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MED/PR/0407/41

MEDACTION

____________________________________

POLICIES FOR LAND USE TO

COMBAT DESERTIFICATION

_____________________________________

Deliverable 28

DEVELOPMENT OF GUIDELINES FOR SUSTAINABLE LAND MANAGEMENT IN

THE AGRI AND COBRES TARGET BASINS

______________________________________

Contract No EVK2-CT-2000-00085

James C. Bathurst and Isabella Bovolo

University of Newcastle upon Tyne

UK

July 2004


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DETAILS OF THE CONTRACTOR

Contractor: University of Newcastle upon Tyne

Responsible Scientist: Dr J C Bathurst

Address: Water Resource Systems Research Laboratory

School of Civil Engineering and Geosciences

University of Newcastle upon Tyne

Newcastle upon Tyne

NE1 7RU

UK

Telephone +44 191 222 6333/6319

Fax: +44 191 222 6669

Email: [email protected]

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mailto:[email protected]:[email protected]


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1 BACKGROUND

This report is a deliverable of Workpackage 3.1 (WP3.1 Development and application

of Decision Support System to the Alentejo and Agri target areas).

Concern about the consequences of desertification has prompted the EuropeanCommission (EC) to support through its Environment Programme a programme of

investigation to identify, understand and mitigate the effects of the phenomenon in

southern Europe. One aspect of the resulting research has been the development of

models and Decision Support Systems (DSS), intended to integrate available

knowledge and data and provide the strongest basis for making decisions on land

management to mitigate desertification. WP3.1 was therefore aimed at the application

of a simple DSS in two target areas, the Agri basin in Italy and the Cobres basin in

Portugal. The workpackage was to advance beyond earlier work merely developing

DSS to apply the DSS in direct liaison with local agencies to provide outputs suitable

for practical application, e.g. related to land use and climate change impacts. There

was to be particular emphasis on end-user participation by transferring the results tothe public domain and by providing educational outputs which could be used to raise

awareness of the desertification problem.

The workpackage had two deliverables. Deliverable 27 was DSS output for specified

land use, climate and policy scenarios in the two target areas. Deliverable 28 was the

interpretation of this output to provide guidelines for sustainable land management in

the target areas. This report describes the work involved in completing the

deliverables.

2 WORKPACKAGE OBJECTIVES

The workpackage objectives were:

(i) Refinement and modification of a previously developed Decision Support

System (DSS) for application in the Agri and Cobres basins, including

necessary data assembly.

(ii) Application of the DSS to the Agri and Cobres basins to assess hydrological,

soil erosion and crop yield responses for land management, crop subsidy and

climate scenarios.

(iii) Development of guidelines on, and contribution towards, policy formulation

for sustainable land management in the Agri and Cobres basins, relevant to

local end-users.

Before application, the DSS was to be validated using information from

MEDACTION Module 2, which examines the impact of past policies on land use. In

particular, if the past policy could be represented in the DSS as, for example, a

subsidy change, the DSS could be validated against the recorded land use

development. Once validated the DSS could be used to explore the impacts of future

policies, within a context also of climate change. By this means the DSS couldcontribute to exploration of different options for policies which support sustainable

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land use. Liaison with the local stakeholders would allow the scenarios and models to

be attuned to their needs.

3 DEVELOPMENT OF THE SHETRAN DECISION SUPPORT SYSTEM

The DSS which was used was a simplified version of the design described by Bathurstet al. (2003) and originally proposed for the Agri target basin. Simplification was

necessary because the original project research associate left the University of

Newcastle in April 2002 (an unforeseen event) and it was clear that, by the time a new

research associate had been recruited and had become familiarised with the DSS,

there would not be enough time to complete the programme of restoring and applying

the original, more complex, DSS. Very considerable effort went into redesigning and

recoding the DSS to suit, amongst other constraints, a new computer operating system

at the University of Newcastle, and into setting up the DSS for both the Agri and

Cobres basins. The DSS consists of a hydrological and sediment yield model

SHETRAN to simulate fluxes and storages of water and sediment; a crop growth

model EPIC to provide annual crop yield; and a farmer response model for selectingthe crop type. In a feedback cycle, the hydrological model simulates soil moisture as a

function of the crop type, the crop growth model simulates crop yield as a function of

the soil moisture and the farmer response model selects next years crop type

depending (in part) on which crop is returning the highest yield in the current year.

The simulated change in crop cover then forms a feedback to improve the

hydrological modelling.

4 DATA ASSEMBLY, INCLUDING SOCIO-ECONOMIC DATA

The simulation period for the Agri basin remained the same as used in the

MEDALUS III project (i.e. 1985-88) (Bathurst et al., 2002). No additional data were

therefore needed for SHETRAN. The crop economic data required for the farmer

response model, originally collected in MEDALUS III (Bathurst et al., 2003), were

updated in collaboration with Professor Giovanni Quaranta at the University of

Basilicata.

The Cobres basin had been modelled with SHETRAN in the MEDALUS I project for

the periods 1977-79, 1980-82 and 1983-85. For the DSS application, though, it was

decided to use a more recent period, in the 1990s, in part to include the extreme storm

event of 5 November 1997. The required data were collected through a number of

visits to Portugal and with the help of the Alentejo target area team (especiallyProfessor Maria Roxo at the Universidade Nova de Lisboa and Mr Miguel Vieira).

Time series data for the 1990s were obtained largely from the Instituto de Agua

(INAG), Ministerio do Ambiente e do Ordenamento do Territorio. Daily precipitation

data are available for six sites (although only three extend beyond 1997), daily

temperature is available at two sites and daily pan evaporation data are available for

much of the period for the same two sites. Daily discharge data are available at three

gauging stations up to the late 1990s. Data for the extreme November 1997 flood are

also available for one of these gauging stations (Entradas). However, the daily flow

records are not reliable. They appear to be reasonably complete for Entradas but are

inconsistent with the rainfall record for the Albernoa station and are discontinuous for

the Monte da Ponte outlet station. Turbidity data (relevant to suspended sedimentdischarge) are available for 2001-02 at the Monte da Ponte outlet. In addition,

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available data from the Vale Formoso experimental agricultural station consist of

daily rainfall for 1966-2001 and event sediment yield for 1990-99 for several land

uses at the plot scale.

Hourly rainfall data for the 1990s were required as the basis for converting the daily

records (for which there is a good 1990s availability) to the hourly time series formingthe SHETRAN input. Hourly data on paper chart were eventually obtained for the

Vale Formoso experimental agricultural station but too late in the project to be

digitized, analyzed and put to use. Therefore the disaggregation was based on

statistics derived from the continuous breakpoint data from the late 1970s and early

1980s, for the Beja meteorological station (already available from the MEDALUS I

project (Bathurst et al., 1996)). The assumption is that the rainfalls from the two

periods have the same duration/intensity characteristics. A rainfall-duration curve

was derived statistically. This was then used to distribute each days rainfall over the

appropriate duration as a bell curve. The procedure was carried out for six

raingauges.

The crop economic data (standard sets of values for yields, prices and production

costs) were obtained from Mr Peter Eden (Instituto para o Desenvolvimento Rural e

Gesto Ambiental). Particular changes in land use from the period simulated in

MEDALUS I have been the replacement of soft wheat by durum wheat and, in the

Alentejo generally but not much in the Cobre basin, the plantation of stone pine and

eucalyptus trees.

The data required for running EPIC for both target areas were obtained from data

records, from the literature and from the EPIC user guidelines. The data include

temperature, daily solar radiation, soil properties, crop properties and biomass

parameters. Provision of complete temperature records required infilling of some

gaps, achieved through correlation between neighbouring meteorological stations.

The EPIC user guidelines did not provide all the necessary information: some of the

parameters were therefore adjusted in tests for each target area to ensure that the

model produced physically plausible values of biomass, leaf area index, crop height,

root depth and weight and other crop data.

5 VALIDATION OF SHETRAN BASIN MODELS

The simulation periods were 1/1/95 31/12/98 for the Cobres catchment (with 1994as a settling down period to allow the effects of initial conditions to dissipate) and

1/1/85 31/12/88 for the Agri catchment (with August 1983 to 31/12/84 as the

settling down period).

Since the original validation of SHETRAN for the Agri catchment by Bathurst et al.

(2002) there have been changes in both staff and computer systems at the University

of Newcastle. However, a test showed that SHETRAN still closely reproduced the

annual runoff of the original validation. Sediment yields were of the same order of

magnitude as before but generally a little lower. SHETRAN was therefore still

considered to be validated for the Agri catchment, albeit with a slightly different

baseline condition.

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For the Cobres basin, the input data consisted of hourly rainfall for six gauges and

daily potential evaporation from the pan evaporation record at Vale de Camelos.

Simulations for the 1977-85 period of the MEDALUS I project allowed the model

parameters to be adjusted slightly from their original values in the light of more recent

information on the catchment and the changes in the University of Newcastle

computer systems. The vegetation parameter values were altered to reflect thedifferent crops of the 1990s. Because of the general unreliability of the 1990s

discharge data, validation was carried out indirectly. On the assumption that the

Entradas data were sufficiently reliable a comparison was made between daily flow

duration curves derived from the measured and simulated data for this station. The

simulated curve initially overestimated the more extreme flows and the overland flow

Strickler resistance coefficient was therefore reduced from 5 to 2 to improve the

agreement. Annual simulated rainfall was also plotted against annual simulated runoff

for the baseline conditions to show that the 1995-98 results followed the same trend as

the 1977-85 results. On the basis of these comparisons, SHETRAN was considered to

be validated for the Cobres catchment, at least at the scale of the annual water budget,

and to provide a sufficient basis for comparing results from scenario runs.

6 DSS BASELINE RUNS

Full applications of the DSS were made to each target area to establish baseline runs.

These were runs for the given simulation periods with the validated SHETRAN

models and with the EPIC and farmer response models likewise parameterized for the

observed conditions of the simulation periods. The baseline runs provide the basis for

comparing the effects of the changes in catchment conditions introduced in the

scenario runs. With the current version of the DSS, the runs do not include feedback

on crop selection from the farmer response model to SHETRAN, i.e. crop cover is

static. However, the output from the farmer response model still shows the predicted

crop choice for each year.

Baseline runs were completed for both target catchments. The stored results include

the meteorological input data, hydrographs for the gauging stations, monthly and

annual runoff, monthly and annual sediment yield and the predicted crop distribution

for each year. To compensate for the lack of feedback on crop selection, each baseline

run was repeated by replacing the original crop distribution with the final predicted

distribution from the run. The results showed the hydrological outputs and the

variation in the predicted crop distributions to be sensitive to the initial crop

distribution, emphasizing the importance, therefore, of including feedback on cropselection in the DSS.

A one-year test run showed that SHETRAN run on its own for the Agri catchment

produced the same results as SHETRAN run within the DSS with the other models

switched off. In other words, the code linking SHETRAN to the other models did not

cause any spurious results.

Validation of the DSSs ability to represent changes in land use arising from policy

implementation was carried out using information from MEDACTION Module 2.

The aim was to represent a past policy in the DSS (e.g. a subsidy change) and then

test the ability of the DSS to reproduce the recorded land use development (e.g. a cropchange). Validation was carried out using the time series data for the sequence of

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years 1977-79, 1980-82 and 1983-85 for the Cobres basin and 1985-88 for the Agri

basin. As a policy detrimental in desertification terms, a durum wheat subsidy was

introduced, in line with the Durum Wheat Common Market Organization Regulators:

the DSS duly simulated an expansion of the wheat growing area, as observed in

practice. As a policy beneficial in desertification terms, a tree subsidy was introduced

in line with the Agri-environmental Regulation and the DSS accordingly showed anexpansion of tree cover. The results are presented in fuller detail in the report for

Deliverable 26.

7 SCENARIO DEVELOPMENT

Scenarios were generated for each target basin, for investigation with the DSS. These

referred to land use or climatic conditions which could potentially develop or be

implemented in the near to medium term (decades to century). The results from the

corresponding DSS applications were the basis for developing guidelines for

sustainable land management in the target areas.

The scenarios were selected from discussions with the target area teams and from a

review of relevant literature (e.g. Roxo et al., 1996; Bathurst et al., 1996; Roxo et al.,

1998; Loureno et al., 1998; Mairota et al., 1998; Kosmas et al., 2002; Basso et al.,

2002a,b). Discussions with the Alentejo team suggested two important scenarios. The

first is the replacement of conventional ploughing and seeding with direct seed

drilling. Introducing seeds plus fertilizer at the same time along narrow slits in the

ground, leaving the intervening ground unbroken (and covered by residues) reduces

runoff, erosion and evaporation. Also, while the initial investment in the seeding

machinery is relatively large, the subsequent seeding costs are less than for the

conventional approach, allowing greater farmer profit. On both environmental and

economic grounds, therefore, direct drilling is attractive for minimizing land

degradation. The second scenario is a minimum level of subsidy by 2020. The finally

adopted scenarios were: agricultural technique (seed drill), land abandonment, partial

afforestation, subsidy change and climate change.

The land use changes were represented by changes to the relevant model data files.

However, SHETRAN does not simulate agricultural technique directly. A sensitivity

analysis was therefore carried out for the MEDALUS I 1977-79 (wet) and 1980-82

(dry) simulation periods for the Cobres basin to find out to which parameters the

model results are most sensitive and thus to provide a basis for selecting parameterswhich can represent indirectly the changes in agricultural technique. Sensitivity

graphs were produced to show percentage change in annual discharge, in maximum

discharge and in the 90th

percentile discharge of the flow duration curve for given

percentage changes in the model parameters. (The simulated and observed flow

duration curves are similar. The high-discharge end of the curve is used as little

sensitivity is observed for the rest of the curve.) The most useful model parameters

were found to be overland flow resistance (Strickler coefficient), soil porosity and the

evaporation function (the ratio of actual to potential evapotranspiration varying as a

function of soil moisture tension).

The climate scenarios were compiled from data on the EC WRINCLE projectswebsite (http://www.ncl.ac.uk/wrincle). This project has generated climate data on a

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50-km resolution grid network across Europe, for both the recent past (1961-90) and

for a projected future climate (derived using output from the HADCM3 climate

model). Precipitation and potential evaporation data are presented as mean monthly

values for the two cases: there is an inconsistency, though, in that the future rainfall is

given for 2070-2099 while the potential evaporation is given for 2021-2050. The

WRINCLE data were extracted for the grid square most relevant to each of the Agriand Cobres basins. The ratios of future to present rainfall and of future to present

potential evaporation were calculated for each month and these ratios were then

applied to the rainfall and potential evaporation records already obtained for the

baseline simulation periods for each basin. This is a relatively unsophisticated way of

generating future climate data but is expected to be sufficient for showing directions

of change, even if the magnitudes are uncertain.

8 DECISION SUPPORT SYSTEM SCENARIO RUNS

Output on meteorological data, hydrographs for the river gauging stations, monthly

and annual runoff and sediment yield and the predicted crop distribution for each yearis displayed on the MEDACTION project website (currently via

http://www.ncl.ac.uk/medaction), forming Deliverable 27. The results are presented

for the baseline runs and the scenario runs, for both the Cobres and the Agri

catchments.

9 RESULTS/INTERPRETATIONS

Interpretation of the baseline and scenario simulation results provides a basis for

developing some simple guidelines on future land management in the target areas,

thus forming Deliverable 28. However, in view of the uncertainty associated with a)

the relatively unsophisticated scenario development and b) the model

parameterization (a problem typical of physically based modelling systems (e.g.

Beven, 1989; Bathurst et al., 2004), the results are appropriate more for showing

direction of change and relative change rather than providing absolute magnitudes of

discharge and sediment yield. In this sense the results are illustrative and may be used

to educate planners about the potential consequences of different actions and about

some of the factors which should be considered in future land management.

Appendices A and B show the simulation results for the Cobres and Agri catchments

respectively. Data on runoff and sediment yield are provided as tables of annual

values normalized by catchment area (i.e in mm and t ha

-1

yr

-1

respectively) and asgraphs showing mean monthly values for the simulation period, in mm and kg

respectively. Sample hydrograph time series are given for the Cobres catchment for

1/10/95-30/9/96 and for the Agri catchment for 1/10/85-30/9/86. Within the Cobres

catchment, output data are given for the main outlet at Monte da Ponte as well as for

the Albernoa and Entradas gauging stations. Within the Agri catchment, data are

given for the outlet at Gannano and for the subcatchment defined by the Pertusillo

reservoir. The farmer choice of crop to be planted in the following year is shown for

each year of the simulation (for the baseline and subsidy change runs only).

For the Cobres baseline condition (1995-98), there is a considerable variation in

annual rainfall (355-867 mm) and consequent runoff (62-399 mm), characteristic ofthe interannual variation in the Mediterranean region. Typically this is larger than the

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predicted future decrease in mean annual rainfall. For the Agri baseline condition

(1985-88), annual rainfall steadily decreases from 1016 to 811 mm and runoff falls

from 324 to 128 mm. In both catchments the main runoff period is autumn-winter-

spring; summer flows are low. The patterns at the main outlets are generally mirrored

at the subcatchment level, albeit with different magnitudes.

Abandoned land is represented by shrubs and bushes with reduced evapotranspiration

rates. In both catchments there is a resulting increase in runoff at the monthly and

annual scale and also in sediment yield. (In most cases, sediment yield varies in the

same direction as simulated runoff.) The baseline hydrograph shape is maintained,

with appropriate changes in peak and baseflow magnitudes.

Direct drilling is represented by increased overland flow resistance, increased soil

porosity and decreased evapotranspiration. In the Cobres catchment there is a

moderate increase in runoff and a significant reduction in sediment yield. Hydrograph

peaks are reduced and baseflow is increased. In the Agri catchment there is rather less

impact, corresponding to the smaller proportion of the catchment planted with wheatcompared with the Cobres catchment.

Afforestation is limited to the higher half of each catchment and is characterized by

trees with an increased evapotranspiration rate. The result is decreased runoff and

sediment yield. The hydrograph shape is maintained, with appropriate changes in peak

and baseflow magnitudes.

The future climate is drier and warmer. Consequently runoff and sediment yield

decrease.

For the purposes of the simulation, the farmer model crop data were adjusted so that

no one crop would be dominant under all conditions, thereby allowing the simulation

to show changes. However, the model output is sensitive to the data, so the results

discussed here should be considered as illustrative of model capability rather than the

most likely scenarios for the target areas. Under baseline conditions, the preferred

crop changes from year to year for the Cobres catchment, so that no one crop is

consistently more profitable than another. For the Agri catchment, pasture and olives

are preferred in certain parts of the catchment but there is no catchment dominant

crop. Removal of the wheat subsidy has relatively little effect in the Cobres catchment

and tends to increase the preference for pasture in the Agri catchment.

To summarize the results:

- Changes in monthly runoff and sediment yield are most noticeable in the autumn-

winter-spring period. Particularly in the Cobres catchment, the summer flows are

negligible in all cases. In the Agri catchment the differences remain significant

through the summer (e.g. abandoned land gives a higher summer baseflow);

- Change of land cover (abandoned land, afforestation) affects runoff total and

hydrograph magnitude, through altered evapotranspiration;

- Seed drilling can beneficially affect hydrograph shape and sediment yield (and isthe only case where sediment yield changes in the opposite direction to runoff);

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- Land use changes or seed drilling must be implemented over significant proportions

of a catchment if they are to affect the response at the catchment scale;

- The annual water balance is affected more by climate change than land use change

in the Cobres catchment but the impacts of the two changes are more equal in the Agricatchment, e.g. afforestation of the higher half of the Agri has the same effect as

climate change while abandoned land retains higher runoff relative to the baseline

condition even for the future climate. However, seed drilling in the Cobres catchment

does reduce sediment yield by an amount similar to that caused by climate change;

- At least for the crop data used, certain crops may dominate farmer choice in

particular parts of the catchment but there is no dominant choice of crop at the

catchment scale, suggesting that a mixture of crops is sustainable.

10 RECOMMENDATIONS FOR LAND MANAGEMENT GUIDELINES

Within the Mediterranean area, there is likely to be a trend towards a drier, warmer

climate, with reduced winter rainfall and increased summer evaporation (although the

trend may be masked by strong interannual variation). There should therefore be a

move towards land uses which minimize water requirements and evaporation. The

principal recommendations for land management are therefore :

- Plant crops or cover which minimize evaporation: large-scale afforestation should

therefore be avoided;

- Introduce agricultural techniques like seed drilling which may reduce evaporation

but, perhaps more importantly, reduce runoff peaks and increase baseflow, i.e. they

reduce variability and increase reliability of river flow;

- Subsidy levels can be manipulated so as to induce farmers to adopt crops and

techniques which are environmentally sustainable and also (because of the subsidy)

economically sustainable.

On a purely educational front, land use planners should be aware that large-scale

changes in crop type or land cover can significantly affect catchment runoff and

sediment yield.

11 CONCLUSIONS

Validation of the DSS against the impacts of past policies (Deliverable 26) showed

that the DSS can be used to explore the effects of subsidy changes on crop selection

and land use pattern. It may therefore be a useful tool in the formulation of

agricultural and land management policy.

The development of guidelines for land management from the scenario runs similarly

shows the relevance of the DSS to stakeholder interests. The DSS can be used to

explore the effects of different land management strategies within overall policy

constraints, for example to find a sustainable agricultural strategy sufficient to providefarmers with an acceptable quality of life.

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An important aspect of the project was to have been the involvement of local

stakeholders in the application of the DSS and the development of the guidelines for

sustainable land management. Because of the tighter project timetable caused by the

change in project research associate (Section 6.3.1), that involvement was not as

extensive as originally intended. Nevertheless consultation with the target area focusgroups (including a presentation of the Agri simulations to local stakeholders) ensured

that the work was relevant to the needs of the stakeholders. As a result, the scenario

simulations had local significance (e.g. direct seed drilling, removal of subsidies). In

addition, the consultations were a contribution to the transfer of existing research and

to the bridging of the communication gap between scientists, policy-makers, policy-

implementers and end-users, as recommended by the International Conference on

Mediterranean Desertification, held in Crete in 1996.

Discussions in the Alentejo region of Portugal showed that there was general interest

in sediment transport among relevant agencies and research groups, because of the

prevalence of soil erosion and topical concern about sedimentation of the newGuardiana reservoir and the resulting reduced sediment supply to the Guardiana

estuary. The cost of soil erosion was raised as a research issue, incorporating fertilizer

use, clearing ditches, reservoir sedimentation and reduced biodiversity. Stakeholder

interest in the Basilicata region of Italy concerned the allocation of water resources

between different users, including interbasin transfers.

12 REFERENCES

Basso, F., Bove, E. and Del Prete, M. 2002a. General description of the Agri basin,

southern Italy. In Mediterranean Desertification : A Mosaic of Processes and

Responses, N.A. Geeson, C.J. Brandt and J.B. Thornes (eds), Wiley, Chichester,

UK., 321-330.

Basso, F., Pisante, M. and Basso, B. 2002b. The Agri valley sustainable agriculture

in a dry environment: crop systems and management. In Mediterranean

Desertification : A Mosaic of Processes and Responses, N.A. Geeson, C.J. Brandt

and J.B. Thornes (eds), Wiley, Chichester, UK., 331-346.

Bathurst, J.C., Kilsby, C. and White, S. 1996. Modelling the impacts of climate and

land-use change on basin hydrology and soil erosion in Mediterranean Europe. In

Mediterranean Desertification and Land Use, C.J. Brandt and J.B. Thornes (eds.),Wiley, Chichester, UK, 355-387.

Bathurst, J.C., Sheffield, J., Vicente, C., White, S.M. and Romano, N. 2002.

Modelling large basin hydrology and sediment yield with sparse data : the Agri

basin, southern Italy. In Mediterranean Desertification : A Mosaic of Processes

and Responses, N.A. Geeson, C.J. Brandt and J.B. Thornes (eds), Wiley,

Chichester, UK, 397-415.

Bathurst, J.C., Sheffield, J., Leng, X., and Quaranta, G. 2003. Decision support system

for desertification mitigation in the Agri basin, southern Italy. Physics and Chemistry

of the Earth, 28, 579-587.

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Bathurst, J.C., Ewen, J., Parkin, G., OConnell, P.E., and Cooper, J.D. 2004. Validation

of catchment models for predicting land-use and climate change impacts. 3. Blind

validation for internal and outlet responses.Journal of Hydrology, 287, 74-94.

Beven, K. 1989. Changing ideas in hydrology the case of physically-based models.

Journalof Hydrology, 105, 157-172.

Kosmas, C., Danalatos, N.G., Lpez-Bermdez, F. and Romero Daz, M.A. 2002.

The effect of land use on soil erosion and land degradation under Mediterranean

conditions. In Mediterranean Desertification : A Mosaic of Processes and

Responses, N.A. Geeson, C.J. Brandt and J.B. Thornes (eds), Wiley, Chichester,

UK, 57-70.

Loureno, N., Correia, T.P., Jorge, M.do R. and Machado, C.R.1998. Farming

strategies and land use changes in Southern Portugal: land abandonment or

extensification of the traditional systems? Mediterrneo (Instituto Mediterrnico,

Universidade Nova de Lisboa), Nos 12/13, 191-208.

Mairota, P., Thornes, J.B. and Geeson, N. 1998. Atlas of Mediterranean Environments

in Europe: The Desertification Context. Wiley, Chichester, UK, 205 pp.

Roxo, M.J., Casimiro, P.C. and Brito, R.S.de.1996. Inner Lower Alentejo field site:

cereal cropping, soil degradation and desertification. In Mediterranean

Desertification and Land Use, C.J. Brandt and J.B. Thornes (eds.), Wiley,

Chichester, UK, 111-135.

Roxo, M.J., Mouro, J.M. and Casimiro, P.C. 1998. Polticas agrcolas, mundanas de

uso do solo e degradaao dos recursos naturais Baixo Alentejo Interior.

Mediterrneo (Instituto Mediterrnico, Universidade Nova de Lisboa), Nos 12/13,

167-189.

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APPENDIX A

SIMULATION DATA FOR THE COBRES

TARGET BASIN

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ANNUAL DISCHARGE TOTALS

COBRES

Monte da Ponte area = 701 km**2

Measured Simulated Runoff

Rainfall PE Runoff Current Future Current Future Current Future Current Future

Year (mm) (mm) (mm) (mm) (mm) (mm) (mm) (mm) (mm) (mm) (mm)

1995 538.28 1835 146 172 79 199 99 181 86 155 68

1996 867.13 1536 399 456 286 511 305 456 297 429 269

1997 820.48 1602 343 387 243 417 262 423 262 367 221

1998 355.05 1593 62 82 63 103 69 85 64 77 58

Average 645.24 1641 238 274 168 307 184 286 177 257 154

COBRES

Albanoa area = 172 km**2




1995 159 167 62 198 84 172 73 155 57

1996 432 440 297 504 314 454 308 424 282

1997 412 401 266 435 285 441 280 385 248

1998 90 88 65 111 75 96 67 86 62

Average 273 274 173 312 189 291 182 263 162

COBRES

Entradas area = 51 km**2




1995 168 157 54 187 72 163 65 135 45

1996 443 407 279 460 291 423 292 379 253

1997 397 334 224 361 240 371 235 308 193

1998 83 61 50 66 55 65 50 58 46

Average 273 240 152 269 165 256 161 220 134

Base Abandoned Direct Drilling A ff orestation



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ANNUAL SEDIMENT YIELD

COBRES

Monte da Ponte area = 701 km**2

Measured Simulated Sediment Yield


Year (mm) (mm) (mm) (t/ha/yr) (t/ha/yr) (t/ha/yr) (t/ha/yr) (t/ha/yr) (t/ha/yr) (t/ha/yr) (t/ha/yr)1995 538.28 1835 - 0.45 0.17 0.51 0.22 0.25 0.08 0.41 0.14

1996 867.13 1536 - 0.86 0.48 0.96 0.50 0.49 0.28 0.81 0.45

1997 820.48 1602 - 1.23 0.57 1.29 0.64 0.64 0.27 1.16 0.49

1998 355.05 1593 - 0.16 0.11 0.20 0.12 0.07 0.05 0.15 0.10

Average 645.24 1641 - 0.68 0.33 0.74 0.37 0.36 0.17 0.63 0.30

COBRES

Albanoa area = 172 km**2



Year (mm) (mm) (mm) (t/ha/yr) (t/ha/yr) (t/ha/yr) (t/ha/yr) (t/ha/yr) (t/ha/yr) (t/ha/yr) (t/ha/yr)

1995 - 0.17 0.06 0.20 0.08 0.09 0.03 0.16 0.05

1996 - 0.35 0.19 0.41 0.21 0.20 0.11 0.34 0.18

1997 - 0.69 0.27 0.73 0.33 0.30 0.11 0.66 0.25

1998 - 0.09 0.06 0.12 0.06 0.04 0.03 0.09 0.06

Average - 0.33 0.15 0.36 0.17 0.16 0.07 0.31 0.13

COBRES

Entradas area = 51 km**2




1995 - 0.08 0.02 0.09 0.04 0.05 0.01 0.07 0.02

1996 - 0.19 0.10 0.20 0.10 0.11 0.06 0.17 0.08

1997 - 0.32 0.13 0.33 0.15 0.15 0.05 0.28 0.091998 - 0.03 0.02 0.03 0.02 0.01 0.01 0.02 0.02

Average - 0.15 0.07 0.16 0.08 0.08 0.03 0.14 0.05




16


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Cobres Monte da Ponte

Simulated Average Monthly Discharge

Monte da Ponte

0

10

20

30

40

50

60

70

80

90

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

AverageMonthlyDischarge(mm)

Base

Abandonded

Afforestation

Direct Drilling

Monte da

0

10

20

30

40

50

60

70

80

90

Jan Feb Mar Apr May Jun Ju


Monte da Ponte

0

10

20

30

40

50

60

70

80

90



Base

Base - Future

Afforestation

Afforestation - Future

Monte da

0

10

20

30

40

50

60

70

80



17


17/36

Cobres Albenoa


Albanoa

0

10

20

30

40

50

60

70

80

90



Base

Abandonded

Afforestation

Direct Drilling

Albano

0

10

20

30

40

50

60

70

80

90



Albanoa

0

10

20

30

40

50

60

70

80

90



Base

Base - Future

Afforestation


Albano

0

10

20

30

40

50

60

70

80



18


18/36

Cobres Entradas


Entradas

0

10

20

30

40

50

60

70

80

90



Base

Abandonded

Afforestation

Direct Drilling

Entrad

0

10

20

30

40

50

60

70

80

90



Entradas

0

10

20

30

40

50

60

70

80

90



Base

Base - Future

Afforestation


Entrad

0

10

20

30

40

50

60

70

80



19


19/36


Simulated Average Sediment Yield

Monte da Ponte

0.0E+00

2.0E+06

4.0E+06

6.0E+06

8.0E+06

1.0E+07

1.2E+07

1.4E+07


AverageMonthlySedimentYield(Kg)

Base

Abandonded

Afforestation

Direct Drilling

Monte da

0.0E+00

2.0E+06

4.0E+06

6.0E+06

8.0E+06

1.0E+07

1.2E+07

1.4E+07

Jan Feb Mar Apr May Jun


Base

Base - Future

Abandonded

Abandoned - Future

Monte da Ponte

0.0E+00

2.0E+06

4.0E+06

6.0E+06

8.0E+06

1.0E+07

1.2E+07

1.4E+07


Av

erageMonthlySedimentYield(Kg)

Base

Base - Future

Afforestation


Monte da

0.0E+00

2.0E+06

4.0E+06

6.0E+06

8.0E+06

1.0E+07

1.2E+07

1.4E+07


Av


Base

Base - Future

Direct Drilling

Direct Drilling - Future

20


20/36

Cobres Albenoa


Albanoa

0.0E+00

2.0E+05

4.0E+05

6.0E+05

8.0E+05

1.0E+06

1.2E+06

1.4E+06

1.6E+06

1.8E+06

2.0E+06



Base

Abandonded

Afforestation

Direct Drilling

Albano

0.0E+00

2.0E+05

4.0E+05

6.0E+05

8.0E+05

1.0E+06

1.2E+06

1.4E+06

1.6E+06

1.8E+06

2.0E+06



Base

Base - Future

Abandonded

Abandoned - Future

Albanoa

0.0E+00

2.0E+05

4.0E+05

6.0E+05

8.0E+05

1.0E+06

1.2E+06

1.4E+06

1.6E+06

1.8E+06

2.0E+06


Av


Base

Base - Future

Afforestation


Albano

0.0E+00

2.0E+05

4.0E+05

6.0E+05

8.0E+05

1.0E+06

1.2E+06

1.4E+06

1.6E+06

1.8E+06

2.0E+06


Av


Base

Base - Future

Direct Drilling


21


21/36

Cobres Entradas


Entradas

0.0E+00

5.0E+04

1.0E+05

1.5E+05

2.0E+05

2.5E+05

3.0E+05



Base

Abandonded

Afforestation

Direct Drilling

Entrad

0.0E+00

5.0E+04

1.0E+05

1.5E+05

2.0E+05

2.5E+05

3.0E+05



Base

Base - Future

Abandonded

Abandoned - Future

Entradas

0.0E+00

5.0E+04

1.0E+05

1.5E+05

2.0E+05

2.5E+05

3.0E+05


Av


Base

Base - Future

Afforestation


Entrad

0.0E+00

5.0E+04

1.0E+05

1.5E+05

2.0E+05

2.5E+05

3.0E+05


Av


22


22/36


Simulated Discharge for

1st

October 1985 to 1st

October 1986

Simulated daily discharge - Monte da PonteOct 95 - Sep 96

0

5

10

15

20

25

15312 16312 17312 18312 19312 20312 21312 22312 23312

Hours from 1-8-83

DailyDischarge(mm)

BaseAbandoned

Afforestation

Direct Drilling

Simulated daily discharge - MOct 95 - Sep 96

0

5

10

15

20

25

15312 16312 17312 18312 19312 2031

Hours from 1-8-83

DailyDischarge(mm)

Simulated daily discharge - Monte da Ponte

Oct 95 - Sep 96

0

5

10

15

20

25

15312 16312 17312 18312 19312 20312 21312 22312 23312

Hours from 1-8-83

DailyDischarge(mm)

Base

Afforestation

Simulated daily discharge - M

Oct 95 - Sep 96

0

5

10

15

20

25

15312 16312 17312 18312 19312 2031

Hours from 1-8-83

DailyDischarge(mm)

23


23/36


24/36

Baseline Landuse

Initial Land Use Crop selection at the end of 1995

Crop selection at the end of 1994 Crop selection at the end of 1996

25


25/36

Subsidy Scenario

Initial Land Use Crop selection at the end of 1995


26


26/36

APPENDIX B

SIMULATION DATA FOR THE AGRI TARGET

BASIN

27


27/36

ANNUAL DISCHARGE TOTALS

AGRI

Gannano area = 1532 km**2




1985 1016 1363 - 324 302 387 356 335 305 299 287

1986 832 1327 - 139 112 220 187 134 114 112 90

1987 853 1348 - 121 91 213 179 114 95 93 68

1988 811 1364 - 128 94 224 185 122 98 96 68

Average 878 1351 - 178 150 261 227 176 153 150 128

AGRI

Pertusillo area = 585 km**2




1985 1257 1348 536 727 647 858 749 761 652 647 628

1986 1038 1302 320 537 449 663 584 523 460 471 396

1987 957 1332 313 354 278 488 404 342 281 272 205

1988 929 1353 321 302 239 441 377 294 269 227 163

Average 1045 1334 372 480 403 612 528 480 416 404 348

ANNUAL SEDIMENT YIELD

AGRI

Gannano area = 1532 km**2




1985 1016 1363 - 14.8 13.5 16.6 15.0 15.0 13.6 13.6 12.8

1986 832 1327 - 7.2 6.3 9.6 8.4 7.1 6.4 6.3 5.5

1987 853 1348 - 6.1 5.5 8.8 7.6 5.9 5.2 5.1 4.4

1988 811 1364 - 6.6 5.3 9.7 8.0 6.3 5.4 5.3 4.4

Average 878 1351 - 8.7 7.7 11.2 9.8 8.6 7.7 7.6 6.8

AGRI

Pertusillo area = 585 km**2




1985 1257 1348 - 9.8 6.5 12.0 7.1 9.8 6.5 7.9 6.4

1986 1038 1302 - 4.6 3.3 5.4 4.1 4.3 3.3 3.7 2.6

1987 957 1332 - 3.3 1.8 4.4 2.5 2.9 1.7 1.9 0.9

1988 929 1353 - 2.8 2.5 3.9 2.9 2.4 2.2 1.6 0.7

Average 1045 1334 - 5.1 3.5 6.4 4.1 4.8 3.4 3.7 2.6

Base Abandoned Direc t Dr illing Affores tation




28


28/36

Agri - Gannano


Gannano

0

10

20

30

40

50

60

Jan Feb Mar April May June July Aug Sep Oct Nov Dec


BaseAbandoned

Afforestation

Direct Drilling

Gannano

0

10

20

30

40

50

60

Jan Feb Mar April May June July


Gannano

0

10

20

30

40

50

60


A

verageMonthlyDischarge(mm)

Base

Base - Future

Direct Drilling


Gannano

0

10

20

30

40

50

60

Jan Feb Mar April May June July

A


29


29/36

Agri - Pertusillo


Pertusillo

0

20

40

60

80

100

120



BaseAbandoned

Afforestation

Direct Drilling

Pertusillo

0

20

40

60

80

100

120

Jan Feb Mar April May June Ju


Pertusillo

0

20

40

60

80

100

120


A


Base

Base - Future

Direct Drilling


Pertusillo

0

20

40

60

80

100

120

Jan Feb Mar April May June Ju

A


30


30/36

Agri - Gannano


Gannano

0.E+00

5.E+07

1.E+08

2.E+08

2.E+08

3.E+08

3.E+08

4.E+08

4.E+08



BaseAbandoned

Afforestation

Direct Drilling

Gannano

0.E+00

5.E+07

1.E+08

2.E+08

2.E+08

3.E+08

3.E+08

4.E+08

4.E+08

Jan Feb Mar April May June J


Gannano

0.E+00

5.E+07

1.E+08

2.E+08

2.E+08

3.E+08

3.E+08

4.E+08

4.E+08



Base

Base - Future

Direct Drilling


Gannano

0.E+00

5.E+07

1.E+08

2.E+08

2.E+08

3.E+08

3.E+08

4.E+08

4.E+08



31


31/36

Agri - Pertusillo


Pertusillo

0.E+00

1.E+07

2.E+07

3.E+07

4.E+07

5.E+07

6.E+07

7.E+07

8.E+07

9.E+07



BaseAbandoned

Afforestation

Direct Drilling

Pertusillo

0.E+00

1.E+07

2.E+07

3.E+07

4.E+07

5.E+07

6.E+07

7.E+07

8.E+07

9.E+07



Pertusillo

0.E+00

1.E+07

2.E+07

3.E+07

4.E+07

5.E+07

6.E+07

7.E+07

8.E+07

9.E+07



Base

Base - Future

Direct Drilling


Pertusillo

0.E+00

1.E+07

2.E+07

3.E+07

4.E+07

5.E+07

6.E+07

7.E+07

8.E+07

9.E+07



32


32/36

Agri - Pertusillo

Simulated Discharge for

1st

October 1985 to 1st

October 1986

Simulated hourly discharge into the Pertusillo reservoir

0

2

4

6

8

10

12

14

16

18

20

19008 20008 21008 22008 23008 24008 25008 26008 27008

Hours from 1-8-83

Discharge(mm)

BaseAbandoned

Afforestation

Direct Drilling

Run 6.1

Simulated hourly discharge into th

0

2

4

6

8

10

12

14

16

18

20

19008 20008 21008 22008 23008 2400

Hours from 1-8-83

Discharge(mm)

Run 6.1

Simulated hourly discharge into t he Pertusillo reservoir

0

2

4

6

8

10

12

14

16

18

20

19008 20008 21008 22008 23008 24008 25008 26008 27008

Hours from 1-8-83

Discharge(mm)

Base

Afforestation

Run 6.1

Simulated hourly discharge into th

0

2

4

6

8

10

12

14

16

18

20

19008 20008 21008 22008 23008 2400

Hours from 1-8-83

Discharge(mm)

Run 6.1

33


33/36

Agri

Monthly Sediment Yield

Base

0.00E+00

1.00E+08

2.00E+08

3.00E+08

4.00E+08

5.00E+08

6.00E+08

Jan-85

Mar-85

May-85

Jul-85

Sep-85

Nov-85

Jan-86

Mar-86

May-86

Jul-86

Sep-86

Nov-86

Jan-87

Mar-87

May-87

Jul-87

Sep-87

Nov-87

Jan-88

Mar-88

May-88

Jul-88

Sep-88

Nov-88

SedimentDischargekg

Gan

Pert

1985 198819871986 1989

Abandone

0.E+00

1.E+08

2.E+08

3.E+08

4.E+08

5.E+08

6.E+08

Jan-85

Mar-85

May-85

Jul-85

Sep-85

Nov-85

Jan-86

Mar-86

May-86

Jul-86

Sep-86

Nov-86

Jan-87

SedimentDischargekg

Gan

Pert

1985 19871986

Afforestation

0.E+00

1.E+08

2.E+08

3.E+08

4.E+08

5.E+08

6.E+08

Jan-85

Mar-85

May-85

Jul-85

Sep-85

Nov-85

Jan-86

Mar-86

May-86

Jul-86

Sep-86

Nov-86

Jan-87

Mar-87

May-87

Jul-87

Sep-87

Nov-87

Jan-88

Mar-88

May-88

Jul-88

Sep-88

Nov-88

SedimentDischargekg

Gan

Pert

1985 198819871986 1989

Direct Drill

0.E+00

1.E+08

2.E+08

3.E+08

4.E+08

5.E+08

6.E+08

Jan-85

Mar-85

May-85

Jul-85

Sep-85

Nov-85

Jan-86

Mar-86

May-86

Jul-86

Sep-86

Nov-86

Jan-87

SedimentDischargekg

Gan

Pert

1985 19871986

34


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Baseline Land Use

Initial land use



35


35/36

Subsidy Scenario

Initial land use



36


36/36

Documents

MEDACTION_cobres