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Flow-variation-paced sampling: a method for automatic sampling of streamflow during peak runoff periods
HYDROL 3940
Journal of Hydrology 229 (2000) 255–264 www.elsevier.com/locate/jhydrol
Flow-variation-paced sampling: a method for automatic sampling of streamflow during peak runoff periods E. Lopez a, B. Soto b,*, D. Rubinos b, F. Diaz-Fierros b a
Facultade de Ciencias, Departamento de Bioloxia Vexetal e Ciencia do Solo, Campus de Ourense, Universidade de Vigo, Ourense, Spain b Facultade de Farmacia, Departamento de Edafoloxia, Universidade de Santiago, 15706 Santiago, Spain Received 7 May 1999; received in revised form 16 December 1999; accepted 13 January 2000
Abstract Automated sampling of streamflow water in small watersheds is usually controlled by a flow-paced algorithm (i.e. sampling rate is proportional to discharge, l s ⫺1). However, this sampling method typically takes too few samples during runoff peaks (the critical periods for assessment of suspended solids losses) and too many samples during periods of basal or near-basal discharge (increasing the likelihood that there will be no sample bottles left when an important event occurs). We describe a sampling algorithm designed to overcome these problems: specifically, sampling rate is made proportional to the absolute rate of change in discharge (l s ⫺2). We call this approach “flow-variation-paced (FVP) sampling”, and have developed a simple device for its implementation. This device has proved reliable in field trials. Furthermore, simulated sampling studies using data from a small agricultural watershed in northwest Spain indicate that estimation of suspended solids losses on the basis of FVP sampling is considerably more accurate than estimation on the basis of conventional flow-paced sampling. 䉷 2000 Elsevier Science B.V. All rights reserved. Keywords: Automatic sampling; Stream discharge; Suspended solids
1. Introduction The monitoring of transport processes and changes in the physicochemical properties of natural waters evidently requires sampling. The design of the sampling programme typically requires a detailed knowledge of the transport characteristics of the watershed in question. Sampling requirements are generally higher for studies of suspended solids than for studies of dissolved components, since the former are more heavily dependent on the kinetic energy of the current, i.e. the flow rate. * Corresponding author. Tel.: ⫹34-81563100; fax: ⫹34-981594912. E-mail address: [email protected] (B. Soto).
Until recently, streamflow water sampling was an expensive activity requiring constant monitoring of flow rates. In many cases, it is not possible for the sampling personnel to reach the sampling station quickly enough during periods of peak flow (Walling and Webb, 1981). One solution to these problems is to use an integrating sampler, which diverts an approximately constant proportion of the flow to a collection container, which is checked at intervals. Another automated approach is to use multiple bottles, each of which collects for a fixed time interval (i.e. sampling rate is constant, and sample amount is proportional to discharge) (Maring, 1999). These procedures permit reasonably accurate estimation of total suspended solid losses over the sampling period, as the product of suspended solids
0022-1694/00/$ - see front matter 䉷 2000 Elsevier Science B.V. All rights reserved. PII: S0022-169 4(00)00160-8
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concentration in sample and total discharge volume during the sampling period. The chief disadvantage of this approach is that it does not permit analysis of the events occurring within the sampling period, so that the maximum loads reached are not known. This disadvantage is particularly relevant in the monitoring of contaminants with low toxicity thresholds (Gallart, 1992). Currently, the most widely used devices are automated samplers, in which the sample collector is controlled by a programmable microprocessor with memory. Such devices permit samples to be collected and distributed to a series of collecting bottles (generally 24). Sampling may be discrete or integrated, and may be at predetermined intervals, or controlled by signals (continuous signal proportional to the flow rate or a pulsed signal per unit volume) received from a flowmeter or other devices such as a turbidity sensor (Harsham, 1995; Evans et al., 1997). The conventional approach is flow-paced sampling, in which a sample is collected whenever total cumulative discharge exceeds a given interval (e.g. sample 1 after 5 l, sample 2 after 10 l, etc.). In order to deal effectively with both low-flow and flood periods, it is thus necessary to periodically adjust the interval used. Furthermore, this method has clear drawbacks when used in small watersheds with rapid runoff responses: specifically, too few samples are typically obtained during runoff peaks (the critical periods for assessment of suspended solids losses), while too many samples are obtained during periods of basal or near-basal discharge (increasing the likelihood that the sampler bottles will have been filled up when an important event occurs). In the present study we describe an alternative sampling system, in which a sample is collected whenever discharge rises or falls by a predetermined amount. Sampling rate is thus proportional to the absolute rate of variation in discharge. We describe a simple set-up for sampling in this way, and evaluate the efficiency of this approach and the conventional flow-paced approach for monitoring of suspended solids transport during flood events. 2. Materials and methods 2.1. Conventional flow-paced sampling Fixed-time-interval water sampling during floods
has evident drawbacks, and will not be considered further. Flow-paced sampling is basically similar in all automatic sampling devices currently available. Specifically, a flowmeter continuously determines velocity of flow (dimensions LT ⫺1), and transmits each determination to the controller unit, which calculates discharge (dimensions L 3T ⫺1), allowing estimation of cumulative discharge (dimensions L 3) since the last sample; a new sample is taken when cumulative discharge since the last sample exceeds a user-specified amount (Qstep). The system usually includes a float switch or other inhibitor so that cumulative discharge is incremented only when discharge exceeds a user-defined minimum (Qmin). The efficiency of this approach depends on both baseflow and hydrograph shape. Furthermore, Qmin will generally have to be adjusted seasonally (Evans et al., 1997). As a result, flow-paced sampling can be very efficient if the hydrological behaviour of the watershed is well known, and if baseflow at different times of year can be reliably predicted. When the hydrological behaviour of the watershed is not known in detail, however, or when there are rapid variations in baseflow, the selection of system-control parameters may prove difficult. Such problems are particularly acute in small watersheds, which have lower storage capacity and thus steeper recession limbs. 2.2. Flow-variation-paced (FVP) sampling In the system described in the present study, sampling rate is dependent not on the velocity of flow (as in flow-paced sampling) but on the rate of change in the velocity of flow. We thus use the term “FVP sampling”. In theory, this approach could be implemented using a microprocessor-based device to control sampling, on the basis of continuous calculation of the first derivative of the incoming velocity-of-flow data. Note that it would first be necessary to eliminate flowmeter background noise using a low-pass filter (compare Figs. 1 and 2), which requires enough data-storage capacity to maintain a sufficiently long data series. However, in most contexts it is clearly impractical to control sampling with a personal computer (whether on-site or remote), while currently available data-logging devices designed for field use
E. Lopez et al. / Journal of Hydrology 229 (2000) 255–264
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Fig. 1. Streamflow hydrograph for a peak-runoff event at the O Abelar agricultural research station (dashed line), with the corresponding first derivative plotted alongside (unbroken line).
are inadequate for this purpose, because of low datastorage capacity and because they cannot be programmed to perform calculations. We, therefore, developed a simple mechanical system for FVP sampling, as illustrated schematically
in Fig. 4. This system collects a sample whenever discharge (dimensions L 3T ⫺1, as indicated by stage) varies by a given amount (QVstep) with respect to discharge at the last sample. Note that a sample is collected regardless of whether the change in
Fig. 2. Streamflow hydrograph for the peak-runoff event of Fig. 1 (dashed line), showing the first derivative after smoothing with a low-pass filter algorithm (unbroken line).
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Fig. 3. Streamflow hydrograph for the peak-runoff event of Fig. 1 (unbroken line), showing cumulative discharge (l, long dashes) and absolute rate of variation in discharge (l s ⫺2).
discharge is positive or negative (see Fig. 3). The system comprises a float in a stilling well, suspended on a counter-weighted toothed float-line that passes over a pulley wheel. The pulley wheel attaches via a hub to a co-rotating opaque wheel with regularly spaced windows along its rim. The rim of this second wheel passes through an IR photocell (i.e. between the IR emitter and the detector), which transmits a pulse every time the beam is broken or unbroken. This pulse is fed to the automatic sampler; in the present study, we used a conventional automatic sampler, with pulses from the IR beam fed to the external signal input, and the sampler programmed to take a sample when a given number of pulses (2–6) had been received. One of the disadvantages of this system is that it is sensitive to turbulence and oscillations in water level. This problem can be overcome by fixing a piece of permeable fabric (in the present study, a standard absorbent kitchen cloth) over the lower end of the stilling well. The system has proved reliable in the field. With a 12 V DC supply, it requires 200 mA; however, it should be borne in mind that we used a commercially available photocell-plus-relay unit, and that power requirement could be reduced by eliminating the relay from the circuit.
2.3. Description of the study watershed We tested the system in the 10.2 ha watershed of the O Abelar agricultural research station (Abegondo, A Corun˜a, northwest Spain), of which about 70% is dedicated to pasture and about 30% to maize.
3. Results 3.1. Sampling timecourses of flow-paced versus FVP sampling The sampling timecourses obtained with the two systems were compared using data for a two-day period in November 1997, during which a high-runoff event occurred. Sampling was in both cases simulated, not real. For flow-paced sampling, Qmin was set at zero and Qstep at 50 m 3. For FVP sampling, QVstep was set at 0.005 l ⫺1 s 2. In each case, the value of the control parameter (Qstep or QVstep) was selected so as to obtain 24 samples well distributed over the test period. Given these parameters, the times at which samples were collected by each system are shown in Fig. 3. These results show that the FVP system is more selective than the flow-paced system, in that the
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Fig. 4. Diagrammatic representation of the system used for FVP sampling, showing (A) the stilled float turning a pulley wheel with windows, and (B) a cross-section of the pulley wheel, showing the IR photocell which sends a pulse to the sampler each time a window moves into or out of the IR beam.
former collected 18 samples during the two runoff peaks, while the latter collected only eight samples during these periods. In other words, during runoff peaks the FVP system took more than twice as many samples as the flow-paced system. In the watershed studied, between 60 and 80% of the total suspended solids lost in each runoff event are exported before streamflow reaches its peak for that event. Maximum suspended solids concentration is typically reached when streamflow is about 70% of the maximum (see Fig. 5). This is in accordance with the results of previous studies of small agricultural watersheds (Allen, 1981), and confirms the importance of increasing sampling frequency during periods of peak discharge, and particularly during the rising limb. Another advantage of the FVP system, concomitant with the increased sampling frequency during periods of peak discharge, is that sampling frequency is lower during periods of near-basal discharge, so that the
probability of the sampler filling its 24 bottles before an important runoff event occurs is reduced. This can again be illustrated with reference to the hydrograph shown in Fig. 3. During baseflow discharge, the conventional flow-paced system collected a sample every 3.5 h; in the absence of runoff events, 24 bottles would thus be filled in 3.5 days. To overcome this problem, most automatic samplers have a samplinginhibitor input, to which the operator can feed a signal from a float switch or other inhibitory device, thus defining a minimum discharge (Qmin) below which samples are not collected. If Qmin were set at 5 l s ⫺1, and Qstep maintained at 50 m 3, the first sample would be collected when discharge reached 10 l s ⫺1 (i.e. about 2/3 of the maximum discharge of the first peak), while the second sample would be collected close to the peak; thus only two samples would be taken during the rising limb (or three samples if the system were set to collect a sample at the onset of above-Qmin discharge). If Qstep were reduced to
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Fig. 5. Streamflow hydrograph for a peak-runoff event at the O Abelar agricultural research station (short dashes), showing the timecourse of suspended solids load obtained from real samples at given times (vertical continuous lines), and the interpolated suspended solids load data (hexagons and point-dashed line).
25 m 3 in order to counteract this problem, between 4 and 6 samples would be taken during the rising limb of the first peak; this is acceptable, but at the same time implies that the 24 sampling bottles would be filled only 15 h later. 3.2. Comparison of sampling efficiency with regard to suspended solids transport Sampling efficiency with regard to suspended solids transport was compared between the two methods on the basis of simulated sampling, using data for runoff, a runoff event that occurred in the study watershed on 23 and 24 November 1997. These data comprised a continuous record of discharge and suspended solids measurements in FVP samples obtained with our device. First, it was necessary to interpolate the suspended solids load curve between the FVP samples, since the times of FVP sampling did not correspond precisely to the times of simulated sampling. Interpolation was done with the algorithm of Fritch (1982), as performed by
the PCHIC and PCHFE subroutines of SLATEC mathematical software library. This algorithm determines the interpolated points from the piecewise cubic function of the array of observed data pairs (here time and measured suspended solids concentration). The resulting interpolated estimates are shown in Fig. 5. Once the suspended solids load curve had been obtained in this way, we simulated suspended solids sampling using the two algorithms (flow-paced and FVP), with the results shown in Fig. 6 (flow-paced) and Fig. 7 (FVP). As is clear from comparison of the two figures, FVP sampling predicted suspended solids contents much more accurately. To assess goodness-of-fit, we performed the same procedure with a total of seven events that had occurred in the study watershed (Table 1). Events 1–3 can be considered “short sharp” events, whereas events 4–7 can be considered relatively “smooth” events. The residual mass coefficients (RMC) indicate that total suspended solids loss during these events was over-estimated by up to 41% by the flow-paced
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Fig. 6. Suspended solids load-curve for a peak-runoff event at the O Abelar agricultural research station (dashed line). Bars show the estimates of solids losses that would be obtained by flow-paced sampling (the centre of each bar corresponds to a sampling event).
Fig. 7. Suspended solids load-curve for the peak-runoff event of Fig. 6 (dashed line). Bars show the estimates of solids losses that would be obtained by FVP sampling (the centre of each bar corresponds to a sampling event).
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Table 1 Goodness-of-fit statistics for prediction of suspended solids losses in each of the seven events, on the basis of flow-paced sampling and FVP sampling. ME, maximum error (kg); SE, sample efficiency; RMSE, root mean square error; RMC, residual mass coefficient e.n.
a
Flow-paced sampling n
1 2 3 4 5 6 7
b
23 19 18 15 12 11 8 a b
c
d
e
r
2
0.65 0.58 0.86 0.91 0.89 0.86 0.91
FVP sampling c
ME
SE
117 50 55 43 45 53 29
0.12 0.19 0.57 0.89 0.82 0.76 0.84
RMSE
d
0.19 0.32 0.113 0.089 0.129 0.15 0.135
RMC 0.37 0.41 0.19 0.12 0.16 0.19 0.10
e
r2
ME
SE c
RMSE d
RMC e
0.99 0.86 0.98 0.97 0.96 0.94 0.93
25 16 26 26 27 25 26
0.97 0.88 0.97 0.97 0.96 0.96 0.88
0.031 0.056 0.039 0.045 0.061 0.064 0.117
0.028 0.033 0.038 0.043 0.06 0.08 0.11
e.n. Event number. n Number of samples. Pn P 2 n1 x^i ⫺ xi 2 x ⫺ X SE 1 i Pn : 2 1 xi ⫺ X qP n 2 i x^i ⫺ xi : RMSE nX Pn Pn xi ⫺ 1 x^i RMC 1 P : n 1 xi
approach, but by no more than 11% by the FVP approach; furthermore, the flow-paced approach over-estimated much more severely than the FVP approach in all events except event seven (for which the over-estimates were 10 and 11%, respectively). Model efficiency (i.e. sample efficiency), SE, of the flow-paced approach ranged from 0.12 to 0.89, versus 0.88 to 0.97 for the FVP approach; sample efficiencies of less than 0.5 are generally considered to be inadequate. The root mean square error (RMSE) (indicating the likely dispersion of predicted values with respect to real values) likewise suggest that the estimates obtained with the flow-paced approach are worse than those obtained with the FVP approach. Taken together, these results confirm that the FVP algorithm is particularly effective for “sharp” events, which are inadequately sampled by the flow-paced algorithm. Fig. 8 shows suspended solids loads as inferred from samples obtained by FVP sampling during two runoff events, one lasting 5 h and the other 50 min. It can be seen that sampling density changes with the duration of the runoff peak, being markedly lower during the 5-h peak than during the 50min peak.
4. Conclusions In small watersheds with rapid runoff responses, conventional flow-paced automatic sampling of streamflow is often inadequate as a basis for estimation of suspended solids losses during peak-runoff periods. Typically, samples are taken with insufficient frequency during the period of interest (the runoff peak). Conversely, samples are taken with excessive frequency during unimportant periods (near-baseflow conditions), filling up the sampling bottles unnecessarily, and thus increasing the likelihood that an important event will be missed. In view of these problems, we have developed a more selective sampling approach, in which sampling rate is dependent not on discharge (as in flow-paced sampling) but on the rate of change in discharge. We describe a simple and reliable device for implementation of the sampling algorithm, and report the results of sampling simulations designed to compare the efficiency of the conventional approach (flow-paced sampling) and our approach (FVP sampling), using real discharge and suspended solids transport data from a small agricultural watershed in Northwest Spain. The results of these simulations clearly indicate
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Fig. 8. Performance of the FVP sampling device during two runoff events, one lasting 5 h (top) and the other 50 min (bottom). The dotted lines show suspended solids contents as determined in runoff samples taken by the sampling device. Vertical dotted lines indicate the time of each sample (the gap in the sampling series in the bottom plot was due to an autosampler failure.
that our FVP sampling approach is considerably more accurate as a basis for predicting suspended solids losses, particularly during “sharp-peak” runoff events.
Acknowledgements This work was financed by the European Union, through the project “Effective Land Management for Surface Runoff Control” (FAIR 1-CT95-0458).
References Allen, P.B. 1981. Measurement and prediction of erosion and sediment yield. USDA Agricultural Reviews and Manuals, Southern Series, vol. 15, pp. 1–23. Evans, J.G., Wass, P.D., Hodgson, P. 1997. Integrated continuous water quality monitoring for the LOIS river programme. The Science of the Total Environment, vol. 194–195, pp. 111–118. Fritch, F.N., 1982. Code for interpolation. Lawrence Livermore National Laboratory, Livermore, CA. Gallart, F., 1992. Medida de flujos de agua y sedimentos a escala de pequen˜a cuenca. Seminario Teorico-practico de Me´todos para el
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Estudio de Procesos de Erosion. Instituto Jaume Almera. CSIC. Barcelona. Harsham, K.D., 1995. Water Sampling for Pollution Regulation, Gordon and Breach, Luxembourg (205pp). Maring, K., 1999. New sampling routines with automatic waste-
water samplers. International Environmental Technology 9 (4), 20. Walling, D.E., Webb, B.W., 1981. The reliability of suspended sediment load data. Erosion and Sediment Transport Measurements. IAHS Publ. No. 133, pp. 177–194.
Journal of Hydrology 229 (2000) 255–264 www.elsevier.com/locate/jhydrol
Flow-variation-paced sampling: a method for automatic sampling of streamflow during peak runoff periods E. Lopez a, B. Soto b,*, D. Rubinos b, F. Diaz-Fierros b a
Facultade de Ciencias, Departamento de Bioloxia Vexetal e Ciencia do Solo, Campus de Ourense, Universidade de Vigo, Ourense, Spain b Facultade de Farmacia, Departamento de Edafoloxia, Universidade de Santiago, 15706 Santiago, Spain Received 7 May 1999; received in revised form 16 December 1999; accepted 13 January 2000
Abstract Automated sampling of streamflow water in small watersheds is usually controlled by a flow-paced algorithm (i.e. sampling rate is proportional to discharge, l s ⫺1). However, this sampling method typically takes too few samples during runoff peaks (the critical periods for assessment of suspended solids losses) and too many samples during periods of basal or near-basal discharge (increasing the likelihood that there will be no sample bottles left when an important event occurs). We describe a sampling algorithm designed to overcome these problems: specifically, sampling rate is made proportional to the absolute rate of change in discharge (l s ⫺2). We call this approach “flow-variation-paced (FVP) sampling”, and have developed a simple device for its implementation. This device has proved reliable in field trials. Furthermore, simulated sampling studies using data from a small agricultural watershed in northwest Spain indicate that estimation of suspended solids losses on the basis of FVP sampling is considerably more accurate than estimation on the basis of conventional flow-paced sampling. 䉷 2000 Elsevier Science B.V. All rights reserved. Keywords: Automatic sampling; Stream discharge; Suspended solids
1. Introduction The monitoring of transport processes and changes in the physicochemical properties of natural waters evidently requires sampling. The design of the sampling programme typically requires a detailed knowledge of the transport characteristics of the watershed in question. Sampling requirements are generally higher for studies of suspended solids than for studies of dissolved components, since the former are more heavily dependent on the kinetic energy of the current, i.e. the flow rate. * Corresponding author. Tel.: ⫹34-81563100; fax: ⫹34-981594912. E-mail address: [email protected] (B. Soto).
Until recently, streamflow water sampling was an expensive activity requiring constant monitoring of flow rates. In many cases, it is not possible for the sampling personnel to reach the sampling station quickly enough during periods of peak flow (Walling and Webb, 1981). One solution to these problems is to use an integrating sampler, which diverts an approximately constant proportion of the flow to a collection container, which is checked at intervals. Another automated approach is to use multiple bottles, each of which collects for a fixed time interval (i.e. sampling rate is constant, and sample amount is proportional to discharge) (Maring, 1999). These procedures permit reasonably accurate estimation of total suspended solid losses over the sampling period, as the product of suspended solids
0022-1694/00/$ - see front matter 䉷 2000 Elsevier Science B.V. All rights reserved. PII: S0022-169 4(00)00160-8
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concentration in sample and total discharge volume during the sampling period. The chief disadvantage of this approach is that it does not permit analysis of the events occurring within the sampling period, so that the maximum loads reached are not known. This disadvantage is particularly relevant in the monitoring of contaminants with low toxicity thresholds (Gallart, 1992). Currently, the most widely used devices are automated samplers, in which the sample collector is controlled by a programmable microprocessor with memory. Such devices permit samples to be collected and distributed to a series of collecting bottles (generally 24). Sampling may be discrete or integrated, and may be at predetermined intervals, or controlled by signals (continuous signal proportional to the flow rate or a pulsed signal per unit volume) received from a flowmeter or other devices such as a turbidity sensor (Harsham, 1995; Evans et al., 1997). The conventional approach is flow-paced sampling, in which a sample is collected whenever total cumulative discharge exceeds a given interval (e.g. sample 1 after 5 l, sample 2 after 10 l, etc.). In order to deal effectively with both low-flow and flood periods, it is thus necessary to periodically adjust the interval used. Furthermore, this method has clear drawbacks when used in small watersheds with rapid runoff responses: specifically, too few samples are typically obtained during runoff peaks (the critical periods for assessment of suspended solids losses), while too many samples are obtained during periods of basal or near-basal discharge (increasing the likelihood that the sampler bottles will have been filled up when an important event occurs). In the present study we describe an alternative sampling system, in which a sample is collected whenever discharge rises or falls by a predetermined amount. Sampling rate is thus proportional to the absolute rate of variation in discharge. We describe a simple set-up for sampling in this way, and evaluate the efficiency of this approach and the conventional flow-paced approach for monitoring of suspended solids transport during flood events. 2. Materials and methods 2.1. Conventional flow-paced sampling Fixed-time-interval water sampling during floods
has evident drawbacks, and will not be considered further. Flow-paced sampling is basically similar in all automatic sampling devices currently available. Specifically, a flowmeter continuously determines velocity of flow (dimensions LT ⫺1), and transmits each determination to the controller unit, which calculates discharge (dimensions L 3T ⫺1), allowing estimation of cumulative discharge (dimensions L 3) since the last sample; a new sample is taken when cumulative discharge since the last sample exceeds a user-specified amount (Qstep). The system usually includes a float switch or other inhibitor so that cumulative discharge is incremented only when discharge exceeds a user-defined minimum (Qmin). The efficiency of this approach depends on both baseflow and hydrograph shape. Furthermore, Qmin will generally have to be adjusted seasonally (Evans et al., 1997). As a result, flow-paced sampling can be very efficient if the hydrological behaviour of the watershed is well known, and if baseflow at different times of year can be reliably predicted. When the hydrological behaviour of the watershed is not known in detail, however, or when there are rapid variations in baseflow, the selection of system-control parameters may prove difficult. Such problems are particularly acute in small watersheds, which have lower storage capacity and thus steeper recession limbs. 2.2. Flow-variation-paced (FVP) sampling In the system described in the present study, sampling rate is dependent not on the velocity of flow (as in flow-paced sampling) but on the rate of change in the velocity of flow. We thus use the term “FVP sampling”. In theory, this approach could be implemented using a microprocessor-based device to control sampling, on the basis of continuous calculation of the first derivative of the incoming velocity-of-flow data. Note that it would first be necessary to eliminate flowmeter background noise using a low-pass filter (compare Figs. 1 and 2), which requires enough data-storage capacity to maintain a sufficiently long data series. However, in most contexts it is clearly impractical to control sampling with a personal computer (whether on-site or remote), while currently available data-logging devices designed for field use
E. Lopez et al. / Journal of Hydrology 229 (2000) 255–264
257
Fig. 1. Streamflow hydrograph for a peak-runoff event at the O Abelar agricultural research station (dashed line), with the corresponding first derivative plotted alongside (unbroken line).
are inadequate for this purpose, because of low datastorage capacity and because they cannot be programmed to perform calculations. We, therefore, developed a simple mechanical system for FVP sampling, as illustrated schematically
in Fig. 4. This system collects a sample whenever discharge (dimensions L 3T ⫺1, as indicated by stage) varies by a given amount (QVstep) with respect to discharge at the last sample. Note that a sample is collected regardless of whether the change in
Fig. 2. Streamflow hydrograph for the peak-runoff event of Fig. 1 (dashed line), showing the first derivative after smoothing with a low-pass filter algorithm (unbroken line).
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Fig. 3. Streamflow hydrograph for the peak-runoff event of Fig. 1 (unbroken line), showing cumulative discharge (l, long dashes) and absolute rate of variation in discharge (l s ⫺2).
discharge is positive or negative (see Fig. 3). The system comprises a float in a stilling well, suspended on a counter-weighted toothed float-line that passes over a pulley wheel. The pulley wheel attaches via a hub to a co-rotating opaque wheel with regularly spaced windows along its rim. The rim of this second wheel passes through an IR photocell (i.e. between the IR emitter and the detector), which transmits a pulse every time the beam is broken or unbroken. This pulse is fed to the automatic sampler; in the present study, we used a conventional automatic sampler, with pulses from the IR beam fed to the external signal input, and the sampler programmed to take a sample when a given number of pulses (2–6) had been received. One of the disadvantages of this system is that it is sensitive to turbulence and oscillations in water level. This problem can be overcome by fixing a piece of permeable fabric (in the present study, a standard absorbent kitchen cloth) over the lower end of the stilling well. The system has proved reliable in the field. With a 12 V DC supply, it requires 200 mA; however, it should be borne in mind that we used a commercially available photocell-plus-relay unit, and that power requirement could be reduced by eliminating the relay from the circuit.
2.3. Description of the study watershed We tested the system in the 10.2 ha watershed of the O Abelar agricultural research station (Abegondo, A Corun˜a, northwest Spain), of which about 70% is dedicated to pasture and about 30% to maize.
3. Results 3.1. Sampling timecourses of flow-paced versus FVP sampling The sampling timecourses obtained with the two systems were compared using data for a two-day period in November 1997, during which a high-runoff event occurred. Sampling was in both cases simulated, not real. For flow-paced sampling, Qmin was set at zero and Qstep at 50 m 3. For FVP sampling, QVstep was set at 0.005 l ⫺1 s 2. In each case, the value of the control parameter (Qstep or QVstep) was selected so as to obtain 24 samples well distributed over the test period. Given these parameters, the times at which samples were collected by each system are shown in Fig. 3. These results show that the FVP system is more selective than the flow-paced system, in that the
E. Lopez et al. / Journal of Hydrology 229 (2000) 255–264
259
Fig. 4. Diagrammatic representation of the system used for FVP sampling, showing (A) the stilled float turning a pulley wheel with windows, and (B) a cross-section of the pulley wheel, showing the IR photocell which sends a pulse to the sampler each time a window moves into or out of the IR beam.
former collected 18 samples during the two runoff peaks, while the latter collected only eight samples during these periods. In other words, during runoff peaks the FVP system took more than twice as many samples as the flow-paced system. In the watershed studied, between 60 and 80% of the total suspended solids lost in each runoff event are exported before streamflow reaches its peak for that event. Maximum suspended solids concentration is typically reached when streamflow is about 70% of the maximum (see Fig. 5). This is in accordance with the results of previous studies of small agricultural watersheds (Allen, 1981), and confirms the importance of increasing sampling frequency during periods of peak discharge, and particularly during the rising limb. Another advantage of the FVP system, concomitant with the increased sampling frequency during periods of peak discharge, is that sampling frequency is lower during periods of near-basal discharge, so that the
probability of the sampler filling its 24 bottles before an important runoff event occurs is reduced. This can again be illustrated with reference to the hydrograph shown in Fig. 3. During baseflow discharge, the conventional flow-paced system collected a sample every 3.5 h; in the absence of runoff events, 24 bottles would thus be filled in 3.5 days. To overcome this problem, most automatic samplers have a samplinginhibitor input, to which the operator can feed a signal from a float switch or other inhibitory device, thus defining a minimum discharge (Qmin) below which samples are not collected. If Qmin were set at 5 l s ⫺1, and Qstep maintained at 50 m 3, the first sample would be collected when discharge reached 10 l s ⫺1 (i.e. about 2/3 of the maximum discharge of the first peak), while the second sample would be collected close to the peak; thus only two samples would be taken during the rising limb (or three samples if the system were set to collect a sample at the onset of above-Qmin discharge). If Qstep were reduced to
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Fig. 5. Streamflow hydrograph for a peak-runoff event at the O Abelar agricultural research station (short dashes), showing the timecourse of suspended solids load obtained from real samples at given times (vertical continuous lines), and the interpolated suspended solids load data (hexagons and point-dashed line).
25 m 3 in order to counteract this problem, between 4 and 6 samples would be taken during the rising limb of the first peak; this is acceptable, but at the same time implies that the 24 sampling bottles would be filled only 15 h later. 3.2. Comparison of sampling efficiency with regard to suspended solids transport Sampling efficiency with regard to suspended solids transport was compared between the two methods on the basis of simulated sampling, using data for runoff, a runoff event that occurred in the study watershed on 23 and 24 November 1997. These data comprised a continuous record of discharge and suspended solids measurements in FVP samples obtained with our device. First, it was necessary to interpolate the suspended solids load curve between the FVP samples, since the times of FVP sampling did not correspond precisely to the times of simulated sampling. Interpolation was done with the algorithm of Fritch (1982), as performed by
the PCHIC and PCHFE subroutines of SLATEC mathematical software library. This algorithm determines the interpolated points from the piecewise cubic function of the array of observed data pairs (here time and measured suspended solids concentration). The resulting interpolated estimates are shown in Fig. 5. Once the suspended solids load curve had been obtained in this way, we simulated suspended solids sampling using the two algorithms (flow-paced and FVP), with the results shown in Fig. 6 (flow-paced) and Fig. 7 (FVP). As is clear from comparison of the two figures, FVP sampling predicted suspended solids contents much more accurately. To assess goodness-of-fit, we performed the same procedure with a total of seven events that had occurred in the study watershed (Table 1). Events 1–3 can be considered “short sharp” events, whereas events 4–7 can be considered relatively “smooth” events. The residual mass coefficients (RMC) indicate that total suspended solids loss during these events was over-estimated by up to 41% by the flow-paced
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Fig. 6. Suspended solids load-curve for a peak-runoff event at the O Abelar agricultural research station (dashed line). Bars show the estimates of solids losses that would be obtained by flow-paced sampling (the centre of each bar corresponds to a sampling event).
Fig. 7. Suspended solids load-curve for the peak-runoff event of Fig. 6 (dashed line). Bars show the estimates of solids losses that would be obtained by FVP sampling (the centre of each bar corresponds to a sampling event).
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Table 1 Goodness-of-fit statistics for prediction of suspended solids losses in each of the seven events, on the basis of flow-paced sampling and FVP sampling. ME, maximum error (kg); SE, sample efficiency; RMSE, root mean square error; RMC, residual mass coefficient e.n.
a
Flow-paced sampling n
1 2 3 4 5 6 7
b
23 19 18 15 12 11 8 a b
c
d
e
r
2
0.65 0.58 0.86 0.91 0.89 0.86 0.91
FVP sampling c
ME
SE
117 50 55 43 45 53 29
0.12 0.19 0.57 0.89 0.82 0.76 0.84
RMSE
d
0.19 0.32 0.113 0.089 0.129 0.15 0.135
RMC 0.37 0.41 0.19 0.12 0.16 0.19 0.10
e
r2
ME
SE c
RMSE d
RMC e
0.99 0.86 0.98 0.97 0.96 0.94 0.93
25 16 26 26 27 25 26
0.97 0.88 0.97 0.97 0.96 0.96 0.88
0.031 0.056 0.039 0.045 0.061 0.064 0.117
0.028 0.033 0.038 0.043 0.06 0.08 0.11
e.n. Event number. n Number of samples. Pn P 2 n1 x^i ⫺ xi 2 x ⫺ X SE 1 i Pn : 2 1 xi ⫺ X qP n 2 i x^i ⫺ xi : RMSE nX Pn Pn xi ⫺ 1 x^i RMC 1 P : n 1 xi
approach, but by no more than 11% by the FVP approach; furthermore, the flow-paced approach over-estimated much more severely than the FVP approach in all events except event seven (for which the over-estimates were 10 and 11%, respectively). Model efficiency (i.e. sample efficiency), SE, of the flow-paced approach ranged from 0.12 to 0.89, versus 0.88 to 0.97 for the FVP approach; sample efficiencies of less than 0.5 are generally considered to be inadequate. The root mean square error (RMSE) (indicating the likely dispersion of predicted values with respect to real values) likewise suggest that the estimates obtained with the flow-paced approach are worse than those obtained with the FVP approach. Taken together, these results confirm that the FVP algorithm is particularly effective for “sharp” events, which are inadequately sampled by the flow-paced algorithm. Fig. 8 shows suspended solids loads as inferred from samples obtained by FVP sampling during two runoff events, one lasting 5 h and the other 50 min. It can be seen that sampling density changes with the duration of the runoff peak, being markedly lower during the 5-h peak than during the 50min peak.
4. Conclusions In small watersheds with rapid runoff responses, conventional flow-paced automatic sampling of streamflow is often inadequate as a basis for estimation of suspended solids losses during peak-runoff periods. Typically, samples are taken with insufficient frequency during the period of interest (the runoff peak). Conversely, samples are taken with excessive frequency during unimportant periods (near-baseflow conditions), filling up the sampling bottles unnecessarily, and thus increasing the likelihood that an important event will be missed. In view of these problems, we have developed a more selective sampling approach, in which sampling rate is dependent not on discharge (as in flow-paced sampling) but on the rate of change in discharge. We describe a simple and reliable device for implementation of the sampling algorithm, and report the results of sampling simulations designed to compare the efficiency of the conventional approach (flow-paced sampling) and our approach (FVP sampling), using real discharge and suspended solids transport data from a small agricultural watershed in Northwest Spain. The results of these simulations clearly indicate
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Fig. 8. Performance of the FVP sampling device during two runoff events, one lasting 5 h (top) and the other 50 min (bottom). The dotted lines show suspended solids contents as determined in runoff samples taken by the sampling device. Vertical dotted lines indicate the time of each sample (the gap in the sampling series in the bottom plot was due to an autosampler failure.
that our FVP sampling approach is considerably more accurate as a basis for predicting suspended solids losses, particularly during “sharp-peak” runoff events.
Acknowledgements This work was financed by the European Union, through the project “Effective Land Management for Surface Runoff Control” (FAIR 1-CT95-0458).
References Allen, P.B. 1981. Measurement and prediction of erosion and sediment yield. USDA Agricultural Reviews and Manuals, Southern Series, vol. 15, pp. 1–23. Evans, J.G., Wass, P.D., Hodgson, P. 1997. Integrated continuous water quality monitoring for the LOIS river programme. The Science of the Total Environment, vol. 194–195, pp. 111–118. Fritch, F.N., 1982. Code for interpolation. Lawrence Livermore National Laboratory, Livermore, CA. Gallart, F., 1992. Medida de flujos de agua y sedimentos a escala de pequen˜a cuenca. Seminario Teorico-practico de Me´todos para el
264
E. Lopez et al. / Journal of Hydrology 229 (2000) 255–264
Estudio de Procesos de Erosion. Instituto Jaume Almera. CSIC. Barcelona. Harsham, K.D., 1995. Water Sampling for Pollution Regulation, Gordon and Breach, Luxembourg (205pp). Maring, K., 1999. New sampling routines with automatic waste-
water samplers. International Environmental Technology 9 (4), 20. Walling, D.E., Webb, B.W., 1981. The reliability of suspended sediment load data. Erosion and Sediment Transport Measurements. IAHS Publ. No. 133, pp. 177–194.