Annual Water Research Articles

First full-scale application of barium carbonate as an effective dispersed alkaline substrate for sulfate removal from acid mine drainage

A full-scale passive treatment plant using barium carbonate (BaCO3), the mineral witherite, as a Dispersed Alkaline Substrate (DAS) for strongly contaminated acid mine drainage was implemented for the first time globally at Mina Concepción, located in the Iberian Pyrite Belt (SW Spain). The plant was monitored over a 105-day period, covering the wettest months of the hydrological year and with a mean flow around 4 L s−1. The AMD treated in the plant exhibits a high strength, with an average sulfate concentration around 1500 mg L−1 and net acidity close to 1000 mg L−1 as CaCO₃ equivalent. According to the above, the loading rate for SO4 and Fe was around 400 and 80 kg day−1, respectively. The treatment process produced an alkaline effluent with low metal content. Nearly complete removal of most metal(loid)s was achieved, with significant sulfate decrease to below 500 mg L−1 in the alkaline outflow of the barium carbonate tank. Barium carbonate demonstrated superior performance compared to magnesia, particularly in enhancing alkalinity and lowering net acidity and concentrations of sulfate and manganese. The high efficiency attained by the plant after the barium carbonate treatment is evidenced by compliance with environmental water quality standards for most contaminants.

Characteristics of deep soil layer water deficit under different artificial vegetation types of the Loess Plateau, China

AbstractSoil water is a crucial factor for the growth of vegetation and sustainable development in water‐limited areas. After large‐scale vegetation restoration on the Chinese Loess Plateau, understanding the relationship between vegetation and deep soil moisture has become a crucial focus in current research. In this study, artificial forest (Pinus tabulaeformis [PT], Robinia pseudoacacia [RP] and Platycladus orientalis [PO]), apple orchard (AO), secondary forest (SF) and farmland (FL) were selected as the research objects, and grassland (GL) as the control, using soil‐drilling techniques. We systematically monitored the soil water content of 0–10 m soil layer over two hydrological years, and explored the effects of different vegetation types on soil water deficiency. The results showed that: (1) The deep soil water various significantly among different vegetation types. Compared with GL, the soil water content in all forest land was generally lower, and this difference became more pronounced in deeper soil layer (>7 m), which indicating the depth of the influence of vegetation on soil water has reached 10 m. (2) The mean soil water deficit size (SWDS) values of PT (0.14), RP (0.17), PO (0.07), AO (0.15), SF (0.10) and FL (0.27) in 0–1 m were all positive, indicating that surface soil water had accumulated during more than half of the sampling periods. In the 2–10 m soil layer, mean SWDS was negative in all vegetation types except in FL, leading to soil desiccation. SWDS was found to fluctuate with soil depth. (3) SWDS was affected by a combination of soil properties and vegetation growth. Our results indicate that the current afforestation model could lead to the deficiency of deep soil water. Therefore, it is imperative to make reasonable vegetation structure according to the available local soil and water resources in future vegetation allocation and management.

Spatio-temporal variability of precipitation from 1980 to 2021 within the Oum Er Rbia hydraulic basin (Morocco)

Abstract The aim of this work is to assess the spatio-temporal variability of the mean annual rainfall during the last four decades within the Oum Er Rbia hydraulic basin. The used database in this study consists with a series of rainfall data at different time scale. These data were subjected to statistical and cartographic analysis. The obtained results show that, during the period of 1980-2021, interannual variability marked the evolution of annual rainfall averages. Furthermore, this variability is characterized by alternating sequences of dry and wet seasons. From the hydrological year of 2015, a general decreasing trend of rainfall has clearly marked and observed. Rainfall patterns in the Oum Er Rbia basin are also characterized by spatial variability. Interannual averages vary considerably from one catchment to another. The upstream part of the basin receives the most amount of rainfall. By contrast, the middle of the basin is the driest. The recent drop in precipitation has had a negative impact on the basin’s territory, most notably on water resources and agriculture.

Energy‐Water Asynchrony Principally Determines Water Available for Runoff From Snowmelt in Continental Montane Forests

ABSTRACTChanges in the volume, rate, and timing of the snowmelt water pulse have profound implications for seasonal soil moisture, evapotranspiration (ET), groundwater recharge, and downstream water availability, especially in the context of climate change. Here, we present an empirical analysis of water available for runoff using five eddy covariance towers located in continental montane forests across a regional gradient of snow depth, precipitation seasonality, and aridity. We specifically investigated how energy‐water asynchrony (i.e., snowmelt timing relative to atmospheric demand), surface water input intensity (rain and snowmelt), and observed winter ET (winter AET) impact multiple water balance metrics that determine water available for runoff (WAfR). Overall, we found that WAfR had the strongest relationship with energy‐water asynchrony (adjusted r2 = 0.52) and that winter AET was correlated to total water year evapotranspiration but not to other water balance metrics. Stepwise regression analysis demonstrated that none of the tested mechanisms were strongly related to the Budyko‐type runoff anomaly (highest adjusted r2 = 0.21). We, therefore, conclude that WAfR from continental montane forests is most sensitive to the degree of energy‐water asynchrony that occurs. The results of this empirical study identify the physical mechanisms driving variability of WAfR in continental montane forests and are thus broadly relevant to the hydrologic management and modelling communities.

Towards a new generation of fluvial facies models for the interpretation of ancient deposits, based on inter‐annual peak discharge variance of modern rivers

ABSTRACTFluvial facies models based on river planform are flawed and not fully fit for purpose. An alternative approach to classifying fluvial deposits is based on river discharge characteristics. A recent paper showed that the co‐efficient of variance of annual peak discharge (CVQp) correlates well with the characteristics of preserved alluvium for a suite of modern rivers. Here, the database of rivers is expanded and augmented, and the utility of this statistic confirmed. For modern rivers, plotting the running‐value of CVQp for a set interval (for example, 30 years) over a longer discharge record shows that the statistic varies both spatially and temporally. The CVQp can rise abruptly at a given location in response to a single flow event if that event is significantly larger than is common in that river. Such abrupt changes in CVQp are superimposed on longer‐term patterns of more gradual change stimulated by environmental factors or anthropogenic effects such as dam construction. If the period of calculation for CVQp is relatively short, ‘anomalous’ events appear more frequently. Sequential studies of modern rivers indicate that such anomalous events have a high probability of being preserved in the alluvial record of the river, and suggest that, over the timeframes of channel filling and abandonment, they may constitute the dominant (characteristic) portion of the record in high CVQp systems. Since flow events with strongly peaked hydrographs (flashy discharges) are more common in high CVQp systems and leave a record dominated by upper flow regime stratification styles, it follows that the alluvial record of high CVQp rivers will be dominated by upper flow regime stratification. In contrast, in lower CVQp systems the occurrence of an event that changes the running CVQp value significantly may form a distinct event deposit, and the temporarily changed CVQp is unrepresentative for the duration of the channel's life. The dominance of upper flow regime stratification, together with decreased preservation of identifiable macroform structure, increased lateral lithological heterogeneity, and in many cases increased preservation of in situ tree fossils in channel deposits of higher CVQp rivers, forms the basis for a series of new facies models for low, moderate, high and very high/ultra‐high CVQp alluvial systems and deposits. The new models can be applied to ancient successions either in combination with traditional, planform‐based models, or not. These models provide information about ancient palaeoenvironmental conditions, and changes in such conditions over time at various scales via stratigraphic investigations.

Is digitalization essential for abating carbon emission growth in South Asia?

Output generation processes across South Asia are deemed unclean (highly emission-intensive) due to excessive reliance on fossil fuels. Thus, decarbonizing the growth processes within this region has critical emphasis among policymakers. However, since the South Asian countries are yet to be ready to undergo the renewable energy transition, it is unlikely that “their annual carbon discharge levels will subside” anytime soon. Under such circumstances, these countries need to limit the rate at which their carbon emission levels rise each year. Therefore, the impacts of digitalization on annual carbon emission growth rates in selected South Asian countries are assessed in this study. Overall, considering internet penetration rate as a proxy of digital technology adoption, the results confirm that policies aimed at digitalizing the concerned South Asian economies not only exert emission growth rate-reducing impacts via a direct channel, but also indirectly reduce emission growth rates by making natural resources sectors more productive, expediting the energy sector greening processes, greening the financial sectors, making corruption controlling measures within institutions more effective, and limiting urbanization-induced environmental quality-worsening effects. Therefore, it is relevant for the South Asian government to emphasize on digitalization while simultaneously ensuring that green digital technologies are adopted within the major macroeconomic sectors across this region.

Determination of ecological flow based on probability distributions of annual and monthly flows

ABSTRACT Developing scientifically sound ecological flow is crucial for protecting river ecosystems. However, most of the existing hydrological methods for determining ecological flow make it difficult to consider both inter-annual and intra-annual changes in runoff. To compensate for this shortcoming, this paper proposes an innovative ecological flow determination method based on the probability distributions of annual and monthly flows. Marginal distributions of annual and monthly flows are first fitted, and the Copula function is used to create joint probability distributions of annual and monthly flows. Conditional probabilities for different monthly flow sizes under different annual flow conditions are then calculated based on Bayesian inference. The conditional probabilities are combined with the flow–duration curve-–based method to finalize the ecological flow process considering both intra- and inter-annual runoff changes. A case study was conducted in Jinsha River, China. The results show that the total annual ecological water demand of the Jinsha River is 1.50, 1.25, and 1.04 × 1011 m3 under annual flow scenarios of high, medium, and low flows, respectively, which provide a red line for the development of water resources and hydro-energy resources of the Jinsha River, as well as for the better protection of the natural plant and animal species.

No Future Growth Enhancement Expected at the Northern Edge for European Beech due to Continued Water Limitation.

With ongoing global warming, increasing water deficits promote physiological stress on forest ecosystems with negative impacts on tree growth, vitality, and survival. How individual tree species will react to increased drought stress is therefore a key research question to address for carbon accounting and the development of climate change mitigation strategies. Recent tree-ring studies have shown that trees at higher latitudes will benefit from warmer temperatures, yet this is likely highly species-dependent and less well-known for more temperate tree species. Using a unique pan-European tree-ring network of 26,430 European beech (Fagus sylvatica L.) trees from 2118 sites, we applied a linear mixed-effects modeling framework to (i) explain variation in climate-dependent growth and (ii) project growth for the near future (2021-2050) across the entire distribution of beech. We modeled the spatial pattern of radial growth responses to annually varying climate as a function of mean climate conditions (mean annual temperature, mean annual climatic water balance, and continentality). Over the calibration period (1952-2011), the model yielded high regional explanatory power (R2 = 0.38-0.72). Considering a moderate climate change scenario (CMIP6 SSP2-4.5), beech growth is projected to decrease in the future across most of its distribution range. In particular, projected growth decreases by 12%-18% (interquartile range) in northwestern Central Europe and by 11%-21% in the Mediterranean region. In contrast, climate-driven growth increases are limited to around 13% of the current occurrence, where the historical mean annual temperature was below ~6°C. More specifically, the model predicts a 3%-24% growth increase in the high-elevation clusters of the Alps and Carpathian Arc. Notably, we find little potential for future growth increases (-10 to +2%) at the poleward leading edge in southern Scandinavia. Because in this region beech growth is found to be primarily water-limited, a northward shift in its distributional range will be constrained by water availability.

Impacts of Climate Change on Rainfall ‘Seasonality Index’ and Its Potential Implications on Water Savings and Reliability through Household Rainwater Tanks

This study depicts potential climate change impacts on annual rainwater savings from household rainwater harvesting using two different climate projection models; ACCESS 1.0 and CSIRO-Mk3.6. This paper also investigates potential changes in the relationships of ‘water saving efficiency’ and reliability with rainfall ‘seasonality index’ under the mentioned climate change scenarios. The annual water savings were calculated for three weather conditions: dry, average, and wet. Historical daily rainfall amounts provided by the Australian Bureau of Meteorology were used for three locations within the city of Brisbane (Australia). For the same locations, projected future daily rainfall amounts were collected from an online data portal facilitated by the Australian government. Potential annual water savings, water saving efficiency, and reliability values for the selected locations were calculated through a widely used tool, eTank, developed on water balance methodology at a daily scale. It was found that for the coastal location, Manly, the future water savings are not likely to change significantly. However, for the inland location, Sunnybank, the future water savings are expected to decrease under all the weather conditions through both the considered climate projections. For the far inner location, Oxley, the water savings are likely to decrease in the dry year, whereas in wet year, they are likely to increase. Also, it was found that the overall average relationship of SI–water saving efficiency is steeper for ACCESS 1.0 projected data compared to that produced through CSIRO-Mk3.6 data, and that significant differences exist among individual relationships for each location. The overall reliabilities calculated through the model projected data show lower values compared to the reliabilities calculated using historical data.

Remotely Sensed Comparative Spatiotemporal Analysis of Drought and Wet Periods in Distinct Mediterranean Agroecosystems

Drought is a widespread natural hazard resulting from an extended period of reduced rainfall, with significant socioeconomic and ecological consequences. Drought severity can impact food security globally due to its high spatial and temporal coverage. The primary objective of this paper consists of a comparative spatiotemporal analysis of environmental extremes (drought/wetness) through the estimation of a twelve-month Standardized Precipitation Index (SPI12) between three distinct vulnerable agricultural regions in the Mediterranean basin (i.e., Spain, Lebanon and Tunisia), under a climate change environment in the last 38 years (1982–2020). The added value of this paper lies in the simultaneous estimation of temporal and spatial variability of drought and wetness periodic events, paying special attention to the geographical patterns of these extremes both in annual and interannual (seasonal) time scales. The results indicated that Spain and Tunisia (western Mediterranean) exhibit similar patterns over the studied period, while Lebanon demonstrates contrasting trends. Comparing the two extreme dry hydrological years, the Spanish study area faced the highest drought intensity, areal extent and duration (SPI12 = −1.18; −1.84; 28–78%; 9–12 months), followed by the Lebanese (SPI12 = −1.28; −1.39; 37–50%; 7–12 months) and the Tunisian ones (SPI12 = −1.05; −1.08; 10–34%; 8 months). Concerning the wettest hydrological years, the Lebanese study domain has recorded the highest SPI12 values, areal extent and duration (SPI12 = 1.58; 2.28; 66–83%; 8–11 months), followed by the Tunisian (SPI12 = 1.55; 1.79; 49–73%; 7–10 months) and Spanish one (SPI12 = 1.07; 1.99; 21–73%; 4–11 months). The periodicity of drought/wetness episodes is about 20 years in Spanish area and 10 years in the Lebanese area (for drought events), whereas there seems no periodicity in the Tunisian one. Understanding the spatial distribution of drought is crucial for targeted mitigation strategies in high-risk areas, potentially avoiding broad, resource-intensive measures across entire regions.

Influence of biochar on the productivity of spring wheat

The drought of the spring climate over the past 2 years has a significant impact on the decline in crop yields in the North Kazakhstan region. If the land is not used properly for many years in agriculture, the structural, water and physical properties of the soil will deteriorate. Changes in the qualitative and quantitative composition of land resources, and in some cases causes the deteriorationand destruction of the soil cover. As a result, resistance to dry climates and moisture retention are reduced, as well as loss of organic matter, as erosion washes away the topsoil and humus, resulted from improper management of agricultural soil conservation systems with widespread use of agricultural land in the region. One of the main reasons for the drainage of the soil cover is the long-term use of monocultures in the agricultural system and the violation of the crop rotation system, the lack of the introduction of organic and biofertilizers.

방사성 물질 흡착용 활성탄소섬유 시험방법 연구

The global demand for energy is escalating due to the increased power consumption for AI data centers, leading to the expansion of nuclear power facilities and a subsequent rise in radioactive waste generation. To address this, activated carbon filter systems have been employed in nuclear power plants to adsorb and prevent the atmospheric release of radioactive iodine, a byproduct of these facilities. However, the substantial annual discharge of activated carbon is causing challenges such as a shortage of waste storage facilities. To mitigate this issue, this study investigated the application of activated carbon fiber (ACF) in nuclear power plant filter systems. Adhering to existing standards for radioactive material adsorption, we established a suitable testing environment for ACF and conducted adsorption and removal tests. The results demonstrated a maximum removal efficiency of over 99.918% for radioactive iodine, indicating a performance comparable or superior to that of conventional activated carbon used in current processes. This research is expected to contribute positively to the diversification of materials used for radioactive material adsorption and removal in nuclear power plants, as well as the establishment of relevant standards.

Satellite observations indicate that chia uses less water than other crops in warm climates

Many parts of the world face severe and prolonged drought conditions, stressing the sustainability of water resources and agriculture. Transitioning to water-efficient crops is one strategy that can help adapt to water scarcity. An emerging drought-tolerant crop of interest is chia (Salvia hispanica). Yet, no study has compared its large-scale water use dynamics to those of widely established crops across the globe. Here, we use satellite data over multiple years to assess the water use efficiency of chia, alfalfa, corn, and soybean globally. Results show that chia consumed 13-38% less water than alfalfa, corn, and soy and assimilated 14-20% more carbon per amount of water used. Substituting 10% of Southwest United States alfalfa cultivation with chia would save 184 million liters of water per growing season, equivalent to the annual water consumption of 1,300 households. Future research shall explore the economic, societal, and environmental ramifications of substituting alfalfa with chia in dry areas worldwide. These insights can guide decision-makers in promoting sustainable agriculture and water resource management.

An integrated simulation-optimization modeling approach for coupled risk management of blue water and green water under changing environmental conditions

Due to the impact of global climate change and land use changes, the spatiotemporal distribution and water cycle processes of watershed water resources are affected. In order to sustainably manage watershed water resources, it is necessary to accurately assess the available water volume to meet the coordinated management of the watershed's socio-economic subsystem and eco-environment subsystem. The amount of Bluewater resources (BW) is closely related to the amount of Greenwater resources (GW). BW is directly related to human consumption in the socio-economic subsystem, while GW is used to maintain the health of the ecosystem. A method called the integrated simulation-optimization modeling system (ISOMS) was developed to evaluate adaptive strategies for dealing with the combined effects of climate change and land-use changes. ISOMS not only predicts future hydrological trends under varying environmental conditions but also generates comprehensive risk management plans that incorporate different types of uncertainties, including random and fuzzy factors. The Copula function is introduced to handle the interaction between available BW and available GW. The results showed that: (i) uncertainties in the hydrologic system could result in alterations to the distribution of water resources; (ii) system benefits are, to some extent, affected by land use change and climate change; (iii) the shortage of BW is affected by the level of risk, and the joint risk increases, resulting in an increase in water scarcity; (iv) the planned annual agricultural water consumption is the highest, followed by domestic water consumption, and industrial water consumption is the lowest. Through the results of the model operation, the joint risk assessment and adaptive management of BW and GW in the East River Basin (ERB) under changing environments, as well as the BW allocation plan, are obtained to provide support for scientific and reasonable resource collaborative decision-making and promote the synchronized advancement of the socio-economic subsystem and eco-environment subsystem in the ERB.

A machine learning approach to nearshore wave modeling in large lakes using land-based wind observations

This study presents a novel machine learning-based (ML) framework that utilizes the ConvLSTM-1D model to simulate wave heights at a nearshore location in Lake Michigan using a nonuniform land-based array of wind observations from a broad geographic region as an input. This approach was applied to Lake Michigan to perform a 70-year ice-free hindcast of waves near Chicago, IL (USA). Because of annual winter gaps in Great Lakes buoy observations, output from the Wave Information System model (WIS) was used for the training, validation, and testing of the ML model. Models with different numbers of wind stations were tested, showing that a single wind station as an input feature produced a reasonably accurate wave height. However, the wave height model accuracy increased as more wind input data was included from around the lake, largely plateauing beyond the inclusion of four stations that spanned Lake Michigan’s southern basin. The optimized model lookback period was found to be 10 h for all models, suggestive of a fetch-limited temporal coupling between the wind observations and nearshore waves. The extended time series showed a statistically significant increase in the interannual standard deviation of the storm wave height and the storm height over the mean wave height while no correlation was found with the annual water level time series. The ML framework offers a promising avenue for utilizing historical wind records to extend wave height time series for nearshore locations, particularly in enclosed and semi-enclosed basins where waves are strongly linked to local winds.

Disentangling the Impacts of Environmental Factors on Evaporative Fraction Across Climate Regimes

AbstractEvaporative fraction (EF) is a useful measure for quantifying land surface energy partitioning processes and determining evaporative regimes; however, its influencing factors remain highly uncertain. Here, global data sets were compiled to disentangle the effects of environmental variables on EF variations along climate and land surface gradients. We found that (a) at annual timescales, ecosystem‐level EF could be expressed as a power law function of aridity index. The relationships of mean annual soil water content (SWC) and leaf area index (LAI) with mean annual EF resembled the traditional evaporative regime theory; (b) at daily timescales, the boosted regression tree method quantitatively revealed that the impacts of environmental variables (including meteorological variables) on EF showed equal importance, especially at humid sites, primarily due to the different response direction and magnitude of latent heat (LE) and sensible heat (H) fluxes to environmental changes. Particularly, the contrasting responses of LE (positive) and H (negative) to SWC, LAI, and relative humidity enhanced the positive effects of those influencing variables on EF; whereas, the correlations between EF and energy‐related factors (i.e., net radiation‐Rn and air temperature‐Ta) deteriorated as both LE and H showed positive response patterns to those variables; (c) meteorological factors were also found to have nonlinear effects on daily EF, further modified by climatic conditions. Rn near 150 W/m2 and Ta near 15°C appeared to be important energy‐partitioning thresholds at drier and humid sites, respectively. Moreover, changing interactions among environmental variables with climates were demonstrated to be important for better explaining EF variations.

Relative contribution of the ocean-air heat exchange and advective heat transport to the increase of the Barents Sea water temperature in the early 21st century

The annual water temperature in the major water masses of the Barents Sea (BS) has significantly increased since the early 2000s. Advective heat transport from the neighboring water areas and heat exchange through the sea surface are the major factors, which shape the hydrological conditions in the BS. The paper estimates the contributions of heat exchange at the sea-atmosphere boundary and advective heat transport to changes in the average water temperature of the BS for the entire sea area. The average annual heat balance of the BS is calculated using atmospheric and oceanic reanalysis data. The change in the average temperature of the BS water is estimated taking into account the heat consumption for ice melting. The average surface heat balance from 1993 to 2018 was negative throughout the entire sea area: –70…–100 W/m2 in the south and –10…–20 W/m2 in the north. The advective heat supply was calculated for 9 straits with neighboring water areas. The determining source of advective heat is the influx of Atlantic waters from the Norwegian Sea between Cape Nordkapp and Bear Island. An average of 40.8 TW of advective heat is supplied through this margin. The calculations showed the predominance of annual heat influx due to advection over heat loss from the sea surface. This excess heat influx resulted in an estimated increase in the water temperature of the BS from 1993 to 2018 at a rate of 0.28 °C per year (taking into account the heat consumption for ice melting). In conclusion, it can be argued that the analysis has validated the hypothesis proposed in the article about compensation of heat losses from the surface of the BS by advective heat flow. The hypothesis is quantitatively confirmed by calculations on a simple box model (with an accuracy of up to an order of magnitude) based on atmospheric and oceanic reanalysis data. The ERA5 and GLORYS12V1 reanalysis data reliably describe the basic patterns of observed variability of ocean, sea ice and atmospheric parameters in the Barents Sea.

Evaluation of probability distribution methods for flood frequency analysis in the Jhelum Basin of North-Western Himalayas, India

The Kashmir Valley has frequently endured devastating floods, presenting significant challenges for flood management due to unpredictable flood magnitudes and limited pre-disaster preparedness. A major difficulty in addressing these challenges is the lack of reliable flood frequency analysis (FFA) for effective planning and mitigation. This study seeks to overcome these issues by employing a rigorous quantitative analysis of annual peak discharge data over a 51-year period (1971–2021). One key challenge was the presence of low outliers, which could compromise the integrity of the data. To address this, the Multiple Grubbs-Beck test was applied to remove these outliers before conducting FFA. The study's original achievement lies in its application of multiple distribution models which include Gumbel (EV1), Generalized Extreme Variations (GEV), Log-Normal, Log Pearson III (LP III), Gamma and Normal distribution. Goodness-of-fit tests, including Kolmogorov-Smirnov (KS), Anderson-Darling (AD), and Chi-square at the 5 % significance level, along with visualization techniques such as Probability plots (PP), Quantile plots (QQ), and Probabilistic distribution (PD) graphs, were used to identify the most suitable distribution methods. The Log Pearson Type III (LP-III) was identified as the best fit for the Sangam gauge site (Upper Jhelum), the gamma distribution for Ram Munshibagh (Middle Jhelum), and the Generalized Extreme Value (GEV) and LP-III for Asham (Lower Jhelum). For Sangam, the estimated discharges for 2, 5, 10, 50, 100, 150, 200, and 250-year return periods were 549.63, 1028.43, 1471.34, 2907.64, 3758.92, 4338.61, 4790.99, and 5167.23 cumecs, respectively, using LP-III. For Ram Munshibagh, the discharges were 602.13, 911.03, 1107.04, 1512.12, 1674.35, 1767.0, 1831.87, and 1881.74 cumecs using the gamma distribution. For Asham, the discharges were 685.8, 998.0, 1193.3, 1593.2, 1750.6, 1839.4, 1901.0, and 1948.0 cumecs using the GEV distribution. The findings indicate that the Jhelum River cannot accommodate excess discharge for return periods of 5 years or more, underscoring the need for enhanced flood management strategies.

Spatiotemporal responses of runoff to climate change in the southern Tibetan Plateau

Abstract. A comprehensive understanding of spatiotemporal runoff changes in the Yarlung Zangbo (YZ) basin in the southern Tibetan Plateau (TP) at a sub-basin scale, amidst varying climatic and cryospheric conditions, is imperative for effective water resources management. However, spatiotemporal differences of runoff composition and change and their attribution within the YZ basin have not been extensively explored, primarily due to the lack of hydrometeorological observations, especially in the downstream region. In this study, we investigated historical and future evolution of annual and seasonal total water availability, as well as glacier runoff and snowmelt contributions across six sub-basins of the YZ, with a particular focus on the comparison between the upstream Nuxia (NX) basin and the downstream Nuxia–Pasighat (NX-BXK) basin, based on a newly generated precipitation dataset and a well-validated model with streamflow, glacier mass, and snow cover observations. Our findings revealed that large spatiotemporal differences in changes exist within the YZ basin for 1971–2020. Firstly, runoff generation was dominated by rainfall runoff throughout the YZ basin, with glacier runoff playing a more important role in the annual total runoff (19 %) in the NX-BXK sub-basin compared to other sub-basins. Notably, glacier runoff contributed 52 % of the total runoff at the Pasighat outlet of the YZ basin. Secondly, annual runoff exhibited an increasing trend in the NX basin but a decreasing trend in the NX-BXK, primarily attributed to rainfall runoff changes influenced by atmospheric moisture. Glacier runoff enhanced water supply by offsetting the decreasing contribution from rainfall. Total runoff will consistently increase (27–100 mm (10 yr)−1) across the sub-basins through the 21st century, resulting from increased rainfall runoff and a minor effect of increased snowmelt and glacier runoff.

The role of the cryosphere for runoff in a highly glacierised alpine catchment, an approach with a coupled model and in situ data

Abstract Runoff from heavily glacierised catchments, its seasonality and the contribution from different storage units are highly relevant for assessing the seasonal and long-term water supply and flood prediction. Modelling studies on runoff from such basins often use simulated meteorological input (e.g. downscaling products) based on remote observations. We investigate the contribution of snow, firn and ice to runoff in the Vernagtferner basin (Ötztal Alps) from 2020 to 2022, using a physical modelling chain driven by a local observation network. We use the SNOWPACK model to simulate snow/ice development at observation sites and the Alpine3D model to calculate accumulation and melt at the catchment scale. Basin discharge is estimated using a gridded version of the HBV-ETH model. This approach largely reproduces observed glacier mass balances, while modelled and measured basin discharge are in good agreement. Snowmelt dominates discharge in the early melt season, while ice melt becomes increasingly important during summer. This is in strong contrast to the near-equilibrium mass balances in the 1980s, when ice melt played a minor role for annual discharge. The strong reduction of the accumulation area leads to a fundamental change from a snowmelt regime to an ice melt regime, which is especially pronounced in 2022.