Annual Streamflow Research Articles

Changes in Snow Drought and the Impacts on Streamflow Across Northern Catchments

AbstractSnow drought, characterized by an anomalous reduction in snowpack, exerts profound hydrological and socioeconomic impacts in cold regions. Despite its significance, the influence of diverse snow drought types, including warm, dry, and warm‐and‐dry variants, on streamflow remains inadequately understood. Here we present the first hemispheric‐scale, observation‐based assessment of snow drought patterns and the impacts on seasonal and annual streamflow (Q) across 3049 northern catchments over 1950–2020. Our findings reveal that catchments with a lower mean annual snowfall fraction () exhibit a heightened prevalence and severity of warm and warm‐and‐dry snow droughts, whereas high‐ experience a more prevalent but less severe dry snow drought. This disparity arises from distinct sensitivities of snowpack to cold‐season precipitation and temperature. In addition, dry and warm‐and‐dry snow droughts induce a reduction in Q during both cold and warm seasons, culminating in a significant decrease in annual Q. Conversely, warm snow drought increases annual Q in catchments with but decreases annual Q in catchments with , attributable to a trade‐off between increased cold‐season streamflow (Qc) and decreased warm‐season streamflow (Qw). With ongoing climate warming, a continued reduction in snowfall is anticipated, which is expected to further increase the frequency and severity of warm and warm‐dry snow droughts. These circumstances, particularly impactful under low conditions, are poised to present formidable challenges for water resources management in cold regions globally.

Climatic and Anthropogenic Influences on Long-Term Discharge and Sediment Load Changes in the Second-Largest Peninsular Indian Catchment

In recent decades, understanding how climate variability and human activities drive long-term changes in river discharge and sediment load has become a crucial field of research in fluvial geomorphology, particularly for South Asia’s densely populated and environmentally sensitive regions. This study analyses spatio-temporal trends in water discharge (Qd) and sediment load (Qs) in the Krishna basin, Peninsular India’s second-largest catchment. Using nearly 50 years of daily discharge, sediment concentration, and rainfall data from the Central Water Commission (CWC) and India Meteorological Department (IMD), we applied Mann–Kendall, Pettitt tests, and double mass equations to detect long-term trends, abrupt changes, and the relative influence of climate and anthropogenic effects. Results showed a notable decline in the annual discharge, with 15 of 20 stations showing decreasing trends, especially along the Bhima, Ghataprabha, and lower Krishna rivers. The annual stream flow data showed a 53% decline in the mean Qd from 26.01 × 109 m3 year−1 before 2000 to 12.32 × 109 m3 year−1 after 2000 at the terminal station. Eight of ten gauging stations showed a significant decrease (p-value < 0.05) in their annual sediment load, with a 76% reduction across the Krishna basin after its changepoint in 1983. The Pettitt test identified a statistically significant downward shift in discharge at seven stations. Double mass plots indicate that anthropogenic factors, such as large-scale reservoirs and water diversion, are the main contributors, accounting for 82.7% of sediment decline, with climatic factors contributing 17.1%. The combined trend analysis and double mass plots confirm these findings, underscoring the need for further study of human impacts on the basin’s hydro-geomorphology. This study offers a clear and robust approach to quantifying the relative effects of climate and human activities, providing a versatile framework that can enhance understanding in similar studies worldwide.

Mining and Climate Change Alters Water Storage and Streamflow Dynamics of Northern Peatland‐Dominated Catchments

AbstractThe Hudson Bay Lowlands (HBL) of northern Ontario, a globally significant carbon store, are characterized by expansive peatland complexes of patterned bogs and fens, which play a vital role in regional water regulation. These peatlands are threatened by disturbance from large‐scale resource extraction and projected climate change, both of which have the potential to compromise their ecohydrological function. Field measurements and numerical modeling were used to investigate the hydrological responses of peatlands and downgradient streamflow as a consequence of disturbance from mining and shifts in climate, individually and in combination. Mine dewatering reduced groundwater storage by as much as 150 mm, equivalent to a water table lowering of 75 cm, thereby decreasing annual streamflow by 66% in impacted tributaries. Although the projected increases to precipitation and evapotranspiration due to climate change were approximately balanced, resulting in minor changes to storage, there were pronounced shifts in the temporal patterns of streamflow, with a diminished snowmelt and spring freshet occurring a month earlier. When considering the cumulative impacts of climate change coupled with mining, a potential shift in peatland ecohydrology toward new equilibria is plausible, implying altered water movement across the landscape and compromised ecosystem function. This study emphasizes the critical need for further monitoring and modeling efforts to characterize the thresholds and mechanisms driving these ecohydrological changes. This research will guide future investigations on the implications of disturbance on local and regional hydrologic connectivity and facilitate the protection of peatland ecosystems in the HBL and other northern peatland‐dominated landscapes.

Potential of tree-ring chronologies for multi-centennial streamflow reconstructions: an insight from Nepal

Abstract. Rivers in the Himalayan and adjacent mountain regions are the lifelines of over 1 billion people and are the backbone of civilizations therein. The short gauge records of Nepal do not provide a sufficient time window to understand the natural variations in river discharge from a long-term climate perspective. By developing a network of over 100 tree-ring chronologies across Nepal, we checked their hydrological sensitivity for long-term streamflow reconstruction. This shows huge potential for long-term annual or seasonal streamflow reconstructions in different river basins of Nepal. A robust reconstruction model was developed between tree growth and streamflow, capturing 56 % of the variance in the actual data, and was used to reconstruct the March–July monthly average streamflow of Sinja Khola (river) at Diware from AD 1700 to 2013. The reconstruction revealed several dry and pluvial periods with the recent decline in the streamflow in the Sinja River. We found short- (2 to 8.7 years) to medium-term (35.2 years) periodicities in the reconstruction that are likely to be associated with climatic oscillations, such as the El Niño–Southern Oscillation (ENSO), the Atlantic Multidecadal Oscillation (AMO), and the North Atlantic Oscillation (NAO), along with the influence of local circulation patterns. Since Sinja Valley is related to the origin of the Nepali language and civilization, the information on long-term streamflow will be beneficial for water resource management in the context of rapid climate change and for preparedness for water-induced disasters in the region.

Quantifying the Impacts of Fire‐Related Perturbations in WRF‐Hydro Terrestrial Water Budget Simulations in California's Feather River Basin

ABSTRACTWildfire activity in the western United States (WUS) is increasingly impacting water supply, and land surface models (LSMs) that do not explicitly account for fire disturbances can have critical uncertainties in burned areas. This study quantified responses from the Weather Research and Forecasting Hydrological modelling system (WRF‐Hydro) to a suite of fire‐related perturbations to hydrologic soil and runoff parameters, vegetation area, land cover classifications and associated vegetation properties, and snow albedo across the heavily burned Feather River Basin in California. These experiments were used to quantify the impacts of fire‐related perturbations in model simulations under the observed meteorological conditions during the 2000–2022 water years and determine whether applying these fire‐related perturbations enhanced post‐fire model accuracy across the 11–12 post‐fire months evaluated herein. The most comprehensive fire‐aware simulation consistently modelled enhanced annual catchment streamflow (by 8%–37%), subsurface flow (by 72%–116%), and soil moisture (by 4%–9%), relative to the baseline simulation which neglected fire impacts. Simulated fire‐enhanced streamflow was predominately attributable to fire‐induced vegetation area reductions that reduced transpiration. Simulated streamflow enhancements occurred throughout the water year, excluding early‐summer (e.g., May–June) when the baseline simulation modelled relatively more snowmelt and streamflow because fire perturbations caused earlier model snow depletion. Vegetation area reductions favoured increased model ground snow accumulation and enhanced snow ablation while imposed snow albedo darkening enhanced ablation, ultimately resulting in similar peak SWE and earlier snow disappearance (on average by 8‐days) from the most comprehensive fire‐aware simulation relative to the baseline simulation. The baseline simulation had large degradations in streamflow accuracy following major fire events that were likely partially attributable to neglecting fire disturbances. Applying fire‐related perturbations reduced post‐fire streamflow anomaly biases across the three study catchments. However, remaining large post‐fire streamflow uncertainties in the fire‐perturbed simulation underscores the importance of additional observationally constrained fire‐disturbance model developments.

Predicting future impacts of climate and land use change on streamflow in the middle reaches of China's Yellow River

With increasing temperatures, changing weather patterns and ongoing development, it is becoming increasingly important to clarify the evolution mechanism of future regional streamflow processes and their controlling factors. In this study, an integrated framework for watershed streamflow prediction based on a Global Climate Model (GCM), the Patch-generating Land Use Simulation model (PLUS), and the Soil and Water Assessment Tool (SWAT) was proposed in the middle Yellow River. The results indicate that, compared with the baseline period (1989–2018), levels of precipitation and maximum and minimum temperatures are expected to increase in the next 30 years, resulting in a warmer and wetter regional climate. Under various climate scenarios, the annual streamflow is projected to increase by 49.2–115.1%. The acreage of various land types may have tended to be saturated, and the main land types such as cropland, forest and grassland have little change (−6.6%-0.6%), so the impact on streamflow will be correspondingly reduced. Under various land use scenarios, the annual streamflow is projected to increase by 5.0%–7.3%. The annual average streamflow trends under the combined climate and land use scenarios are consistent with the climate change scenarios, while the mean values corresponding to the combined scenarios are higher than those of the single scenario. Findings show that climate change is the main driver influencing streamflow, with a contribution of 86.3%–95.1%. This study deepens understanding of the change pattern and influence mechanism of the streamflow process, which can provide a scientific basis for the development and refinement of regional ecological construction plans.

Temporal Variability of Hydroclimatic Extremes: A Case Study of Vhembe, uMgungundlovu, and Lejweleputswa District Municipalities in South Africa

The current study investigated hydroclimatic extremes in Vhembe, Lejweleputswa, and uMgungundlovu District Municipalities based on streamflow data from 21 river gauge stations distributed across the study site for the period spanning 1985–2023. Statistical metrics such as the annual mean and maximum streamflow, as well as trends in annual, maximum, seasonal, and high/low flow, were used to evaluate the historical features of streamflow in each of the three district municipalities. Moreover, the Standardized Streamflow Index (SSI) time series computed from streamflow observations at 3- and 6-month accumulation periods were used to assess hydroclimatic extremes, including drought episodes, proportion of wet/dry years and trends in SSI, drought duration (DD), and drought severity (DS). The results indicate that the three district municipalities have experienced localized and varying degrees of streamflow levels and drought conditions. The uMgungundlovu District Municipality in particular has experienced a significant decline in annual and seasonal streamflow as well as an increase in drought conditions during the 38-year period of analysis. This is supported by the negative trends observed in most of the assessed metrics (e.g., annual, maximum, seasonal, low/high flow, and SSI), whereas DD and DS showed positive trends in all the stations, suggesting an increase in prolonged duration and severity of drought. The Lejweleputswa District Municipality depicted positive trends in most of the assessed metrics, suggesting that streamflow increased, whereas drought decreased in the region over the 38-year period of study. Moreover, the Vhembe District Municipality experienced both negative and positive trends, suggesting localized variations in dry and wet conditions. The results presented in this study contribute towards drought monitoring and management efforts in support of policy- and decision-making that aim to uplift water resources management and planning at local and district municipality levels.

How uncertainty in calibration data affects the modeling of non-point source pollutant loads in baseflow

Baseflow is a major transport pathway for non-point source (NPS) pollutants. Watershed water quality (WWQ) models calibrated by low-quality data may produce misleading predictions of baseflow NPS pollutant loads, resulting in poor management decisions. We evaluated how models of the baseflow nitrate loads in the Huron River basin, southwest of Lake Erie, were affected by uncertainty in the calibration data. Based on a five-year time series of daily streamflow, nitrate concentration, and specific conductance, two sets of “observed” baseflow nitrate load data that include uncertainty were estimated using various tracer-based and non-tracer-based hydrograph separation methods, in conjunction with assumptions regarding baseflow nitrate concentrations. We calibrated the Soil and Water Assessment Tool plus (SWAT+) model with the two “observed” data sets and used the Generalized Likelihood Uncertainty Estimation (GLUE) approach to quantify parameter and predictive uncertainties. The results showed that baseflow accounted for 26 %–34 % of the mean annual total streamflow (11.8 m3/s) and 8 %–37 % of the mean annual total nitrate load (14.3 kg·ha−1·year−1) in the Huron River basin. The baseflow and nitrate load estimates from the non-tracer-based methods resembled those from the tracer-based method but had greater uncertainty. The posterior parameter distributions, as well as the weighted means and 90 % prediction intervals of the simulated baseflow nitrate loads, exhibited minimal variation when different calibration data sets for SWAT+ and different threshold likelihood values for GLUE were used. Our analysis emphasizes the necessity of calibrating WWQ models with baseflow pollutant loads/concentrations when addressing water quality issues related to baseflow. It also demonstrates the feasibility of utilizing multiple non-tracer-based hydrograph separation methods to estimate baseflow NPS pollutant loads. These non-tracer-based methods offer a simplicity and broader applicability compared to tracer-based methods. This study has provided insights into how calibration data uncertainty impacts the modeling of NPS pollution in baseflow and highlights the practical value of non-tracer-based hydrograph separation methods.

Drought‐Rich Periods Are More Likely Than Flood‐Rich Periods in Brazil

AbstractStreamflow exhibits persistent decadal variability; however, it is unclear if the magnitude and spatial extent of these variabilities are symmetric for droughts and floods. Here, we examine drought‐rich and flood‐rich periods in 319 streamflow gauges in Brazil from 1940 to 2020. Drought‐ and flood‐rich periods are detected by computing annual streamflow minima and maxima time series and using scan statistics to verify if events exceeding a threshold follow a Bernoulli process. We contrast streamflow time clustering with rainfall, evaporation, water abstraction, the Atlantic Multidecadal Oscillation (AMO), and the Pacific Decadal Oscillation (PDO). We detected a higher spatial frequency of drought‐ than flood‐rich periods. For 5‐year return period thresholds, drought‐rich periods are observed in 81% of the basins, 16.7 times the false positive rate (4.8%) and 4.7 times flood‐rich periods (17%). This asymmetry is linked with sharp increases in water abstractions since the 1990s and a higher prevalence of rainfall‐poor periods (41% of gauges) compared to rainfall‐rich (22% of gauges), which we interpret as being further amplified into drought‐rich periods due to an interannual persistence of water storage deficits. Brazil experienced a dry period until the 1960s, extensive flooding in the 1980s, and record low flows from the 2000s onward. Drought and flood‐rich periods are well aligned with rainfall clustering, water abstractions, the AMO and PDO. Droughts‐rich periods are more frequent in shorter time scales (several years to one decade) and flood‐rich periods in longer time scales (a few decades). Our findings highlight the nonlinearity and asymmetry of drought and flood change at decadal scales.

Understanding the drivers of the catchment hydrological cycle of the Jonkershoek Valley catchment, South Africa

Understanding trends in hydro-climate variables and the impacts of land use on the streamflow is crucial for the development of appropriate catchment water management strategies. Jonkershoek (146 km2) is an important headwater catchment in the Table Mountain Group (TMG) geological region, contributing flow to the Cape Winelands District Municipality in the Western Cape. This study analyses hydro-climate variables at annual, monthly, and seasonal scales using an integrated approach composed of statistical homogeneity testing for abrupt changes, Mann-Kendall tests for trend analysis, and the Indicators of Hydrological Alteration (IHA) tool for streamflow alterations. Analyses were conducted for three headwater sub-catchments within the Jonkershoek value, each with different land use history.Homogeneity test of rainfall and streamflow data spanning from 1946 to 2019 identified gradual downwards change points for annual rainfall and streamflow across the sub-catchments. Moreover, the change points for streamflow were inconsistent with those of rainfall. The identified change points in streamflow were consistent with the timing of afforestation activities in Tierkloof, whereas in Bosboukloof and Langrivier they could be attributed to earlier climatic variability. Furthermore, Mann-Kendall test detected significant (p < 0.05) decreasing trends for both annual and seasonal rainfall which coincided with most of the streamflow trends. Trends were strongest for the winter season suggesting a possible shift in climate patterns which influence winter rainfall. Winter streamflows declined by 15.5%–39.5%. Analysis of hydrological flow indices indicated significant decrease in 1-,7- and 30-day annual maximum extremes during afforestation which were attributed to high evapotranspiration rates of pines. The opposite was observed during clearfelling period in Bosboukloof. The median monthly flow also showed a decrease for winter months. This shows that climate variability and land-use change by afforestation have major impacts on streamflow. The findings of this study are important to inform policymakers on the impacts of climate change and land use, allowing pro-active mitigation and adaptation.

Combining the digital filtering method with the SWAT model to simulate spatiotemporal variations of baseflow in a mountainous river basin

Study regionGanjiang River Basin, a typical mountainous river basin which located on the south bank of the middle-lower Yangtze River. The Ganjiang River is the seventh largest tributary of the Yangtze River. Study focusBaseflow, a key recharge source for the river streamflow. This study combined the digital filtering method with the SWAT model to examine the temporal and spatial patterns of baseflow across the Ganjiang River Basin, and quantitatively assessed land use change impact on baseflow. New hydrological insights for the regionBaseflow in the Ganjiang River Basin shows a "single peak" intra-annual distribution. Monthly variations of streamflow and baseflow across the basin are different. The variation of baseflow index is generally opposite to that of streamflow. A positive correlation has been noted between the annual baseflow and streamflow, while a negative correlation was found between the annual baseflow index and precipitation. Due to the potential influence of basin topography, river flow direction and rock layer distribution, baseflow and baseflow modulus showed a spatially increasing trend from south to north, with the northwest region having extremely strong groundwater recharge. In comparison to the basic scenario, under extreme land use scenarios of forest, grassland, and cropland, baseflow may experience an increase of 14.7 % and 2.9 %, while witness a decrease of 13.9 %. All results improve the understanding of baseflow spatiotemporal variations in river basins.

Evaluating the dynamics of climate and anticipated snow cover changes on the hydrological response of rivers in the Hindu Kush Himalaya region

ABSTRACT The research aims to assess the interplay between climate dynamics and snow cover changes, informing water resource management. Utilizing the SWAT model with historical and future data, hydrological responses in the Marshyangdi River Basin are examined. The model's performance confirms its ability to simulate runoff components effectively. Projections indicate a concerning decrease in snow cover area for 2030, 2050, and 2090, with declines of 2.03, 4.03, and 14.20%, respectively, attributed to global warming and human activities. Isolating climate change reveals substantial increases in stream flow, notably pre-monsoon surges under different scenarios, with projected increments of 84 and 130% under SSP245 and SSP585, respectively. Analysis of snow cover impact shows a slight increase in annual stream flow, with a 3.54% anticipated decrease during the post-monsoon period, raising concerns for water availability in the dry season. Comparing both impacts reveals no significant differences in stream flow or precipitation. Annual stream flow increases under different scenarios, driven by precipitation, with varying impacts. Climate change emerges as the dominant driver, affecting surface runoff, groundwater, and evapotranspiration. This research unravels complex relationships between climate change, snow cover, and hydrological responses, providing valuable insights for water resource management in mountainous regions like the Hindu Kush Himalaya.

Streamflow trends and flood frequency analysis: a regional study of the UK.

In recent years, the escalating effects of climate change on surface water bodies have underscored the critical importance of analyzing streamflow trends for effective water resource planning and management. This study conducts a comprehensive regional investigation into the streamflow rate trends of 18 rivers across the United Kingdom (UK). An enhanced Mann-Kendall (MK) test was employed to meticulously analyze both rainfall and streamflow trends on monthly and annual scales. Additionally, the Innovative Trend Analysis (ITA) method was applied to elucidate the variability of streamflow rates, providing a more nuanced understanding of hydrological changes in response to climatic shifts. MK test reveals statistically significant positive trends in streamflow rates, particularly for rivers in south-central Scotland and northern England. Specifically, in January, rivers such as the Tay at Ballathie, Tweed at Peebles, and Teviot at Ormiston showed Z-scores above 2. Annually, similar positive trends were observed, with the Tay at Ballathie (Z = 3.42) and Nith at Friars Carse (Z = 3.35) exhibiting the highest increases in streamflow rates. The ITA method showed no relevant trends for the lowest values of streamflow, except for the Thames at Kingston, while considerable variability was observed for the highest streamflow rates, with several rivers showing positive trends and, however, some England rivers, like Bure at Ingworth, Test at Broadlands, and Trent at Colwick, showing negative trends. From this perspective, a more in-depth analysis of the extreme streamflow trends was carried out. In particular, the flood frequency of the maximum annual streamflow was assessed, based on the fitting of the Generalized Extreme Value (GEV) distribution on the annual maxima. Increasing location parameter (μ) and return period trends were observed for several rivers across the UK. In particular, the Tay at Ballathie (Scotland) showed the most marked increase, with μ that ranged from about 730 m3/s to more than 900 m3/s. At the same time, slight decreasing trends were observed for the Trent River (μ from 378 m3/s to 341 m3/s). The critical comparison of the MK test, ITA, and GEV distribution fitting revealed both agreements and discrepancies among the methods. While the analyses generally aligned in detecting significant trends in streamflow rates, notable discrepancies were observed, particularly in rivers with negligible trends. These inconsistencies highlight the complexity of hydrological responses and the limitations of individual methods. Overall, the study provides a comprehensive view of how streamflow dynamics are evolving in UK rivers, highlighting regional variations in the impact of climate change. This understanding can improve water resource management strategies by integrating diverse analytical approaches.

Impacts of Climate Change on Streamflow on Dawa Sub-watershed, Genale-Dawa River Basin, Southern Ethiopia

&amp;lt;i&amp;gt;Climate change is statistical variations over an extended period in the features of the climate system, such as variations in global temperatures and precipitation, caused by human and natural sources.&amp;lt;/i&amp;gt; In this study aimed to measure and examine how streamflow in the Dawa sub-basin, Genale Dawa River basin was affected by climate change. It used the average of five regional climate models from the Coordinated Regional Climate Downscaling Experiment (CORDEX) Africa, under two different scenarios of Representative Concentration Pathways: RCP4.5 and RCP8.5. The baseline scenario was based on the data from 1975 to 2005, while the future scenarios were based on the data from 2020s (2025–2054) and 2050s (2055–2084). The HBV hydrological model used to assess the impact on streamflow. The HBV model showed good statistical performance in simulating the impact of climate change on streamflow, with a coefficient of determination (R&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt;) of 0.88 and Nash-Sutcliffe Efficiency (NSE) of 0.77 for monthly calibration, and R&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt; of 0.86 and NSE of 0.83 for monthly validation. The impacts quantified using the mean monthly changes in precipitation, maximum and minimum temperatures. The bias-corrected precipitation and temperature showed a reasonable increase in both future periods for both RCP 4.5 and RCP 8.5 scenarios. These changes in climate variables resulted in a decrease in mean annual streamflow by 1.6 and 3.5% for RCP 4.5 and by 4.6 and 4.9% for RCP 8.5 scenarios of the 2020s and 2050s, respectively. Based on the analysis that predicted a drop in precipitation during the months, and seasons and an increase in precipitation during the &amp;lt;i&amp;gt;Belg&amp;lt;/i&amp;gt; season, with a corresponding decrease and rise in stream flow throughout the watershed. So to offset the variation in the watershed, community should adopt various; Soil and water conservation technologies, Using drought tolerant crops, Implementing various trees and appropriate design and applying a water harvesting structure like in-situ, internal or micro catchment, external or macro catchment water harvesting and Surface runoff harvesting. This result offers useful information for current and future water resource management in the basin and similar other watershed in the country.

Can Agricultural Managed Aquifer Recharge (Ag‐MAR) Recover Return Flows Under Prior Appropriation in a Warming Climate?

AbstractGroundwater return flow to streams is important for maintaining aquatic habitat and providing water to downstream users, particularly in irrigated watersheds experiencing water scarcity. However, in many agricultural regions, increased irrigation efficiency has reduced return flows and their subsequent in‐stream benefits. Agricultural managed aquifer recharge (Ag‐MAR)—where artificial recharge is conducted via irrigation canals and agricultural fields—may be a tool to recover these return flows, but implementation is challenged by water supply and water management. Using climate‐driven streamflow simulations, an integrated operations‐hydrology model, and a regional groundwater model, we investigated the potential for Ag‐MAR to recover return flows in the Henrys Fork Snake River, Idaho (USA). We simulated potential Ag‐MAR operations for water years 2023–2052, accounting for both future water supply conditions and local water management rules. We determined that Ag‐MAR operations reduced springtime peak flow at the watershed outlet by 10%–14% after accounting for return flows. Recharge contribution to streamflow peaked in July and November, increasing July–August streamflow by 6%–14% and November–March streamflow by 9%–14%. Furthermore, sites where Ag‐MAR was conducted incidental to flood irrigation had more water available for recharge, compared to sites requiring recharge rights, which are junior in priority to agricultural rights. Mean annual recharge volume for the incidental recharge sites averaged 12% of annual natural streamflow, ranged from 269 to 335 Mm3, and was largely available in April and October. We demonstrate Ag‐MAR can effectively recover groundwater return flows when applied as flood irrigation on agricultural land with senior‐priority water rights.

Understanding the effects of afforestation on water quantity and quality at watershed scale by considering the influences of tree species and local moisture recycling

Forest restoration emerges as a sustainable practice to counteract biodiversity loss and enhance ecosystem services such as carbon sequestration and water quality improvement. However, more research is necessary on the hydrological effects of forest restoration under different strategies such as tree species options. In this study, we investigate how afforestation with longleaf pine (Pinus palustris) and loblolly pine (Pinus taeda L.) may affect the full hydrologic cycles including precipitation (P) and water quality across two large watersheds: the Alabama-Coosa-Tallapoosa (ACT) and Tombigbee-Black Warrior (TBW) river basins in the southeast United States. To capture the impacts of afforestation on precipitation, we leveraged the Soil and Water Assessment Tool (SWAT) model and a local moisture recycling ratio (LMR) dataset to establish a relationship between model-simulated evapotranspiration (ET) and LMR. Longleaf pine and loblolly pine have contrasting forest structure characteristics that affect model parameters and hydrological responses. Results showed that afforestation with longleaf pine increased mean annual ET by 3 % (25 mm/year) and 6 % (48 mm/year) across the ACT and TBW watersheds, respectively. As a result, mean annual streamflow decreased by 3.3 % (18 mm/year) and 1.6 % (11 mm/year) in the ACT and TBW watersheds, respectively. In contrast, afforestation with loblolly pine led to larger increases in mean annual ET of 17 % (131 mm/year)and 10 % (79 mm/year) in affected areas in the ACT and TBW watersheds, respectively. As a result, mean annual streamflow decreased by 5.2 % (29 mm/year) and 2.8 % (19 mm/year) at the watershed level in the ACT and TBW watersheds, respectively. Overall, the afforestation scenarios led to decreases in watershed-scale sediment and nutrient exports, especially under longleaf pine afforestation. Large-scale afforestation had negligible effects on precipitation via local moisture recycling at the watershed scale. Our study indicates that the choices of tree species and forest structure are important to water yield in the southeastern U.S. and that moisture recycling has minor influences on the local water cycle of the study region.

Extent of gross underestimation of precipitation in India

Abstract. The underestimation of precipitation (UoP) in the hilly and mountainous parts of South Asia is estimated by some studies to be as large as the observed precipitation (P). However, UoP has been analyzed to only a limited extent across India. To help bridge this gap, watershed-scale UoP was analyzed using various P datasets within a water imbalance analysis. Among these P datasets, the often-used Indian Meteorological Department (IMD) dataset is of primary interest. The gross UoP was identified by analyzing the extent of the imbalance in the annual water budget of watersheds corresponding to 242 river gauging stations for which quality-controlled data on catchment boundaries and streamflow are available. The water year (WY)-based volume of observed annual P was compared against the observed annual streamflow (R) and the satellite-based actual evapotranspiration (ET). Across many watersheds of both Northern and Peninsular India, spurious water imbalance scenarios (P≤R or P≪R+ET) were realized. It is shown that the management of water, such as groundwater extraction, reservoir storage and water diversion, is generally minimal compared to the annual P in such watersheds. It is also shown that annual changes in terrestrial water storage are minimal compared to the annual P in such watersheds. Assuming that data on R (and, to a lesser extent, ET) are reliable, it is concluded that UoP is very likely the cause of this imbalance. Inter-watershed groundwater flow (IGF) is assumed to be negligible. While the effect of IGF on R is unknown, examples are provided which show that IGF is unlikely to be the cause of the observed imbalance in certain watersheds. All 12 of the P datasets analyzed here suffer from UoP, but the extent of the UoP varies by dataset and region. The reanalysis-based datasets ERA5-Land and IMDAA are less affected by UoP than the IMD dataset. Based on the 30-year period of WY 1985–2014, P for the whole of India could be as much as 19 % (ERA5-Land) to 37 % (IMDAA) higher than that from the IMD, with substantial variability within years and river basins. The actual magnitude of UoP is speculated to be even greater. Moreover, trends seen in the IMD's P are not always present in ERA5-Land and IMDAA. Studies using IMD should exercise caution since UoP could lead to the misrepresentation of water budgets and long-term trends. Limitations of this study are discussed.

Mimicking functional elements of the natural flow regime promotes native fish recovery in a regulated river.

Streamflow regimes that maintain vital functions and processes of aquatic ecosystems are critical to sustaining ecosystem health. In rivers with altered flow regimes, restoring components of the natural flow regime is predicted to conserve freshwater biodiversity by supporting ecological functions and geomorphological processes to which native communities are adapted. However, the effectiveness of environmental flow restoration is poorly understood because of inadequate monitoring and uncertainty in ecological responses to managed changes in specific, quantifiable aspects of the annual streamflow regime. Here, we used time series models to analyze 25 years of fish assemblage data collected before and after environmental flow implementation in a dammed river in California, USA. We examined the response of the fish community to changes in individual components of the flow regime known to support ecosystem functions. We found that as functional flow components shifted toward their predicted natural range, the quasi-extinction risk (likelihood of population declines of >80%) decreased for the native fish assemblage. Following environmental flow implementation, observed changes toward natural ranges of dry season duration, fall pulse flow magnitude, and wet season timing each reduced quasi-extinction risk by at least 40% for the native assemblage. However, functional flow components that shifted away from their predicted natural range, including lower spring recession flows and higher dry season baseflow, resulted in greater quasi-extinction risk for native species. In contrast, non-native species decreased in abundance when flow components shifted toward predicted natural ranges and increased when components shifted away from their natural range. Although most functional flow components remained outside of their natural range following environmental flow implementation, our results indicate that even moderate shifts toward a natural flow regime can benefit native and suppress non-native fish species. Overall, this study provides the most compelling evidence to date of the effectiveness of functional environmental flows in supporting native fish recovery in a highly regulated river.

Past, present and future changes in the annual streamflow of the Lancang-Mekong River and their driving mechanisms

The rapid development of the Greater Mekong Subregion (GMS) makes it essential to understand the major mechanisms controlling the streamflow, especially for the Lancang-Mekong River (abbr. Mekong River). We used instrumental annual streamflow data (1960–2007) from Chiang Saen hydrological station and several gridded hydroclimatic datasets to explore the hydroclimatic evolution of the Mekong River, together with its driving mechanisms. We found that changes in the Mekong streamflow are consistent with precipitation changes, and the Mekong is thus a precipitation-dominated river that is susceptible to the effects of ongoing climate change. The instrumental record of Mekong annual streamflow is closely related to hydroclimatic changes, especially those related to moisture, within the area from the Hengduan Mountains to the Chiang Saen Station. Based on these gridded records, we extended the Mekong annual streamflow record to cover 1891–2021 using nested multiple linear regression fitting. The fitted streamflow explained up to 57.6 % of the instrumental changes and it indicates that the major 2019 drought was not unique over the past century. Despite extremely low precipitation and high temperatures, it is likely that the effects of drought can be mitigated via hydraulic engineering regulation. Climatological analyses showed that the Mekong annual streamflow is driven by the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), which is consistent with observed quasi-interannual cycles of 3–4 years. A multi-model ensemble of CMIP6 revealed that the Mekong annual streamflow will experience an upward trend in the future, accompanied by the more extreme impacts of ENSO and the IOD.

Assessing the impacts of climate change on streamflow in the upper Omo Gibe basin of Southwest Ethiopia using MIKE NAM

ABSTRACT Climate change affecting the rainfall-runoff processes in the upper Omo Gibe river basin was articulated using bias-corrected ensemble simulations of the CORDEX-Africa under RCP4.5 and RCP8.5 climatic scenarios. CMhyd was used to downscale the ensembles statistically followed by bias-adjustment using distribution mapping. MIKE NAM model was used (1980-2005) to project streamflow for three time periods; the near future (2023-2048), the middle future (2049-2074), and the far future (2075-2100). The average temperature of the basin will rise by 1.59°C and 2.56°C, respectively, under RCP4.5 and RCP8.5, respectively, while, the precipitation for wet and dry seasons decreases by 7.97% and 23.67%, respectively. MIKE NAM has demonstrated a strong correlation between simulated and observed runoff with coefficients of determination (R2) and NSE of more than 0.75. It has been predicted that the mean dry season, wet season, and annual streamflow will decline by 15-27%, 4-13%, and 8-24%, respectively. Intricate study of climate change followed by judicious and timely precautionary measures if not taken today, will decrease in streamflow and put negative consequences on long-term irrigation and hydropower development in the river catchment of upper Omo Gibe basin.