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

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.

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

Catchment monitoring calculation of load

Discharge measurement using Crump weir, V-notch

Water sampling and analysis(TDS, Ntot, Ptot)

runoff(mm)

N,P,SS loss (kg.ha-1)

Flat V – weir (modifisert Crump)

Construction on crest Crump weir

Skuterud, oppstuvning?

Skuterud backwater

Winter, what now

Heating of station

Flumeshttp://www.uwsp.edu/cnr/watersheds/GradStudents/Freihoefer.htm

http://info1.ma.slu.se/IM/images/RW1.jpg

H flume

tipping bucket as discharge measurement4 structure

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.

Different ways to calculate load when grab sampling

Load(T) = conc(c) x volume in period (V))

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

Vannprøvetaking/stofftap

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• 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.

Vannprøvetaking/stofftap

Short-term variability in NO3-N concentrations in Høyjord October 6-9, 1995

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Phosphorus dynamics in a typical small agricultural stream (Timebekken, 1.1 km2)

Characteristics

Runoff and nutrient loss

Characteristic for runoff generation is strong seasonality in runoff

Catchment WinterDec - Feb

SpringMar - Apr

SummerMay - Aug

AutumnSept - Nov

Høgfoss 0.30 0.25 0.17 0.28Skuterud, 0.28 0.27 0.13 0.33Räpu (Est.) 0.35 0.36 0.15 0.15Rägina (Est.) 0.32 0.31 0.16 0.21Mellupite catchment (Lat.) 0.49 0.24 0.07 0.21Mørdre 0.23 0.35 0.16 0.26Skuterud, 0.28 0.27 0.13 0.33Kolstad 0.10 0.41 0.23 0.25

During growing season very little runoff

Yearly runoff and nutrient loss is generated in only limited number of days

runoff SS TP TN% days50 26 12 16 2390 118 66 80 106100 365 365 365 365

An example for the Skuterud catchment, Norway (4.5 km2)

Runoff and nutrient loss in a large catchment

runoff TN TP% days

50 38 38 2490 174 166 132

100 365 365 365

Lena catchment (181 km2)

runoff TP TN% days50 26 16 2390 118 80 106100 365 365 365

Skuterud catchment

Characteristic for many catchments is the large in-day variation in discharge

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. disch1 coeff. var.catchment day hr day hr

Skuterud 2.9 5.7 209 239

Mørdre 1.7 2.8 222 245Kolstad 1.4 2.4 182 195

  spec. disch1 coeff. var.catchment day hr day hr

Skuterud 2.9 5.7 209 239

Mørdre 1.7 2.8 222 245Kolstad 1.4 2.4 182 195

Høgfoss 1.3 1.5 123 125

Lena 1.3 1.5 120 123

This is much less pronounced in the large catchments

  spec. disch1 coeff. var.catchment day hr day hrRäpu 0.6 0.7 133 135

Rägina 0.4 0.5 121 122

Mellupite 1 1.2 182 188

Skuterud 2.9 5.7 209 239

Mørdre 1.7 2.8 222 245Kolstad 1.4 2.4 182 195

Høgfoss 1.3 1.5 123 125

Lena 1.3 1.5 120 123

Latvian and Estonian catchments show less variation

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

Runoff generation caused by freeze/thaw cycles in combination with snowmelt/precipitation

Variation in discharge can be expressed through a flashiness index, showing the

rate of change

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Which factors influence runoff generation?

Runoff generation, scale and subsurface drainage

Subs dr.

Subs dr.

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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

The effects of subsurface drainage and nutrient – and soil loss

Vandsemb, 1992 - 2004 surfacesubsurface

.N-loss (kg/ha) 2 22P-loss (kg/ha) 0.6 0.5SS(kg/ha) 470 90Runoff (mm) 126 202

Bye, 1994 - 2007 surface subsurfaceN-loss (kg/ha) 1.1 29P-loss (kg/ha) 0.3 0.04

SS(kg/ha) 220 20Runoff (mm) 14 165

groundwater leveldrain

Drain spacing, L = 8 – 10 mDrain depth, d = 0.8 – 1.0 m bss.

Soil types important

Macropore/preferential flow

Fast transport to subsurface drainage systems

Transporting soil particles/phosphorus?

Skuterud, 1994 - 2006N_loss (kg/ha) 45P_loss (kg/ha) 2SS(kg/ha) 1190Avrenning (mm) 504

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).

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Flashiness and base flow index

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

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

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)

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 oC • Precipitation as snow• Water turns into ice • Slippery roads, traffic problems, accidents

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

Infiltration and frozen soils, is there any, and how to measure

• Skuterud catchment 2001/2002

TDR equipmentliquid water content

Neutron scatteringtotal water content

Infiltration and frozen soils, is there any, and how to measure

• Skuterud catchment 2001/2002

Infiltration and frozen soils, is there any and how to measure

• Infiltration tests in frozen soils, Vandsemb catchment (2002)

Excavation in May 2002

Infiltration and frozen soils, is there any and how to measure

• Infiltration tests in frozen soils, Vandsemb catchment (2002)

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.

The effect of latent heat on soil frost development

Season 2000 - 2001

Season 2002 - 2003

The effect of snow on soil frost development

Season 2002 - 2003

Season 2000 - 2001

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

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

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

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

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But even freezing periods are characterised by several freeze/thaw periods

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.

Variation in freezing index

Variation in freeze/thaw cycles

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

Some results

• Nitrogen• N loss occurs during the freezing period

Löytäneenoja Graisupis Skuterud M36

N loss freez. per. 4.9 (35 %) 4.5 (33 %) 8.7 (20 %) 1.4 (5 %)

N loss year 13.9 13.5 45.3 25.6

Some results

• Phosphorus loss during freezing period

Löytäneenoja Graisupis Skuterud M36

P loss fr. period 0.1 (20 %) 0.1 (33 %) 0.5 (20 %) 0.01 (3 %)

P loss year 0.5 0.3 2.4 0.3

Is ice then too cold?

If not taken into account the right processes.

Freez/thaw cycles – aggregate stability changeusle, rusle, musle, wepp, eurosem,

InfiltrationLatent heat of freezing, Change over time in infiltration capacityEffects of snow(Coup, soil, shaw)

Winter processes affect the hydrologyin large areas of Europe!

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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