Climate-Informed Water Allocation in Central Asia: Leveraging Decision Support System

Abstract

As the impacts of climate change intensify, water resource conflicts are escalating globally, particularly in regions with uneven water distribution, such as Central Asia. Long-standing disputes over water allocation persist between Kyrgyzstan and Uzbekistan. This paper aims to examine the conflicts and challenges in water allocation between the two countries and explore the potential of Decision Support Systems (DSSs) as a viable solution. The paper begins by reviewing the historical evolution of water allocation in Central Asia, analyzing upstream–downstream disputes and notable cooperation efforts, with a focus on key water agreements. It then outlines the definitions, development, and classifications of DSSs in the context of water allocation and presents two illustrative case studies—the Tarim River Basin in Xinjiang, China, and the Nile River Basin in Africa. These cases demonstrate the applicability of DSSs in water-scarce regions with similar socio-ecological dynamics and complex multi-country, cross-sectoral water demands. Building on these insights, the paper analyzes the key challenges to implementing DSSs for transboundary water allocation in Central Asia, including limited data availability and sharing, insufficient technical capacity, chronic funding shortages, socio-political complexities, climate change impacts, and the inherent difficulty of modeling complex systems. In response, a set of targeted pragmatic recommendations is proposed. While acknowledging its limitations, the paper argues that establishing a structured, system-based decision-making framework—namely DSSs—can help stakeholders enhance climate-informed strategic planning and foster cooperation, ultimately contributing to more equitable and sustainable water resource allocation in the region.

1. Introduction

Efficient and equitable transboundary water allocation is fundamental to regional stability, particularly in climate-vulnerable and water-scarce regions such as Central Asia [1]. Intensifying climate change, rising population pressures, and competing national development priorities have heightened the stress on shared water resources, making cooperative basin governance increasingly difficult [2]. Despite a long history of negotiated agreements, recurring tensions, especially between upstream and downstream countries, illustrate the persistent challenges of managing shared rivers under climate uncertainty and divergent sectoral needs [3,4].

These challenges reflect a broader regional problem: current water allocation practices remained fragmented, reactive and insufficiently informed by data or long-term planning tools. Decision-making is often driven by political negotiation rather than analytical assessment, limiting the region’s capacity to anticipate hydrological variability, evaluate trade-offs, develop sustainable allocation strategies, and address climate change. This lack of structure, and transparent and science-based support mechanisms represents a critical governance gap.

Modern water governance increasingly relies on Decision Support Systems (DSSs) to address such complexity. DSSs integrate hydrological data, climate projections, stakeholder inputs and analytical models to evaluate management alternatives and enhance cooperative planning. In many transboundary basins worldwide—including Nile, Mekong and Colorado—DSSs have facilitated more transparent dialogue, reduced conflict potential, and supported evidence-based allocation decisions [5,6,7]. However, Central Asia currently lacks a basin-specific DSS capable of capturing its unique water-energy-food dynamics, institutional context, and climate vulnerabilities.

Therefore, this Opinion article argues that a transition toward climate-informed, evidence-based decision-making can help facilitate more cooperative, transparent, strategic and equitable allocation decisions. The aims of this article are thus to:

(i)

examine historical and contemporary water allocation challenges in Central Asia,

(ii)

assess the potential and challenges of DSSs for improving transboundary basin management, and

(iii)

provide practical recommendations for designing a climate-sensitive DSS for the Syr Darya context.

To this end, Section 2 presents the study area and outlines the methodological approach adopted in this Opinion paper. Section 3 introduces transboundary water allocation in Central Asia, beginning with the Soviet-era background and expanding into current water conflicts. Section 4 introduces the definitions, evolution, and typologies of DSSs, complemented by two DSS case studies—the Tarim River Basin and the Nile River Basin. Section 4 examines the specific challenges in developing DSSs for transboundary water allocation in the study area and offer corresponding recommendations. Section 5 provides a conclusion to the entire review.

2. Study Area and Methodology

2.1. Study Area

Central Asia is highly agrarian with an arid to semi-arid climate where evaporation outweighs precipitation to a significant extent [8,9]. Water resources are distributed unequally, with the vast majority of surface water generated in the upstream regions of Kyrgyzstan and Tajikistan, while most of the region’s water consumption occurs downstream, primarily in Uzbekistan and Turkmenistan. These disparities underscore the importance of sustainable use of shared water resources and the need for regional cooperation [1]. The main rivers of the region, the Syr Darya and Amu Darya, originate in the high mountains of Kyrgyzstan and Tajikistan and flow through the neighboring states of Uzbekistan, Kazakhstan, and Turkmenistan. Following the dissolution of the Soviet Union in 1991, five now-independent Central Asian states—Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan—began independently managing water and energy systems that were once centrally coordinated.

This study focuses on the upper Syr Darya Basin, with particular attention to the transboundary dynamics between upstream Kyrgyzstan and downstream Uzbekistan. The region plays a central hydrological, socio-economic, and political role in Central Asian water management. The Syr Darya originates in the Ferghana Valley from the confluence of the Naryn and Kara Darya rivers, both rising in the mountainous terrain of Kyrgyzstan. The Ferghana Valley is one of the most densely populated regions in Central Asia, supporting approximately 16 million people. It is also a major agricultural hub, contributing significantly to Uzbekistan’s irrigated agriculture sector. Surrounded by the Tian Shan Mountains to the east and north and the Alay Mountains to the south, the valley forms a semi-enclosed basin that channels water toward Uzbekistan and Kazakhstan. While the central part of the valley lies within Uzbekistan, its northern and eastern portions extend into Kyrgyzstan, and a smaller section to the west and southwest belongs to Tajikistan. This spatial configuration has a strong influence on hydrological connectivity, upstream–downstream dependencies, and competing water uses (Figure 1).

The climate is predominantly arid to semi-arid, characterized by low rainfall, high evaporation, and increasing hydrological uncertainty driven by glacier retreat, rising temperatures and changing precipitation patterns. Recent studies indicate significant declines in glaciation, with glacier area in Kyrgyzstan decreasing by 23.4% since the mid-20th century, contributing to shifts in seasonal runoff [10,11,12]. The basin depends heavily on snowmelt- and glacier-fed runoff, resulting in pronounced seasonal variability. Spring and summer (April–September) form the high-flow period, enabling downstream irrigation in Uzbekistan. In contrast, winter (October–March) represents the low-flow period, as precipitation is stored in snow and ice and natural inflows decline sharply. This natural pattern is further modified by regulated releases from the Toktogul Reservoir. Kyrgyzstan stores water during summer for winter hydropower generation, thereby inverting the natural flow regime through increased winter releases and reduced summer flows. As a result, the basin exhibits a hybrid natural–regulated flow regime with strong upstream–downstream implications.

Water use priorities differ substantially between the two countries: Kyrgyzstan relies on hydropower for approximately 90% of its electricity generation, necessitating winter reservoir releases, while Uzbekistan depends on large-scale irrigated agriculture, primarily cultivating cotton, wheat, and horticultural crops. This upstream–downstream asymmetry creates persistent tensions over flow timing, allocation volumes, and reservoir operation. The broader socio-economic context—including high population pressure, extensive irrigated land, and growing climate-induced water stress—further amplifies the challenges of sustainable water sharing. Together, these characteristics illustrate why the Syr Darya Basin represents a highly dynamic and politically sensitive setting for examining the potential of DSSs in transboundary water allocation.

2.2. Methodology

This study employs a qualitative review-based methodology, combining a systematic literature review with experiential insights from stakeholder engagement. Relevant scientific articles, books, and institutional reports were collected and organized using the Mendeley search and reference management system, which enabled efficient extraction and synthesis of materials related to transboundary water allocation and Decision Support Systems (DSSs). Beyond the literature, the identification of DSS challenges and formulation of recommendations draw heavily on the authors’ practical experience during the EU Horizon Europe WE-ACT (Water Efficient Allocation in a Central Asian Transboundary River Basin) project, which focuses on developing a climate-sensitive DSS for the upper Syr Darya Basin. Multiple stakeholder interaction activities, including interstate, regional, and local workshops, technical meetings, and personal communication with key water managers, provided first-hand knowledge of data limitations, institutional barriers, and user needs. Stakeholders included transboundary river basin organizations, national ministries, regional water agencies, and irrigation management institutions. Integrating academic evidence with practitioner-based insights allows this study to ground its analysis in both scientific understanding and real-world decision-making contexts.

3. Water—The Driver of Peace and Conflict

Water scarcity and distribution disparities in Central Asia have triggered conflict among states. Kyrgyzstan and Tajikistan have an excess of water, while the other three states claim they do not receive their fair share from major rivers. Factors such as an increasing population, depletion of resources like land and soil, failing infrastructure and climate change exacerbate this crisis further. Weak economies and fragile states fuel nationalism, border disputes and regional tensions, impeding efforts at finding acceptable solutions based on bilateral agreements. There is an urgent need for new approaches that incorporate bilateral agreements as soon as possible [13].

The primary issue stems from the collapse of the Soviet Union’s “resource sharing” system in Central Asia, which was in place until 1991. Under this system, Kyrgyzstan, Tajikistan, and Kazakhstan supplied water to Turkmenistan and Uzbekistan in the summer, while they received coal, gas, and electricity during the winter from these countries. This system began to deteriorate in the late 1990s, and subsequent bilateral and regional agreements have failed to resolve the issue [4].

3.1. Soviet Legacy

Cotton is the protagonist of the story of water management in Central Asia, often referred to as the “white gold” of the region [4]. In the 19th century, cotton imports from the United States were disrupted due to Civil War. Russian textile factory owners sought alternative sources for raw cotton production by expanding cotton plantations in Central Asia to reduce dependence on costly American imports. Recognizing the region’s favorable climate and access to major rivers, Russia saw Central Asia’s potential for cotton production following its expansion into the area [14].

During the 1930s, Turkmenistan, Uzbekistan, and Tajikistan became centers to an extensive cotton monoculture, known as “the dictatorship of white gold,” making Central Asia the primary cotton-producing regions for the entire Soviet Union. Agricultural mechanization in the 1960s led to increased irrigation systems throughout Central Asia with cotton cultivation being given priority. Numerous reservoirs, extensive water supply and drainage networks as well as large pumping stations were constructed specifically to meet the high water demands of cotton production. This period under Russian governance saw significant growth in cotton production in Central Asia. In the 1860s, the region supplied only 4–7% of Russia’s raw cotton; by 1914–1915, this figure had skyrocketed to 70% [3].

3.2. Water Conflicts

The water conflict between Kyrgyzstan and Uzbekistan dates back to early years of the independence of the Central Asia states. The two countries have had tensions over the water resources where the upstream Kyrgyzstan is rich in water resources while the downstream Uzbekistan is rich in fossil fuel but relies heavily on the water for its irrigation. Kyrgyzstan has sought to make full use of its water resources by trying to monetize it and even make favorable laws that contradict existing agreements, such as the Almaty and Syr Darya Agreements [15].

In 1997, tensions escalated dramatically when Uzbekistan deployed 130,000 troops near the Toktogul reservoir area along their mutual border. This strategic move provoked a significant policy shift in Kyrgyzstan. According to Ramos (2021) [16], this military positioning caused resentment within Kyrgyzstan, leading to the enactment of a 1997 resolution designating water as a marketable asset, thus allowing Kyrgyzstan to capitalize economically its water resources. In a retaliatory act, Uzbekistan cut off gas supplies to Kyrgyzstan in 1998, citing the lack of payment [16].

The power dynamic between Kyrgyzstan and Uzbekistan is complex, with each country heavily dependent on the other. Over the years, both have come close to armed conflict on multiple occasions. Uzbekistan, with its greater gross domestic production (GDP) and population, often uses its forces to intimidate its upstream neighbor, while Kyrgyzstan has leveraged its control over water, at times flooding Uzbek cotton fields by releasing water from Toktogul reservoir or withholding its water to barren the land.

3.3. Cooperation—Noteworthy Agreements

3.3.1. Almaty Agreement 1992—The Birth of Interstate Commission for Water Coordination (ICWC) in Central Asia

On 12 October 1991, water ministers from Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan agreed to continue using Soviet-era water allocations, a decision known as the Almaty Agreement of February 1992. This agreement aimed to cooperatively manage and safeguard water resources, emphasizing fair usage and mutual responsibility for rational use and protection, according to the area’s water availability. It also stipulated that each country should avoid actions that could harm others, reflecting the principles established by the 1966 Helsinki Rules and the 1992 UN/EC Helsinki Convention on transboundary watercourses [17].

Tripathi & Gaur (2019) points out the limitations of the 1992 agreement, emphasizing the fact that the agreement needs to be updated to ensure the stability in the region [18]. The authors consider climate change and the melting glaciers in the Kyrgyz side to be worrying as it will decrease the flow of water into downstream countries, creating further strains in between the neighboring republics [18]. Although the Almaty Agreement was a stepping stone towards cooperation, it has not dissipated the water tensions in the region, mainly due to the following reasons: (1) lack of coherent water management; (2) non-compliance with or update to assigned water quotas.; (3) unfulfilled or delayed barter agreements and payments; (4) uncertainty surrounding future infrastructure plans; and (5) lack of representation of agricultural or industrial users, non-governmental organizations, and other relevant stakeholders.

3.3.2. Syr Darya Agreement 1998—The Revival of Barter Agreements

The Syr Darya Agreement was signed by Kazakhstan, Kyrgyzstan and Uzbekistan in 1998, with Tajikistan joining a year later, facilitated by the United States Agency for International Development (USAID). The primary goal was to incorporate the soviet era barter agreements between the republics, where natural resources such as water, coal, fuel etc., were exchanged, an aspect that the Almaty agreement failed to address.

Although the 1998 agreement initially appeared to resolve water conflicts, it ultimately failed due to conflicting interests. Murthy & Mendikulova (2017) [14] elaborates in detail the main reasons behind the lack of success of the Syr Darya Agreement, which are summarized as follows:

i.

The agreement stipulated that the cost of operation, maintenance, and renovation of water infrastructures must be borne by the owner, i.e., Kyrgyzstan. This made Kyrgyzstan liable for all costs, leading to disagreements as the maintenance costs for the Toktogul reservoir range between $15 to $27 million annually.

ii.

The agreement mandated that the countries must annually negotiate water distribution, a process that frequently resulted in intense disputes or the inability to establish or uphold agreements.

iii.

The agreement led to less energy compensation in wet years, prompting Kyrgyzstan to release more water in winter from Toktogul, causing downstream flooding and summer water shortages. This issue arose due to the agreement’s lack of provisions for yearly water variations and reservoir costs.

iv.

In 2001, Kyrgyzstan adopted a new law monetizing its water resources (On the Interstate Use of Water Installations, Water Resources and Hydro Facilities in the Kyrgyz Republic), which conflicted the existing barter agreement, heightening tensions with downstream countries, particularly Uzbekistan.

3.4. Challenges in Central Asia

Despite various efforts to resolve water issues and fairly allocate resources in Central Asia, none of the attempts and agreements have achieved complete success. Instead, they have often added layers of complexity. Here, several main causes for the inefficacy of such agreements are identified, providing valuable lessons for further initiatives:

i.

Narrow Scope and Sectoral Silos

Historically, Central Asia’s river basin organizations had operated with a narrowly defined scope, concentrating on specific technical tasks and restricting their role in addressing broader social and environmental challenges. For example, institutions such as ICWC focus mainly on distributing water quotas and lack authority over highly interdependent sectors like agriculture and energy. This limited mandate, compounded by weak interagency coordination across the water-energy-environment nexus, severely restricts integrated water resource management.

ii.

Capacity Deficits

Water institutions in the region continue to suffer from inadequate technical capacity, understaffing, and outdated management structures—legacies of the centralized Soviet system. These deficiencies severely hinder the resolution of water-related disputes. For instance, water allocation quotas are still based on river flow forecasts issued only twice a year, which often contains great uncertainty. As a result, countries must contend with unreliable data that complicates planning and makes timely adaptation difficult. Furthermore, weak systems for water accounting and the lack of high-quality, actionable data continue to undermine effective and equitable water distribution. Additionally, the need for consensus during decision-making bodies like the ICWC and the IFAS often leads to deadlock when countries’ interests differ.

iii.

Insufficient and Uneven Funding

Effective water allocation negotiations require significant financial investment in terms of time, data, and expertise. However, the unstable economies of the Central Asian states are unable to fund initiatives adequately, resulting in minimal achievements. Among member states, only Turkmenistan and Uzbekistan consistently contribute financially. This results in unbalanced resource allocation, staffing disparities, and geographically skewed distribution of executive bodies, all of which undermine the legitimacy and functionality of transboundary institutions.

iv.

Weak Enforcement and Limited Jurisdiction

Institutions struggle to enforce agreements, undermining their authority and discouraging compliance. Treaties for equitable water-sharing on the Syr Darya face issues like non-compliance and insufficient enforcement. Limited access, visa requirements for inspections, restricted monitoring resources, and a lack of power to penalize or shut down non-compliant facilities further hinder these institutions from effectively upholding their agreements.

v.

Inadequate Attention to Long-Term Risks and Uncertainty

Regional water management often focuses on short-term operational concerns while neglecting long-term planning and adaptation. There is an urgent need to incorporate forward-looking tools—such as scenario analysis, hydrological modeling, and joint action planning—to anticipate and prepare for the impacts of climate change. Embracing collaborative adaptive management would allow institutions to revise strategies dynamically in response to evolving climatic, societal, and political conditions. In a region where future water availability is increasingly uncertain, flexible and anticipatory governance is no longer optional, but essential.

4. Decision Support System for Transboundary Water Allocation

4.1. Definition, Development & Classification

Decision-making can generally be classified into three types: structured, unstructured, and semi-structured [19]. Structured decisions are made under conditions of certainty, with clear, repeatable steps and standard solutions. Unstructured decisions involve high uncertainty, often requiring intuition and advanced support tools. Semi-structured decisions lie between these two, where outcomes are partially predictable but still involve multiple possibilities requiring the best possible choice based on available information.

Since the 1970s, Decision Support Systems (DSSs) have been defined in many ways, evolving from tools for structured and unstructured problems to much more complex systems. Power (1997) broadly defined DSSs as any system that aids decision-making, such as management information systems, executive support systems, geographic information systems, OLAP, or software agents [20]. While this reflects one dimension, technological advances and growing problem complexity have expanded the concept significantly.

Mysiak et al. (2005) argue that DSSs must address so-called wicked problems—those lacking clear, universally agreed definitions [21]. Addressing one aspect often reveals another, more complex dimension. A key feature of wicked problems is that stakeholders often see issues only from their own perspective, without a holistic view. This is especially true in Central Asia, where transboundary water allocation conflicts can be seen as classic unstructured, wicked problems. A well-designed DSS can help reduce tensions and foster shared understanding of resource allocation.

Technically, humans have made water allocation decisions for millennia, initially through simple irrigation and reservoir construction. Over time, these methods have become more sophisticated, with modern technology enabling automated monitoring and decision processes. Advances in computing, sensors, and communication have transformed global water data exchange and ushered in a new era of DSS-enabled management [16]. As data quality and availability improve, computing power increases, and sensor technology advances, many barriers to adopting water-focused DSSs are being overcome. Wardropper (2022) highlights that cloud computing and storage now allow simulations to run without expensive local infrastructure, enabling more inclusive DSS designs [22].

A successful DSS typically has several key features: interactive use enabling smooth collaboration with databases and users; effective change detection to monitor and recognize important events; user-friendly interfaces for clear communication; the ability to detect and manage user errors while acknowledging system limitations; intelligent extraction of meaningful insights from large datasets while removing ambiguity; and predictive capabilities to assess the potential impact of changes over both short and long timeframes.

Yet, water allocation decisions remain highly complex despite technological advances. Managing a transboundary river basin with multiple stakeholders requires extensive negotiation and careful consideration of socioeconomic impacts, environmental consequences, and competing national water rights. Historically, water allocation was guided by social criteria, focusing on providing drinking and sanitation water with less attention to economic efficiency. However, with population growth and growing scarcity, water’s economic value and efficient use have become increasingly important. Nel (2022) notes that viewing water as an economic good has encouraged more decentralized management and greater stakeholder participation [23]. Basin planning now requires a holistic approach that accounts for environmental concerns, climate change, sociopolitical factors, and stakeholder objectives.

Recognizing the need to balance social, economic, and environmental goals, Nel (2022) [23] categorizes DSS approaches for water allocation:

• Rule-based systems, which rely on expert knowledge and can incorporate simulation results to refine rules;
• Economic benefit models, using cost–benefit analysis to optimize economically viable water distribution;
• Computable General Equilibrium (CGE) models, combining economic theory and data to model the entire economy and sector interactions;
• Game theory approaches, which actively engage stakeholders to resolve conflicts, especially at transboundary scales, with cooperative variants incentivizing mutual benefits;
• Multi-Criteria Analysis, ranking options against diverse criteria to support balanced decisions;
• Multi-Objective Analysis, often seen as an extension of MCA, explicitly solving for multiple goals;
• System dynamics, using system thinking and descriptive modeling to forecast future scenarios [24].

Nel (2022) [23] concludes that Multi-Criteria and Multi-Objective Analyses are especially effective for balancing social, environmental, and economic requirements. Although his study is based in South Africa, these insights are widely applicable, offering frameworks that can guide DSS selection for other river basins.

The following sections will review two practical examples to illustrate DSS applications in transboundary water allocation.

4.2. SuMaRiO DSS—An Exemplar for the Region

The Tarim river, situated in the northwestern province of China, Xinjiang, is at a strategic location between China and Central Asia. It bordering mountain ranges of Tian Shan, Kunlun and Pamir in the north, south and west, respectively. The Aksu River, a main tributary of the Tarim River, contributing approximately 80% of its discharge. The region is notorious for its arid climate, characterized by low precipitations and high evapotranspiration rates. With evaporation rates around 2000 mm per year and rainfall rates averaging only 100 mm per year, the Tarim and Aksu Rivers rely heavily on upstream inflow [25].

Xinjiang is an important agricultural region that provides 15% of the world’s cotton. Given cotton’s water-intensive nature, an average of 4000 cubic meters of water per hectare is used in China [26]. Balancing the water needs of human beings, agriculture, natural ecosystems in an arid climate poses a complex problem that encompasses all aspects and hence requires a holistic approach to managing water resources and land use effectively. These challenges led to the development of the Sustainable Management of River Oases along the Tarim River (SuMaRiO) project.

4.2.1. SuMaRiO—A Holistic DSS

Many DSSs focus on a singular aspect such as socio-economic, climate change, land use, or water use to keep the model less complex. However, integrating multiple aspects into a DSS is worthy [25]. The SuMaRiO project, which began in 2011, was a collaboration among 11 German and 6 Chinese universities. It concluded in 2015 with the creation of a comprehensive DSS. Data was collected from various fields, including climate modelling, hydrology, agricultural sciences, cryology, ecology and geoinformatics, to understand the impacts of various water availability schemes on human activities and natural ecosystems [25].

The Tarim River region depends entirely on river water due to its low rainfall and high evaporation. In summer, the river receives fresh water mainly from melting glaciers and snow, which can lead to floods, filling reservoirs and channels. Over the past 50 years, the average temperature has increased by 0.4 °C, and climate models predict this warming trend will continue. This could result in more water availability and an increase in cotton farming upstream. However, the region faces two major issues: the competition for water between human needs and natural vegetation, and the conflict between cotton farming and preserving natural land. These conflicts contribute to land degradation and desertification [26].

The purpose of the SuMaRiO project was to manage land and water use through a DSS in a very water-scarce region. This objective resonates with the focus of this review, i.e., Central Asia. Given the proximity to Central Asia and similarity of the problems faced in the region over water and land use, the SuMaRiO project can serve as an example for new similar projects developed in Central Asia.

The SuMaRiO Decision Support System (DSS) integrated surface water and groundwater modeling. The system receives input discharge data from a database called WASA Surface flow is modeled using MIKE HYDRO, while groundwater dynamics are simulated using MODFLOW. The models are interconnected, with MIKE HYDRO simulating surface flow and MODFLOW providing groundwater recharge boundary conditions. This integrated approach ensures a comprehensive analysis of water distribution, supporting efficient decision-making through different scenarios for sustainable water resource management.

4.2.2. Remarks on SuMaRiO DSS

The Decision Support Tool (DST), a key result of the SuMaRiO project, serves as a vital link for communication among scientists from various fields, as it requires them to merge their expertise into a tangible product. Additionally, the DST is instrumental for engaging stakeholders and increasing public awareness. It allows people of all educational backgrounds to evaluate various scenarios of land and water management. This way, stakeholders can comprehend how different management approaches might impact their daily lives and understand the broader impacts of their decisions on water use.

The tool is designed to be user-friendly, enabling stakeholders from diverse backgrounds to understand and utilize it, thus fostering a better understanding of the Tarim River Basin’s environmental system. The tool operates with basic rules that stakeholders can update with new data based on their specific needs and available information.

The development of the DST involved extensive discussions with multiple stakeholders at different levels. These discussions were crucial in identifying important factors for setting up climate scenarios, socio-economic models, and management choices. By involving stakeholders in the decision-making process, the DST ensures that the resulting strategies are well-informed and broadly supported.

4.3. Nile DSS—An Exemplar for Central Asia

The Nile Basin (NB) is without a doubt one of the most important transboundary rivers and due to the reliance of many countries over its resources, it makes its allocation even more complicated. The Nile basin stretches over 11 countries, i.e., Burundi, DR Congo, Egypt, Eritrea, Ethiopia, Kenya, Rwanda, South Sudan, the Sudan, Tanzania and Uganda, covering an area of approximately 3,170,000 square kilometers [27].

Although the geographical location of the Nile is entirely different than that of Central Asia, but the conflict of interest over water resources among the countries and the dry climate remains similar. Recently the construction of the Great Ethiopian Reconnaissance Dam, or more commonly known as GERD by the Ethiopian authorities, over the Nile has caused dispute with the neighboring Egypt and Sudan, while the case of the Nile is on a larger scale and the tendency of dispute is greater, we could use the learning outcomes and the development of the Nile DSS while developing the DSS for central Asia.

The major challenge in the Nile basin is the limited availability of water resources that are exacerbated by climate change. In addition, the rainfall average of around 700 mm/year is not evenly distributed spatially. Most rainfall in the Nile basin occurs in the upper regions, mainly around Lake Victoria and the Ethiopian Highlands. Downstream areas like Sudan and Egypt, however, get very little rain. The Blue Nile’s largest rain-contributing region is also highly seasonal, experiencing most of its rainfall during the wet season from June to September. Despite this, the Nile’s overall water yield is relatively low, with a runoff coefficient of around 4%. This means that the limited water available in the Nile basin must be fairly distributed among all the countries that rely on it [5].

Similar challenges are being faced in Central Asia, in particular between the upstream Kyrgyzstan and downstream Uzbekistan. The precipitation quantity and water usage differs between the two countries. The key water use in Kyrgyzstan is generation of hydropower while downstream Uzbekistan wants to use the water for agriculture [27].

4.3.1. Decision-Making Process of NB DSS

Eight thematic focus areas that the riparian states agree upon were chosen for which the DSS will provide support for decision-making. They ranged from water resources development to flood and drought management [5]. Various alternatives, known as scenarios, were used to evaluate the decisions against a set of defined criteria ranging from climate change to socio-economics.

The alternatives are formed through the so called “Scenario Manager”, that utilizes pre-established setup of models, providing the user multiple versions of the system, known as alternatives. These alternatives are formed by the changes made in the parameters or input data. Once the scenarios are identified, they are evaluated through Multi Criteria Analysis (MCA), each scenario is tested against a set of criteria in favor of stakeholders. A weighting scheme can be used to evaluate the scenarios [5].

4.3.2. Benefits and Challenges of NB DSS

The NB DSS is a comprehensive DSS with more than a decade of usage since its release in 2012. The experiences and challenges faced during its development can be a used when developing a new DSS in a different region of the world and the mistakes can be avoided. One of the positive aspects of the NB DSS is the flexibility of its User Interface (UI), other than the independent modelling tools, all the other tools would be accessed through one homogeneous interface which makes it easy to use.

Another positive aspect of the NB DSS is that its development was done in three stages, where at the end of each stage a version was released to be tested. This allowed for any potential discrepancies to go not go unnoticed and make sure the design was up to the expectation of the user. In addition to the intricate design phase, extensive trainings were provided to the members of each member country of Nile Basin Initiative (NBI) and a team of 40 experts from the member states were chosen to help with the development and design of the DSS.

The NB DSS provides a common platform for analysis and exchange of information and has been a stepping stone towards cooperation among the Nile Basin countries; however, a tool alone can never be sufficient, and there is a need for strong political support and willingness to cooperate. According to Jonoski (2016) [5], lack of data and huge price tag for developing such a versatile tool are the main challenges when it comes to such systems. In addition, due to lack of internet access in some of the regions, the DSS is desktop based which makes it limited in useability. Finally, the licensing of the expenses for MIKE family modelling tools were high which led to limited users, this was resolved by adding plugins to WEAP and SWAT to complement the MIKE modelling tools. It must be noted that NBI is constantly working towards the betterment of the NB DSS and making the UI more friendly.

5. Challenges and Recommendations for Leveraging DSSs for Transboundary Water Allocation in Central Asia

Decision Support Systems (DSSs) emerge as a pivotal tool in navigating the complexity of transboundary water management. The current landscape in Central Asia, marked by sporadic unilateral decisions and bilateral and multilateral negations and agreements, underscores the urgency for a comprehensive, data-driven and evidence-based approach to water allocation. DSSs offer the potential to integrate diverse data sources, predictive analytics, and stakeholder inputs into a cohesive framework, fostering a more collaborative and equitable water management paradigm.

5.1. Challenges for Leveraging DSSs in Central Asia

However, implementing DSSs for transboundary water allocation in Central Asia faces significant hurdles: These include limited technological infrastructure, a dearth of reliable data, limited capacity and resistance to change from entrenched institutional structures. Moreover, the intricate socio-political situation of the region, the uncertainties introduced by climate change, and the cross-sector, cross-border nature of water allocation with its intertwined socioeconomic and ecological implications, further add layers of complexity to the adoption of such systems.

i.

Data Scarcity & Restrictions: The scarcity of hydrometeorological and water quality stations and restricted data sharing pose significant challenges to the effective implementation of DSSs in Central Asia. The decreasing number of hydrometeorological stations in recent decades has increased uncertainty in impact assessments and made model validation more difficult [28]. The region has very few available high-resolution and high-quality hydrometeorological datasets, and their quantity and quality decrease with elevation [29]. Many stations still rely on manual monitoring, leading to data scarcity and inconsistencies. Although the hydrometeorological services in Central Asia have established data exchange mechanisms, these are limited to certain stations and are not openly accessible to the public. These limitations hinder the effectiveness of DSSs, which rely on accurate and comprehensive data inputs to generate meaningful insights.

ii.

Institutional Resistance and Capacity Barriers: Resistance to change from entrenched institutional structures and established working methods poses another challenge. Many institutions are accustomed to traditional methods of water management and may lack the capacity or willingness to adopt new technologies. For example, the overall acceptance of novel runoff forecasting models and digital technologies—which are crucial for water allocation management—remains low. More broadly, the region lacks sufficient professional expertise and training systems in areas such as data processing, model application, scenario design and analysis and DSS operation, posing a significant constraint on the long-term success of DSSs. In addition, the effective promotion and operation of DSSs require not only the technical systems themselves but also robust institutional support, including clear policies, legal frameworks, and regulatory bodies to facilitate data sharing, enforce water management agreements, and facilitate conflict resolution.

iii.

Funding Shortages and Sustainability Concerns: One of the most significant barriers to the implementation of DSSs for transboundary water management in Central Asia is the chronic shortage of funding. The development, deployment, and maintenance of sophisticated DSSs require substantial and ongoing financial investments. However, many countries in the region have limited economic capacity and cannot easily bear the high costs of construction and operation. Moreover, the rapid pace of technological change means that even with sufficient initial investment, long-term and stable funding is needed to support system upgrades and maintenance. Uncertainty in the policy environment further heightens sustainability risks, leading to situations where systems that have been built may gradually become obsolete without continued support, failing to deliver the intended long-term benefits.

iv.

Socio-Political Complexities: The intricate socio-political situation of the region, marked by historical rivalries and distrust, adds layers of complexity to the adoption of DSSs. The legacy of Soviet-era water distribution still significantly influences the region’s water governance, complicating the transition to independent and cooperative water management. Geopolitical tensions, particularly between upstream and downstream countries, exacerbate these challenges, making consensus-building difficult. While a DSS can facilitate data input and modeling presentation, the willingness to cooperate among countries is paramount. A key characteristic of a successful DSS is to foster trust and commitment to the system. Ideally, the DSS for water allocation needs to be jointly acknowledged by the riparian countries.

v.

Climate Change Impacts: Climate change further complicates water management in Central Asia. The impacts on glacial and snow melt in the Tian Shan Mountain range will drastically affect the flow of the Syr Darya, with an increased river runoff expected in the short term due to rapid glacier melt, followed by a reduction in river runoff in the long term. The increase in water availability in the short term might sound promising but it is due to rapid meltwater from glaciers in the high mountain ranges of Kyrgyzstan. According to Kalashnikova et al. (2023), the area of glaciation in Kyrgyzstan has reduced by 16% for large glaciers and 17% for small glaciers, exacerbating water stress [11]. This is quite concerning as the Kyrgyz republic acts as the water tower in the region that is already experiencing water stress. It is of utmost importance now more than ever to discuss these issues and be prepared for the upcoming future. Moreover, Rai et al. (2024) reported that both extreme dry and wet precipitation events are projected to increase and intensified in most areas in Central Asia [30]. Considering these predictive variability holds significant strategic importance for future water resource management and adaptive management strategies, up-to-date water allocation strategies considering climate change impacts and climate-sensitive DSSs are urgently needed. Moreover, the impacts of climate change are always fraught with uncertainty, and how to communicate this uncertainty to decision-makers through DSSs poses an even greater challenge.

vi.

The Challenge of Describing Complex System: Ultimately, it is difficult for the complexity of the real system of transboundary water allocation to be fully reflected in a DSS. Beyond the political factors and climate change impacts previously discussed, numerous other factors influence the boundary conditions of transboundary water allocation. These include cross-sectoral interactions—such as those between water, energy, food, and ecosystems (WEFE nexus), economic impacts, market and price, end-user behaviour, etc. Incorporating all these elements into one model system is highly challenging, often requiring the integration of advanced tools like hydroeconomic models and water-food-energy-ecosystem nexus systematic models, cost–benefit analysis. As a result, the models could become exceptionally intricate and resource-intensive. It is important to note that this challenge is not unique to Central Asia. They are equally relevant to transboundary water allocation efforts in other regions, highlighting the universal complexity of managing shared water resources in a dynamic and interconnected world.

5.2. Recommendations for DSS Development

To address these challenges, several recommendations are proposed:

i.

Improve Data Availability and Enhance Data Sharing: To address data scarcity and improve monitoring capabilities, it is essential to invest in automated stations by upgrading existing hydrometeorological and water quality monitoring systems to reduce reliance on manual processes and enhance data consistency. Additionally, increasing station density, particularly in underrepresented areas such as high-elevation regions, will improve data coverage and resolution. Complementing ground-based monitoring with satellite-based remote sensing and Internet of Things (IoT) technologies and developing AI-based approaches can help fill data gaps and address data limitations [31,32,33].

While respecting data sovereignty, it is essential to promote data exchange and sharing. The issue of protecting sensitive data while enabling the sharing of non-sensitive data can be addressed by enhancing database technologies, such as through decentralized data storage structures. In this approach, each country’s data is stored on servers physically located within its own territory, ensuring local storage while facilitating necessary data exchange through secure connections. Within the DSS database, data can be classified into different levels of access. For example, some data may be restricted to the country of origin, while other data may be shared within transboundary water management institutions, with additional levels of access as needed.

For effective water allocation, integrating data from hydrometeorological monitoring stations, water quality monitoring stations, agricultural irrigation systems, major canal monitoring, and end-user water consumption is crucial. For operational water allocation within a DSS, short- to medium-term water flow forecasts play a key role. For example, the river flow forecasting system developed under the SAPHARIRE project serves as an excellent example. By implementing DSSs, countries can witness the tangible benefits of data utilization, which can further encourage and promote data sharing.

ii.

Stakeholder Engagement and Interactive Design: Incorporating the perspectives and expertise of local stakeholders and specialists in Central Asia is crucial for creating any new DSS tool. Effective implementation of a DSS in the Upper Syr Darya Basin requires structured and inclusive stakeholder involvement that extends beyond high-level decision-makers to encompass regional authorities, basin organizations, technical staff, and water users such as farmers.

The development team of the DSS must immerse themselves in the regional context to understand the intricacies of water allocation at various levels. Local engagement can be strengthened through a tiered participation mechanism, including understanding the total water allocation quotas at the transboundary level, the management of large dams, barrages and main canals at the regional level, the operation of local irrigation infrastructures, and the practices of farmers in utilizing water resources. Serious games can serve as an effective participatory tool to facilitate this process, allowing cross-border stakeholders to simulate water management scenarios and collaboratively explore solutions [34]. Embedding these mechanisms within existing institutions (e.g., basin organizations, WUAs, district water departments) ensures that the DSS tool is attuned to the present and future water challenges and aids in formulating effective water management strategies for the Upper Syr Darya Basin.

Specifically, the development of the DSS can begin with a questionnaire for each stakeholder. Through this questionnaire, one could identify the key thematic focus of the DSS, medium of interaction, main stakeholders and potential DSS end-users, the types of data available, the types of decisions it can support, and the types of output that is generated to support the decisions. Next, a more detailed and tailored questionaries could be done for the selected main end-users of the DSS to understand their needs.

After the investigation of end-users’ needs and decision processes, the development of a new DSS in Central Asia should adopt a multi-stage approach, ensuring that the system evolves in line with end-users’ feedback and expectations. By releasing and testing versions at the end of each development phase, potential issues can be addressed promptly, ensuring that the final product meets the specific needs of the region. Furthermore, by conducting extensive training sessions and forming a specialized team of experts from within the region, the DSS can incorporate a wide range of perspectives and expertise, enhancing its relevance and effectiveness. This inclusive approach not only fosters collaboration among Central Asian countries but also ensures that the DSS is designed with a deep understanding of the region’s unique challenges and opportunities.

In addition, adopting open-source models and modular, scalable system designs can help reduce future development and maintenance costs, ensuring that the DSS remains adaptable to technological and policy changes.

iii.

Strengthen International Cooperation and Capacity Building: Central Asian countries are low income and the process of building the necessary infrastructure and talent for a transboundary water allocation DSS is a tedious and expensive endeavor. Seeking funding from international organizations, such as the World Bank, Asian Development Bank, and United Nations, can provide the necessary financial support. Forming partnerships with technologically advanced countries and institutions can also bring in expertise and funding. The support of countries such as from European Union is vital in making such efforts possible. For example, the Water Efficient Allocation in a Central Asian Transboundary River Basin (WE-ACT) project funded by the Horizon Europe program aims to develop a climate-sensitive water allocation decision support system in the upper Syr Darya basin. These initiatives are iterative and recursive nature, meaning they continuously evolve and adapt in response to fresh insights gained throughout the project’s lifespan.

In addition to seeking funding and support from external international organizations, it is imperative to enhance cross-border water resource cooperation among Central Asian nations. This involves the establishment of clear policies, robust legal frameworks, and regulatory bodies that encourage data sharing, enforce water management agreements, and facilitate conflict resolution. DSSs can provide crucial information for cross-border water allocation decisions, thereby improving transparency and fostering mutual trust among nations. This, in turn, will enable them to collaboratively make informed and appropriate decisions regarding water resource distribution.

Enhancing the capacity of regional institutions is fundamental for effective DSS operation and utilisation. This enhancement is not limited to infrastructural development but also extends to the improvement of human capital, necessitating training and the exchange of knowledge. Capacity building should encompass all facets of water allocation DSSs, including data management, data analysis, model development, interpretation of model outcomes, scenario configuration, scenario analysis, decision optimization, and DSS interface navigation. A clear understanding of the capabilities and limitations of DSSs is immensely beneficial for end users. Investing in local capacity building through training programs, workshops, and educational initiatives ensures that there is a skilled workforce to manage and sustain DSSs. Knowledge transfer from international experts to local professionals is crucial.

iv.

Climate-informed DSSs & Coping with Uncertainty: Climate change is a key driver of recent and ongoing allocation reforms [2]. Given its significant impact on water resources, Central Asian countries have shown willingness to integrate climate adaptation strategies into their water management policies. However, many existing DSSs for water allocation do not incorporate climate change scenarios, particularly operational DSSs that lack a strategic focus. Research highlights the need to revise current water allocation protocols, as they often overlook the impacts of climate change and fail to ensure equitable resource distribution. To address these challenges, it is critical to develop climate-informed and climate-smart strategic DSSs that directly address end-user pain points.

Climate models inherently carry uncertainties. When developing water allocation strategies under climate change, integrating multiple model and scenarios (e.g., best-case, worst-case, and intermediate scenarios) can provide decision-makers with a clearer understanding of potential ranges of potential futures. Furthermore, preparing for extreme climate scenarios—such as intense precipitation events or prolonged droughts—requires the establishment of specific frameworks to manage these situations effectively. Impact models should also undergo iterative validation to ensure reliability. The precautionary principle should be followed to develop management scenarios to cope with un-certainty in impact assessments.

Given the inevitability of uncertainty, it is essential to design tools, such as confidence intervals, probability distributions, or scenario-based visualizations, that effectively communicate this uncertainty to decision-makers and chart adaptive pathways toward alternative futures in the DSS. Such tools should be designed with understanding decision-makers’ capacity and preferences for managing uncertainty and risk. This enables them to make informed decisions while understanding the limitations and variability of the models.

v.

Water-Food-Energy Nexus and Benefit-Sharing Approaches: The WEFE Nexus framework offers a holistic approach particularly suited to Central Asia’s transboundary river basins, where water allocations directly govern energy production in upstream hydropower states and irrigated agriculture in downstream nations. By integrating WEFE nexus models into DSSs, decision-makers can better quantify sectoral trade-offs—such as how winter hydropower releases from Toktogul Reservoir affect summer irrigation in the Fergana Valley—while identifying synergies for improved regional cooperation.

However, the integration of WEFE nexus models often increases the complexity and resource requirements of DSSs. To mitigate this, benefit-sharing methods, e.g., valuing water approaches can be employed to prioritize modeling efforts and ensure that the DSS remains practical and actionable. Benefit-sharing approaches focus on identifying and distributing the mutual gains from cooperative water management, rather than solely allocating water volumes. By incorporating benefit-sharing principles into DSSs, stakeholders can explore scenarios that maximize collective benefits—such as increased agricultural productivity, enhanced energy security, or improved ecosystem services—while minimizing conflicts.

For instance, a DSS could use valuing water approach to assess the full spectrum of benefits generated by investments in water-efficient irrigation technologies, including both direct economic returns and ecosystem service enhancements. This valuation then informs benefit-sharing arrangements that distribute gains equitably between upstream and downstream users. Such an approach not only fosters cooperation but also reduces the need for highly detailed models by focusing on value creation and distribution. While not eliminating all complexities, this value-based approach

While these approaches cannot fully eliminate the complexity of transboundary water systems, they provide a practical pathway for addressing post-Soviet allocation disputes by shifting focus from rigid water quotas to multi-sector benefit optimization, risk-sharing for climate-variable flows and equitable cost–benefit distribution. By combining WEFE nexus modeling with benefit-sharing principles, DSSs can better support decision-making in a dynamic and interconnected world, ultimately promoting sustainable and equitable water allocation.

In summary, Figure 2 presents a conceptual framework for a climate-sensitive Decision Support System (DSS) tailored to the Syr Darya Basin. The diagram illustrates how multiple data streams—including hydrometeorological observations, satellite products, IoT-based monitoring, and water-demand information—feed into modelling components that support scenario analysis and multi-objective optimization. These models integrate both climate and socio-economic scenarios, as well as management and policy options, to evaluate alternative allocation pathways under changing conditions. The resulting outputs are visualized through a DSS dashboard that enables shared information, scenario comparison, and trade-off assessment. Finally, stakeholder engagement and co-design ensure that DSS outputs translate into transparent, cooperative, and basin-specific decision-making, supporting more effective water allocation between Kyrgyzstan and Uzbekistan.

6. Conclusions

Decision Support Systems have evolved into platforms that encourage stakeholder engagement, promoting transparent and informed decision-making through holistic modeling. These systems utilize multiple integrated models, detailed for physical processes and broader for human interventions, to create a comprehensive view of the natural–human system, facilitating information transfer and model refinement. This approach underpins participatory planning, fostering a collective understanding of the system and facilitating the creation of future scenarios and management strategies. It emphasizes the significance of human capital and continual learning for long-term problem-solving and sustainability, particularly in the face of the uncertainties posed by rapid environmental and economic changes and the effects of climate change. To effectively implement adaptive management, it is crucial to integrate system monitoring, modeling, stakeholder participation, and decision-making within existing institutional frameworks, aiming for a balance of understanding, economic viability, social fairness, and environmental sustainability.

Active pursuit of integrating Decision Support Systems (DSSs) in water management by Central Asian countries is also crucial. This requires substantial investments in Information and Communication Technology (ICT) infrastructure, data collection, monitoring systems, and the development of human expertise in data analytics and system operations. Engaging various stakeholders is equally vital. Adopting a participatory approach that includes local communities, non-governmental organizations, and international partners is essential. The contributions of these diverse groups can offer valuable insights into the local context, ensuring the DSS is effectively tailored to meet the socio-economic realities of the region.

In conclusion, addressing the multifaceted water management challenges in Central Asia demands a comprehensive approach. By harnessing technology through DSSs, reinforcing regional cooperation, and fostering institutional capacity building, Central Asian countries are well-positioned to forge a path toward a more stable, prosperous, and water-secure future.