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Reproducibility is a foundational principle in scientific research. Yet in computational hydrology the code and data that actually produces published results are not regularly made available, inhibiting the ability of the community to reproduce and verify previous findings. In order to overcome this problem we recommend that reuseable code and formal workflows, which unambiguously reproduce published scientific results, are made available for the community alongside data, so that we can verify previous findings, and build directly from previous work. In cases where reproducing large-scale hydrologic studies is computationally very expensive and time-consuming, new processes are required to ensure scientific rigor. Such changes will strongly improve the transparency of hydrological research, and thus provide a more credible foundation for scientific advancement and policy support.

We present an overview of the contributions collected to celebrate the fiftieth anniversary of Water Resources Research along with a critical discussion of the legacy and perspectives for the science of hydrology in the 21st century. This collection of papers highlights exciting pathways to the future of water sciences. New monitoring and modeling techniques and increasing opportunities for data and knowledge sharing from hydrological research will provide innovative means to improve water management and to ensure a sustainable development to society. We believe that this set of papers will provide valuable inspiration for future hydrologists, and will support the intensification of international cooperation among scientists.

Hydrology is an integrative discipline linking the broad array of water-related research with physical, ecological, and social sciences. The increasing breadth of hydrological research, often where subdisciplines of hydrology partner with related sciences, reflects the central importance of water to environmental science, while highlighting the fractured nature of the discipline itself. This lack of coordination among hydrologic subdisciplines has hindered the development of hydrologic theory and integrated models capable of predicting hydrologic partitioning across time and space. The recent development of the concept of the critical zone (CZ), an open system extending from the top of the canopy to the base of groundwater, brings together multiple hydrological subdisciplines with related physical and ecological sciences. Observations obtained by CZ researchers provide a diverse range of complementary process and structural data to evaluate both conceptual and numerical models. Consequently, a cross-site focus on “critical zone hydrology” has potential to advance the discipline of hydrology and to facilitate the transition of CZ observatories into a research network with immediate societal relevance. Here we review recent work in catchment hydrology and hydrochemistry, hydrogeology, and ecohydrology that highlights a common knowledge gap in how precipitation is partitioned in the critical zone: “how is the amount, routing, and residence time of water in the subsurface related to the biogeophysical structure of the CZ?” Addressing this question will require coordination among hydrologic subdisciplines and interfacing sciences, and catalyze rapid progress in understanding current CZ structure and predicting how climate and land cover changes will affect hydrologic partitioning. This article is protected by copyright. All rights reserved.

Socio-hydrology views human activities as endogenous to water system dynamics; it is the interaction between human and biophysical processes that threatens the viability of current water systems through positive feedbacks and unintended consequences. Di Baldassarre et al. implement socio-hydrology as a flood risk problem using the concept of social memory as a vehicle to link human perceptions to flood damage. Their mathematical model has heuristic value in comparing potential flood damages in green versus technological societies. It can also support communities in exploring the potential consequences of policy decisions and evaluating critical policy tradeoffs, for example, between flood protection and economic development. The concept of social memory does not, however, adequately capture the social processes whereby public perceptions are translated into policy action, including the pivotal role played by the media in intensifying or attenuating perceived flood risk, the success of policy entrepreneurs in keeping flood hazard on the public agenda during short windows of opportunity for policy action, and different societal approaches to managing flood risk that derive from cultural values and economic interests. We endorse the value of seeking to capture these dynamics in a simplified conceptual framework, but favor a broader conceptualization of socio-hydrology that includes a knowledge exchange component, including the way modeling insights and scientific results are communicated to floodplain managers. The social processes used to disseminate the products of socio-hydrological research are as important as the research results themselves in determining whether modeling is used for real-world decision making.

[1] From imaging spectrometer data, we simultaneously estimate the abundance of the three phases of water in an environment that includes melting snow, basing the analysis on the spectral shift in the absorption coefficient between water vapor, liquid water, and ice at 940, 980, and 1030 nm respectively. We apply a spectral fitting algorithm that measures the expressed abundance of the three phases of water to a data set acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over Mount Rainier, Washington, on 14 June 1996. Precipitable water vapor varies from 1 mm over the summit of Mount Rainier to 10 mm over the lower valleys to the northwest. Equivalent path absorption of liquid water varies from 0 to 13 mm, with the zero values over rocky areas and high-elevation snow and the high values associated with liquid water held in vegetation canopies and in melting snow. Ice abundance varies from 0 to 30 mm equivalent path absorption in the snow- and glacier-covered portions of Mount Rainier. The water and ice abundances are related to the amount of liquid water and the sizes of the ice grains in the near-surface layer. Precision of the estimates, calculated over locally homogeneous areas, indicates an uncertainty of better than 1.5% for all three phases, except for liquid water in vegetation, where an optimally homogeneous site was not found. The analysis supports new strategies for hydrological research and applications as imaging spectrometers become more available.

[1] The dialog between experimentalist and modeler in catchment hydrology has been minimal to date. The experimentalist often has a highly detailed yet highly qualitative understanding of dominant runoff processes; thus there is often much more information content on the catchment than we use for calibration of a model. While modelers often appreciate the need for “hard data” for the model calibration process, there has been little thought given to how modelers might access this “soft” or process knowledge. We present a new method where soft data (i.e., qualitative knowledge from the experimentalist that cannot be used directly as exact numbers) are made useful through fuzzy measures of model simulation and parameter value acceptability. We developed a three-box lumped conceptual model for the Maimai catchment in New Zealand, a particularly well-studied process-hydrological research catchment. The boxes represent the key hydrological reservoirs that are known to have distinct groundwater dynamics, isotopic composition, and solute chemistry. The model was calibrated against hard data (runoff and groundwater levels) as well as a number of criteria derived from the soft data (e.g., percent new water, reservoir volume, etc.). We achieved very good fits for the three-box model when optimizing the parameter values with only runoff (Reff = 0.93). However, parameter sets obtained in this way showed in general a poor goodness of fit for other criteria such as the simulated new water contributions to peak runoff. Inclusion of soft data criteria in the model calibration process resulted in lower Reff values (around 0.84 when including all criteria) but led to better overall performance, as interpreted by the experimentalist's view of catchment runoff dynamics. The model performance with respect to soft data (like, for instance, the new water ratio) increased significantly, and parameter uncertainty was reduced by 60% on average with the introduction of the soft data multicriteria calibration. We argue that accepting lower model efficiencies for runoff is “worth it” if one can develop a more “real” model of catchment behavior. The use of soft data is an approach to formalize this exchange between experimentalist and modeler and to more fully utilize the information content from experimental catchments.

Socio‐hydrology advanced the field of hydrology by considering humans and their activities as part of the water cycle, rather than as external drivers. Models are used to infer reproducible trends in human interactions with water resources. However, defining and handling water problems in this way may restrict the scope of such modeling approaches. We propose an interdisciplinary socio‐hydrological approach to overcome this limit and complement modeling approaches. It starts from concrete field‐based situations, combines disciplinary as well as local knowledge on water‐society relationships, with the aim of broadening the hydro‐centric analysis and modeling of water systems. The paper argues that an analysis of social dynamics linked to water is highly complementary to traditional hydrological tools but requires a negotiated and contextualized interdisciplinary approach to the representation and analysis of socio‐hydro systems. This reflection emerged from experience gained in the field where a water‐budget modeling framework failed to adequately incorporate the multiplicity of (non‐hydrological) factors that determine the volumes of withdrawals for irrigation. The pathway subsequently explored was to move away from the hydrologic view of the phenomena and, in collaboration with social scientists, to produce a shared conceptualization of a coupled human‐water system through a negotiated approach. This approach changed the way hydrological research issues were addressed and limited the number of strong assumptions needed for simplification in modeling. The proposed socio‐hydrological approach led to a deeper understanding of the mechanisms behind local water‐related problems and to debates on the interactions between social and political decisions and the dynamics of these problems.