WLI 1 st Regional Coordination Meeting (ICARDA, Aleppo, Syria, 13-15 February, 2011
WLI Regional Knowledge Exchange Workshop on Decision...
Transcript of WLI Regional Knowledge Exchange Workshop on Decision...
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WLI Regional Knowledge Exchange Workshop on Decision-support Tools and Models
23-27 September, 2013, Djerba, Tunisia
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Table of Contents Executive Summary .................................................................................................................................. 2
Introduction .............................................................................................................................................. 3
Strategic Approaches to Integrated Management of Water and Land Resources – Experiences of WLI
Partnering Countries ................................................................................................................................ 4
Tunisia .................................................................................................................................................. 4
Iraq........................................................................................................................................................ 6
Lebanon ................................................................................................................................................ 8
Palestine ............................................................................................................................................. 10
Jordan ................................................................................................................................................. 11
Yemen ................................................................................................................................................. 12
Egypt ................................................................................................................................................... 13
Expert Presentations on Selected Decision Support Tools and Models ................................................ 16
HidroMore .......................................................................................................................................... 16
Modflow ............................................................................................................................................. 17
Water Evaluation and Planning (WEAP) System ................................................................................ 18
Soil Water Analysis Tool (SWAT) ........................................................................................................ 21
CropSyst .............................................................................................................................................. 23
Soil Water Mass Balance Model and Optimization of Irrigation using Soil Water Sensors ............... 26
Field Visit ................................................................................................................................................ 27
Challenges to identify potential impacts of improved water productivity at larger spatial scales ........ 28
Information Dissemination ..................................................................................................................... 33
Economic analysis of improved water management techniques .......................................................... 33
Overview of WLI Annual Reporting and Workplanning ......................................................................... 34
Conclusion .............................................................................................................................................. 35
Appendix 1: Agenda ............................................................................................................................... 36
Appendix 2: Map for site visits ............................................................................................................... 40
Appendix 3: List of participants of the workshop .................................................................................. 41
Appendix 4: List of participants in breakout sessions ............................................................................ 42
Appendix 5: Outline for the Regional Knowledge Exchange on Decision-support Tools and Models ... 43
Appendix 6: Definitions of selected WLI FtF Indicators ......................................................................... 47
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Executive Summary
The goal of WLI is to improve the livelihoods of households and communities by pilot-testing
sustainable water, land use and livelihood strategies in selected benchmark sites of eight
participating countries for scaling up. Various decision support tools are used by partnering
countries to assess and identify the best strategies for sustainable management of water and
land resources, and present to policy makers.
The workshop created a platform for partnering countries to share their experiences with
various models for water and land management as applied in their specific context, discuss
challenges, explore compatibility and comparability of the various models used within the
WLI, and to assess their potential application to address regional water and land management
related challenges. Decision-making tools considered during the workshop include Soil and
Water Assessment Tool (SWAT), Water Evaluation and Planning (WEAP), CropSyst,
Aquacrop, Modflow, Hidromore, as well as economic analysis tools such as Cost-Benefit
Analysis for improved water management techniques.
The workshop was attended by WLI Team leaders and bio-physical team members from seven
partnering countries (Annex 3). Also in attendance was Dr. Srinivasan from Texas A&M
University (TAMU) one of the developers of SWAT. The thematic group on modeling, led by
Dr. Nahla Zaki from the National Water Resource Center (NWRC) of Egypt, was activated
during the workshop. The group is expected to encourage comparative research in cases where
there are similarities of models and contexts, promote collaboration among WLI partnering
counties including data sharing and making use of student exchange programs, facilitate
engagement of partnering US universities, and identify needs for capacity building.
The five-day workshop was also very useful in identifying common challenges that need
further research and recommendations to begin tackling them including challenges of scale
(national versus site specific data needs), uncertainty and variability especially as it applies to
downscaling climate data, inter-sectoral collaboration to assess water demand and use by
different sectors, and understanding complex water resource bases such as groundwater and
reusable water resources. Discussions of the challenges resulted in the identification of five
key topics for regional knowledge exchange as well as potential decision support tools that
could help address them (Table 7).
Future knowledge exchange workshops on the topic will build on the success of this workshop
and contribute to the advancement of scientific knowledge on modeling water and land
management strategies, as well as adaptation and application of various models to fit regional
bio-physical and socio-economic conditions.
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Introduction
The Water and Livelihood Initiative (WLI) organized the workshop in order to exchange
knowledge on decision support tools as instruments to validate and out-scale land and water
management strategies. Specifically the objectives included:
- Review available assessments of present and future water availability and use at the
watershed and basin-scale and identify scope for updates to reflect the full potential of
improvements in on-farm land and water management
- Inform regional decision-makers and other key stakeholders at the benchmark sites of
the relevance and potential further use of outputs from decision support tools to
evaluate options for improved management of land, water and livelihoods
- Stimulate knowledge exchange and research collaboration amongst WLI research
teams using and developing tools to support integrated water and land-use strategies
with key stakeholders
Discussions mainly focused on various decision-support tools that are currently used by
partnering countries, and the identification of alternative or complimentary models.
The workshop began with opening statements from Dr. Mohammed Ouessar (on-behalf of Dr.
Houcine Khatteli –Director General of IRA), Dr. Theib Oweis - Director of the Integrated
Water and Land Management Program (ICARDA), Professor Netij Ben Mechlia from INAT,
Dr. Nahla Zaki from National Water Resource Center (Egypt) representing the WLI thematic
group on Modeling, and Dr. Hamed Daly on-behalf of Dr. Ben Salem – Director General of
INRAT, and Dr. Caroline King – WLI Manager. Other participants included WLI team
leaders and bio-physical team members from partnering National Agricultural Research and
Extension Services (NARES) in Egypt, Iraq, Jordan, Lebanon, Palestine, Tunisia and Yemen;
Dr. Raghavan Srinivasan from Texas A&M University (TAMU), and selected scientists from
ICARDA‟s Integrated Water and Land Management Program (IWLMP). Participants from
Syria were not able to attend the workshop. Please refer to Appendix 3 for a complete list of
participants.
A brief presentation on the overall objectives of the workshop was given by Dr. King, who
emphasized the importance of using decision support tools to make watershed-level
projections of potential benefits of pilot tested water and land management strategies. The
tools, it was explained, can be used to influence policy makers by using current status of water
balance such as volume of water used or volume of water available, to predict future outcomes
with and without adoption of recommended water and land management practices (Figure 1).
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Figure 1: Excerpt from Dr. King‟s presentation
Strategic Approaches to Integrated Management of Water and Land
Resources – Experiences of WLI Partnering Countries
Discussions on strategic approaches to integrated management of water and land resources
were initiated by presentations from partnering WLI countries, and are summarized below in
the order of their presentations.
Tunisia
The Tunisian team presented on the three sites located in the south, central and northern part
of the country representing different gradients of aridity.
South Tunisia (Presented by Dr. Mohamed Ouessar, IRA): represents the arid site located in
Medenine/Tataouine where rainfall ranges between 160-200 mm from the east plain of Jeffara
to the central part in the mountain of Beli Khedache, and can be as low as 100 mm in the
western plateau of Dhahar. Land use in the area was characterized as covered with olives and
small scale irrigation in the East, fruit trees behind water harvesting structures in the center,
and the rangelands in the west. The team gave a broad overview of their research in the area
focusing on their experience in using HidroMore to model vulnerability of olive groves to
climate change, and AquaCrop to model effects of climate change on the production of citrus.
Follow up discussions focused on application of Deficit Irrigation (DI) for citrus trees and
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advantages of using AquaCrop. The team reported that they have found AquaCrop to be user-
friendly and a strong decision support tool to model water, crop growth and climate change as
it requires less data, accounts for carbondioxide (CO2), and salinity.
Central Tunisia (Presented by Dr. Hamed Daly, INRAT): The study site is located in Sidi
Bouzid which represents a semi-arid agro-ecosystem with about 220 mm of rainfall, hot dry
winds, and extensive dependence on groundwater resources (deep well) for drinking and
irrigation. The main source of agricultural income for the area is livestock, followed by
cereals, olives and cactus. Main challenge for farmers is high cost of inputs particularly animal
feed. The team uses CropSyst and Canadian GCM to project potential impacts of climate
change on production of selected crops. Follow up discussions focused on data collection
including amount and type of data required to use CropSyst. The team acknowledged the need
for historical data and also explained how additional data could be gathered by downscaling
climatic data and accounting for climate variability for precipitation.
North Tunisia (Presented by Dr. Asma Larsam, INAT): The site is located in a semi-arid area
with a relatively higher level of annual rainfall ranging between 350-450 mm. 85% of the
national citrus production is from this region and heavily relies on ground water extraction
through private wells or surface water purchased by farmers from the public water network.
The team is promoting Supplemental Irrigation (SI) and other strategies to manage rainfed
agriculture. They use AquaCrop to model water productivity and harvest index HI for cereals,
CropSyst and empirical relationships between yields and total water reduction for citrus, and
GR/SWAT to model runoff following adoption of various water management strategies.
Follow up discussions focused on the benefits of each model and the need to model changes in
water, CO2 and other parameters. The Egyptian team has offered to share their experience
with the team regarding model selection criteria.
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Iraq (Presented by Dr. Bassam Kanaan Abdul Jabbar)
The Abu Ghraib benchmark site, located west of Baghdad, represents an irrigated benchmark
site with an average rainfall of about 123mm/year. As in the case of most irrigated areas in the
region, water demand at the site exceeds the supply (Figure 2). According to Dr. Jabbar, 80%
of the irrigation water comes from the network, 17% from wells, and the remaining 3% from
drainage water.
Figure 2: Rate of flow in Abu Ghraib scheme during the period 2005-2013(m3/sec) –(An
excerpt from Dr. Jabbar‟s presentation)
Achievements over the past two years were summarized as follows:
Increased water productivity and yield due to changes in the number of irrigation
during filling stage (Figure 3)
Increased yield in eggplants (Solanum melongena L.) and cauliflowers grown under
subsurface drip irrigation as compared to those grown under surface drip irrigation and
furrow or traditional irrigation practices. Increase in yield and water productivity for
cucumbers and tomatoes grown under protected agriculture (Greenhouses) with
monitored application of foliar amino acids, organic extracts
Improved water productivity of Berseem, a forage crop, due to application of amino
acids and organic extracts.
Calculated gross margin per ha for a number of crops including wheat, barley, sheep
and various vegetables
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low
(
MC
M)
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Figure 3: Water Productivity of vegetables and crops – kg/m3 (Excerpt from Dr. Jabbar‟s
presentation)
Follow up discussions highlighted the need to report on levels of water productivity with and
without application of improved technologies, and adding a time frame for the gross margin
calculations as these are bound to change with changes in price, etc. The team was also
encouraged to step up their efforts in using extension to disseminate pilot-tested and proven
technologies.
0100200300
Wat
er
pro
du
ctiv
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(Kg
/ M
3)
Vegetable crops
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Lebanon (Presented by Dr. Ihab Jomaa and Eng. Randa Massaad from LARI, and Dr. Hadi Jaafar
from AUB)
The El Qaa benchmark site in Lebanon represents a rainfed agro-ecosystem. The team
reported on two major activities including:
- Investigation of water availability at the benchmark area, and water distribution
schemes analysis study (Figure 4),
- NDVI and FOV temporal and spatial changes during the 21st century – A GIS and
Remote Sensing (RS) approach
- Irrigation/rainfed (micro level water harvesting) strategies including najarims micro
catchments and Semi-circular bunds
Figure 4: Water sources for El Qaa Village (An excerpt from Dr. Jomaa‟s presentation)
Dr Jaafar presented a GIS and RS based appraoch to assess Net Difference Vegetation Index
(NDVI) and Fraction of Vegetation (FOV) temporal and spatial changes during the period
2000-2013. The study area in Qaa covered 17,838 ha and used Landsat 5, 7 and 8 as data
source (Figure 5).
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Figure 5: FOV Time Series-Mean and Std. Dev. (An excerpt from Dr. Jaafar‟s presentation)
Based on the study, Dr. Jaafar concluded that an increase in fraction of vegetation cover (due
to agricultural land expansion) will result in an increase in evapotranspiration and less
downstream flow to lower parts of the Orontes.
The third presentation was made by Eng. Massaad and focused on the team‟s efforts to
demonstrate the benefits of using conservation agriculture or zero-tillage as compared to
conventional practices. On-farm pilot testing of conservation agriculture was carried out on 2
dunum of land and compared with 2 dunum of land under conventional farming practice. The
fields were planted with durum wheat (Lahn). Preliminary results of the study showed higher
numbers of seed, biomass and straw collected from the field with zero-tillage. The team is
currently putting together a booklet to disseminate their findings.
Follow up discussions focused on difficulties related to trans-boundary characteristics of the
benchmark watershed as well as security problems related to the situation in neighboring
Syria.
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0.080
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Frac
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Time Period (2000- 2013)
MEAN
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Palestine (Presented by Dr. Mohamed Selmyah)
The presentation focused on pilot tested land and water management strategies in the
rangeland and rainfed benchmark sites of Tammun and Adaherya (in Hebron). These included
construction of various water harvesting structures and development of suitability maps to
identify appropriate areas to out-scale pilot tested water and land management strategies. The
team also developed land use/land cover analysis of the benchmark on the basis of which they
classified the land as agricultural, natural, urban, and industrial areas (Table 1).
Table 1: Land use/Land cover classification for the WLI benchmark sites of Taman and
Hebron (An excerpt from Dr. Selmyah‟s presentation)
Land use/Land Cover Class
Benchmark sites
Tammun Hebron
Dunum % of total Dunum % of total
Arable land 5439 21.06 10871 41.11
Inter cropping agricultural areas 322 1.24 0 0.00
Permanent crop 466 1.80 770 2.91
Plastic houses 1 0.01 2 0.01
Agriculture 6228 24.1 11643 44
Open spaces with little or no vegetation 17758 68.74 13629 51.54
Shrub and/or herbaceous vegetation
associations 1595 6.17 0 0.00
Forests 0 0.00 34 0.13
Natural land 19353 74.9 13663 51.7
Palestinian Built-up Area 134 0.52 868 3.28
Israeli Military Base/Settlements 116 0.45 6 0.02
Wall zone 0 0.00 10 0.04
Urban Fabric 249 0.96 884 3.34
Industrial, commercial and transport unit 1 0.00 3 0.01
Mine, dump and construction sites 0.45 0.00 249 0.94
Total area 25832 100 26442 100
Security challenges related to accessing different areas outside of “Zone C” was highlighted as
a major challenge.
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Jordan (Presented by Dr. Yasser Mohawesh)
WLI in Jordan operates in the Muhareb watershed in the Jordanian Badia (Mejedeyae) that is
characterized by very low but high intensity average annual rainfall that cause runoff and
erosion. Various water harvesting technologies including contour ridges, check dams, sub-
surface dam, vallerani, and marabs are pilot tested at these sites to optimize the benefit of
available rainwater for crop production, recharge aquifers, and to reduce soil erosion. The
team is trying to adapt the SWAT model, originally designed to capture land cover impact
with weather, soil, topography, and vegetation data within the context of large-river basins, to
estimate the effect of water harvesting on the reduction of soil erosion and runoff in arid
conditions (Figure 6).
Figure 6: Parameters modified in SWAT to fit arid conditions (An excerpt from Dr. Yasser‟s
presentation)
The team is still collecting data for the SWAT model at four sites with four different water
harvesting techniques and is twigging the model to develop a robust model that can be scaled
out in similar areas in the region. Preliminary results indicate that the water harvesting
interventions are reducing soil runoff, and erosion. Follow up discussions focused on the
research time needed to build the model, and preliminary results generated to date. The team
explained that modeling will help select appropriate sites for application of different water
harvesting interventions, and to monitor runoff and sediments from areas with and without
intervention.
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Yemen (Presented by Dr. Khader Atroosh)
WLI in Yemen operates in two wadies within the Delta Abyan – Wadi Bana and Wadi Hassan
– where floods draining from the two catchments serve as the main source of both surface and
ground water resources. Water and land management strategies for the area are devised based
on multi-secotral collaboration involving both the public and private sector in the area. To date
the team has assessed water resources based on 60 years data on water flow (Table 2), updated
soil and land use classifications, and has prepared land suitability maps for the main crops in
the area. The team has also managed to improve production of forage (lipid and sorghum) by
promoting supplemental irrigation of spate irrigated fields. Follow up discussions focused on
the importance of having a good understanding of water balance in the benchmark site and
challenges in accessing historical data. Importance of collaborating with relevant ministries
and other governmental institutions working in the area was emphasized as a strategy to
strengthen data mobilization efforts.
Table 2: Overall Water Balance in the Abyan Delta (Excerpt from Dr. Atroosh‟s presentation)
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Egypt (Presented by Dr. Samar Atthar)
WLI in Egypt operates in three irrigated sites located in the Old, New and Salt affected lands
within the Nile Delta. The team strives to improve water productivity by introducing improved
water and land management strategies based on a sound understanding of the irrigation system
(about 200 years old). Over usage of water is a common problem in Egypt often exasperating
on-farm salinization problems. According to Figure 7 below the Water Use Index (WUI) is
greater than 1 in both Habib and Sabia mesqas indicating higher volume of water use as
compared to actual demand at the tertiary levels.
Figure 7: Assessing sustainability of the irrigation system (Excerpt from presentations made
by the Egypt team)
Current research activities are thus focused on modeling the sustainability of the irrigation
system, particularly looking at the gap between on-farm irrigation management and general
irrigation network management; analysis of on-farm soil degradation due to farmers‟ irrigation
and land management practices; and assessing effects of water constraint on crop selection and
subsequently farmers‟ income in the New Land. The latter is a collaborative research with the
International Water Management Institute (IWMI).
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The team is using Water Productivity (WP) Optimizer, an integrated modeling framework to
analyze water productivity and environmental impacts of irrigation practices starting from the
field-scale and progressing to the scale of tertiary canal irrigation zones. The model was
selected based on rigorous selection criteria that compared eight related models (Table 3). WP
Optimizer is developed and coded by VB.Net using ArcGIS 10 tools for Windows 7. The
model covers the entire tertiary canal system and is fed by two other models that assess - (i)
on-farm irrigation networking, and (ii) SaltMed – an on-farm water management model
developed by (Ragab 2002) as a generic model that can be used for a variety of irrigation
systems, soil stratifications, crops and trees, water management strategies (blending or cyclic),
leaching requirements and water quality. WP-Optimizer model can thus assess three levels of
water productivity – on-farm, small canal or mesqa level, and tertiary level (Figure 8). Among
the expected outputs of the model are data on current water usage including water used by end
users, water used for groundwater recharge, water lost in irrigation system, and drainage water
(quantity and quality).
The team plans to include branch canals in its next calibration of the model. Plans to use
AquaCrop to model and study effects of applying deficit irrigation on major field crops and
potential effects of climate change in the old land was also proposed.
Table 3: Criteria used for selecting most suitable on-farm model (Excerpt from presentations
made by WLI Egypt team)
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Figure 8: WP-Optimizer structure and theoretical basis (Excerpt from presentations made by
WLI-Egypt team)
Follow up discussions focused on the following key points:
Assessing sustainability of irrigation – what do we mean by it and what is the best way
to do it? It was agreed that what can be assessed is the sustainability of the „irrigation
system‟.
Model selection: the advantages and risks of building new models. It was agreed that
the added value of modeling should be clearly articulated, and the output usable to
influence policy makers.
Importance of conducting multi-sectoral research that equally engages socio-
economists, hydrologists, the community, etc. to establish a good understanding of
social and cultural conditions that influence irrigation practices, and to ensure that our
findings/recommendations are transmitted and adopted.
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Expert Presentations on Selected Decision Support Tools and Models
HidroMore Potential contributions on use of HydroMore model in olive groves vulnerability to climate
change
Ms. A Hachani, Dr. M. Ouessar, and A. Zerrim (IRA)
Thirty percent of arable land in Tunisia is used to grow olives a major contributor to the
national GDP. However, olive trees are very sensitive to climate change.
Ms Hachani presented a case study conducted in the watershed of Oum Zessar, Medenine
(South East Tunisia) where she used HidoMore to develop climate change induced adaptation
strategies for olive trees. HidroMore is a hydrological model for operational estimates of
recharge and actual evapotranspiration based on water balance equation.
Parameters of the model were based on previous studies while actual calibration was based on
other models including- Geophysical Fluid Dynamics Laboratory (GFDL) used to simulate
and improve understanding and predictability of the behavior of the atmosphere and HiRAM
C 360 – a GFDL Global High Resolution Atmospheric model. Normalized Difference
Vegetation Index (NDVI) images downloaded from USGS were also used after geometrical
and atmospherically corrections.
The modeling exercise revealed that in comparison with the reference period (1996-2005) the
years 2030 and 2090 will experience an increase in temperature (1°C) and (5°C), rainfall will
decrease by (5.4%) and (20%) respectively. Reference Crop Evapotranspiration (ET0) will
increase by (3%) and (9%), and crop evapotranspiration under non-standard conditions
(ETCadj) will reduce by (2%) and (18%) respectively. Thus, it is expected that suitable land
for olive cultivation will shrink and the cropping system become increasingly problematic and
unsustainable.
Follow up discussions focused on data selection and extrapolation, particularly daily NDVI
data that can be inferred from one-point monthly data. The practicality of using NDVI data for
baseline in climate change simulations was questioned because NDVI will change in time as
plants adapt to new climatic conditions. The possibility of using supplemental irrigation to
increase water availability for existing olive groves while discouraging expansion into
marginal lands was also discussed. Participants were encouraged to carefully consider data
limitations and the added value of using a particular model before investing their time and
resources in calibrating a model.
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Modflow Modflow utilization for the management of Saharan aquifers
Prof. Mounira Zammouri - Faculty of Sciences of Tunisia(FST)
Modflow is a modular finite difference groundwater simulation model code developed by the
US Geoplogical Surveys (McDonald and Harbaugh 1988) on the basis of which several
softwares including Visual Modflow, Processing Modflow, GMS, etc. were developed.
Prof. Zammouri presented on the application of Modflow piloted by the “Observatoire du
Sahara et du Sahel (OSS)” to assess the impact of the long-term (2000-2050) implications of
existing and planned water extraction plans for the Saharan aquifer also known as Système
Aquifère du Sahara septentrional (SASS). The groundwater resource basin is shared by
Algeria, Tunisia and Libya (Figure 9). The model was calibrated for the period 1950-2000 in
order to adjust for geological and hydrological system parameters on the basis of which the
simulation model was extended to the year 2050 with various management alternatives
modeled according to the planned extraction projects in the three countries. Assessment of
current and projected levels of abstraction and recharge indicate that water outflow far exceeds
rate of inflow. Implications of this imbalance were also seen in increased level of salinity,
vanishing natural springs, degradation of groundwater quality. Based on the findings, the
study recommended that immediate measures be taken to limit salinization including –
revising planned extraction projectes in the south of the Nefzawa region, increasing irrigation
efficiency, and implementation of effective drainage measures.
Figure 9: Groundwater basin shared by Algeria, Tunisia and Libya (Excerpt from Dr.
Zammouri‟s presentation)
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Follow up discussions focused on challenges of measuring recharge as well as the benefits and
challenges of conducting cross-boundary research. For this particular case it was explained
that the current rate of recharge is already negligible and is not expected to increase
considering anticipated reduction in rainfall due to climate change.
Water Evaluation and Planning (WEAP) System Dr. Vinay Nangia (ICARDA) –Introduction and Application
WEAP is a GIS based integrated water resource planning system that uses graphical drag and
drop interface. It uses basic physical simulation of water demands and supplies but can also
accommodate additional user-created variables and modeling equations (Figure 10). It has
scenario management capabilities and can be linked with spreadsheets and other models. The
modeling process begins with defining the study area and time steps for analysis, creating the
current account, creating a future scenario, and evaluating the results. The model has a number
of elements that require data entry and calibration (Table 4).
Figure 10: WEAP system elements (Excerpt from Dr. Vinay‟s presentation)
WEAP is a very useful model to conduct high level planning and strategic analysis at local,
national and regional levels; to model demand management, and prioritize water allocation.
However, WEAP is not a practical tool for daily operations and does not calculate least-cost
optimization of supply and demand. Examples of areas where WEAP offers a comparative
advantage include sectoral demand analyses, establish water rights and allocation priorities
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simulate groundwater and streamflow, track pollution, etc. WEAP can thus be used to assess
vulnerability and predict adaptability including vulnerability of water supplies to different
demographic, technological and climatological changes; and project alternative policy
scenarios for demand and supply management, predict implications for multiple and
competing demands on water systems, and evaluate policy outcomes.
Table 4: Water Demand-Shortage (Excerpt from Dr. Vinay‟s Presentation)
Various methods of estimating demand were also discussed including the per capita “unit”
water use method, agricultural demand (soil, plant, climate, and irrigation), and urban demand
(urban indoor and outdoor). On the supply side the model considers rivers, groundwater,
diversions (e.g. canals and pipelines), reservoirs and others, including desalination.
Participants were encouraged to look into the evaluation version of the model which is freely
available at http://www.weap21.org
Follow up discussions focused on data needs and adaptability of the model. Participants were
assured that the model is indeed user friendly and does not require a lot of data but generates
outputs that can readily be used by decision makers.
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Dr. Vinay also provided a practical example on how the model can be used for different
analysis using a study by Droogers et.al (2012)1 where SWAT was used to reflect on Water
Scarcity and Adaptation Options for 22 countries in the MENA Region (Water Outlook 2050).
The study, though at a general level, aimed to analyze detailed water supply and demand for
the years 2010-2050, and identify potential options to overcome water shortage. Data on water
availability (streams, reservoirs, groundwater) and needs (irrigation, domestic, and industry)
were combined with results from selected climate change and hydrological models and fed
into the WEAP model to analyze supply and demand options based on anticipated water stress
levels. The direct outputs of the model i.e. economic evaluation of the supply and demand
were used to identify potential adaptation strategies, estimate the cost of „adaptation‟, and
inform policy makers and end users of the resource.
Follow up discussion focused on challenges in accessing country specific data. Dr. Nangia
informed participants of the database on present land and water use for all countries that can
be accessed through PCR-GLOBWB. The data, however, will need to be complemented with
country specific datasets and more accurate data points.
1 Droogers, P., Immerzeel, W.W., Terink, W., Hoogeveen, J., Bierkens, M.F.P., Van Beek,
L.P.H., Debele, B. (2012) Water resources trends in Middle East and North Africa towards
2050 Hydrol. Earth Systems Science, 16, 3101–3114.
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Soil Water Analysis Tool (SWAT)
Connecting SWAT to other models to identify impacts of land management on
productivity and water use in evapotranspiration, groundwater recharge and surface
runoff
Dr. Raghavan Srinivasan (TAMU) and Dr. Feras Ziadat (ICARDA)
SWAT is a product of over 40 years of model development by the United States Department
of Agriculture (USDA). It is a daily time step distributed model that divides study areas into
Hydrologic Response Units (HRUs) based on soil, slope and land use (Figure 11). It is most
widely used to assess water quality, water supply, climate changes and landuse change.
SWAT is a continuous watershed simulation model originally built to capture land cover
impact with weather, soil, topography, and vegetation data within the context of large river
basins in semi-arid areas. SWAT has algorithms to simulate weather, hydrology,
sedimentation, plant growth, nutrients, pesticides, management, and bacteria.
Figure 11: Hydrologic Balance in SWAT (Excerpt from Dr. Srini‟s presentation)
Dr. Srini presented on the international applications of SWAT referring to a number of studies
conducted in various countries. Among the studies presented were the use of SWAT for flood
and drought prediction in Africa, and its application in Iran to assess the feasibility of applying
the „virtual water trade strategy‟ to alleviate water stress in the country.
Adaptability of SWAT to respond to land use changes overtime, applicability of the model for
small scale research studies, and its ability to predict sedimentation were questioned during
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the discussion session. Dr. Srini assured all that the model does accommodate all the concerns
and also spoke of a SWAT-Modflow hybrid which is now available to researchers worldwide.
Dr. Feras‟ presentation focused on the application of SWAT in Jordan giving participants a
more specific and detailed look into the model. Dr. Feras highlighted the challenges of
adopting the model to evaluate water harvesting systems in an arid environment. He spoke of
on-going research to modify the existing SWAT database and parameters to accommodate
biophysical conditions in arid areas including high intensity, sporadic, low rainfall that result
in extensive runoff and soil erosion. Dr. Feras explained that his research team is trying to
model the benefits of water harvesting interventions in the Jordan Badia including
groundwater recharge, decreased runoff, increased crop yield, and decreased erosion which
are not easily quantified. Dr. Feras explained that his research team is now trying to introduce
a new land use class in SWAT model for contour ridges, modified curve number, and heat
unit. So far the team have collected 2 years‟ worth of data on soil erosion and hope to replicate
the study in other similar environments within the MENA region.
23
CropSyst Improving water productivity in response to climate change: Setting targets
Dr. Maria Glazirina (ICARDA)
Dr. Maria‟s presentation focused on modeling water balance and water productivity using
CropSyst. The model is a multi-year, multi-crop, daily time step cropping systems simulation
model originally programed by Prof. C. Stöckle and R. Nelson (Figure 12). The model is
freely available and can be accessed through
http://www.bsyse.wsu.edu/CS_Suite/CropSyst/index.html
Figure 12: Input-output influxes in CropSyst (An excerpt from Dr. Glazirina‟s presentation)
It is based on the understanding of management interactions between plants, soil and weather
including phonological development, photosynthesis and growth, stress effects (water, N, salt,
and potassium), as well as root water uptake. The crop and soil processes in CropSyst are
presented in Table 5 below.
24
Table 5: Crop and soil processes in CropSyst (Extracted from Dr. Glazirina‟s presentation)
Crop Processes in CropSyst Soil Processes in CropSyst
Development
growth
light interception
net photosynthesis
biomass partitioning
leaf expansion
roots deepening
leaf senescence
water uptake
nitrogen uptake
water stress
nitrogen stress
light stress
water infiltration
water redistribution
runoff
evaporation
percolation
solutes transport
salinization
nitrogen fixation
residues fate
O.M. mineralization
nitrogen transformations
water erosion
amonia volatilization
ammonium sorption
The model provides:
generic crop-growth component as it allows adaptation/calibration to any crop, and
species and cultivars are characterized by a set of parameters which determine crop
response to the environment
link to the GIS-software Arc/Info (spatial application)
user-friendly reporting format for outputs such as MS-Excel and flexibility in levels of
reporting e.g. daily, seasonal, annual or topical
fast graphics viewer, and
CropSyst is very well documented, maintained and regularly updated. Moreover, the model
considers the influence of soil salinity and shallow groundwater table, allows using a finite
difference solution of Richard‟s equation to simulate water transport, and handles conservation
agriculture features (to some extent). Data requirements from the model include various soil,
weather, land management practices, crops, and water sources. Please see Figure 13 below for
more information on specific features of the data required.
25
Figure 13: CropSyst data requirements (An excerpt from Dr. Glazirina‟s presentation)
Among other things, CropSyst can also calculate water balance, model crop growth under
different climate scenarios.
I. Water Balance: Water balance is calculated by using precipitation and irrigation as
incoming water and Evapotranspiration, infiltration of water and surface runoff or surface
drainage as outgoing water balance components. Various evapotranspiration models including
Penman-Monteith and Priestly-Taylor were discussed. Approaches to estimate surface runoff,
models to estimate soil water infiltration and redistribution (cascade and finite difference), and
soil hydraulics were also highlighted during the presentation.
II. Crop Growth: CropSyst models crop development i.e. the progression of a crop
through phonological stages through Growing Degree Days (GDDs) that govern crop
development and taking into account temperature, photoperiod, vernalization, and water
stress.
III. Climate change impact assessment: CropSyst can calibrate and evaluate crop grown
under currently prevailing climatic conditions in a selected agro-ecosystem and model the
impact of climate change on the crop‟s productivity using various climate change scenarios
including daily time-step weather data. The model also has the capacity to account for crop
growth (CO2 response), as well as water and temperature stress. This was demonstrated using
a case study on wheat grown in Central Asia.
Follow up discussions focused on challenges in accessing required data including daily
weather data, ability of the model to accommodate salinity and its potential effect on drought
and plant growth. The model was endorsed as being especially useful for modeling on-farm
water management practices within the context of irrigated agriculture.
26
Soil Water Mass Balance Model and Optimization of Irrigation using Soil
Water Sensors (Presented by Dr. Srini on behalf of Dr. Ashok Alva)
The presentation focused on an advanced on-farm irrigation measuring tool that can monitor
continuous real time soil water content such as Capacitance Probes. The technology is a Low
Energy Pressurized (LEP) system for irrigation and can be used to assess soil water content for
trees, vegetables and row crops like corns, soy beans etc. The probes can be spaced across
different spans and depth with minimal disturbance to the soil to determine the amount of
water applied and how much of it is retained in the soil. It is thus a very useful tool to assess
irrigation efficiency at the individual sensor level. Information from the data logger can be
accessed through telemetry, USB, or can even be linked to the irrigation system to regulate
irrigation scheduling. The probe offers various levels of data output ranging from real time
data per sensor or a group of sensors. The capability of the sensor was demonstrated through
case studies that used EnviroSCAN probes for potato in USA and for date palms in Kuwait.
Follow up discussions focused on accessibility and affordability of the technology for research
use by WLI partners. It was agreed that researchers should explore all options to determine the
right instrument taking into account its cost, simplicity, benefits it offers, environmental
sustainability, etc.
27
Field Visit
A field visit was organized by IRA offering participants an opportunity to see selected water
harvesting and irrigation management practices under field research. The visit began with a
brief presentation of IRA‟s research work in Tunisia and a tour of the Head Quarters. The
team was met and welcomed by Dr. Houcine Khatteli, Director General of the Institute. Other
site visits included irrigation management in Bedoui, Gabion check dams and recharge of
wells in Koutine (Figure 14), traditional Oasis in the mountains at Ksar Hallouf and water
harvesting in Ain El Anba.
Figure 14: Field visit of research on recharge of wells in Koutine
28
Challenges to identify potential impacts of improved water
productivity at larger spatial scales (i.e. landscape and watershed scales)
and over suitable time periods (1-year, 2-year, 5-year, 10-year)
The session was initiated by a short recap of progress and remaining challenges in identifying
potential impacts of improved water productivity at larger spatial scales presented by Dr.
Caroline King. Remaining challenges and proposed solutions were briefly discussed (Table 6).
Key challenges for future regional knowledge exchange were also discussed during this
session (Table 7). Please also refer to excerpts from Dr. Caroline‟s presentation below –
Figures 15 and 16.
Table 6: Summarized list of challenges and Modeling Options as presented by Dr. King
Predicting Future Water Productivity
Remaining Challenges Modeling Options
Scale Challenge
Diversity of land and water
conditions and qualities
Diversity of cropping patterns
Integrating crops and livestock
Other uses of water
Water reuse
Definition and measurement of
water consumption
(economic aspects, prices, future
uncertainties)
GIS
GIS and SaltMod
CropSyst
Work with economists
Work with farmers
Define our approach following
FAO 66
Assessment of Water Balance
Remaining Challenges Modeling Options
Integration of WLI data elements
Scale challenges
Temporal challenges for prediction
of future water availability
Uncertainty, variability and data
access (real and perceived)
Inter-sectoral cooperation
Some water sources less understton
i.e. groundwater, reusable
wastewater
Assess state of knowledge and gaps
Scale down from national water
balance assessments
Scale down from climate change
assessments
Use statistical techniques to fill
gaps and account for
uncertainty/variability
Refer to existing applications of
WEAP, enhance and contribute
Use SWAT to deepen
understanding of complex processes
in soil and water
29
Table 7: Key Challenges for future regional knowledge exchange (summarized from Dr.
King‟s presentation)
Key Topics Decision Support Tools to be explored
Modeling climatic effects in cropping systems including
trees (global climatic changes and regulation of the
microclimate for improved soil and crop productivity)
AquaCrop and Crop Syst
Modeling surface-groundwater interactions in rainfed
and irrigated agroecosystems
SWAT and Modflow
Assessing water productivity in integrated crop and
livestock systems
SaltMed & Economic Models
Improved land use CropSyst, Aquacrop
Modeling water productivity in saline conditions SaltMed
Reaching Decision Makers (cross-cutting for all) WEAP, cost-benefit analysis
For this session participants were divided into 2 groups with one group covering the irrigated
systems (led by Dr. Srini, TAMU) and the second group focusing on rangeland and rainfed
agro-systems (led by Drs. Feras Ziadat and Vinay Nangia ICARDA). Discussions focused on
the following points:
Research achievements over the past year at the country level and plans for 2014
Identification of common challenges and approaches to resolve the issue
Identification of opportunities for potential collaborations
Figures 15 and 16: Excerpts from Dr. Caroline‟s presentation
30
31
I. Irrigated agroecosystems – these included Iraq, Yemen, Tunisia, Lebanon and Egypt
Table 8: Achievements, workplans for 2014 and challenges for WLI partners under irrigated agroecosystems
WLI
Country
Achievements Workplans for 2014 Challenges/Needs
Iraq – Abu
Ghraib
Field experiments on various irrigation techniques
(supplemental, subsurface and drip irrigation) to assess
their effect of water productivity of selected crops and
vegetables including wheat, maize, tomato, cucumbers,
cauliflower and bersim.
Activities will focus on growing different crops such as
barley with the same irrigation system
Connecting pilot site technology to the
calculation of water productivity at
benchmarks level, selecting suitable
decision making model for their area,
convincing decision makers, collaboration
with other WLI teams.
Yemen –
Abyan Delta
Completed bio-physical characterization including land
use planning. Supplemental irrigation was also used to
increase yield and improve water productivity for
cotton, sesame, banana and papaya
Continue land use planning, transfer of technology to
farmers (field days) and communicate success with
decision-makers, and select appropriate models for
decision making.
Training in GIS and modeling to improve
land use planning, and downscaling
climate data.
Tunisia Field experiments are underway to assess effects of drip
irrigation on selected crops and vegetables grown in
sandy soil over relatively dry seasons. These include
potatoes, carrots, green beans and pepper. Experiments
were also conducted to assess the effect of deficit
irrigation and irrigation scheduling on improving water
productivity of citrus orchards in the South (Megarine)
and North (Beni Khalled). Moreover, the team is using
Aquacrop to model climate change impact and
assessing adaptation strategies on potatoes and wheat. y
Replicate experiments in farmers‟ fields –
demonstration plots, validate calibration of Aquacrop
to determine impact of CC on potato and wheat
production, develop field activities at the watershed
scale, improve communication strategies targeting
decision makers and other stakeholders. A workshop
for decision makers for the north, center and south plus
one on modeling will be organized in Tunisia.
The purchase of equipment (sensors) takes
time with ICARDA approval and this may
delay the introduction of irrigation
management based on real time soil water
sensors. The team needs suitable models
for heat, salinity and climate change and
workshop on modelling using Aquacrop
and CropSyst models
Lebanon Distribution efficiency of surface irrigation was
evaluated at two sites in Qaa, drip irrigation was used to
grow grapes and eggplants under deficit irrigation to
asses effects on water productivity. Furrow irrigation
was tested for wheat crop. Conservation agriculture and
supplemental irrigation were also launched.
Conduct trials on potato under drip irrigation using
mulching techniques and estimate evapotranspiration.
Introduce drought resistant varieties of tomatoes, and
use either WEAP or SWAT decision making models.
The team plans to organize 1 or 2 field days/workshops
and 1 or 2 publications
Training on modeling
Egypt The team has so far managed to monitor the irrigation
system and cropping patters, and is in the process of
building a model with the aim of improving water
productivity. Effects of farming practices on soil
compaction were also assessed.
Continue assessment & evaluation of the model for the
irrigation system focusing on downstream i.e. from
branch canals to farmers‟ fields, disseminate results of
soil compaction study, study causes of soil degradation
in the Old Land, use water productivity optimized
models for rice, alfalfa and other vegetables, improve
communication strategies with decision makers to
influence policy change on water use. Plan to have two
field days and national workshops.
Regional levels for modeling
32
II. Rangeland and rainfed agroecosystems: these include Tunisia, Palestine and Jordan
Table 9: Achievements, workplans for 2014 and challenges for WLI partners under rangeland and rainfed agroecosystems
WLI
Country
Achievements Workplans for 2014 Challenges/Needs
Tunisia
(Rangeland)
Progress in studying consumption of water in relation to
feed and exploring alternative livestock feeding options
Improve calibration & validation of CropSyst;
conduct cost benefit analyses of improved
technologies; introduce alley cropping of
olives and cactus (to increase feed availability
and reduce ET); estimate the effects of CC on
forage productivity and overall cropping
systems; collaborate with ICARDA (Dr.
Feras) on adapting SWAT in their watershed,
Establish a group of researchers to work on CC
(including partners from outside of Tunisia); lack
of information on ground water recharge – need
to work out best management of water flows
Jordan
(Rangeland)
Good progress in modeling SWAT and outscaling work
to be done in collaboration with UIUC; new shrubs
plated including vetches, barley, safflower, acacia and
artiplex; supplemental irrigation; erosion reduced at field
level,
Palestine
(Rainfed)
Tested new drought varieties of wheat (3) and barley (2);
capacity building in processing and packaging of cheese;
Lack of data required to calculate simple water
productivity; lack of resources to promote
adoption of improved technologies; water is
available at no cost to farmers;
Palestine
(Rangeland)
Conducted plant inventory to calculate biomass; pilot
testing different water harvesting technologies at suitable
sites selected by using GIS;
Assess financial feasibility of tested
technologies; introduce shrubs compatible
with introduced WH strategies; develop
strategies to influence; cost benefit analysis of
silage usage (project funded through FAO) in
order to upscale the strategy; prepare
extension brochures on silage, food processing
and water harvesting
Funding; activities limited to only Area C; lack of
data for modeling; need to include livestock in
their research
Projecting impact on water balance with and without improved water management practices Information Dissemination “Communicating potential impacts of improved water productivity on water balance at the
watershed scale to decision makers” by Prof. Mongi Sghaier (IRA)
Dr. Mongi‟s presentation focused on the importance of developing a sound communication
strategy that is based on the information needs of different stakeholders including targeted
decision makers, community members, farmers, etc. Direct engagement of scientists with
decision makers and end users of the research was emphasized as an essential foundation to build
trust, accountability and to demonstrate commitment. Importance of selecting appropriate
methods of communication including language to be used and mediums of communication were
also highlighted. Follow up discussions focused on various strategies that can be used to
disseminate research findings and methodologies to measure effectiveness of communication
strategies. In the case of the latter, it was agreed that appropriate indicators should be selected
and be part of the research plan.
Economic analysis of improved water management techniques
(Presented by Dr. Hamed Daly)
Dr. Daly‟s presentation highlighted the importance of using cost-benefit analysis to assess and
demonstrate private and social profitability (net benefits) of proposed water management
technologies to policy makers and potential end-users based on comparison of “with” and
“without” intervention scenarios. The challenges of quantifying impact, and predicting the
magnitude of annual incremental costs and benefits over the life span of the technology were
discussed, and alternative strategies to estimate benefits in economic terms explored. Dr. Daly
also explained the importance of discounting and conducing Sensitivity analysis to account for
risks and uncertainty. A general guideline to identify costs and benefits was provided (Table 10).
Table 10: Identification of costs and benefits (An excerpt from Dr. Daly‟s presentation)
Follow up discussions highlighted the need to consider qualitative benefits and explore other
multi-criteria analysis tools to make comprehensive assessments of accrued benefits.
34
Overview of WLI Annual Reporting and Workplanning (Ms Bezaiet Dessalegn)
An overview of the reporting guideline was presented by Ms Dessalegn the WLI Livelihood and
M&E Specialist. Different sections of the report were briefly discussed with particular emphasis
on expected reports on WLI selected Feed the Future (FTF) indicators listed below and detailed
under Annex 5:
Number of hectares under improved technologies or management practices as a result of
USG assistance
Number of farmers and others who have applied new technologies or management
practices as a result of USG assistance
Number of individuals who have received USG supported short-term agricultural sector
productivity or food security training
Number of food security private enterprises (for profit), producers organizations, water
user associations, women‟s groups, trade and business associations, and community based
organization (CBOs) receiving USG assistance
Number of stakeholders implementing risk-reducing practices/actions to improve
resilience to climate change as a result of USG assistance
Number of new technologies or management practices in one of the following phases of
development (Phase I/II/II representing work– under research/field testing/made
available for transfer)
Gross margin per unit of land, kilogram, or animal of selected product
Discussions also included definition of project beneficiaries, importance of gender and collection
of sex disaggregated data, and methods of summarizing FtF results across the quarters.
35
Conclusion
The five-day workshop was very useful in facilitating knowledge exchange on selected decision
making tools and water and land management strategies (including field visit to IRA managed
research sites on water harvesting and irrigation management), identifying common challenges
and seeking potential solutions to address them. The workshop was also very important in
identifying key topics for regional knowledge exchange. At the end of the workshop all
partnering countries confirmed that they will try to project cropping patterns, water volume, and
gross margins in their respective sites for the year 2014. The projection will be based on available
data and data to be generated in the near future.
The workshop ended with closing remarks from Dr. Nahla Zaki- leader of the WLI thematic
group on decision making tools, and Dr. King – WLI Manager. Dr. Nahla commended all
participants for their valuable contributions and expressed her confidence in continued
collaboration among the NARES, partnering US Universities and USDA. She offered a word of
encouragement to those who are building their own models and emphasized the need to explore
all other possibilities before embarking on such a rigorous task. The need to move to regional
scales through collaborative research on regional questions was also highlighted.
Dr. Feras encouraged all to tap into the expertise of US Universities through collaborative
research that could be done by graduate students from the region working with professors from
the US or vice versa. Dr. Srini confirmed his availability to provide guidance to the WLI team
should they require it. Dr. Monji stressed the importance of creating formal communication
channels among members of the thematic group and with the community to facilitate
collaboration to do comparative analysis and promote technology uptake.
Participants were encouraged to carefully consider the merits of each model, giving due attention
to their applicability in the context of specific agroecosystems, their compatibility and
comparability with other models, and the scale at which they will be most useful (field specific,
watershed scale, spatial and temporal, etc.). It was agreed that the team will explore livestock
analysis models as well as point scale models such as DSSAT which is currently used by
MAWRED across the region. Dr. Vinay was identified as a resource person for DSSAT.
36
Appendix 1: Agenda
WLI Regional Knowledge Exchange Workshop on Decision-support Tools and Models
23-27 September, 2013, Djerba, Tunisia Monday 23 September 8:00 – 9:00 Registration of participants 9:00 – 9:50 Opening session, Rapporteur: Dr. Vinay Nangia
Welcome address by Dr. Houcine Khatteli, Director General, IRA Statement by Dr. Theib Oweis, Director, Integrated Water and Land management Program (IWLMP), ICARDA Statement by Prof. Netij Ben Mechlia, on behalf of Director General, INAT Statement by Dr. Nahla Zaki, Thematic Group Leader Statement by Dr. Hamed Daly, on behalf of Director General, INRAT Overview of WLI and workshop objectives, by Dr. Caroline King, WLI Manager
9:50 – 10:00 Group picture 10:00 -10:30 Coffee break Strategic Approaches to Integrated Management of Land, Water and Livelihoods along an Aridity Gradient: Tunisia Chair: Dr. Nahla Zaki, (12 minutes presentation and 8 minutes Q&A for each) Rapporteur: Dr. Debra Turner 10:30 -11:30 Southern Tunisia
Central Tunisia Northern Tunisia
11:30 – 12:00 Discussions 12:00 – 13:00 Lunch Strategic Approaches to Integrated Management of Land, Water and Livelihoods at Different Levels of Aridity: Regional Chair: Dr. Hichem Ben Salem (12 minutes presentation and 8 minutes Q&A for each) Rapporteur: Dr. Mohamed Ouessar 13:00 – 14:00 WLI Iraq
WLI Lebanon WLI Palestine
14:00 – 14:30 Discussions
14:30 – 15:00 Coffee Break Expert Presentations on Selected Decision Support Tools and Models Chair: Dr. Theib Oweis (12 minutes presentation and 8 minutes Q&A for each) Rapporteur: Dr. Maria Glazirina 15:00 – 15:40 Hydromore – Dr. Ouessar et al. Modflow – Prof. Mounira Zammouri 15:40 – 16:10 WEAP – Dr. Vinay Nangia
37
16:00 – 16:40 Discussion Tuesday 24 September
Regional and International Exchange of Knowledge, Decision Support Tools and Models to Improve Integrated Management of Land, Water and Livelihoods Strategic Approaches to Integrated Management of Land, Water and Livelihoods: Regional Chair: Dr. Houcine Khatteli (12 minutes presentation and 8 minutes Q&A for each) Rapporteur: Dr. Hamed Daly 9:00 – 9:40 WLI Jordan
WLI Yemen 9:40 – 10:30 Discussions 10:30 -11:00 Coffee break Strategic Approaches to Integrated Management of Land, Water and Livelihoods: Regional Chair: Dr Netij Ben Mechlia, (12 minutes presentation and 8 minutes Q&A for each) Rapporteur: Dr. Maria Glazirina 11:00 – 13:00 WLI Egypt 12:00 – 13:00 Discussions 13:00 – 14:00 Lunch Challenges to set targets for effects of strategies under pilot testing on water productivity and water balance, Dr. Caroline King, WLI Manager Rapporteur: Dr. Debra Turner 14:00 - 14:30 Open Discussion 15:00 -15:30 Coffee Break Chair: Dr. Mohamed Ouessar Rapporteur: Dr. Vinay Nangia 15:30 - 17:00 Connecting SWAT to other models to identify impacts of land management on
productivity and water use in evapotranspiration, groundwater recharge and surface runoff (General overview and case study applications). Dr. R. Srinivasan, TAMU and Dr. Feras Ziadat, ICARDA
19:00 – 21:30 Group Dinner to be organized by IRA
38
Wednesday 25 September
Improving Agricultural Water Productivity in Response to Climate Change: Setting Targets Chair: Dr. Caroline King Rapporteur: Dr. Feras Ziadat 9:00 – 10:00 Technical Presentation including use of at least 2 crop-water productivity models
(aquacrop/CropSyst/DSSAT/EPIC) Dr. Debra Turner and Maria Glazirina 10:00 – 10:30 Coffee Break Short recap of progress and challenges to identify potential impacts of improved water productivity at larger spatial scales (i.e. landscape and watershed scales) and over suitable time periods (1-year, 2-year, 5-year, 10-year), Chair: Dr. Caroline King Breakout group discussion session of target setting by agroecosystem
10:30 – 12:30 Rangeland systems: Group Leader: Dr. Feras (rapporteur to be designated) Rainfed systems: Group Leader: Dr. Vinay (rapporteur to be designated) Irrigated systems Group Leader: Dr. Srini (rapporteur to be designated) 12:30 – 13:30 Lunch Reports on targets for improved water productivity at larger spatial scales (i.e. landscape and watershed scales) and over suitable time periods (1-year, 2-year, 5-year, 10-year) Facilitator: Dr. Theib Oweis (Reports 10 Minutes each) Rapporteur: Dr. Kamel Nagaz 13:30 – 14:00 Rangeland systems Rainfed systems Irrigated systems 14:00 – 15:00 Open discussion of methodological and data-related challenges for WLI Thematic
Research Group on Water Use Efficiency and Water Productivity 15:00 – 15:30 Coffee Break 15:30 – 15:45 Overview of WLI Annual Reporting and Workplanning Ms Bezaiet Dessalegn 15:45 – 16:00 Briefing on field visit Prof. Netij Ben Mechlia 16:00 – 16:30 Soil Water Mass Balance Model and Optimization of Irrigation using Soil Water Sensors.
Dr. Ashok Alva, USDA-ARS Facilitator: Dr. Caroline King Rapporteur: Dr. Mohamed Ouessar
39
Thursday 26 September
9:00 – 15:00 Field Visit. This will include:
Brief visit to IRA’s headquarters’ (missions, main programs, etc.) in the El Fjé Technological park
Field tour to visit some selected research sites of WLI Tunisia in the South of the country (WH, irrigation management)
Webinar event on the recently updated Feed the Future (FtF) Guide
08:00 Meet at the hotel lobby to take the bus arranged by IRA
Friday 27 September
Projecting Impact on Water Balance with- and without- improved water management Chair: Dr. Mohamed Ouessar Rapporteur: Dr. Maria Glazirina 9:00 – 9:40 Observations on challenges to identify potential impacts of improved water productivity
on the water balance at the watershed scale and communicate them to decision-makers Prof. Mongi Sghaier
Integrating hydrological and economic models of watershed management Dr. Hamed Daly Hassen 9:40 -10:00 Presentations and discussions on WEAP (general overview and case study applications). Dr. Vinay Nangia 10:00 -10:30 Discussions 10:30 – 11:00 Coffee Break 11:00 – 11:20 Conclusions for the WLI Thematic Research Group on Decision support tools and models
Group Leader: Dr. Nahla Zaki 11:20 – 13:00 Wrapping up and recommendations for improvement and finalization of regional and
country level research plans for WLI 2013-14 Dr. Caroline King Saturday 28 September
Participants depart to their respective destinations.
***********************
40
Appendix 2: Map for site visits
41
Appendix 3: List of participants of the workshop
42
Appendix 4: List of participants in breakout sessions
Break out group – Rangeland and Rainfed
Agroecosystems
Break out group Irrigated
Agroecosystems
Dr. Mohamed Annabi, Tunisia Dr. Nahla Zaki, Egypt
Dr. Hamed Daly, Tunisia Dr. Samar Attaher, Egypt
Dr. Mohamed Al Salimiya, Palestine Dr. Ibraheem Abderabdo, Egypt
Dr. Feras Ziadat, ICARDA Dr. Bassam Kanaan, Iraq
Mr. Awad Al Kaabnh, Jordan Dr. Ali Hasan Faraj, Iraq
Eng. Afaf Al-Madadha, Jordan Eng. Randa Massad, Lebanon
Mr. Monji Ben Zaied, Tunisia Dr. Ihab Jomaa, Lebanon
Dr. Yasser Mohawesh, Jordan Dr. Hadi Hfaar, Lebanon
Dr. Debra Turner, ICARDA Dr. Khader Atroosh, Yemen
Dr. Nasser Sholi, Palestine Dr. Nashwan Obeid, Yemen
Dr. Vinay Nangia, ICARDA Dr. Kamel Nagaz, Tunisia
Dr. Mohamed Ouessar, Tunisia Dr. Monji Sghaier, Tunisia
Dr. Caroline King, ICARDA Ms. Fathia El Mokh
Ms Asma Lasram
Ms Hachani Amal
Dr. Mariya Glazirina
43
Appendix 5: Outline for the Regional Knowledge Exchange on
Decision-support Tools and Models
Title: Regional Knowledge Exchange on Decision-support Tools and Models to
Project Improved Strategies for Integrated Management of Land, Water and
Livelihoods
22-27 September, 2013, Djerba, Tunisia
Purpose:
To identify scope for available watershed and basin-scale water balance assessments
to include scenarios demonstrating improvements in integrated management of
land, water and livelihoods to be achieved through upscaling of WLI pilot-tested
strategies and technologies
Objectives:
- Review available assessments of present and future water availability and use at
the watershed and basin-scale and identify scope for updates to reflect the full
potential of improvements in on-farm land and water management
- Inform regional decision-makers and other key stakeholders at the benchmark
sites of the relevance and potential further use of outputs from decision support
tools to evaluate options for improved management of land, water and livelihoods
- Stimulate knowledge exchange and research collaboration amongst WLI research
teams using and developing tools to support integrated water and land-use
strategies with key stakeholders
Key Words: Knowledge Exchange, Decision Support Tools, Models, Regional
Background:
The Water and Livelihoods Initiative (WLI) addresses the development challenge of
improving agricultural water management in water scarce agro-ecosystems in order to
address food security and improve rural livelihoods in the Middle East and North Africa
(MENA) region. This is achieved through pilot testing of integrated water and land-use
management strategies, focusing initially on selected benchmark sites, with the intention
of scaling up to larger areas where water scarcity, land degradation, water quality
deterioration, food security and health problems are prevalent.
Intended results from strategies pilot tested through WLI include reduced losses of
rainwater to runoff and evaporation; increased volumes of water retained in the soil for
uptake by crops, increased storage of water in cisterns, wells and aquifers for use in
irrigation (including supplementary irrigation and deficit irrigation); increased water
productivity of crops and livestock; increased on-farm income and improved livelihoods
of rural households at the benchmark sites. Use of scientific decision-support tools,
including Water Evaluation and Planning (WEAP), the Soil Water Assessment Tool
(SWAT), and other available tools to model future climate scenarios and crop-
productivity responses can help researchers to assess and communicate the current water
balance and potential future scenarios to communities of water users and other
stakeholders.
44
Economic assessments likely to convince national decision-makers of the merit of
outscaling strategies require decision-support model outputs that effectively quantify the
volumes of crops and livestock to be produced and valued, and the volumes water stored
and conserved. In some cases, decision-makers may also wish to know the volumes and
values of other additional ecosystem services that could be affected by different land and
water management strategies (eg soil organic carbon, biodiversity, etc). In heterogeneous
landscapes, Geographic Information Systems (GIS) can provide an effective means for
supporting and integrating these assessments on a strategic scale, and a strong visual
representation of changes to be anticipated.
Workshop Outline: (5 days)
Day 1: Strategic Approaches to Integrated Management of Land, Water and
Livelihoods in North Africa and the Middle East
- Opening Session including overview of WLI and workshop objectives
- 3 Selected WLI Country team presentations on national strategies, assessments and
models in target watersheds
-Presentations of WLI Tunisia (Overview and 3 site presentations)
-Presentation on 3 selected decision support tools and models
-Additional invited presentations on potential contributions on use of Hidromore,
Modflow and WEAP to refinement of water balance estimates (focus on water
availability)
Day 2: Regional and International Exchange of Knowledge, Decision Support Tools
and Models to Improve Integrated Management of Land, Water and Livelihoods
- 3 WLI Country team presentations on national strategies, assessments and models in
target watersheds
- Additional invited presentations on connecting SWAT to other models to identify
impacts of land management on productivity and water use in evapotranspiration,
groundwater recharge and surface runoff (General overview and case study applications)
Day 3: Improving Agricultural Water Productivity in Response to Climate Change:
Setting Targets
- Overview of WLI achievements in pilot testing strategies to improve water productivity
at field and farm levels and challenges of scaling up
- Achievements and remaining challenges in rangeland agroecosystems
- Achievements and remaining challenges in rainfed agroecosystems
- Achievements and remaining challenges in irrigated agroecosystems
-Brainstorming on challenges to identify potential impacts of improved water
productivity at larger spatial scales (i.e. landscape and watershed scales) and over suitable
time periods (1-year, 2-year, 5-year, 10-year)
- Technical presentation including use of at least 2 crop-water productivity models (e.g.:
Aquacrop/CropSyst/DSSAT/EPIC?)
-Conclusions for the WLI Thematic Research Group on Water Use Efficiency and Water
Productivity
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- Additional invited presentation on Soil Water Mass Balance Model and Optimization of
Irrigation using Soil Water Sensors
Day 4: Field visit
This will include:
- Brief visit to IRA‟s headquarters‟ (missions, main programs, etc.) in the El Fjé
Technological park
- Field tour to visit some selected research sites of WLI Tunisia in the South of the
country (WH, irrigation management)
- A webinar event on recently launched Guide on Feed the Future (FtF) Indicators
Day 5: Water Balance with- and without- improved water management: Projecting
Impact
-Brainstorming on challenges to identify potential impacts of improved water
productivity on water balance in target systems and at the watershed scale, and
communicating them to decision-makers
-Economic analysis of improved water management
-Practical examples on WEAP,
-Open discussion on methodological and data-related challenges for WLI
-Conclusions for the WLI Thematic Research Group on Decision support tools and
models
-Wrapping up and recommendations for improvement of regional and country level
research plans for WLI 2013-14
Expected Outputs:
Enhanced annual reports and PPT presentations from 8 WLI countries and
regional team
Training materials online for other interested researchers to benefit from
Short workshop report including list of participants
Expected Outcomes:
WLI thematic research group on decision support tools and models activated
WLI thematic research group on water use efficiency activated
Improved connection of WLI pilot testing to strategic level decision-making
and improved outscaling strategies for integrated land and water management
Improved management of land, water and livelihoods in WLI countries
Expected Impacts:
Reduced threat of water scarcity for all sectoral uses, including agriculture and
reduced vulnerability to land degradation (affecting food production, water
availability and quality)
Increased on-farm income at the benchmark sites
Improved livelihoods of rural households at the benchmark sites
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Preparatory Materials for Participants:
WLI:
- Regional Reports: 1st and 2
nd Quarterly reports, 2013
-Tunisia program document
- Further information: http://temp.icarda.org/wli/
WEAP:
- Regional paper:
Droogers, P., Immerzeel, W.W., Terink, W., Hoogeveen, J., Bierkens, M.F.P., Van Beek,
L.P.H., Debele, B. (2012) Water resources trends in Middle East and North Africa
towards 2050 Hydrol. Earth Systems Science, 16, 3101–3114.
- Tunisia case study:
Hadded, R., I. Nouiri, O. Alshihabi, J. Maßmann, M. Huber, A. Laghouane, H. Yahiaoui
& J. Tarhouni (2013) A Decision Support System to Manage the Groundwater of
the Zeuss Koutine Aquifer Using the WEAP-MODFLOW Framework Water
Resources Management, 27, 1981-2000.
- Further information and manual: http://www.weap21.org/index.asp?NewLang=EN
SWAT:
-Overview paper (Gassman):
http://www.card.iastate.edu/environment/items/asabe_swat.pdf
-Tunisia case study paper:
Ouessar, M., A. Bruggeman, F. Abdelli, R. H. Mohtar, D. Gabriels & W. M. Cornelis
(2009) Modelling water-harvesting systems in the arid south of Tunisia using
SWAT. Hydrology and Earth System Sciences, 13, 2003 -2021.
- Further information and manual: http://swat.tamu.edu/
CROP Syst:
- Overview paper:
Stockle, C. O., M. Donatelli & R. Nelson (2003) CropSyst, a cropping systems
simulation model. European Journal of Agronomy, 18, 289–307.
- Tunisia case study paper (Belhouchette2008)
Belhouchette, H., E. Braudeau, M. Hachicha, M. Donatelli, R. H. Mohtar & J. Wery
(2008) INTEGRATING SPATIAL SOIL ORGANIZATION DATA WITH A
REGIONAL AGRICULTURAL MANAGEMENT SIMULATION MODEL: A
CASE STUDY IN NORTHERN TUNISIA Transactions of the American Society
of Agricultural and Biological Engineers (ASABE) 51, 1099-1109.
- Further information and
manual: http://www.bsyse.wsu.edu/CS_Suite/CropSyst/manual/index.html
AquaCrop:
- Overview publication (FAO Irrigation and Drainage paper nr. 66) and further
information available from: http://www.fao.org/nr/water/aquacrop.html
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Appendix 6: Definitions of selected WLI FtF Indicators
SPS LOCATION: Program Element 4.5.2: Agricultural Sector Productivity INITIATIVE AFFILIATION: FTF – IR 1: Improved Agricultural Productivity / Sub IR 1.2: Enhanced Technology Development, Dissemination, Management and Innovation
INDICATOR TITLE: 4.5.2-2 Number of hectares under improved technologies or management practices as a result of USG assistance (RiA) (WOG)
DEFINITION: This indicator measures the new and continuing area (in hectares) of land under new technology during the current reporting year. Any technology that was first adopted in a previous reporting year and continues to be applied should be marked as “Continuing” (see disaggregation notes below). Technologies to be counted here are agriculture-related technologies and innovations including those that address climate change adaptation and mitigation (e.g. carbon sequestration, clean energy, and energy efficiency as related to agriculture). Relevant technologies include: • Mechanical and physical: Irrigation, new land preparation, harvesting, processing and product handling technologies, including biodegradable packaging; • Biological: New germ plasm (varieties, breeds, etc.) that could be higher-yielding or higher in nutritional content and/or more resilient to climate impacts; affordable food-based nutritional supplementation such as vitamin A-rich sweet potatoes or rice, or high-protein maize, or improved livestock breeds; soil management practices that increase biotic activity and soil organic matter levels; and livestock health services and products such as vaccines; • Chemical: Fertilizers, insecticides, and pesticides safe storage application and disposal of agricultural chemicals, effluent and wastes, and soil amendments that increase fertilizer-use efficiency (e.g. soil organic matter); • Management and cultural practices: Information technology, conservation agriculture, improved/sustainable agricultural production and marketing practices, increased use of climate information for planning disaster risk strategies in place, climate change mitigation and energy efficiency, and natural resource management practices that increase productivity (e.g. upstream watershed conservation or bio-diesel fueled farm equipment) and/or resilience to climate change including soil and water conservation and management practices (e.g. erosion control, water harvesting, low or no-till); sustainable fishing practices (.e.g. ecological fishery reserves, improved fishing gear, establishment of fishery management plans); Integrated Pest Management (IPM), and Integrated Soil Fertility Management (ISFM), and Post-Harvest Handling (PHH) related to agriculture should all be included as improved technologies or management practices. Significant improvements to existing technologies should be counted. If a hectare is under more than one improved technology type (e.g. improved seed (crop genetics) and IPM (pest management), count the hectare under each technology type (i.e. double-count). In addition, count the hectare under the total w/one or more improved technology category. Since it is very common that more than one improved technology is disseminated and applied, this approach allows FTF to accurate count the uptake of different technology types, and to accurately count the total number of hectares under improved technologies. If a hectare is under more than one improved technology, some of which continue to be applied from the previous year and some of which were newly applied in the reporting year, count the hectare under the relevant technology type as new or continuing, depending on the technology, and under new for the total w/one or more improved technology category (i.e. any new application of an improved technology
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categorizes a hectare as new, even if other technologies being applied are continuing.)
RATIONALE: Tracks successful adoption of technologies and management practices in an effort to improve agricultural productivity, agricultural water productivity, sustainability, and resilience to climate impacts.
UNIT: Hectares
DISAGGREGATE BY: Technology type:
crop genetics (including nutritional enhancement), animal genetics, pest management, disease management, soil-related (fertility and conservation, including tillage), irrigation, water management, post-harvest handling and storage, processing, climate mitigation or adaptation, fishing gear/technique, other, total w/one or more improved technology
Duration: --New = this is the first year the hectare came under improved technologies or management practices --Continuing = the hectare being counted continues to be under improved technologies or management practices from the previous year Sex: --male --female --association-applied
TYPE: Outcome
DIRECTION OF CHANGE: Higher is better
DATA SOURCE: Implementing Partners will collect this data through census or survey of program participants, direct observations of land, and report into program documents.
MEASUREMENT NOTES: LEVEL of COLLECTION: Project-level; only those hectares affected by USG assistance, and only
those brought or continuing under new technologies/management during the current reporting year
WHO COLLECTS DATA FOR THIS INDICATOR: Implementing partners HOW SHOULD IT BE COLLECTED: Via survey or other applicable method FREQUENCY of COLLECTION: Annually reported
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SPS LOCATION: Program Area 4.5 Agriculture INITIATIVE AFFILIATION: FTF – IR 1: Improved Agricultural Productivity
INDICATOR TITLE: 4.5-4 Gross margin per unit of land, kilogram, or animal of selected product (crops/animals/fisheries selected varies by country)
DEFINITION: The gross margin is the difference between the total value of sales of the agricultural product (crop, livestock, fish) and the cost of producing that item, divided by the total number of units (hectares of crops, kilograms of fish, number of animals for livestock) in production. Gross margin per hectare, or per animal, or per kilogram of fish for targeted commodities, is a measure of net income for that farm/fishery/livestock-use activity. Input costs included should be those significant input costs that can be easily ascertained. These are likely to be the cash costs. Most likely items are: purchased water, fuel, electricity, seed, feed or fish meal, fertilizer, pesticides, hired labor, hired enforcement, and hired machine/veterinary services. Reporting of current-year results for individuals and firms who have benefited in previous years from this same USG assistance should be included along with current-year results of current beneficiaries. Reporting all data elements (Area, Production, Quantity of Sales, Value of Sales, and Purchased Input Cost) requested is critical to the ability to aggregate results across missions. In addition, a sixth data element – water consumption in cubic meters – can be obtained in order to calculate water productivity (see measurement notes).
RATIONALE: Improving the gross margin of value chains for farming commodities or animals contributes to increasing agricultural GDP, will increase income, and thus directly contribute to the IR of improving production and the goal indicator of reducing poverty. Also assessing the gross margin of fisheries – through assessing biomass of fish caught - is an appropriate measure of the productivity of a fishery and the impacts of fisheries management interventions.
UNIT: dollars/hectare (crops); dollars/animal (livestock); or kilograms of fish (fishery); Note: convert local currency to USD by using an average of the market foreign exchange rate for the reporting period
DISAGGREGATE BY: --Targeted commodity (type of crop, type of animal, or type of fish – freshwater or marine) --Gendered household type: female no male (FNM); male no female (MNF); male and female (M&F) --Rain-fed v. irrigated areas System note: These disaggregations will not necessarily be available in FACTS Info, but will be available in the FTF Monitoring System in a drop-down menu.
TYPE: Outcome
DIRECTION OF CHANGE: Higher is better
DATA SOURCE: Implementing partners
MEASUREMENT NOTES: Gross margin is calculated by applying a formula against these 5 data points: 1) Area (hectares) or Kilograms (for fish) or Number of animals (for livestock), 2) Production, 3) Value of Sales (USD), 4) Quantity of Sales , and 5) purchased input costs (report only those costs that are at least 5% of total cost, i.e. do not report miniscule costs). Price = value of sales divided by quantity of sales; gross revenue = price x production; net revenue = gross revenue minus purchase input cost; gross margin (per ha, per kg of fish, or per animal) = net revenue divided by area (for crops), by animals (for livestock), It is strongly recommended that data also be gathered on the m3 of water consumed since the inclusion of this sixth data point in addition to the five data points used for Gross Margin allows for the calculation of water productivity. Provision of data on water consumption should be mandatory for Implementing Partners to report in irrigated areas, and strongly encouraged in rain-fed areas. Increasing Agricultural Production per unit of water consumed is an important way to improve food security. Current constraints on collection of data on water consumption in rain-fed areas are nonetheless acknowledged. FTF System Note: Simply enter the 5 data points into the FTF Monitoring System (FTFMS), and it will do the calculation of gross margin automatically. This calculation cannot be done without all 5 data points. Adding the
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6th data point will also enable the system to automatically calculate water productivity. LEVEL of COLLECTION: Project-level, in targeted commodities/fisheries/livestock
WHO COLLECTS DATA FOR THIS INDICATOR: Implementing Partners HOW SHOULD IT BE COLLECTED: Through farmer/fisher/rancher surveys FREQUENCY of COLLECTION: Implementing partners should obtain this data annually (required). Data will be collected through standardized approaches wherein implementing partners/extension workers collect data quarterly through producer organization meetings using standardized group questionnaire. Note: If the item is home consumed then the market price received by farmers selling the product is used to value it. Cost includes all purchased inputs, purchased transportation (including fuel), or hired labor, but does not include any imputed value of family or community labor.
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SPS LOCATION: Program Element 4.5.2: Agricultural Sector Productivity INITIATIVE AFFILIATION: FTF – IR 1 Improved Agricultural Productivity / Sub IR 1.1 Enhanced human and institutional capacity development for increased sustainable agriculture sector productivity
INDICATOR TITLE: 4.5.2-11 Number of food security private enterprises (for profit), producers organizations, water users associations, women’s groups, trade and business associations, and community-based organizations (CBOs) receiving USG assistance (RiA) (WOG)
DEFINITION: Total number of private enterprises, producers’ associations, cooperatives, producers organizations, fishing associations, water users associations, women’s groups, trade and business associations and community-based organizations, including those focused on natural resource management, that received USG assistance related to food security during the reporting year. This assistance includes support that aims at organization functions, such as member services, storage, processing and other downstream techniques, and management, marketing and accounting. “Organizations assisted” should only include those organizations for which implementing partners have made a targeted effort to build their capacity or enhance their organizational functions. In the case of training or assistance to farmer’s association or cooperatives, individual farmers are not counted separately, but as one entity.
RATIONALE: Tracks civil society capacity building that is essential to building agricultural sector productivity.
UNIT: Number
DISAGGREGATE BY: Type of organization (see indicator title for principal types) New/Continuing: --New = the entity is receiving USG assistance for the first time during the reporting year --Continuing = the entity received USG assistance in the previous year and continues to receive it in the reporting year System note: In the FTF Monitoring System (FTFMS), you will enter the number of each type of organization receiving assistance for your projects, and the system will aggregate the total number for this indicator across all projects.
TYPE: Output
DIRECTION OF CHANGE Higher is better
DATA SOURCE: Implementing partners
MEASUREMENT NOTES:
LEVEL of COLLECTION: Project-level WHO COLLECTS DATA FOR THIS INDICATOR: Implementing partners HOW SHOULD IT BE COLLECTED: Project records of training and various USG assistance for these
specific types of organizations/associations FREQUENCY of COLLECTION: Annually reported
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SPS LOCATION: Program Element 4.5.2: Agricultural Sector Productivity INITIATIVE AFFILIATION: FTF – IR 1: Improved Agricultural Productivity / Sub IR 1.1: Enhanced human and institutional capacity development for increased sustainable agriculture sector productivity
INDICATOR TITLE: 4.5.2-7 Number of individuals who have received USG supported short-term agricultural sector productivity or food security training (RiA) (WOG
DEFINITION: The number of individuals to whom significant knowledge or skills have been imparted through interactions that are intentional, structured, and purposed for imparting knowledge or skills should be counted. This includes farmers, ranchers, fishers, and other primary sector producers who receive training in a variety of best practices in productivity, post-harvest management, linking to markets, etc. It also includes rural entrepreneurs, processors, managers and traders receiving training in application of new technologies, business management, linking to markets, etc., and training to extension specialists, researchers, policymakers and others who are engaged in the food, feed and fiber system and natural resources and water management. In-country and off-shore training are included. Include training on climate risk analysis, adaptation, mitigation, and vulnerability assessments, as it relates to agriculture. Delivery mechanisms can include a variety of extension methods as well as technical assistance activities. An example is a USDA Cochran Fellow. Training should include food security, water resources management/IWRM, sustainable agriculture, and climate change resilience, but should not include nutrition-related trainings, which should be reported under indicator #3.1.9-1 instead. This indicator is to count individuals receiving training, for which the outcome, i.e. individuals applying new practices, should be reported under #4.5.2-5
RATIONALE: Measures enhanced human capacity for increased agriculture productivity, improved food security, policy formulation and/or implementation, which is key to transformational development.
UNIT: Number
DISAGGREGATE BY: Type of individual: -Producers (farmers, fishers, pastoralists, ranchers, etc.) -People in government (e.g. policy makers, extension workers) -People in private sector firms (e.g. processors, service providers, manufacturers) -People in civil society (e.g. NGOs, CBOs, CSOs, research and academic organizations)
Note: While producers are included under MSMEs under indicators 4.5.2-30 and 4.5.2-37, only count them under the Producers and not the Private Sector Firms disaggregate to avoid double-counting. While private sector firms are considered part of civil society more broadly, only count them under the Private Sector Firms and not the Civil Society disaggregate to avoid double-counting.
Sex: Male, Female
TYPE: Output
DIRECTION OF CHANGE: Higher is better
DATA SOURCE: Implementing partners
MEASUREMENT NOTES: LEVEL of COLLECTION: Project-level; individuals targeted by USG program WHO COLLECTS DATA FOR THIS INDICATOR: Implementing partners HOW SHOULD IT BE COLLECTED: Program training records FREQUENCY of COLLECTION: Annually reported
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SPS LOCATION: Program Element 4.5.2: Agricultural Sector Productivity INITIATIVE AFFILIATION: FTF – IR 1: Improved Agricultural Productivity / Sub IR 1.2: Enhanced Technology Development, Dissemination, Management and Innovation
INDICATOR TITLE: 4.5.2-39 Number of technologies or management practices in one of the following phases of development:
….in Phase I: under research as a result of USG assistance
….in Phase II: under field testing as a result of USG assistance
….in Phase III: made available for transfer as a result of USG assistance (S)
DEFINITION: Technologies to be counted here are agriculture-related technologies and innovations including those that address climate change adaptation and mitigation (including carbon sequestration, clean energy, and energy efficiency as related to agriculture), and may relate to any of the products at any point on the supply chain. Relevant technologies include:
• Mechanical and physical: New land preparation, harvesting, processing and product handling technologies, including packaging, sustainable water management practices; sustainable land management practices; sustainable fishing practices; • Biological: New germ plasm (varieties, breeds, etc.) that could be higher-yielding or higher in nutritional content and/or more resilient to climate impacts; biofortified crops such as vitamin A-rich sweet potatoes or rice, or high-protein maize, or improved livestock breeds; soil management practices that increase biotic activity and soil organic matter levels; and livestock health services and products such as vaccines; • Chemical: Fertilizers, insecticides, and pesticides sustainably and environmentally applied, and soil amendments that increase fertilizer-use efficiencies; • Management and cultural practices: Information technology, improved/sustainable agricultural production and marketing practices, increased use of climate information for planning risk management strategies, climate change mitigation and energy efficiency, and natural resource management practices that increase productivity and/or resiliency to climate change. IPM, ISFM, and PHH as related to agriculture should all be included as improved technologies or management practices
Significant improvements to existing technologies should also be counted; an improvement would be significant if, among other reasons, it served a new purpose or allowed a new class of users to employ it. Examples include a scaled-down milk container that allows individuals to carry it easily, a new blend of fertilizer for a particular soil, tools modified to suit a particular management practice, and improved fishing gear.
…in Phase I: under research as a result of USG assistance
New technologies or management practices under research counted should be only those under research in the current reporting year. Any new technology or management practice under research in a previous year but not under research in the reporting year should not be included. Technologies under research are as follows:
a. For biotech crop research: When technologies are under research, the process is contained in a laboratory or greenhouse; once the possibility of success is judged high enough, a permit is required to move to field testing. The change of location from a contained laboratory or greenhouse to a confined field and the receipt of a permit indicate that the research has completed the “under research” stage.
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b. For non-biotech crop research: When technologies are under research, plant breeders work on developing new lines on research plots under controlled conditions. All research should have a target, often expressed in terms of traits to be combined into a specific cultivar or breed. When the research achieves “proof of concept” (by accumulating technical information and test results that indicate that the target is achievable), the “under research” phase is completed. Note that for crops, much or all of this phase might be conducted outdoors and in soil; these attributes do not make this work “field testing.”
c. For non-crop research: “under research” signifies similarly research conducted under ideal conditions to develop or support the development of the product or process.
…in Phase II: under field testing as a result of USG assistance
“Under field testing” means that research has moved from focused development to broader testing and this testing is underway under conditions intended to duplicate those encountered by potential users of the new technology. This might be in the actual facilities (fields) of potential users, or it might be in a facility set up to duplicate those conditions. More specifically:
a. For biotech crop research: Once a permit has been obtained and the research moves to a confined field, the research is said to be “under field testing.”
b. For non-biotech crop or fisheries research: During this phase the development of the product or technology continues under end-user conditions in multi-location trails, which might be conducted at a research station or on farmers’/producer’s fields/waters or both. Note that for crops, all of this phase would be conducted outdoors and in soil, but this is not what makes this work “field testing.”
c. For non-crop research: “under field testing” signifies similarly research conducted under user conditions to further test the product, process, or practice. In the case of research to improve equipment, the endpoint of field testing could be sales of equipment (when the tester is a commercial entity). In other cases it could be distribution of designs (when the tester is a noncommercial entity) and also distribution of publications or other information (on the force of the good results of field testing).
…in Phase III: made available for transfer as a result of USG assistance.
Note that completing a research activity does not in itself constitute having made a technology available. In the case of crop research that developed a new variety, e.g., the variety must have passed through any required approval process, and seed of the new variety should be available for multiplication. The technology should have proven benefits and be as ready for use as it can be as it emerges from the research and testing process. In some cases more than one operating unit may count the same technology. This would occur if the technology were developed, for instance, in collaboration with a U.S. university and passed through regional collaboration to other countries. Technologies made available for transfer should be only those made available in the current reporting year. Any technology made available in a previous year should not be included.
RATIONALE: This indicator tracks the three stages in research and technology investments and progress toward dissemination.
UNIT: Number
DISAGGREGATE BY: Phase of development: -Under research as a result of USG assistance;
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-Under field testing as a result of USG assistance; -Made available for transfer as a result of USG assistance
Type: Output
DIRECTION OF CHANGE: Higher is better
DATA SOURCE: Implementing partners
MEASUREMENT NOTES:
LEVEL of COLLECTION: Project-level; only those technologies made available under field research as a result of the USG project
WHO COLLECTS DATA FOR THIS INDICATOR: Implementing partners HOW SHOULD IT BE COLLECTED: Project records or survey FREQUENCY of COLLECTION: Annually reported
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SPS LOCATION: Program Element 4.5.2: Agricultural Sector Productivity INITIATIVE AFFILIATION: FTF – IR 1: Improved Agricultural Productivity / Sub IR 1.1: Enhanced human and institutional capacity development for increased sustainable agriculture sector productivity
INDICATOR TITLE: 4.5.2-5 Number of farmers and others who have applied new technologies or management practices as a result of USG assistance (RiA) (WOG)
DEFINITION: This indicator measures the total number of farmers, ranchers and other primary sector producers (food and non-food crops, livestock products, wild fisheries, aquaculture, agro-forestry, and natural resource-based products are included), individual processors (not firms), rural entrepreneurs, managers and traders, natural resource managers, etc. that applied new technologies anywhere within the food and fiber system as a result of USG assistance. This includes innovations in efficiency, value-addition, post-harvest management, sustainable land management, forest and water management, managerial practices, input supply delivery. Any technology that was first applied in a previous year and that continues to be applied should be included as ‘continuing’. Technologies to be counted here are agriculture-related technologies and innovations including those that address climate change adaptation and mitigation (including, but not limited to, carbon sequestration, clean energy, and energy efficiency as related to agriculture). Relevant technologies could include: • Mechanical and physical: New land preparation, harvesting, processing and product handling technologies, including biodegradable packaging • Biological: New germ plasm (varieties, breeds, etc.) that could be higher-yielding or higher in nutritional content and/or more resilient to climate impacts; affordable food-based nutritional supplementation such as vitamin A-rich sweet potatoes or rice, or high-protein maize, or improved livestock breeds; soil management practices that increase biotic activity and soil organic matter levels; and livestock health services and products such as vaccines; • Chemical: Fertilizers, insecticides, and pesticides sustainably and environmentally applied, and soil amendments that increase fertilizer use efficiencies; • Management and cultural practices: sustainable water management; practices; sustainable land management practices; sustainable fishing practices; information technology, improved/sustainable agricultural production and marketing practices, increased use of climate information for planning disaster risk strategies in place, climate change mitigation and energy efficiency, and natural resource management practices that increase productivity and/or resiliency to climate change. IPM, ISFM, and PHH as related to agriculture should all be included as improved technologies or management practices Significant improvements to existing technologies should be counted. In the case where, for example, a farmer applies more than one innovation as a result of USG assistance, they are still only counted once. Also, if more than one farmer in a household is applying new technologies, count all the farmers in the household who apply. This indicator is to count individuals who applied new technologies, whereas indicator #4.5.2-28 is to count firms, associations, or other group entities applying new technologies.
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RATIONALE: Technological change and its adoption by different actors in the in the agricultural supply change will be critical to increasing agricultural productivity which is the Intermediate Result which this indicator falls under.
UNIT Number
DISAGGREGATE BY: Duration --New = This reporting year is the first year the person applied the new technology or management practice --Continuing = The person first applied the new technology or practice in the previous year and continues to apply it Sex: Male, Female
TYPE: Outcome
DIRECTION OF CHANGE: Higher is better
DATA SOURCE: Implementing Partners
MEASUREMENT NOTES: LEVEL of COLLECTION: Project-level; only those individuals targeted by USG programs WHO COLLECTS DATA FOR THIS INDICATOR: Implementing partners HOW SHOULD IT BE COLLECTED: Survey of all targeted individuals, Project or association
records, farm records FREQUENCY of COLLECTION: Annually reported
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SPS LOCATION: Program Element 4.5.2:Agricultural Sector Productivity INITIATIVE AFFILIATION: GCC and FTF – IR 1: Improved Agricultural Productivity / Sub IR 1.1: Enhanced human and institutional capacity development for increased sustainable agriculture sector productivity
INDICATOR TITLE: 4.5.2-34 Number of stakeholders implementing risk-reducing practices/actions to improve resilience to climate change as a result of USG assistance (S)
DEFINITION: There is strong scientific and evidence-based information that stakeholders (in the case of this indicator defined as “producers”) involved in sectors such as agriculture, livestock, fishing, other areas of natural resources can mitigate the effects of climate change by using appropriate new and tested management practices or implement measures that reduce the risks of climate change impacts. For example, risk-reducing management practices in agriculture and livestock might include changing the exposure or sensitivity of crops (e.g., switching crops, using a greenhouse, or changing the cropping calendar), soil management practices that reduce rainwater run-off and increase infiltration, changing grazing practices, or adjusting the management of other aspects of the system. Risk reducing measures might include applying new technologies like improved seeds or irrigation methods, diversifying into different income-generating activities or into crops that are less susceptible to drought and greater climatic variability. Any adjustment to the management of resources or implementation of an adaptation action that responds to climate-related stresses and increases resilience can be considered. Practices and actions will aim to increase predictability and/or productivity of agriculture under anticipated climate variability and change.
RATIONALE: While many management practices and technologies exist and can be diffused, others may not be well suited to perform under emerging climate stresses. Improved management and new technologies are available and others are being developed to perform better under climate stresses. Resource management experiences from other parts of the world may be useful as climate conditions shift geographically.
UNIT: Number of stakeholders
DISAGGREGATE BY: Type of Risk reducing practice: -Agriculture – practices and actions will aim to increase predictability and/or productivity of agriculture under anticipated climate variability and change. -Water – practices and actions will aim to improve water quality, supply, and efficient use under anticipated climate variability and change. -Health – practices and actions will aim to prevent or control disease incidence and outcomes under anticipated climate variability and change outcomes. -Disaster Risk Management – practices and actions will aim to reduce the negative impacts of extreme events associated with climate variability and change. -Urban – practices and actions will aim to improve the resilience of urban areas, populations, and infrastructure under anticipated climate variability and change. Sex: Male, Female
Type: Outcome
DIRECTION OF CHANGE Higher is better
DATA SOURCE: Field surveys by local project partners, including extension agents and farmer/producer organizations (and other types of organizations)
MEASUREMENT NOTES: LEVEL of COLLECTION: Project-level; only those stakeholders involved in USG programs WHO COLLECTS DATA FOR THIS INDICATOR: Implementing partners HOW SHOULD IT BE COLLECTED: Via Implementing Partner records, survey or other applicable
method FREQUENCY of COLLECTION: Annually reported