Observation to Openness: Governing Hydrological Data in a Non-Stationary World

Bhanu R. Neupane; Dhiraj Pradhananga

doi:10.55630/dipp.2026.16.5

Authors

Bhanu R. Neupane UNESCO World Water Assessment Programme (WWAP), 7 Place de Fontenoy, 75352 Paris 07 SP, France
Dhiraj Pradhananga UNESCO Chair in Mountain Cryosphere and Water, Department of Meteorology, Tri-Chandra Multiple Campus, Tribhuvan University, Ghantaghar, 44600 Kathmandu, Nepal , The Small Earth Nepal (SEN), 626 Bhakti Thapa Sadak, Thapagaon, New Baneshwor, 44600 Kathmandu, Nepal

DOI:

https://doi.org/10.55630/dipp.2026.16.5

Keywords:

Anthropocene, Environmental Data, Open Data, Hydrological Data Governance, FAIR, Interoperability, Non-stationarity, Water Security, Metadata, Digital Public Infrastructure

Abstract

The movement from observation to openness has become a defining challenge in environmental sciences. This challenge is particularly acute for hydrological governance in a non-stationary world. The assumptions underpinning water management, planning, and infrastructure design have been increasingly challenged by climatic variability, land-use change, and urbanization. These pressures have increased both the volume of environmental data produced and the strategic importance of governing that data effectively. However, hydrological data systems remain dispersed across institutions, scales, and jurisdictions. This paper argues that the transition from observation to openness is no longer a secondary technical reform but a core condition for water security, scientific reproducibility, risk governance, and equitable adaptation. Using a systems lens, it examines the full hydrological observation and data lifecycle and shows how bottlenecks at any stage can undermine decision-making. The paper then interrogates the quality-versus-quantity debate under conditions of non-stationarity, uncertainty, and the abundance of multi-source data, emphasizing that openness without metadata, standards, and accountability can reproduce rather than address epistemic weaknesses. A new governance paradigm is proposed, anchored in FAIR data principles, interoperability, public-value logic, and the doctrine of openness, as open as possible, and as closed as necessary. Particular attention is given to transboundary hydrology, data sovereignty, institutional asymmetries, and the growing need for trusted cross-border data flows. The paper concludes with a layered policy agenda for Member States, distinguishing what should, might, or can be done. Its central claim is that, in a non-stationary world, hydrological observation achieves full public value only when it is embedded in a culture of governed openness.

References

Addor, N., Newman, A. J., Mizukami, N., & Clark, M. P. (2017). The CAMELS data set: Catchment attributes and meteorology for large-sample studies. Hydrology and Earth System Sciences, 21, 5293–5313. https://doi.org/10.5194/hess-21-5293-2017

Antarikchya. (n.d.). Hydro web portal—Antarikchya. Retrieved April 13, 2026, from https://hydro.antarikchya.org.np/

Bäthge, A., Vargas, C. R., Lischeid, G., Collenteur, R., Cuthbert, M., Fleckenstein, J., Flörke, M., de Graaf, I., Gnann, S., Hartmann, A., Huggins, X., Moosdorf, N., Wada, Y., Wagener, T., & Reinecke, R. (2026). A global-scale time series dataset for groundwater studies within the Earth system. Scientific Data, 13, Article 401. https://doi.org/10.1038/s41597-026-06966-1

Beven, K. J. (2012). Rainfall-runoff modelling: The primer (2nd ed.). Wiley-Blackwell. https://doi.org/10.1002/9781119951001

Blöschl, G., Hall, J., Viglione, A., et al. (2019). Changing climate both increases and decreases European river floods. Nature, 573, 108–111. https://doi.org/10.1038/s41586-019-1495-6

Clark, M. P., et al. (2015a). A unified approach for process-based hydrologic modeling: 1. Modeling concept. Water Resources Research, 51(4), 2498–2514. https://doi.org/10.1002/2015WR017198

Clark, M. P., et al. (2015b). A unified approach for process-based hydrologic modeling: 2. Model implementation and case studies. Water Resources Research, 51(4), 2515–2542. https://doi.org/10.1002/2015WR017200

Crutzen, P. J. (2006). The Anthropocene. In E. Ehlers & T. Krafft (Eds.), Earth system science in the Anthropocene (pp. 13–18). Springer. https://doi.org/10.1007/3-540-26590-2_3

Crystal-Ornelas, R., et al. (2022). Enabling FAIR data in Earth and environmental science with community-centric (meta)data reporting formats. Scientific Data, 9, Article 700. https://doi.org/10.1038/s41597-022-01606-w

GEO. (2022). Revised GEO data sharing and data management principles. Retrieved April 13, 2026, from https://old.earthobservations.org/documents/open_eo_data/PB-23-12_Revised%20GEO%20Data%20Sharing%20and%20Data%20Management%20Principles.pdf

Guzha, A. C., Rufino, M. C., Okoth, S., Jacobs, S., & Nóbrega, R. L. B. (2018). Impacts of land use and land cover change on surface runoff, discharge and low flows: Evidence from East Africa. Journal of Hydrology: Regional Studies, 15, 49–67. https://doi.org/10.1016/j.ejrh.2017.11.005

Hannah, D.M., Demuth, S., van Lanen, H.A.J., Looser, U., Prudhomme, C., Rees, G., Stahl, K., & Tallaksen, L.M. (2011). Large-scale river flow archives: Importance, current status and future needs. Hydrological Processes, 25(7), 1191–1200. https://doi.org/10.1002/hyp.7794

Intergovernmental Panel on Climate Change (IPCC). (2021). Climate change 2021: The physical science basis. Cambridge University Press. https://doi.org/10.1017/9781009157896

Intergovernmental Panel on Climate Change (IPCC). (2023). Summary for policymakers. In Climate change 2023: Synthesis report (pp. 1–34). https://doi.org/10.59327/IPCC/AR6-9789291691647.001

Janssen, M., Charalabidis, Y., & Zuiderwijk, A. (2012). Benefits, adoption barriers and myths of open data and open government. Information Systems Management, 29(4), 258–268. https://doi.org/10.1080/10580530.2012.716740

Kidd, J., Bergbusch, N. T., Epstein, G., Gunn, G., Swanson, H., & Courtenay, S. C. (2025). A fresh perspective on freshwater data management and sharing: Exploring insights from the technology sector. Water, 17(14), 2153. https://doi.org/10.3390/w17142153

Kratzert, F., Nearing, G., Addor, N., T. Erickson, Gauch, M., Gilon, O., Gudmundsson, L., Hassidim, A., Klotz, D., Nevo, S., Shalev, G., & Matias, Y. (2023). Caravan: A global community dataset for large-sample hydrology. Scientific Data, 10, Article 61. https://doi.org/10.1038/s41597-023-01975-w

Lindersson, S., Brandimarte, L., Mård, J., & Di Baldassarre, G. (2020). A review of freely accessible global datasets for floods, droughts and interactions with human societies. WIREs Water, 7(2), e1424. https://doi.org/10.1002/wat2.1424

Lippolis, A. S., Lodi, G., & Nuzzolese, A. G. (2025). The Water Health Open Knowledge Graph. Scientific Data, 12, Article 274. https://doi.org/10.1038/s41597-025-04537-4

Marhaento, H., Booij, M. J., & Hoekstra, A. Y. (2018). Hydrological response to future land-use change and climate change in a tropical catchment. Hydrological Sciences Journal, 63(9), 1368–1385. https://doi.org/10.1080/02626667.2018.1511054

Markovinović, D., Cetl, V., Šamanović, S., & Bjelotomić Oršulić, O. (2022). Availability and accessibility of hydrography and hydrogeology spatial data in Europe through INSPIRE. Water, 14(9), Article 1499. https://doi.org/10.3390/w14091499

Milly, P. C. D., Betancourt, J., Falkenmark, M., Hirsch, R. M., Kundzewicz, Z. W., Lettenmaier, D. P., & Stouffer, R. J. (2008). Stationarity is dead: Whither water management? Science, 319(5863), 573–574. https://doi.org/10.1126/science.1151915

Mons, B., Neylon, C., Velterop, J., Dumontier, M., Santos, L. O. B. da S., & Wilkinson, M. D. (2017). Cloudy, increasingly FAIR; revisiting FAIR data principles for EOSC. Information Services and Use, 37(1), 49–56. https://doi.org/10.3233/ISU-170824

Montanari, A., et al. (2013). “Panta Rhei—Everything flows”: Change in hydrology and society. Hydrological Sciences Journal, 58(6), 1256–1275. https://doi.org/10.1080/02626667.2013.809088

Nicholson, N., Shailes, S., & Mons, B. (2025). A FAIR perspective on data quality frameworks. Data, 10(9), Article 136. https://doi.org/10.3390/data10090136

Pahl-Wostl, C. (2015). Water governance in the face of global change. Springer. https://doi.org/10.1007/978-3-319-21855-7

Pradhan, N. S., Parajuli, R., & Shrestha, A. B. (2017). Reaching the most vulnerable across the border. ICIMOD.

Pradhananga, D., Smith, J., Crowe, M., Bharati, L., Aryal, K., Kayastha, D., & Manandhar, S. (2025). Filling critical data gaps in high-altitude environments of the Himalayan region. EGU General Assembly 2025. https://doi.org/10.5194/egusphere-egu25-8959

Reichstein, M., Camps-Valls, G., Stevens, B., Jung, M., Denzler, J., Carvalhais N., & Prabhat. (2019). Deep learning and process understanding for Earth system science. Nature, 566, 195–204. https://doi.org/10.1038/s41586-019-0912-1

Rodell, M., Famiglietti, J.S., Wiese, D.N, Reager, J. T., Beaudoing, H. K., Landerer, F. W., & Lo, M.-H. (2018). Emerging trends in global freshwater availability. Nature, 557, 651–659. https://doi.org/10.1038/s41586-018-0123-1

Sivapalan, M., Savenije, H. H. G., & Blöschl, G. (2012). Socio-hydrology: A new science of people and water. Hydrological Processes, 26(8), 1270–1276. https://doi.org/10.1002/hyp.8426

Tenopir, C., Allard, S., Douglass, K., Aydinoglu, A. U., Wu, L., Read, E., Manoff, M., & Frame, M. (2011). Data sharing by scientists: Practices and perceptions. PLoS ONE, 6(6), e21101. https://doi.org/10.1371/journal.pone.0021101

The Rising Nepal. (2026, March 12). HiM-DATA project to close weather data gaps in “Third Pole”. Gorkhapatra Corporation. Retrieved April 13, 2026, from https://risingnepaldaily.com/news/76765

The Small Earth Nepal. (2026, February 20). Monks and climate scientists collaborate to strengthen mountain climate monitoring. Retrieved April 13, 2026, from https://smallearth.org.np/activities/monks-and-climate-scientists-collaborate/

Tsering, K., Shrestha, M., Shakya, K., Bajracharya, B., Matin, M., Sánchez Lozano, J. L., Nelson, J., Wangchuk, T., Parajuli, B., & Bhuyan, M. A. (2021). Verification of two hydrological models for real-time flood forecasting in the Hindu Kush Himalaya (HKH) region. Natural Hazards, 110, 1821–1845. https://doi.org/10.1007/s11069-021-05014-y

UNESCO. (2021). Recommendation on open science. https://www.unesco.org/en/open-science/about

UNESCO. (2022). IHP-IX: Strategic plan of the Intergovernmental Hydrological Programme: Science for a water-secure world in a changing environment (ninth phase 2022–2029). UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000381318

UNESCO. (n.d.). The Water Information Network System (IHP-WINS). https://en.unesco.org/hydrology/ihp-wins

United Nations. (2024a). The sustainable development goals report 2024. https://unstats.un.org/sdgs/report/2024/The-Sustainable-Development-Goals-Report-2024.pdf

United Nations. (2024b). Pact for the future. https://www.un.org/pga/wp-content/uploads/sites/109/2024/09/The-Pact-for-the-Future-final.pdf

Vörösmarty, C., McIntyre, P., Gessner, M. Dudgeon, D., Prusevich, A., Green, P., Glidden, S., Bunn, S. E., Sullivan, C. A., Liermann, C. R. & Davies, P. M. (2010). Global threats to human water security and river biodiversity. Nature, 467, 555–561. https://doi.org/10.1038/nature09440

Wester, P., Mishra, A., Mukherji, A., & Shrestha, A. B. (Eds.). (2019). The Hindu Kush Himalaya assessment: Mountains, climate change, sustainability and people. Springer. https://doi.org/10.1007/978-3-319-92288-1

Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J. A., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., Bonino da Silva Santos, L., Bourne, P. E., Bouwman, J., Brookes, A. J., Clark, T., Crosas, M., Dillo, I., Dumon, O., Edmunds, S., Evelo, C. T., Finkers, R., … Mons, B. (2016). The FAIR guiding principles for scientific data management. Scientific Data, 3, Article 160018. https://doi.org/10.1038/sdata.2016.18

Wing, O.E.J., Lehman, W., Bates, P.D., Sampson, C. C., Quinn, N., Smith, A. M., Neal, J. C., Porter, J. R., & Kousky, C. (2022). Inequitable patterns of US flood risk in the Anthropocene. Nature Climate Change, 12, 156–162. https://doi.org/10.1038/s41558-021-01265-6

World Meteorological Organization (WMO). (2021). Unified policy for the international exchange of Earth system data. https://wmo.int/wmo-unified-data-policy-resolution-res1

World Meteorological Organization (WMO). (2023). WMO hydrological observing system (WHOS). https://wmo.int/activities/wmo-hydrological-observing-system-whos