm³ undisturbed soil cores collected at 115 locations situated in two horizons in three profile pits along the hillslope. Furthermore, in situ field saturated hydraulic conductivity was estimated at 120 locations using single‐ring pressure infiltrometer measurements. The sensitivity analysis of 13 soil physical parameters (saturated hydraulic conductivity (K_s), saturated moisture content (θ_s), residual moisture content (θ_r), inverse of the air‐entry value (α), van Genuchten shape parameter (n), Averjanov shape parameter (N) for both horizons, and depth (d) from surface to B horizon) in a two‐layer single column model showed that the parameter N is the least sensitive parameter. K_s of both horizons, θ_s of the A horizon and d were found to be the most sensitive parameters. Distributions over all locations of the effective parameters and the distributions of the estimated soil physical parameters from the undisturbed soil samples and the single‐ring pressure infiltrometer estimates were found significantly different at a 5% level for all parameters except for α of the A horizon and K_s and θ_s of the B horizon. Different reasons are discussed to explain these large differences. Copyright © 2004 John Wiley & Sons, Ltd.