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Revised Thesis proposal FINAL VERSION

Research Supervisory committee members:
Dr. Annalisa Molini
Dr. Lina Yousef
Dr. Matteo Chiesa
Dr. Riaan van der Merwe
Dr. Maryam Rashed Al Shehhi
DECEMBER 5, 2020
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1.1 What is APV
The co-location of photovoltaic and crop production – often referred to as Agrophotovoltaic (APV) or simply
Agrivoltaic – has been recently proven to be an economically viable solution to mitigate the competition for
land between food and solar energy production, maximizing at the same time energy and agricultural yield.
The main idea behind APV is that the same plot of land can be exploited for both energy and food production
utilizing several synergistic relations feedbacks among water resources crop productivity, marginal land
reclamation, and solar energy production. It has also been proposed as an adaption strategy to the food-waterenergy nexus.
Agrophotovoltaic possesses a great potential for marginal land reclamation and the enhancement of
agricultural and solar energy production efficiency in the arid regions of the world. APV can in fact modify
surface heat fluxes by reducing sensible (temperature and thus water loss) and increasing latent heat fluxes
(evaporative cooling) which are expected to enhance the performance of PV panels and boost crops’
productivity. The efficient application of APV solutions implies an optimal sharing of solar resources between
the crops and the PVs units. Therefore, suitable solar technology solutions are required to optimize solar energy
partitioning, and to mitigate crop heat and water stresses.
1.2 Why APV is relevant to arid regions?
Arid and semi-arid regions occupy 30% of the total land area in the world with more areas turning into drylands
due to climate change and poor land management practices. Due to rapid population growth in these areas of the
world, the water demand is expanding at unprecedented rate (Koch & Missimer, 2016) Irrigation accounts for
80% of water use in arid regions and this percentage is expected to increase (Dehghanisanij et al., 2006). Water
security in arid regions thus requires the use of agricultural technologies that allow for production of food with
minimum use of water and environmental resources. The inception of APV in most regions around the world
came as a response to the rising competition between food and energy harvesting systems. However, APV
applications are expected to possess the highest potential in arid and semi-arid regions of the world – where
competition for land has yet a minor role. Particularly, APV allows the optimization of agriculture/energy
production in arid regions in many ways including (a) increase overall plant productivity, and above/below
ground carbon storage in otherwise unproductive or degraded lands, optimizing at the same time, irrigation water
use; (b) improve PV systems efficiency through the evaporative cooling deriving from increased latent heat
fluxes (plant transpiration and bare soil evaporation). These Outcomes are particularly appealing which start
now to be intensively tested in the field across different arid regions worldwide together with tailored PV
technological solutions for drylands. APV could also play in important role in achieving food security by
building a sustainable system for agricultural produce with minimum resource usage and least effects on the
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1.3 How to assess the potential of APV
in Arid regions?
efficiency (a-b) are two particularly appealing outcomes of
APV implementation, which start now to be intensively
tested in the field across different arid regions worldwide
(see State of the Art Section). Both these effects can be
explained in terms of surface energy budget as shown in
Soil moisture
Q* + Q F = Q H + Q E + ∆Q s + ∆Q PV (WM )
Q* = net all-wave radiation (solar and terrestrial)
Q F = anthropogenic heat flux
Q H = sensible heat flux (atmospheric heating)
Q E = latent heat flux (or evapotranspiration)
∆Q s = net storage heat flux
Q PV = energy transferred through
energy production
Figure 1 from (Barron-Gafford et al., 2019). By and large,
assuming equal rates of incoming radiation from the sun
(dashed yellow arrows), a transition from a vegetated
ecosystem/cropland (a) to a solar PV installation (b)
significantly alters the surface energy budget, by
evapotranspiration, ET and the corresponding ‘evaporative
Fig. 1 | Illustration of changes in midday energy exchange with transitions from natural systems, solar PV arrays and a colocated agrivoltaic system.
a,b, Assuming equal rates of incoming energy from the sun (broken yellow arrows), a transition from a vegetated ecosystem (a) to a solar PV installation
(b) will significantly alter the energy flux dynamics of the area because of the removal of vegetation, and thus the latent heat fluxes (blue arrows). This
leads to greater sensible heat fluxes (red and orange arrows), which yield higher localized temperatures. c, Reintroduction of vegetation, in this case
agricultural plants, restores latent heat fluxes and should reduce sensible heat loss to the atmosphere. Energy re-radiation from PV panels (teal arrows)
and energy transferred to electricity (green arrows) are also shown. Arrow size and abundance correspond to the magnitude of the effect.
Credit: Illustration modified from ref. 49, Springer Nature Ltd.
Figure 1: Illustration of changes in midday
cooling; blue arrows), while enhancing sensible heat fluxes
energy exchange with transitions from natural
(red arrows), thus rising surface temperature and increasing
systems, solar PV arrays and a co-located
capacity (to meet 14% of national demands), with 209 GW expected orange arrows, respectively). Within natural ecosystems, vegetation
from reduces
heat gainet
in soils by creating surface
shading,transfer into the soil through conduction (orange
to be ground-mounted
solar, which would system
require approximately
8,000 km2 of land, including agricultural land42,43.
Drylands of the southwestern United States are among the best
positioned for supporting renewable energy through PV because of
the abundance of sunlight44,45, but projections of increasing ambi14
ent temperatures dampen this renewable energy source potential
because of PV panel sensitivity to increases in temperature. While
PV panels vary, their temperature coefficient—the rate of performance decline for every 1 °C increase in temperature >25 °C—
illustrates that PV panel efficiency decreases by an average of
~0.6% oC–1)46–48. Additionally, recent research has found that larger
PV arrays cause a ‘heat island’ effect that warms the area within the
installations49, creating a negative feedback of additional warming.
As with the urban heat island effect, landscape change shifts ecosystem structure from one dominated by vegetation to one characterized by a blend of built structures and vegetation, which alters
the energy balance of absorption, storage and release of short- and
long-wave radiation50. Incoming solar energy is either reflected
back to the atmosphere or absorbed, stored and later re-radiated
in the form of latent or sensible heat51 (Fig. 1, blue or red and
though the degree of shading varies among plant types (Fig. 1a)52.
Transitions of liquid water-to-water vapour loss to the atmosphere
through evapotranspiration—the combined water loss from soils
(evaporation) and vegetation (transpiration)—use energy absorbed
by vegetation and surface soils. Because many PV installations have
gravel as groundcover, with little to no vegetation, they have little to
no means of energy dissipation through latent heat exchange (Fig. 1,
transition from a to b), and thus are subjected to more sensible heat.
Sustainable development practices of low-impact urban design
counter the urban heat island effect with strategic planting that
reintroduces latent heat exchange of energy by way of plant transpiration. How might a similar model be applied to a PV heat
island? Restoration ecology suggests that there is an important role
for ‘novel ecosystems’—non-historical assemblages of species that
result from the combined effects of shifts in abiotic conditions, land
cover change and environmental management53. Novel ecosystems
serve important functional roles, contribute to the provision of ecosystem services and enhance well-being in human-dominated and
built landscapes54,55.
arrows). This effect goes under the name of Photovoltaic
Heat Island (PVHI) . On the other side, the introduction of vegetation, i.e., crops, under the PV panels (APV,
c) restores latent heat fluxes, hence reducing sensible heat loss to the atmosphere. Also, energy re-radiation from
PV panels (teal arrows) will become in this case partitioned among sensible and latent heat fluxes (arrow size
and abundance correspond to the magnitude of the effect). If both the PVHI and APV effects have been
observed experimentally in the field in different sites characterized by hot semi-arid to arid conditions (see
State of the Art Section), the actual magnitude of these effects has not been yet quantified in hyperarid climates
NATURE SUSTAINABILITY | VOL 2 | SEPTEMBER 2019 | 848–855 | www.nature.com/natsustain
like the one characterizing the UAE, where extremely harsh environmental conditions could lead to counterintuitive results in terms of APV water use benefits and potential for evaporative cooling. For example, the
extreme temperature regime characterizing the region could still be able to limit plant transpiration and
productivity, despite the PV shadowing, thus thwarting the benefits of evaporative cooling on PV efficiency.
Above a certain threshold of heat and water stress, in fact, vegetation, including drought-resilient species
(xerophytes) tends to limit water loss by closing leaf stomata and suppressing transpiration. Since PV shadowing
is not a continuous process – varying with the time of the day – and can only partially alleviate the effects of
heat- and water-stress the actual potential of classic APV systems for evaporative cooling efficiency in hot
hyperarid climates remains mainly unquantified, as well as their actual capability for marginal dry land
reclamation and remediation. This follows from the fact that, for the part of the day in which shadowing is
partial and vegetation heat and water stress remain high, transpiration may be suppressed no matter the specific
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Up to 30% efficiency, 4-5x more efficient
than other translucent solar modules
Smart translucency with direct light
traits of heat-resilience of the considered crops, and latent heat fluxes
(and evaporative
could of
up to 78%
substantially reduced. At the same time, during the part of the day for
which shadowing is maximum, it would
be photosynthesis to be impaired, with an expected major reduction of
crop productivity
is directly
be provided by
(cost of itelectricity,
proportional to transpiration) as already documented in studies from temperate
is crucial land
yield, OPEX reductions)
to consider that aridity in the UAE is often coupled with high levels of soil salinization, requiring the adoption
of below PV crops not only draught- and heat-resilient but also salt-tolerant
however aresolar
As easy (halophytes),
to mount aswhich
known to be radically less productive than traditional salt-sensitive panels
crops (glycophytes). As a consequence, the
application of APV solutions in hyperarid regions requires a thoughtful
of APVs
under the harsh
environmental conditions characterizing these climates, and the implementation
of of
aimed to
increase plant productivity and water use efficiency, yet preserving the
potential of dry-land
for increasing
(direct + diffuse light) without electricity
PV efficiency by sustaining evaporative cooling. An economically viable solution to overcome the limitations
of classic 30%
APV applications in hot hyper-arid climates could be represented by the implementation of Agrivoltaic
solutions DIRECT
based on transparent,
tracking-integrated photovoltaic
(CPV) modules – which we will
call from CONVERSION
now on ‘Through EFFICIENCY
light’-optimized APV
systems (TLo-APVs). These recently developed
Up to 78%
CPV modules are in fact able to harvest direct light
by the internal adjustments of the cells and optics and
let through the diffuse component (Figure 2),
ensuring in this way (a) continuous day-time
and high cropSA
productivity through the
diffuse light
component, and (b) simultaneous
thermal comfort by the lowering of radiative forcing
for unit of cropland. The main goal here, is
therefore to quantify the potential of different
implementation of Agrivoltaic in hot-desert
©Insolight SA
regions by both an experimental field campaign
and ad-hoc modeling tools. In the following, I will
discuss the state of the art, the work that has been
done during my first thesis semester, and the way
REV08 – Mar 2020
Figure 2: Tracking-integrated CPVs use the internal
adjustments of the cells and optics to concentrate direct
radiation, avoiding the need for external sun-tracking
devices. At the same time, in these transparent
modules, diffuse light is free to pass through (graphics
from Technical Features – Insolight, n.d.).
A literature review has been carried out to help addressing the main design problems that may be coupled
with a ‘field’ assessment of APV in arid regions. The main goal was to build on the results of previous
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APV installations in drylands to design a field experimental campaign for the evaluation of APV
technologies in the UAE. The literature review was subdivided in two parts: a first part focused on crop
related aspects (crop selection) and one more centered on the general design of the test field.
2.1 Crops selection criteria
The selection of Crops for APV applications in drylands must rely on criteria consistent with the prevalent
climatic conditions in arid regions and account for APV shadowing effects. The selection criteria thus
investigated the major stressors that limits agricultural productivity in arid and semiarid regions. The stressors
that limit crop productivity in these regions are (a) water scarcity and (b) predominance of salt-affected soils.
Additionally, APV is expected to limit – at different extent depending on the adopted technology - the light
reaching the crops. As a consequence, (a) drought tolerance, (b) salt tolerance, and (c) shade tolerance was
adopted as principal criteria for crop selectin. The selection was based on the literature and on quantitative
criterium which assessed these plant resilience characteristics through the use of indicators for each trait. To
quantify salt tolerance, we used absolute salinity tolerance threshold (in terms of ECe, i.e., the soil electrical
conductivity of an extract of a saturated soil paste). Using ECe, different crops can be categorized into tolerant,
moderately tolerant, moderately sensitive, and sensitive. Crops belonging to tolerant and moderately tolerant
groups were only selected and were given priority according to their ECe value. Additional salt tolerance criteria
are presently under evaluation. Drought tolerance was evaluated via (a) irrigation water requirements for unit of
area and time ( L/ m2/ day) which denotes amount of water recommended for the crop per day, (b) water footprint
(m3 per ton) which represents the ecological impacts of different crops, (c) time to harvest from sow (days)
which indirectly embodies the water needs of the crops. These parameters were investigated quantitatively based
on which the crops were ordered in priority. Drought resistant species are considered as those with a short time
to harvest (taken as 90 days here) to maturity or those that have daily irrigation requirements lower than 5
L/m2/day or both. Also, the crops that have water footprint less than 900 m3/ton were considered drought
resilient. The priority was given to the crops that satisfy the three criteria. Lastly, shade tolerance was assessed
mainly through the Light Saturation point (LSP) metric, namely the point of maximum photosynthesis efficiency
after which no further increase in light absorption result in more photosynthetic CO2 assimilation. The LSPs can
be extrapolated from the relation between net CO2 uptake (micromoles of CO2/m2/s) and PAR (Photosynthetic
Active Radiation, in terms of photon flux, micromoles/m2/s), and are given measured in terms of
micromoles/m2/s. Crops with a LSP lower than 1100 micromoles/m2/s where classified as shade tolerant.
Further, the sunlight requirements of crops were investigated and those with requirements less than 8 hours were
selected. The priority was given to crops which satisfy both the criteria, although priority was given to LSP.
The overall selection was based on a tradeoff among the different parameters. The priority was given to
salinity tolerance followed by drought tolerance and then shadow tolerance. Based on these criteria, a
number of ‘perspective’ crops was selected, including Sugarbeet, Marrow/Squash , Quinoa, Cabbage &
Cauliflower, Asparagus, Cucumber Spinach, Tomato, Arugula/Parsley/Basil, pepper, Sweet potato &
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Potato. A database detailing the magnitude of the different parameters as well as ancillary parameters such
as soil PH requirements, NPK Fertilizer requirements (kg/ha) per ton and additional Economic
Considerations was developed and used to guide the selection process. As main output of the literature
review work, I am preparing a review paper focused on the state of the art of APV applications in arid
regions and the challenges ahead.
2.2 APV in arid regions: Where do we stand.
The literature review also includes an
overview of recently developed APV
installations, with particular focus on arid
and semi-arid regions of the world.
Information of interest included Name of
Developers/stakeholders, location (lat,
Forecasted production (kWh/year), Plant
Area (ha), Cultivated Crops, Type of PV
modules, Tracking Technology used,
height of panels(m), Date of installation,
Figure 3: Existing APV systems documented in the literature.
Arid regions’ systems are shown in yellow color.
connection, Climate & Hydrology, and
the reported Productivity of crops. The APV systems (mostly experimental) documented in the literature are
shown in the map of Figure 3, where arid regions APVs are highlighted in yellow.
Improving water use efficiency is one of the best documented APV outcomes reported in the literature. It was
found in some settings that shading can result in help in reducing summer water evaporation of plants by 1429% depending on the level of shade ((Dinesh & Pearce, 2016). Also, the improvement of crop photosynthetic
performance can be achieved by preventing excessive heat and light stress. The APV setup, at the same time,
requires low LSPs to avoid significant plant productivity losses. The extent of solar radiation reduction under an
APV setup depends on multiple factor including seasonal solar altitude, the position of plants under PV panels,
and technical implementation of APV setup which includes orientation of panels, tilt angle and row spacing
between them (Weselek et al., 2019). In the literature, there are many studies that examined the effects of shade
on crops productivity. However, only few were done under an APV setup. Most of these studies were carried
out under agroforestry systems or artificial lighting conditions (Weselek et al., 2019) One of the few studies
carried out under an APV setup, was the one of (Marrou, Dufour, et al., 2013; which experimented different
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lettuce varieties with 3.2m PV panel spacing allowed 73% of the incoming radiation to reach the plants resulting
in a relative yield of 81-99% compared with the full-sun control setup.
APV had been implemented in few arid and semi-arid locations around the world and in fact as far as I
know no APV system has been implemented in the MENA region so far. Only few systems were
implemented in semi-arid regions. Table 1 shows the features of two sample systems. A notable setup was
implemented at the university of Arizona through a collaboration between the Department of Agriculture and
the University of Arizona’s Biosphere 2 institute (Barron-Gafford et al., 2019) The adopted crops were tomatoes,
peppers, swiss chard, jalapeno, kale, and herbs. A monitoring system was implemented to measure the yield as
well as microclimatic conditions and water use. The authors showed that soil moisture remained approximately
15% higher in the Agri-voltaic system when compared with a control plot without PV but analogous irrigation
conditions. Pepper productivity was tripled in an Agri-voltaic system, similarly tomato production was doubled.
Jalapenos produced a similar amount of fruit in both the Agrivoltaic systems and the traditional plot but did so
with 65% less transpiration water loss (Barron-Gafford et al., 2019) .
Table 1: Examples of the APV installations in arid regions documented in the literature
Name of
the APV
Type of plant
(lat, long)
University of
ere 2 lab
states of
'N 110°51'04.8
Potato, clover
cherry tomato,
Swiss chard,
and kale
Gafford et
al., 2019)
es are
Huawei Fusion
, China
'N 106°06'29.2
berry shrubs:
goji, and
c systems
g, n.d.)
A second example of an arid region based APV can be found in Ningxia city located in Ningxia province in
North Eastern China. This system was implemented by Baofeng Group, a Chinese Internet information services
in 2014 with initial capacity of 640 MW which was upgraded recently to one GW. The project was built over a
desertified land over an area of more than 100 km2(Blueberries are grown under giant agrivoltaic systems |
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Blueberries Consulting, n.d.). The land below the panels was initially cultivated with alfalfa which was then
removed and replanted with berry shrubs including blueberries, goji berries, and buckthorn. The project
representatives reported that the irrigation water use was greatly reduced which is attributed to lower evaporation
which was reported to be reduced by 30-40%. Additionally, the vegetation cover was increased by 85%
compared to original conditions before the implementation of the project. The solar panels were installed at 2.9
m clearance to allow for operators to move. The system is intelligently monitored through the smart management
system developed by Huawei.
3.1 Experimental campaign
The main aim of the Project is to assess
the viability and potential of applying
innovative APV solutions
in arid
region. To successfully implement
APV, it is essential to have the right
crops, right irrigation system, and right
solar technology. This project will
involve experimental and modeling
parts in addition to the aforementioned
design module. The goal of the
experimental campaign to quantify
the changes in surface energy budget,
Figure 4: The proposed configuration of the testing plots including the
monitoring system.
deriving from the implementation of different APV technologies (traditional PVs versus TLo’s). Despite
water use and crop productivity,
these potential benefits, the magnitudes of these effects have not yet been quatified in an experimental system
in a hyperarid region like the UAE. To do so in an objective manner, a comprehensive plan is needed that details
all the aspects pertaining to the different implementation aspects of the project is needed. Particularly, the
following design and implementation problems needs to be addressed: 1) a proper methodology of installation
of the system’s compoenets and a suitable design of the test field including the solar technology, irrigation
system, soil preparation and soil amenedments are needed; 2) Proper selection crieria of the crops, accounting
for the main stressors of plants in arid regions; 3) A suitable design of the project plant where an indiviual
account of the the effects of APV on solar and agricultural systems’ performace can be compared. This goals
can be fullfilled by agivoltaic test fields adopting the ‘four plots’ scheme shown in Figure 4. Plot 1 (bare soil)
is here devoted to the assessment of the energy budget in bare soil conditions. At this goal, observations of net
radiation (CNR4 net radiometer), 2D wind speed and direction (WINDSONIC4 sonic anemometer), and
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potential evapotranspiration (WMO standard evaporation pan) are collected. Plot 2 (vegetated plot) will serve
as reference crop productivity and will yield the partitioning between sensible and latent heat using Bowen ratio
technique using measurements of air temperature and relative humidity (HMP155A Vaisala temperature/RH
probe), upwelling (IR) radiation (CS300 pyranometer), and wind speed at two different heights. Also, surface
energy closure will be evaluated through the estimation of heat fluxes from the soil - through soil temperature
(CS108 temperature probe), soil water content (CS655 water content reflectometer) and soil heat-flux (HFP01SC
soil heat flux plate) probes. Plot 3 (PV) will assess the surface energy partitioning in the presence of PV modules
(instrumental setup as in Plot 2). Plot 4 (APV) is used to assess the performance of the actual APV system. The
monitoring system set-up will be the same as in Plot 2 and 3 measuring the partition and surface energy budget
My effort at this stage will be concentrated on providing support for the design of the test fields and crops
selection. Part of this goal has been achieved through the crop selection criteria based on the literature review.
More work is although needed on the irrigation system design and water efficiency optimization.
3.2 Modeling the soil water budget under different APV configurations
On the other hand, it is necessary to model the changes and parameters under different installation specifications.
This modeling exercise will complement and help interpret the results obtained from the experimental campaign.
The modeling shall include long term (climatological) simulations of the effects of the different irrigations
methods on the field by developing a simple model which will help anticipate and verify water saving and saltaccumulation (comparing to observed data). Additionally, modeling can simulate the effects of shadowing or
reduced radiation in the system in order to factor in the effects
of PV shadowing in the model. Specifically, the effects of
diffuse radiation shall be simulated which are anticipated to
constitute the majority of the light reaching the crops in the
case of TLos. Ultimately, the goal of the modeling part is to
develop a parsimonious stochastic model of soil-water
balance under irrigated condition in addition to the effects of
shadowing which differs with each solar technology. This
modeling exercise will support the estimation of water use
patterns under different APV configuration (in addition to
surface energy budget), both through transient and steady
state simulations.\
In an irrigated system, at the plot scale the soil water balance Figure 5: Schematic representation of the soil
water budget.
can be summarized through the following stochastic budget:
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𝑛𝑍# $& = 𝑅(𝑡) − 𝑬𝑻(𝒔, 𝑪, 𝒔𝒉𝒂𝒅𝒐𝒘𝒊𝒏𝒈) − 𝐿(𝑠, 𝑡)+ Irrigation
Where: n is the soil porosity ,Zr the root depth , R the precipitation input (random, and modeled as a Marked
Poisson Process), ET the evapotranspiration, s the relative soil moisture, L the leakage losses and C is the
concentration of soluble salts in the soil. This balance need to be coupled with the dynamic of the salt mass in
the soil (see Figure 5). The solutions of stochastic equations are given in terms of steady state or transient
probability density functions and not as deterministic values.
Contribution and work done so far is summarized in the Gantt chart of table 2. Future work will include
both experimental, modeling, and validation components as shown in the below Gantt chart of table 3.
Table 2: Gantt chart of work done.
Tasks & Activities
Q3/ Q4
Q1/ Q2
Q3/ Q4
T1.Work done
T1.1: Review the literature for traits relevant to agriculture in Arid
T1.2: Parameterizing, Quantifying, and reporting values for crops
T1.3: Review literature for APV setups
T1.4: Developing a database for crop selection(including main &
ancillary traits)
T1.5: Developing a database detailing existing APV setups
(including arid regions-based installations)
T2.Work almost done
T2.1: Review paper about APV and food security
Table 3: Gantt chart of future work.
Tasks & Activities
Q1/ Q2
Q3/ Q4
T3: Test field tasks
T3.1.2: Support field implementation
T4: Modeling tasks
T4.1: Select irrigation system
T4.2: Define, implement, and test soil water balance model accounting for shadowing.
T4.3: Define, implement, and test surface energy budget functions.
T5: Validation task
T5.1: Verifying the developed models through measurements and interpreting the results.
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Barron-Gafford, G. A., Pavao-Zuckerman, M. A., Minor, R. L., Sutter, L. F., Barnett-Moreno, I.,
Blackett, D. T., Thompson, M., Dimond, K., Gerlak, A. K., Nabhan, G. P., & Macknick, J. E.
(2019). Agrivoltaics provide mutual benefits across the food–energy–water nexus in
drylands. Nature Sustainability, 2(9), 848–855. https://doi.org/10.1038/s41893-0190364-5
Blueberries are grown under giant agrivoltaic systems | Blueberries Consulting. (n.d.).
Retrieved October 28, 2020, from https://blueberriesconsulting.com/en/arandanos-secultivan-bajo-gigantes-sistemas-agrivoltaicos/
Dehghanisanij, H., Oweis, T., & Qureshi, A. S. (2006). Agricultural water use and management
in arid and semi-arid areas: Current situation and measures for improvement. Annals of
Arid Zone, 45(3–4), 355–378.
Dinesh, H., & Pearce, J. M. (2016). The potential of agrivoltaic systems. Renewable and
Sustainable Energy Reviews, 54(October), 299–308.
Koch, M., & Missimer, T. M. (2016). Water resources assessment and management in
drylands. Water (Switzerland), 8(6), 1–5. https://doi.org/10.3390/w8060239
Marrou, H., Dufour, L., & Wery, J. (2013). How does a shelter of solar panels influence water
flows in a soil-crop system? European Journal of Agronomy, 50, 38–51.
Marrou, H., Guilioni, L., Dufour, L., Dupraz, C., & Wery, J. (2013). Microclimate under
agrivoltaic systems: Is crop growth rate affected in the partial shade of solar panels?
Agricultural and Forest Meteorology, 177(August), 117–132.
Weselek, A., Ehmann, A., Zikeli, S., Lewandowski, I., Schindele, S., & Högy, P. (2019).
Agrophotovoltaic systems: applications, challenges, and opportunities. A review.
Agronomy for Sustainable Development, 39(4), 1–20. https://doi.org/10.1007/s13593019-0581-3
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