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hydrosystems @ cyphynets


Many developing world countries face severe water shortages, a large magnitude of which can be attributed to the inefficient operation of their water networks. One of our main research thrusts is control, estimation and optimization of water resources in Pakistan. We look at water distribution problems in large-scale irrigation networks, contamination spread in surface and groundwater resources and decision support systems for basin management. We freely employ control and estimation techniques from the domain of cyber-physical systems into design and operation of hydro-systems. We are now involved in building several practical systems and testbeds in Pakistan in cooperation with provincial government agencies and non-governmental institutes.

An overview of our hyrdosystems research can be found in the following presentations.

  • Building a Smart Water Grid for Pakistan, SSE Seminar Series, March 2012. Slides
  • Modeling, Simulation and Data Assimilation for Indus River Basin Management, Planning Commission, April 2011. Slides

Please check Publications for more details on specific projects.


  • Abubakr Muhammad (Lead)
  • Hasan Arshad Nasir (Control & estimation of open channels)
  • Zaeem Hussain (Data assimilation & sparse estimation in groundwater models)
  • Maryam Javed (Data assimilation algorithms)
  • Zahoor Ahmad (Electronics & instrumentation for smart water meters)
  • Zarrar Khan (GIS, Geotechnical engineering)
  • Ehsan ul Haq (Software Systems)
  • Allah Bakhsh (Electronics & instrumentation for smart water meters)


Smart Water Meters for IWMI Project: Revitalizing Irrigation in Pakistan

  • Funding. International Water Management Institute (IWMI)
  • Duration. 2012-14

IWMI's project Revitalizing Irrigation in Pakistan (RevIIP) aims to contribute to agricultural development in Pakistan through the efficient management of surface water and the sustainable use of groundwater in selected canals within the Indus Basin Irrigation System to enhance food security, reduce poverty and adapt to uncertainties brought about by climate change. The beneficiaries of this project primarily be; farmers, Farmer Organizations, Area Water Boards, and the water and canal management organizations e.g Irrigation Departments. The project funded by the Royal Government of the Netherlands will be executed by the International Water Management Institute (IWMI).

We have partnered with IWMI to build smart water meters to study water usage, scarcity and drainage patterns in different canal networks in Pakistan. The development effort entails instrumentation, calibration, data dissemination and data analysis in cooperation with experts from IWMI.

Contamination Spread Monitoring in Surface and Groundwater

  • Funding. Environment Protection Agency (EPA)
  • Duration. 2012-14
  • Partners. TU Delft, KAUST

This project aims to develop a decision support system for the Environmental Protection Agency (EPA), Govt of Punjab to monitor surface and ground water contamination spread in the province’s natural water resources. We are building a unified analytical and computational framework to overcome the limitations of inaccurate and sparse water quality surveys as well as fundamental limitations of prediction with physical models. Mathematical techniques called as data assimilation combine inaccurate sensor data with uncertain physical models to filter the effect of both and give a more accurate picture of the underlying contamination spread dynamics. The research team is working with EPA to develop a methodology to employ these techniques for practical contamination monitoring, starting with the processing of river contamination surveys available with EPA and possibly extending it to groundwater data. The project entails a concerted effort in mathematical modeling, software development and information dissemination to benefit the end user.

Bayesian Inversion, Compressive Sensing & Data Assimilation in Hydrosystems

  • Funding. LUMS, KAUST
  • Duration. 2011-present
  • Partners. KAUST, TU Delft

We are developing the computational and mathematical framework to perform state estimation in subsurface hydrology using Ensemble Kalman Filtering and Bayesian inversion and filtering. To overcome the limitations of sparse measurements, predictions from geophysical models such as contaminant transport models and historical data are combined with measurements in a sophisticated mathematical and computational framework of data assimilation for which Bayesian techniques are one of the most sophisticated methods developed to-date. The general framework of Bayesian filtering allows such processing in a provably correct manner. Initial estimates (prior density) are combined with system dynamics to generate a prediction, which results in an optimally corrected estimate (posterior density) when combined with sensor measurement. The framework has been applied to a wide range of problems in science & engineering. The application of this framework to subsurface hydrology problem is both novel and challenging due to the large dimension of state as well as the sparsity of measurement data. We are also looking at sparse signal recovery techniques (a.k.a. compressive sensing) to deal with the problem of sparsity of dug wells in this problem.

Software Architectures for Smart Water Grids

  • Funding. LUMS
  • Duration. 2011-
  • Partners. Georgia Tech.

Future irrigation networks represent a prime example of cyber physical systems. Effective operation of these complex cyber physical systems is not possible with conventional methods and requires unprecedented levels of automation and decision-support tools. These cyber physical systems will require a complete model-driven toolset for effective operation. As a first step towards that tool flow, we have developed a model-driven simulation infrastructure for irrigation networks. We have developed a domain-specific modeling language (DSML) for irrigation networks, implementation of this DSML in Generic Modeling Environment (GME), and automatic simulator M-file generation capability from the DSML-based case diagram of an arbitrary irrigation network. We have also done case studies of water distribution and flood management to show the utility as well as the effectiveness of our approach.

Control & Identification of Irrigation Channels

  • Funding. LUMS startup and FIF
  • Duration. 2009-present
  • Partners. University of Melbourne, Punjab Irrigation Department

In this project we have tackled the issue of managing canal irrigation networks from the viewpoint of implementing a cyber physical systems (CPS). We have proposed an infrastructure in which networked embedded controllers and level & flow sensors can be used for monitoring and regulation of a very large-scale canal network. We describe PDE models for open channel flows, system identification techniques to simplify the model, local control system design and strategies to implement a decentralized control network. The theoretical study is supported by simulations on large networks. The work has been extended to study system health monitoring issues, such as the location of illegal dumps, leaks and breaches in a network. We view these problems from the point of cyber and physical attacks on the security of a CPS.

Water Rights in Smart Water Grids

  • Funding. Development Policy Research Center at LUMS
  • Duration. 2011-12

By understanding the connections between new technologies and traditional methods in enforcing water rights at various levels in the Indus river basin, this project provides a critical connection for interdisciplinary efforts on water related research. We aim to develop a reference for the scientific and engineering community to understand the existing irrigation canal infrastructure, historical contexts of its evolution from pre-colonial times to recent reforms, institutional control mechanisms and concrete estimates of the (extremely low) distribution inefficiencies. We also catalog cases of automation and irrigation infrastructure failures and the development of flood control mechanisms both prior and subsequent to the 2010 floods in Pakistan.

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