Catchment Discharge Research Articles

Assessing Future hydrological response of an urban watershed using machine learning based LULC forecasting models

Urbanization in terms of land-use/cover (LULC) change has a long-term significant impact on the hydrological cycle as the LULC is one of the most important influencing parameters to produce curve number (CN). The drastic change in LULC changes the CN. This change directly affects surface water including peak flows. This study aims to assess the change in surface runoff due to changes in LULC. Hydrological modeling is done for the consistent long-term behavioral study of surface runoff. The area focused on the study is the Kharun river, a tributary of the Mahanadi River. For the assessment of the impact of LULC change on the catchment discharge, a daily-step conceptual model soil and water assessment tool (SWAT) was applied. Landuse maps were prepared with the Landsat Thematic Mapper satellite images. The future land use was forecasted with the technique of spatial statistical modeling. The machine learning (ML) tool is used for quantifying the influences on the LULC change dynamics and producing the LULC map for 2024 and 2030. Remote sensing (RS) and geographic information system (GIS) analysis were coupled with hydrological SWAT modeling to investigate the connection between the LULC change and hydrologic regime. The SWAT Model’s calibration efficiency is verified by comparing the simulated and observed discharge time series at the Patharidih gauge and discharge station. The monthly and daily calibrations were quite satisfactory, with Nash-Sutcliffe an efficiency coefficient of 0.86 and 0.67. This modeling provides reliable information for sustainable management of available water resources of the catchment.

Unveiling the future water pulse of central asia: a comprehensive 21st century hydrological forecast from stochastic water balance modeling

This study uses a new dataset on gauge locations and catchments to assess the impact of 21st-century climate change on the hydrology of 221 high-mountain catchments in Central Asia. A steady-state stochastic soil moisture water balance model was employed to project changes in runoff and evaporation for 2011–2040, 2041–2070, and 2071–2100, compared to the baseline period of 1979–2011. Baseline climate data were sourced from CHELSA V21 climatology, providing daily temperature and precipitation for each subcatchment. Future projections used bias-corrected outputs from four General Circulation Models under four pathways/scenarios (SSP1 RCP 2.6, SSP2 RCP 4.5, SSP3 RCP 7.0, SSP5 RCP 8.5). Global datasets informed soil parameter distribution, and glacier ablation data were integrated to refine discharge modeling and validated against long-term catchment discharge data. The atmospheric models predict an increase in median precipitation between 5.5% to 10.1% and a rise in median temperatures by 1.9 °C to 5.6 °C by the end of the 21st century, depending on the scenario and relative to the baseline. Hydrological model projections for this period indicate increases in actual evaporation between 7.3% to 17.4% and changes in discharge between + 1.1% to –2.7% for the SSP1 RCP 2.6 and SSP5 RCP 8.5 scenarios, respectively. Under the most extreme climate scenario (SSP5-8.5), discharge increases of 3.8% and 5.0% are anticipated during the first and second future periods, followed by a decrease of -2.7% in the third period. Significant glacier wastage is expected in lower-lying runoff zones, with overall discharge reductions in parts of the Tien Shan, including the Naryn catchment. Conversely, high-elevation areas in the Gissar-Alay and Pamir mountains are projected to experience discharge increases, driven by enhanced glacier ablation and delayed peak water, among other things. Shifts in precipitation patterns suggest more extreme but less frequent events, potentially altering the hydroclimate risk landscape in the region. Our findings highlight varied hydrological responses to climate change throughout high-mountain Central Asia. These insights inform strategies for effective and sustainable water management at the national and transboundary levels and help guide local stakeholders.

Potential Amplifiers of Hydrological Drought: A Deep Dive into the Seasonal Variations of New, Young, and Old Water Fractions in the Stream Discharge of a Pre-Alpine Catchment

This study examines runoff generation processes by focusing on new, young, and old water fractions in the stream discharge within the Swiss pre-Alpine Alp catchment and its smaller tributaries, Erlenbach and Vogelbach. Young water represents a contribution from the three most recent rainfall-runoff events. This research utilises a four-year time series of daily stable water isotope data from stream water and precipitation to investigate seasonal variations. An extended two-component hydrograph separation method is applied to analyse the catchment water and tracer mass balance across both the event and pre-event time axes. The calculated new, young and old water components in stream discharge help estimate time-varying backward travel time distributions. Factors such as air temperature, snow depth, and evapotranspiration data are considered to understand isotope fractionation because of phase changes. The results suggest that discharge generated in autumn and winter may have longer backward travel times compared with spring or summer discharge. Additionally, forest cover influences water fractions older than 40 days. The study identifies a nivo-pluvial runoff regime, with new water fractions peaking in August (Erlenbach, Vogelbach) and January (Alp). Young water fractions reach their highest levels at the start of winter and during snowmelt, while old water fractions peak towards the end of snowmelt and in mid-autumn. The Alp catchment and its tributaries exhibit higher new and young water components than old water following a month of low precipitation and high evapotranspiration in July. These findings are significant in light of the projected drier summers in Central Europe.

How do different runoff generation mechanisms drive stream network dynamics? Insights from physics‐based modelling

AbstractNon‐perennial river catchments are characterized by an ever‐changing spatial configuration of their flowing streams. A combination of empirical data and simplified analytical frameworks has been frequently used in the literature to analyse the co‐evolution of the total active stream length () and the catchment discharge at the outlet (). However, despite the increasing availability of field data, understanding how runoff generation processes drive the spatio‐temporal dynamics of non‐perennial river reaches remains challenging. In this paper we use CATHY, an integrated surface–subsurface hydrological model (ISSHM), to investigate the impact of saturation‐excess (Dunnian) and infiltration‐excess (Hortonian) runoff generation on the stream network dynamics of two virtual catchments with spatially homogeneous subsurface properties but different morphology. The numerical simulations show that when surface runoff is triggered by saturation‐excess mechanisms, the subsurface domain is slowly saturated, and the stream network gradually expands upstream from the outlet towards the catchment divides. In these conditions, the specific inflow per unit contributing area is relatively uniform along the network, thereby implying that and display a monotonically increasing one‐to‐one relationship. On the other hand, infiltration‐excess mechanisms lead to more heterogeneous saturation patterns in the subsurface domain. In particular, during the wetting phase, Hortonian processes originate highly transient conditions and a non‐uniform spatial distribution of the specific inflow along the stream network. This is reflected by a hysteretic relation and a marked asymmetry between the wetting and drying phases of the event. The application of an ISSHM proved to be a useful tool to elucidate the processes that drive stream network expansion and retraction in non‐perennial rivers.

Optimal control strategies for stormwater detention ponds

Stormwater detention ponds are essential stormwater management solutions that regulate the urban catchment discharge towards streams. Their purposes are to reduce the hydraulic load to avoid stream erosion, as well as to minimize the degradation of the natural waterbody by direct discharge of pollutants. Currently, static controllers are widely implemented for detention pond outflow regulation in engineering practice, i.e., the outflow discharge is capped at a fixed value. Such a passive discharge setting fails to exploit the full potential of the overall water system, hence further improvements are needed. We apply formal methods to synthesize (i.e., derive automatically) optimal active controllers. We model the stormwater detention pond, including the urban catchment area and the rain forecasts with its uncertainty, as hybrid Markov decision processes. Subsequently, we use the tool UppaalStratego to synthesize using Q-learning a control strategy maximizing the retention time for pollutant sedimentation (optimality) while also minimizing the duration of emergency overflow in the detention pond (safety). These strategies are synthesized for both an off-line and on-line settings. Simulation results for an existing pond show that UppaalStratego can learn optimal strategies that significantly reduce emergency overflows. For off-line controllers, a scenario with low rain periods shows a 26% improvement of pollutant sedimentation with respect to static control, and a scenario with high rain periods shows a reduction of overflow probability of 10%–19% for static control to lower than 5%, while pollutant sedimentation has only declined by 7% compared to static-control. For on-line controllers, one scenario with heavy rain shows a 95% overflow duration reduction and a 29% pollutant sedimentation improvement compared to static control.

Assessing Climate-Change-Driven Impacts on Water Scarcity: A Case Study of Low-Flow Dynamics in the Lower Kalu River Basin, Sri Lanka

The adverse impacts of climate change are becoming more frequent and severe worldwide, and Sri Lanka has been identified as one of the most severely affected countries. Hence, it is vital to understand the plausible climate-change-driven impacts on water resources to ensure water security and socio-economic well-being. This study presents novel assessments on low-flow dynamics along the lower Kalu River Basin, Sri Lanka, and water availability during the dry spells of the 2030–2060 period. Bias-corrected daily precipitation projections of a high resolution (25 km × 25 km) NCC-NORESM1-M regional climate model is used here to force a calibrated HEC-HMS hydrological model to project catchment discharge during the future period considered under the two end-member Representative Concentration Pathways (i.e., RCP 2.6 and RCP 8.5). Our results show that the study area (i.e., Kuda Ganga sub-basin) may become warmer (in non-monsoonal periods) and wetter (in monsoon season) under both scenarios during the near future (2030–2040) when compared to the baseline period (1976–2005) considered. Consequently, the streamflow may reduce, making it the decade with the largest water deficit within the time horizon. The subsequent deficit volume assessment for the 2031–2040 period shows a probable water shortage (~5 million m3) under the RCP 2.6 scenario, which may last for ~47 days with an average daily intensity of 105,000 m3. Our results highlight the need of incorporating climate-change-driven impacts in water resources management plans to ensure water security.

The Alteration of Flood Peak Discharge by Land Cover Change in Prek Thnot Watershed, Kampong Speu Provine, Cambodia

This study analyses the alterations of peak catchment runoff from Prek Thnot watershed using the Soil Conservation Service Curve Number (SCS-CN) methodology. Two major studies using different approaches have previously been conducted in the catchment, albeit producing inconsistent results. The Snowy Mountain Hydro-electric Authority published the first study in 1967 and found that the peak surface flow runoff over a 10-year return period was 710 m3/s. The second study was conducted by the Japanese International Cooperation Agency (JICA) between 1991 and 2006 and reported a peak catchment discharge of 1,380 m3/s. To date, there has been no discussion comparing the two studies to determine why the discharge during the later study was double that of the first. As the annual rainfall during the two study periods was similar, it is suggested that this discrepancy may be attributed to physical changes in the watershed, such as changes to forest cover. We deployed the Hydrologic Engineering Centre-Hydrologic Modeling System to simulate the peak runoff of the catchment. Our result was very similar to the JICA finding. Our data suggested that the increase in catchment discharge may be attributed to the conversion of 26% of forest cover in the catchment to agricultural land since the early 2000s. This information is useful for flood management practices, particularly with respect to managing catchment runoff in the context of rapid deforestation and the hydrological impacts of climate change within the watershed. The paper analyzes the impact of land-use changes on catchment runoff and provides valuable insights for flood management practices in the context of climate change and deforestation.

Increasing spruce budworm defoliation increases catchment discharge in conifer forests

Forest insect outbreaks cause significant reductions in the forest canopy through defoliation and tree mortality that modify the storage and flow of water, potentially altering catchment runoff and stream discharge patterns. Despite a growing understanding of the impacts of insect outbreaks on the hydrology of broadleaf forests, little is known about these impacts to catchment hydrology in northern conifer-dominated forests. We measured the effects of cumulative defoliation by spruce budworm (Choristoneura fumiferana) on stream discharge and runoff in 12 experimental catchments (6.33–9.85 km2) across the central Gaspé Peninsula in eastern Québec, Canada over a three-year period (2019–2021). Six catchments were aerially treated with BtK (Bacillus thuringiensis kurstaki) insecticide to suppress the outbreak and six catchments were left untreated, leading to a defoliation gradient across the study sites. Stage-discharge relationships were established between June and October from 2019 to 2021. Stream volumetric discharge (r = 0.71, p < 0.01, t(34) = 5.85), runoff (r = 0.55, p < 0.01, t(34) = 3.81) and runoff ratios (r = 0.67, p < 0.01, t(33) = 5.19) were all strongly positively correlated with cumulative defoliation intensity, likely by reducing available water storage in the catchment and therefore enhancing runoff generation. Seasonally, volumetric discharge, runoff, and runoff ratios were more strongly correlated with defoliation in the summer than autumn months, likely because available catchment storage was more limited following the freshet. Overall, we found that insect defoliation impacts forested catchment hydrology similar to other landscape disturbances, and such consequences should be considered in forest management and the control of forest insect outbreaks.

Nonstationary frequency analysis and uncertainty quantification for extreme low lake levels in a large river-lake-catchment system

Extreme hydrological events have become increasingly frequent on a global scale. The middle Yangtze River also faces a substantial challenge in dealing with extreme flooding and drought. However, the long-term characteristics of the extreme hydrological regime have not yet been adequately recognized. Moreover, there is uncertainty in the extreme value estimation, and this uncertainty needs to be distinguished and quantified. In this study, we investigated the nonstationary frequency characteristics of extreme low lake levels (ELLLs), taking the Poyang Lake as an example. Daily lake levels from 1960 to 2022 were utilized to estimate the return level using the generalized Pareto distribution (GPD). The uncertainty from three sources, i.e., the parameter estimator, threshold selection, and covariate, was quantified via variance decomposition. The results indicate that (1) the parameter estimator is the predominant source of uncertainty, with a contribution rate of approximately 87 %. The total uncertainty of the covariate, threshold, and interaction term is only 13 %. (2) Two indexes, namely the annual minimum water level (WLmin) and the days with peak over the 90 % threshold per year (DPOT90), decreased (0.01–0.03 m/year) and increased (0.17–1.39 days/year), respectively, indicating a progressively severe drought trend for Poyang Lake. (3) The return level with return period of 5 to 100 years significantly decreased after the early 21st century. A large spatial heterogeneity was identified for the variation in the return level, and the change rate of the return level with a 100-year return period ranged from 5 % to 40 % for the whole lake. (4) The ELLLs had a stronger correlation with the catchment discharge than with the Yangtze River discharge and the large-scale atmospheric circulation indices. This study provides a methodology with reduced uncertainty for nonstationary frequency analysis (NFA) of ELLLs exemplified in large river–lake systems.

Contrasting hydrological responses to climate change in two adjacent catchments dominated by karst and nonkarst

Karst systems are well-known for their special features, such as epikarst zone and quick flow, compared to other hydrological systems. However, few studies explored the difference in hydrological responses to climate change between karst and nonkarst catchments. In this paper, two adjacent catchments dominated by karst and nonkarst in Southwest China (subtropical monsoon climate) were selected to investigate their different hydrological behaviors under future climates. To account for potential model structure uncertainties, three different karst hydrological models and three traditional catchment models were used to simulate these two catchments. The results demonstrate that different models yield comparable streamflow simulations within each catchment, allowing for the focus to be on the impact of climate change and catchment hydrological characteristics. The karst-dominated catchment is modeled to have larger actual evapotranspiration (AET) than the nonkarst-dominated catchment under similar climate conditions, with the AET of the former being more sensitive to changes in precipitation and potential evapotranspiration. These differences are primarily due to the presence of the epikarst in the unsaturated zone of the karst system, which can store more infiltration rainwater for evapotranspiration. Both catchments are expected to experience a wetter projection in the wet season and a drier projection in the dry season in the future. However, the karst-dominated catchment will face a drier climate with a significant increase in precipitation in just two months (July and August). Additionally, because of a higher sensitivity of monthly AET to climate change, the karst-dominated catchment will experience a greater monthly discharge reduction in the first two wet months (April and May), a relatively lower discharge increase in other wet months, and a lower monthly discharge in dry months, while the monthly discharge of the nonkarst-dominated catchment increases in the wet season and decrease in the dry season. Furthermore, the karst-dominated catchment will have a much lower annual discharge than the nonkarst-dominated catchment, particularly during extremely dry years in the future period due to its larger AET consumption. These all suggest that the karst-dominated catchment will be more vulnerable to droughts. Overall, due to the drier climate and the different hydrological backgrounds of the karst-dominated catchment, it is expected to have much drier hydrological conditions in the future compared to the nonkarst-dominated catchment.

Understanding groundwater storage and drainage dynamics of a high mountain catchment with complex geology using a semi-distributed process-based modelling approach

Mountainous groundwater systems are usually characterized by great geological complexity and highly heterogeneous hydraulic properties. For that reason, proper system characterization, monitoring and modelling remain challenging. In this study, we investigated a geologically complex alpine catchment (from 1400 to 2900 m asl) in the Dolomites (Italian Alps) by combining hydrogeological field investigation, hydrological monitoring and modelling. A semi-distributed process-based hydrological model was applied to simulate the continuous measured catchment discharge in a period of three years, which covers a large variation of hydrodynamic conditions. The model structure couples the sequential hydrogeological units within the studied catchment: (1) the fractured dolomitic rocks as bedrock aquifer and 2) the unconsolidated deposits accumulating on the slopes and at the valley floor as porous aquifer. In order to evaluate the model structure and parameterization in depth, we applied a multi-step evaluation approach considering both parameter sensitivity and uncertainty. The modelling results demonstrate that the newly developed model can reproduce most discharge behavior of aquifers. The model indicates a seasonal dynamic linkage between surface and subsurface storage units during different flow conditions. Besides the matrix and conduit flow in fractured dolomitic aquifer, it highlights the important role of unconsolidated sediments (porous aquifer) to the storage and discharge behavior of the entire groundwater system. Furthermore, with the comprehensive model evaluation we learned the model performance deficit during extreme high flow conditions and proposed a more detailed hydrogeological conceptual model. We believe that the proposed modelling approach can be transferred to other high mountain catchments with similar hydro(geo)logical characteristics to characterize the collective behavior of aquifer systems, explore conceptual model weakness and optimize catchment monitoring work.

Most Global Gauging Stations Present Biased Estimations of Total Catchment Discharge

AbstractStream gauging stations provide critical streamflow measurements for hydrological applications; however, they may not accurately capture total catchment discharge due to unmonitored regional groundwater flow. Here, we evaluate the effectiveness of streamflow data from gauging stations worldwide to represent total catchment discharge through a modified hydrological model that includes baseflow signatures to constrain groundwater flow processes. We find that approximately 70% of gauging stations present biased estimations of total catchment discharge (bias &gt;10%). This result implies that hydrology‐related processes may not be fully understood, and misleading conclusions may be drawn owing to the low streamflow measurement effectiveness. By influencing subsurface hydrological processes, catchment factors, including catchment area, topography, climate, and geological features, are linked to the effectiveness of streamflow measurements. Our findings highlight the importance of accurate streamflow measurement effectiveness for obtaining a reliable understanding of catchment hydrological processes to support sustainable water resource management.

Per- and polyfluoroalkyl substances (PFAS) contamination in a microtidal urban estuary: Sources and sinks

This study evaluates PFAS contamination and determines the major drainage sources to a temperate microtidal estuary, the Swan Canning Estuary, in Perth Western Australia. We describe how variability in these sources influences PFAS concentrations within this urban estuary. Surface water samples were collected from 20 estuary sites and 32 catchment sites in June and December from 2016 to 2018. Modelled catchment discharge was used to estimate PFAS load over the study period. Three major catchment sources of elevated PFAS were identified with contamination likely resulting from historical AFFF use on a commercial airport and defence base. Estuary PFAS concentration and composition varied significantly with season and spatially with the two different estuary arms responding differently to winter and summer conditions. This study has found that the influence of multiple PFAS sources on an estuary depend on the historical usage timeframe, groundwater interactions and surface water discharge.

Assessing the Impacts of Land Use and Climate Changes on River Discharge towards Lake Victoria

The Lake Victoria basin’s expanding population is heavily reliant on rainfall and river flow to meet their water needs, making them extremely vulnerable to changes in climate and land use. To develop adaptation and mitigation strategies to climate changes it is urgently necessary to evaluate the impacts of climate change on the quantity of water in the rivers that drain into Lake Victoria. In this study, the semi-distributed hydrological SWAT model was used to evaluate the impact of current land use and climate changes for the period of 1990–2019 and assess the probable future impacts of climate changes in the near future (2030–2060) on the Simiyu river discharge draining into Lake Victoria, Northern Tanzania. The General Circulation Model under RCPs 4.5, 6.0 and 8.5 predicted an increase in the annual average temperature of 1.4 °C in 2030 to 2 °C in 2060 and an average of 7.8% reduction in rainfall in the catchment. The simulated river discharge from the hydrological model under RCPs 4.5, 6.0 and 8.5 revealed a decreasing trend in annual average discharge by 1.6 m3/s from 5.66 m3/s in 2019 to 4.0 m3/s in 2060. The increase in evapotranspiration caused by the temperature increase is primarily responsible for the decrease in river discharge. The model also forecasts an increase in extreme discharge events, from a range between 32.1 and 232.8 m3/s in 1990–2019 to a range between 10.9 and 451.3 m3/s in the 2030–2060 period. The present combined impacts of climate and land use changes showed higher effects on peak discharge at different return periods (Q5 to Q100) with values of 213.7 m3/s (Q5), 310.2 m3/s (Q25) and 400.4 m3/s (Q100) compared to the contributions of climate-change-only scenario with peak discharges of 212.1 m3/s (Q5), 300.2 m3/s (Q25) and 390.2 m3/s (Q100), and land use change only with peak discharges of 295.5 m3/s (Q5), 207.1 m3/s Q25) and 367.3 m3/s (Q100). However, the contribution ratio of climate change was larger than for land use change. The SWAT model proved to be a useful tool for forecasting river discharge in complex semi-arid catchments draining towards Lake Victoria. These findings highlight the need for catchment-wide water management plans in the Lake Victoria Basin.

Incorporating experimentally derived streamflow contributions into model parameterization to improve discharge prediction

Abstract. Environmental tracers have been used to separate streamflow components for many years. They allow us to quantify the contribution of water originating from different sources, such as direct runoff from precipitation, subsurface storm flow, or groundwater to total streamflow at variable flow conditions. Although previous studies have explored the value of incorporating experimentally derived fractions of event and pre-event water into hydrological models, a thorough analysis of the value of incorporating hydrograph-separation-derived information on multiple streamflow components at varying flow conditions into model parameter estimation has not yet been performed. This study explores the value of such information to achieve more realistic simulations of catchment discharge. We use a modified version of the process-oriented HBV model that simulates catchment discharge through the interplay of hillslope, riparian-zone discharge, and groundwater discharge at a small forested catchment which is located in the mountainous north of South Korea, subject to a monsoon season between June and August. Applying a Monte-Carlo-based parameter estimation scheme and the Kling–Gupta efficiency (KGE) to compare discharge observations and simulations across two seasons (2013 and 2014), we show that the model is able to provide accurate simulations of catchment discharge (KGE ≥ 0.8) but fails to provide robust predictions and realistic estimates of the contribution of the different streamflow components. Using a simple framework that compares simulated and observed contributions of hillslope, riparian zone, and groundwater to total discharge during two sub-periods, we show that the precision of simulated streamflow components can be increased, while remaining with accurate discharge simulations. We further show that the additional information increases the identifiability of all model parameters and results in more robust predictions. Our study shows how tracer-derived information on streamflow contributions can be used to improve the simulation and predictions of streamflow at the catchment scale without adding additional complexity to the model. The complementary use of temporally resolved observations of streamflow components and modeling provides a promising direction to improve discharge prediction by representing model internal dynamics more realistically.

Ensemble Evaluation and Member Selection of Regional Climate Models for Impact Models Assessment

Climate change increasingly is affecting every aspect of human life on the earth. Many regional climate models (RCMs) have so far been developed to carefully assess this important phenomenon on specific regions. In this study, ten RCMs captured from the European Coordinated Downscaling Experiment (EURO CORDEX) platform are evaluated on the river Chiese catchment located in the northeast of Italy. The models’ ensembles are assessed in terms of the uncertainty and error calculated through different statistical and error indices. The uncertainties are investigated in terms of signal (increase, decrease, or neutral changes in the variables) and value uncertainties. Together with the spatial analysis of the data over the catchment, the weighted averaged values are used for the models’ evaluations and data projections. Using weighted catchment variables, climate change impacts are assessed on 10 different hydro-climatological variables showing the changes in the temperature, precipitation, rainfall events’ features, and the hydrological variables of the Chiese catchment between historical (1991–2000) and future (2071–2080) decades under RCP (Representative Concentration Path for increasing greenhouse gas emissions) scenario 4.5. The results show that, even though the multi-model ensemble mean (MMEM) could cover the outputs’ uncertainty of the models, it increases the error of the outputs. On the other hand, the RCM with the least error could cause high signal and value uncertainties for the results. Hence, different multi-model subsets of ensembles (MMEM-s) of 10 RCMs are obtained through a proposed algorithm for different impact models’ calculations and projections, making tradeoffs between two important shortcomings of model outputs, which are error and uncertainty. The single model (SM) and multi-model (MM) outputs imply that catchment warming is obvious in all cases and, therefore, evapotranspiration will be intensified in the future where there are about 1.28% and 6% value uncertainties for monthly temperature increase and the decadal relative balance of evapotranspiration, respectively. While rainfall events feature higher intensity and shorter duration in the SM, there are no significant differences for the mentioned features in the MM, showing high signal uncertainties in this regard. The unchanged catchment rainfall events’ depth can be observed in two SM and MM approaches, implying good signal certainty for the depth feature trend; there is still high uncertainty about the depth values. As a result of climate change, the percolation component change is negligible, with low signal and value uncertainties, while decadal evapotranspiration and discharge uncertainties show the same signal and value. While extreme events and their anomalous outcomes direct the uncertainties in rainfall events’ features’ values towards zero, they remain critical for yearly maximum catchment discharge in 2071–2080 as the highest value uncertainty is observed for this variable.

Resolving streamflow diel fluctuations in a small agricultural catchment with an integrated surface‐subsurface hydrological model

AbstractDuring dry periods, stream discharge in vegetated catchments can naturally fluctuate up to 10% daily. Despite intensive efforts put in observing and interpreting diel fluctuations of stream discharge across a range of instrumented natural catchments worldwide, the capability of state‐of‐the‐art hydrological models to reproduce and explain such processes has rarely been tested. Here, we used CATHY, a physics‐based integrated surface‐subsurface hydrological model (ISSHM), to simulate the stream discharge in a small tile‐drained agricultural catchment in Switzerland, where streamflow diel fluctuations appeared in dry periods. The model was able to satisfactorily reproduce the measured stream discharge, including the observed diel fluctuations. Next, we designed and simulated a series of modelling scenarios aimed to disentangle the processes contributing to the diel fluctuations in stream discharge. These scenarios revealed the predominant role of evapotranspiration (ET) in the establishment of diel fluctuations in stream discharge. Irrigation sustained the baseflow in dry periods and caused short‐living streamflow peaks, which did not directly cause, but superposed to, diel patterns. Vegetation rooting depths and response to oxygen stress in the root zone slightly affected the amplitude of the streamflow diel fluctuations, while changes in the saturated hydraulic conductivity driven by diel soil temperature fluctuations caused an amplitude of the streamflow diel signal 10 times smaller compared to the one caused by ET. Our study demonstrates that ISSHMs such as CATHY can provide high‐fidelity spatially‐distributed dynamic simulations of evapotranspiration and irrigation fluxes, as well as soil moisture and groundwater flows, enhancing our understanding of the role of these hydrological processes during dry periods and thus making these models useful tools for a more sustainable management of agricultural catchments.

Wavelet analysis of hydro-climatic time-series and vegetation trends of the Upper Aragón catchment (Central Spanish Pyrenees)

Water managers and researchers noted with concern a nearly generalized decline in Mediterranean rivers discharge over the last decades. Changes in climatic forces (precipitation and air temperature) and land use and land cover (LULC) changes characterized by re-vegetation and greenness are the two most possible explanations for this discharge decline. The direct impact on river discharge stemming from these changes is difficult to assess and their role is generally studied separately. Here, we use the method of wavelet transformation to interpret the time-scale dependency of catchment discharge concerning the uneven temporal climatic fluctuations and re-vegetation processes. We analyzed the temporal variation of concurrent air temperature, precipitation and river discharge time-series for the Upper Aragón catchment, located in the Central Spanish Pyrenees. A long-term database collected over 60 years (1956–2020) was used. Land cover maps corresponding to different decades were used and the results indicated that the catchment experienced a significant increase in the area covered by mixed and broadleaf forests, mostly as a consequence of land abandonment. We show how temperature slightly increased and precipitation moderately decreased. However, catchment discharge experienced a sharp decline in its magnitude and also changes in its temporal variability dynamics. The relevance of the seasonal time-scales with regard to the available discharge is reduced, which strengthens the importance of the inter-annual time-scales for the catchment discharge dynamics. Furthermore, the catchment storage-discharge cycle at inter-annual time-scales is also reduced. Such changes can mostly be attributed to the changes in plant coverage, with an increasing weight in shaping hydrological processes at catchment scale due to the greenness effect. As such, we conclude that LULC changes have played a dominant role on the river discharge dynamics. Climatic trends, on the contrary, have been small, and they have played a secondary role in the decline of river discharge. Future research can use these observations to constrain the pace of upcoming water demands based on the available water resources at Mediterranean catchment scale.

Warming-induced monsoon precipitation phase change intensifies glacier mass loss in the southeastern Tibetan Plateau

Glaciers are key components of the mountain water towers of Asia and are vital for downstream domestic, agricultural, and industrial uses. The glacier mass loss rate over the southeastern Tibetan Plateau is among the highest in Asia and has accelerated in recent decades. This acceleration has been attributed to increased warming, but the mechanisms behind these glaciers' high sensitivity to warming remain unclear, while the influence of changes in precipitation over the past decades is poorly quantified. Here, we reconstruct glacier mass changes and catchment runoff since 1975 at a benchmark glacier, Parlung No. 4, to shed light on the drivers of recent mass losses for the monsoonal, spring-accumulation glaciers of the Tibetan Plateau. Our modeling demonstrates how a temperature increase (mean of 0.39 ∘C ⋅dec-1 since 1990) has accelerated mass loss rates by altering both the ablation and accumulation regimes in a complex manner. The majority of the post-2000 mass loss occurred during the monsoon months, caused by simultaneous decreases in the solid precipitation ratio (from 0.70 to 0.56) and precipitation amount (-10%), leading to reduced monsoon accumulation (-26%). Higher solid precipitation in spring (+18%) during the last two decades was increasingly important in mitigating glacier mass loss by providing mass to the glacier and protecting it from melting in the early monsoon. With bare ice exposed to warmer temperatures for longer periods, icemelt and catchment discharge have unsustainably intensified since the start of the 21st century, raising concerns for long-term water supply and hazard occurrence in the region.

Impact of climate and NDVI changes on catchment storage–discharge dynamics in southern Taiwan

This study used streamflow recession analysis to assess the changes in the groundwater–streamflow relationships using streamflow data. The groundwater response to climate and Normalized Difference Vegetation Index (NDVI) changes was considered as a variable in the recession analysis. The integrated impact could thus be compared to assess the consistency of these effects on the catchment discharge processes. The results showed that the recession characteristics is linked to regional topography and streamflow condition. Variation of storage–discharge sensitivities in most catchments was not linked to the variation of groundwater due to the lower capacity of groundwater contribution. The quantified impacts aided in assessing the relationship between climate, land cover, groundwater storage and discharge. This study provides a simple explanation of effects of environmental coevolution on storage–discharge processes.