Changes In Streamflow Research Articles

Future flood envelope curves for the estimation of design flood magnitudes for highway bridges at river crossings

Creager flood envelope curves, which serve as the upper bound/limit of observed extreme flows, are commonly used by practitioners to estimate design flood magnitudes, which in the case of most river-crossing highway bridges is 75-year flood magnitude in Canada. This study proposes a novel framework for climate change adaption of Creager curves for estimating future design floods. These curves, for the current period, are assessed considering 417 observation stations, located in seven major Canadian river basins (i.e., Fraser, Nelson, Mackenzie, Yukon, Churchill, St Lawrence and St John). The Creager coefficient C, which defines flood envelope curves, varies between 1 and 45 across the studied river basins. To adapt Creager curves for future changes in streamflow, a correction factor, RC, which is the ratio of future to current period C values, is proposed. These factors are obtained for observation sites, using streamflow data from an ensemble of Regional Climate Model (RCM) simulations for current and future periods, through two Regional Frequency Analysis approaches. The first approach, considering only the RCM cells where the stations are located, suggests RC in the 0.3–1.6 range, with southeasterly basins showing values < 1. The second approach, considering all RCM cells for a given region, yields a wider range for RC and adds useful information in that RC values can also be established at ungauged locations. From a practical viewpoint, the proposed framework for estimating future design floods is robust and transferrable to other basins, but can benefit using streamflow projections from other models for better uncertainty quantification.

Variations in the streamflow of the Nierji Reservoir Basin and quantification of the influencing factors

Abstract Nierji Reservoir is the largest and most important water conservancy project in the Nenjiang River Basin. A thorough understanding of variations in streamflow and the driving factors of the Nierji Reservoir Basin (NERB) is crucial, but there are still gaps. In this paper, the annual streamflow data of Nierji Reservoir from 1898 to 2013 were applied to detect the changing trend and abruptions using the Mann–Kendall method. Additionally, a Back Propagation-Artificial Neural Network (BP-ANN) model was developed to explore the relationships between the streamflow and its influencing factors and further quantify the relative contribution of each factor to the streamflow change. The results revealed that the annual streamflow of NERB significantly increased from 1898 to 2013 but declined during 1988–2013. Human activities were found to be the primary driver of streamflow decrease during 1988–2013, accounting for nearly 75% of the total change. Specifically, GDP had the largest influence, contributing 32% to the overall variation. Forest area, precipitation, and cultivated area had smaller contributions of 25, 23, and 18%, respectively. Temperature was found to have the least impact, with a relative contribution of 2%. This study provides valuable insights into water resources management in the Nenjiang River Basin, benefiting both agriculture and ecology.

Identifying components and controls of streamflow in a cold and arid headwater catchment

Streamflow is increasingly vulnerable to climate change over cold-arid regions. To understand the underlying mechanisms of streamflow changes, it is essential to distinguish streamflow components and identify their drivers due to various meltwater and rainfall runoff processes. This study combines the conceptual temperature-index Snowmelt Runoff Model (SRM) and wavelet coherence analysis to unravel the impacts of environmental factors on streamflow and its components over the semiarid-and-cold headwater catchment of the Manas River in Northwest China during 2001–2015. Our results show that SRM reproduces monthly observed streamflow with determination coefficients of > 0.91, Nash-Sutcliffe Efficiency of > 0.82, and absolute relative error of < 5 % during SRM calibration (2001–2007) and validation (2008–2015) periods. The meltwater runoff and rainfall runoff contribute to 42 % and 31 % of the total streamflow, respectively. The wavelet-based spectral analysis, partial wavelet coherency analysis, and multiple-wavelet coherence together demonstrate that total streamflow (rainfall runoff) is predominantly influenced by snow cover area (precipitation) at a scale of 32 (4–16) months. But the meltwater runoff is simultaneously controlled by precipitation, potential evapotranspiration, and normalized difference vegetation index on scales of 4–16 and > 32 months. Our study provides technical support for streamflow partitioning and controlling factors identification, and has implication to sustainable water resources management in cold and arid regions.

Impacts of Permeability Uncertainty in a Coupled Surface‐Subsurface Flow Model Under Perturbed Recharge Scenarios

AbstractCoupled simulations of surface and variably saturated subsurface flow, termed integrated hydrologic models (IHMs), can provide powerful insights into the complex dynamics of watersheds. The system of governing equations solved by an IHM is non‐linear, making them a significant computational burden and challenging to accurately parameterize. Consequently, a large fraction of the IHM studies to date have been “numerical hypothesis testing” studies, but, as parallel computing continues to improve, IHMs are approaching the point where they might also be useful as predictive tools. For this to become reality, the predictive uncertainty of such highly parameterized simulations must be considered. However, uncertainty is seldom considered in the IHM literature, likely due to the long runtimes of the complex simulations. The questions considered herein are how much uncertainty is there in an IHM for a common watershed simulation scenario, and how likely is it that any one realization of a system will give the same relative change as any other due to a perturbation in recharge? A stochastic ensemble of 250 permeability field realizations was used to show that uncertainty in a high‐mountain headwaters systems is dominated by the subsurface. Recharge perturbation scenarios echo these results, but the uncertainty of changes in streamflow or groundwater pressure heads were significantly smaller than the uncertainty in their base‐case values. The main finding is that IHMs do provide confident, predictive estimates of relative changes in watersheds, even when uncertainty in specific simulation outputs may be high.

Evaluation of hydrological regime alteration and ecological flow processes in the changing environment of the Jialing River, China

Abstract Ecological flow is a key element in maintaining the biodiversity of a basin's aquatic ecosystem. This study quantifies the degree of hydrological regime alteration in the Jialing River and the contributions of various driving factors using the indicators of hydrologic alteration and range of variability approach (IHA-RVA), the river impact method (RI), and the elasticity coefficient method based on long-term hydro-meteorological data. Cross-wavelet analysis is used to reveal the periodicity and coherence of runoff and driving factors. Additionally, the improved Q90 method presents a more effective annual ecological flow process. The results show that the overall hydrological regime in the Jialing River has undergone a moderate change, with RVA and RI values of 45.02% and 0.66. Human activities contribute 54.68% to the changes in streamflow. Streamflow has an extremely significant correlation with precipitation and aridity index (Φ). Approximately 85% of the wavelet cone of influence (COI) area, tested at a 95% confidence level, falls within the region. The study also found that the ecological flow obtained through the improved Q90 method is more conducive to the healthy development of the river ecosystem in the Jialing River. These findings can provide some assistance for aquatic ecosystem restoration in the Jialing River.

Ensemble projections of climate and streamflow in a typical basin of semi-arid steppes in Mongolian Plateau of 2021–2100

The Kherlen River is the main water source for Hulun Lake, the largest lake in northern China. Due to reduced inflow from the Kherlen River, Hulun Lake experienced rapid shrinkage at the beginning of the 21st century, posing a serious threat to the ecological security of northern China. However, there is still a significant lack of projections regarding future climate change and its hydrological response in the Kherlen River basin. This study analyzed the projected climate and streamflow changes in the Kherlen River basin, a vital yet vulnerable international semi-arid steppes type basin. A combination of multi-model ensemble projection techniques, and the soil and water assessment tool (SWAT) model was employed to examine the spatio‒temporal changes in precipitation, temperature, streamflow, and the associated uncertainties in the basin. The temperature (an increase of 1.84–6.42 °C) and the precipitation (an increase of 15.0–46.0 mm) of Kherlen River basin are projected to increase by 2100, leading to a rise in streamflow (1.08–4.78 m3 s−1). The upstream of the Kherlen River exhibits remarkable increasing trends in precipitation, which has a dominant influence on streamflow of Kherlen River. Noteworthy increases in streamflow are observed in April, August, September, and October compared to the reference period (1971–2000). These findings suggest a partial alleviation of water scarcity in the Kherlen River, but also an increased likelihood of hydrological extreme events. The projected temperature increase in the Kherlen River basin exhibits the smallest uncertainty, while more pronounced uncertainties are found in precipitation and streamflow. The spread among the results of CMIP6 models is greater than that of CMIP5 models, with lower signal-to-noise ratio (SNR) values for temperature, precipitation, and streamflow.

Responses of annual streamflow variability to annual precipitation, extreme climate events and large-scale climate phenomena in the Qinghai-Tibet Plateau

Solar activity and large-scale climate phenomena have significant effects on extreme climate events and streamflow variability. As the roof of the world and the water tower of Asia, the Qinghai-Tibet Plateau (QTP) is highly sensitive to climate change. Therefore, it is of great significance to study the relationship between extreme hydrometeorological events of the QTP and climate change for global hydroclimate research. In this study, we analyzed the spatiotemporal variation and significant oscillation period of several hydrometeorological variables such as extreme precipitation indices (EPIs), extreme temperature indices (ETIs) and annual streamflow variability based on the observation data of hydrometeorological stations in the QTP during 1962–2019 using Sen’s slope estimator, Mann-Kendall test and continuous wavelet analysis (CWT). And the teleconnection patterns and the lead-lag relationship between annual precipitation, extreme climate events, multiple nonstationary climate mode and annual streamflow were evaluated using wavelet coherence (WTC). The results show that the climate of the QTP has been wetter and warmer in the past 58 years. The annual streamflow of several natural rivers in the QTP mainly show an increasing trend over the last 60 years. The annual streamflow of natural river (except Yellow River) increases significantly in three-rivers headwater region, and the rivers in the northeast and northwest also show a significant increase trend, but there is no significant change in the natural river streamflow in the south of QTP. In addition, the annual streamflow of natural rivers had significant periodicities in the bands of 2–4 years, 4–7 years and 7–11 years. The significant coherence of WTC spectra between annual precipitation and streamflow indicate that precipitation is the main reason for annual streamflow variation in the QTP. The variation of extreme climate events significantly regulates the regional annual streamflow. All EPIs except consecutive dry days show an in-phase correlation with annual streamflow of most headwater. Annual streamflow of Naijin River is positively and negatively correlated with extreme warm and extreme cold, respectively, and has a clearer lead-lag relationship than that with EPIs. Annual streamflow of headwater has higher correlations with EI Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) than with sunspot number (SSN). Solar activity may first affect ENSO and PDO, and then this effect is transferred sequentially to the hydrological cycle of the QTP by SSN-modulated PDO and PDO-SSN co-modulated ENSO. It is of great significance to investigate the response of streamflow variation to annual precipitation, extreme climate events and large-scale climate phenomena for water resources management, flood control, ecosystem restoration, and the well-being of surrounding residents and sustainable development in the QTP.

A holistic approach to projecting streamflow and analyzing changes in ecologically relevant hydrological indicators under climate and land use/cover change

Understanding streamflow change and its ecological impacts under climate change and land use/cover change (LUCC) makes possible the improvement of water and ecological governance decision-making. Gaining a comprehensive understanding of the drivers of historical streamflow changes can provide valuable insights for effective projections of future streamflow. Meanwhile, future changes in ecologically relevant hydrological indicators need more attention to maintain the ecological stability of rivers. This study has developed a holistic framework based on a physically based model (the Variable Infiltration Capacity model, or VIC) and the indicators of hydrological alteration (IHA) method to decouple the drivers of historical streamflow change and to project changes in future streamflow and ecologically relevant hydrologic indicators. The proposed framework was applied in the upper Han River basin (UHRB), which is the water source for the water diversion project in China. The results showed that climate change contributed 99.67 % of the streamflow decrease in the 1980–1990s and 108.21 % and 102.09 % of the streamflow increase in the 1990–2000s and 2000–2010s respectively. LUCC had a weak impact on streamflow in these three periods. Projected climate change will further exacerbate streamflow change. The projected monthly streamflow is expected to increase from October to December. The counts of streamflow pulses are expected to decrease, but the duration of each high pulse will increase. These changes will cause stress in floodplain vegetation, alterations to stream chemistry, reductions in fish diversity (decreased streamflow pulses), and alterations to river landscape and animal habitat (increased flood duration). The developed framework is expected to provide significant technical guidance for water resource management and river conservation.

Integrating conceptual and machine learning models to enhance daily-Scale streamflow simulation and assessing climate change impact in the watersheds of the Godavari basin, India

This study examined and addressed climate change's effects on hydrological patterns, particularly in critical places like the Godavari River basin. This study used daily gridded rainfall and temperature datasets from the Indian Meteorological Department (IMD) for model training and testing, 70% and 30%, respectively. To anticipate future hydrological shifts, the study harnessed the EC-Earth3 data, presenting an innovative methodology tailored to the unique hydrological dynamics of the Godavari River basin. The Sacramento model provided initial streamflow estimates for Kanhargaon, Nowrangpur, and Wairagarh. This approach melded traditional hydrological modeling with advanced multi-layer perceptron (MLP) capabilities. When combined with parameters like lagged rainfall, lagged streamflow, potential evapotranspiration (PET), and temperature variations, these initial outputs were further refined using the Sac-MLP model. A comparison with Sacramento revealed the superior performance of the Sac-MLP model. For instance, during training, the Nash Sutcliffe efficiency (NSE) values for the Sac-MLP witnessed an improvement from 0.610 to 0.810 in Kanhargaon, 0.580 to 0.692 in Nowrangpur, and 0.675 to 0.849 in Wairagarh. The results of the testing further corroborated these findings, as evidenced by the increase in the NSE for Kanhargaon from 0.890 to 0.910. Additionally, Nowrangpur and Wairagarh experienced notable improvements, with their NSE values rising from 0.629 to 0.785 and 0.725 to 0.902, respectively. Projections based on EC-Earth3 data across various scenarios highlighted significant shifts in rainfall and temperature patterns, especially in the far future (2071–2100). Regarding the relative change in annual streamflow, Kanhargaon projections under SSP370 and SSP585 for the far future indicate increases of 584.38% and 662.74%. Similarly, Nowrangpur and Wairagarh are projected to see increases of 98.27% and 114.98%, and 81.68% and 108.08%, respectively. This study uses EC-Earth3 estimates to demonstrate the Sac-MLP model's accuracy and importance in climate change water resource planning. The unique method for region-specific hydrological analysis provides vital insights for sustainable water resource management. This research provides a deeper understanding of climate-induced hydrological changes and a robust modeling approach for accurate predictions in changing environmental conditions.

Response Study of Streamflow and Sediment Reduction in the Northeast Region of the Loess Plateau under Changing Environment

The Sanggan River Basin in the loess hill and gully area is the primary water source for the establishment of the capital water conservation function area and the ecological environment support zone. Against the backdrop of global warming, population growth, and accelerated urbanization, water consumption in the Sanggan River Basin has persistently increased in recent years, leading to a series of issues, such as river pollution, surface streamflow reduction, groundwater over-exploitation, soil erosion, and decreased vegetation coverage. In this research, we employed the DMC approach, SWAT model, InVEST model, and CA-Markov model to quantitatively analyze the correlation between alterations in streamflow and sediment within this area and three influential factors: climate variations, LUCC, and other human interventions. Furthermore, we clarified the relative contributions of climate factor elements, land-use types, and human activities to streamflow and sediment in this region. The findings indicate a decline in the annual streamflow and sediment quantities observed within this region from 1960 to 2020, with reduction rates of 1.27 × 108 m3/10 a and 129.07 × 104 t/10 a, respectively, and an abrupt change year in 1983 and 1982. Compared to the annual streamflow, the annual sediment volume demonstrates more substantial variation. Based on the constructed model, three scenario simulation periods: P0 (1962–1981/1982), P1 (1983/1982–1999), and P2 (2000–2020) were set. Compared with P0, the respective contribution rates of climatic variation, land use, and other human intervention to streamflow (sediment volume) were 15.247% (19.601%), −0.03% (−1.349%), and 84.783% (81.748%) in P1. In P2, the contribution rates of these three factors on streamflow (sediment volume) were 9.160% (9.128%), 0.211% (3.053%), and 90.629% (84.818%), respectively. Through a quantitative analysis of climatic factors on streamflow and sediment, we found a positive correlation between precipitation and both streamflow and sediment. Additionally, there is an inverse relationship between temperature and streamflow, but streamflow will increase when temperature rises by 10%. Under three different future land-use scenarios, the variations in streamflow and sediment exhibited as ecological protection scenario &lt; urban expansion scenario &lt; natural development scenario. Changes in streamflow in this region are primarily caused by human intervention that alters the underlying surface. The increase in check dams and silted land could lead the runoff and sediment to decrease. Moreover, compared with the increase in industrial and agricultural water consumption, the increase in urban water consumption is the main factor for human water consumption.

Upper Colorado River Streamflow Dependencies on Summertime Synoptic Circulations and Hydroclimate Variability

Abstract The southwestern United States is highly sensitive to drought, prompting efforts to understand and predict its hydroclimate. Oftentimes, the emphasis is on wintertime precipitation variability, yet the southwestern United States exhibits a summertime monsoon where a significant portion of annual precipitation falls through daily convection activities manifested by a midtropospheric ridge of high pressure. Here, we examine synoptic patterns of the southwestern ridge through a k-means clustering analysis and assess how these synoptic patterns translate into streamflow changes in the upper Colorado River basin. A linear perspective suggests ∼17% of upper Colorado River discharge at the Lee’s Ferry, Arizona, gauge comes from summertime monsoon rains. The ridge of high pressure exhibits diversity in its intensity, structure, and position, inducing changes in moisture advection and precipitation. A ridge shifted north or east of its climatological center increases moisture and precipitation over the southwestern United States, while a ridge toward the south or northwest inhibits precipitation. A ridge east of its climatological center contributes to increased streamflow, whereas a ridge west or northwest of its climatological center decreases streamflow. Cooling in the central tropical Pacific and the Pacific meridional mode region favors an eastward shift of the ridge of high pressure corresponding to wet days. Eastern tropical Pacific warming favors a southward shift of the ridge corresponding to dry days. These results support an intermediate scale between climate forcing and summertime Colorado River discharge through changes in the intensity, structure, and position of the southwestern ridge of high pressure, integral to the U.S. Southwest hydroclimate.

Understanding hydrological processes of glacierized catchments in the western Himalayas by a multi‐year tracer‐based hydrograph separation analysis

AbstractSnow and glacier melt are significant contributors to streamflow in Himalayan catchments, and their increasing contributions serve as key indicators of climate change. Consequently, the quantification of these streamflow components holds significant importance for effective water resource management. In this study, we utilized the spatio‐temporal variability of isotopic signatures in stream water, rainfall, winter fresh snow, snowpack, glaciers, springs, and wells, in conjunction with hydrometeorological observations and Snow Cover Area (SCA) data, to identify water sources and develop a conceptual understanding of streamflow dynamics in three catchments (Lidder, Sindh, and Vishow) within the western Himalayas. The following results were obtained: (a) endmember contributions to the streamflow exhibit significant spatial and seasonal variability across the three catchments during 2018–2020; (b) snowmelt dominates streamflow, with average contributions across the entire catchment varying: 59% ± 9%, 55% ± 4%, 56% ± 6%, and 55% ± 9% in Lidder, 43% ± 6%, 38% ± 6%, 32% ± 4%, and 33% ± 5% in Sindh and 45% ± 8%, 40% ± 6%, 39% ± 6%, and 32% ± 5% in Vishow during spring, summer, autumn, and winter seasons, respectively; (c) glacier melt contributions can reach ~30% to streamflow near the source regions during peak summer; (d) The primary uncertainties in streamflow components are attributed to the spatiotemporal variability of tracer signatures of winter fresh snow/snowpack (±1.9% to ±20%); (e)regarding future streamflow components, if the glacier contribution were to disappear completely, the annual average streamflow in Lidder and Sindh could decrease up to ~20%. The depletion of the cryosphere in the region has led to a rapid increase in runoff (1980–1900), but it has also resulted in a significant streamflow reduction due to glacier mass loss and changes in peak streamflow over the past three decades (1990–2020). The findings highlight the significance of environmental isotope analysis, which provides insights into water resources and offers a critical indication of the streamflow response to glacier loss under a changing climate.

A novel coupled algorithm-based method, and the characteristics and driving mechanism of water shortage in the upper Yellow River

ABSTRACT Gaining a clear understanding of the spatiotemporal characteristics of water shortage and their driving mechanism in the upper Yellow River (UYR) is crucial for the assessment and effective management of water resources in the region. The standardized streamflow index (SSI) and the improved Hilbert-Huang transform (IHHT) algorithm are combined to form a coupled SSI-IHHT method (CSIHM). The streamflow above Lanzhou Station over 1969–2015 is analysed. Results show that summer and autumn are high-risk periods of continuous water shortage. Annual streamflow has inter-annual change cycles of 3.5–9.0 a and inter-decadal change cycles between 16.4 and 28.2 a. The annual streamflow change is mainly affected by climate change. But the seasonal streamflow change is mainly influenced by human activities resulting from the operation of reservoirs. The CSIHM has advantages of mutual verification of the results and wide applicability to the field of water shortage.

Hydrological changes in Serra da Mantiqueira Range watersheds (Southeast Brazil)

The Serra da Mantiqueira Environmental Protection Area is one of the most important Atlantic Forest biodiversity hotspots in the World, and one of the main water sources for the Brazilian Southeast Region. In this study, we analyze the existence and characteristics of streamflow changes in two watersheds (Sapucaí-Mirim and Sapucaí-Guaçu River watersheds) of the Serra da Mantiqueira Range, and if these changes are due to climate change, alterations of land cover and/or external factors. Mann-Kendall and Pettit tests were used to detect changes in streamflow, rainfall and evapotranspiration data series, at different time scales. The characteristics and magnitude of land cover changes were evaluated from multi-temporal maps, produced from satellite images and the supervised classification technique. The results show an increase in winter rainfall at the two watersheds studied. No changes were detected in the streamflows of the Sapucaí-Mirim River Basin. The summer streamflow of Sapucaí-Guaçu River watershed reduced at a rate of −0.035 m³.s−1. year−1. In addition, there were sudden streamflow changes in the summer (from the year 1967) and autumn (from the year 1988) in Sapucaí-Guaçu watershed. Furthermore, the reference summer evapotranspiration of the Sapucaí-Guaçu watershed showed an increasing trend and an abrupt increase (in 1988), besides a sudden reduction of actual evapotranspiration in 2006. The integrated analysis of these results, together with the changes in land cover and population, allow us to conclude that the reductions in summer and autumn streamflows at the Sapucaí-Guaçu watershed were probably due to the increase in the water withdrawal for public supply, added to the effects of urbanization on the hydrology of the watershed.

Spatiotemporal variations of inter- and intra-annual extreme streamflow in the Yangtze River Basin

Climate change has led to anomalous fluctuations in extreme streamflow from global river systems, and the superposition of human activities such as damming has compounded the changes in extreme streamflow, affecting floods and river ecosystems. However, muti-temporal scale variations of extreme streamflow and the dominant driving factors were limitedly understood. In this study, we examined the changing patterns of inter- and intra-annual extreme (maximum 1-day, consecutive 3-days and 7-days) streamflow (including magnitude and timing) in the Yangtze River Basin (YRB) from the 1940 s to 2020. Furthermore, the roles of ENSO events and dams on temporal anomalies of extreme streamflow at inter- and intra-annual scales were identified in the whole basin. We found that the annual streamflow extremes increased in the source YRB and the middle and lower YRB but decreased in the upper YRB. The extreme streamflow during spring and autumn was characterized by increasing trends in the source and decreasing trends in other reaches. The occurrence timing of winter extreme streamflow in the upper and middle YRB was significantly delayed. The inter-annual extreme streamflow in the source and upper YRB had a negative relationship with ENSO, while the positive relationship held in the middle and lower YRB. The major anomalies (>50 %) of annual extreme streamflow generally occurred in ENSO (1+2) yrs, while precipitation contributes to the seasonal distribution of extreme streamflow. There was a good correlation between precipitation and both annual and summer extreme streamflow in the lower YRB, but the relationship completely shifted in the upper YRB after 2003. Further, the construction of dams has severely affected extreme streamflow, leading to a stepwise drop in annual and summer/autumn flows and a sudden rise in spring/winter flows. This study facilitates the prediction of extreme streamflow and the development of sustainable basin management strategies.

Streamflow responses to forest and climate change in the boreal Da Hinggan Mountains, Northeastern China

AbstractBoreal forests cover vast stretches of land across all continents and represent a principal source area of clean water in the northern hemisphere. Increasingly, studies are conducted on the impact of changes in boreal forest cover on water yield; however, much remains unknown concerning the effects of forest structure changes on stream discharge over the course of multi‐decadal forest harvest cycles. In this study, we analysed long‐term hydrometeorological and forest dynamics data spanning from 1990 to 2016 from a typical boreal forest watershed in the Da Hinggan Mountains in northern China. Our objective was to quantify how changes in forest age and tree species composition affect mean annual streamflow and flow regimes in the context of a changing climate. To distinguish the effects of forest and climate changes on annual streamflow from one another, we employed a combination of a sensitivity‐based method and a temporal trend analysis. Further, we evaluated the impact of forest changes on flow regimes using four indicators: magnitude, duration, frequency, and variability. The results indicated that mean annual streamflow increased by 55.8 mm, with forest changes contributing +61.4 mm compared to −5.6 mm due to climate change (negative effect). This increase occurred when approximately 20% of mature coniferous forests transitioned to mid‐age broad‐leaved forests, accompanied by a 10% increase in total stock volume during the later period. Finally, the effect of changes in forest structure on flow regime were not significant. Our results underscore that variations in forest structure affect streamflow differently depending on stand age and species proportions. Therefore, dynamic forest structure management can benefit not only carbon sequestration but also water supply capacity in boreal forested watersheds.

Flood Inundation and Streamflow Changes in the Kabul River Basin under Climate Change

The Kabul basin yields around 16% of the total annual water availability in Pakistan. Changing climate will alter the precipitation regime in terms of intensity and frequency, which will affect the water yield and cause flood hazards. Against this background, this study aims to quantify the impacts of changing climate on the water yield, its timings, and, more importantly, the associated flood hazards in the transboundary Kabul basin. For this, we used a rainfall-runoff inundation (RRI) model coupled with the snow and glacier melt routines and drove it for historical and future climates simulated by the atmosphere-only general circulation model (AGCM) at 20 km spatial resolution. The model simulations reveal that rainfall runoff contributes around 50% of the annual flows, and the rest is contributed by glaciers and snow melts. Annual precipitation is projected to increase by 14% from 535 mm, whereas temperatures will rise by 4.7 °C. In turn, the Kabul River flows will only increase by 4% to 1158 m3s−1 from 1117 m3s−1, mainly due to an increase in winter flows. In contrast to a minute increase in the mean river flows, the maximum flood inundation area is projected to increase by 37%, whereas its depth will rise between 5 and 20 cm.

A call to action: The need for evaluation of carbon storage by lacustrine large woody debris

Abstract Global climate change and the push to develop Natural Climate Solutions have increased urgency around the need to quantify, capture, and store carbon to reduce atmospheric concentrations of carbon dioxide—but we may be overlooking a potentially important, long‐term carbon sink. Carbon stored in large woody debris (LWD) in lakes is largely missing from local and global carbon budgets. Waterlogged LWD may remain relatively intact in cold, low‐oxygen hypolimnetic regions for decades to centuries, while LWD buried in lake‐bottom sediments may store carbon for millennia. We postulate that lacustrine LWD may be an important component of local and global carbon budgets, and modern land‐use effects (deforestation, agriculture, stream flow changes) may be reducing inputs of LWD into long‐term lacustrine carbon pools. Quantifying lacustrine LWD, particularly in large lakes, is logistically challenging, resulting in a data gap in carbon budgets. Here, we propose that new aerial and underwater technologies be employed to map and quantify littoral LWD and deposits of sunken and buried LWD to estimate carbon storage and the role of lacustrine LWD in regional and global carbon cycling.

Irrigation intensification impacts sustainability of streamflow in the Western United States

Quantifying the interconnected impacts of climate change and irrigation on surface water flows is critical for the proactive management of our water resources and the ecosystem services they provide. Changes in streamflow across the Western U.S. have generally been attributed to an aridifying climate, but in many basins flows can also be highly impacted by irrigation. We developed a 35-year dataset consisting of streamflow, climate, irrigated area, and crop water use to quantify the effects of both climate change and irrigation water use on streamflow across 221 basins in the Colorado, Columbia, and Missouri River systems. We demonstrate that flows have been altered beyond observed climate-related changes and that many of these changes are attributable to irrigation. Further, our results indicate that increases in irrigation water use have occurred over much of the study area, a finding that contradicts government-reported irrigation statistics. Increases in crop consumption have enhanced fall and winter flows in some portions of the Upper Missouri and northern Columbia River basins, and have exacerbated climate change-induced flow declines in parts of the Colorado basin. We classify each basin’s water resources sustainability in terms of flow and irrigation trends and link irrigation-induced flow changes to irrigation infrastructure modernization and differences in basin physiographic setting. These results provide a basis for determining where modern irrigation systems benefit basin water supply, and where less efficient systems contribute to return flows and relieve ecological stress.

Assessing the Influence of Upstream Basin and Climatic Characteristics on Post-Dam Downstream Streamflow Changes: Empirical Insights from Peninsular India

Assessing the Influence of Upstream Basin and Climatic Characteristics on Post-Dam Downstream Streamflow Changes: Empirical Insights from Peninsular India