- Email: [email protected]
IoT Enabled Analysis of Irrigation Rosters in the Indus Basin Irrigation System
Available online at www.sciencedirect.com
ScienceDirect Procedia Engineering 154 (2016) 229 – 235
12th International Conference on Hydroinformatics, HIC 2016
IoT Enabled Analysis of Irrigation Rosters in the Indus Basin Irrigation System Abubakr Muhammada,b*,Bilal Haiderb, Zahoor Ahmadb a b
Dept. of Electrical Engineering, Lahore Universiry of Management Sciences (LUMS), Lahore 54792, Pakistan Center for Water Informatics & Technology, Lahore Universiry of Management Sciences (LUMS), Lahore 54792, Pakistan
Abstract
The Indus Basin Irrigation System (IBIS) is the world’s largest contiguous irrigation system, irrigating over 2.5 million acres and running over 90,000 km of watercourses. It ensures equitable water distribution to farmers through irrigation rosters or warabandi (literally meaning “taking turns”) which is a fixed-turn rotation system following a time roster issued by the government agencies. To study this irrigation system, we have developed an Internet-ofThings (IoT) inspired custom-built water metering network, capable of near real-time reporting of flow discharges through GPRS and backend server services. In 2013-14, a network of flow meters was deployed on 17 distributary canals in the Hakra Branch Canal command in IBIS covering more than two cropping seasons. By comparing the captured water distribution data (sampled every 10 minutes) with Punjab Irrigation Department (PID) issued warabandi rosters, an analysis of the warabandi rosters is presented in this paper. © 2016 byby Elsevier Ltd.Ltd. This is an open access article under the CC BY-NC-ND license © 2016The TheAuthors. Authors.Published Published Elsevier (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of HIC 2016. Peer-review under responsibility of the organizing committee of HIC 2016
Keywords: Irrigation rosters, Indus basin, hydrometry, Internet of Things, smart water management
1. Introduction Irrigation practices around the world are changing to enhance food security while saving water. Both developed and
* Corresponding author. Tel.: +92-42-3560-8132. E-mail address: [email protected]
1877-7058 © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of HIC 2016
doi:10.1016/j.proeng.2016.07.457
230
Abubakr Muhammad et al. / Procedia Engineering 154 (2016) 229 – 235
developing countries are shifting from purely supply based to demand based approach. Demand based practices are not possible in in a country like Pakistan where water resources are monitored and controlled manually and water resources are unevenly distributed in time and space [1]. Supply based water distribution to farmers is carried out through warabandi (literally meaning “taking turns”) which is a fixed-turn rotation system [2], following a time roster issued by the government agencies. The fixed time allocation is based on the size of landholding of individual water users presupposes an overall shortage of water supply [1]. There is systematic equity i.e., the system is designed for equal distribution but operational equality remains the biggest challenge for irrigation department. In [3], the authors describe that the objectives of warabandi is to provide water to farmers such that, on average, each farmer irrigates one third of the cultivable command area (CCA) four times per season. Information, computation, communication and control enabled technologies such as wireless sensor networks; cyber physical systems and Internet of Things (IoT) are replacing the manual practices in numerous industrial, environmental and agricultural applications [4,5]. Water resources in developing countries are operated manually and there is a huge potential for information automation based technologies to overcome problems associated with water monitoring and delivery. For demand based water deliveries, IoT enabled technologies are required to monitor discharges in the distributaries and control water deliveries. As a first step, we have started with the monitoring part of automating these large scale irrigation networks. Available water in rivers in the Indus Basin is distributed at three levels. Water from rivers is distributed into main canals, link canals and their branches. Distributary canals emerging from these main canals transport water to canal command areas (CCA). Finally, outlets from distributary canals bring water to the farm gates. Distribution equity should be maintained at all levels. Effective management of scarce water resources requires accurate information on water distribution at all levels [6]. In [7], the authors monitor water level of small canal outlets using mesh wireless sensor network. The frequency of anomalous events such as the absence of water supply when a particular distributary is scheduled to receive water; or the presence of significant flow in a distributary when it is not scheduled to receive water; or sharp rises and falls in water levels can be reported using smart water metering. As discussed in [8], wireless real-time monitoring of water quantity and quality can capture temporal changes and provide broader spatial coverage. Thus, questions about transparency, efficiency and systematic ways to address them can be reported using smart metering approach. A province-wide real-time flow metering (RTFM) system is currently in planning stages by Punjab Irrigation Department for 3000+ critical sites [9, 10]. In that context, our current work provides guidelines and constructive answer to questions related to scalability, appropriate software backend services and fault detection. 2. Sensor Network Deployment A network of GPRS based smart water meters was deployed on 17 distributary canals in the Hakra Branch Canal command in Southern Punjab province of Pakistan as shown in Fig. 1. Water levels in these distributaries were sampled using non-contact ultrasonic sensors with a frequency of 10 minutes for more than two cropping seasons in 2013-14. Technical design of the electronics and backend software of this project have been reported in [11,12].
Abubakr Muhammad et al. / Procedia Engineering 154 (2016) 229 – 235
Fig. 1. Hakra branch canal, its distributaries and canal commands in Bahawalnagar district, Pakistan.
Refer to Fig. 2 for the system diagram, where ultrasonic range finding sensor is mounted in a stilling well. The instrument sends time stamped range reading d to the server. Here ݁ is the instrument elevation, ݁ is the canal bed elevation and s is the level of silt accumulated on the bed. The server computes depth of water h, which is then converted to discharge Q(h) in cusecs according to a hydraulic rating curve. The data can be accessed by a client on the network.
Fig. 2. System diagram showing sensor mounted in stilling well sends time stamped range reading d to the server [11] and [12].
3. Analysis of Irrigation Rosters Refer to Tables 1 and 2 for the irrigation rosters issued by the concerned government department for Kharif cropping season of 2014. Table 1 shows sub groups and rotation time at distributary heads whereas Table 2 shows warabandi schedule for first 9 weeks of the cropping season Kharif 2014. For the cropping season Rabi (15 October till 15 April), we have similar warabandi schedule each year. The groups are further divided into sub groups for finer scale distribution. Irrigation rosters for distributaries in Hakra Branch are overlaid on measurements as color codes in Fig. 3, Fig. 4 and Fig. 5 for group C, A and B respectively. The designed discharge for each distributary is represented by a red horizontal line. A grid on horizontal axis represents one week time span. Distributaries in Hakra Branch are
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divided into three groups A, B and C which are further divided into sub groups. Distributaries in a group for a particular week are either in the first, second or third priority according to the annual irrigation roster issued by the irrigation department. If a group is in the first priority for a week, all distributaries in this group get water. If still more water is available, it is provided to the distributaries with second priority for that week. Distributaries with third priority only get water if still more water available. Flows in distributaries in a group for a particular week is represented by green, blue and red colors in case of first, second and third priority respectively. Through such an IoT enabled deployment anomalous events such as water misappropriation and unavailability of water in a distributary when it is scheduled to receive water and vice versa can be reported instantly through SMS or e-mail alerts to the concerned officials of the irrigation department. Table 1. Sub groups (left two columns) and rotation time at distributary heads (right three coulumns). Sub group
Distributaries in the sub group
-
Heads name
Rotation time
Distributaries
A1
HR, HL
-
GA
05:00 AM
BS, 1R, 2R, 3R, 4R, 1L
A2
4R, 1L
-
6R
10:00 AM
5R, 6R, 2L
B1
BS, 1R, 2R, 3R
-
7R
12:00 PM
7R, 3L
B2
5R, 2L, 7R, 3L, 4L, 8R, FC
-
8R
04:00 PM
8R, 4L
C1
6R
-
9R
04:00 PM
9R
C2
9R
-
TH
07:00 PM
HR, HL, FC
Table 2. An interpretation of warabandi schedule issued by Punjab Irrigation Department for first nine weeks of Kharif 2014. Week
Period
Group
Sub-group
From
To
1
2
3
1
2
Week1
4/18/2014
4/25/2014
B
C
A
B1
B2
C1
C2
A1
A2
L-R
Week2
4/26/2014
5/3/2014
A
B
C
A2
A1
B2
B1
C2
C1
R-L
Week3
5/4/2014
5/11/2014
C
A
B
C1
C2
A1
A2
B1
B2
L-R
Week4
5/12/2014
5/19/2014
B
C
A
B2
B1
C2
C1
A2
A1
R-L
Week5
5/20/2014
5/27/2014
A
B
C
A1
A2
B1
B2
C1
C2
L-R
Week6
5/28/2014
6/4/2014
C
A
B
C2
C1
A2
A1
B2
B1
R-L
Week7
6/5/2014
6/12/2014
B
C
A
B1
B2
C1
C2
A1
A2
L-R
Week8
6/13/2014
6/20/2014
A
B
C
A2
A1
B2
B1
C2
C1
R-L
Week9
6/21/2014
6/28/2014
C
A
B
C
C
A
A
B
B
L-R
Fig. 3. Warabandi for group C for the year 2014-2015.
3
Sequence
Abubakr Muhammad et al. / Procedia Engineering 154 (2016) 229 – 235
Fig. 4. Warabandi for group A for the year 2014-2015.
4. Water Delivery Discharges computed for different distributaries over a cropping season are then converted into volumes delivered per acre. Each distributary has its own cultivable command areas. Fig. 6 shows water delivery per acre to cultivable command areas of all 17 distributaries in Hakra Branch for the six month cropping season of Kharif 2014 arranged in a sequence of decreasing order of distributary’s design discharge from left to right. The lowest volume delivered per acre is below 40,000 cft (cubic feet) and the highest volume delivered is more than 100,000 cft which indicates unequal distribution of water amongst the stakeholders. Practical equity is better than what the graph are depicting because we are comparing small distributaries like BS, 4L, 3L and HL with design discharges of 7 cfts (Cubic feet per second), 9 cfts, 10 cfts and 23 cfts with large distributaries of HR, 6R, 3R, 7R and 4R with design discharges of 573 cfts, 546 cfts, 353 cfts, 273 cfts and 266 cfts respectively. Distributaries with low design discharge are more vulnerable to silt deposition due to low velocity of water at their heads. The distributary bed level is changing and it is very difficult to tract the bed at regular intervals on a remote site. For larger distributaries with designed discharge greater than 30 cfts, the water operational delivery is around 57,000-74,000 cft/acre which indicates a reasonable distribution equity at the inter-distributary level.
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Fig. 5. Warabandi for group B for the year 2014-2015.
Abubakr Muhammad et al. / Procedia Engineering 154 (2016) 229 – 235
Fig. 6. Water delivered per acre to 17 distributary canals in Hakra Branch (sequenced in decreasing order of design discharge from left to right) for the cropping season Kharif 2014 (15th April 2014 till 15th October 2014).
5. Conclusion Large scale deployment of smart water meters with high sampling and transmission frequencies and backend services would ensure equal distribution of water resources amongst stakeholders and improve management practices. There is small operational inequity in inter-distributary deliveries considering only larger distributaries. The deployment also provided the potential of large scale deployment of smart water metering for surface water management in the Indus basin. Acknowledgements The authors would like to acknowledge support provided by the IWMI (International Water Management Institute) to undertake the research described in this paper. References [1] D. Bandaragoda and S. ur Rehman, Warabandi in Pakistan's canal irrigation systems: Widening gap between theory and practice. No. 7, IWMI, 1995. [2] Anwar, A. A., & Ul Haq, Z. (2013). An old–new measure of canal water inequity. Water international, 38(5), 536-551. [3] Seckler, D., Sampath, R. K., & Raheja, S. K. (1988). AN INDEX FOR MEASURING THE PERFORMANCE OF IRRIGATION MANAGEMENT SYSTEMS WITH AN APPLICATION. [4] J. Gutierrez, J. F. Villa-Medina, A. Nieto-Garibay, and M. A. Porta-Gandara, Automated irrigation system using a wireless sensor network and gprs module," Instrumentation and Measurement, IEEE Transactions on, vol. 63, no. 1, pp. 166{176, 2014}. [5] Y. Kim, R. G. Evans, and W. M. Iversen, Remote sensing and control of an irrigation system using a distributed wireless sensor network," Instrumentation and Measurement, IEEE Transactions on, vol. 57, no. 7, pp. 1379{1387, 2008}. [6] Stein, A., & Bastiaanssen, W. G. (2004). Estimation of disaggregated canal water deliveries in Pakistan using geomatics. International journal of applied earth observation and geoinformation, 6(1), 63-75. [7] N. M. Phuong, M. Schappacher, A. Sikora, Z. Ahmad, and A. Muhammad, Real-time water level monitoring using low-power wireless sensor network," in Embedded World Conference, 2015. [8] T. Younos and C. J. Heyer, Advances in water sensor technologies and real-time water monitoring," in Advances in Watershed Science and Assessment, pp. 171{203, Springer, 2015. [9] Habibullah Bodhla. “Technology being used for the Monitoring of Canal Operation”, Symposium on Telemetry Systems for Water, LUMS, Lahore, 2014. [10] World Bank, Punjab Barrages Improvement Phase II Project (PBIP-II) Project Report. 2015. [11] Ahmad, Z., & Muhammad, A. (2014, October). Low power hydrometry for open channel flows. In Industrial Electronics Society, IECON 2014-40th Annual Conference of the IEEE (pp. 5314-5320). IEEE. [12] Ahmad, Z., Asad, E. U., Muhammad, A., Ahmad, W., & Anwar, A. (2013). Development of a low-power smart water meter for discharges in indus basin irrigation networks. In Wireless Sensor Networks for Developing Countries(pp. 1-13). Springer Berlin Heidelberg.
235
ScienceDirect Procedia Engineering 154 (2016) 229 – 235
12th International Conference on Hydroinformatics, HIC 2016
IoT Enabled Analysis of Irrigation Rosters in the Indus Basin Irrigation System Abubakr Muhammada,b*,Bilal Haiderb, Zahoor Ahmadb a b
Dept. of Electrical Engineering, Lahore Universiry of Management Sciences (LUMS), Lahore 54792, Pakistan Center for Water Informatics & Technology, Lahore Universiry of Management Sciences (LUMS), Lahore 54792, Pakistan
Abstract
The Indus Basin Irrigation System (IBIS) is the world’s largest contiguous irrigation system, irrigating over 2.5 million acres and running over 90,000 km of watercourses. It ensures equitable water distribution to farmers through irrigation rosters or warabandi (literally meaning “taking turns”) which is a fixed-turn rotation system following a time roster issued by the government agencies. To study this irrigation system, we have developed an Internet-ofThings (IoT) inspired custom-built water metering network, capable of near real-time reporting of flow discharges through GPRS and backend server services. In 2013-14, a network of flow meters was deployed on 17 distributary canals in the Hakra Branch Canal command in IBIS covering more than two cropping seasons. By comparing the captured water distribution data (sampled every 10 minutes) with Punjab Irrigation Department (PID) issued warabandi rosters, an analysis of the warabandi rosters is presented in this paper. © 2016 byby Elsevier Ltd.Ltd. This is an open access article under the CC BY-NC-ND license © 2016The TheAuthors. Authors.Published Published Elsevier (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of HIC 2016. Peer-review under responsibility of the organizing committee of HIC 2016
Keywords: Irrigation rosters, Indus basin, hydrometry, Internet of Things, smart water management
1. Introduction Irrigation practices around the world are changing to enhance food security while saving water. Both developed and
* Corresponding author. Tel.: +92-42-3560-8132. E-mail address: [email protected]
1877-7058 © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of HIC 2016
doi:10.1016/j.proeng.2016.07.457
230
Abubakr Muhammad et al. / Procedia Engineering 154 (2016) 229 – 235
developing countries are shifting from purely supply based to demand based approach. Demand based practices are not possible in in a country like Pakistan where water resources are monitored and controlled manually and water resources are unevenly distributed in time and space [1]. Supply based water distribution to farmers is carried out through warabandi (literally meaning “taking turns”) which is a fixed-turn rotation system [2], following a time roster issued by the government agencies. The fixed time allocation is based on the size of landholding of individual water users presupposes an overall shortage of water supply [1]. There is systematic equity i.e., the system is designed for equal distribution but operational equality remains the biggest challenge for irrigation department. In [3], the authors describe that the objectives of warabandi is to provide water to farmers such that, on average, each farmer irrigates one third of the cultivable command area (CCA) four times per season. Information, computation, communication and control enabled technologies such as wireless sensor networks; cyber physical systems and Internet of Things (IoT) are replacing the manual practices in numerous industrial, environmental and agricultural applications [4,5]. Water resources in developing countries are operated manually and there is a huge potential for information automation based technologies to overcome problems associated with water monitoring and delivery. For demand based water deliveries, IoT enabled technologies are required to monitor discharges in the distributaries and control water deliveries. As a first step, we have started with the monitoring part of automating these large scale irrigation networks. Available water in rivers in the Indus Basin is distributed at three levels. Water from rivers is distributed into main canals, link canals and their branches. Distributary canals emerging from these main canals transport water to canal command areas (CCA). Finally, outlets from distributary canals bring water to the farm gates. Distribution equity should be maintained at all levels. Effective management of scarce water resources requires accurate information on water distribution at all levels [6]. In [7], the authors monitor water level of small canal outlets using mesh wireless sensor network. The frequency of anomalous events such as the absence of water supply when a particular distributary is scheduled to receive water; or the presence of significant flow in a distributary when it is not scheduled to receive water; or sharp rises and falls in water levels can be reported using smart water metering. As discussed in [8], wireless real-time monitoring of water quantity and quality can capture temporal changes and provide broader spatial coverage. Thus, questions about transparency, efficiency and systematic ways to address them can be reported using smart metering approach. A province-wide real-time flow metering (RTFM) system is currently in planning stages by Punjab Irrigation Department for 3000+ critical sites [9, 10]. In that context, our current work provides guidelines and constructive answer to questions related to scalability, appropriate software backend services and fault detection. 2. Sensor Network Deployment A network of GPRS based smart water meters was deployed on 17 distributary canals in the Hakra Branch Canal command in Southern Punjab province of Pakistan as shown in Fig. 1. Water levels in these distributaries were sampled using non-contact ultrasonic sensors with a frequency of 10 minutes for more than two cropping seasons in 2013-14. Technical design of the electronics and backend software of this project have been reported in [11,12].
Abubakr Muhammad et al. / Procedia Engineering 154 (2016) 229 – 235
Fig. 1. Hakra branch canal, its distributaries and canal commands in Bahawalnagar district, Pakistan.
Refer to Fig. 2 for the system diagram, where ultrasonic range finding sensor is mounted in a stilling well. The instrument sends time stamped range reading d to the server. Here ݁ is the instrument elevation, ݁ is the canal bed elevation and s is the level of silt accumulated on the bed. The server computes depth of water h, which is then converted to discharge Q(h) in cusecs according to a hydraulic rating curve. The data can be accessed by a client on the network.
Fig. 2. System diagram showing sensor mounted in stilling well sends time stamped range reading d to the server [11] and [12].
3. Analysis of Irrigation Rosters Refer to Tables 1 and 2 for the irrigation rosters issued by the concerned government department for Kharif cropping season of 2014. Table 1 shows sub groups and rotation time at distributary heads whereas Table 2 shows warabandi schedule for first 9 weeks of the cropping season Kharif 2014. For the cropping season Rabi (15 October till 15 April), we have similar warabandi schedule each year. The groups are further divided into sub groups for finer scale distribution. Irrigation rosters for distributaries in Hakra Branch are overlaid on measurements as color codes in Fig. 3, Fig. 4 and Fig. 5 for group C, A and B respectively. The designed discharge for each distributary is represented by a red horizontal line. A grid on horizontal axis represents one week time span. Distributaries in Hakra Branch are
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Abubakr Muhammad et al. / Procedia Engineering 154 (2016) 229 – 235
divided into three groups A, B and C which are further divided into sub groups. Distributaries in a group for a particular week are either in the first, second or third priority according to the annual irrigation roster issued by the irrigation department. If a group is in the first priority for a week, all distributaries in this group get water. If still more water is available, it is provided to the distributaries with second priority for that week. Distributaries with third priority only get water if still more water available. Flows in distributaries in a group for a particular week is represented by green, blue and red colors in case of first, second and third priority respectively. Through such an IoT enabled deployment anomalous events such as water misappropriation and unavailability of water in a distributary when it is scheduled to receive water and vice versa can be reported instantly through SMS or e-mail alerts to the concerned officials of the irrigation department. Table 1. Sub groups (left two columns) and rotation time at distributary heads (right three coulumns). Sub group
Distributaries in the sub group
-
Heads name
Rotation time
Distributaries
A1
HR, HL
-
GA
05:00 AM
BS, 1R, 2R, 3R, 4R, 1L
A2
4R, 1L
-
6R
10:00 AM
5R, 6R, 2L
B1
BS, 1R, 2R, 3R
-
7R
12:00 PM
7R, 3L
B2
5R, 2L, 7R, 3L, 4L, 8R, FC
-
8R
04:00 PM
8R, 4L
C1
6R
-
9R
04:00 PM
9R
C2
9R
-
TH
07:00 PM
HR, HL, FC
Table 2. An interpretation of warabandi schedule issued by Punjab Irrigation Department for first nine weeks of Kharif 2014. Week
Period
Group
Sub-group
From
To
1
2
3
1
2
Week1
4/18/2014
4/25/2014
B
C
A
B1
B2
C1
C2
A1
A2
L-R
Week2
4/26/2014
5/3/2014
A
B
C
A2
A1
B2
B1
C2
C1
R-L
Week3
5/4/2014
5/11/2014
C
A
B
C1
C2
A1
A2
B1
B2
L-R
Week4
5/12/2014
5/19/2014
B
C
A
B2
B1
C2
C1
A2
A1
R-L
Week5
5/20/2014
5/27/2014
A
B
C
A1
A2
B1
B2
C1
C2
L-R
Week6
5/28/2014
6/4/2014
C
A
B
C2
C1
A2
A1
B2
B1
R-L
Week7
6/5/2014
6/12/2014
B
C
A
B1
B2
C1
C2
A1
A2
L-R
Week8
6/13/2014
6/20/2014
A
B
C
A2
A1
B2
B1
C2
C1
R-L
Week9
6/21/2014
6/28/2014
C
A
B
C
C
A
A
B
B
L-R
Fig. 3. Warabandi for group C for the year 2014-2015.
3
Sequence
Abubakr Muhammad et al. / Procedia Engineering 154 (2016) 229 – 235
Fig. 4. Warabandi for group A for the year 2014-2015.
4. Water Delivery Discharges computed for different distributaries over a cropping season are then converted into volumes delivered per acre. Each distributary has its own cultivable command areas. Fig. 6 shows water delivery per acre to cultivable command areas of all 17 distributaries in Hakra Branch for the six month cropping season of Kharif 2014 arranged in a sequence of decreasing order of distributary’s design discharge from left to right. The lowest volume delivered per acre is below 40,000 cft (cubic feet) and the highest volume delivered is more than 100,000 cft which indicates unequal distribution of water amongst the stakeholders. Practical equity is better than what the graph are depicting because we are comparing small distributaries like BS, 4L, 3L and HL with design discharges of 7 cfts (Cubic feet per second), 9 cfts, 10 cfts and 23 cfts with large distributaries of HR, 6R, 3R, 7R and 4R with design discharges of 573 cfts, 546 cfts, 353 cfts, 273 cfts and 266 cfts respectively. Distributaries with low design discharge are more vulnerable to silt deposition due to low velocity of water at their heads. The distributary bed level is changing and it is very difficult to tract the bed at regular intervals on a remote site. For larger distributaries with designed discharge greater than 30 cfts, the water operational delivery is around 57,000-74,000 cft/acre which indicates a reasonable distribution equity at the inter-distributary level.
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Fig. 5. Warabandi for group B for the year 2014-2015.
Abubakr Muhammad et al. / Procedia Engineering 154 (2016) 229 – 235
Fig. 6. Water delivered per acre to 17 distributary canals in Hakra Branch (sequenced in decreasing order of design discharge from left to right) for the cropping season Kharif 2014 (15th April 2014 till 15th October 2014).
5. Conclusion Large scale deployment of smart water meters with high sampling and transmission frequencies and backend services would ensure equal distribution of water resources amongst stakeholders and improve management practices. There is small operational inequity in inter-distributary deliveries considering only larger distributaries. The deployment also provided the potential of large scale deployment of smart water metering for surface water management in the Indus basin. Acknowledgements The authors would like to acknowledge support provided by the IWMI (International Water Management Institute) to undertake the research described in this paper. References [1] D. Bandaragoda and S. ur Rehman, Warabandi in Pakistan's canal irrigation systems: Widening gap between theory and practice. No. 7, IWMI, 1995. [2] Anwar, A. A., & Ul Haq, Z. (2013). An old–new measure of canal water inequity. Water international, 38(5), 536-551. [3] Seckler, D., Sampath, R. K., & Raheja, S. K. (1988). AN INDEX FOR MEASURING THE PERFORMANCE OF IRRIGATION MANAGEMENT SYSTEMS WITH AN APPLICATION. [4] J. Gutierrez, J. F. Villa-Medina, A. Nieto-Garibay, and M. A. Porta-Gandara, Automated irrigation system using a wireless sensor network and gprs module," Instrumentation and Measurement, IEEE Transactions on, vol. 63, no. 1, pp. 166{176, 2014}. [5] Y. Kim, R. G. Evans, and W. M. Iversen, Remote sensing and control of an irrigation system using a distributed wireless sensor network," Instrumentation and Measurement, IEEE Transactions on, vol. 57, no. 7, pp. 1379{1387, 2008}. [6] Stein, A., & Bastiaanssen, W. G. (2004). Estimation of disaggregated canal water deliveries in Pakistan using geomatics. International journal of applied earth observation and geoinformation, 6(1), 63-75. [7] N. M. Phuong, M. Schappacher, A. Sikora, Z. Ahmad, and A. Muhammad, Real-time water level monitoring using low-power wireless sensor network," in Embedded World Conference, 2015. [8] T. Younos and C. J. Heyer, Advances in water sensor technologies and real-time water monitoring," in Advances in Watershed Science and Assessment, pp. 171{203, Springer, 2015. [9] Habibullah Bodhla. “Technology being used for the Monitoring of Canal Operation”, Symposium on Telemetry Systems for Water, LUMS, Lahore, 2014. [10] World Bank, Punjab Barrages Improvement Phase II Project (PBIP-II) Project Report. 2015. [11] Ahmad, Z., & Muhammad, A. (2014, October). Low power hydrometry for open channel flows. In Industrial Electronics Society, IECON 2014-40th Annual Conference of the IEEE (pp. 5314-5320). IEEE. [12] Ahmad, Z., Asad, E. U., Muhammad, A., Ahmad, W., & Anwar, A. (2013). Development of a low-power smart water meter for discharges in indus basin irrigation networks. In Wireless Sensor Networks for Developing Countries(pp. 1-13). Springer Berlin Heidelberg.
235