In today’s intrinsically connected world, the Water–Food–Energy–Climate Nexus (WFEC Nexus) concept provides a starting point for informed and transparent decision-making based on the trade-offs and synergies between different sectors, including aquatic ecosystems, food security, energy production, and climate neutrality. The WFEC Nexus approach is particularly applicable in regions requiring transboundary water management, such as Central Asia. Unfortunately, this region with unevenly distributed water resources—consisting of Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan—is characterized by data scarcity, which limits informed decision-making. However, open-source geodata is becoming increasingly available. This paper aims to fill Central Asia’s WFEC Nexus data gap by providing an overview of key data. We collected geodata through an integrated survey of stakeholders and researchers, stakeholder consultation, and literature screening. Sixty unique datasets were identified, belonging to one of six thematic categories: (1) climate, (2) hydrology, (3) geography and topography, (4) geomorphology, (5) ecology, and (6) anthropogenic uses. For each dataset, a succinct description, including a link to the online source, is provided. We also provide possible applications of using the presented datasets, demonstrating how they can assist in conducting various studies linked to the WFEC Nexus in Central Asia and worldwide.

1. Ecohydraulic studies first appeared in the peer-reviewed literature in the late twentieth century (Figure 1a), as researchers began to face challenges and limitations in traditional hydraulic ri...

Central Asia faces increasing pressure on transboundary water, energy and food systems, particularly in the Aral Sea Basin, where hydropower, agriculture and downstream water availability are closely linked. This study applies a spatially disaggregated Water–Energy–Food (WEF) Nexus System Dynamics Model under combined climate–socioeconomic scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5) to assess hydropower development and policy pathways at basin and sub-basin scales in the Amu Darya and Syr Darya basins during 2015–2050. At basin scale, mean annual water supply remains stable across scenarios, at approximately 42 and 87 million hm³/year, respectively. Under national hydropower plans, installed capacity nearly doubles by 2050, reaching 10.45 and 10.65 GW, respectively. Food supply is more sensitive to climate–socioeconomic pathways than to hydropower expansion, with 2050 values ranging from 1120 to 1370 tonnes in the Syr Darya and 1405 to 1780 tonnes in the Amu Darya. Spatial simulations show that upstream-only development concentrates energy gains, whereas integrated basin-wide planning delivers more balanced WEF outcomes and the highest Aral Sea inflows, reaching 8.41 million hm³/year and 17,319 hm³/year, respectively. Persistent Amu Darya trade-offs underscore the need for transboundary coordination in reservoir operation, irrigation planning and downstream-flow safeguards. Spatial disaggregation reveals trade-offs concealed by basin-scale averages.

Hydropower development exerts strong pressure on river systems by fragmenting river basins, trapping sediments and creating downstream sediment starvation. These alterations severely degrade river ecosystems through losses in habitat abundance and deterioration of substrate composition. As hydropower continues to expand, there is an urgent need for informed sediment management to be included in hydropower planning. In Central Asia, where a high potential for hydropower development remains, hydromorphological data are limited, constraining the assessment of morphological processes. To address this data scarcity, this study creates for the first time a high-resolution dataset containing qualitative information on sediment transport and sediment connectivity in Central Asia. We modified a sediment connectivity model to work with openly available geospatial datasets and statistically variable input data. The simulation outputs were aggregated into spatially explicit probabilities of sediment transport, entrainment and deposition for five grain-size classes, along with connectivity indices. Comparisons with results from 2D numerical hydraulic modeling at four sites indicated an overall good agreement, although a consistent tendency toward overestimation. The resulting dataset facilitates the decision-making process in hydropower planning by informing three application domains: comparing hydropower sites, deciding on design and operational strategies, and evaluating ecological and morphological impacts. Although site-specific assessments and field data are crucial for individual hydropower projects, our dataset provides essential decision support for basin-wide hydropower development in Central Asia.