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An overview presenting some of our activities related to; 1.Hydrology in small agricultural catchments; pathways and their impact on nutrient and soil loss. 2.Water sampling 3.Winter and climate change 4.Other issues
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Analysis on runoff from agricultural dominated catchment Effects of subsurface drainage systems on hydrology/runoff and nutrient loss The effect of time resolution on the hydrological characters The effect of scale on hydrological characters.
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Location of catchments Catchment are located in Norway (Mørdre, Skuterud, Høgfoss, Lena), Estonia (Rägina, Räpu) and Latvia (Mellupite) All catchments except Høgfoss and Lena are part of National Agricultural Environmental Monitoring Programmes. Quantifying runoff, nutrient and soil loss
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Catchment monitoring calculation of load Discharge measurement using Crump weir, V- notch Water sampling and analysis(TDS, N tot, P tot ) runoff(mm) N,P,SS loss (kg.ha -1 )
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Flat V – weir (modifisert Crump)
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Construction on crest Crump weir
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Skuterud, oppstuvning?
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Skuterud backwater
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Winter, what now
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Heating of station
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Flumes http://www.uwsp.edu/cnr/watersheds/GradStudents/Freihoefer.htm http://info1.ma.slu.se/IM/images/RW1.jpg H flume
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tipping bucket as discharge measurement4 structure
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Point samples strategies. In general, point sampling routines can be divided into three categories, i.e. –point sampling with variable time intervall –point sampling with fixed time intervall –volume proportional point sampling.
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Different ways to calculate load when grab sampling Load(T) = conc(c) x volume in period (V))
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Composite volume proportional sampling An alternative to point sampling systems is volume proportional water samples. In this case a small water sample is taken each time a preset volume of water has passed the monitoring station. The sub-samples are collected and stored into one container for subsequent analysis. This composite sample then represents the average concentration of the runoff water over the sampling period. A prerequisite is the availability of a head-discharge relation for the location of the measurement station + datalogger
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Vannprøvetaking/stofftap
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in which Ltotal load during sample period C concentration in composite sample for time period t=1 to t=n qt hourly discharge at time t n number of hours represented by the composite sample period Volume proportional sampling
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Vannprøvetaking/stofftap Sampling systems might be combined so as best to suit its purpose. It is assumed that the chemical concentration of runoff water during low flow periods in a way can be considered constant as long as agricultural runoff is concerned. For low flow periods, a point sampling system with fixed time interval can be implemented, combined with a flow proportional point sampling system for high flow periods.
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Vannprøvetaking/stofftap Short-term variability in NO3-N concentrations in Høyjord October 6-9, 1995
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Vannprøvetaking/stofftap Phosphorus dynamics in a typical small agricultural stream (Timebekken, 1.1 km2)
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Characteristics
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Runoff and nutrient loss
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Characteristic for runoff generation is strong seasonality in runoff Catchment Winter Dec - Feb Spring Mar - Apr Summer May - Aug Autumn Sept - Nov Høgfoss0.300.250.170.28 Skuterud,0.280.270.130.33 Räpu (Est.)0.350.360.15 Rägina (Est.)0.320.310.160.21 Mellupite catchment (Lat.)0.490.240.070.21 Mørdre0.230.350.160.26 Skuterud,0.280.270.130.33 Kolstad0.100.410.230.25 During growing season very little runoff
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Yearly runoff and nutrient loss is generated in only limited number of days runoffSSTPTN %days 5026121623 901186680106 100365 An example for the Skuterud catchment, Norway (4.5 km 2 )
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Runoff and nutrient loss in a large catchment runoffTNTP %days 5038 24 90174166132 100365 Lena catchment (181 km 2 ) runoffTPTN %days 50261623 9011880106 100365 Skuterud catchment
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Characteristic for many catchments is the large in-day variation in discharge
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Flow characteristics of catchments 1 – specific discharge (l s -1 ha -1 ); In small Norwegian catchments, yearly discharge shows a high variation, is extremely outlier prone. Specific discharge, calculated on average daily and hourly discharge values respectively for Skuterud(4.5 km^2) and Høgfoss(300 km^2) spec. disch 1 coeff. var. catchmentdayhrdayhr Skuterud2.95.7209239 Mørdre1.72.8222245 Kolstad1.42.4182195 spec. disch 1 coeff. var. catchmentdayhrdayhr Skuterud2.95.7209239 Mørdre1.72.8222245 Kolstad1.42.4182195 Høgfoss1.31.5123125 Lena1.31.5120123 This is much less pronounced in the large catchments spec. disch 1 coeff. var. catchmentdayhrdayhr Räpu0.60.7133135 Rägina0.40.5121122 Mellupite11.2182188 Skuterud2.95.7209239 Mørdre1.72.8222245 Kolstad1.42.4182195 Høgfoss1.31.5123125 Lena1.31.5120123 Latvian and Estonian catchments show less variation
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Winter runoff (Øygarden, 2000) January 30 Runoff: 25 mm Soil loss: 2 kg ha - 1 January 31 Runoff: 77 mm Soil loss: 3 050 kg ha -1 Winter/snowmelt
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Runoff generation caused by freeze/thaw cycles in combination with snowmelt/precipitation
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Variation in discharge can be expressed through a flashiness index, showing the rate of change day; hour (in- day variation); Which factors influence runoff generation?
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Runoff generation, scale and subsurface drainage Subs dr. 1.The size of the catchment is important and share of agr. land. 2.Subsurface drainage systems seem to have a significant influence on runoff generation
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The effects of subsurface drainage and nutrient – and soil loss Vandsemb, 1992 - 2004surfacesubsurface. N-loss (kg/ha) 222 P-loss (kg/ha) 0.60.5 SS(kg/ha) 47090 Runoff (mm) 126202 Bye, 1994 - 2007surfacesubsurface N-loss (kg/ha) 1.129 P-loss (kg/ha) 0.30.04 SS(kg/ha) 22020 Runoff (mm) 14165 groundwater level drain Drain spacing, L = 8 – 10 m Drain depth, d = 0.8 – 1.0 m bss.
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Soil types important Macropore/preferential flow Fast transport to subsurface drainage systems Transporting soil particles/phosphorus? Skuterud, 1994 - 2006 N_loss (kg/ha)45 P_loss (kg/ha)2 SS(kg/ha)1190 Avrenning (mm)504
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Base flow index Has been calculated using the smooth minima technique (Gustard et al, 1992) Input average daily discharge values No programs available to calculate on hourly discharge values Digital filter is looked at (Chapman, Eckhard). Q t – total runoff Q d – direct runoff
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Flashiness and base flow index
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Some conclusions and challenge Norwegian small agricultural catchments show higher variation in discharge compared to those in Estonian and Latvia Factors playing a role seem to be –Subsurface drainage systems –The size of catchment –Share of the agricultural land Time resolution seems to play an important role, small catchment -> high resolution data important Challenge to calculate baseflow on hourly values Only when we have models which simulate the dominating flow generating processes and there affect on nutrient and soil loss under our prevailing climatic conditions we can be successful in implementing the WFD
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Do we have models to deal with those situations Several models are testet in a Norwegian catchment SWAT (water balance, nutrient and soil loss) –The SWAT model has also been applied in Norway as part of EuroHarp and Striver, two EU – projects (large scale) –The model is tested now in Skuterud DRAINMOD, developed at NCSU (Skaggs) simulating subsurface drainage/surface runoff/nitrogen dynamics HBV – model (hydrology) INCA – model (hydrology, nutrient dynamics) SOIL/SOIL_NO and COUP (hydrology,nitrogen); have been tested (developed by SLU) WEPP (Water erosion prediction model) tested on small plots
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IS ice too cold for non – Scandinavian models Johannes Deelstra and Sigrun H. Kværnø Based partly on a presentation we had focussing on the winter season and nutrient and soil loss during that period, results of EuroHarp project (EU)
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What is so special with a winter The winter is the coldest season of the year and for most meteorological purposes is taken to include December, January, and February in the Northern Hemisphere. Air temperatures below 0 o C Precipitation as snow Water turns into ice Slippery roads, traffic problems, accidents
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Characteristics of Nordic winter Winter season - the time period between the first and last day with an average daily temperature below zero. Often characterised by several freeze/thaw cycles
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Infiltration and frozen soils, is there any, and how to measure Skuterud catchment 2001/2002 TDR equipment liquid water content Neutron scattering total water content
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Infiltration and frozen soils, is there any, and how to measure Skuterud catchment 2001/2002
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Infiltration and frozen soils, is there any and how to measure Infiltration tests in frozen soils, Vandsemb catchment (2002) Excavation in May 2002
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Infiltration and frozen soils, is there any and how to measure Infiltration tests in frozen soils, Vandsemb catchment (2002)
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Infiltration and frozen soils ―>latent heat of freezing Water, when freezing releases heat, latent heat of freezing. This know property is used in frost protection The effects of not including the latent heat of freezing in the simulation leads to errors in simulated frost depth.
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The effect of latent heat on soil frost development Season 2000 - 2001 Season 2002 - 2003
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The effect of snow on soil frost development Season 2002 - 2003 Season 2000 - 2001
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The effects of freeze/thaw cycles on aggregate stability Reduction: –Clay: 25 % after 6 cycles –Silt: 50 % after 1 cycle more frequent alterations between mild and cold periods can be expected to increase the erosion risk erosion risk is higher on silt than on clay
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The effects of freeze/thaw cycles on shear strength Reduction: 25 % after 6 cycles Erosion risk increases under unstable winter conditions Wet soils particularly vulnerable
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Freeze/thaw and runoff generation
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Freeze/thaw and runoff generation (Øygarden, 2000) January 30 Runoff: 25 mm Soil loss: 2 kg ha - 1 January 31 Runoff: 77 mm Soil loss: 3 050 kg ha -1
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Effect of freeze-thawing on P release from plants (M. Bechmann)
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Freezing period At one stage during the winter season a prolonged period starts with below – zero temperature But even freezing periods are characterised by several freeze/thaw periods
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Freezing period In cold regions, the freezing index is among others used to predict the depth of frost penetration The development of frozen soils is influenced by factors such soil moisture condition at the onset of freezing, snow cover, soil type and soil cover.
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Variation in freezing index Variation in freeze/thaw cycles
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Measurement results on runoff and nutrient losses from 4 small agricultural catchments in Lithuania, Finland, Sweden and Norway Johannes Deelstra, Sigrun H. Kværnø, Kirsti Granlund, Antanas Sigitas Sileika, Kazimieras Gaigalis, Antanas S. Sileika, Katarinana Kyllmar, Nils Vagstad
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Some results Nitrogen N loss occurs during the freezing period LöytäneenojaGraisupisSkuterudM36 N loss freez. per.4.9 (35 %)4.5 (33 %)8.7 (20 %)1.4 (5 %) N loss year13.913.545.325.6
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Some results Phosphorus loss during freezing period LöytäneenojaGraisupisSkuterudM36 P loss fr. period0.1 (20 %)0.1 (33 %)0.5 (20 %)0.01 (3 %) P loss year0.50.32.40.3
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Is ice then too cold? If not taken into account the right processes. Freez/thaw cycles – aggregate stability change usle, rusle, musle, wepp, eurosem, Infiltration Latent heat of freezing, Change over time in infiltration capacity Effects of snow (Coup, soil, shaw)
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Winter processes affect the hydrology in large areas of Europe!
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USLE – regression model, no winter USLENO – calibrated USLE to Norwegian climate RUSLE – revised USLE, K – factor adj. according to freeze/thaw cycles CREAMS – process based model; hydrology, erosion (ULSE factors) and chemistry (nutrients and pesticides) GLEAMS – improved winter hydrology ICECREAMS – modified CREAMS, Finnish version SWAT – winter hydrology, uses modified USLE (MUSLE) ERONOR – hydrology simulated by SOIL model, uses USLE based factors EUROSEM – process based model, no winter hydrology routine EROSION-3D – winter hydrology routine under development WEPP – winter hydrology routine (under review and testing)
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Takk for oppmerksomhet
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