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The performance of the most frequently used flood frequency probability distributions in South Africa (Log-Normal, Log Pearson3 and Generalised Extreme Value) were reviewed and all tend to perform poorly when lower exceedance probability frequency events are estimated, especially where outliers are present in the dataset. This can be attributed to the challenge when analysing very limited 'samples' of annual flood peak populations, which are an unknown. At present outliers are inadequately 'managed' by attempting to 'normalise' the flood peak dataset, which conceals the significance of the observed data. Thus, to adequately consider the outliers, this study was undertaken with the aim to improve the current statistical approach by developing a more stable and consistent methodology to estimate flood quantiles. The approach followed in the development of the new methodology, called IPZA, might be considered as unconventional, given that a multiple regression approach was used to accommodate the strongly skewed data, which are often associated with annual flood peak series. The main advantages of IPZA are consistency, the simplicity of application (only one set of frequency factors for every parameter, regardless of the skewness), the integrated handling of outliers and the use of conventional method of moments, thereby eliminating the need to adjust any moments. The performance of IPZA exceeded initial expectations. The results are more consistent and, by taking outliers into account, appear to be more sensible than existing probability distributions. It is recommended that IPZA should be used as a valuable addition to the existing set of decision-making tools for hydrologists/engineers performing flood frequency analyses. [ABSTRACT FROM AUTHOR]

Estimating peak discharge in the catchment poses a challenge for hydrologists due to the potential overflow risks. The present study examined various methods, including Synthetic unit hydrograph, Melchior, and Rational, to determine the peak discharge value in the Lesti River Catchment Area. Accurate hydrological input data is essential for effectively estimating peak discharge and mitigating potential damage or failure. Optimized physical parameters using geographic information systems are critical in generating peak discharge values, emphasizing their importance in the estimation process. The mean absolute percentage error (MAPE) and mean average error (MAE) were used to determine the accurate method for estimating peak discharge. Analysis results showed varied peak discharge values across different methods, and it found that the MAPE values ranged from 15.15% to 7.48% and the MAE values ranged from 1.47% to 0.63%, respectively. The Nakayasu synthetic unit hydrograph obtained the minimum error measure value compared to other methods by 7.48% in MAPE and 0.63% in MAE. Therefore, the MAPE and MAE performance considered that the Nakayasu was closely approximating the observed peak discharge and a relatively accurate method for estimating peak discharge in the Lesti River catchment area. [ABSTRACT FROM AUTHOR]

Recent studies have emphasized the importance of the long-distance diffusion model in characterizing tracer transport occurring within both subsurface and surface environments, particularly in heterogeneous systems. Long-distance diffusion, often referred to as nonlocal diffusion, signifies that tracer particles may experience a considerably long distance in either the forward or backward direction along preferential channels during the transport. The classical advection–diffusion (ADE) model has been widely used to describe tracer transport; however, they often fall short in capturing the intricacies of nonlocal diffusion processes. The fractional operator has gained recognition among hydrologists due to its potential to capture distinct mechanisms of transport and storage for tracer particles exhibiting nonlocal dynamics. However, the hypersingularity of the fractional Laplacian operator presents considerable difficulties in its numerical approximation in bounded domains. This study focuses on the development and application of the fractional Laplacian-based model to characterize nonlocal tracer transport behavior, specifically considering both forward and backward diffusion processes on bounded domains. The Riesz fractional Laplacian provides a mathematical framework for describing tracer diffusion processes on a bounded domain, and a novel finite difference method (FDM) is introduced as an effective numerical solver for addressing the fractional Laplacian-based model. Applications reveal that the fractional Laplacian-based model can effectively capture the observed nonlocal tracer transport behavior in a heterogeneous system, and nonlocal tracer transport exhibits dynamic characteristics, influenced by the evolving heterogeneity of the media at various temporal scales. [ABSTRACT FROM AUTHOR]

Satellite-based rainfall estimates are a good and cost-effective alternative to low-density rain gauges because they provide information for these areas. In this study, the accuracy of seven satellite-based precipitation datasets SPDs (TRMM-3B42v7, CHIRPSv2, RFEv2, ARC2, PERSIANN-CDR, GPCPv3.1, and TAMSATv3.1) was evaluated against ground-based observations. The performance of these datasets was evaluated at daily, dekadal, and monthly time scales from 2001 to 2014 using continuous and categorical statistical indicators. The results showed that CHIRPS and TAMSAT slightly underestimate precipitation in the Sahelian and Sudano–Sahelian zones by 2.1 to 8.3%, while the other datasets overestimate by between 3.7 and 13.2%. In the Sudanian zone, they all underestimated rainfall by 1.8 to 9.4%, except for GPCP and PERSIANN-CDR, which slightly overestimated rainfall in the range of 1.7 to 4.9%. The best performance was attributed to TAMSAT on the daily scale, while GPCP showed the weakest performance. CHIRPS dataset demonstrated the most accurate estimate of ground precipitation across all zones on the dekadal time scale, whereas TAMSAT showed unsatisfactory performance. On the monthly scale, CHIRPS again exhibits strong performance in the Sahelian and Sudano–Sahelian zones, ahead of TRMM-3B42. In the southernmost area, PERSIANN-CDR consistently exhibits good agreement with ground rainfall. In contrast to the results for the Sahelian and Sudano–Sahelian zones, larger errors were found for all SPDs within the Sudanian zone. The results suggest that the TAMSAT and CHIRPS datasets appear to be a good alternative source of information to rain gauge data. Therefore, these datasets could be valuable for different stakeholders such as meteorologists, hydrologists, and agronomists in Burkina Faso and support operational applications. [ABSTRACT FROM AUTHOR]

With climate change, data on throughfall, stemflow and rainfall interception in forests are much needed by hydrologists throughout the world, including the Mediterranean region. Such data are rare for Algeria, especially for cedar forests. Thus, the present study is interested in analysis of throughfall, stemflow and rainfall interception in a cedar forest dominated by Cedrus atlantica Manetti in the province of Batna (Eastern Algeria) and establishing models for forecasting the different rainfall fractions in this forest type. Specific containers (plastic bottles and collars) were installed at stems of 30 trees, under tree crowns and in an open area not covered by tree crowns between January 2018 and December 2019 to collect the different studied fractions of water (rainfall, throughfall and stemflow). Our results reveal that throughfall was with 65.41% of the total rainfall the greatest fraction in the studied cedar forest. Stemflow represented only a very small fraction of total rainfall with 3.86%. The mean rainfall interception was 30.72 % of the total rainfall. The relationships between rainfall, throughfall and stemflow were assessed by linear regressions. We found strong correlations between throughfall, stemflow and rainfall with coefficient of determination R² ranging between 0.92 and 0.99. The equations developed by this study revealed that the studied cedar forest must receive at least 1.70 and 4.46 mm of rainfall, to trigger throughfall and stemflow, respectively. [ABSTRACT FROM AUTHOR]

Given the tradeoffs between spatial and temporal resolution, questions about resolution optimality are fundamental to the study of global snow. Answers to these questions will inform future scientific priorities and mission specifications. Heterogeneity of mountain snowpacks drives a need for daily snow cover mapping at the slope scale (≤30 m) that is unmet for a variety of scientific users, ranging from hydrologists to the military to wildlife biologists. But finer spatial resolution usually requires coarser temporal or spectral resolution. Thus, no single sensor can meet all these needs. Recently, constellations of satellites and fusion techniques have made noteworthy progress. The efficacy of two such recent advances is examined: (1) a fused MODIS–Landsat product with daily 30 m spatial resolution and (2) a harmonized Landsat 8 and Sentinel 2A and B (HLS) product with 3–4 d temporal and 30 m spatial resolution. State-of-the-art spectral unmixing techniques are applied to surface reflectance products from 1 and 2 to create snow cover and albedo maps. Then an energy balance model was run to reconstruct snow water equivalent (SWE). For validation, lidar-based Airborne Snow Observatory SWE estimates were used. Results show that reconstructed SWE forced with 30 m resolution snow cover has lower bias, a measure of basin-wide accuracy, than the baseline case using MODIS (463 m cell size) but greater mean absolute error, a measure of per-pixel accuracy. However, the differences in errors may be within uncertainties from scaling artifacts, e.g., basin boundary delineation. Other explanations are (1) the importance of daily acquisitions and (2) the limitations of downscaled forcings for reconstruction. Conclusions are as follows: (1) spectrally unmixed snow cover and snow albedo from MODIS continue to provide accurate forcings for snow models and (2) finer spatial and temporal resolution through sensor design, fusion techniques, and satellite constellations are the future for Earth observations, but existing moderate-resolution sensors still offer value. [ABSTRACT FROM AUTHOR]

Drought is one of the most complex natural hazards. Therefore, precise drought monitoring and forecasting are the biggest tasks for hydrologists and environmentalists. Under grid data structure, this paper provides a new drought index—the adaptive standardized precipitation index (ASPI), for the evolution of drought, inferring its spatio-temporal patterns and detecting trends. The methodology of the proposed index is based mainly on dynamic time warping clustering algorithm and dynamic principal components. Historical simulated precipitation data from the Australian community climate and earth-system simulator model of coupled model intercomparison project 6 of 727 grid points scattered around the Tibet Plateau has been considered. Results show that as the time scale increases, the severe and extreme drought trends have increased significantly. Further, the significant decreasing magnitude in ASPI reveals the persistence of future drought in the Tibet Plateau region. From a data mining point of view, the outcomes associated with this research recommend the endorsement of ASPI for effective and precise drought monitoring under grid data structure. [ABSTRACT FROM AUTHOR]

argued that computational hydrology can only be a proper science if the hydrological community makes sure that hydrological model studies are executed and presented in a reproducible manner. Hut, Drost and van de Giesen replied that to achieve this hydrologists should not "re-invent the water wheel" but rather use existing technology from other fields (such as containers and ESMValTool) and open interfaces (such as the Basic Model Interface, BMI) to do their computational science. With this paper and the associated release of the eWaterCycle platform and software package (available on Zenodo: 10.5281/zenodo.5119389,), we are putting our money where our mouth is and providing the hydrological community with a "FAIR by design" (FAIR meaning findable, accessible, interoperable, and reproducible) platform to do science. The eWaterCycle platform separates the experiments done on the model from the model code. In eWaterCycle, hydrological models are accessed through a common interface (BMI) in Python and run inside of software containers. In this way all models are accessed in a similar manner facilitating easy switching of models, model comparison and model coupling. Currently the following models and model suites are available through eWaterCycle: PCR-GLOBWB 2.0, wflow, Hype, LISFLOOD, MARRMoT, and WALRUS While these models are written in different programming languages they can all be run and interacted with from the Jupyter notebook environment within eWaterCycle. Furthermore, the pre-processing of input data for these models has been streamlined by making use of ESMValTool. Forcing for the models available in eWaterCycle from well-known datasets such as ERA5 can be generated with a single line of code. To illustrate the type of research that eWaterCycle facilitates, this paper includes five case studies: from a simple "hello world" where only a hydrograph is generated to a complex coupling of models in different languages. In this paper we stipulate the design choices made in building eWaterCycle and provide all the technical details to understand and work with the platform. For system administrators who want to install eWaterCycle on their infrastructure we offer a separate installation guide. For computational hydrologists that want to work with eWaterCycle we also provide a video explaining the platform from a user point of view (https://youtu.be/eE75dtIJ1lk , last access: 28 June 2022)​​​​​​​. With the eWaterCycle platform we are providing the hydrological community with a platform to conduct their research that is fully compatible with the principles of both Open Science and FAIR science. [ABSTRACT FROM AUTHOR]

Rangecroft et al. provide an important and interesting paper on the challenges of interdisciplinary research and fieldwork with participants in water resource management. The paper shows the challenges of interaction between their research areas and demonstrates the importance of how a researcher interacts with their selected study sites. My key points reflect the use of different methodologies within social and natural sciences and across them as well as the main challenge of who has the power to influence the research directions. Research is not value-free and is highly influenced by one's own training and knowledge, which needs to be addressed in the research activities. Finally, an option might be to move beyond interdisciplinary constraints and to work within a stronger transdisciplinary framework. Water research very much needs to interact with non-academic people to understand the challenges and possible solutions. [ABSTRACT FROM AUTHOR]

The Clean Water Act (CWA) is the primary federal mechanism by which the physical, chemical, and biological integrity of streams, lakes, and wetlands are protected in the United States. The CWA has evolved considerably since its initial passage in 1948, including explicit expansions and contractions of jurisdictional scope through a series of legislative actions, court decisions, and agency rules. Here, we provide a practical summary of the CWA's evolution, detailing the major updates or revisions and their circumstances. Additionally, we identify the jurisdictional scope of the law for rivers and streams, lakes, and wetlands based on the language used and implementation by the agencies during the same time period. While the rulemaking process commonly uses language that will be abstract to many hydrologists, understanding the on‐the‐ground implications, quantifying regulatory (un)certainties, and assessing the magnitude of changes through time is important to understanding the implications of environmental regulation development, litigation, and enforcement. Thus, we translate the enforcement norms and definitions into quantitative estimates for Clean Water Act scope in the Wabash River Basin (Illinois, Indiana, and Ohio, USA) as a demonstration of the spatial consequences of changing regulatory language. This article is categorized under:Engineering Water > Planning WaterHuman Water > Water GovernanceWater and Life > Conservation, Management, and Awareness [ABSTRACT FROM AUTHOR]

The purpose of the current study is to analyze the frequency of peak flood discharge with a 100- year return period in 206 Iran watersheds and to quantify it based on the most important factors. In this regard, flood frequency analysis was performed based on annual maximum discharge data and fitting of conventional continuous distributions in hydrology and fitting statistical tests. Then, for modeling, 8 parameters affecting the flood peak discharge including heavy daily rainfall, average vegetation, area, perimeter, average slope, average elevation, length of the main river, and the slope of the main river at the catchment area leading to the extraction of selected hydrometric stations. Also, the stepwise regression analysis technique was used to determine the factors affecting the production of flood peak discharge in the selected stations. The results of the study showed that the southwestern, southern, and southeastern basins of Iran with peak discharges of more than 4000 m3 /s had the highest 100-year peak discharges among the study basins. The results of the stepwise regression model indicated that five parameters of area, heavy rainfall, elevation, vegetation, and slope of the basin with an adjusted coefficient of determination of 0.72, standard error of estimation of 132.7, Akaike's information criterion of 1.62, and variance inflation factor of 0.62 had the best performance in estimating the flood peak discharge. The results of this study, considering its large spatial scale, which includes the whole of Iran, can be used as a practical guide by the hydrologists and decision-makers in estimating the 100- year flood peak discharge in ungauged watersheds based on the most important factors affecting its generations. [ABSTRACT FROM AUTHOR]

The original plotting position concept was suggested more than a century ago. Since then, many alternative plotting position approaches have been developed. Despite a general lack of agreement around which plotting position is theoretically 'correct' and the 'best' to use, all plotting positions fail to adequately address outliers and data of similar magnitude. Hydrologists generally fail to acknowledge that the plotting position primarily offers an informative display of data, against which distributions can be compared, rather than an absolute measure of probability. This paper does not intend to challenge any of the many lengthy theoretical mathematical arguments, utilised to 'prove' why one plotting position is superior to the others. These theoretical arguments may very well be valid for a 'population' of flood peaks -- the reality, however, is that hydrologists are confronted with the challenge of analysing very limited 'samples' of the population. Consequently, the plotting position issue demands a more pragmatic approach, rather than a purely theoretical approach. This paper illustrates various problems with existing plotting position techniques in use and offers an alternative approach and a more sensible plotting position technique, using Z-scores and referred to as the Z-set PP, against which distributions can be checked. The study further illustrates how effectively the Z-set PP deals with outliers and its robustness with various record lengths. Although derived from a study of flood peak data obtained from South African flow-gauging sites, it is deemed that it will be universally applicable. [ABSTRACT FROM AUTHOR]

This article examines the conflicts over knowledge, expertise, spiritual promises, and agroecological realities that collided in the construction of an early-1900s rural water conservation district in Cache Valley, Utah. Out of these tensions emerged a field-based view of conservation that oscillated between hydrologists' teachings of rational management through irrigation and local dry farming practices that seemed to acknowledge the valley's limitations-- allin a futile effort to make the land faithful to an agri-spiritual aesthetic that persuaded scientists and farmers alike to rebuild District No. 1 over and over again. From debates about whose expertise to follow to economic devastation from illicit dealings of dubious financiers and unruly environmental conditions, the saga of Cache County Water Conservation District No. 1 reveals an irrigated rural western landscape that was as unpredictable as it was inescapable. [ABSTRACT FROM AUTHOR]

The paper presents prominent Nordic contributions to stochastic methods in hydrology and water resources during the previous 50 years. The development in methods from analysis of stationary and independent hydrological events to include non-stationarity, risk analysis, big data, operational research and climate change impacts is hereby demonstrated. The paper is divided into four main sections covering flood frequency and drought analyses, assessment of rainfall extremes, stochastic approaches to water resources management and approaches to climate change and adaptation efforts. It is intended as a review paper referring to a rich selection of internationally published papers authored by Nordic hydrologists or hydrologists from abroad working in a Nordic country or in cooperation with Nordic hydrologists. Emerging trends in needs and methodologies are highlighted in the conclusions. [ABSTRACT FROM AUTHOR]

Monitoring and predicting river floods have always been of concern for hydrologists. Anomalies in flow patterns alert us of upcoming events. The effect of such anomalies on the multifractality and nonlinear dynamics of the river flow is investigated in this research. The river flow of the River Trent in England from 2018 to 2019 was dissected using the multifractal, power spectrum, and phase space reconstruction techniques. Results show a reduction in multifractality strength before the anomalies in the time series. Moreover, receding trajectories from the attractor in the phase space and augmentation of the power spectrum confirmed a decline in flow multifractality due to anomalies. A compliance comparison of multifractality reduction before anomalies in river flow leads to predicting river floods approximately 12 days in advance. Furthermore, if the multifractal strength does not return to its equilibrium, this is a warning that floods are expected in the near future (less than 10 days). [ABSTRACT FROM AUTHOR]

Rangecroft et al. (2021) offer a set of principles for conducting interdisciplinary research and fieldwork with participants from a hydrologist perspective. In this invited paper, I present some thoughts from a social scientist's perspective, not to disagree with their points but to add to them. Specifically, I use my sociology background and interdisciplinary experiences to reflect on qualitative evaluative criteria, power dynamics in the scientific community, barriers to interdisciplinary research, and approaches to overcome obstacles. Individual researchers can educate themselves about other disciplines, and there are also opportunities for institutional change on the part of universities, funders, and journals to support interdisciplinary work. I am enthusiastic about the emerging hydrology–social science collaborations I am witnessing. Indeed, I hope that more of my social science colleagues will see the unlimited potential of studying water systems with hydrologists and engineers, as I have. [ABSTRACT FROM AUTHOR]

To understand two-way linkages between water and society, achieve sustainable water management, and effectively communicate science and policy outcomes, Rangecroft et al. (2021) highlight the need for interdisciplinary collaboration between hydrologists and social scientists and outline considerations for conducting fieldwork with participants.1 In this discussion, I expand upon Rangecroft et al. (2021) to propose two contributions of qualitative social science for research about social-hydrological systems. First, qualitative social science research can help build an understanding of the lived experiences and perspectives of individuals within hydrological systems with the aim of sustainable water management. Second, drawing from a constructivist theoretical framework, qualitative social science research can highlight nuance and complexity within social-hydrological systems. In my discussion of these contributions, I provide real-world examples of effective data integration from research on the impacts of natural hazards, groundwater governance, understanding systematic vulnerabilities and adaptation to water scarcity, and sustainability science and planning. [ABSTRACT FROM AUTHOR]

The original plotting position concept was suggested more than a century ago. Since then, many alternative plotting position approaches have been developed. Despite a general lack of agreement around which plotting position is theoretically ‘correct’ and the ‘best’ to use, all plotting positions fail to adequately address outliers and data of similar magnitude. Hydrologists generally fail to acknowledge that the plotting position primarily offers an informative display of data, against which distributions can be compared, rather than an absolute measure of probability. This paper does not intend to challenge any of the many lengthy theoretical mathematical arguments, utilised to ‘prove’ why one plotting position is superior to the others. These theoretical arguments may very well be valid for a ‘population’ of flood peaks – the reality, however, is that hydrologists are confronted with the challenge of analysing very limited ‘samples’ of the population. Consequently, the plotting position issue demands a more pragmatic approach, rather than a purely theoretical approach. This paper illustrates various problems with existing plotting position techniques in use and offers an alternative approach and a more sensible plotting position technique, using Z-scores and referred to as the Z-set PP, against which distributions can be checked. The study further illustrates how effectively the Z-set PP deals with outliers and its robustness with various record lengths. Although derived from a study of flood peak data obtained from South African flow-gauging sites, it is deemed that it will be universally applicable. [ABSTRACT FROM AUTHOR]

In this reply to Thaler, we take the opportunity to explore two main aspects of his piece to continue the discussion: (1) the integration of data from the social and natural sciences, and (2) the importance of transdisciplinary research. We agree, and highlight that necessary learning, reflections and participation processes are time-intensive for researchers, practitioners and participants. We believe that these discussion pieces are important for informing, engaging, and debating challenges and practices, providing continued opportunities to learn from one another, enabling new forms of research and collaborations to flourish. [ABSTRACT FROM AUTHOR]

Estimating evapotranspiration (ET) is a primary challenge in modern hydrology. Hydrogravimetry is an integrative approach providing highly precise continuous measurement of gravity acceleration. However, large‐scale effects (e.g., tides, polar motion, atmospheric loading) limit the fine time‐scale interpretation of the gravity data and processing leads to residual signal noise. To circumvent this limitation, we exploited the difference between two superconducting gravimeters (SGs) vertically spaced by 512 m. The gravity difference allows to remove common large‐scale effects. Daily variation of the gravity difference is significantly correlated with daily evapotranspiration as estimated using the water balance model SimpKcET (p‐value = 4.10−10). However, this approach is effective only during rain‐free periods. In the future, comparison with direct ET measurements (e.g., eddy‐covariance, scintillometer) may confirm and strengthen our interpretation. Improved hydrogravimetric data processing could extend the proposed approach to other experimental sites equipped with a single SG. Plain Language Summary: Land evaporation and vegetation transpiration are crucial parameters in ecohydrology because evapotranspiration constitutes more than two‐thirds of precipitated water at the continental scale. However, this invisible flux is difficult to characterize, especially at kilometric scale, and its quantification is challenging for the hydrologist community. Continuous gravity monitoring using a superconducting gravimeter is a direct estimation of the mass change of lands with high precision. At a mountain site in southern France, we highlight a significant association between evapotranspiration calculated by a numerical model and the mass loss of the mountain. This approach provides a novel way to monitor evapotranspiration that will reinforce traditionally used methods. Key Points: For the first time, two vertically spaced gravimeters allow to interpret small gravity hydrologically induced signal (<5 nm/s²)Superconducting gravimetric signal are correlated with evapotranspiration at daily time stepGravimetry enables an integrative estimate of evapotranspiration particularly relevant for hydrology [ABSTRACT FROM AUTHOR]

Global hydrological models (GHMs) are a useful tool in the assessment of the land surface water balance. They are used to further the understanding of interactions between water balance components and their past evolution as well as potential future development under various scenarios. While GHMs have been part of the hydrologist's toolbox for several decades, the models are continuously being developed. In our study, we present the HydroPy model, a revised version of an established GHM, the Max Planck Institute for Meteorology's Hydrology Model (MPI-HM). Being rewritten in Python, the new model requires much less effort in maintenance, and due to its flexible infrastructure, new processes can be easily implemented. Besides providing a thorough documentation of the processes currently implemented in HydroPy, we demonstrate the skill of the model in simulating the land surface water balance. We find that evapotranspiration is reproduced realistically for the majority of the land surface but is underestimated in the tropics. The simulated river discharge correlates well with observations. Biases are evident for the annual accumulated discharge; however, they can – at least to some extent – be attributed to discrepancies between the meteorological model forcing data and the observations. Finally, we show that HydroPy performs very similarly to MPI-HM and thus conclude the successful transition from MPI-HM to HydroPy. [ABSTRACT FROM AUTHOR]

Continental- to global-scale hydrologic and land surface models increasingly include representations of the groundwater system. Such large-scale models are essential for examining, communicating, and understanding the dynamic interactions between the Earth system above and below the land surface as well as the opportunities and limits of groundwater resources. We argue that both large-scale and regional-scale groundwater models have utility, strengths, and limitations, so continued modeling at both scales is essential and mutually beneficial. A crucial quest is how to evaluate the realism, capabilities, and performance of large-scale groundwater models given their modeling purpose of addressing large-scale science or sustainability questions as well as limitations in data availability and commensurability. Evaluation should identify if, when, or where large-scale models achieve their purpose or where opportunities for improvements exist so that such models better achieve their purpose. We suggest that reproducing the spatiotemporal details of regional-scale models and matching local data are not relevant goals. Instead, it is important to decide on reasonable model expectations regarding when a large-scale model is performing "well enough" in the context of its specific purpose. The decision of reasonable expectations is necessarily subjective even if the evaluation criteria are quantitative. Our objective is to provide recommendations for improving the evaluation of groundwater representation in continental- to global-scale models. We describe current modeling strategies and evaluation practices, and we subsequently discuss the value of three evaluation strategies: (1) comparing model outputs with available observations of groundwater levels or other state or flux variables (observation-based evaluation), (2) comparing several models with each other with or without reference to actual observations (model-based evaluation), and (3) comparing model behavior with expert expectations of hydrologic behaviors in particular regions or at particular times (expert-based evaluation). Based on evolving practices in model evaluation as well as innovations in observations, machine learning, and expert elicitation, we argue that combining observation-, model-, and expert-based model evaluation approaches, while accounting for commensurability issues, may significantly improve the realism of groundwater representation in large-scale models, thus advancing our ability for quantification, understanding, and prediction of crucial Earth science and sustainability problems. We encourage greater community-level communication and cooperation on this quest, including among global hydrology and land surface modelers, local to regional hydrogeologists, and hydrologists focused on model development and evaluation. [ABSTRACT FROM AUTHOR]

In this reply we thank both authors for their thoughtful insights on our original opinion piece "Guiding principles for hydrologists conducting interdisciplinary research and fieldwork with participants." We believe these discussions will help to inspire and guide current and future researchers and illustrate how to continue to bring together physical and social data, experiences, and perspectives, and bridge the gap between the two disciplines with respect to socio-hydrological topics. Furthermore, we are confident that these insights and experiences will help foster a deeper understanding for hydrologists and natural scientists engaging with these discussions and research. Here we focus on two important themes that cut across both Quandt and Haeffner's replies: (1) further discussions on the importance of perceptions and lived experiences; and (2) further discussions on collaborative working and some of the major external barriers. [ABSTRACT FROM AUTHOR]

Socio-hydrology has recently garnered attention as a promising research paradigm among hydrologists. In this paper, we argue that viewing the socio-hydrological systems as a network of causal factors can assist in these efforts by revealing emergent properties of socio-hydrological systems. These factors, which are neither actors nor affiliations but symbolic representations of miscellaneous phenomena, represent the key variables affecting socio-hydrological system behaviour. Despite being crucial for understanding system dynamics, these factors are not captured by most equations of coupled human–water coevolutionary models. To demonstrate our method, we use qualitative case study research to analyse the Jaguaribe Basin in Ceará State-Brazil as a network of factors, i.e. mental conceptions, and representations of water resource management experts. We show that most results are unsurprising, exhibiting expected causal relationships. However, there was at least one unexpected result, which showed that the variable "conflict" was the single most sensitive variable to systemic evolution. [ABSTRACT FROM AUTHOR]

Continental- to global-scale hydrologic and land surface models increasingly include representations of the groundwater system. Such large-scale models are essential for examining, communicating, and understanding the dynamic interactions between the Earth System above and below the land surface as well as the opportunities and limits of groundwater resources. We argue that both large-scale and regional-scale groundwater models have utility, strengths and limitations so continued modeling at both scales is essential and mutually beneficial. A crucial quest is how to evaluate the realism, capabilities and performance of large-scale groundwater models given their modeling purpose of addressing large-scale science or sustainability questions as well as limitations in data availability and commensurability. Evaluation should identify if, when or where large-scale models achieve their purpose or where opportunities for improvements exists so that such models better achieve their purpose. We suggest that reproducing the spatio-temporal details of regional-scale models and matching local data is not a relevant goal. Instead, it is important to decide on reasonable model expectations regarding when a large scale model is performing "well enough" in the context of its specific purpose. The decision of reasonable expectations is necessarily subjective even if the evaluation criteria is quantitative. Our objective is to provide recommendations for improving the evaluation of groundwater representation in continental- to global-scale models. We describe current modeling strategies and evaluation practices, and subsequently discuss the value of three evaluation strategies: 1) comparing model outputs with available observations of groundwater levels or other state or flux variables (observation-based evaluation); 2) comparing several models with each other with or without reference to actual observations (model-based evaluation); and 3) comparing model behavior with expert expectations of hydrologic behaviors in particular regions or at particular times (expert-based evaluation). Based on evolving practices in model evaluation as well as innovations in observations, machine learning and expert elicitation, we argue that combining observation-, model-, and expert-based model evaluation approaches, while accounting for commensurability issues, may significantly improve the realism of groundwater representation in large-scale models. Thus advancing our ability for quantification, understanding, and prediction of crucial Earth science and sustainability problems. We encourage greater community-level communication and cooperation on this quest, including among global hydrology and land surface modelers, local to regional hydrogeologists, and hydrologists focused on model development and evaluation. [ABSTRACT FROM AUTHOR]

We develop a nonparametric procedure to assess the accuracy of the normality assumption for annual rainfall totals (ART), based on the marginal statistics of daily rainfall. The procedure is addressed to practitioners and hydrologists that operate in data-poor regions. To do so we use 1) goodness-of-fit metrics to conclude on the approximate convergence of the empirical distribution of annual rainfall totals to a normal shape and classify 3007 daily rainfall time series from the NOAA/NCDC Global Historical Climatology Network database, with at least 30 years of recordings, into Gaussian (G) and non-Gaussian (NG) groups; 2) logistic regression analysis to identify the statistics of daily rainfall that are most descriptive of the G/NG classification; and 3) a random-search algorithm to conclude on a set of constraints that allows classification of ART samples on the basis of the marginal statistics of daily rain rates. The analysis shows that the Anderson–Darling (AD) test statistic is the most conservative one in determining approximate Gaussianity of ART samples (followed by Cramer–Von Mises and Lilliefors's version of Kolmogorov–Smirnov) and that daily rainfall time series with fraction of wet days fwd < 0.1 and daily skewness coefficient of positive rain rates skwd > 5.92 deviate significantly from the normal shape. In addition, we find that continental climate (type D) exhibits the highest fraction of Gaussian distributed ART samples (i.e., 74.45%; AD test at α = 5% significance level), followed by warm temperate (type C; 72.80%), equatorial (type A; 68.83%), polar (type E; 62.96%), and arid (type B; 60.29%) climates. [ABSTRACT FROM AUTHOR]

Global hydrological models (GHMs) are a useful tool in the assessment of the land surface water balance. They are used to further the understanding of interactions between water balance components as well as their past evolution and potential future development under various scenarios. While GHMs are a part of the Hydrologist's toolbox since several decades, the models are continuously developed. In our study, we present the HydroPy model, a revised version of an established GHM, the Max-Planck Institute for Meteorology's Hydrology Model (MPI-HM). Being rewritten in Python, the new model requires much less effort in maintenance and due to its flexible infrastructure, new processes can be easily implemented. Besides providing a thorough documentation of the processes currently implemented in HydroPy, we demonstrate the skill of the model in simulating the land surface water balance. We find that evapotranspiration is reproduced realistically for the majority of the land surface but is underestimated in the tropics. The simulated river discharge correlates well with observations. Biases are evident for the annual accumulated discharge, however they can – at least to some part – be attributed to discrepancies between the meteorological model forcing data and the observations. Finally, we show that HydroPy performs very similar to MPI-HM and, thus, conclude the successful transition from MPI-HM to HydroPy. [ABSTRACT FROM AUTHOR]

To explore and address complex water-related issues, true collaborative, interdisciplinary research at the interface of hydrology and social science is necessary. Accordingly, hydrologists are increasingly working with social sciences and becoming involved in fieldwork with participants. With the overarching aim of facilitating collaboration and interdisciplinary water research, here we discuss important considerations and guiding principles for hydrologists, both those new to and those already familiar with interdisciplinary research, who are: (i) involved in fieldwork with participants; and (ii) working more collaboratively with social scientists. Drawing on first-hand experiences, this paper combines theory and experience from hydrologists and social scientists from their various interdisciplinary research projects to better understand key ethical, theoretical and practical considerations when working with participants. Complementary to this, we discuss the barriers and opportunities in collaborative interdisciplinary research. Facilitating these practices and understandings for hydrologists is essential to strengthen collaboration and to develop more holistic, successful research. [ABSTRACT FROM AUTHOR]

• We discuss the discomforts of hydrologists in their dialogue with society. • We propose 4 ways to better align scientific stance, research practices & discourse. • This helps to refocus research practices and engage in and with society. • Socio-hydrology allows a collective, interdisciplinary reflexive process. • This is potentially a way to integrate socio-hydrology in society. Although there is a deep historical relationship between hydrology and society, the relationship has considerably evolved in the last three decades. Hydrologists, in particular those involved in designing of decision-support tools, are experiencing a widening gap between an academic discipline which has progressively moved away from field-based applied natural science to computational hydrology, and the multiplication of stakeholders involved in the water-related issues addressed by research. The challenge for hydrology is now to negotiate this shift and to rethink its engagement in society. This paper provides a description of a planned process designed to improve hydrology-society interactions and to foster reflexivity in socio-hydrology. Based on an interdisciplinary reflexive process undertaken in Tunisia from 2016 to 2020, we identified three types of discomforts in the dialogue with society, inviting scientists to lucidly engage with these discomforts. We formulated four key reflexive propositions to achieve a better alignment of scientific stance, research practices and discourse. The first proposition concerns the need to explain more clearly the value systems scientists engage in and with society. The second concerns the need to position hydrology in society and not outside it, by reconsidering the functions that research fulfils in society. The third is an invitation to redefine the perimeter of the research interlocutors and the way to reach them. The fourth is to revisit scientific practices to build on the strengths of the dialogue between field-based natural science and computational hydrology. The paper concludes that adopting a reflexive posture towards these four dimensions of the dialogue between hydrology and society is an effective way to overcome discomforts and to refocus research stance, practices and discourse. It is a way to renew hydrology's place in society and to contribute to the current thinking in socio-hydrology initiated by hydrologists. [ABSTRACT FROM AUTHOR]

Global‐scale gradient‐based groundwater models are a new endeavor for hydrologists who wish to improve global hydrological models (GHMs). In particular, the integration of such groundwater models into GHMs improves the simulation of water flows between surface water and groundwater and of capillary rise and thus evapotranspiration. Currently, these models are not able to simulate water table depth adequately over the entire globe. Unsatisfactory model performance compared to well observations suggests that a higher spatial resolution is required to better represent the high spatial variability of land surface and groundwater elevations. In this study, we use New Zealand as a testbed and analyze the impacts of spatial resolution on the results of global groundwater models. Steady‐state hydraulic heads simulated by two versions of the global groundwater model G3M, at spatial resolutions of 5 arc‐minutes (9 km) and 30 arc‐seconds (900 m), are compared with observations from the Canterbury region. The output of three other groundwater models with different spatial resolutions is analyzed as well. Considering the spatial distribution of residuals, general patterns of unsatisfactory model performance remain at the higher resolutions, suggesting that an increase in model resolution alone does not fix problems such as the systematic overestimation of hydraulic head. We conclude that (1) a new understanding of how low‐resolution global groundwater models can be evaluated is required, and (2) merely increasing the spatial resolution of global‐scale groundwater models will not improve the simulation of the global freshwater system. Article impact statement: Global groundwater models are a new endeavor for hydrologists that face multiple challenges. [ABSTRACT FROM AUTHOR]

Luna B. Leopold was a hydrologist and fluvial geomorphologist who headed the Water Resource Division of the U.S. Geological Survey from 1957 to 1966 and was one of the leaders of the postwar quantitative revolution in geomorphology. Like other quantitative geomorphologists of his generation, he turned to numbers partly to strengthen his professional authority in policy debates, particularly those concerning a looming 'water crisis' in the United States. This paper traces the traces the evolution of Leopold's thought from the 1950s to the 1970s, when he turned from seeking universal empirical regularities in river processes to arguing that fluvial systems were inherently indeterminate and unpredictable. While this position was largely rejected by Leopold's scientific colleagues, it was embraced by members of the emerging environmental movement, for whom Leopold's stochastic understanding of rivers provided a seemingly authoritative rationale for the position that complete control and prediction of river systems would always remain out of reach. More broadly, this case shows how quantitative imprecision and uncertainty can sometimes be advantageous for experts seeking to establish authority in a contested policy domain. • Describes the work of Luna B. Leopold at the U.S. Geological Survey. • Contextualizes that work in relation to U.S. water policy in the 1950s–1970s. • Argues that Leopold initially saw quantification as a way of increasing his authority. • Shows how and why he embraced uncertainty and indeterminacy in river science. • Shows how his changing view of rivers affected his environmental advocacy. [ABSTRACT FROM AUTHOR]

In the calibration of hydrological models, evaluation criteria are explicitly and quantitatively defined as single- or multi-objective functions when utilizing automatic calibration approaches. In most previous studies, there is a general opinion that no single-objective function can represent all important characteristics of even one specific hydrological variable (e.g., streamflow). Thus hydrologists must turn to multi-objective calibration. In this study, we demonstrated that an optimized single-objective function can compromise multi-response modes (i.e., multi-objective functions) of the hydrograph, which is defined as summation of a power function of the absolute error between observed and simulated streamflow with the exponent of power function optimized for specific watersheds. The new objective function was applied to 196 model parameter estimation experiment (MOPEX) watersheds across the eastern United States using the semi-distributed Xinanjiang hydrological model. The optimized exponent value for each watershed was obtained by targeting four popular objective functions focusing on peak flows, low flows, water balance, and flashiness, respectively. Results showed that the optimized single-objective function can achieve a better hydrograph simulation compared to the traditional single-objective function Nash-Sutcliffe efficiency coefficient for most watersheds, and balance high flow part and low flow part of the hydrograph without substantial differences compared to multi-objective calibration. The proposed optimal single-objective function can be practically adopted in the hydrological modeling if the optimal exponent value could be determined a priori according to hydrological/climatic/landscape characteristics in a specific watershed. [ABSTRACT FROM AUTHOR]

The present study involves a comparative appraisal of three different sink removal algorithms. The publicly available shuttle radar topographic mission (SRTM) digital elevation model (DEM) version 3.0 of 90 m resolution was used as input DEM. Three sink filling algorithms proposed by Jennson and Domingue (JD), Planchon and Darboux (PD), and impact reduction approach by Lindsay were evaluated for their efficiency in removing the sink from SRTM DEM with minimum alteration of original DEM quality. Various primary and secondary parameters were used for comparative assessment. It was found that all the three algorithms altered the originality of the DEM significantly, but to a different extent. It was found that the PD method of sink removal was better than the other two methods studied here. However, the results also substantiated that the hydrologist must take due care to minimize any uncertainty that might arise due to DEM preprocessing. [ABSTRACT FROM AUTHOR]

Pysteps is an open-source and community-driven Python library for probabilistic precipitation nowcasting, that is, very-short-range forecasting (0–6 h). The aim of pysteps is to serve two different needs. The first is to provide a modular and well-documented framework for researchers interested in developing new methods for nowcasting and stochastic space–time simulation of precipitation. The second aim is to offer a highly configurable and easily accessible platform for practitioners ranging from weather forecasters to hydrologists. In this sense, pysteps has the potential to become an important component for integrated early warning systems for severe weather. The pysteps library supports various input/output file formats and implements several optical flow methods as well as advanced stochastic generators to produce ensemble nowcasts. In addition, it includes tools for visualizing and post-processing the nowcasts and methods for deterministic, probabilistic and neighborhood forecast verification. The pysteps library is described and its potential is demonstrated using radar composite images from Finland, Switzerland, the United States and Australia. Finally, scientific experiments are carried out to help the reader to understand the pysteps framework and sensitivity to model parameters. [ABSTRACT FROM AUTHOR]

There is an increasing need for accurate groundwater-level (GWL) prediction to support effective seasonal water management. It is desirable for forecasting tools to be not only accurate but also accessible for decision-makers. We test the Prophet forecasting procedure, an open-source code released by Facebook, to address these challenges. It is based on an additive model considering non-periodic changes and periodic components in a Bayesian framework with easily-interpretable parameters. Predictions of daily GWL data in an area affected by pumping near a tourist complex in the Ramsar wetland area of Doñana (Spain) are compared to other forecasting methods. Prophet outperforms most methods in predicting GWL making it a fast and flexible forecasting tool for hydrologists and water managers. Furthermore, it allows gaining insight into the influence of each component of the forecast separately, helping to assess the hydrodynamic response to external drivers such as groundwater pumping. [ABSTRACT FROM AUTHOR]

With increasing spatiotemporal resolution and accuracy, satellite-based precipitation estimations (SPEs) have become critical data sources for hydrological applications. Their global scale coverage and short latency perfectly fit the requirements of flood forecasting. However, the comprehensive evaluation of the latest generation of SPEs is an essential step before the confident use of these indirect precipitation estimators. Therefore, the latest releases of the Integrated MultisatellitE Retrievals for Global Precipitation Measurement (IMERG) Version 5 products, including the near-real-time "Early" run and "Later" run products (IMERG-E and IMERG-L, respectively), and the post-real-time "Final" run IMERG product (IMERG-F), are employed in this paper. Through the hydrometeorological assessment of these three IMERG products against dense gauge observations during the period from April 2014 to December 2015 over the Upper Huaihe River Basin (UHRB), the usability of IMERG products in hydrological application is explored via the Variable Infiltration Capacity model. The results indicate that, irrespective of a slight positive bias, the post-real-time IMERG-F product presents the best performance among the three IMERG products at both the grid scale and basin scale. Although all three IMERG products show remarkably high probability of detection (POD, approximately 0.82), the IMERG-E presents a relatively higher false alarm ratio (FAR = 0.37) in comparison with IMERG-L (FAR = 0.32) and IMERG-F (FAR = 0.31), which is primarily due to the significant overestimation in light rain events. In terms of hydrological simulations of streamflow, the dense gauge observations exhibit very good performance for both entire simulation period and flood events, as expected. IMERG-F demonstrates acceptable performance in entire simulation, while both IMERG-E and IMERG-L demonstrate poor performance. Given the clear overestimation in short-terms flooding and the notable underestimation in long-terms flooding, all three IMERG products should be used with caution in flood simulation over UHRB. Overall, this is a systematic assessment of IMERG products. We hope this study can provide useful guidelines for potential hydrologists of IMERG products and further IMERG algorithm development. Also, given the scope of on-going efforts to improve the IMERG products, we believe the subsequent versions of IMERG can be widely used in global or regional hydrological application, particularly in the field of flood forecasting. Unlabelled Image • The latest IMERG-E, IMERG-L, and IMERG-F are statistically and hydrologically evaluated over upper Huaihe River Basin. • IMERG-F presents the best performance, and IMERG-E demonstrate comparably statistical performance to IMERG-L. • IMERG-F demonstrates acceptable performance in daily hydrological simulation. • Both IMERG-E and IMERG-L demonstrate poor hydrological utility. • All three IMERG products should be used with caution in flood simulation over upper Huaihe River Basin. [ABSTRACT FROM AUTHOR]

Detailed analyses of hydrological data are necessary in order to examine changes in their character. This article focuses on an analysis of the average monthly discharges of 14 stage-discharge gauging stations in Slovakia. The measured period is from 1931 to 2016. The approaches used are hydrological exploration methods, which were created by hydrologists to describe the behaviour of hydrological time series. The methods are used to identify a change-point through an analysis of any residuals, Pettitt´s test, and an analysis of the relationship between the mean annual discharge deviations from the long-term annual discharge and the deviations of the average monthly discharge from the long-term average monthly discharge. A considerable number of change-points were identified in the 1970s and 1980s. The results of the analyses show changes in the hydrological regimes, but to confirm the accuracy of the outcomes, it is also necessary to examine other hydrological and meteorological elements such as, e.g., precipitation and the air temperature. [ABSTRACT FROM AUTHOR]

Traditional continuous hydrological models have a large number of free parameters whose values need to be determined through calibration, and thus their applicability is limited to gauged basins. For prediction in ungauged catchments, hydrologists generally follow regionalization methods to develop region-specific calibration-free continuous models. An alternative attempt was made recently to develop a calibration-free model by proposing an empirically derived universal 'decay function' that enables definition of instantaneous dryness index as a function of antecedent rainfall and solar energy. The model was earlier tested in the USA, and its performance was found to be comparable to that shown by regionalization-based models. Here, we test the instantaneous dryness index-based calibration-free model considering data from 108 Indian catchments. The medians of coefficient of determination (R2), Nash-Sutcliffe efficiency (NSE) and Kling-Gupta efficiency (KGE) values for the study catchments, respectively, are 0.50, 0.38 and 0.40. Furthermore, the model's performance significantly improved upon Box-Cox transformation (RBC 2, NSEBC and KGEBC, respectively, are 0.70, 0.52 and 0.57), suggesting that the model predicts discharge quite well except during flood periods. Overall, our results suggest the model can be used as an alternative platform for predicting discharge in ungauged catchments in the USA and peninsular India, if not in every part of the world. [ABSTRACT FROM AUTHOR]

• We review and discuss key concepts of Bayesian multi-model approaches. • Different modeling goals call for different treatment of conceptual uncertainty. • BMS and BMA are tailored to identify a single (quasi-) true model. • In contrast, BMC identifies the most plausible combined model. • We offer guidance to choose the most suitable method for specific modeling tasks. Model selection and model averaging have become popular tools to address conceptual uncertainty in hydro(geo)logical modeling. Within the last two decades, many different flavors of approaches and implementations have emerged which complicate an easy access to and a thorough understanding of the underlying principles. With the many approaches and applications, a variety of terms has been defined, which easily leads to misunderstandings and confusion among the community. Here, we review Bayesian model selection (BMS) and averaging (BMA) as a rigorous statistical framework for model choice under uncertainty. We aim to clarify the theoretical foundations of both methods, their relationship to one another and to alternative approaches, and implications of implementation choices. We further build a bridge to Bayesian model combination (BMC) which turns out to be Bayesian averaging or selection of combined models (BCMA/BCMS). Concluding from our theoretical review, we argue that the goal and the philosophical perspective of modeling should be main drivers when choosing to use the B(C)MS/A toolbox, and we offer guidance to identify the suitable approach for specific modeling goals. With this review, we hope to further strengthen the utility of Bayesian methods in the face of conceptual uncertainty by directing their use into the right channels. [ABSTRACT FROM AUTHOR]

Highlights • Detection of boundaries between hydrologists and hydrogeologists. • We propose approaches to overcome boundaries between the disciplines. • Approaches must respect the problems' nature instead of the discipline's 'nurture'. • Collaboration can lead to more realistic groundwater recharge pattern. • Collaboration improves simulated fluxes (surface water, groundwater and interaction). Abstract Hydrologists and hydrogeologists both study the flux and storage of water with the numerous interactions and feedback mechanisms of surface water and groundwater. Traditionally however, focus, models and scales of the studies differ. In this commentary, situations are illustrated where boundary conditions that each discipline assumes, preserves and actively uses, can and have to be overcome. These situations occur when the domain of one discipline cannot be separated from the other one because of existing interaction and feedback mechanisms at the boundaries. Highlighted are especially these boundary conditions, where closer collaboration between catchment hydrologists and hydrogeologists would be most useful. Often such collaborations would be relatively straight-forward and rather requiring an increased awareness than novel methods. [ABSTRACT FROM AUTHOR]

Highlight • Two-phase data-intelligent model is designed for multiple-horizon runoff prediction. • Integration of ELM with CEEMDAN and VMD yields hybrid (CVEE-ELM) model. • Single-phase CEE-ELM (minus VMD) and ELM model used as benchmark. • Model evaluated at 1-, 3- and 6-month lead prediction. • Hybrid two-phase model outperforms single-phase and ELM models. Abstract Expert systems adopted in real-time multi-scale runoff prediction are useful decision-making tools for hydrologists but the stochastic nature of any hydrological variable can pose significant challenges in attaining a reliable predictive model. This paper advocates a data-driven approach used to design two-phase hybrid model (i.e., CVEE-ELM). The model utilizes complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) coupled with the variational mode decomposition (VMD) algorithms for better frequency resolution of the input datasets and the extreme learning machine (ELM) algorithm as the objective predictive model. In the first stage of the presented model design, notable frequencies in the predictor-target data series are uncovered, utilizing the CEEMDAN algorithm where the model's inputs are decomposed into their respective Intrinsic Mode Functions (IMFs) and the Residual (Res) series. The second stage entails a VMD approach, used to decompose the yet-unresolved high frequencies (i.e., IMF 1) into their variational modes, further discerning and establishing the data attributes to be incorporated into the ELM model to simulate the respective IMFs, Res and VM data series, aggregated as an integrative tool for multiscale runoff prediction. In the model evaluative phase, the hybrid CVEE-ELM is cross-validated with a single-phase hybrid ELM and an autoregressive integrated moving average (ARIMA) model to benchmark its accuracy for predicting 1-, 3- and 6-month ahead runoff in Yingluoxia watershed, Northwestern China. Two-phase hybrid model exhibits superior accuracy at all lead times, to accord with high degree of correlations between the observed and the forecasted runoff, a relatively large Nash-Sutcliffe and the Legate-McCabe Index. Taylor diagrams depict the two-phase hybrid CVEE-ELM model generated forecasts located close to a reference (i.e., a perfect) model, with a lower root-mean square centered difference, and a correspondingly large correlation for all forecast horizons, although the model's accuracy for shorter lead times (1-month), as expected, are better than the 3- and 6-month horizon. The study shows that the two-phase hybrid CVEE-ELM model where an integration of two frequency resolution algorithms are made, is a preferred data-driven tool that can be explored for real-life decision-system design, particularly for hydrological forecasting problems that have significantly stochastic data features, and thus, will require reliable forecasts to be generated at multi-step horizons. [ABSTRACT FROM AUTHOR]

The Theis solution is perhaps the most influential and frequently used analytical model in groundwater hydrology. Its publication in 1935 led to immediate and continued use for simulating hydraulic head drawdown, in both confined and unconfined aquifers, as a tool in aquifer parameter estimation. For educational purposes, the Theis solution and the related Jacob's approximation often serve as the backbone for teaching pumping-well theory, including topics such as boundary conditions in aquifers, image well theory, linear superposition, and pumping-induced streamflow depletion. Clearly, a thorough understanding of the Theis solution is critical for groundwater engineers and hydrologists. However, the solution often is presented as a "black box", neglecting the actual origins of its derivation and accompanying physical context. This can lead to misconceptions about the model and its inherent limitations. In this paper, a physically based detailed derivation of the Theis solution is presented, along with a method of calculating drawdown from a pumping well without resorting to the final Theis equation. Examples of both constant-rate pumping and variable-rate pumping are presented and compared to results using the original Theis solution. In particular, variable pumping rates are accounted for by direct numerical integration of an earlier form in the original Theis derivation, removing the need for linear superposition of solutions in time. In this way, it is hoped the paper will provide a method of calculation that ties the model user to the physical meaning of the solution, including its assumptions. [ABSTRACT FROM AUTHOR]

Highlights • A model is proposed to evaluate runoff and AET of green roofs with a storage layer. • Daily ET and event runoff of green roofs decrease as ADP increases. • A storage layer enlarges the ability of green roofs to increase AET and reduce runoff. • The effects are pronounced under high temperature and rainy weather. • The effects of an additional storage layer have seasonal and yearly variations. Abstract Reduction in runoff and increase in actual evapotranspiration (AET) are two well-known benefits of green roofs. However, few studies have been carried out to investigate how green roofs affect runoff and AET when there is interaction between them. Such interaction is most prominent when green roofs have an additional storage layer. In this study, a modified hydrological model for green roofs is proposed to explicitly describe water retention and release in different layers and during wet/dry periods, which can reflect the interaction between runoff and AET under alternating dry and wet conditions. After calibration and validation with experimental data, the model was used to evaluate the combined effects of runoff reduction and increase in AET for green roofs under moist sub-tropical weather condition (such as Shenzhen, China). The results indicate that the daily AET and event runoff of green roofs decrease with increasing antecedent dry period (ADP); an additional storage layer can increase the ability of green roofs in reducing runoff and increasing AET. Generally, the effect is more pronounce under weather conditions with higher temperature, more rainfall amount and longer ADP. Such results provide hydrologists and engineers with a new and effective tool to simulate and understand the performance of green roofs by considering water retention and release in the layers. [ABSTRACT FROM AUTHOR]

Highlights • Trust among stakeholders is an important outcome in a co-innovation process. • In practice, co-innovation is context specific, thus requiring an adaptive mind-set. • A staged approach allows better integration of flexibility and adaptability in co-innovation projects. • Co-innovation processes are ideally suited for conditions where management of a public good resource is in discussion. Abstract Uptake of irrigation scheduling tools by New Zealand (NZ) farmers has remained static for many years and some researchers consider the use of linear, tech-transfer approaches as the main reason for this. To understand the controls and drivers that influence the uptake of these tools and to evaluate the effectiveness of a co-innovation approach in improving their (tools) uptake, a team of biophysical (hydrologists) and social researchers undertook a pilot study in an irrigation scheme in the South Island of NZ. Co-innovation offers a multi-directional, multi-level, multi-actor approach, in which input from stakeholders is valued in every part of the process, from problem definition to solution adoption. In this study, we focused on the adaptive aspect of co-innovation that allows stakeholders to periodically review their actions and respond to it in a way that is inclusive others' views and reflective of feedback received. The pilot study activities were analysed retrospectively to develop a systemic view to the implementation of a co-innovation-based multi-stakeholder hydrology project. While implementing a co-innovation approach, five chronologically-distinct yet overlapping phases emerged in the project: 1. concept development , where the hydrologists came up with the research idea and seed concept; 2. trust building , where researchers (hydrologists and social) interacted with key on-farm stakeholders in developing and implementing the research idea into a pilot field study; 3. knowledge synthesis, where researchers collected on-farm biophysical and behavioural data to record practice change; 4. extended outreach, where stakeholders, including researchers, devised pathways to sustain the lessons learned and practices changed, and disseminated the learnings to the wider irrigation community; and 5. project legacy, where the researchers, after the development of the seed concept into a practice change, evolved an exit strategy. Apart from core research activities, such as data collection on irrigation water use and changes in irrigation scheduling practices, each one of the five phases included actions that were unique to that phase as well as to achieving the wider pilot study goal of improving water use efficiency. This paper discusses the learnings from these phases, including insights, and key identifiers and indicators of pilot study progression during each phase, which may serve as an example to other biophysical studies that propose to employ co-innovation-based multi stakeholder approach. [ABSTRACT FROM AUTHOR]

This paper highlights mistakes that have helped shape my professional career. I use examples of personal, as well as technical failures to explore some guiding principles that I have found useful when navigating my professional journey. It is only the rarest of technical gurus who can afford to ignore the limitations of their personal interactions: to be impactful, the rest of us need to give as much, if not more, attention to soft skills than we do to our technical ones. I thus discuss the qualities that I think are needed to leverage technical strengths, and I outline some professional behaviours that I think are required to be effective. I also outline some high level technical themes that I have found important as a hydrologist. These cover the challenges of extrapolation, the analysis of joint interactions in compound events, the differentiation between hydrologic change and variability, and the value of separately considering different sources of uncertainty. [ABSTRACT FROM AUTHOR]

Large tipping-bucket flow meters (TBFs, one tip > 200 ml) have been employed by hydrologists to quantify various water fluxes in a variety of contexts. The over-arching goal of this study is to develop a generalized correction equation for various TBFs. Based on our testing, we recommend the following to minimize TBF error: (1) periodic checking of the static calibration volume ( c ) since c is a gauge-specific value which has been found to vary after field deployment; and (2) for dynamic calibration, the use of our newly derived generalized correction equation when the tipping rate is less than 0.2 Hz. In equation form, the generalized correction equation for common TBFs with flat triangular buckets is: V  = −0.75 Q 2  + 0.72 Q  + 1 ( R 2  = 0.843; p  <0.0001), where V  =  v/c and v is the water volume for one tip under dynamic conditions, and Q  =  q / c [s − 1 ] and q is the water flow rate into the TBF. From our field test in a Japanese cedar forest stand, using stemflow ( S F ) as an example, we found that use of the generalized correction equation was successful in eliminating the 2–3% error in S F amounts. Moreover, we found that the generalized correction equation performed nearly as well as gauge-specific derived correction equations. Thus, our generalized correction equation is applicable to correct flow estimates of TBFs when one does not have time and/or laboratory set-up for the laborious task of testing individual TBFs themselves. Although our correction procedure may not completely eliminate all error, we recommend use of the generalized correction equation for TBFs to improve the accuracy of water flux calculations in hydrologic studies. [ABSTRACT FROM AUTHOR]

The sharing of data and collection of new data are both essential, but they are not inherently complementary. When data are openly available, researchers may be motivated to use those data rather than collect more because field work has costs and risks. The competitive advantage to those who do not put resources towards fieldwork may discourage field hydrology. Allocating efforts towards generating field data, which benefits hydrological sciences, is not necessarily best for individual hydrologists, especially in an era of open data. The objective of this work is to open a conversation on whether individuals’ best interests may contrast with the community’s desire for new observations. If the community wants new field observations, there is a need to consider the shifting balance of incentives and disincentives for pursuing field studies in hydrology. [ABSTRACT FROM AUTHOR]