Annual River Discharge Research Articles

Midpoint characterization factors to assess impacts of turbine water use from hydropower production

PurposeLife cycle assessment (LCA) distinguishes three types of water use: (1) consumptive water use, (2) degradative water use, and (3) in-stream water use. When it comes to assessing the impact of turbine water use (TWU, major source of in-stream water use) in LCA, so far, no method exists to quantify the related environmental impacts. Here, we developed the first midpoint characterization factors (CFs) with global coverage for turbine water use of storage and pumped storage hydropower power plants.MethodsThe midpoint CF at the basin scale describes the hydropower regulation potential (HRP) [HDOR·y] per TWU [m3]. The HRP indicates the probability of how strongly the natural flow regime of a river is potentially affected by all upstream reservoir operation, calculated as the quotient between reservoir volume [m3] and the annual river discharge [m3/y]. The hydropower degree of regulation (HDOR) thereby equals the unitless m3/m3 fraction. The TWU depends on the electricity production [kWh] and the turbine efficiency [m3/kWh]. We tested the sensitivity of the input data on the calculated CFs for four parameters (discharge, turbine efficiency, multipurpose allocation, and plant type). Furthermore, we performed a case study to analyze if consumptive and TWU impacts of producing 1 kWh are correlated or not.Results and discussionThe calculated CFs for the 342 basins vary from 1.13E-13 HDOR·y/m3 to 3.28E10-7 HDOR·y/m3. The HDOR values range from 0.0015 to 16.66, and the TWU varies between 0.0030 km3 and 2824 km3. A HDOR ≥ 0.02 can be interpreted as affected basin, and only 23 out of 342 basins have a HDOR below this threshold. This confirms that TWU of hydropower production can have important environmental impacts. The sensitivity analyses revealed that discharge and turbine efficiency are the most sensitive parameters because they are influencing almost all basins. The results of the case study showed that a high consumptive water-use impact does not automatically lead to a high TWU impact and vice versa (R2 values of 0.0081 and 0.003).ConclusionOur study highlights that it is important to account for the environmental impacts of in-stream water use in LCA, as otherwise, the environmental impact can be underestimated, which could lead to wrong conclusions. However, the CFs are not meant to replace a local risk assessment of hydropower reservoir operation and should only be used for relative comparison between basins. The CF application in LCA will represent a step forward towards more sustainable hydropower development.

From data to decisions: Leveraging ML for improved river discharge forecasting in Bangladesh

River discharge forecasting stands at the forefront of environmental management, contributing significantly to sustainable development through its impact on flood prevention, water resource management, ecological conservation, and energy production. This study forecasted the annual river discharge forecasting in the Nilphamari district of Bangladesh, employing random forest (RF), support vector machine (SVM), and gradient boosting machine (GBM) techniques. Historical river discharge data spanning from 1990 to 2020, obtained from eight surface water stations, forms the basis of the analysis. The forecast was performed from 2021 to 2030. 11 statistical parameters were considered for performance evaluation. Additionally, four evaluation plots, comprising a quantile–quantile plot (QQ plot), a residual plot, a Bland Altman plot, and Theil’s U statistic, were employed for a detailed understanding of model accuracy. Results demonstrate that the random forest regression technique exhibited superior accuracy compared to SVM and GBM in training and testing stages. Notably, the coefficient of determination reached 97 % during the testing phase, emphasizing the robustness of this model. While Mean Absolute Error is lower (1085.071 cubic meter per second), in training, the model captures relative changes (Mean Absolute Percentage Error = 0.154) better during prediction. Willmott’s Index in training (0.77) and testing (0.55) suggest the model memorizes training data well and outperforms the other models in testing stage. The findings underscore the efficacy of RF regression as a superior alternative for short-term discharge forecasting, offering valuable insights for integrated water resources management, particularly in flood warning systems and the expansion of irrigation initiatives.

Predicting River Discharge in the Niger River Basin: A Deep Learning Approach

Across West Africa, the River Niger is a major source of freshwater. In addition, the river system also provides services such as aquaculture, transportation, and hydropower. The river network plays a critical role in the hydropolitics and hydroeconomics of the region. Therefore, River Niger is integral to the development of West Africa, hence, there is a need to ensure that the river’s ecosystem is a healthy one. In light of the changing climate and its associated threats such as droughts and floods, constant monitoring and measurements of the the river’s flow system cannot be overemphasized. This study investigates temporal variations in annual river discharge characteristics at eight stations (Koulikoro, Dioila, Kirango, Douna, Mopti, Dire, Ansongo, and Niamey) in the Niger River basin, presenting detailed quantitative findings. Analyzing discharge data of River Niger from 1950 to 1990, the minimum discharge measures (minimum and 10th percentile) exhibit a consistent decreasing trend post-1960, persisting into the 1990s at several stations. Central tendency measures (mean and 50th percentile) also consistently reduced since 1950, with near-zero median values observed in Diola and Douna. Recovery in mean discharge is evident in Ansongo after 1980. Extreme values (maximum and 90th percentile) show decreasing trends across all stations, with some locations exhibiting a slight recovery after 1980. The decreasing trend in annual minimum, mean, and maximum values has implications for water resources, affecting hydroelectric generation, fish farming, and dry season irrigation. Machine learning algorithms (MLAs) are deployed to predict the prediction of monthly river discharge, with LSTM identified as the best-performing model overall. However, model performance varies across locations, with TCN excelling in Diola but underperforming in Koulikoro. This study emphasizes the chaotic nature of time series data and external drivers limiting the long-term predictive capabilities of MLAs. Quantitative evaluation of MLA performance reveals specific strengths and weaknesses at each station. This study underscores the importance of predicting the 10th percentile of annual river discharge for water resource planning. Models exhibit diverse performance across basins, emphasizing the need for tailored approaches. Further analysis considers measures of central tendencies, predicting the 50th percentile (Q50) and mean discharge values. TCN emerges as the best model for Q50 prediction, showcasing superior performance over other models. Additionally, the study delves into predicting high and low extreme discharges, crucial for understanding potential flood events and preparing for meteorological and hydrological droughts. This study concludes by emphasizing the necessity for location-specific studies in the River Niger basin to facilitate an enhanced integrated river management system.

Groundwater recharge influenced by ephemeral river flow and land use in the semiarid Limpopo Province of South Africa

Determining the sustainability of groundwater use in drylands with high climate variability is complex. Central to this determination is an understanding of groundwater recharge and associated processes and controls. Groundwater recharge in drylands can occur by diffuse and focused recharge (focused recharge being associated with intense episodic rainfall events and ephemeral river flow, predicted to increase and intensify with climate change). This study evaluated the relative significance and dominant controls on these two recharge processes. Ten groundwater hydrographs with multidecadal observations were collated from the Limpopo Province, South Africa, based on their proximity to river channels and rain gauges, representing diversity in local climate, landscape, vegetation, and hydrogeological conditions. The hydrographs showed that groundwater-level rises are sensitive to rainfall intensity during the rainy season, with generally larger increases after years with large episodic rainfall events, which disproportionately contribute to groundwater replenishment. Recharge processes and annual recharge volumes were quantified using the water-table fluctuation method and the numerical model HYDRUS-1D. This allowed for the inference of additional recharge contributions from focused recharge in proximity to ephemeral rivers, up to a factor of five relative to diffuse recharge. The analysis revealed synchronicity and linear correlation between annual river discharge and recharge close to the river, substantiating the importance of focused recharge close to the river network. The study showed that recharge in drylands is subject to large spatial and temporal variation and that consideration of focused and episodic recharge is critically important for managing groundwater resources at various scales in these regions.

Southern Flounder Life History Diversity and Contributions to Fisheries from Differing Estuarine Salinity Zones

AbstractOtolith chemistry is a useful natural tracer for discerning habitat‐use of estuarine fishes. For Southern Flounder Paralichthys lethostigma, recent otolith chemistry studies have revealed a diversity of residency patterns across salinity gradients. However, the contribution of recruits with specific residency patterns to fisheries is poorly understood. The objectives of this study were to (1) use otolith chemistry from fishery‐independent and fishery‐dependent collections in Mobile Bay, Alabama, to classify lifetime residency patterns (i.e., freshwater, transient, estuarine) in Southern Flounder collected across a large estuarine salinity gradient (0–30 psu); (2) to test if Southern Flounder exhibited resident or migratory behavior by determining if lifetime residency patterns in fishery‐independent samples matched expected salinity patterns in the region of collection after accounting for annual variation in river discharge; and (3) to examine which residency patterns contributed to the commercial and recreational Southern Flounder fisheries in nearby coastal waters. Age‐0 residency patterns in fishery‐independent samples were strongly correlated with region of collection and annual river discharge, suggesting that the majority of Southern Flounder had resided in the same region in which they spent their age‐0 growth phase. Southern Flounder with a combination of freshwater and estuarine salinity signals and classified as “transient” did not appear to have conducted large‐scale movements across salinity gradients, but instead resided in regions of the estuary experiencing seasonal fluctuations in salinity. The majority (57%) of commercially and recreationally harvested Southern Flounder were transients, while a minority (39%) were estuarine residents and lifetime freshwater residents (4%) were rarely harvested. Results from this study suggest that Southern Flounder settle in and remain in the certain habitats during the estuarine residency phase. Given the lack of movement across habitats, future efforts to understand how habitat‐specific conditions (e.g., abiotic, biotic, fishing exploitation) affect vital rates seems warranted for a species currently experiencing population declines.

Synoptic and Seasonal Variability of Small River Plumes in the Northeastern Part of the Black Sea

Small river plumes are typical features at many coastal regions in the World Ocean. These water masses have relatively small areas and volumes; however, due to their energetic dynamics localized in a thin surface layer, they strongly affect coastal circulation, water quality, and ocean-atmosphere interaction. In this study, we investigate external factors, which govern synoptic and seasonal variability of small river plumes, and, therefore, affect land-ocean fluxes of fluvial water and biogeochemically important material. We use numerical modeling to simulate small river plumes at the northeastern part of the Black Sea. We describe the response time of small river plumes to changes in river discharge and wind forcing conditions, which determines variability of river plumes at different time scales. We reveal that the influence of river plumes on coastal processes depends not only on total annual river discharge volume, but also on temporal distribution of high-discharge and low-discharge periods. Seasonal and synoptic features of local atmospheric circulation could strongly modify the relation between river plume characteristics and river discharge rate. The results obtained in this study are important for better assessment of delivery and fate of river-borne suspended and dissolved matter, as well as floating litter in coastal areas.

Divergent and Changing Importance of Glaciers and Snow as Natural Water Reservoirs in the Eastern and Southern Tibetan Plateau

AbstractGlaciers and snow are natural water reservoirs in the Tibetan Plateau (TP), affecting ecosystems, water and food security, and more than one billion downstream people. Meltwater volumes are traditionally estimated using the degree‐day concept considering only air temperature, which cannot consider the influence from downward solar and longwave radiation, humidity, wind and resultant turbulent heat fluxes. Here, we used a physically based energy budget approach considering the full energy balance in seven large river basins in the eastern and southern TP. For 1982–2011, the estimated average glacier melt was 0.32 ± 0.007 m water equivalent/yr with large spatial variability. Air temperature, downward longwave radiation, humidity, and wind speed influenced the overall glacier melt trend, and glacier melt accelerated with a rate of 0.42 mm/yr. Yet, downward shortwave radiation played an additional role in influencing the glacier melt rate fluctuation. On average, snow and glacier melt contributed 17.6% of annual river discharge during 1982–2011, including 10.0% from snow and 7.6% from glaciers. The highest and lowest relative melt contributions were in the Yarlung Tsangpo and Yalong Rivers, respectively. Mainly due to decreasing snow melt, glacier and snow melt contributions to discharge would decrease to 11.9% during 2021–2050 under the extreme climate scenario (RCP8.5), and the greatest change in the relative contributions would occur in the Upper Nu River (−9.2%). These findings indicate the divergent and changing importance of glaciers and snow as natural water reservoirs, potentially affecting socioeconomic development and adaptation to climate change in South, Southeast, and East Asia.

Structure and Inter-Annual Variability of the Freshened Surface Layer in the Laptev and East-Siberian Seas During Ice-Free Periods

This work is focused on the structure and inter-annual variability of the freshened surface layer (FSL) in the Laptev and East-Siberian seas during ice-free periods. This layer is formed mainly by deltaic rivers among which the Lena River contributes about two thirds of the inflowing freshwater volume. Based on in situ measurements, we show that the area of this FSL during certain years is much greater than the area of FSL in the neighboring Kara Sea, while the total annual freshwater discharge to the Laptev and East-Siberian seas is 1.5 times less than to the Kara Sea (mainly from the estuaries of the Ob and Yenisei rivers). This feature is caused by differences in morphology of the estuaries and deltas. Shallow and narrow channels of the Lena Delta are limitedly affected by sea water. As a result, undiluted Lena discharge inflows to sea from multiple channels and forms relatively shallow plume, as compared to the Ob-Yenisei plume, which mixes with subjacent saline sea water in deep and wide estuaries. Due to small vertical extents of FSL in the Laptev and East-Siberian seas, wind conditions strongly affect its spreading and determine its significant inter-annual variability, as compared to relatively stable FSL in the Kara Sea. During years with prevailing western and northern winds, FSL is localized in the southern parts of the Laptev and East-Siberian seas due to southward Ekman transport, meridional extent (<250 km) and area (∼250,000 km2) of FSL are relatively small. During years with strong eastern winds FSL spreads northward over large area (up to 500,000 km2), its meridional extent increases up to 500–700 km. At the same time, area and position of FSL do not show any dependence on significant variability of the annual river discharge volume and ice coverage during warm season.

Estimation of Long-Term River Discharge and Its Changes in Ungauged Watersheds in Pamir Plateau

The Pamir Plateau is an extremely important water resource area for over 60 million people in Central Asia. With the increasingly significant response of water resources to climate change, timely hydrological predictions for the future supply are necessary. In the plateau, accessing and monitoring the glaciers and their melt outflow are challenging due to the harsh geographic environments. Unmanned aerial vehicles (UAVs) combined with remote sensing technologies offer great potential for providing information to improve water resources management and decision-making. In this study, we integrated UAV and satellite remote sensing data, and applied a water balance model to estimate monthly and annual river discharges for the ten river sections in the Eastern Pamir Plateau, China from 1999 to 2020. We found that the glacier area in the controlled basins of these sections has decreased by approximately 63% from 1999 to 2020. Basins with smaller glacier areas are more sensitive to climate change. The ten river sections are characterized by decreasing trends in monthly river discharge, with an average reduction of −21.05%. The annual variation of total runoff and glacial meltwater discharge is consistent with the monthly variation of discharge, and the average discharge from glacier meltwater accounts for 83% of the total runoff. We conclude that the overall decreasing trend of discharge is closely related to the recession of glaciers. Under the background of climate warming in the region, glaciers are no longer sufficient to support the increase in river discharge, which has passed its peak value and shows a decreasing trend.

The Impact of Climate Change on Hydrological Regime of the Transboundary River Shu Basin (Kazakhstan–Kyrgyzstan): Forecast for 2050

The impact of regional climate change on the runoff and the regime of glacier- and snow-fed rivers in the transboundary river Shu basin between Kazakhstan and Kyrgyzstan is investigated. This study covered three of the most representative rivers of the Shu basin. It was based on the weather and gauging stations’ observation data in the river Shu basin — the northern Tien Shan. Based on the trend analysis, an increase in the average annual temperature and river discharge was identified within the observation period as a whole, and for the separate compared periods. Furthermore, the mean annual flow projections were made based on the methodology of the retrospective analysis of runoff and the rate of river flow increase for the observation period, and further extrapolation of data for the forecast period. According to the analysis, the mean annual flow for the considered rivers will be decreased by 25 to 30% on average by 2050. These findings are necessary for elaborating adaptation measures in water allocation for freshwater supply, irrigation and hydropower within this transboundary river.

Assessment of climate change impact on water availability in the upper Dong Nai River Basin, Vietnam

Abstract On a global scale, climate change is projected to have detrimental impacts on water availability. This situation will become more severe owing to accumulated impacts of climate change and anthropogenic activities. This study aims to investigate climate change impact on water availability in the upper Dong Nai River Basin using the Soil and Water Assessment Tool (SWAT) and Water Evaluation and Planning (WEAP) models. Future rainfall scenarios were downscaled from five different general circulation models under RCP4.5 and RCP8.5 using the Long Ashton Research Station Weather Generator (LARS-WG) tool. Under the climate change impact, annual river discharge in the study region is generally projected to have upward trends in the future, except for the near-future period of the 2030s under RCP4.5. In addition, dry-seasonal river discharge is expected to be increased in the future. Considering the baseline condition of water use, there was an annual water shortage of approximately 32.9 × 103 m3, which mostly occurred in the dry season from January to March. Climate change may reduce the water shortage in the study region ranging from 7.0 to 30.1% in the future. Under the combined impacts of climate change and increasing water demand, the water shortage will vary from −18.6 to 6.0% in the future. The results can provide valuable insights to implement appropriate future water resources planning and management in the study region.

Impact of climate change on snowmelt runoff in a Himalayan basin, Nepal.

The Hindu Kush Himalaya (HKH) is one of the major sources of fresh water on Earth and is currently under serious threat of climate change. This study investigates the future water availability in the Langtang basin, Central Himalayas, Nepal under climate change scenarios using state-of-the-art machine learning (ML) techniques. The daily snow area for the region was derived from MODIS images. The outputs of climate models were used to project the temperature and precipitation until 2100. Three ML models, including Gated recurrent unit (GRU), Long short-term memory (LSTM), and Recurrent neural network (RNN), were developed for snowmelt runoff prediction, and their performance was compared based on statistical indicators. The result suggests that the mean temperature of the basin could rise by 4.98°C by the end of the century. The annual average precipitation in the basin is likely to increase in the future, especially due to high monsoon rainfall, but winter precipitation could decline. The annual river discharge is projected to upsurge significantly due to increased precipitation and snowmelt, and no shift in hydrograph is expected in the future. Among three ML models, the LSTM model performed better than GRU and RNN models. In summary, this study depicts severe future climate change in the region and quantifies its effect on river discharge. Furthermore, the study demonstrates the suitability of the LSTM model in streamflow prediction in the data-scarce HKH region. The outcomes of this study will be useful for water resource managers and planners in developing strategies to harness the positive impacts and offset the negative effects of climate change in the basin.

How much do human and livestock actually contribute to steroids emission and surface water pollution from past to the future: A global research

A comprehensive global inventory of past, present, and future steroid emissions was firstly developed based on the global 5′ × 5′ grids relevant data available. From 1970 to 2070, the growth rate of the annual global steroid emission was relatively stable around 10%. At present (in 2015), the global steroid emissions was 18,270 t, with 17% contributed by humans. Almost one-third of total animal emissions have been occurring in India and Brazil. India also had the highest value of human steroid emissions. Regions with highest steroid emissions were concentrated between 10° ~ 35° N and 70° ~ 90° E. The increase of sewage treatment rates can effectively reduce the total quantity of steroids entering the environment, especially for some developing countries. But the “technology bonus” from sewage treatment process will be exhausted until to 2030. Meanwhile, global surface water pollution was predicted based on steroid emissions into water compartment and on the digital river network with annual river discharge. The modelling results show that steroids are widely distributed across the globe, with concentrations mostly below 100 ng/L. However, if no proper treatment measures for animal excretions, in another 100 years, the range of the surface water contaminated by steroids will increase by 1.2 times. The Nile River resulted as the most polluted among the eight world's longest and famous rivers during the whole period investigated. Various measured concentrations worldwide validated our modelling result. The global steroid emission inventory and surface water pollution from past to the future will stand as an important data and knowledge base for the management of pollution from different types of steroids at global and regional level.

Climate change impact on water availability of main river basins in Ukraine

Study regionEight main river basins covering the major part of Ukraine. Study focusThe main aim of this study was to provide an assessment of climate change impacts on water availability across Ukraine using global hydrological models. Six global hydrological models were evaluated for their performance in the historical period in the basins under study. Future river discharge was simulated by using the best performing model and all available models driven by bias-corrected GCM projections from the ISIMIP project under the RCP 2.6 and RCP 8.5 scenarios. New hydrological insights for the regionThe results show precipitation increase up to 10 % under RCP 2.6, and variable changes from -14 % to +10 % under RCP 8.5 by the end of the century. The projections show the decreasing mean annual river discharge in the majority of basins for the middle (2040–2070) and far future (2071–2100) periods under both RCPs, and the decrease is stronger under RCP 8.5. The seasonal changes are characterised by a decrease in summer and a small to moderate increase in winter months in most of the basins. The highest reduction of mean annual discharge was projected for the Pripyat, Southern Bug and Dniester basins, reaching up to -30 % to the end of the century under RCP 8.5.

Influence of Seasonal River Discharge on Tidal Propagation in the Ganges‐Brahmaputra‐Meghna Delta, Bangladesh

AbstractSignificant research efforts have been devoted to understanding river‐tide interactions in estuaries. However, studies on the impact of monsoon‐driven fluctuations of river discharge are limited. Here, the role of varying river discharge on the tidal propagation and tidal limit along the Ganges‐Brahmaputra‐Meghna Delta (GBMD), a macrotidal estuary subject to seasonal and annual river discharge variations, is investigated. The Delft3D hydrodynamic model is validated and applied to an average flood year condition and nine idealized scenarios covering the typical hydrological conditions. Results reveal that the upper limit of the tidal propagation shifts 75 km upstream during the dry season. The residual water level slope and tidal damping rate increase with river discharge beyond 100 km from the estuary mouth. The balance between the generation and dissipation of quarterdiurnal tides shifts spatially as a result of changes in channel convergence and friction and temporally as a function of river discharge, which controls the total friction in the upper tidal river. The balance between tidal dissipation and generation depends on the residual velocity generated by river discharge and the velocity of the principal tides. The maximal generation of quarterdiurnal tides in the upper GBMD depends on the friction generated from the river‐tide interaction. Critical river discharge thresholds produce an optimal condition of dissipation of semidiurnal tides and generation of quarterdiurnal tides through friction at the upper and middle estuary. River discharge above the critical river discharge amount more rapidly dissipates both semidiurnal and quarterdiurnal tides than generates quarterdiurnal tides from nonlinear interactions.

Direct Versus Indirect Tree Ring Reconstruction of Annual Discharge of Chemora River, Algeria

Annual river discharge is a critical variable for water resources planning and management. Tree rings are widely used to reconstruct annual discharge, but errors can be large when tree growth fails to respond commensurately to hydrologically important seasonal components of climate. This paper contrasts direct and indirect reconstruction as statistical approaches to discharge reconstruction for the Chemora River, in semi-arid northeastern Algeria, and explores indirect reconstruction as a diagnostic tool in reconstruction error analysis. We define direct reconstruction as predictions from regression of annual discharge on tree ring data, and indirect reconstruction as predictions from a four-stage process: (1) regression of precipitation on tree rings, (2) application of the regression model to get reconstructed precipitation for grid cells over the basin, (3) routing of reconstructed precipitation through a climatological water balance (WB) model, and (4) summing model runoff over cells to get the reconstructed discharge at a gage location. For comparative purposes, the potential predictors in both modeling approaches are the same principal components of tree ring width chronologies from a network of drought-sensitive sites of Pinus halepensis and Cedrus atlantica in northern Algeria. Results suggest that both modeling approaches can yield statistically significant reconstructions for the Chemora River. Greater accuracy and simplicity of the direct method are countered by conceptual physical advantages of the indirect method. The WB modeling inherent to the indirect method is useful as a diagnostic tool in error analysis of discharge reconstruction, points out the low and declining importance of snowmelt to the river discharge, and gives clues to the cause of severe underestimation of discharge in the outlier high-discharge year 1996. Results show that indirect reconstruction would benefit most in this basin from tree ring resolution of seasonal precipitation.

The impact of climate change and glacier mass loss on the hydrology in the Mont-Blanc massif

The Mont-Blanc massif, being iconic with its large glaciers and peaks of over 4,000 m, will experience a sharp increase in summer temperatures during the twenty-first century. By 2100, the impact of climate change on the cryosphere and hydrosphere in the Alps is expected to lead to a decrease in annual river discharge. In this work, we modelled the twenty-first century evolution of runoff in the Arve river, downstream of Mont-Blanc’s French side. For the first time for this region, we have forced a hydrological model with output from an ice-dynamical glacier model and 16 downscaled climate projections, under RCP4.5 and RCP8.5 scenarios. By 2100, under RCP8.5 (high-emission scenario), the winter discharge of the Arve river remains low but is expected to increase by 80% when compared to the beginning of the century. By contrast, the summer season, currently the most important discharge period, will be marked by a runoff decrease of approximately 40%. These changes are almost similar according to a scenario with a lower warming (RCP4.5) and are mostly driven by glacier retreat. These shifts will have significant downstream impacts on water quantity and quality, affecting hydroelectric generation, agriculture, forestry, tourism and aquatic ecosystems.

Quantification and uncertainty of the impact of climate change on river discharge and sediment yield in the Dehbar river basin in Iran

The purpose of this study is to identify future changes in weather variables (precipitation and temperature) due to climate change using different general circulation models (GCMs) for different emission scenarios, so as to assess the impact of climate change on river discharge and sediment yield in the Dehbar river basin in Iran. The magnitude and uncertainty of the impact of climate change on river discharge and sediment yield in the Dehbar river basin in Iran is quantified using a calibrated and validated SWAT model with future weather inputs generated using the LARS-WG6 program to downscale the output of five large-scale GCMs for three possible emission scenarios (RCP26, RCP45, and RCP85) and the period 2021–2040. Annual maximum and minimum temperatures are projected to increase by 22–28% and 65–84%, respectively, with a 1-month shift in temperature peak. The future rainfall amounts show both increasing (fall and winter) and decreasing (spring and summer) trends. Future temperature and rainfall patterns are predicted to cause the largest flows to occur a month earlier (February instead of March), an increase in discharge in the “wet” months of fall and winter (up to 137%) and a decrease in the “dry” months of spring and summer (down to − 100%). Sediment yield, which is caused by runoff (also controlling river discharge), has a similar projected trend, with a general decrease in spring and summer (down to − 95%) and an increase in fall and winter (up to 340%). The coefficient of variation of the future monthly, seasonal and annual river discharges and sediment yields are relatively low, revealing a general agreement in projections among the different GCM and RCP scenarios considered. This study highlights the significant negative impact of climate change on the Dehbar river basin, with amplification of river flows and sediment concentrations in the wet season and increased water scarcity in the dry season. Both effects may adversely impact the region’s livelihood (cultivation, fish farming) and land resources.

Sustainable water management for cross-border resources: The Balkhash Lake Basin of Central Asia, 1931–2015

The water level in Balkhash Lake is an important indicator for basin-wide ecosystem conditions, which is affected by many factors. The Ili River is a typical trans-boundary river between China and Kazakhstan, and its flows occupy about 80% of the runoff of all rivers flowing into Balkhash Lake. Several studies argued that overexploitation of water resources on the China side caused the decrease of river discharge of the Ili River, eventually leading to the decline of the Balkhash Lake’s water level. This study uses trend and correlation analysis to characterize variations in lake level, precipitation, temperature, evapotranspiration, land cover and population in the Balkhash Lake Basin. Results show that a substantial increase in the amount of discharges that flows from China to Kazakhstan has been observed from 1931 to 2013, and the average annual discharge from 1998 to 2013 reflects a 26.5% increase (36.33 × 108 m3) over the average from 1931 to 1997. The Kapchagay reservoir significantly reduced annual river discharges by about 11.67 × 108 m3 during the period 1970–1997, which significantly caused the decline of the Balkhash Lake’s levels. Agricultural land increased by 0.74 × 103 km2/year from 1992 to 2015, mainly in the southeast of Kazakhstan during the period 1998–2001, leading to an increasing trend in water consumption due to evapotranspiration from increasing irrigation. Overall, water resources are in long-term decline in the Balkhash Lake Basin when glaciers melt and irrigation must therefore be managed with increasing efficiency. The results presented here provide essential information for a comprehensive understanding of lake and water resources allocation and management.

Routing of terrestrial organic matter from the Congo River to the ultimate sink in the abyss: a mass balance approach (André Dumont medallist lecture 2017)

We address the role of the Congo River sediment dispersal in exporting and trapping organic carbon into deep offshore sediments. Of particular interest is the Congo submarine canyon, which constitutes a permanent link between the terrestrial sediment sources and the marine sink. The Congo River delivers an annual sediment load of ~40 Tg (including 2 Tg of C) that feed a mud-rich turbidite system. Previous estimates of carbon storage capacity in the Congo turbidite system suggest that the terminal lobe complex accounts for ~12% of the surface area of the active turbidite system and accumulates ~18% of the annual input of terrestrial particulate organic carbon exiting the Congo River. In this paper, we extend the approach to the whole active turbidite depositional system by calculating an average burial of terrestrial organic matter in the different environments: canyon, channel, and levees. We estimate that between 33 and 69% of terrestrial carbon exported by the Congo River is ultimately trapped in the different parts of turbidite system and we evaluate their relative efficiency using a source to sink approach. Our carbon budget approach, which consider annual river discharge versus offshore centennial accumulation rates, indicates that about half of the total particulate organic matter delivered yearly by the Congo River watershed escapes the study area or is not correctly estimated by our deep offshore dataset and calculations.