Charles MAGUIN - Rapport de stage...

Charles MAGUIN – Atrazine and Diuron Runoff Modelling in the Burdekin Region – 2010 CSIRO

Mémoire

Présenté par : CHARLES MAGUIN Dans le cadre de la dominante d’approfondissement : IDEA Stage effectué du 12/04/2010 au 29/10/2010 avec l’organisme

CSIRO (Australian Commonwealth Scientific and Resea rch Organization) CSIRO Ecosystems Sciences Queensland Bioscience Precinct 306 Carmody Rd St. Lucia QLD 4067 AUSTRALIA Sur le thème :

Modélisation des pertes en herbicides dans les cult ures de canne a sucre du Burdekin

Pour l’obtention du : DIPLÔME D’INGÉNIEUR D’AGROPARISTECH

Cursus ingénieur agronome et du DIPLÔME D’AGRONOMIE APPROFONDIE

Enseignant/e-tuteur responsable de stage : David MONTAGNE

Maîtres de stage : Peter Thorburn et JODY BIGGS Soutenu le : 04/10/2010


Acknowledgements I wish to express my gratitude to Dr. Peter Thorburn and Jody Biggs for their help and support during my working at the CSIRO and for the writing of the present report. I would like to thank the CSIRO staff. I have met interesting and friendly people, who kindly invited me at the morning teas where not only cakes but also ideas were sheared. This internship could not have been completed without the support of the HowLeaky? developing team : I would like to thank Brett Robinson, Melanie Shawn, Mark Silburn and David McClymont for their help.

My colleague, Gustavo Resende, also provided me with valuable support and pieces of advice. AgroParisTech professors, in special David Montagne and Philippe Martin are thanked for their assistance with that work.


Executive Summary

The Great Barrier Reef, this extraordinary but fragile ecosystem, located in Australian waters is threatened by human activities. Sugarcane farming is one of them. The many chemical inputs used in the fields are found in the waters around the Reef and threaten its natural balance.

The Australian government has implemented programs to monitor water quality and protect the Great Barrier Reef. This is the context where the present paper gives its contribution.

Herbicides are one of the main threats to the Reef, because they destroy the vegetable part of the ecosystem. Diuron and Atrazine are the two most used one in the Burdekin (the study area) sugarcane cropping systems. The purpose of this study is to model the loss of herbicides from sugarcane farms in order to better understand the mechanisms that lead to pollution.

The model called HowLeaky? was used to model runoff and the herbicide losses associated to it. The result shows that the model correctly predicts the major runoff events, but fails to represent the small-scale events. This leads to over predictions of pesticide losses and delay in time.

Adjustments will be made to the parameterization of the model to refine the predictions and provide more satisfactory results in a later version of this document.

Résumé La Grande Barriere de Corail, cet extraordinaire mais fragile écosystème, situe dans les eaux territoriales australiennes, est menacée par les activités humaines. La culture de la canne à sucre est l’une d’entre elle. Les nombreux intrants chimiques utilisés dans les champs se retrouvent dans les eaux qui baignent le corail et menacent son équilibre naturel. Le gouvernement australien a mis en place des programmes de surveillance de la qualité des eaux et de protection de la Grande Barriere de Corail. C’est dans ce cadre que ce document apporte sa contribution. Les herbicides constituent une des menaces principales pour le corail, car ils détruisent la partie végétale de l’écosystème. Atrazine et Diuron sont les deux produits les plus utilises dans la culture sucrière du Burdekin, la région étudiée. L’objet de cette étude est de modéliser les pertes en herbicides au niveau des champs de canne a sucre afin de mieux appréhender les mécanismes qui conduisent aux pollutions. Le modèle HowLeaky? a été utilisé pour modéliser les ruissellements et les pertes en pesticide associées. Le résultat montre que le modèle prédit correctement les événements de ruissèlement majeurs, mais échoue à représenter les événements de faible envergure. Cela conduit à des prédictions de perte en pesticide exagérées et décalée dans le temps. Des corrections vont être apportées à la paramétrisation du modèle pour affiner la modélisation et proposer des résultats plus satisfaisants dans une version ultérieure du présent document.


Table of contents Acknowledgements ...................................................................................................... 2 Executive Summary...................................................................................................... 3 Résumé ......................................................................................................................... 3 Table of contents .......................................................................................................... 4

Pesticides Runoff Modelling in the Burdekin Region...................................................... 1 Introduction .................................................................................................................. 1

A Stake, a Threat, a Problem.................................................................................... 1 CSIRO Sustainable Ecosystems ............................................................................... 2 Modelling pesticide losses........................................................................................ 3 HowLeaky?............................................................................................................... 4 Method...................................................................................................................... 4

PART 1 : Context of the Study..................................................................................... 5 The Burdekin : a sugar cane agriculture in a tropical climate .................................. 5 HowLeaky?............................................................................................................... 9 The importance of parameterizing.......................................................................... 12 Atrazine and Diuron specificities ........................................................................... 13 Time span of the study ........................................................................................... 14

PART 2 : HowLeaky? predictions.............................................................................. 14 HowLeaky? Predictions.......................................................................................... 14 HowLeaky? versus APSIM and measured values.................................................. 15

PART 3 : Analyses and prospective ........................................................................... 18 Coming back to parameterizing.............................................................................. 18 Prospective ............................................................................................................. 19 Investigating HowLeaky? pesticide module code.................................................. 20 Improving the farming management practises ....................................................... 22

CONCLUSION .......................................................................................................... 22 References .................................................................................................................. 23 APPENDIX - 1 ........................................................................................................... 25 Total Water Balance (HAT) ....................................................................................... 25 APPENDIX - 1 ........................................................................................................... 26 Total Water Balance (NEIL) ...................................................................................... 26 APPENDIX - 2 ........................................................................................................... 27 HowLeaky Predicted Runoff (HAT) .......................................................................... 27 APPENDIX - 2 ........................................................................................................... 28 HowLeaky Predicted Runoff (NEIL) ......................................................................... 28 APPENDIX - 3 ........................................................................................................... 29 HowLeaky Predicted Atrazine Losses (HAT)............................................................ 29 APPENDIX - 3 ........................................................................................................... 30 HowLeaky Predicted Atrazine Losses (NEIL)........................................................... 30

Charles MAGUIN – Atrazine and Diuron Runoffs Modelling in the Burdekin Region – 2010

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Pesticides Runoff Modelling in the Burdekin Region

31/08/2010

Introduction A very modern and highly productive agriculture, using a lot of chemicals, set in

a tropical area where extreme rain events happen, next to one of the richest and most

fragile ecosystem in the world. This is the situation of the sugar cane industry in the

Burdekin Region, Australia, near the Great Barrier Reef.

(Australia and the Burdekin - Google Earth)

A Stake, a Threat, a Problem Australia is one of the world biggest sugar exporters. The sugarcane is grown

essentially in Queensland (98% of Australia’s exported raw sugar is Queensland grown) [15], and the biggest sugar producing region in Queensland is the Burdekin. The Burdekin River has the second largest catchment draining into the Great Barrier Reef and is one of the biggest rivers in Australia (by volume of flow) [2].

The Burdekin River discharges only 30km away from the world famous Great

Barrier Reef, which has been classified as a World Heritage Area since 1981. This natural treasure is being threatened in numerous ways. The chemicals used in the local


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agriculture are one of these threats : the livestock is responsible for erosion and produces particulate nutrients and the cropping systems use pesticides and dissolved nutrients. Sugarcane, in the Burdekin, is by far the main crop, and biggest user of fertiliser and pesticide. These chemicals are brought to the Great Barrier Reef through the rivers, either diluted in the water or bound to the sediments coming from the erosion of the fields.

The pesticide problem is a part of the reef water quality problem, which led in

2003 to the creation of the Reef Water Quality Protection Plan by the Australian and Queensland governments. A body of evidence, summed up in the Scientific Consensus Statement on Water Quality in the Great Barrier Reef [7], supports the existence of the decline in the water quality and dedicate a whole chapter to the specific pesticide problem.

The Great Barrier Reef, an extremely precious ecosystem, is also feeding an

extremely profitable touristic business, which generates over 6 billion AUD per year, while the Australia wide sugar cane industry generates about 2 billion AUD [4,9]. So the pesticide problem is definitely an economical stake for the Queensland and the Australian Governments.

CSIRO Sustainable Ecosystems

Australia’s CSIRO (Commonwealth Scientific and Industrial Research Organisation) is a large governmental research organisation, with over 6.600 employees. The researchers deal with many subjects, from mathematics and health sciences to agricultural sciences. CSIRO Sustainable Ecosystem is an operational division of CSIRO that specifically deals with economic, social and environmental sustainability research [14]. This is the division I have been working in, in the frame of a Great Barrier Reef Conservation Project.

This Great Barrier Reef Conservation Project associates CSIRO, the Queensland

Government, Regional Natural Resource Management Bodies, shires, agricultural and marine industries, and other science providers. Its three main areas of focus are sustainable irrigation farming, repairing coastal floodplains, and productive and healthy inland grazing landscapes [17].


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Modelling pesticide losses In order to fight the pollution due to agriculture chemicals, it is necessary to

understand how these chemicals, initially applied on sugar cane fields, eventually arrive in the sensitive Reef area. This implies to understand the behaviour of these chemicals in soils and the way they are carried away by runoff water. Modelling through computer software how soils properties, climate and crop interact with pesticide is a way to better understand the process controlling the movement of these chemicals. Once the model is reliable, it allows to testing various scenarios, make predictions and design better management practises.

In CSIRO, I have been working with Jody Biggs and Peter Thorburn (Northern

Farming Systems research team leader). They are working on a model called APSIM (Agricultural Production Systems Simulator) to describe the runoff from the sugar cane fields in different situation of climate, management practices and soil types. They deal mainly with the nitrogen pollution, which leads to algal-blooms in the reef [10]. Their work is used to elaborate new agricultural practices that aim at a better quality of the Great Barrier Reef watersheds (Nitrogen Replacement Scheme). The International Society of Sugar Cane Technologists presented Dr Thorburn and his co-authors with the award for best agricultural research paper at its triennial congress in Durban, South Africa, in 2007 [14].

However, little has been done yet on pesticide runoff modelling, even though

pesticides have been proved to be harmful for the coral reefs [7]. Pesticide concentration measurements have been done by the CSIRO in several sugar cane cropping areas and in the Great Barrier Reef, including the Herbert and the Burdekin regions.

Atrazine and Diuron are two herbicides that are widely used in the sugar cane industry in Australia. These two herbicides are of high concern, because they are quite soluble. Their concentrations regularly exceed the ecosystem health guidelines [6,11]. This study chooses to focus on these two herbicides.

The purpose of my internship at the CSIRO was to run the first modellings of the herbicide problem in the Burdekin region, in order to give feedback on a rather little tested model, called HowLeaky?.


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HowLeaky?

HowLeaky? is a model for water balance in a crop field. Its goal is to provide

insight into the impact a range of land management practises on water quality. It has been developed by the Agricultural Production Systems Research Unit in Toowoomba, Australia[12]. It includes a pesticide runoff module, which APSIM does not (yet). HowLeaky? was the only model in Australia to model pesticide losses at the time of this report.

My first task was to get HowLeaky? running on a computer, gather all the data

needed to run simulations and compare the results with those provided by APSIM and with the measured data. In a second time, I was expected to investigate HowLeaky?’s code, describe it and prepare the creation of a pesticide module for APSIM.

Method The idea of the study is to have a first insight of how HowLeaky? can help us model the herbicide losses from the sugar cane fields. The method is simple. First, I gathered real data from two CSIRO experimental sites (HAT and NEIL), located in the Burdekin, where runoff samples have been collected over the past years. Data from these two sites have been used to parameterize HowLeaky?. Then, I calibrated HowLeaky?, using literature and specialists knowledge. The next step was to compare HowLeaky? predictions with APSIM predictions, and with the actual measurements. The goal of this comparison is to come back to the parameterization and help improve the calibration. Due to the flatness of the Burdekin and the properties of Atrazine and Diuron, the most important thing was to get realistic water runoff predictions.

As well as undertaking the model comparison, I was investigating HowLeaky? code, to both help me understand the model and also allow me to design a flow chart to prepare for a APSIM pesticide module. Indeed, in case HowLeaky? could not provide satisfying runoff predictions, using APSIM runoffs with HowLeaky? pesticide module would help the CSIRO team to get pesticide losses predictions.


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PART 1 : Context of the Study

The Burdekin : a sugar cane agriculture in a tropic al climate

The Burdekin is one of the largest sugar cane producing regions in Australia, with over 8 millions tons of sugar cane produced each year. The sugar cane industry (including milling) is, along with tourism, one of the major activity in this area. The farms are usually large (100 ha), well equipped with modern machineries and fully irrigated – the climate making it necessary in order to achieve high yields.

Study area The Burdekin region extends from the top of the Great Dividing Range to the

coast and includes a part of the Great Barrier Reef. It’s located in Queensland, in Australia, and is subject to a dry tropical climate. The part where the sugar cane farms are concentrated covers a very flat area of 5,000 km2 with a mainly rural population of almost 20,000 inhabitants. The climate in the Burdekin is very dry : the Burdekin area receives an average of 300 days of sunshine and 950mm of rain a year. In summer, there are sudden and violent tropical rains, which are difficult to forecast. During the cooler months (April to October), the weather is dry, sunny and warm [1]. Here is the measured rain on the two CSIRO experimental sites in the Burdekin, from 2004 to 2008. The most important part of the rain falls between January and March. The rest of the year is rather dry.


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The soil characteristics in the Burdekin Extensive soil analyses have been made on the two experimental sites (HAT and

NEIL). A part of the results are shown in the following diagram, which is related to the HAT site. The soil is a little bit sandier at NEIL site. What we can say about these soil analyses is that they show a potential for runoff, due mainly to the soil texture.

Figure 1: Mulgrave Soil (HAT) - Keimi et al. SRDC Technical Report


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Physical / Hydraulic properties for Mulgrave Soil (HAT) - Keimi et al. SRDC Technical Report :

Medium Clay

General description

Depth (cm) 10 - 15 10 - 15 40 - 45 75 - 80 125 - 130 170 - 175 Horizon AP1Row AP1Inter Layer2 Layer3 Layer4 Layer5 Texture

Medium Clay

Medium Clay

Medium Clay

Medium Clay

Medium Clay

Light Sandy Clay

Particle Size Analysis

- clay % 39.4 39.4 44.4 52.5 54.8 38.3

- silt % 20.6 20.6 19.8 16.3 7.9 3.7

- fine sand % 36.2 36.2 31.6 27.1 28.0 38.8

- coarse sand % 3.9 3.9 4.2 4.2 9.2 19.2

Soil physical indices

Bulk density (g/cm3) 1.34 1.54 1.62 1.70 1.73 1.84 Total porosity (vol %) 49.31 41.96 38.92 35.93 34.85 30.67 Macro porosity (vol %) 18.73 7.16 -1.69 3.04 3.11 6.62 Field capacity (DUL – vol %) 30.58 34.80 40.61 37.44 37.22 30.03 Permanent wilting point (DLL – vol%) 22.29 23.97 31.73 30.25 30.95 23.61 Plant available water (PAWC - vol%) 8.29 10.83 8.88 7.18 6.26 6.42

Specificities of sugar cane farming Sugar cane grows best in very warm and sunny areas, with an access to plenty of water. These conditions are met in the Burdekin, but only thanks to an intense irrigation: in most cases, over 1,000mm of extra irrigation is needed each year in order to prevent the crop from suffering from water stress. The paddock are usually flood irrigated, using a pipes system. This causes runoff. The irrigation, combined with the paddock sizes, would probably cause important soil erosion if it were not for the flatness of the region.


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Figure 2: Irrigation system in the Burdekin – CSIRO (Peter Thorburn)

Sugar cane takes between 12 and 16 months to be ready for the harvest. At that

time, it is commonly 4 meters tall. A ratoon is left on the field. Following harvest, the cane is allowed to ratoon (i.e. spontaneously regrow), and this can be done up to 4 or 5 times, until you have to plant a new cane crop. Farmers usually harvest in the end of the dry season (in October for instance), after one or two months without irrigation, so that the sugar content is maximal. In the Burdekin, contrary to other Australian sugar cane regions, the cane is still burnt before harvest. Burning the cane is the easiest and cheapest way to get rid of the unwanted parts of the plant. However, besides emitting CO2 and causing discomfort to the neighbourhood, burning the cane lowers the soil’s organic matter regeneration.

The noxious weeds are one of the main environmental threats to the sugar cane industry in the Burdekin area [3] which leads to a massive use of herbicides, such as Diuron and Atrazine. Sugar cane needs weed protection mostly when it is young, because it quickly grows tall enough to prevent light from reaching the weed seeds.

On the CSIRO experimental sites, the management practises for cane are :

1. Burning in early October 2. Harvest in October 3. Fertilizer application 4. Disc and tillage 5. Herbicide application 6. Post field management irrigation (and then, depending on the soil

moisture and plant needs) 7. New ratoon cycle (or planting) – 12 months


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The Burdekin River and nearby reef ecosystem The Burdekin River is the fourth-largest in Australia by volume of flow, but due

to the climate specificity, its flow is so variable that its discharge can reach the mean discharge of the Yangtze River or have as many as seven months with no flow[20]. Queensland’s biggest dam [19] has been built on the course of the Burdekin River, and it provides most of the water needed for the sugar cane growing needs.

The Burdekin River discharges only 30km far from the world famous Great

Barrier Reef, which has been classified as a World Heritage Area since 1981. This coral reef is the world’s largest reef system (350.000m2) and has been classified as a World Heritage Area since 1981 for:

• Exceptional natural beauty and aesthetic importance

• Significant geomorphic or physiographic features

• Significant ecological and biological processes

• Significant natural habitats for biological diversity [9].

When there is a large rain event, the River is likely to be flooded. Runoff from sugar cane fields is likely to happen, and the water will be collected by the Burdekin River, which will transport the polluted water quickly to the ocean. The amount of water carried is huge; a flood plume is going to form, bringing nutrients, sediments and chemicals to the sensitive reef ecosystem.

HowLeaky?

HowLeaky? is a software for modelling water balance on a paddock scale for various land uses. Its core water balance equations are based on a model called PERFECT which is also the basis of the water balance modelling in APSIM. PERFECT, released in 1989, is no longer used, but has been used for years and thus acquired a certain level of recognition.

The water balance model in HowLeaky? The water balance model in HowLeaky? describes each soil layer as a bucket. Each bucket has a saturated water content which is the maximum amount of water it is possible for the layer to hold. If more water is coming to the layer, it is going to the upper layer, or it runs off if the top layer is full. Each bucket has a hole with a pipe in it. The width of the pipe is the speed of the drainage from an upper layer to the layer situated just below it. There is drainage only if the amount of water in the layer is superior to the field capacity.


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A crucial parameter of the model is the runoff curve number. This number describes the partition of the falling rain between infiltration (part of the rain which goes into the bucket model) and runoff. The curve number depends on the soil moisture content at the time of the rain event, tillage and crop residue cover. These factors are taken into account in HowLeaky? in a very simple way: if there has been a tillage event, the runoff curve number is changed (reduced, so less runoff) and the user can define an amount of rain needed to restore the runoff curve number to its initial value. In case of a high crop cover, the number can also be changed.

(Charles MAGUIN – CSIRO – 2010)

In addition to this basic model, there is a water balance between the air and the

first layer of the soil, plus of course the intake of water by the crop, which is lost through transpiration. The crop can absorb water from the soil only if the water content is above the wilting point. The crop model in HowLeaky? is very simple, because the model focuses on water balance rather than crop modelling.

Water in HowLeaky? is lost through transpiration, evaporation, runoff and deep drainage.


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The pesticide model in HowLeaky? The pesticide model is mainly based on two factors: a sorption coefficient and a half life. According to Rattray et al. [16], these two are the most important processes controlling the fate of Atrazine in the soil, but it is actually true for most pesticides. The sorption coefficient describes how much of the pesticide is bound to the soil particles and how much is dissolved in the soil water.

The pesticide, when applied, is stored in several compartments like the soil, the stubble, the vegetation (depending on the spraying mode). It disappears according to its half life for each compartment. In case of rain, the pesticide is partly washed off the vegetation and the stubble and ends in the soil. If there is runoff, the amount of pesticide taken away is a function of its concentration in the soil and of the erosion. The following diagram describes the pesticide model in HowLeaky?.

`


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The importance of parameterizing

Parameters in HowLeaky? To run a simulation, HowLeaky? needs :

• A climate file: SILO [8] provides climate files all over Australia, in a format HowLeaky can use (.p51). However, the data I used were provided by the CSIRO in .apsim format and had to be converted to .p51.

• A soil template: this template describes the soil's parameters. Some of these inputs are not measured in soils and have to be either guessed or, in my case, were adapted outputs from APSIM. Some parameters are described layer by layer. The soil template also allows describing some paddocks characteristics, like the length of the slope and how steep it is.

• A vegetation template: this template describes the crop or pasture or any agriculture related land use. There are two ways of modelling the crop in HowLeaky. One uses a Leaf Area Index to describe the crop, the other one is a crop-factor model, which is simpler. HowLeaky models the crop only for its impact on the water balance, and does not have a very extensive yield model. This template describes how deep the vegetation can take the water from, but also describes the field cover. Green cover is the cover made by the living plant while residue cover is the cover made by the trash, on the ground. The cover slows the water falling down, and thus reduces the runoff.

• An irrigation template: this template describes the irrigation. Several options are available, like irrigating when the soil reaches a certain level of moisture content, or irrigating regularly. I used the scheduled irrigation, which allows defining the irrigation dates and amounting.

• A fertilizer template: this template describes the chemical properties of the pesticide applied and the parameters of the application.

• A tillage template: this template describes the management practises and their schedule.

An important part of the modelling work is to calibrate or parameterize the

model, based on data. Most data will be gathered through measurements (like a layer thickness or its field capacity), but some parameters can not be measured or are too difficult or expensive to measure: what is the layer drainage speed to the next one? The runoff curve number is also a very sensitive parameter: it is difficult to assess but crucial for the simulation. My data came from various sources. The first one was the soil data provided by the CSIRO. They conducted extensive measurements of the experimental sites properties. However, some soil parameters like the maximum drainage per layer per day, are not inputs for APSIM, and thus were not provided. I first used APSIM outputs


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to estimate values for maximum drainage but the first simulations were not satisfying enough and I had to get in touch with the HowLeaky? developing team to discuss the matter. They helped me characterized the soil and find an appropriate value for the model, in accordance with the soil type. I found the data for the two herbicides in HowLeaky templates and in the scientific literature. However, you cannot say if your parameterization is good until you have compared predictions with reliable measurements.

Atrazine and Diuron specificities Atrazine[5] Atrazine (2-chloro-4-(ethylamine)-6-(isopropylamine)-s-triazine) is a widely used pre- and post-emergence herbicide in the USA and in Australia. In the EU, this chemical has been excluded from a re-registration process in 2003 because of a lack of water monitoring data given by the registrants. It has not been banned but is not used anymore because it has not been re-approved. The Australian Pesticides and Veterinary Medicines Authority made an extensive review of Atrazine in 2008 and concluded it was still safe to use, if used according to the product label instructions.

Atrazine is used for the control of grass and broadleaf weeds in crops such as

sorghum, maize and sugarcane. It has raised concerns about wildlife and human toxicity, and has been proved to be harmful to the Great Barrier Reef ecosystem, especially the seagrass [7]. The legal limits of Atrazine concentrations in Australia are :

• Drinking water guideline value : 0.1ug/L

• Wildlife biodiversity protection guideline (fresh water) : 13ug/L

• Drinking water health value : 40 ug/L

Atrazine is moderately to highly mobile in soils. Because it does not absorb strongly to soil particles (Koc = 100 g/ml) and it has a rather long soil half-life (60 to 100+ days), it has a high potential for groundwater and surface water contamination, even though it is only moderately soluble in water (33 ug/ml) [13].

On CSIRO experimental sites, Atrazine was applied in the most common way,

respecting all the packaging instructions and good management practises. It was applied after the harvest, in October, when the ratoons were still short and the sprayer can be driven on the field. It was not applied every year, but every two years. The field was then irrigated briefly so that the chemical drains into the soil, in the first 2cm. It improves the molecule efficiency and reduces its availability on the surface, where it could be washed up. No herbicide is needed once the sugar cane is grown up, because it shades the soil, preventing weeds to grow.


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Diuron (to be completed)

Time span of the study

The main campaign of pesticide measurements made by the CSIRO ran from 2004 to 2007. Analysing pesticide content in runoff samples is a time consuming and costly task, which is the reason why there have been few measurements.

PART 2 : HowLeaky? predictions

HowLeaky? Predictions

Total Water Balance [Appendix1] It is interesting to first look at the total water balance. It gives us an overall idea

of how the climate/soil/crop system works in this case. HowLeaky predicts that transpiration is the main water use on the paddock, which is good because it means that an important part of the water is used by the plant. However, more than 50% of the water is lost through other means, especially drainage. Over 7 years, the two sites appear to have pretty similar properties.

Runoff [Appendix2] Most of the runoff events predicted by HowLeaky? happen in January or February, during the wet season. The rest of the year is dry, and very few runoff events occur. The runoff events during the wet season can reach up to 100mm in a single day! Surprisingly, even during such major runoff events, the erosion is very low (up to 1.6t/ha, but mostly under 0.5t/ha). This is due to the flatness of the Burdekin area: the slopes steepness is under 0.3% on the experimental sites.

Pesticide losses [Appendix3] Pesticide losses happen only when there is a runoff event. Atrazine and Diuron have an intermediate sorption coefficient, which means they are found both in the soil water and bound to the soil particles. Because of the low erosion level in the Burdekin, herbicide losses are mostly proportional to the runoff event. Some other chemical would runoff only if there is erosion. The amount of herbicide lost is higher when the runoff event happens shortly after the application. After the first major loss, the other runoff events are not causing much herbicide losses, for most of it has already gone. On a major runoff event, the Atrazine loss can be up to 150g/ha, according to HowLeaky?. Atrazine concentration in runoff water is then up to 200ug/L, but the mean event concentrations are 118ug/L for HAT and 97ug/L for NEIL.


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HowLeaky? versus APSIM and measured values

To get the pesticide losses predictions right, it is necessary to get runoff predictions right. So I compared HowLeaky? predicted runoff events with those predicted by APSIM and those measured on the field. The measurements are not to be taken as THE truth. In case of floods, the measurement tool could be overflowed and the runoff measure is then underestimated (they were then re-estimated with the help of APSIM). It also happened that the measurement system broke, which lead to missing data in the time series. The focus is made on runoffs, because the pesticide losses predictions rely mostly on it. HAT and NEIL show similar results.

Howleaky? versus Measured data Here are the comparison graphs between HowLeaky? and the measured data.

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taking only these two months into account, our prediction with HowLeaky? has 80% accuracy. However, it fails in predicting small runoff events during the dry season. This is especially true when we compare cumulated runoff:


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f (m

m)

HowLeaky

Measured

Howleaky? versus APSIM Here are the comparison charts between HowLeaky runoff predictions and

APSIM predictions, for HAT, over 7 years.

Monthly Runoff HLvsAPSIM (HAT)

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off (

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)

HL RO

APSIM RO

Between the two models, we can run the simulations on a longer period, using

climate data from SILO and standard irrigation and management practises (irrigation and management data starts from 2004 only). The results are pretty similar to what we


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get with the measured data: HowLeaky? does a decent job with big events, but fails to predict small events. This is especially visible with the linear regression (HAT site):

APSIM vs HL

y = 1.3938x + 20.681

R2 = 0.7716

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Herbicide losses predictions versus measured values

Here is the chart showing Atrazine losses on HAT:

Atrazine runoff

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Time

Her

bici

de lo

ad (

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)

HowLeaky

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The herbicide prediction is not satisfying in many ways. The predicted amount of Atrazine lost is up to 6 times higher than the measured one and the loss occurs two months later. The Atrazine loss happens with the first runoff event predicted by HowLeaky? after the Atrazine application date. There is uncertainty about the application date in 2004, but it obviously was prior to the 2nd of November, when the loss was recorded.

PART 3 : Analyses and prospective

Coming back to parameterizing In order to achieve a good simulation, the modeller goes through a long process

of trial and error. The modeller has got an idea of what the reality should be (simple logic like: “there can not be a sudden runoff event without a rain or irrigation event” or “a less permeable soil is more likely to provoke runoff”), and when the model obviously shows something that is not real, then it means there has been an error in the parameterization. But each error is an occasion to get a better knowledge of how the model works and how sensitive it is regarding some parameters.

Once the main errors have been eliminated, it becomes necessary to see how your predictions work against measurements. This is how the smaller parameterizing problems are discovered. Looking at the results given by HowLeaky?, we see mainly one problem: the small runoff events are not predicted, which leads to an incorrect pesticide runoff prediction. It would be too easy to conclude that the model is wrong. Even if it might suffer from imperfections, the main reason for inaccurate predictions is mainly calibration.

Parameters : infiltration speed and runoff curve number It was necessary to look at some specifics outputs in HowLeaky? to understand

the problem better. The way the runoff curve number was evolving in time was one of them. It showed that HowLeaky? does not make the difference between residue cover and green cover when it comes to the runoff curve number reduction: if there is a cover, be it residue or green cover, it reduces the runoff curve number. The runoff curve number determines how much runoff there is. If we set it higher, runoff events will happen more often, but every event will also be bigger. The runoff curve number is already rather high.

A second interesting HowLeaky? output is the soil moisture. It seems that the soil dries up too fast, which could be due to the infiltration speed. The infiltration speed has been set rather high. This was one of the hardest parameter to set, because no measurements were made for it. Lowering the value could help keep the soil moist.


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Initialization Another way to look at the problem is too realize that the soil moisture improves significantly from the middle of 2004, that is, when the experiment started and irrigation data were recorded. A very basic irrigation was introduced during the model initialization period (2000-2003), but it was obviously not enough. In HowLeaky?, the soil is too dry in the beginning of 2004, which leads to almost no runoff in late 2004, when the main Atrazine loss was recorded by the CSIRO. Only after the January heavy rain does the herbicide loss happen in HowLeaky?. Simply saturating the soil before starting the model could be a solution to initialize it.

HowLeaky? weaknesses During the process of analysing the inaccuracy of HowLeaky? predictions, some weaknesses of the model have been revealed. The slope, for instance, has no effect on the runoff. In the Burdekin, the slopes are not steep (0.16%). So the water should not runoff easily, and should rather stay in the soil longer. It is not what happens in HowLeaky: during big rain events, the runoff is very high, and then the soil dries up fast. If the slope was taken into account, maybe the big rain events would provoke smaller runoff events, leaving more water into the soil. The soil staying moist longer, other runoff events could happen even with smaller rain events. The fact that HowLeaky? does not differentiate between green cover and residue cover is also arguable. Green cover slows rain down and makes it hit the ground with much less strength, consequently favouring infiltration against drainage. But residue cover could have a more important impact because runoff happens on the surface of the ground, where the residue is. Residue cover slows down runoff, creating mini dams. In APSIM, residue cover has a stronger impact on diminishing the runoff than green cover.

Prospective As the result of the last simulation turns out to be still disappointing, more work will be done on that, and simulations will be re-run with a new parameterization, trying to achieve more frequent runoffs. Once the runoffs are predicted correctly, the herbicide losses prediction should improve much provided a small change in the half-life is done. The herbicide half-life has been set too high and will have to be reduced from 70 days to 60 days (average in this kind of soil). While running HowLeaky? to predict runoff, I also worked on the pesticide module code. If a pesticide module was implemented in APSIM, assuming that the runoffs are predicted correctly, that would allow better herbicide losses predictions.


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Investigating HowLeaky? pesticide module code

HowLeaky? pesticide module is coded in C++, which is an object oriented programming language. It is divided in several functions, which process the fate of pesticide in the farming system step by step. The following diagram is the result of my investigation of HowLeaky? pesticide module code. It is not the exact HowLeaky code, though, as I slightly reworked it to make it clearer and more efficient. HowLeaky? is distributed under GNU license and it is thus allowed to use its code. The module is mainly made of three parts. The first one is the application one. If the date is set to an application day, then the pesticide is applied on the soil, the vegetation and the stubble (residue), according to the application parameter. The second part is the degradation, according to the half life. The third part is the runoff part. In case of runoff, the amount of pesticide carried away is calculating. On the following diagram, a square is a function and a lozenge is a condition. The first parameters in a square are the input parameters of the functions; the outputs are in the lower part of the square.


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Improving the farming management practises The ways to lower herbicide losses are mostly known already [18,21]:

• Applying long before the wet season

• Mix the herbicide in the shallow layer of the soil

• Pre and post emergence application

• Use limited band spraying

• Do not spray near rivers

• Constructing sediment ponds

• Establishing grass filtering strips However, they can not always be applied easily, as a farm has to stay productive

and profitable for its owner. Modelling helps find which combination of good practises helps most at the cheapest cost. The herbicide runoff modelling is not relevant yet, but what seems to be efficient and not too costly is to mix the herbicide in the first layer of the soil. It has been proven to reduce the availability of the herbicide for runoff.

CONCLUSION Modelling is an important work of trial and error. During this process, I got to understand better how HowLeaky? works, and thus helped the CSIRO understand it as well. The difficulty of forecasting the weather in the Burdekin area makes predicting runoff from rainfall a tough job, and HowLeaky? is still a young model, whose code is updated almost every month. The results of my pesticide losses modelling with HowLeaky? are not satisfying yet, but I am getting closer to an acceptable prediction. The next step is to come back to the parameterization once again, and fix it with the new ideas. Once the runoff prediction will be correct, the pesticide losses prediction will be usable. The flow diagram for a pesticide module is the ideal tool to help software designers to build a pesticide loss module for APSIM. Using the highly sophisticated APSIM engine to predict runoff could be a way to get closer to accurate predictions of pesticide losses. An other team in the CSIRO is working on creating a pesticide module for APSIM, but from the pest fighting point of view: how do the pests affect the yields, and how do the pesticide help against them. This module could be linked to my pesticide loss module, in order to have a broader overview of the farming system.


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References

[1]Australian Agricultural College Corporation. (2010). The Burdekin Region. Available: http://www.agriculturalcollege.qld.edu.au/campus/burdekin/region.htm. Last accessed 31/08/10. [2]Australian Bureau of Statistics. (2010). Burdekin NRM Region. Available: http://www.abs.gov.au/AUSSTATS/[email protected]/Lookup/4619.0Main+Features502008-09. Last accessed 31/08/10. [3]Australian Natural Resources Atlas. (2010). Sugar Industry - Herbert / Burdekin

Region. Available: http://www.anra.gov.au/topics/agriculture/sugar/region-herbert-burdekin.html. Last accessed 31/08/10. [4]Australian Industry Report. (2010). Sugar Cane Growing in Australia (Industry Code / ANZSIC Code: A0161). Available: http://www.ibisworld.com.au/industry/default.aspx?indid=29. Last accessed 31/08/10. [5]Australian Pesticides and Veterinary Medicines Authority. (2008-2010). Atrazine. Available: http://www.apvma.gov.au/products/review/docs/atrazine_faq.pdf. Last accessed 31/08/10. [6]Australian Government - PIMC. (2000). Australian and New Zealand Guidelines

for Fresh and Marine Water Quality. Available: http://www.mincos.gov.au/publications/australian_and_new_zealand_guidelines_for_fresh_and_marine_water_quality. [7]Brodie et al. (2008). Synthesis of evidence to support the Scientific Consensus

Statement on Water Quality in the Great Barrier Reef

[8]Department of Environment and Resource Management (Australia). (2009). SILO, Meteorology for the Land. Available: http://www.longpaddock.qld.gov.au/silo/. Last accessed 31/08/10. [9]Great Barrier Reef Marine Park Authority. (2010). Great Barrier Reef Outlook

Report. Available: http://www.gbrmpa.gov.au/corp_site/about_us/great_barrier_reef_outlook_report. Last accessed 31/08/10. [10]Great Barrier Reef Marine Park Authority. (2010). Principal water quality

influences on Great Barrier Reef ecosystems. Available:


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http://www.gbrmpa.gov.au/corp_site/key_issues/water_quality/principal_influences.html. Last accessed 31/08/10. [11]Lewis S., Davis A., Brodie J., Bainbridge Z., McConnell V., Maughan M. (2007). Pesticides in the lower Burdekin and Don River catchments

[12]McClymont D., Freebairn DM., Rattray DJ. & Robinson JB. (2006). HowLeaky? Exploring water balance and water quality implications for different land

uses

[13]Office of Drinking Water, US EPA, Washington DC. (1988). Atrazine: Health

Advisory. [14]Peter Thorburn. (2007). International award for sustainable sugar breakthrough. Available: http://www.csiro.au/news/Nreplacement.html. Last accessed 31/08/10. [15]Queensland Sugar Limited. (2010). About. Available: http://www.qsl.com.au/page.cfm?pageid=199. Last accessed 31/08/10. [16]Rattray et al. (2007). Atrazine degradation and transport in runoff on a Black

Vertosol.

[17]Sheriden Morris, Great Barrier Reef coordinator. (2004). Healthy country for a

healthy reef. Available: http://www.csiro.au/files/mediaRelease/mr2004/PrWFHCreef.htm. Last accessed 31/08/10. [18]Thomas G. Franti et al. (1996). Agricultural Management Practices to Reduce

Atrazine in Surface Water. Available: http://www.p2pays.org/ref/09/08380.htm#c. Last accessed 31/08/10. [19]Wikipedia. (2010). Burdekin Dam. Available: http://en.wikipedia.org/wiki/Burdekin_Dam#cite_note-1. Last accessed 31/08/10. [20]Wikipedia. (2010). Burdekin River. Available: http://en.wikipedia.org/wiki/Burdekin_River. Last accessed 31/08/10.

[21]Wyatte L. Harman,* E. Wang, and J. R. Williams. (2004). Reducing Atrazine Losses: Water Quality Implications of Alternative Runoff Control Practices


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APPENDIX - 1

Total Water Balance (HAT)


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APPENDIX - 1

Total Water Balance (NEIL)


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APPENDIX - 2

HowLeaky Predicted Runoff (HAT)


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APPENDIX - 2

HowLeaky Predicted Runoff (NEIL)


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APPENDIX - 3

HowLeaky Predicted Atrazine Losses (HAT)


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APPENDIX - 3

HowLeaky Predicted Atrazine Losses (NEIL)

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