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A comprehensive water balance methodology for collective irrigation systems
Agricultural Water Management 223 (2019) 105660
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A comprehensive water balance methodology for collective irrigation systems
T
Henrique Cunhaa, , Dália Loureiroa, Gonçalo Sousab, Dídia Covasc, Helena Alegrea ⁎
a
Hydraulics and Environment Department, National Laboratory for Civil Engineering, Av.do Brasil 101, 1700-066, Lisbon, Portugal Associação de Regantes e Beneficiários do Vale do Sorraia, R. 5 de Outubro 14, 2100-127, Coruche, Portugal c CERIS, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001, Lisbon, Portugal b
ARTICLE INFO
ABSTRACT
Keywords: Collective irrigation systems Water balance Water losses
This paper presents the development and application of a comprehensive methodology for the systematic water balance calculation in collective irrigation systems (CIS), applicable to pressurized pipelines or open canals. Existing approaches focus solely on the assessment the water resources use efficiency of CIS single components (e.g., leakage in some canal reaches), without a system-wide approach. A water balance approach allows accounting for the different system volume inputs (i.e., water abstraction, imported water, water volume due to precipitation or surface runoff), authorized and non-authorized consumptions and water losses either in canal, mixed or pressurized CIS, which has never been presented in literature. The proposed methodology allows the assessment of different water loss components (i.e., evaporation losses, unauthorized uses, metering errors, leakage and discharges) and the calculation of water loss performance indicators that allow the identification of the main problems in terms of water losses and provides guidance about measures to control water losses. Although based on the existing and consolidated water balance schemes specifically developed for urban water supply systems, the proposed methodology includes novel components in terms of system input volume, authorized consumption and water loss that are specific of CIS. The methodology is tested and applied to a mixed collective irrigation system. Results show that the water losses due to discharges in canal systems can be one of the most relevant component of the non-revenue water, representing approximately half of its total volume, followed by leakage in canals and metering errors. These results highlight the importance of improving daily operation of these systems and also rehabilitating ageing infrastructures.
1. Introduction The agricultural sector is responsible for ca. 70% of the freshwater consumed volume in the world (Molden, 2007). As the world population grows, food demand increases and a higher pressure is put on irrigated agriculture that, despite representing only 20% of the total cultivated land, contributes in 40% to the total food produced worldwide (FAO, Aquastat 2019). Thus, more water is required to meet food production requirements. Irrigation systems allow the compensation of the precipitation time and space irregularity, being fundamental that these systems use water resources efficiently. Collective irrigation systems (CIS) are infrastructures composed of a set of assets, which assure the abstraction, storage, conveyance and distribution of water to the users. Water can be abstracted either from surface sources (rivers and reservoirs) or from groundwater wells. The conveyance and distribution can be made either through canals or
⁎
pressurized pipelines. In terms of the delivery to irrigation users, diversion structures, also known as turnouts, are typical of canal delivery and water meters of pressurized networks. CIS are usually managed by Water Users Associations (WUAs), who are responsible for system operation and for assuring an adequate level of service for the consumers. As for the delivery methods, the service can be classified as on-demand, scheduled or rotation, depending on the system flexibility (FAO, 2007). The latter is the most rigid method, on which the system manager sets a delivery schedule, obliging the users to use water in a specific time and during a limited period. In systems operating under scheduled delivery, users must specify the time and the volume of water they wish in advance (US Department of Interior 1991), allowing the system manager to operate the system according to its needs. A drawback of this concept is the low efficiency due to the higher water loss volumes caused by frequent canal flow control needs (Rijo, 2010). On-demand distribution is the most common method used in pressurized systems, having only
Corresponding author. E-mail address: [email protected] (H. Cunha).
https://doi.org/10.1016/j.agwat.2019.05.044 Received 28 January 2019; Received in revised form 24 May 2019; Accepted 27 May 2019 0378-3774/ © 2019 Elsevier B.V. All rights reserved.
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one constraint – the flow – that is physically imposed by the outlets characteristics (Rijo, 2010). The canal systems are controlled by their delivery method and by the hydraulic structures used to control water levels (FAO, 1975). Canal check gate structures are flow control structures responsible for the regulation of the water level inside the canal, being usually located near turnout structures to ensure the minimum hydraulic head. Irrigation canals usually operate at a flow rate that changes over time depending on water demand (Burt, 1995), increasing the system operation complexity. Upstream water level control consists in controlling the water level upstream of each control structure, while manually operated systems require numerous structures to be adjusted whenever the flow regime changes (FAO, 2019). These systems tend to have higher water loss volumes not only due to canals’ leakage but also due to their manual operation which result in high discharge volumes (Burt, 1995). Intermediate reservoirs allow to store part of the excessive flows that otherwise would be lost in canal discharges, and, at the same time, allow faster response times to water demand at downstream. Water losses in canals are highly dependent on the soil permeability, canal lining, depth of water and groundwater levels. The soil plays a major role in canal leakage, with recent studies demonstrating that soil compaction is also a critical aspect of seepage reduction (Alam and Bhutta, 2004). Rates of canal seepage between 25 and 50 L/(m2.day) have been generally accepted as reference values for canals that fulfil their undertakings (Montañés, 2006). Water consumption in canal systems can be measured by modules equipped with a stopwatch. Operation of these modules is done by the opening of certain slots, according to the flow requests downstream. These slots are designed to assure a certain flow, as long as the water level upstream fits in a certain range. As for the metering devices used in pressurized systems, paddle wheel meters are usually installed due to their ability to allow suspended solids in the flow without damaging the equipment (Arregui et al., 2006). In these meters, an impeller on the upper part of the meter is responsible for measuring the flow, integrating the velocity in the same upper part. Although, differences between the average velocity inside the pipe and the one metered by the meter can be quite significant, which diminishes the measuring performance of the paddle wheel meter when compared to meters with different operating principles (Arregui et al., 2006). Besides the factors mentioned above that can affect measurements, upstream conditions also play a major role on the meter accuracy. These meters are quite sensitive to perturbations of the velocity profile. Tests in laboratory show that the effects of a partially closed gate valve placed at a distance of three diameters at upstream can lead to very high under metering errors (up to 30%) (Arregui et al., 2005). The performance of irrigation systems is dependent of on-farm water use efficiency, assets structural condition and manpower requirements for the system operation. A different water balance approach from the one presented is commonly used by farmers to assess crop water demands and set up irrigation scheduling (FAO, 2017). Traditionally, approaches to evaluating the performance of irrigation schemes are focused on gross production and efficient water use (Clemmens and Molden, 2007). In the past, approaches were focused on ensuring an adequate supply to farms (Molden and Gates, 1990). These approaches assist irrigation managers to improve water delivery service to users, but do not allow cross-system comparisons. Bos (1997) recommends a set of performance indicators to be used in irrigation and drainage performance assessment. These indicators aim to evaluate the level of service provided by covering not only a volumetric dimension but also evaluating sustainability and equity aspects (Bos and Nugteren, 1990; Bos, 1997). A more in-depth analysis can be carried out to the conveyance system and the distribution network by evaluating, respectively, the supply efficiency (i.e., the ratio between abstracted water volume and supplied volume to the distribution system) and the distribution efficiency (i.e., the ratio between water received by the distribution system and the water supplied to the users) (Bos and
Nugteren, 1990). In a broader scope, Molden et al. (1998) define a set of indicators which relates outputs from irrigated agriculture to inputs (water, land and finance). Results allow an initial screening of systems’ performance in different environments (Molden et al., 1998). Although performance of irrigation schemes is site specific, continual improvement through benchmarking allows comparison with future targets, previous performances (both internal) or against similar organizations (Malano and Burton, 2001). In fact, benchmarking is one of the most utilized tools to compare WUAs at service delivery and resource uses levels (Malano and Burton, 2001). Nevertheless, a systematic and standardized approach to individually characterize every component of water used in conveyance and distribution systems in terms of consumption and water loss, is lacking. The water balance proposed by Alegre et al. (2006) for urban water supply systems has become a valuable tool to carry out the systematic assessment of water losses in water services (Alegre et al., 2006). A reliable water balance allows utilities to carry out the diagnosis of their systems, to establish tactical plans to reduce water losses, to improve the infrastructure asset management and to continuously monitor the effectiveness of implemented measures/actions. The water balance developed for urban water supply systems cannot be directly applied to all collective irrigation systems since the latter can include not only pipes but large reservoirs and open canals that are subjected to different system input volumes and water losses (e.g., evaporation, canal discharges, variation of reservoir storage). Although these different components are already evaluated by WUAs, an integrated approach on which systems are analyzed as a whole is still missing. The current paper presents several innovative contributions to current knowledge. The first is the development of a comprehensive water accounting methodology specific for collective irrigation systems, grounded on the consolidated approach for urban water systems, but including other assets, such as canals and intermediate reservoirs. The scope of application is the conveyance system and the distribution network, up to the point of delivery to the consumers; it does not involve reservoirs at the inlet of the system, neither the farms’ irrigation systems. The second novel contribution is the detailed description of methods for assessing different types of water losses (e.g., evaporation losses, metering errors, leakage, overflows and discharges) and water input volumes (e.g., canal inflows, reservoirs volume variation) that occur in these assets. The third is the methodology demonstration using a real-life case study with the assessment of the importance of each water loss component and guidance on measures to improve efficiency. 2. Methodology 2.1. Novel water accounting method A comprehensive water accounting methodology specific for collective irrigation systems is proposed and described herein. The first step is the definition of the irrigation system boundaries and the reference period. The analyzed system should include all the conveyance and distribution infrastructures of water to farms and for which the water use efficiency aims to be improved. The reference period for the water balance calculation in collective irrigation systems should correspond to the period in which the system is operated (i.e., irrigation is performed). Therefore, a reference period shorter than the irrigation seasons is not recommended due to gaps between readings of system input volumes and consumptions in farms. The presented analysis is focused on fluxes of water that cross the defined boundaries during the period on which the system is operating. It is substantially different from the typical water balance analysis performed (FAO, 2017), since its boundaries, and consequently its components, are considerably different, as it is shown in Fig. 1. The water balance boundaries do not include irrigation fields or catchments (marked in grey), rather only the conveyance and distribution network of irrigation systems up to the point of delivery to its 2
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closing the water balance with higher accuracy levels. The system input volume sub-components addressed are related with precipitation, runoff and intermediate reservoirs storage, with new authorized sub-components (i.e., minimum operational volume) and canal-related water loss components (i.e., evaporation losses, canal leakage and discharges) also being covered. It should be noted that a component related to the water inflow through canal linings is not considered herein since the hydraulic head is higher inside the canal; this can be explained by the lower velocities registered in groundwater flows, allowing the respective kinetic head to be neglected (Quintela, 2010). If these inflows can be significant on the region where the water balance is to be applied, further studies should be carried out in order to evaluate the associated flows. Some of these components that are assessed by WUAs are mainly used for the daily operation of the system (e.g., canal discharges). However, there is no assessment in a larger time scale (i.e., irrigation season) and with a system-wide view of the different water components. In the following sections, new components of the proposed water balance for collective irrigation systems will be detailed, and when necessary, suggested methodologies to estimate each of them will be presented.
Fig. 1. System boundary to consider for water balance calculation in CIS.
users and to existing system discharges. As a result, the proposed water balance considers components that are different from the ones typically used. Since the system may include open canals and intermediate reservoirs, new components should be considered when calculating the water balance. The proposed water balance scheme specific for collective irrigation systems is presented in Fig. 2. The procedure for the water balance calculation is similar to the one carried out for urban water systems being composed of nine main steps, as follows: 1 Estimate system input volume sub-components (i.e., abstracted water, imported water, precipitation, runoff and intermediate reservoir contributions). 2 Calculate the revenue water, summing the billed metered consumption and the billed unmetered consumption. 3 Calculate non-revenue water by subtracting the revenue water (2) to the system input volume (1). 4 Estimate the unbilled authorized consumption and determine the authorized consumption. 5 Obtain the total water losses volume by subtracting the authorized consumption (4) to the system input volume (1). 6 Estimate evaporation losses in canal and intermediate reservoirs by the most appropriate method available. 7 Assess apparent losses components by the most appropriate methods available. 8 Estimate real losses by subtracting evaporation (6) and apparent losses (7) from total water losses (5). 9 Assess real loss components by best methods available and crosscheck with the real losses volume previously obtained in (8).
2.2. System input volume due to precipitation in canals and intermediate reservoirs In open canals and intermediate reservoirs, the precipitation that directly occurs on the surface area is included in the system’s input volume. Precipitation data, canal reaches and intermediate reservoir geometry, as well as their geographic locations, are required to estimate the input volume due to precipitation. The calculation is carried out for each canal reach, which is defined by the canal length between two consecutive water level control structures, using data from the nearest weather station. If the geographic information is not available, the average value from existing weather stations should be used. The total volume that entering the system due to direct precipitation is obtained by multiplying the precipitation head, P (m), by the canal/reservoir surface area, A (m2). Although the canal width varies with the water level in canals with trapezoidal cross-sections, it is assumed that all the water that falls inside the canal slopes ends up reaching the flow, being neglected water losses occurring in the canal slopes (e.g. infiltration or evaporation). Therefore, the canal surface area is the one that corresponds to the top width of the canal. The same approach is applied for intermediate reservoirs, considering the flooded area at the maximum storage level as the calculation area for the precipitated volume. A typical canal cross section is presented in Fig. 3.
The steps above might also be described as a top-down approach, on which the total value for the real losses components is estimated. Afterwards, as described in step number 9, the water balance calculation follows a bottom-up approach where real loss components should be assessed. Results obtained following these two approaches assist on
Fig. 2. Water balance components for collective irrigation systems. 3
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located outside the conveyance and distribution system (e.g., customers that use water directly from catchments) should not be considered for the water balance calculation. At the beginning of the irrigation season, before the system starts operating, it is required to fill up the canal network to guarantee water to the users. As in these canals the derivation from one canal to another, or the delivery to the user, is done by water intake structures, it is required a certain water level at the water intake. The water volume inside the canal required to reach the water intake is referred to as the minimum operational volume. Since this volume is usually discharged at the end of the irrigation season, for the water balance purpose it is considered as authorized unbilled and unmetered consumption. If stored, for example in intermediate reservoirs, the volume would be included in system input volume due to intermediate storage. A schematic sketch of the minimum operation volume and the water levels involved in its determination is presented in Fig. 4.
Fig. 3. Irrigation canal cross-section details.
2.3. System input volume due to surface runoff Surface flows can also occur, depending on the rainfall intensity and duration and on the soil characteristics. If there are infrastructures that allow the inlet of these flows, such as intermediate reservoirs or water streams, their volumes should be calculated and included in the water balance. When considering artificial canals, it is admitted that the canal and the surface water drainage system, which prevents runoff from getting into the canal, are built side by side (Fig. 3). The methodology used to estimate this component depends on available data. In case these inflows are metered, collected data should be used. If very few information is available, a lower bound for the runoff volume might be given, for example, by the revenue water during the time without any water collected from system sources. On the other hand, if in a particular part of the system the runoff is the only unknown variable, a water balance can be calculated for the sub-system to estimate this variable. The runoff volume can also be estimated using a mathematical relationship between the volume of water precipitated in a specific basin and the volume of water stored inside the same basin. This empirical relationship is often calculated to estimate inflows to the WUA main reservoirs and can be used to estimate runoff volumes. Lastly, another possible estimation for the runoff can be through a sequential water balance. This method requires assessing a soil parameter, which describes the soil water holding capacity, therefore requiring a more in-depth study of the basin.
Fig. 4. Variables for calculation of the minimum operation volume in canals.
The calculation of this volume should be done for each canal reach with the required water level being given by the further downstream water intake level. The downstream water depth for the minimum volume calculation (hd,min) is given by:
hd, min = hd
2.4. System input volume due to intermediate storage
where hd is the water height downstream the reach (m) and Hintake is the nominal hydraulic head of the water intake (m). Upstream water depth for the minimum volume estimation (hu,min) is calculated as follows:
The water balance inside the reservoirs should be calculated to estimate intermediate reservoirs positive or negative contribution to the global balance of the irrigation system. The reservoir volume variation is given by:
V = (Vin + Vp + Vrun off )
(Vout + Vevap + Vleaks + Vd)
(2)
Hintake
hu, min = hdown, min
(3)
L×i
where L is the canal reach length (m), and i is the canal reach slope (m/ m). Knowing the total length of the canal reach and the cross-section for each water depth (Aup,min and Adown,min), the minimum operation volume (Vmin) is calculated as follows:
(1)
where Vin is the volume from the canal to the reservoir, Vp is the precipitated volume in the reservoir, Vrun off is the affluent runoff volume to the reservoir, Vout is the volume from the reservoir to the canal, Vevap is the evaporated volume in the reservoirs, Vleaks is the volume of leaks and Vd is the volume of discharges from the reservoir. A positive volume variation in the intermediate reservoir means that water has been accumulated in the reservoir. Therefore it contributes to system global input volume with a negative volume. Conversely, a negative volume is associated with the reservoir water level decrease, having this system input volume component a positive value.
Vmin =
Au, min + Ad, min ×L 2
(4) 2
where Au,min is the upstream cross-section area (m ) and Ad,min is the downstream cross-section area (m2). 2.6. Water loss components In the proposed water balance for CIS, the water loss components covered in the water balance for urban water supply systems are also considered (i.e., apparent losses and real losses). Also, new water losses components related to canal system and intermediate reservoirs should be taken into account. The latter ones are divided into canal or intermediate reservoir leakage, evaporation and discharges. Water losses components, with special emphasis on components that should be estimated for canals and intermediate reservoirs, are described in the current section. When accounting for the water losses due to evaporation, if open canals or intermediate reservoirs are part of the system, estimations should be conducted. Similar to the precipitation estimations, data from
2.5. Authorized consumption Water consumption is divided into billed or unbilled and metered or unmetered components. Beyond water uses and consumptions that occur inside the system, if the WUA exports water to any other system, the transferred volume should also be considered as authorized consumption. The billed authorized consumption should be obtained from the WUA’s billing system, taking into account metered and unmetered volumes delivered to irrigators or other customers (e.g., industrial or urban). This component is also known as revenue water. It should be noted that customers supplied by the WUA infrastructure should be considered. Authorized customers that have their intake infrastructure 4
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the weather stations (i.e., precipitation records) should be collected in order to estimate the evaporation volume. If evaporation data is not available, it is proposed to estimate evaporation using Thornthwaite empirical formula:
ETp = 16Nm
10T¯m Ia
Table 1 Water surface area values for evaporation estimation in canal.
a
(5)
where Nm is a correction factor according to the latitude and time of the year, T¯ m is the average monthly temperature (°C), Ia is the annual
thermal index, and a is a polynomial function of the index. The reason why Thornthwaite empirical formula is proposed in this methodology is due to its simplicity (it only requires to know average monthly temperatures) when compared to other empirical approaches that demand more data. Studies conducted in northeastern USA (Rosenberry et al., 2007) and in southern Portugal (Rodrigues, 2009) concluded that, when compared with the results obtained by the energy balance calculation, Thornthwaite formula provided valid evaporation estimates. However, when evaluating evaporation in other regions, it is recommended to check the adequacy of this method. Evaporation volume is obtained by multiplying the estimated evaporation during the reference period by the water surface area. In intermediate reservoirs, flooded area records for each month of the reference period should be used to estimate evaporation volumes. In case these are not available, the area corresponding the full storage level should be considered. However, this can lead to an overestimation of the real area. When estimating water surface areas for the canal network, the most accurate estimation is obtained by calculating the water surface profile for each canal reach. Nevertheless, this procedure is a demanding and time-consuming. Thus, more straightforward methods were analyzed in this study to estimate surface areas. A sensitivity analysis between three considered hypotheses a), b) and c) depicted in Fig. 5 was carried out in one reach of the conveyance system of the case study, in order to assess which one returns an area estimation closer to the one of the water surface profile. Hypothesis a) considers the water depth along the canal equal to the one at the downstream end; hypothesis b) considers the water depth along the canal equal to the one of the uniform equilibrium flow; and hypothesis c) considers the water
Description
Hypothesis
Surface area, As (m2)
Δ (%)
hw = hd hw = hu hupstream = hu hdownstream = hd Actual water level profile
a) b) c)
28 021 24 903 26 462
+ 4.9% −6.8% −0.9%
–
26 711
–
are two components also covered by the proposed water balance. The water supply in open canal systems is usually performed by WUA employees who are responsible for operating the flow control structures that deliver water to the users. In this way there is direct control of the number of users, reducing the chances of unauthorized uses. Either way, when the user is collecting water directly from the canal or the distribution is carried out by a pressurized system, unauthorized uses can still occur. Tampering or routing around the water meter are some examples of illegal uses that may happen. The WUA can perform periodic inspections in suspicious areas where illegal uses may be occurring, but estimating the unauthorized uses components is a difficult task. Users whose consumption is fairly different from the water demand of a certain crop should be studied in order to understand such deviation. To reduce the volumes associated with unauthorized uses, consistent monitoring of the system should be carried out. The other apparent loss component considered in the presented water balance is the metering errors. This component accounts for the deviations between the metered volumes and the real volumes delivered to the user. A variety of factors can be responsible for these deviations (e.g., type of meter, age, installation conditions, range of the metered flows) (Vermersch et al., 2016). When water consumption is metered in modules equipped with a stopwatch, the metering results from the integration of the modules discharge coefficient during the registered opening time. Sediments, lack of proper adjustment and erosion are some of the factors responsible for the change in the discharge coefficient of the modules (Jorabloo and Sarkardeh, 2010). Therefore, hydraulic performance of irrigation meters and modules should be assessed in order to evaluate the metering accuracy of these devices. As for real losses, similar to urban water supply systems, leakage in mains and storage tanks, as well as overflows, should also be considered. Depending on the leakage control policy of the WUA, bursts can be identified, allowing to estimate a volume of water lost in each event (i.e., during the event and repair) (Thornton et al., 2008). Due to the variety of conditions that one can encounter, seepage tests should be carried out. Between the various methods used to estimate canal seepage, ponding tests have been proved to be a method capable of producing results with a higher accuracy level (Alam and Bhutta, 2004). Lastly, a monitoring system should be installed in order to determine the canal discharges component in the water balance, and subsequently, data should be stored to be available for the water balance calculation. Measuring the canal discharges will not only allow to estimate the volumes discharged and increase the water balance reliability, but also improve the system management if updated and timely data are provided to the system manager.
Fig. 5. Water level hypothesis considered to estimate evaporation losses in a canal reach.
depth varying linearly between the previous two depths. Results show a negative variation of the water surface area of 6.8% in comparison with the actual water level profile, when assuming a constant water level equal to the water depth of the uniform equilibrium flow (hu), and a positive variation of 4.9%, when a constant level equal to the water depth downstream (hd) is used. In the proposed methodology, the water depth at downstream, hd, is the one given by the water depth control structure and the one at upstream, hu, is the water depth of the uniform equilibrium flow, also known as design water depth. This hypothesis is the one that has the least deviation from the estimation of the water surface profile area. The water surface profile was determined using the Direct Step Method for the design discharge of the canal reach. The comparison between the results of the water surface are estimations based on the three studied hypotheses is summarized in Table 1. As for the apparent losses, unauthorized uses and metering errors
3. Application 3.1. Case study description The proposed methodology is applied to a collective irrigation system in Portugal, a country where these infrastructures account for 35% of the total irrigated area (DGADR, 2014) and it is estimated that global water efficiency of these systems is below 65% (APA, 2012). This value that can, in part, be explained by their age and need of urgent 5
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rehabilitation interventions to reduce water loss (DGADR, 2014). The collective irrigation system – Aproveitamento Hidroagrícola do Vale do Sorraia (AHVS) – is located in Tejo river basin and lies alongside Sorraia river and two tributaries – Sôr and Raia rivers. The system conveyance is entirely in open canal. The distribution is carried out by a mixed system, composed of canals and pipes – assuring the connection of the conveyance system with the users. The total irrigated area is 16 351 ha. In this irrigation system, underflow gates (AMIL) are the canals water level control structures, which guarantee the required level for the intake structures (Neyrpic modules). The majority of users are farmers (responsible for 98% of the billed authorized consumption) with the remaining volume being consumed by two industries. The distribution method implemented by the WUA is a prior agreement method on which users must request water 24 h in advance, so the utility manager operates the system to supply the flow rate at the requested time. The primary water sources are Maranhão, Montargil and Magos reservoirs. The water collected at Maranhão reservoir is conveyed through Raia stream until Gameiro weir. This weir was built to enable two pumping stations to raise water to two distributors located at higher terrain levels. Downstream Gameiro weir is Furadouro weir which was built to feed the artificial conveyance canal of the system. At Montargil reservoir the water collected is conveyed in an artificial canal that meets the main conveyance canal in Santa Justa junction. Right before the Peso node, where the main conveyance canal splits in two, an intermediate reservoir was built. This reservoir stores surpluses volumes, reducing the discharged volume at downstream. Along the system, water is collected from the water line and enters the system through pumping stations. Magos reservoir is a catchment decoupled from the main system that together with a pumping station supplies water to a smaller canal network. A schematic representation of the system is presented in Fig. 6. The boundaries of the sub-system later considered for runoff estimation using water balance calculation are
water consumption is separated from other crops consumption. Fig. 7 shows the effect that precipitation changes have on the water demand by the users. In years with higher precipitation, billed metered consumption reaches lower values, whereas, when precipitation is scarce, water demand increases. This situation obliges WUA to manage water storage and system operation more efficiently in order to prevent users from not having supplied water in quantity and in the time they need. 3.2. Water balance calculation The reference period for the water balance calculation was established based on the availability of the service to the users during the year 2017. The agricultural season started in March 2017 and lasted until October 2017, with the system operating during this period. During this time, the total water collected from the system sources – reservoirs and pumping stations – calculated, being detailed according Table 2 Estimated system input volume components in 2017. System input components
Volumes (m3)
Abstracted water
174 362 955 10 699 315 Not applicable 167 878 3 352 4 669 247 (details in Table 3) Not applicable (closed reservoir)
Imported water Precipitation Runoff
from reservoirs from the river in canal in intermediate reservoirs to canal to intermediate reservoirs
Intermediate storage Total system input volume
0 (constant level) 189 902 746
to the source in Table 2. Water volumes abstracted from reservoirs were metered, unlike the abstracted volume from the river through pumping stations which result from estimations based on the nominal power and working time of each pump. In order to calculate the total input volume due to precipitation, data from the WUA’s weather stations was gathered and accumulated precipitation during the reference period was calculated for each weather station. Since there was no geographical information related to the canal reaches, the average value of the accumulated precipitation in the six stations was adopted for the whole canal network. For the weirs and the intermediate reservoirs, accumulated precipitations from the nearest weather station to each structure were adopted. Since part of the conveyance system is a stream, runoff volume estimations had to be conducted. The basin that drains to the system is the one associated to Raia stream, located between Maranhão reservoir and Gameiro weir. As a first approach, the billed volume at the beginning of the irrigation season, during a time without any reservoir input, was obtained. Having enough data to estimate the runoff volume by the three other methods, estimations were carried out, and obtained
Fig. 6. Collective irrigation system layout with subsystem boundaries.
also presented. Irrigation systems are highly dependent on precipitation, not only from a water storage point of view but also because it is a key factor influencing water consumption of the users. Billed meter consumption and precipitation records from 2013 to 2017 are depicted in Fig. 7. Since rice crop farmers are the largest water consumers in AHVS, with an average consumption in the last five years of 11 220 m3/ha, rice
Table 3 Hypothesis tested for estimating runoff volume in canal component during irrigation season.
Fig. 7. Annual billed volumes and average precipitation in the last five years. 6
Method
Runoff volume (m3)
Billed volume during the initial operation time Water balance Runoff/Precipitation relation in Maranhão water catchment Sequential water balance (hydrological) in Raia river basin until Furadouro section
1 049 670 4 669 247 5 700 000 48 000 000
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results are presented in Table 3. The estimated runoff volume obtained by calculating the sequential water balance returned a value (48 Mm3) with a higher order of magnitude than the remaining methods. This skewed estimation should be revised, and a better assessment of the soil parameter should be done. The estimations returned by the water balance (4.67 Mm3) and the runoff/precipitation relation (5.70 Mm3) seem coherent, converging to a value of the same order of magnitude. Both estimations are higher than the billed volume during the initial operation time (1.05 Mm3), a value obtained when supply to crops downstream of Furadouro section is ensured without any reservoir input. That estimation can be seen as rough estimation given by the WUA of the system input component to be estimated. The method adopted for the runoff estimation in this system was the water balance, given the fact that the required data were available and its calculation resulted from measured variables. The sub-system considered in the water balance for the runoff estimation is the one presented in Fig. 6. The subsystem input volumes were the abstracted volumes from Maranhão reservoir and the runoff volume. The revenue water and the water received by the canal constitute the authorized consumption, causing the discharge in the weir to be the only water loss considered. The supplied volumes by the WUA to the users (billed authorized consumption) were obtained from the billing system of the WUA since unbilled authorized consumption is not applicable in this system. About 95% of this volume was metered and the rest obtained with estimations based on the irrigated area and type of crop. Subcomponents related with water exportation, firefighting and WUA uses were not considered during the reference period, since the WUA does not have any record. The minimum operational volume was calculated for a conveyance canal reach and for a distribution canal reach that were considered as being representative of each system. The estimated volume for the
each structure. Results are presented in Table 5. As the WUA did not have information about any illegal consumption that may have occurred during the reference period, estimation of this component was done taking into account the lower probabilities of these phenomena to happen, when compared to urban water supply systems, due to the presence of WUA employees that guarantee a correct operation of the system. Employees are responsible to account for water requests, ensure good metering performance and operate flow control structures, leaving small room for unauthorized uses to happen. As for the metering errors, at this stage, no meters were tested. Nevertheless, the WUA started to collect essential data that will help to select the meters to be submitted to metering error auditing tests. This analysis was performed for meters installed in rice crops since it is the crop with the highest water consumption (Fig. 7). The flow meter distribution according to their age for two metering diameter classes is
Fig. 8. Age distribution of meters installed for rice crops.
presented in Fig. 8. Age distribution allows identifying a set of ageing meters, over than 12 years, with high values of metered volumes. This can cause changes in the performance characteristics of the meter, highlighting to the need of assessing the accuracy of meters operating under these conditions and considering their substitution by new equipment. Considering that rice crops consumption can be characterized by a steady flow during the peak months of the irrigation season, average flow rates in both diameter classes analyzed were obtained for each month. Results are presented in Fig. 9, as well as the metrological characteristics (Q1 and Q2) of two models of water meters currently in use: M1 and M2. As it is not possible to distinguish between DN80 and DN100 meters, and since DN100 meters is the prevailing diameter, the minimum flow (Q1) and the transitional flow (Q2) presented corre-
Table 4 Estimated minimum operational volume in system canals.
Conveyance system Distribution network Total
Extension (km)
Minimum operational volume (m3)
120.5 109.5 230.0
647 476 29 899 677 376
entire system is presented in Table 4. The next step of the approach is the estimation of the water losses components. As the collective irrigation system is mainly in open canal, evaporation losses were estimated. Similar to the minimum operation volume calculation, the evaporation estimation was carried out for the same two canals and then extrapolated for the whole network. Evaporation in the river part of the conveyance system was calculated considering an average surface width of 25 m and a total length of 32.6 km. Evaporation value considered was the average value recorded during the irrigation season between the WUA’s weather stations. The estimation for the intermediate reservoir and the two weirs was done with the evaporation value registered in the nearest weather station of
Fig. 9. Hourly mean flow between May and September in rice crops and comparison with minimum flow (Q1) and transitional flow (Q2) given according to metrological characteristics of two models of water meters (M1 and M2): (a) DN80-100 meters; (b) DN150 meters.
Table 5 Estimated water losses due to evaporation in canals and intermediate reservoirs in 2017.
Conveyance system (river) Conveyance system (canal) Distribution network (canal) Intermediate reservoir Weirs Total
Extension (km)
Evaporated volume (m3)
32.6 120.5 109.5 – – 262.6
647 925 615 460 91 833 16 127 89 629 1 460 974
spond to the ones from DN100 meters. Results show a distinct behavior between the two diameter classes during the peak consumption months – June, July and August. It is noticeable a growing trend of the average flow in the lower diameter classes, in contrast to the higher diameter class that shows a more stable behavior with a small decrease in the average volume towards the end of the irrigation season. According to the WUA, this can be explained by 7
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an intermittent operation of the meters at the beginning of the rice irrigation process. Taking into account meter technical characteristics, these average flow values fit between the minimum flow and the transitional in M2 model, a range where metering errors by default tend to be higher. Further analysis should be carried out in order to assess the effect that these inaccuracies have on the apparent losses component. Network pipes leakage was estimated considering the reference value of real losses for urban distribution systems with poor service quality, 5 m3/(km.day) (ERSAR and LNEC, 2013). The reason why a pessimistic value was considered is due to the age of the infrastructure, concrete pipes have ca. 60 years, which is beyond their expectable technical operating life, and several pipe bursts were reported by the WUA (Covas et al., 2018). Given the age of the canal network, some rehabilitation works have been carried out by the WUA so that continuous system operation is guaranteed. Nowadays, the canals’ condition suggests that the real losses may be over the values found in the bibliography. In order to estimate a value for the leaks in these assets, an inflow-outflow study was carried out in a representative reach of canal. The canal studied has an approximate length of 20 km, and at the time all the canal gates were closed. However, AMIL gates are not entirely watertight allowing the flow of a small discharge. At the canal head, the registered inflow was 150 L/s, and since there were no flow meters at downstream the canal, a value of 20 L/s was adopted as the outflow based on in-situ observations. The estimated flow associated with water leakage through the canal is 130 L/s, which corresponds to 53 L/(m2.day) water loss rate according to the canal geometrical characteristics. Later, the WUA carried out ponding tests in two canal reaches from the distribution network. Preliminary results alert to a key factor that affects canal water loss: soil. One of the canal reaches shows clear signs of deterioration, reason why it was expected to have higher water loss rates than the other canal reach which is in better conditions. However, the more degraded canal is operating in clayey soils which may explain a lower water loss rate than the one expected. Further works are being planned in order to increase the canal leakage estimation. The application of the proposed methodology for calculating the water balance in CIS has shown to be a challenging task in which several methodologies are still being tested for estimating the new components. The complete water balance for the 2017 irrigation season
in AHVS is presented in Fig. 10. The non-revenue water components are presented in detail in Fig. 11. Real losses volume is responsible for the most significant share (70%). Results indicate that the WUA actions should be focused on reducing the weight that real losses and apparent losses have on the
Fig. 11. Non-revenue water components in the system in 2017: (a) non-revenue components; (b) real losses components.
system water balance (ca. 33.7% of total input volume). When assessing real losses in a mixed system, such as AHVS, canalrelated components such as discharges and leakage should be considered. Canal discharges are estimated in 48.9% of the non-revenue water, which highlights the need to improve the estimation of this component and to reduce system operational losses. Leakage in canals cannot be neglected as this represents around 20% of the non-revenue water in the analyzed irrigation system. 4. Conclusions A novel comprehensive methodology has been proposed and illustrated for the water balance calculation in irrigation systems. This methodology can become an important performance evaluation tool for both canal and pressurized systems, helping WUA to achieve more efficient water management practices. The water balance calculation allows to have a diagnosis of the system, in terms of system input volume, consumption (billed and unbilled) and water losses, helping WUAs to take improvement measures. The water balance is also an essential tool to calculate a set of water loss indicators which will allow WUAs to evaluate its performance over time and benchmarking different collective irrigation systems. The systematic water balance calculation for every irrigation season allows to evaluate the impact of improvement measures that were taken. Inspired on the urban water balance principles, the proposed water balance includes new components on the system input, authorized consumption and water losses. The methodology was tested for the first time in a WUA, highlighting the importance that real water losses have on the collective irrigation system. Hydrological modelling of the basin that contributes with runoff should be performed in order to validate the results obtained. Regarding metering errors, in pressurized systems, the water meters’ error should be assessed and, in open canal systems, the hydraulic performance of the modules responsible for the derivation of flow to the user should be evaluated, as part of the forthcoming works. The current work pointed out that some installed meters’ flow range does not match the range of water demand associated with rice crop demand; this is caused by an inappropriate meter size selection. Results highlight to the need to rehabilitate the conveyance and distribution infrastructures as well as
Fig. 10. Results of the water balance calculation for the system in 2017.
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reducing canal discharges. In the future, more CIS should be tested in order to consolidate the methodology and to improve canal leakage estimation. The water-energy balance scheme, following the principles proposed by Mamade et al. (2017) for urban water supply systems, is also being developed for irrigation systems.
Burt, C.M., 1995. The surface irrigation manual - A comprehensive guide to design and operation of surface irrigation systems. Exeter: Waterman Industries. Clemmens, A., Molden, D., 2007. Water uses and productivity of irrigation systems. Irrig. Sci. 25, 247–261. Covas, D., Cabral, M., Pinheiro, A., Marchionni, V., Antunes, S., Lopes, N., Mamouros, L., Brôco, N., 2018. Construction Costs of Infrastructures Associated to the Urban Wate Cycle. ERSAR. DGADR, 2014. Strategy for Public Irrigation 2014-2020 (in Portuguese). DGADR, Lisbon. ERSAR, LNEC, 2013. Guide to the Quality of Service Assessment for Drinking Water Supply, Urban Astewater Management and Municipal Waste Management Services 2nd Generation of the Assessment System (in Portuguese). ERSAR, Lisbon. FAO, 1975. Small Hydraulic Structures. FAO, Rome. FAO, 2007. Modernizing irrigation management - the MASSCOTE approach. Rome: FAO. FAO, 2017. Water Accounting and Auditing - a Sourcebook. FAO, Rome. FAO, 2019. AQUASTAT. Food and Agriculture Organization of the United Nations [Online]. [Accessed 2018/10/16 January 2019]. Jorabloo, M., Sarkardeh, H., 2010. Hydraulic evaluation of neyrpic-modules at water distribution network of Garmsar Plain. World Appl. Sci. J. 10 (no. 11), 1363–1367. Malano, H., Burton, M., 2001. Guidelines for Benchmarking Performance in the Irrigation and Drainage Sector. FAO, Rome. Mamade, A., Loureiro, D., Alegre, H., Covas, D., 2017. A comprehensive and well tested energy balance for water supply systems. Urban Water J. Molden, D., 2007. Water for Food, Water for Life: A Comprehensive Assessment of Water Management in Agriculture. Earthscan and IWMI, London. Molden, D., Gates, T., 1990. Performance measures for evaluation of irrigation-waterdelivery systems. J. Irrig. Drain. Eng. 116 (6), 804–823. Molden, D., Sakthivadivel, R., Perry, C., Fraiture, C., 1998. Indicators for Comparing Performance of Irrigated Agricultural Systems. IWMI, Colombo. Montañés, J.L., 2006. Hydraulic Canals - Design, Construction, Regulation And Maintenace. Taylor & Francis, Abingdon. Quintela, A.C., 2010. Hydraulics (in Portuguese), 12th edition. Calouste Gulbenkian Foundation, Lisbon. Rijo, M., 2010. Conveyance Canals - Design, Operation, Control and Modernization (in Portuguese). Edições Sílabo, Lda, Lisbon. Rodrigues, C., 2009. PhD thesis in engineering of Water resources. Calculation of Evaporation in High Regulation Reservoirs in Southern of Portugal (in Portuguese). University of Évora. Rosenberry, D., Winter, T., Buso, D., Likens, G., 2007. Comparison of 15 evaporation methods applied to a small mountain lake in the northeastern USA. J. Hydrol. (Amst). Thornton, J., Sturm, R., Kunkel, G., 2008. Water Loss Control, 2nd edition. McGraw-Hill, USA. US Department of the Interior, 1991. Canal Systems Automation Manual, Denver. Vermersch, M., Carteado, F., Rizzo, A., Johnson, E., Arregui, F., Lambert, A., 2016. Guidance Notes on Apparent Losses and Water Loss Reduction Planning.
Funding This research was funded by PDR2020 grant number PDR2020-101031878. Conflicts of interest The authors declare no conflict of interest. Acknowledgements The authors gratefully acknowledge all project AGIR partners that directly or indirectly contributed to the presented paper. A special thanks to Professor Madalena Moreira and Engineer Carina Arranja for the valuable contributions. References Alam, M., Bhutta, M., 2004. Comparative evaluation of canal seepage investigation techniques. Agric. Water Manag. Alegre, H., Baptista, J.M., Cabrera Jr., E., Cubillo, F., Duarte, P., Hirner, W., Merkel, W., Parena, R., 2006. Performance Indicators for Water Supply Services, 2nd edition. IWA Publishing, London. APA, 2012. National Program for the Efficient Use of Water (in Portuguese). Arregui, F., Cabrera Jr, E., Cobacho, R., García-Serra, J., 2005. Key factors affecting water meter accuracy. IWA Water Loss Conference. Arregui, F., Cabrera Jr, E., Cobacho, R., 2006. Integrated Water Meter Management. IWA Publishing, London. Bos, M.G., 1997. Performance indicators for irrigation and drainage. Irrig. Drain. Syst. Bos, M.G., Nugteren, J., 1990. On Irrigation Efficiencies, 4th edition. International Institute for Land Reclamantion and Improvement, Wageningen.
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Agricultural Water Management journal homepage: www.elsevier.com/locate/agwat
A comprehensive water balance methodology for collective irrigation systems
T
Henrique Cunhaa, , Dália Loureiroa, Gonçalo Sousab, Dídia Covasc, Helena Alegrea ⁎
a
Hydraulics and Environment Department, National Laboratory for Civil Engineering, Av.do Brasil 101, 1700-066, Lisbon, Portugal Associação de Regantes e Beneficiários do Vale do Sorraia, R. 5 de Outubro 14, 2100-127, Coruche, Portugal c CERIS, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001, Lisbon, Portugal b
ARTICLE INFO
ABSTRACT
Keywords: Collective irrigation systems Water balance Water losses
This paper presents the development and application of a comprehensive methodology for the systematic water balance calculation in collective irrigation systems (CIS), applicable to pressurized pipelines or open canals. Existing approaches focus solely on the assessment the water resources use efficiency of CIS single components (e.g., leakage in some canal reaches), without a system-wide approach. A water balance approach allows accounting for the different system volume inputs (i.e., water abstraction, imported water, water volume due to precipitation or surface runoff), authorized and non-authorized consumptions and water losses either in canal, mixed or pressurized CIS, which has never been presented in literature. The proposed methodology allows the assessment of different water loss components (i.e., evaporation losses, unauthorized uses, metering errors, leakage and discharges) and the calculation of water loss performance indicators that allow the identification of the main problems in terms of water losses and provides guidance about measures to control water losses. Although based on the existing and consolidated water balance schemes specifically developed for urban water supply systems, the proposed methodology includes novel components in terms of system input volume, authorized consumption and water loss that are specific of CIS. The methodology is tested and applied to a mixed collective irrigation system. Results show that the water losses due to discharges in canal systems can be one of the most relevant component of the non-revenue water, representing approximately half of its total volume, followed by leakage in canals and metering errors. These results highlight the importance of improving daily operation of these systems and also rehabilitating ageing infrastructures.
1. Introduction The agricultural sector is responsible for ca. 70% of the freshwater consumed volume in the world (Molden, 2007). As the world population grows, food demand increases and a higher pressure is put on irrigated agriculture that, despite representing only 20% of the total cultivated land, contributes in 40% to the total food produced worldwide (FAO, Aquastat 2019). Thus, more water is required to meet food production requirements. Irrigation systems allow the compensation of the precipitation time and space irregularity, being fundamental that these systems use water resources efficiently. Collective irrigation systems (CIS) are infrastructures composed of a set of assets, which assure the abstraction, storage, conveyance and distribution of water to the users. Water can be abstracted either from surface sources (rivers and reservoirs) or from groundwater wells. The conveyance and distribution can be made either through canals or
⁎
pressurized pipelines. In terms of the delivery to irrigation users, diversion structures, also known as turnouts, are typical of canal delivery and water meters of pressurized networks. CIS are usually managed by Water Users Associations (WUAs), who are responsible for system operation and for assuring an adequate level of service for the consumers. As for the delivery methods, the service can be classified as on-demand, scheduled or rotation, depending on the system flexibility (FAO, 2007). The latter is the most rigid method, on which the system manager sets a delivery schedule, obliging the users to use water in a specific time and during a limited period. In systems operating under scheduled delivery, users must specify the time and the volume of water they wish in advance (US Department of Interior 1991), allowing the system manager to operate the system according to its needs. A drawback of this concept is the low efficiency due to the higher water loss volumes caused by frequent canal flow control needs (Rijo, 2010). On-demand distribution is the most common method used in pressurized systems, having only
Corresponding author. E-mail address: [email protected] (H. Cunha).
https://doi.org/10.1016/j.agwat.2019.05.044 Received 28 January 2019; Received in revised form 24 May 2019; Accepted 27 May 2019 0378-3774/ © 2019 Elsevier B.V. All rights reserved.
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one constraint – the flow – that is physically imposed by the outlets characteristics (Rijo, 2010). The canal systems are controlled by their delivery method and by the hydraulic structures used to control water levels (FAO, 1975). Canal check gate structures are flow control structures responsible for the regulation of the water level inside the canal, being usually located near turnout structures to ensure the minimum hydraulic head. Irrigation canals usually operate at a flow rate that changes over time depending on water demand (Burt, 1995), increasing the system operation complexity. Upstream water level control consists in controlling the water level upstream of each control structure, while manually operated systems require numerous structures to be adjusted whenever the flow regime changes (FAO, 2019). These systems tend to have higher water loss volumes not only due to canals’ leakage but also due to their manual operation which result in high discharge volumes (Burt, 1995). Intermediate reservoirs allow to store part of the excessive flows that otherwise would be lost in canal discharges, and, at the same time, allow faster response times to water demand at downstream. Water losses in canals are highly dependent on the soil permeability, canal lining, depth of water and groundwater levels. The soil plays a major role in canal leakage, with recent studies demonstrating that soil compaction is also a critical aspect of seepage reduction (Alam and Bhutta, 2004). Rates of canal seepage between 25 and 50 L/(m2.day) have been generally accepted as reference values for canals that fulfil their undertakings (Montañés, 2006). Water consumption in canal systems can be measured by modules equipped with a stopwatch. Operation of these modules is done by the opening of certain slots, according to the flow requests downstream. These slots are designed to assure a certain flow, as long as the water level upstream fits in a certain range. As for the metering devices used in pressurized systems, paddle wheel meters are usually installed due to their ability to allow suspended solids in the flow without damaging the equipment (Arregui et al., 2006). In these meters, an impeller on the upper part of the meter is responsible for measuring the flow, integrating the velocity in the same upper part. Although, differences between the average velocity inside the pipe and the one metered by the meter can be quite significant, which diminishes the measuring performance of the paddle wheel meter when compared to meters with different operating principles (Arregui et al., 2006). Besides the factors mentioned above that can affect measurements, upstream conditions also play a major role on the meter accuracy. These meters are quite sensitive to perturbations of the velocity profile. Tests in laboratory show that the effects of a partially closed gate valve placed at a distance of three diameters at upstream can lead to very high under metering errors (up to 30%) (Arregui et al., 2005). The performance of irrigation systems is dependent of on-farm water use efficiency, assets structural condition and manpower requirements for the system operation. A different water balance approach from the one presented is commonly used by farmers to assess crop water demands and set up irrigation scheduling (FAO, 2017). Traditionally, approaches to evaluating the performance of irrigation schemes are focused on gross production and efficient water use (Clemmens and Molden, 2007). In the past, approaches were focused on ensuring an adequate supply to farms (Molden and Gates, 1990). These approaches assist irrigation managers to improve water delivery service to users, but do not allow cross-system comparisons. Bos (1997) recommends a set of performance indicators to be used in irrigation and drainage performance assessment. These indicators aim to evaluate the level of service provided by covering not only a volumetric dimension but also evaluating sustainability and equity aspects (Bos and Nugteren, 1990; Bos, 1997). A more in-depth analysis can be carried out to the conveyance system and the distribution network by evaluating, respectively, the supply efficiency (i.e., the ratio between abstracted water volume and supplied volume to the distribution system) and the distribution efficiency (i.e., the ratio between water received by the distribution system and the water supplied to the users) (Bos and
Nugteren, 1990). In a broader scope, Molden et al. (1998) define a set of indicators which relates outputs from irrigated agriculture to inputs (water, land and finance). Results allow an initial screening of systems’ performance in different environments (Molden et al., 1998). Although performance of irrigation schemes is site specific, continual improvement through benchmarking allows comparison with future targets, previous performances (both internal) or against similar organizations (Malano and Burton, 2001). In fact, benchmarking is one of the most utilized tools to compare WUAs at service delivery and resource uses levels (Malano and Burton, 2001). Nevertheless, a systematic and standardized approach to individually characterize every component of water used in conveyance and distribution systems in terms of consumption and water loss, is lacking. The water balance proposed by Alegre et al. (2006) for urban water supply systems has become a valuable tool to carry out the systematic assessment of water losses in water services (Alegre et al., 2006). A reliable water balance allows utilities to carry out the diagnosis of their systems, to establish tactical plans to reduce water losses, to improve the infrastructure asset management and to continuously monitor the effectiveness of implemented measures/actions. The water balance developed for urban water supply systems cannot be directly applied to all collective irrigation systems since the latter can include not only pipes but large reservoirs and open canals that are subjected to different system input volumes and water losses (e.g., evaporation, canal discharges, variation of reservoir storage). Although these different components are already evaluated by WUAs, an integrated approach on which systems are analyzed as a whole is still missing. The current paper presents several innovative contributions to current knowledge. The first is the development of a comprehensive water accounting methodology specific for collective irrigation systems, grounded on the consolidated approach for urban water systems, but including other assets, such as canals and intermediate reservoirs. The scope of application is the conveyance system and the distribution network, up to the point of delivery to the consumers; it does not involve reservoirs at the inlet of the system, neither the farms’ irrigation systems. The second novel contribution is the detailed description of methods for assessing different types of water losses (e.g., evaporation losses, metering errors, leakage, overflows and discharges) and water input volumes (e.g., canal inflows, reservoirs volume variation) that occur in these assets. The third is the methodology demonstration using a real-life case study with the assessment of the importance of each water loss component and guidance on measures to improve efficiency. 2. Methodology 2.1. Novel water accounting method A comprehensive water accounting methodology specific for collective irrigation systems is proposed and described herein. The first step is the definition of the irrigation system boundaries and the reference period. The analyzed system should include all the conveyance and distribution infrastructures of water to farms and for which the water use efficiency aims to be improved. The reference period for the water balance calculation in collective irrigation systems should correspond to the period in which the system is operated (i.e., irrigation is performed). Therefore, a reference period shorter than the irrigation seasons is not recommended due to gaps between readings of system input volumes and consumptions in farms. The presented analysis is focused on fluxes of water that cross the defined boundaries during the period on which the system is operating. It is substantially different from the typical water balance analysis performed (FAO, 2017), since its boundaries, and consequently its components, are considerably different, as it is shown in Fig. 1. The water balance boundaries do not include irrigation fields or catchments (marked in grey), rather only the conveyance and distribution network of irrigation systems up to the point of delivery to its 2
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closing the water balance with higher accuracy levels. The system input volume sub-components addressed are related with precipitation, runoff and intermediate reservoirs storage, with new authorized sub-components (i.e., minimum operational volume) and canal-related water loss components (i.e., evaporation losses, canal leakage and discharges) also being covered. It should be noted that a component related to the water inflow through canal linings is not considered herein since the hydraulic head is higher inside the canal; this can be explained by the lower velocities registered in groundwater flows, allowing the respective kinetic head to be neglected (Quintela, 2010). If these inflows can be significant on the region where the water balance is to be applied, further studies should be carried out in order to evaluate the associated flows. Some of these components that are assessed by WUAs are mainly used for the daily operation of the system (e.g., canal discharges). However, there is no assessment in a larger time scale (i.e., irrigation season) and with a system-wide view of the different water components. In the following sections, new components of the proposed water balance for collective irrigation systems will be detailed, and when necessary, suggested methodologies to estimate each of them will be presented.
Fig. 1. System boundary to consider for water balance calculation in CIS.
users and to existing system discharges. As a result, the proposed water balance considers components that are different from the ones typically used. Since the system may include open canals and intermediate reservoirs, new components should be considered when calculating the water balance. The proposed water balance scheme specific for collective irrigation systems is presented in Fig. 2. The procedure for the water balance calculation is similar to the one carried out for urban water systems being composed of nine main steps, as follows: 1 Estimate system input volume sub-components (i.e., abstracted water, imported water, precipitation, runoff and intermediate reservoir contributions). 2 Calculate the revenue water, summing the billed metered consumption and the billed unmetered consumption. 3 Calculate non-revenue water by subtracting the revenue water (2) to the system input volume (1). 4 Estimate the unbilled authorized consumption and determine the authorized consumption. 5 Obtain the total water losses volume by subtracting the authorized consumption (4) to the system input volume (1). 6 Estimate evaporation losses in canal and intermediate reservoirs by the most appropriate method available. 7 Assess apparent losses components by the most appropriate methods available. 8 Estimate real losses by subtracting evaporation (6) and apparent losses (7) from total water losses (5). 9 Assess real loss components by best methods available and crosscheck with the real losses volume previously obtained in (8).
2.2. System input volume due to precipitation in canals and intermediate reservoirs In open canals and intermediate reservoirs, the precipitation that directly occurs on the surface area is included in the system’s input volume. Precipitation data, canal reaches and intermediate reservoir geometry, as well as their geographic locations, are required to estimate the input volume due to precipitation. The calculation is carried out for each canal reach, which is defined by the canal length between two consecutive water level control structures, using data from the nearest weather station. If the geographic information is not available, the average value from existing weather stations should be used. The total volume that entering the system due to direct precipitation is obtained by multiplying the precipitation head, P (m), by the canal/reservoir surface area, A (m2). Although the canal width varies with the water level in canals with trapezoidal cross-sections, it is assumed that all the water that falls inside the canal slopes ends up reaching the flow, being neglected water losses occurring in the canal slopes (e.g. infiltration or evaporation). Therefore, the canal surface area is the one that corresponds to the top width of the canal. The same approach is applied for intermediate reservoirs, considering the flooded area at the maximum storage level as the calculation area for the precipitated volume. A typical canal cross section is presented in Fig. 3.
The steps above might also be described as a top-down approach, on which the total value for the real losses components is estimated. Afterwards, as described in step number 9, the water balance calculation follows a bottom-up approach where real loss components should be assessed. Results obtained following these two approaches assist on
Fig. 2. Water balance components for collective irrigation systems. 3
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located outside the conveyance and distribution system (e.g., customers that use water directly from catchments) should not be considered for the water balance calculation. At the beginning of the irrigation season, before the system starts operating, it is required to fill up the canal network to guarantee water to the users. As in these canals the derivation from one canal to another, or the delivery to the user, is done by water intake structures, it is required a certain water level at the water intake. The water volume inside the canal required to reach the water intake is referred to as the minimum operational volume. Since this volume is usually discharged at the end of the irrigation season, for the water balance purpose it is considered as authorized unbilled and unmetered consumption. If stored, for example in intermediate reservoirs, the volume would be included in system input volume due to intermediate storage. A schematic sketch of the minimum operation volume and the water levels involved in its determination is presented in Fig. 4.
Fig. 3. Irrigation canal cross-section details.
2.3. System input volume due to surface runoff Surface flows can also occur, depending on the rainfall intensity and duration and on the soil characteristics. If there are infrastructures that allow the inlet of these flows, such as intermediate reservoirs or water streams, their volumes should be calculated and included in the water balance. When considering artificial canals, it is admitted that the canal and the surface water drainage system, which prevents runoff from getting into the canal, are built side by side (Fig. 3). The methodology used to estimate this component depends on available data. In case these inflows are metered, collected data should be used. If very few information is available, a lower bound for the runoff volume might be given, for example, by the revenue water during the time without any water collected from system sources. On the other hand, if in a particular part of the system the runoff is the only unknown variable, a water balance can be calculated for the sub-system to estimate this variable. The runoff volume can also be estimated using a mathematical relationship between the volume of water precipitated in a specific basin and the volume of water stored inside the same basin. This empirical relationship is often calculated to estimate inflows to the WUA main reservoirs and can be used to estimate runoff volumes. Lastly, another possible estimation for the runoff can be through a sequential water balance. This method requires assessing a soil parameter, which describes the soil water holding capacity, therefore requiring a more in-depth study of the basin.
Fig. 4. Variables for calculation of the minimum operation volume in canals.
The calculation of this volume should be done for each canal reach with the required water level being given by the further downstream water intake level. The downstream water depth for the minimum volume calculation (hd,min) is given by:
hd, min = hd
2.4. System input volume due to intermediate storage
where hd is the water height downstream the reach (m) and Hintake is the nominal hydraulic head of the water intake (m). Upstream water depth for the minimum volume estimation (hu,min) is calculated as follows:
The water balance inside the reservoirs should be calculated to estimate intermediate reservoirs positive or negative contribution to the global balance of the irrigation system. The reservoir volume variation is given by:
V = (Vin + Vp + Vrun off )
(Vout + Vevap + Vleaks + Vd)
(2)
Hintake
hu, min = hdown, min
(3)
L×i
where L is the canal reach length (m), and i is the canal reach slope (m/ m). Knowing the total length of the canal reach and the cross-section for each water depth (Aup,min and Adown,min), the minimum operation volume (Vmin) is calculated as follows:
(1)
where Vin is the volume from the canal to the reservoir, Vp is the precipitated volume in the reservoir, Vrun off is the affluent runoff volume to the reservoir, Vout is the volume from the reservoir to the canal, Vevap is the evaporated volume in the reservoirs, Vleaks is the volume of leaks and Vd is the volume of discharges from the reservoir. A positive volume variation in the intermediate reservoir means that water has been accumulated in the reservoir. Therefore it contributes to system global input volume with a negative volume. Conversely, a negative volume is associated with the reservoir water level decrease, having this system input volume component a positive value.
Vmin =
Au, min + Ad, min ×L 2
(4) 2
where Au,min is the upstream cross-section area (m ) and Ad,min is the downstream cross-section area (m2). 2.6. Water loss components In the proposed water balance for CIS, the water loss components covered in the water balance for urban water supply systems are also considered (i.e., apparent losses and real losses). Also, new water losses components related to canal system and intermediate reservoirs should be taken into account. The latter ones are divided into canal or intermediate reservoir leakage, evaporation and discharges. Water losses components, with special emphasis on components that should be estimated for canals and intermediate reservoirs, are described in the current section. When accounting for the water losses due to evaporation, if open canals or intermediate reservoirs are part of the system, estimations should be conducted. Similar to the precipitation estimations, data from
2.5. Authorized consumption Water consumption is divided into billed or unbilled and metered or unmetered components. Beyond water uses and consumptions that occur inside the system, if the WUA exports water to any other system, the transferred volume should also be considered as authorized consumption. The billed authorized consumption should be obtained from the WUA’s billing system, taking into account metered and unmetered volumes delivered to irrigators or other customers (e.g., industrial or urban). This component is also known as revenue water. It should be noted that customers supplied by the WUA infrastructure should be considered. Authorized customers that have their intake infrastructure 4
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the weather stations (i.e., precipitation records) should be collected in order to estimate the evaporation volume. If evaporation data is not available, it is proposed to estimate evaporation using Thornthwaite empirical formula:
ETp = 16Nm
10T¯m Ia
Table 1 Water surface area values for evaporation estimation in canal.
a
(5)
where Nm is a correction factor according to the latitude and time of the year, T¯ m is the average monthly temperature (°C), Ia is the annual
thermal index, and a is a polynomial function of the index. The reason why Thornthwaite empirical formula is proposed in this methodology is due to its simplicity (it only requires to know average monthly temperatures) when compared to other empirical approaches that demand more data. Studies conducted in northeastern USA (Rosenberry et al., 2007) and in southern Portugal (Rodrigues, 2009) concluded that, when compared with the results obtained by the energy balance calculation, Thornthwaite formula provided valid evaporation estimates. However, when evaluating evaporation in other regions, it is recommended to check the adequacy of this method. Evaporation volume is obtained by multiplying the estimated evaporation during the reference period by the water surface area. In intermediate reservoirs, flooded area records for each month of the reference period should be used to estimate evaporation volumes. In case these are not available, the area corresponding the full storage level should be considered. However, this can lead to an overestimation of the real area. When estimating water surface areas for the canal network, the most accurate estimation is obtained by calculating the water surface profile for each canal reach. Nevertheless, this procedure is a demanding and time-consuming. Thus, more straightforward methods were analyzed in this study to estimate surface areas. A sensitivity analysis between three considered hypotheses a), b) and c) depicted in Fig. 5 was carried out in one reach of the conveyance system of the case study, in order to assess which one returns an area estimation closer to the one of the water surface profile. Hypothesis a) considers the water depth along the canal equal to the one at the downstream end; hypothesis b) considers the water depth along the canal equal to the one of the uniform equilibrium flow; and hypothesis c) considers the water
Description
Hypothesis
Surface area, As (m2)
Δ (%)
hw = hd hw = hu hupstream = hu hdownstream = hd Actual water level profile
a) b) c)
28 021 24 903 26 462
+ 4.9% −6.8% −0.9%
–
26 711
–
are two components also covered by the proposed water balance. The water supply in open canal systems is usually performed by WUA employees who are responsible for operating the flow control structures that deliver water to the users. In this way there is direct control of the number of users, reducing the chances of unauthorized uses. Either way, when the user is collecting water directly from the canal or the distribution is carried out by a pressurized system, unauthorized uses can still occur. Tampering or routing around the water meter are some examples of illegal uses that may happen. The WUA can perform periodic inspections in suspicious areas where illegal uses may be occurring, but estimating the unauthorized uses components is a difficult task. Users whose consumption is fairly different from the water demand of a certain crop should be studied in order to understand such deviation. To reduce the volumes associated with unauthorized uses, consistent monitoring of the system should be carried out. The other apparent loss component considered in the presented water balance is the metering errors. This component accounts for the deviations between the metered volumes and the real volumes delivered to the user. A variety of factors can be responsible for these deviations (e.g., type of meter, age, installation conditions, range of the metered flows) (Vermersch et al., 2016). When water consumption is metered in modules equipped with a stopwatch, the metering results from the integration of the modules discharge coefficient during the registered opening time. Sediments, lack of proper adjustment and erosion are some of the factors responsible for the change in the discharge coefficient of the modules (Jorabloo and Sarkardeh, 2010). Therefore, hydraulic performance of irrigation meters and modules should be assessed in order to evaluate the metering accuracy of these devices. As for real losses, similar to urban water supply systems, leakage in mains and storage tanks, as well as overflows, should also be considered. Depending on the leakage control policy of the WUA, bursts can be identified, allowing to estimate a volume of water lost in each event (i.e., during the event and repair) (Thornton et al., 2008). Due to the variety of conditions that one can encounter, seepage tests should be carried out. Between the various methods used to estimate canal seepage, ponding tests have been proved to be a method capable of producing results with a higher accuracy level (Alam and Bhutta, 2004). Lastly, a monitoring system should be installed in order to determine the canal discharges component in the water balance, and subsequently, data should be stored to be available for the water balance calculation. Measuring the canal discharges will not only allow to estimate the volumes discharged and increase the water balance reliability, but also improve the system management if updated and timely data are provided to the system manager.
Fig. 5. Water level hypothesis considered to estimate evaporation losses in a canal reach.
depth varying linearly between the previous two depths. Results show a negative variation of the water surface area of 6.8% in comparison with the actual water level profile, when assuming a constant water level equal to the water depth of the uniform equilibrium flow (hu), and a positive variation of 4.9%, when a constant level equal to the water depth downstream (hd) is used. In the proposed methodology, the water depth at downstream, hd, is the one given by the water depth control structure and the one at upstream, hu, is the water depth of the uniform equilibrium flow, also known as design water depth. This hypothesis is the one that has the least deviation from the estimation of the water surface profile area. The water surface profile was determined using the Direct Step Method for the design discharge of the canal reach. The comparison between the results of the water surface are estimations based on the three studied hypotheses is summarized in Table 1. As for the apparent losses, unauthorized uses and metering errors
3. Application 3.1. Case study description The proposed methodology is applied to a collective irrigation system in Portugal, a country where these infrastructures account for 35% of the total irrigated area (DGADR, 2014) and it is estimated that global water efficiency of these systems is below 65% (APA, 2012). This value that can, in part, be explained by their age and need of urgent 5
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rehabilitation interventions to reduce water loss (DGADR, 2014). The collective irrigation system – Aproveitamento Hidroagrícola do Vale do Sorraia (AHVS) – is located in Tejo river basin and lies alongside Sorraia river and two tributaries – Sôr and Raia rivers. The system conveyance is entirely in open canal. The distribution is carried out by a mixed system, composed of canals and pipes – assuring the connection of the conveyance system with the users. The total irrigated area is 16 351 ha. In this irrigation system, underflow gates (AMIL) are the canals water level control structures, which guarantee the required level for the intake structures (Neyrpic modules). The majority of users are farmers (responsible for 98% of the billed authorized consumption) with the remaining volume being consumed by two industries. The distribution method implemented by the WUA is a prior agreement method on which users must request water 24 h in advance, so the utility manager operates the system to supply the flow rate at the requested time. The primary water sources are Maranhão, Montargil and Magos reservoirs. The water collected at Maranhão reservoir is conveyed through Raia stream until Gameiro weir. This weir was built to enable two pumping stations to raise water to two distributors located at higher terrain levels. Downstream Gameiro weir is Furadouro weir which was built to feed the artificial conveyance canal of the system. At Montargil reservoir the water collected is conveyed in an artificial canal that meets the main conveyance canal in Santa Justa junction. Right before the Peso node, where the main conveyance canal splits in two, an intermediate reservoir was built. This reservoir stores surpluses volumes, reducing the discharged volume at downstream. Along the system, water is collected from the water line and enters the system through pumping stations. Magos reservoir is a catchment decoupled from the main system that together with a pumping station supplies water to a smaller canal network. A schematic representation of the system is presented in Fig. 6. The boundaries of the sub-system later considered for runoff estimation using water balance calculation are
water consumption is separated from other crops consumption. Fig. 7 shows the effect that precipitation changes have on the water demand by the users. In years with higher precipitation, billed metered consumption reaches lower values, whereas, when precipitation is scarce, water demand increases. This situation obliges WUA to manage water storage and system operation more efficiently in order to prevent users from not having supplied water in quantity and in the time they need. 3.2. Water balance calculation The reference period for the water balance calculation was established based on the availability of the service to the users during the year 2017. The agricultural season started in March 2017 and lasted until October 2017, with the system operating during this period. During this time, the total water collected from the system sources – reservoirs and pumping stations – calculated, being detailed according Table 2 Estimated system input volume components in 2017. System input components
Volumes (m3)
Abstracted water
174 362 955 10 699 315 Not applicable 167 878 3 352 4 669 247 (details in Table 3) Not applicable (closed reservoir)
Imported water Precipitation Runoff
from reservoirs from the river in canal in intermediate reservoirs to canal to intermediate reservoirs
Intermediate storage Total system input volume
0 (constant level) 189 902 746
to the source in Table 2. Water volumes abstracted from reservoirs were metered, unlike the abstracted volume from the river through pumping stations which result from estimations based on the nominal power and working time of each pump. In order to calculate the total input volume due to precipitation, data from the WUA’s weather stations was gathered and accumulated precipitation during the reference period was calculated for each weather station. Since there was no geographical information related to the canal reaches, the average value of the accumulated precipitation in the six stations was adopted for the whole canal network. For the weirs and the intermediate reservoirs, accumulated precipitations from the nearest weather station to each structure were adopted. Since part of the conveyance system is a stream, runoff volume estimations had to be conducted. The basin that drains to the system is the one associated to Raia stream, located between Maranhão reservoir and Gameiro weir. As a first approach, the billed volume at the beginning of the irrigation season, during a time without any reservoir input, was obtained. Having enough data to estimate the runoff volume by the three other methods, estimations were carried out, and obtained
Fig. 6. Collective irrigation system layout with subsystem boundaries.
also presented. Irrigation systems are highly dependent on precipitation, not only from a water storage point of view but also because it is a key factor influencing water consumption of the users. Billed meter consumption and precipitation records from 2013 to 2017 are depicted in Fig. 7. Since rice crop farmers are the largest water consumers in AHVS, with an average consumption in the last five years of 11 220 m3/ha, rice
Table 3 Hypothesis tested for estimating runoff volume in canal component during irrigation season.
Fig. 7. Annual billed volumes and average precipitation in the last five years. 6
Method
Runoff volume (m3)
Billed volume during the initial operation time Water balance Runoff/Precipitation relation in Maranhão water catchment Sequential water balance (hydrological) in Raia river basin until Furadouro section
1 049 670 4 669 247 5 700 000 48 000 000
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results are presented in Table 3. The estimated runoff volume obtained by calculating the sequential water balance returned a value (48 Mm3) with a higher order of magnitude than the remaining methods. This skewed estimation should be revised, and a better assessment of the soil parameter should be done. The estimations returned by the water balance (4.67 Mm3) and the runoff/precipitation relation (5.70 Mm3) seem coherent, converging to a value of the same order of magnitude. Both estimations are higher than the billed volume during the initial operation time (1.05 Mm3), a value obtained when supply to crops downstream of Furadouro section is ensured without any reservoir input. That estimation can be seen as rough estimation given by the WUA of the system input component to be estimated. The method adopted for the runoff estimation in this system was the water balance, given the fact that the required data were available and its calculation resulted from measured variables. The sub-system considered in the water balance for the runoff estimation is the one presented in Fig. 6. The subsystem input volumes were the abstracted volumes from Maranhão reservoir and the runoff volume. The revenue water and the water received by the canal constitute the authorized consumption, causing the discharge in the weir to be the only water loss considered. The supplied volumes by the WUA to the users (billed authorized consumption) were obtained from the billing system of the WUA since unbilled authorized consumption is not applicable in this system. About 95% of this volume was metered and the rest obtained with estimations based on the irrigated area and type of crop. Subcomponents related with water exportation, firefighting and WUA uses were not considered during the reference period, since the WUA does not have any record. The minimum operational volume was calculated for a conveyance canal reach and for a distribution canal reach that were considered as being representative of each system. The estimated volume for the
each structure. Results are presented in Table 5. As the WUA did not have information about any illegal consumption that may have occurred during the reference period, estimation of this component was done taking into account the lower probabilities of these phenomena to happen, when compared to urban water supply systems, due to the presence of WUA employees that guarantee a correct operation of the system. Employees are responsible to account for water requests, ensure good metering performance and operate flow control structures, leaving small room for unauthorized uses to happen. As for the metering errors, at this stage, no meters were tested. Nevertheless, the WUA started to collect essential data that will help to select the meters to be submitted to metering error auditing tests. This analysis was performed for meters installed in rice crops since it is the crop with the highest water consumption (Fig. 7). The flow meter distribution according to their age for two metering diameter classes is
Fig. 8. Age distribution of meters installed for rice crops.
presented in Fig. 8. Age distribution allows identifying a set of ageing meters, over than 12 years, with high values of metered volumes. This can cause changes in the performance characteristics of the meter, highlighting to the need of assessing the accuracy of meters operating under these conditions and considering their substitution by new equipment. Considering that rice crops consumption can be characterized by a steady flow during the peak months of the irrigation season, average flow rates in both diameter classes analyzed were obtained for each month. Results are presented in Fig. 9, as well as the metrological characteristics (Q1 and Q2) of two models of water meters currently in use: M1 and M2. As it is not possible to distinguish between DN80 and DN100 meters, and since DN100 meters is the prevailing diameter, the minimum flow (Q1) and the transitional flow (Q2) presented corre-
Table 4 Estimated minimum operational volume in system canals.
Conveyance system Distribution network Total
Extension (km)
Minimum operational volume (m3)
120.5 109.5 230.0
647 476 29 899 677 376
entire system is presented in Table 4. The next step of the approach is the estimation of the water losses components. As the collective irrigation system is mainly in open canal, evaporation losses were estimated. Similar to the minimum operation volume calculation, the evaporation estimation was carried out for the same two canals and then extrapolated for the whole network. Evaporation in the river part of the conveyance system was calculated considering an average surface width of 25 m and a total length of 32.6 km. Evaporation value considered was the average value recorded during the irrigation season between the WUA’s weather stations. The estimation for the intermediate reservoir and the two weirs was done with the evaporation value registered in the nearest weather station of
Fig. 9. Hourly mean flow between May and September in rice crops and comparison with minimum flow (Q1) and transitional flow (Q2) given according to metrological characteristics of two models of water meters (M1 and M2): (a) DN80-100 meters; (b) DN150 meters.
Table 5 Estimated water losses due to evaporation in canals and intermediate reservoirs in 2017.
Conveyance system (river) Conveyance system (canal) Distribution network (canal) Intermediate reservoir Weirs Total
Extension (km)
Evaporated volume (m3)
32.6 120.5 109.5 – – 262.6
647 925 615 460 91 833 16 127 89 629 1 460 974
spond to the ones from DN100 meters. Results show a distinct behavior between the two diameter classes during the peak consumption months – June, July and August. It is noticeable a growing trend of the average flow in the lower diameter classes, in contrast to the higher diameter class that shows a more stable behavior with a small decrease in the average volume towards the end of the irrigation season. According to the WUA, this can be explained by 7
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an intermittent operation of the meters at the beginning of the rice irrigation process. Taking into account meter technical characteristics, these average flow values fit between the minimum flow and the transitional in M2 model, a range where metering errors by default tend to be higher. Further analysis should be carried out in order to assess the effect that these inaccuracies have on the apparent losses component. Network pipes leakage was estimated considering the reference value of real losses for urban distribution systems with poor service quality, 5 m3/(km.day) (ERSAR and LNEC, 2013). The reason why a pessimistic value was considered is due to the age of the infrastructure, concrete pipes have ca. 60 years, which is beyond their expectable technical operating life, and several pipe bursts were reported by the WUA (Covas et al., 2018). Given the age of the canal network, some rehabilitation works have been carried out by the WUA so that continuous system operation is guaranteed. Nowadays, the canals’ condition suggests that the real losses may be over the values found in the bibliography. In order to estimate a value for the leaks in these assets, an inflow-outflow study was carried out in a representative reach of canal. The canal studied has an approximate length of 20 km, and at the time all the canal gates were closed. However, AMIL gates are not entirely watertight allowing the flow of a small discharge. At the canal head, the registered inflow was 150 L/s, and since there were no flow meters at downstream the canal, a value of 20 L/s was adopted as the outflow based on in-situ observations. The estimated flow associated with water leakage through the canal is 130 L/s, which corresponds to 53 L/(m2.day) water loss rate according to the canal geometrical characteristics. Later, the WUA carried out ponding tests in two canal reaches from the distribution network. Preliminary results alert to a key factor that affects canal water loss: soil. One of the canal reaches shows clear signs of deterioration, reason why it was expected to have higher water loss rates than the other canal reach which is in better conditions. However, the more degraded canal is operating in clayey soils which may explain a lower water loss rate than the one expected. Further works are being planned in order to increase the canal leakage estimation. The application of the proposed methodology for calculating the water balance in CIS has shown to be a challenging task in which several methodologies are still being tested for estimating the new components. The complete water balance for the 2017 irrigation season
in AHVS is presented in Fig. 10. The non-revenue water components are presented in detail in Fig. 11. Real losses volume is responsible for the most significant share (70%). Results indicate that the WUA actions should be focused on reducing the weight that real losses and apparent losses have on the
Fig. 11. Non-revenue water components in the system in 2017: (a) non-revenue components; (b) real losses components.
system water balance (ca. 33.7% of total input volume). When assessing real losses in a mixed system, such as AHVS, canalrelated components such as discharges and leakage should be considered. Canal discharges are estimated in 48.9% of the non-revenue water, which highlights the need to improve the estimation of this component and to reduce system operational losses. Leakage in canals cannot be neglected as this represents around 20% of the non-revenue water in the analyzed irrigation system. 4. Conclusions A novel comprehensive methodology has been proposed and illustrated for the water balance calculation in irrigation systems. This methodology can become an important performance evaluation tool for both canal and pressurized systems, helping WUA to achieve more efficient water management practices. The water balance calculation allows to have a diagnosis of the system, in terms of system input volume, consumption (billed and unbilled) and water losses, helping WUAs to take improvement measures. The water balance is also an essential tool to calculate a set of water loss indicators which will allow WUAs to evaluate its performance over time and benchmarking different collective irrigation systems. The systematic water balance calculation for every irrigation season allows to evaluate the impact of improvement measures that were taken. Inspired on the urban water balance principles, the proposed water balance includes new components on the system input, authorized consumption and water losses. The methodology was tested for the first time in a WUA, highlighting the importance that real water losses have on the collective irrigation system. Hydrological modelling of the basin that contributes with runoff should be performed in order to validate the results obtained. Regarding metering errors, in pressurized systems, the water meters’ error should be assessed and, in open canal systems, the hydraulic performance of the modules responsible for the derivation of flow to the user should be evaluated, as part of the forthcoming works. The current work pointed out that some installed meters’ flow range does not match the range of water demand associated with rice crop demand; this is caused by an inappropriate meter size selection. Results highlight to the need to rehabilitate the conveyance and distribution infrastructures as well as
Fig. 10. Results of the water balance calculation for the system in 2017.
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reducing canal discharges. In the future, more CIS should be tested in order to consolidate the methodology and to improve canal leakage estimation. The water-energy balance scheme, following the principles proposed by Mamade et al. (2017) for urban water supply systems, is also being developed for irrigation systems.
Burt, C.M., 1995. The surface irrigation manual - A comprehensive guide to design and operation of surface irrigation systems. Exeter: Waterman Industries. Clemmens, A., Molden, D., 2007. Water uses and productivity of irrigation systems. Irrig. Sci. 25, 247–261. Covas, D., Cabral, M., Pinheiro, A., Marchionni, V., Antunes, S., Lopes, N., Mamouros, L., Brôco, N., 2018. Construction Costs of Infrastructures Associated to the Urban Wate Cycle. ERSAR. DGADR, 2014. Strategy for Public Irrigation 2014-2020 (in Portuguese). DGADR, Lisbon. ERSAR, LNEC, 2013. Guide to the Quality of Service Assessment for Drinking Water Supply, Urban Astewater Management and Municipal Waste Management Services 2nd Generation of the Assessment System (in Portuguese). ERSAR, Lisbon. FAO, 1975. Small Hydraulic Structures. FAO, Rome. FAO, 2007. Modernizing irrigation management - the MASSCOTE approach. Rome: FAO. FAO, 2017. Water Accounting and Auditing - a Sourcebook. FAO, Rome. FAO, 2019. AQUASTAT. Food and Agriculture Organization of the United Nations [Online]. [Accessed 2018/10/16 January 2019]. Jorabloo, M., Sarkardeh, H., 2010. Hydraulic evaluation of neyrpic-modules at water distribution network of Garmsar Plain. World Appl. Sci. J. 10 (no. 11), 1363–1367. Malano, H., Burton, M., 2001. Guidelines for Benchmarking Performance in the Irrigation and Drainage Sector. FAO, Rome. Mamade, A., Loureiro, D., Alegre, H., Covas, D., 2017. A comprehensive and well tested energy balance for water supply systems. Urban Water J. Molden, D., 2007. Water for Food, Water for Life: A Comprehensive Assessment of Water Management in Agriculture. Earthscan and IWMI, London. Molden, D., Gates, T., 1990. Performance measures for evaluation of irrigation-waterdelivery systems. J. Irrig. Drain. Eng. 116 (6), 804–823. Molden, D., Sakthivadivel, R., Perry, C., Fraiture, C., 1998. Indicators for Comparing Performance of Irrigated Agricultural Systems. IWMI, Colombo. Montañés, J.L., 2006. Hydraulic Canals - Design, Construction, Regulation And Maintenace. Taylor & Francis, Abingdon. Quintela, A.C., 2010. Hydraulics (in Portuguese), 12th edition. Calouste Gulbenkian Foundation, Lisbon. Rijo, M., 2010. Conveyance Canals - Design, Operation, Control and Modernization (in Portuguese). Edições Sílabo, Lda, Lisbon. Rodrigues, C., 2009. PhD thesis in engineering of Water resources. Calculation of Evaporation in High Regulation Reservoirs in Southern of Portugal (in Portuguese). University of Évora. Rosenberry, D., Winter, T., Buso, D., Likens, G., 2007. Comparison of 15 evaporation methods applied to a small mountain lake in the northeastern USA. J. Hydrol. (Amst). Thornton, J., Sturm, R., Kunkel, G., 2008. Water Loss Control, 2nd edition. McGraw-Hill, USA. US Department of the Interior, 1991. Canal Systems Automation Manual, Denver. Vermersch, M., Carteado, F., Rizzo, A., Johnson, E., Arregui, F., Lambert, A., 2016. Guidance Notes on Apparent Losses and Water Loss Reduction Planning.
Funding This research was funded by PDR2020 grant number PDR2020-101031878. Conflicts of interest The authors declare no conflict of interest. Acknowledgements The authors gratefully acknowledge all project AGIR partners that directly or indirectly contributed to the presented paper. A special thanks to Professor Madalena Moreira and Engineer Carina Arranja for the valuable contributions. References Alam, M., Bhutta, M., 2004. Comparative evaluation of canal seepage investigation techniques. Agric. Water Manag. Alegre, H., Baptista, J.M., Cabrera Jr., E., Cubillo, F., Duarte, P., Hirner, W., Merkel, W., Parena, R., 2006. Performance Indicators for Water Supply Services, 2nd edition. IWA Publishing, London. APA, 2012. National Program for the Efficient Use of Water (in Portuguese). Arregui, F., Cabrera Jr, E., Cobacho, R., García-Serra, J., 2005. Key factors affecting water meter accuracy. IWA Water Loss Conference. Arregui, F., Cabrera Jr, E., Cobacho, R., 2006. Integrated Water Meter Management. IWA Publishing, London. Bos, M.G., 1997. Performance indicators for irrigation and drainage. Irrig. Drain. Syst. Bos, M.G., Nugteren, J., 1990. On Irrigation Efficiencies, 4th edition. International Institute for Land Reclamantion and Improvement, Wageningen.
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