There is an increase in the use of water models: from planning, designing and managing infrastructure to disaster risk reduction and pollution mitigation, particularly in scenarios where there are a lot of uncertainties involving climate change.
In the US, the Environment Protection Agency supports the Clean Water and Safe Drinking Water Acts through its Healthy Watersheds Protection Program, where water models are employed to assess vulnerability. Similarly, the Great Lakes Restoration Initiative in North America has funded watershed management projects worth $12.5 million using water modelling. By 2021, the initiative had been highly effective in removing almost 40 percent of pollutants in the lake.
Water models also enable transboundary cooperation across basins and countries, especially for disaster risk reduction. The International Commission for the Protection of the Rhine in Central and Western Europe and Bureau of Meteorology in Australia use water models to estimate flows and flood risks and implement timely evacuation measures.
While there has been significant use of water models in Global North policymaking, policymakers in the Global South lag behind in the use of modelling tools. Three key reasons why this is and how they can be improved using examples from countries in the Asia-Pacific are examined below.
1: Technical limitations and information gaps
Water models are simplified representations of real-world processes and thus are inherently unable to resemble them outside their hydro-geographical area of development, whilst their usage in distinctly different physical domain yields uncertainties.
Furthermore, ideal data to set a robust water model in terms of both quantity and quality are seldom available in developing countries. For instance, Nepal has more than 30 years of meteorological and hydrological information, but the data quality is dubious and cannot be directly used for modelling purposes.
Similarly, modelling geographical characteristics requires meteorological and hydrological information from complex ecosystems and terrains, but much of this data is mostly unavailable. In Fiji, the locations of observation stations are so remote that acquiring information from them manually or even through cellular connections is next to impossible outside the cities. National modellers were thus convinced that the models were either non-representative of their watershed or data limitations induced errors in the information they generate. This results in reducing the scientists’ own confidence in using the results or making recommendations based on the information to policymakers.
2: Limited or misaligned national capacity
Many Asia-Pacific countries rely either partially or fully on international consultants for water modelling efforts due to their own limited capacity. There are two major aspects to this limitation:
In Fiji and Nepal, young people tend to leave their jobs at government or research institutions in their home countries to seek better opportunities abroad. Most often, the state salary is not attractive enough. Moreover, repeated restructuring of line ministries and departments with consequent revisions of mandates and responsibilities affects the placement and distribution of skilled water resources modellers and their ability to best contribute to the water agencies that need their expertise.
In Viet Nam, the Ministry of Agriculture and Rural Development (MARD) and the Ministry of Natural Resources and Environment (MONRE) are engaged in an ongoing dispute to control the country’s water resources management. In 2002, there was a significant shift in responsibilities for water resources management from MARD to MONRE. However, MARD retained the majority of water experts, while MONRE had fewer than 1 percent of water experts among a total staff of 1100. This meant that national modellers who were better at modelling watersheds became less involved in the agency’s activities, thereby undermining MONRE’s modelling efforts.
3: Limited or delayed involvement of policymakers
This is probably the most crucial reason why information from water resources models is not used by policymakers. In most countries in the Asia-Pacific, information generated from water models are either sent to line agencies and ministries as circulars or reports towards the final stage of watershed management efforts or sometimes not shared at all.
In Bangladesh, the government has multiple research institutes involved in water resources modelling and management. Despite having many skilled modellers with extensive knowledge of local watershed processes, these institutes involve policymakers in the last stage of water resources modelling processes. As a result, there is limited interest and engagement from policymakers and subsequently, information generated by modelling process seldom meets the policymakers’ expectations.
Water models are inherently complex and their results need to be interpreted with caution. Given that most policymakers are less interested in the technical terms of the model and more on how they can use it for decisions in different policy scenarios, much frustration emerges among modellers and policymakers in reaching common understanding about results and policy recommendations.
There are at least three ways to ensure modelling can benefit water policymaking in the Asia-Pacific.
1: Better accessibility to technology
In the past, models were “black-box” and modellers did not know the underlying algorithms. However, many water models are currently open-source and are freely and easily modifiable. The modular architecture of the model now allows for modifying original algorithms to better represent hydrogeographical characteristics of interest.
Thanks to the increased understanding of different earth processes, water models are now becoming more representative of geographical, meteorological, physical, biochemical, environmental and anthropogenic components of a real-world system. Water models are now referred to as ecohydrological models and multiple decision support systems are constructed using them and are already operational in many countries of the Asia-Pacific as well. As for limited data, remotely sensed and satellite information are also freely available for the entire world, with very high spatial and temporal resolutions. In addition, several techniques are now available to explicitly deal with limited geographical representation of climatic data, which can increase confidence in using water resources models for complex watersheds. All of this contributes to the increase in confidence of modellers in using model results and passing on the information to decision makers.
2: Find ways to develop or retain modelling expertise
if water modelling is to find more mainstream usage, it needs to be better integrated into national university systems. It is recommended that at least one premier university in developing countries be tasked with providing state-of-the-art knowledge on water resources modelling and management. This will help quickly recruit modelling students into national agencies. Bangladesh is a good example of where the government has multiple modelling research institutes as part of their prestigious universities. If it is not immediately possible, government agencies can also secure memoranda of understandings with well-known foreign universities to provide capacity building for their national modellers, as in is the case with Nepal. However, training modellers alone is not enough. They need to be competitively remunerated to retain them in long-term employment.
Outsourcing water resource modelling projects helps national consultants and university faculties to retain capacity within the country and allows modellers with local knowledge to improve at models. This again increases confidence in modelling information and results in, as in many governments, senior academicians and professors remaining in advisory capacities.
3: Bring policymakers into the modelling process from the beginning
The lack of early policymaker involvement in the modelling process will result in their alienation from the purpose, complexity and reliability of the model results.
Therefore, it is crucial that policy and decision-maker input are taken from the inception of project design. Policymakers are often only interested in clear answers or recommendations for water use rather than the technical aspects of the models. Water resources modellers need to identify the scenarios that policymakers have in mind to enable an inclusive water resources modelling approach. Continuous update and feedback during the modelling process will help policymakers develop a sense of understanding and co-ownership of the results. In addition, a more forgiving legal and executive system and open cultural environment may allow policy and decision makers to test and try the informed decision-making approach using water resources models. There is also a need for using innovative platforms to translate the technical jargon of water models to the policy dialogue tables.
Note: This perspective is based on the Understanding Water Modeling Capacity and Use in the Asia Pacific Region project between the Food and Agricultural Organization and SEI Asia. Seven countries were selected as a part of the initial stage of the project to develop a five-year water scarcity program: Bangladesh, Fiji, Indonesia, Myanmar, Nepal, Thailand and Viet Nam.