Catchment modelling has undergone tremendous developments during the past decades. In the 1970s, the focus was on simulation of catchment runoff with process descriptions and data inputs being lumped to the catchment scale. Later developments included spatially distributed models allowing data inputs and hydrological processes to be simulated at model grid scale, i.e. much finer than catchment scale. These models were able to explicitly simulate various processes such as soil moisture, evapotranspiration, groundwater and surface runoff. With the advancements in remote sensing technology and availability of high-resolution data, increased attention has in recent years been given to enhancing the capability of catchment models to reproduce spatial patterns and in this way improve our understanding of hydrological processes and the physical realism of catchment models. This development process has involved a wide spectrum of different aspects in the modelling process, reaching from an improved understanding of uncertainties in data, model parameters and model structures to new protocols for good modelling practices in water management. Recognizing the important role of biodiversity and social aspects, hydrologists are now extending the scope of their models to capture the interactions between water, biota and human social systems.
The El Niño-Southern Oscillation (ENSO) phenomena, originating in the tropical Pacific region, is an interannual climate variability driven by sea surface temperature and atmospheric pressure changes that affect weather patterns globally. In Mesoamerica, ENSO can cause significant changes in rainfall patterns with major impacts on water resources. This commentary presents results from a nearly 10-yr hydrometric and tracer monitoring network across north-central Costa Rica, a region known as a headwater-dependent system. This monitoring system has recorded different El Niño and La Niña events, as well as the direct/indirect effects of several hurricane and tropical storm passages. Our results show that ENSO exerts a significant but predictable impact on rainfall anomalies, groundwater recharge, and spring discharge, as evidenced by second-order water isotope parameters (e.g., line conditioned-excess or LC-excess). The Oceanic Niño Index (ONI) is correlated with a reduction in mean annual and cold front rainfall across the headwaters of north-central Costa Rica. During El Niño conditions, rainfall is substantially reduced (by up to 69.2%) during the critical cold fronts period, subsequently limiting groundwater recharge and promoting an early onset of baseflow conditions. In contrast, La Niña is associated with increased rainfall and groundwater recharge (by up to 94.7% during active cold front periods). During La Niña, the long-term mean spring discharge (39 Ls -1) is exceeded 63-80% of the time, whereas, during El Niño, the exceedance time ranges between 26% and 44%. These stark shifts in regional hydroclimatic variability are imprinted on the hydrogen and oxygen isotopic compositions of meteoric waters. Drier conditions favored lower LC-excess in rainfall (-17.3‰) and spring water (-6.5‰), whereas wetter conditions resulted in greater values (rainfall=+17.5‰; spring water=+10.7‰). The lower and higher LC-excess values in rainfall corresponded to the very strong 2014-16 El Niño and 2018 La Niña, respectively. During the recent triple-dip 2021-23 La Niña, LC-excess exhibited a significant and consistently increasing trend. These findings highlight the importance of combining hydrometric, synoptic, and isotopic monitoring as ENSO sentinels to advance our current understanding of ENSO impacts on hydrological systems across the humid Tropics. Such information is critical to constraining 21 st century projections of future water stress across this fragile region.
Vegetation structure is considered one of the most important factors shaping the spatial variation of snow accumulation under forest canopies. However, fine scale relationships between canopy density, snow interception, wind redistribution and sub-canopy accumulation are poorly understood and difficult to observe, and their influence governing stand-scale snow distributions that determine snow covered area depletion during melt is largely unknown. In this study, fine-scale observations of forest structure and sub-canopy snow accumulation were analyzed over two mid-winter snowfalls to a sub-alpine forest in Marmot Creek Research Basin, Canadian Rockies, Alberta, to identify the impact of snow-canopy interactions on spatial patterns of sub-canopy snow accumulation. High spatial resolution (5 cm and 25 cm) snow accumulation estimates and canopy structure metrics were calculated from the combination of repeated UAV-lidar observations with snow and photographic surveys, utilizing novel resampling methods including voxel ray sampling of lidar (VoxRS) to improve metric robustness and reduce bias. Over 50% of the spatial variance in forest snow accumulation was found at length scales less than 2 m, supporting the role of local scale canopy structure in governing variation in subcanopy snow accumulation. Additionally, subcanopy snow accumulation showed significant angular spread in relationships with overhead canopy structure; the vertical asymmetry coinciding with local windflow directions during snowfall. Detailed angular analysis showed nontrivial snow-vegetation relationships that likely reflect multiple snowfall-vegetation processes, including unloading and entrainment of intercepted snowfall during wind gusts and funneling of entrained particles by downwind vegetation. These fine-scale findings suggest several emergent processes which may influence snow accumulation at the scale of forest stands, with novel considerations for representing SWE distributions under dense evergreen canopies under varying environmental and canopy conditions. Similar studies over a broad range of conditions and forests will help refine and generalize the effects observed here for further snow hydrology and forestry applications.
Short-term surges in stream temperature in response to storm events have frequently been observed in urban areas , highlighting the need for improved understanding of the factors influencing urban stream temperature. Urban land cover complexity and infrastructure designed for rapid water routing to the sewer system create a direct link between storm events and water release processes, influencing urban stream temperature responses. This study aims to identify predictors of diverse stream temperature response patterns to summer storms. We analyzed 403 storm events from six urban and semi-urban catchments along the US East Coast using dynamic time warping to identify archetype patterns of stream temperature responses. We further disentangled observed stream temperature increase patterns to reveal the drivers associated with “heat pulses”, which are characterized by a rapid but high-magnitude temperature increase followed by a sharp temperature drop at the start of the hydrograph. Our results show that stream temperature patterns were event-specific and linked to pre-event conditions and rainfall-runoff characteristics, with the shape of the hydrograph and rainfall-runoff response identified as the most important determinators of the observed temperature response patterns. Ponded surface waters and storm drains, as well as cooler water from the shallow subsurface, were identified as likely sources contributing to temperature patterns. These findings have important implications for understanding urban hydrology and the contributions of different source zones in urban catchments. Specifically, our results suggest that streamwater temperature can serve as a cost-effective tracer of information about urban water sources and pathways, aiding in the understanding of complex urban hydrology.
Quantitative knowledge about ecohydrological partitioning across the critical zone in different types of urban green space is important to balance sustainable water needs in cities during future challenges of increasing urbanization and climate warming. We monitored stable water isotopes in liquid precipitation and atmospheric water vapour (δ v) using in-situ cavity ring-down spectroscopy (CRDS) over a two-month period in an urban green space area in Berlin, Germany. Our aim was to better understand the origins of atmospheric moisture and its link to water partitioning under contrasting urban vegetation. δ v was monitored at multiple heights (0.15, 2 and 10 m) in grassland and forest plots. The isotopic composition of δ v above both land uses was highly dynamic and positively correlated with that of rainfall indicating the changing sources of atmospheric moisture. Further, the isotopic composition of δ v was similar across most heights of the 10 m profiles and between the two plots indicating limited aerodynamic mixing. Only the surface at ~0.15 m height above the grassland, δ v showed significant differences, with more enriched values indicative of evaporative fractionation immediately after rainfall events. Further, disequilibrium between δ v and precipitation composition was evident during and right after rainfall events with more positive values (i.e. vapour more enriched than precipitation) in summer and negative values in winter, which probably results from higher evapotranspiration and more convective precipitation events in summer. Our work showed that it is technically feasible to produce continuous, longer-term data on δ v isotope composition in urban areas from in-situ monitoring using CRDS, providing novel insights into water cycling and partitioning across the critical zone of an urban green space. Such data has the potential to better constrain the isotopic interface between the atmosphere and the land surface and to improve ecohydrological models that can resolve evapotranspiration fluxes.
The higher elevation forests of Norfolk Island are regularly immersed in the clouds and scientific and anecdotal evidence suggests that in addition to rainfall, water is likely to be collected as cloud droplets are intercepted by the forest canopy. This water is likely to be important for the local hydrology and ecology, yet it has never been quantified. To address this, a field measurement campaign was established to measure hydrological inputs to the forest floor at two elevated forest sites in the Norfolk Island National Park. Instrumentation included throughfall and stemflow systems and measurements of rainfall in the open in nearby clearings. Sites exhibited very high stem density and basal area by international standards and delivery of water to the forest floor was dominated by stemflow because of the funnelling characteristics of the dominant palm and pine trees. Both sites showed similar hydrological behaviour with stemflow and throughfall of around 48% and 32%, respectively. Stemflow contributions of 48% far exceed observations from the literature which are typically less than 10%. Rainfall rarely occurred in the absence of low-level cloud and some cloud immersion events lasted for many days with hydrologic inputs continuing for extended periods despite rainfall not being observed in the open. Cloud interception accounted for approximately 20% of total water input at both sites which is equivalent to 25% extra water on top of rainfall measured in the open. From an island-wide perspective the calculated extra hydrological input is only small due to the limited spatial extent of elevated forest, however, the additional water is likely to be very important to local hydrological processes and the unique plants, insects and animals which inhabit the higher elevation forests of Norfolk Island.
The streambed is the critical interface between the aquatic and terrestrial systems and hosts important biogeochemical hot spots within river corridors. Although the streambed characteristics are significantly different from those of its surrounding soil, the streambed itself has not been explicitly represented in watershed models. We developed an integrated hydrologic model that explicitly incorporated a streambed layer to examine the hydrological effects of streambed characteristics including hydraulic conductivity (K), layer thickness, and width on the exchange fluxes across the streambed as well as the streamflow at the watershed outlet. The numerical experiments were performed in the American River Watershed, a headwater, mountainous watershed within the Yakima River Basin in central Washington. Despite having a negligible effect on the watershed streamflow, an explicit representation of the streambed with distinctive properties dramatically changed the magnitude and variability of the exchange flux. In general, larger streambed K along with a thicker streambed layer induced larger exchange fluxes. The exchange flux was most sensitive to the streambed width or the mesh resolution of the streambed. A smaller streambed width (or a finer streambed resolution) increases exchange fluxes per unit area while reducing the overall exchange volumes across the entire streambed. The amount of baseflow decreased by 6% as the streambed width decreased from 250 m to 50 m. This finding is important because these hydrological changes may in turn affect the exchange of nutrients and contaminants between surface water and groundwater and the associated biogeochemical processes. Our work demonstrated the importance of representing streambed in fully distributed, process-based watershed models in better capturing the exchange flow dynamics in river corridors.
Hydrological models require a complete and accurate time series of weather inputs to adequately represent watershed-scale responses. The Global Historical Climatology Network (GHCN) is the most comprehensive ground-based global weather database and is often used in hydrological modeling studies. Since higher density, lower reliability precipitation measurements from private citizens collected by the Community Collaborative Rain, Hail, and Snow (CoCoRaHS) network data were integrated into the GHCN, hydrological modelers in the U.S. have access to a much greater amount of weather data. However, the benefit of using CoCoRaHS data has not been assessed. The objectives of this work were to develop a method for generating a complete weather data time series based on the combination of data from multiple GHCN monitors and to assess several methods for estimation of missing weather data. Weather data from GHCN monitors located within a specific radius of a watershed were obtained and interpolated using three estimation methods (Inverse Distance Weighting (IDW), Inverse Distance and Elevation Weighting (IDEW), and Closest Station), creating a seamless time-series of weather observations. To evaluate the performance of the methodologies, weather data obtained from each estimation method was used to force the Soil and Water Assessment Tool (SWAT) models of 21 U.S. Department of Agriculture-Conservation Effects Assessment Project watersheds in different climate regions to simulate daily streamflow for 2010-2021. Except for three watersheds, all SWAT models had Nash-Sutcliffe Efficiency above 0.5, the ratio of the root mean square error to the standard deviation of observations below 0.7, and percent bias from -25% to 25% with a satisfactory performance rating. Overall, IDEW and IDW performed similarly, and the Closest Station method resulted in the poorest streamflow simulation. A comparison with published SWAT model results further corroborated improved model performance using newly combined GHCN data with all Closest Station, IDW, and IDEW methods.
Excess nitrate and sediment, mobilized by precipitation events and transported into surface waters, is a global water quality challenge. Recent advances in high frequency, in-situ water quality monitoring sensors have created opportunities to investigate constituent concentration dynamics during short-term hydrological changes. In this study, we characterized the event-scale variability of nitrate ( NO 3 - ) and turbidity (a surrogate for sediment transport) in two large agricultural watersheds of the Upper Mississippi River Basin using hysteresis loop characteristics to determine sources and dominant transport mechanisms. We then applied factor analysis to detect variable groupings and thus determine controls on nitrate and sediment dynamics. We found that NO 3 - hysteresis behavior was consistent between the two watersheds and demonstrated distal contributions and/or late-event mobilization and flushing that was controlled by the characteristics of the event hydrology (such as, event duration and magnitude of event discharge). In contrast, turbidity hysteresis loops indicated sediment delivery differed between the two watersheds; the smaller watershed with more diverse land use demonstrated consistent early-event flushing or rapidly responding pathways whereas the larger, more agricultural watershed showed variability between dilution vs. flushing as well as delivery pathways between events. This dynamic behavior as well as the magnitude of the hysteretic response was principally related to the time lag between turbidity and discharge peaks for the smaller site, and to the event peak discharge and subsequent stream erosive power at the larger site that switched behavior. This result is critical for watershed water quality management especially in the context of a changing climate and further underscores the utility of high-frequency sensors monitoring data to offer deep insights into hydrological processes controls on contaminant transport and delivery.
This commentary discusses a framework for the benchmarking of hydrological models for different purposes when the datasets for different catchments might involve epistemic uncertainties. The approach might be expected to result in an ensemble of models that might be used in prediction (including models of different types) but also provides for model rejection to be the start of a learning process to improve understanding.
Investigating the response characteristics of various hydrological factors to the construction of water conservancy projects and evaluating their impact on the ecological environment is crucial for ecological protection and restoration in the Loess Plateau, China with a complex environment. In this study, we employed a geomorphology-based hydrological model to simulate the hydrological elements of the Qinhe River Basin in the Loess Plateau. Additionally, we explored the response characteristics of the water cycle and hydrological processes to the construction of reservoirs in the basin. We also examined multiyear changes in peak flood volume and sediment discharge during flood seasons influenced by reservoirs. A thorough evaluation of the simulation results indicated their reliability. The sub-basins hosting reservoirs initially showed an increase in evaporation, followed by a decrease. During the change periods, both runoff and soil water decreased, but remained higher than the mean values for the basin during the same period. The Normalized Difference Vegetation Index of sub-basins associated with five reservoirs was significantly higher than the mean value for the basin during the same period. The peak flood volume and sediment discharge in the basin were characterized by decreasing trends, with the latter showing weak sustainability. The value of each index for a sub-basin associated with a reservoir was higher than the average value for the basin. The construction and operation of reservoirs had a positive impact on the ecology of the basin. Water and soil conservation measures, including sediment regulation and storage using reservoirs, significantly decreased water-related disasters and soil erosion in the basin. This study provides a scientific basis for the design of water conservancy projects and ecological governance in the basin.
The continuous exploitation of groundwater has made wetland degradation an ecological and geological environmental problem that cannot be ignored and which has had impacts on the ecological environment and human production and life. In this study, with the help of Visual MODFLOW software, we used numerical simulation technology to simulate the wetland–aquifer interaction during the multiyear pumping process, establish a quasi-ideal model of wetlands based on the actual area of the Baiyangdian Basin, simulate the relationship of water quantity change between wetlands and piedmont plain aquifers during groundwater exploitation and its natural recovery process, and quantify the attenuation of the contribution of groundwater to wetlands caused by groundwater overexploitation. The results show that the impact of groundwater overexploitation on wetland degradation is mainly divided into two parts: one is the reduced base flow from the piedmont plain to the wetland, and the other is the induced infiltration caused by the reverse recharge of groundwater from the wetland due to the pumping effect. At the beginning of pumping, the effect of reduced base flow on wetland degradation is dominant, but with a longer pumping time, the effect of induced infiltration on wetland degradation exceeds the effect of reduced base flow. After stopping pumping, the effect of induced infiltration on wetland degradation responds instantly and decreases rapidly, while the effect of reduced base flow on wetland degradation continues for a long time. The total water reduction of wetlands increases with increasing hydraulic conductivity, and in actual wetland areas, if groundwater overexploitation is not restricted or artificial supply measures are not taken, the amount of wetland water will gradually decrease until it is exhausted.
The Mississippi River channel from New Orleans to the Gulf of Mexico (GOM) is a key deep draft navigation channel and an active deltaic lobe. Natural and engineered lateral exits from this reach into adjacent receiving basins historically has provided mineral sediment for wetland accretion in the face of rising relative sea level and supported estuarine-coastal food webs. However, our analysis indicates water losses from the channel have increased by 25% since 2004 due to (1) bank failures during large floods since 2012 that have created several large exit channels downriver of the flood protection levee, and (2) the opening of an engineered diversion at West Bay in 2004. This has resulted in a 60-80% loss in stream power in the lowermost navigation channel that is accompanied by net shoaling between 2012 and 2022 and an increased dredging need. Our 2022 survey in the GOM exit passes indicates that only 20% of the freshwater, 5% of the total suspended sediment (2% of the sand) at New Orleans now reaches the GOM: this supports previous research indicating the delta front is retreating after centuries of progradation. Together these results indicate that (1) river containment and the sustainability of the navigation channel is threatened, (2) sediment load reaching the seaward end of the delta may be insufficient to avoid major degradation, and (3) the increased freshwater flux into adjacent shallow coastal water bodies has unknown implications for coastal hypoxia and food webs, including commercial species (e.g., oysters) and marine mammals. Future acceleration in sea level rise rates and tropical storm frequency/intensity likely will worsen these trends.
Recently, superparamagnetic silica encapsulated DNA microparticles (SiDNAFe) were designed and in various experiments used as a hydrological tracer. We investigated the effect of bed characteristics on the transport behaviour and especially the mass loss of SiDNAFe in open channel injection experiments. Hereto, a series of laboratory injection experiments were conducted with four channel bed conditions (no sediment, fine river sediment, coarse sand, and goethite-coated coarse sand) and two water qualities (tap water and Meuse water). Breakthrough curves (BTCs) were analysed and modelled. Mass loss of SiDNAFe was accounted for as a first-order decay process included in a 1-D advection and dispersion model with transient storage (OTIS). SiDNAFe BTCs could be adequately described by advection and dispersion with or without a first-order decay process. Mass loss of SiDNAFe increased as a function of the surface roughness of the beds. Retention of SiDNAFe due to surface roughness was 1-2 orders of magnitude greater than gravitational settling rates, as determined in Tang et al. (2022). We speculate this was due to boundary layer kinetic attachment. The dispersive behaviour of SiDNAFe generally mimicked that of NaCl tracer, although SiDNAFe traveled faster on average due to a smaller effective cross-sectional area. No pattern was observed between SiDNAFe mass recovery and water qualities used. DNA concentration data uncertainty was mostly associated with lower SiDNAFe concentrations in the BTCs. This research highlights that riverbeds are important sinks, and the surface roughness affects the fate and transport characteristics of SiDNAFe when in proximity to the water-sediment interface. SiDNAFe possess promising potential as a surrogate for multi-tracing micro-contaminants (e.g., microplastics) in large rivers, which could be a promising tool for enhancing understanding of hydrological processes.
Jarvis-type model with a flexible parameterization of stress functions can improve the descriptions of physiological behaviour for specific vegetation species. However, it is criticized for the empirically formulated multiplicative equation that can deviate from the mutual impact of intercorrelated stress factors, e.g., vapor pressure deficit (VPD) and air temperature ( Ta). This study proposed a modified Jarvis model by adding reduction factors in the stress functions of VPD and Ta to provide a better description of stomatal conductance. The sap flow data of transpiration rate in a beech forest in the mid-latitude of Centre Europe was used to inversely estimate the stomatal conductance, which facilitated the formulation of stress functions. Taking two recommended parameterization strategies for general deciduous broadleaf forest (DBF) led to severe overestimation of transpiration rate with a maximum value of ~2 mm/day in rainless days, which suggested that the beech forest had rather different stomatal response. With the parameterization using boundary analysis, the unmodified and modified Jarvis model provided the better simulation of transpiration with NSE values of 0.75 and 0.77. The results suggested that modelling transpiration can be improved through a more specific parameterization of stomatal conductance, especially for a vegetation species featuring its own stomatal behaviour that differed from its belonged general vegetation type. Particularly, the modified Jarvis model can further improve the description of stomatal conductance and modelling of transpiration in vegetated areas, especially under dry environment conditions with relatively high VPD.
The catchment approach has been traditionally limited to small, experimental catchments where water fluxes can be determined with high accuracy. However, larger catchments where landscape management occurs have emergent drivers of streamflow at scale, and thus may exhibit novel responses to land cover disturbance. We used statistical models of water yield and annual maximum peak streamflow for multiple forested catchments in the low-relief glaciated region of central North America to investigate how forest disturbance may affect water yield and peak flows in similar landscapes. We utilized linear models, linear mixed effects models, and probabilistic flood-frequency analysis, with Bayesian parameter estimation in two case studies in Minnesota, USA: 1) a wildfire comprising ~30% of a 650km 2 wilderness Upper Kawishiwi catchment, and 2) 11 catchments within the St. Louis River Basin ranging from 56 to 8,880 km 2 with a patchwork disturbance regime wherein ~0.25% to 1% of the catchment is harvested or converted to non-forest land use each year. We also assessed for the most likely hydrological recovery year after forest disturbance, and the relative importance of stationary and nonstationary drivers of streamflow. We found forest disturbance correlated with declines in water yield for low-level disturbance regimes, but that water yield increased in response to the large-scale wildfire. Positive and negative associations of forest disturbance with peak flows were observed, generally with low confidence. Hydrologic recovery time ranged from 5 to 12 years for water yield and peak flows following disturbance. Despite these effects of forest disturbance on streamflow, effects of climate variability and stationary catchment size factors were more prominent drivers of streamflow. Basins larger than ~50 km 2 in low-relief glaciated regions were resilient to forest cover change when it comprised <30% of basin area, but climate change may have a larger effect than could be mitigated by land management.
Rapid urbanization and global climate change are likely to exacerbate urban flooding intensity, frequency, and uncertainty. Thus, it is fundamental and crucial to investigate the dominant influencing factors for the mitigation of urban flooding. However, the influence of building patterns on urban flooding remains limited. Taking Beijing, a typical megacity, as a case study area, we quantified the importance of building patterns and their interaction effect at the subwatershed scale using the boosted regression tree (BRT) and geographical detector model (GeoD). The results indicated that (1) the landscape shape index, slope, green space ratio and waterbody ratio were the most important influencing factors determining urban flooding, with a total relative contribution of 67.23%, (2) building metrics had a certain impact on urban flooding, and the sum of the relative contribution can reach 21.03%, (3) with urban flooding density, the landscape shape index, slope, and green space ratio exhibited a combination of negative and positive correlation, and (4) an enhancement effect existed between building metrics, especially the building congestion degree and building density. These findings provide quantitative insights that rational urban morphology planning can improve stormwater management and promote urban sustainability in megacities.
Estimating of soil sorptivity ( S ) and saturated hydraulic conductivity ( K s ) parameters by field infiltration tests are widespread due to the ease of the experimental protocol and data treatment. The analytical equation proposed by Haverkamp et al. (1994) allows the modeling of the cumulative infiltration process, from which the hydraulic parameters can be estimated. This model depends on both initial and final values of the soil hydraulic conductivity, initial soil sorptivity, the volumetric water content increase ( ∆ θ ), and two infiltration constants, the so-called β and γ parameters. However, to reduce the number of unknown variables when inverting experimental data, constant parameters such as β and γ are usually prefixed to 0.6 and 0.75, respectively. In this study, the values of these constants are investigated using numerical infiltration curves for different soil types and initial soil water contents for the van Genuchten-Mualem (vGM) soil hydraulic model. Our approach considers the long-time expansions of the Haverkamp model, the exact soil properties such as S , K s , and initial soil moisture to derive the value of the β and γ parameters for each specific case. We then generated numerically cumulative infiltration curves using Hydrus 3-D software and fitted the long-time expansions to derive the value of the β and γ parameters. The results show that these parameters are influenced by the initial soil water content and the soil type. However, for initially dry soil conditions, some prefixed values can be proposed instead of the currently used values. If an accurate estimate of S and K s is the case, then for coarse-textured soils such as sand and loamy sand, we propose the use of 0.9 for both constants. For the remaining soils, the value of 0.75 can be retained for γ . For β constant, 0.75 and 1.5 values can be considered for, intermediate permeable soils (sandy loam and loam) and low permeable soils (silty loam and silt), respectively. We clarify that the results are based on using the vGM model to describe the hydraulic functions of the soil and that the results may differ, and the assumptions may change for other models.