Surface water storage—including wetlands and other small waterbodies—has largely been disregarded in traditional hydrological models. In this paper, the grid resampling method is adopted to study the influence of the digital elevation model (DEM) grid resolution on depression storage (DS) considering different rainfall return periods. It is observed that the DEM grid size highly affects DS, and the higher the grid resolution is, the larger the DS value. However, when the grid resolution reaches a certain value, the maximum DS value decreases. This suggests that a critical grid resolution value exists at which the water storage capacity of depressions is maximized, namely, 20 m in this work. This phenomenon is further verified in two test cases with and without the infiltration process, i.e., calculations of the local area and without infiltration area, respectively. This research may facilitate the accurate computation of the DS process, which is greatly affected by the grid resolution, thereby improving the reliability of hydrological models.

Using data from five long-term field sites measuring soil moisture, we show the limitations of using soil moisture observations alone to constrain modelled hydrological fluxes. We test a land surface model, MESH/CLASS, with two configurations: one where the soil hydraulic properties are determined using a pedotransfer function (the texture-based calibration) and one where they are assigned directly (the hydraulic properties-based calibration). The hydraulic properties-based calibration outperforms the texture-based calibration in terms of reproducing changes in soil moisture storage within a 1.6 m deep profile at each site, but both perform reasonably well, especially in the summer months. When the models are constrained using observations of changes in soil moisture, the predicted hydrological fluxes are subject to very large uncertainties associated with equifinality. The uncertainty is larger for the hydraulic properties-based calibration, even though the performance was better. We argue that since the pedotransfer functions constrain the model parameters in the texture-based calibrations in an unrealistic way, the texture-based calibration underestimates the uncertainty in the fluxes. We recommend that reproducing observed cumulative changes in soil moisture storage should be considered a necessary but insufficient criterion of model success. Additional sources of information are needed to reduce uncertainties, and these could include improved estimation of the soil hydraulic properties and direct observations of fluxes, particularly evapotranspiration.

Investigating the changes in streamflow regimes is useful for understanding the mechanisms associated with hydrological processes in different watersheds and for providing information to facilitate water resources management. In this study, we selected three watersheds, i.e., Sandu River, Hulu River, and Dali River on the Loess Plateau, to examine the changes in the streamflow regimes and to determine their responses to different soil and water conservation measures (terracing, afforestation, and damming). The daily runoff was collected continuously by three hydrological gauges close to the outlets of the three watersheds from 1965 to 2016. The eco-surplus, eco-deficit, and degree of hydrological change were assessed to detect hydrological alterations. The Budyko water balance equation was applied to estimate the potential impacts of climate change and human activities on the hydrological regime changes. Significant decreasing trends (P < 0.05) were detected in the annual streamflow in the Sandu and Dali River watersheds, but not in the Hulu River watershed where afforestation dominated. The annual eco-surplus levels were low and they decreased slightly at three stations, whereas the eco-deficit exhibited dramatic increasing trends in the Sandu and Dali River watersheds. In the Sandu River watershed (dominated by terraces), the runoff exhibited the most significant reduction and the eco-deficit was the highest among the three watersheds. The integral degrees of hydrological change were higher in the Sandu River watershed than the other two watersheds, thereby suggesting substantial variations in the magnitude, duration, frequency, timing, and rate of change in the daily streamflow. In the Dali River watershed (dominated by damming), the changes in the extreme flow were characterized by a decreasing number appearing in high flow. In these watersheds, human activities accounted for 74.1% and 91.78% of the runoff reductions, respectively. In the Hulu River watershed (dominated by afforestation), the annual runoff exhibited an insignificant decreasing trend but with a significant increase in the low flow duration. Rainfall changes accounted for 64.30% of the runoff reduction.

Mountain regions are an important regulator in the global water cycle through their disproportionate water contribution. Often referred to as the “Water Towers of the World”, mountains contribute 40 to 60% of the world’s annual surface flow. Shade is a common feature in mountains, where complex terrain cycles land surfaces in and out of shadows over daily and seasonal scales. This study investigated turbulent water and carbon dioxide fluxes over the snow-free period in a subalpine wetland in the Canadian Rocky Mountains, from June 7th to September 10th, 2018. Shading had a significant and substantial effect on water and carbon fluxes at our site. Each hourly increase of shade per day reduced evapotranspiration (ET) and gross primary production (GPP) by 0.42 mm and 0.77 gCm-2, equivalent to 17% and 15% per day, respectively, over the entire study period. However, during only peak growing season, when leaves were fully out and mature, shade caused by the local complex terrain, reduced ET and increased GPP, likely due to enhanced diffuse radiation. The overall result was increased water use efficiency at the site during periods of increased shading during the peak growing season. In addition to incoming solar radiation (Rg), temporal variability in ET was found to relate to temporal variability in soil temperature, moisture and vapour pressure deficit. Shade impacted the curvature and intercept of the nonlinear ET-Rg relationship at our site. In contrast, temporal variability in GPP at our site was dependent largely on Rg only. Our findings suggest that shaded subalpine wetlands can store large volumes of water for late season runoff and are productive through short growing seasons.

This study compares the U.S. National Water Model (NWM) reanalysis snow outputs to observed snow water equivalent (SWE) and snow-covered area fraction (SCAF) at SNOTEL sites across the Western U.S. SWE was obtained from SNOTEL sites, while SCAF was obtained from MODIS observations at a nominal 500 m grid scale. Retrospective NWM results were at a 1000 m grid scale. We compared results for SNOTEL sites to gridded NWM and MODIS outputs for the grid cells encompassing each SNOTEL site. Differences between modeled and observed SWE were attributed to both model errors, as well as errors in inputs, notably precipitation and temperature. The NWM generally under-predicted SWE, partly due to precipitation input differences. There was also a slight general bias for model input temperature to be cooler than observed, counter to the direction expected to lead to under-modeling of SWE. There was also under-modeling of SWE for a subset of sites where precipitation inputs were good. Furthermore, the NWM generally tends to melt snow early. There was considerable variability between modeled and observed SCAF as well as the binary comparison of snow cover presence that hampered useful interpretation of SCAF comparisons. This is in part due to the shortcomings associated with both model SCAF parameterization and MODIS observations, particularly in vegetated regions. However, when SCAF was aggregated across all sites and years, modeled SCAF tended to be more than observed using MODIS. These differences are regional with generally better SWE and SCAF results in the Central Basin and Range and differences tending to become larger the further away regions are from this region. These findings identify areas where predictions from the NWM involving snow may be better or worse, and suggest opportunities for research directed towards model improvements.

Many large rivers worldwide are enriched with high levels of suspended solids (SS), which are known to be hotspots of many nitrogen (N) transformation processes (e.g., denitrification, nitrification). However, the influence of SS on microbial ammonium (NH4+) recycling remains unclear. Water column NH4+ regeneration rates (REGs) and potential uptake rates (Upots) as well as community biological NH4+ demand (CBAD) was measured in the river-estuary continuum of the third longest river in the world—Yangtze River, where shows dramatic SS gradients. We found that, REGs, Upots, and CBAD all showed increasing trends along the river flow, with higher REGs, Upots, and CBAD in the estuary than in the river sections. The regeneration and uptake of NH4+ were nearly balanced in the river sections, while the positive CBAD in the estuary indicated obvious NH4+ demand of microbes. Concentrations of SS, which also controls the content of chemical oxygen demand and particulate N, were the main factor influencing NH4+ recycling rates and CBAD. SS induced regenerated NH4+ in the river-estuary continuum of Yangtze River was estimated to be 21.81 × 108 kg N yr−1 and accounted for about 25% of total N inputs, suggesting that regenerated NH4+ is an important N source for microbes and may influence nutrient dynamics in lower coasts. To our knowledge, this is the first to report NH4+ recycling in Yangtze River with an emphasis on its influencing factors and contribution to N budgets.

The era of "big data'' promises to provide new hydrologic insights, and open web-based platforms are being developed and adopted by the hydrologic science community to harness these datasets and data services. This shift accompanies advances in hydrology education and the growth of web-based hydrology learning modules, but their capacity to utilize emerging open platforms and data services to enhance student learning through data-driven activities remains largely untapped. Given that generic equations may not easily translate into local or regional solutions, teaching students to explore how well models or equations work in particular settings or to answer specific problems using real data is essential. This paper introduces an open web-based learning module developed to advance data-driven hydrologic process learning, targeting upper level undergraduate and early graduate students in hydrology and engineering. The module was developed and deployed on the HydroLearn open educational platform, which provides a formal pedagogical structure for developing effective problem-based learning activities. We found that data-driven learning activities utilizing collaborative open web platforms like HydroShare and CUAHSI JupyterHub computational notebooks allowed students to access and work with datasets for systems of personal interest and promoted critical evaluation of results and assumptions. Initial student feedback was generally positive, but also highlights challenges including trouble-shooting and future-proofing difficulties and some resistance to open-source software and programming. Opportunities to further enhance hydrology learning include better articulating the myriad benefits of open web platforms upfront, incorporating additional user-support tools, and focusing methods and questions on implementing and adapting notebooks to explore fundamental processes rather than tools and syntax. The profound shift in the field of hydrology toward big data, open data services and reproducible research practices requires hydrology instructors to rethink traditional content delivery and focus instruction on harnessing these datasets and practices in the preparation of future hydrologists and engineers.

Artificial subsurface (tile) drainage is used to increase trafficability and crop yield in much of the Midwest due to soils with naturally poor drainage. Tile drainage has been researched extensively at the field scale, but knowledge gaps remain on how tile drainage influences the streamflow response at the watershed scale. The purpose of this study is to analyze the effect of tile drainage on the streamflow response for 59 Ohio watersheds with varying percentages of tile drainage and explore patterns between the Western Lake Erie Bloom Severity Index to streamflow response in heavily tile-drained watersheds. Daily streamflow was downloaded from 2010-2019 and used to calculated mean annual peak daily runoff, mean annual runoff ratio, the percent of observations in which daily runoff exceeded mean annual runoff (TQmean), baseflow versus stormflow percentages, and the streamflow recession constant. Heavily-drained watersheds (> 40 % of watershed area) consistently reported flashier streamflow behavior compared to watersheds with low percentages of tile drainage (< 15% of watershed area) as indicated by significantly lower baseflow percentages, TQmean, and streamflow recession constants. The mean baseflow percent for watersheds with high percentages of tile drainage was 20.9 % compared to 40.3 % for watersheds with low percentages of tile drainage. These results are in contrast to similar research regionally indicating greater baseflow proportions and less flashy hydrographs (higher TQmean) for heavily-drained watersheds. Stormflow runoff metrics in heavily-drained watersheds were significantly positively correlated to western Lake Erie algal bloom severity. Given the recent trend in more frequent large rain events and warmer temperatures in the Midwest, increased harmful algal bloom severity will continue to be an ecological and economic problem for the region if management efforts are not addressed at the source. Management practices that reduce the streamflow response time to storm events, such as buffer strips, wetland restoration, or drainage water management, are likely to improve the aquatic health conditions of downstream communities by limiting the transport of nutrients following storm events.

Submersion and exposure from the operation of the Three Gorges Reservoir (TGR) can alter soil properties and plant characteristics at different elevations of the water level fluctuation zone (WLFZ), possibly influencing soil detachment capacity (Dc), but the vertical heterogeneity of this effect is uncertain. Soil samples were taken from 6 segments (5 m elevation per segment) along a slope profile in the WLFZ of the TGR to clarify the vertical heterogeneity of Dc. Scouring experiments were conducted at 5 slope gradients (17.63%, 26.79%, 36.40%, 46.63%, and 57.74%) and 5 flow rates (10, 15, 20, 25, and 30 L min–1) to determine Dc. The results indicate that the soil properties and biomass parameters of the WLFZ are strongly affected by elevation. Dc fluctuates with increasing elevation, with maximum and minimum average values at elevations of 145-150 m and 165-170 m, respectively. Linear equations accurately describe the relationships between Dc and hydrodynamic parameters. τ, ω, and E perform much better than U. Furthermore, a clear improvement is seen when using the general index of flow intensity to estimate Dc. Dc is significantly negatively correlated with MWD (p < 0.05) and organic matter (p < 0.01) but not significantly correlated with other soil properties (p > 0.05). At elevations of 145-150 m and 170-175 m, rill erodibility was greater than at other elevations. The critical hydraulic parameters were highest in the 165-170 m segments, both showing obviously fluctuation in the vertical direction of slope surface. This research highlighted the vertical heterogeneity of the soil detachment and was helpful to understand the mechanisms of soil detachment processes in the WLFZ of the TGR.

In this study we adapted WRF-Hydro to the Cape Fear River basin (CFRB) to assess its performance during Hurricane Florence (2018). The model was first calibrated with a strategy of mixture of automatic and manual calibration during Florence and then evaluated with an independent hurricane event. With satisfactory NSE values (>0.4) achieved at all gages for hourly simulation, the model demonstrates its potential in simulating the flood response at both basin and sub-basin scale during hurricane events. The model’s capability in reproducing rainfall and properly translating it to hydrological response was further evaluated. The analysis suggests that the calibrated WRF-Hydro in combination with a series of WRF simulation using different microphysics schemes can provide reasonable flood simulations. The model reproduced peak streamflow observed at gage stations with acceptable errors in timing and amplitude. Meanwhile, positive(negative) bias in rainfall input is likely to be amplified (reduced) in streamflow forecast when simulated rainfall volume is larger than the “model true”. And the timing bias mostly inherited from rainfall simulation and calibration process.

When formulating a hydrologic model, scientists rely on parameterizations of multiple processes based on field data, but literature review suggests that more frequently people select parameterizations that were included in pre-existing models rather than re-evaluating the underlying field experiments. Problems arise when limited field data exist, when “trusted” approaches do not get reevaluated, and when processes fundamentally change in different environments. The physics and dynamics of snow interception by conifers, including both loading and unloading of snow, is just such a case. The most commonly used interception parameterization is based on data from four trees from one site, but field study results are not directly transferable between environments. The process varies dramatically between locations with relatively warmer versus colder winters. Here, we combine a comprehensive literature review with a model to demonstrate essential improvements to model representations of snow interception. We recommend that, as a first and essential step, all models include increased loading due to increased adhesion and cohesion when temperatures rise from -3 and 0°C. The commonly used parameters of a fixed maximum value for loading and an e-folding time for unloading are not supported by observations or physical understanding and are not necessary to reproduce observations. In addition to unloading based on physical processes, such as wind or canopy warming, all models must represent melting of in-canopy snow so that it can be unloaded in liquid form. As a second step, we propose field experiments across climates and forest types to investigate: a) a representation of the force balance between adhesion and cohesion versus gravity for both interception efficiency and rates of unloading, b) wind effects during and between storms, and c) lubrication when snow melts. For greatest impact, this framework requires dedicated field measurements. These processes are essential for models to accurately represent the impacts of dynamically changing forest cover and snow cover on both global albedo and water supplies.

Based on historical records and crop harvest scores extracted from historical documents, this study reconstructed the spatial-temporal distribution and severities of floods in the Yangtze-Huai River valley in 1823 and 1849. We also summarized the effects of the floods on society and identified government measures taken to cope with the floods in the context of the economic recession in the period of 1801--1850. The 1823 flood, which was caused by the heavy precipitation of the Meiyu period and typhoons, severely affected areas in the lower reaches of the Yangtze River. Meanwhile, the 1849 flood, triggered by long-term, high-intensity Meiyu precipitation in the middle and lower reaches of the Yangtze River, mainly affected areas along the Yangtze River. The 1849 disaster was more serious than the one in 1823. In the lower reaches of the Yangtze River, the 1849 flood caused the worst agricultural failure of the period 1730--1852. To deal with the disasters, the Qing government took relief measures, such as exempting taxes in the affected areas, distributing grain stored in warehouses, and transferring grain to severely afflicted areas. These relief measures were supplemented by auxiliary measures, such as exempting commodity taxes on grain shipped to disaster areas and punishing officials who failed to provide adequate disaster relief. The flood disasters disrupted the water system of the Grand Canal and forced the Qing government to transport Cao rice by sea beginning in 1826. This laid the groundwork for the rise of coastal shipping in modern China. With the economic recession of the 19th century, Chinese society was not as resilient to floods as it was in the 18th century. Compared to droughts, floods are more difficult to deal with and pose greater threats to infrastructure and to normal life and work in the cities.

Climate change in terms of regional warming and modifications in precipitation regimes has large impacts on streamflow in regions where both rainfall and snowmelt are important runoff generating processes like in Norway. Hydrological impacts of recent changes in climate are usually investigated by trend analyses applied on annual, seasonal, or monthly time series. However, neither of them can detect sub-seasonal changes and their underlying causes. Based on high-resolution trend analyses (i.e., applying the Mann-Kendall test on 10-day-moving-averaged daily time series), this study investigated sub-seasonal changes in daily streamflow, rainfall, and snowmelt in 61 and 51 catchments in Western vs. Eastern Norway (Vestlandet vs. Østlandet), respectively, over the period 1983-2012. The relative contribution of rainfall vs. snowmelt to daily streamflow and the changes therein have also been estimated to identify the changing relevance of these driving processes over the same period. Detected changes in daily streamflow were finally attributed to changes in the most important hydro-meteorological drivers using multiple-regression models with increasing complexity. Results reveal a coherent picture of earlier spring flow timing in both regions due to earlier snowmelt. Other streamflow trend patterns differ between both regions: Østlandet shows increased summer streamflow in catchments up to ~1100 m a.s.l. and slightly increased winter streamflow in about 50 % of the catchments, while trend patterns in Vestlandet are less coherent. The importance of rainfall for streamflow contribution has increased in both regions, and the trend attribution reveals that changes in rainfall and snowmelt can explain streamflow changes to some degree in periods and regions where they are dominant (snowmelt: spring and Østlandet; rainfall: autumn and Vestlandet). However, detected streamflow changes can be best explained by adding temperature as an additional predictor which indicates the relevance of additional driving processes for streamflow changes like increased glacier melt and evapotranspiration.

In this study, the impact of spatio-temporal accuracy of four different sea surface temperature (SST) datasets on the accuracy of the Weather Research and Forecasting (WRF)-Hydro system to simulate hydrological response during two catastrophic flood events over Eastern Black Sea (EBS) and Mediterranean (MED) regions of Turkey is investigated. Three time-varying and high spatial resolution external SST products (GHRSST, Medspiration, and NCEP-SST) and one coarse-resolution and invariable SST product (ERA5- and GFS-SST for EBS and MED regions, respectively) already embedded in the initial and boundary condition dataset of WRF model are used in deriving near-surface weather variables through WRF. After the proper event-based calibration performed to the WRF-Hydro using hourly and daily streamflow data of small catchments in both regions, uncoupled model simulations for independent SST events are conducted to assess the impact of SST-triggered precipitation on simulated extreme runoff. Some localized and temporal differences in the occurrence of the flood events with respect to observations depending on the SST representation are noticeable. SST products represented with higher temporal and spatial correlation revealed significant improvement in flood hydrographs for both regions. The higher spatial and temporal correlations of GHRSST dataset show RMSE reduction up to 20% and increase in correlation from 0.3 to 0.8 with respect to the invariable SST (ERA5) in simulated runoffs over the EBS region. The error reduction with GHRSST reached 35% after the calibration of hydrological model parameters compared to not calibrated model. The use of both GHRSST and Medspiration SST data characterized with high spatiotemporal correlation resulted in runoff simulations exactly matching the observed runoff peak of 300 m3/s by reducing the overestimation seen in not calibrated runs over the MED region.

Fully coupled atmospheric-hydrological models allow a more realistic representation of the land surface–boundary layer continuum, representing both high-resolution land-surface/subsurface water lateral redistribution and the related feedback towards the atmosphere. This study evaluates the potential contribution of the fully coupled approach in extended-range mesoscale hydrometeorological ensemble forecasts. Previous studies have shown, for deterministic simulations, that the effect of fully coupling for short-range forecasts is minor compared to other sources of uncertainty, however, it becomes not negligible when increasing the forecast period. Through a proof-of-concept consisting of an ensemble (50 members from the ECMWF Ensemble Prediction System) seven-days-in-advance forecast of a high impact event affecting the Calabrian peninsula (southern Italy, Mediterranean basin) on November 2019, the paper elucidates the extent to which the improved representation of the terrestrial water lateral transport in the Weather Research and Forecasting (WRF) – Hydro modeling system affects the ensemble water balance, focusing on the precipitation and the hydrological response, in terms of both soil moisture dynamics and streamflow in 14 catchments spanning over 42% of the region. The fully coupled approach caused an increase of surface soil moisture and latent heat flux from land in the days preceding the event, partially affecting the lower Planetary Boundary Layer. However, when shoreward moisture transport from surrounding sea rapidly increased becoming the dominant process, only a weak signature of soil moisture contribution could be detected, resulting in only slightly higher precipitation forecast and not clear variation trend of peak flow, even though the latter variable increased up to 10% in some catchments. Overall, this study highlighted a remarkable performance of the medium-range ensemble forecasts, suggesting a profitable use of the fully coupled approach for forecasting purposes in circumstances in which soil moisture dynamics is more relevant and needs to be better addressed.

A regional coupled approach to water cycle prediction is demonstrated for the 4-month period from November 2013 to February 2014 through analysis of precipitation, soil moisture, river flow and coastal ocean simulations produced by a km-scale atmosphere-land-ocean coupled system focussed on the United Kingdom (UK), running with horizontal grid spacing of around 1.5 km across all components. The Unified Model atmosphere component, in which convection is explicitly simulated, reproduces the observed UK rainfall accumulation (r2 of 0.62 for daily accumulation), but there is a notable bias in its distribution – too dry over western upland areas and too wet further east. The JULES land surface model soil moisture state is shown to be in broad agreement with a limited number of cosmic-ray neutron probe observations. A comparison of observed and simulated river flow shows the coupled system is useful for predicting broad scale features, such as distinguishing high and low flow regions and times during the period of interest but are shown to be less accurate than optimised hydrological models. The impact of simulated river discharge on NEMO model simulations of coastal ocean state is explored in the coupled system, with comparisons provided relative to experiments using climatological river input and no river input around the UK coasts. Results show that the freshwater flux around the UK contributes of order 0.2 psu to the mean surface salinity, and comparisons to profile observations give evidence of an improved vertical structure when applying simulated flows. This study represents a baseline assessment of the coupled system performance, with priorities for future model developments discussed.

While 1992 marked the first major dam – Manwan – on the main stem of the Mekong River, the post-2010 era has seen the construction and operationalisation of mega dams such as Xiaowan (started operations in 2010) and Nuozhadu (started operations in 2014) that were much larger than any dams built before. The scale of these projects implies that their operations will likely have significant ecological and hydrological impacts from the Upper Mekong Basin to the Vietnamese Delta and beyond. Historical water level and water discharge data from 1960 to 2020 were analysed to examine the changes to streamflow conditions across three time periods: 1960-1991 (pre-dam), 1992-2009 (growth) and 2010-2020 (mega-dam). At Chiang Saen, the nearest station to the China border, monthly water discharge in the mega-dam period has increased by up to 98% during the dry season and decreased up as much as -35% during the wet season when compared to pre-dam records. Similarly, monthly water levels also rose by up to +1.16m during the dry season and dropped by up to -1.55m during the wet season. This pattern of hydrological alterations is observed further downstream to at least Stung Treng (Cambodia) in our study, showing that Mekong streamflow characteristics have shifted substantially in the post-2010 era. In light of such changes, the 2019-2020 drought – the most severe one in the recent history in the Lower Mekong Basin – was a consequent of constructed dams reducing the amount of water during the wet season. This reduction of water was exacerbated by the decreased monsoon precipitation in 2019. Concurrently, the untimely operationalisation of the newly opened Xayaburi dam in Laos coincided with the peak of the 2019-2020 drought and could have aggravated the dry conditions downstream. Thus, the mega-dam era (post-2010) may signal the start of a new normal of wet-season droughts.

1. IntroductionTropical mountainous ecosystems are recognized as providers of valuable ecological and hydrological services (Viviroli et al, 2007). In Central America, the Páramo, a high‐elevation tropical grassland ecosystem, extends over ~ 200 km2 in Costa Rica and Panama, with ~50% of this area located within the Chirripó National Park between 3,100 and 3,820 m asl (-83.49°, 9.46°). Vegetation mostly consists of 0.5 to 2.5 m tall bamboo dominated (Chusquea subtessellata ) grasslands, covering up to 60% of the total Páramo area in Costa Rica (Fig.1a). The climate is controlled by the northeast trade winds, the latitudinal migration of the Intertropical Convergence Zone (ITCZ), cold continental outbreaks (i.e., northerly winds), and the seasonal influence of Caribbean cyclones. These circulation patterns produce two rainfall maxima on the Pacific slope, one in June and one in September, which are interrupted by a relative minimum between July-August, known as the Mid-Summer Drought, due to intensification of trade winds over the Caribbean Sea (Magaña et al., 1999; Waylen, 1996). The wettest season extends from May to November (contributing up to 89% of the annual precipitation), whereas the driest season is from December to April (Fig. 2a; Esquivel-Hernández et al., 2018). The surface water system of Chirripó is characterized by a lake district which comprises approximately 30 lakes of glacial origin and streams flowing down the Caribbean and Pacific slopes (Fig 1b). Lake catchments are characterized by steep slopes that promote rapid hydrological responses such as fast water‐level changes. Input of water to these glacial lakes is mostly controlled by the seasonal inputs of rainfall, which mix up with stream and subsurface waters. In April 2015, the Chirripó Hydrological Research Site (CHRS) was installed with the goal of advancing the understanding of the hydrological functioning in the Central American Páramo using environmental tracers (i.e., water stable isotopes) in combination with hydrometric data. A detailed map of CHRS is available in Esquivel-Hernández et al. (2019).