Streamflow Trends Research Articles

Assessment of catchment water resources allocation under climate change in Luwombwa sub-catchment, Zambia

The uncertainty in climate change and high water demand pose pressure on the natural water resources supply. Not only does this require better understanding but also a call for immediate interventions, mitigation and adaptive measures. This study evaluates catchment water resources in the Luwombwa sub-catchment in Zambia through statistical analysis in the downscaling of past, present and future climatic variables from the CMIP6 climatic model. These variables are then integrated into WEAP - a semi-distributed hydrological and water evaluation model - to perform water demand and allocation scenario modelling. Mult-site calibration and validation were conducted on five selected micro-catchments within Luwombwa sub-catchment. The model performance was assessed usng the R2, NSE and PBIAS as the objective functions. Satisfactory values of 92 % for R2, 82 % for NSE and 6.9 % for PBIAS were achieved. This allowed for scenario modelling on water demand and allocation among competing users. Three future scenarios (2022–2050) were developed from the historical to baseline (1988–2022) and included state of water resources availability under climate change, expansion of irrigation area and impact of dam construction in the sub-catchment. The study reveals a decrease of 20 % in sub-catchment's water availability resulting from 9.3 % (equivalent to 4oC) rise in maximum temperature and 4.5 % reduction in rainfall within the entire sub-catchment. This is especially under the persistence of SSP370 climate variability scenario projections downscaled from four GCM models by the year 2050. The study further revealed that the change point for anticipated future climate extremes is likely to occur between 2027 and 2030. The results are indicative of downward trends in streamflow under climate change and socioeconomic development leading to increase in water value and water scarcity. The insights from the study are critical to inform formulation of effective catchment water resources management strategies such as the development of management plans and adapation measures in the face of climate change and the needs for different stakeholders involvement.

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.

Hydrologic Responses to Climate Change and Implications for Reservoirs in the Source Region of the Yangtze River

ABSTRACTUnderstanding the hydrological impacts of climate change is essential for robust and sustainable water management. This study assessed the hydrologic conditions under changing climate in the Jinshajiang River basin, the source region of the Yangtze River, using the hydrological model SWAT with the historical observations and the future climate simulations under two Shared Socioeconomic Pathways (SSP2‐4.5 and SSP5‐8.5). For the historical period, with an increasing trend of precipitation, evapotranspiration, and snowmelt, streamflow increases in upstream region but keeps decreasing in the downstream catchment. For future scenarios, a warmer and wetter climate is projected for the basin throughout the 21st century, leading to an overall increase in mean and extreme streamflow. The streamflow magnitude increases more significantly in the far future than in the near future, and more significant under SSP5‐8.5 than SSP2‐4.5. The projected remarkable increase in precipitation causes the transition in changing trend of streamflow compared with the historical period. The projected warming leads to a continuing decline in snowfall and snow water equivalent, followed by an earlier snowmelt and higher peak streamflow, especially at the upstream catchment. Ultimately, reservoirs in the basin are expected to gain more inflows, however, with greater variability including higher likelihoods of flood and drought events, which impose potential challenges on reservoir operations. These outcomes indicate the importance of adaptive water resources management in the melting water contributed basin to sustain and enhance its services under global warming.

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.

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.

Region-scale decline in streamflow across New South Wales catchments

ABSTRACT Changing climate and its interactions with catchments may result in changes to water resources. This study examines the temporal trends in streamflow across New South Wales, Australia. Across 163 catchments with over 35 years of records up to September 2020, we used Mann-Kendall and Sen’s Slope methods to estimate trends in different flow indicators, including the annual, low and high flows, cease to flow, and the rainfall-–runoff relationship. Nearly all (160) catchments have decreasing trends in annual flow, with 62 of these being statistically significant, indicating an overall drying pattern. Most declines are 10–20% per decade relative to the mean annual flows of individual catchments. Trends in rainfall-–runoff relationship suggest that the flow declines are generally greater than expected with given rainfall, and likely due to region-scale processes such as groundwater and vegetation dynamics. Our finding has important implications for future water security for New South Wales and similar environments, such as planning for future reduction in water resources availability with likely increasing demands.

An Interdisciplinary Approach to Understand the Resilience of Agrosystems in the Sahel and West Africa

Sub-Saharan African farmers have long been portrayed with very negative representations, at least since the beginning of coordinated European colonialism in the late 19th century. In the Sahel-Sudan area, agrosystems have been described as overgrazed, forests as endangered, and soils as overexploited, with local and traditional “archaic” practices. Against this background, the objective of this article is to focus on these agrosystems’ resilience, for which several criteria have been monitored. The approach used in this research was to synthesize observations from a large amount of material gathered over multiple years by the authors, drawing on our long-term commitment to, and inter-disciplinary study of, the evolution of surface hydrology, ecosystems, and agrosystems of West Africa. The positive trends in rainfall and streamflows, reinforced by farmer’s practices, confirm the overall regreening and reforestation of the Sahel-Sudan strip, especially in areas with high population densities, including the mangrove areas. The intensification of agricultural systems and the recovery of the water-holding capacity of soils and catchments explain the recorded general increase in terms of food self-sufficiency in the Sahel, as well as in crops yields and food production. Finally, we compare the neo-Malthusian discourse to the actual resilience of these agrosystems. The article concludes with a recommendation calling for the empowerment of smallholder farmers to take greater advantage of the current wet period. Overall, the speed of change in knowledge and know-how transfer and implementation, and the farmers’ ability to adapt to ecological and economic crises, must be highlighted. Far from being resistant to change, West African agriculturalists innovate, experiment, borrow, transform, and choose according to their situation, projects, and social issues.

Climate Driven Trends in Historical Extreme Low Streamflows on Four Continents

AbstractUnderstanding temporal trends in low streamflows is important for water management and ecosystems. This work focuses on trends in the occurrence rate of extreme low‐flow events (5‐ to 100‐year return periods) for pooled groups of stations. We use data from 1,184 minimally altered catchments in Europe, North and South America, and Australia to discern historical climate‐driven trends in extreme low flows (1976–2015 and 1946–2015). The understanding of low streamflows is complicated by different hydrological regimes in cold, transitional, and warm regions. We use a novel classification to define low‐flow regimes using air temperature and monthly low‐flow frequency. Trends in the annual occurrence rate of extreme low‐flow events (proportion of pooled stations each year) were assessed for each regime. Most regimes on multiple continents did not have significant (p &lt; 0.05) trends in the occurrence rate of extreme low streamflows from 1976 to 2015; however, occurrence rates for the cold‐season low‐flow regime in North America were found to be significantly decreasing for low return‐period events. In contrast, there were statistically significant increases for this period in warm regions of NA which were associated with the variation in the Pacific Decadal Oscillation. Significant decreases in extreme low‐flow occurrence rates were dominant from 1946 to 2015 in Europe and NA for both cold‐ and warm‐season low‐flow regimes; there were also some non‐significant trends. The difference in the results between the shorter (40‐year) and longer (70‐year) records and between low‐flow regimes highlights the complexities of low‐flow response to changing climatic conditions.

Connecting past, present, and future trends of hydraulic and phosphorus loading in the Bay of Quinte tributaries, Ontario, Canada

Study regionThe Bay of Quinte watershed, located on the northeastern shore of Lake Ontario, Canada. Special focus is placed on the Napanee River and Wilton Creek catchments, where the presence of a subterranean network of conduits that facilitate groundwater-surface water interactions is conducive to an increase in the delivery of nutrients during storm events and can exacerbate the risk of eutrophication. Study focusDevelopment of a rigorous modelling framework that can advance our understanding of past and present trends of streamflow and tributary phosphorus (P) concentration and loads. We also analyze future streamflow rates and P export trends in order to guide the long-term watershed management in the area. Our analysis is carried out through a comprehensive combination of data-driven and process-based models. Novel hydrological insights for the regionRetrospective analysis provides evidence of a recent increase in the impact of nonpoint-source P pollution. General Circulation Models suggest a future increase in both temperature minima and maxima relative to present conditions (2002–2018). Precipitation projections are indicative of increased frequency of occurrence of high extreme precipitation events during the summer and mid-fall, when the Bay of Quinte is more susceptible to undesirable ecological shifts. Our study predicts a seasonality shift in the streamflow, with the spring freshet occurring earlier in the year accompanied by higher flow rates in the local creeks for the winter and early spring. We also examined the relationship between precipitation and streamflow across varying levels of flow regulation. Our analysis indicates that our predictive capacity declines with increased flow regulation as well as when streamflow rates are predicted by contemporaneous precipitation values.

Impacts of Rainfall Variability on Streamflow in the Drylands of Northern Kenya: Assessing Water Availability under a Changing Climate

Water availability is a function of climatic and land surface conditions, which determine the amount and distribution of atmospheric water as it reaches the surface. This largely depends on rainfall, whose variability affects water, food and livelihood security. This paper sought to quantify the effects of rainfall variability on water availability in an effort to support effective water resources management. Coefficient of Variation (CV), Standardized Anomaly Index (SAI) and Mann-Kendall trend test approaches were used to assess variability and trends, while correlation and regression analysis were employed to determine effects of rainfall variability on streamflow. A hydrological model, Soil and Water Assessment Tool (SWAT), was used to simulate streamflow with a view to assessing water availability under two climate change scenarios; Representative Concentration Pathways (RCP) 4.5 and 8.5. Results show that the area experiences moderate to extreme rainfall variability, as indicated by CV and SAI values that ranged from 20 to 99% and -2.5 to +3 respectively, resulting in moderate to extreme floods and droughts that often disrupt livelihoods. Current streamflow simulations (1981 – 2020) indicated increasing trends. Near and far future streamflow volumes will decrease by 15% during the April-May-June season while during October-November-December season they will increase by 13%, compared to the present. Increasing trends of rainfall and streamflow indicate that the area has opportunities for rainwater harvesting while the high variability indicates a need for early warning systems to cushion communities from climatic shocks evidenced by the impacts of climate extremes experienced in the area.

Spatio-temporal deep learning model for accurate streamflow prediction with multi-source data fusion

Accurately predicting streamflow and early flood warning are important but also very challenging, due to the complexity and stochastic nature of the runoff process. By describing the process nature, this study proposes a spatio-temporal deep learning model, which integrates multiple sources of information including Hydrology-related data from the Global Land Data Assimilation System (GLDAS), hydro-meteorological and streamflow data, to better capture the complexity of the hydrological processes. The Maximum Information Coefficient (MIC) is utilized to reduce data dimensionality and assess the relationship between streamflow and other variables. The Completely Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Variational Mode Decomposition (VMD) methods are combined to extract the most significant features in the predictors. The Time Convolutional Network (TCN) and Gated Recurrent Unit (GRU) are also combined for prediction, enhancing the model's robustness and balancing short-term and long-term forecasting effects. The integration of predictive sub-models with Random Forest (RF) improves overall performance. The framework is applied to 11 hydrological stations in the upper, middle, and lower reaches of the Jialing River mainstream basin in China. According to performance measures, our approach outperforms other baseline models. Flood, probabilistic, and lead time predictions of streamflow make the model more widely applicable and robust. In order to increase the interpretability, the SHAP tool is used in this study to analyze the contribution of each selected influencing variable to the long-term trend of streamflow.

A Combined Seasonal Mann–Kendall and Innovative Approach for the Trend Analysis of Streamflow Rate in Two Croatian Rivers

Climate change profoundly impacts hydrological systems, particularly in regions such as Croatia, which is renowned for its diverse geography and climatic variability. This study examined the effect of climate change on streamflow rates in two Croatian rivers: Bednja and Gornja Dobra. Using seasonal Mann–Kendall (MK) tests, overall streamflow trends were evaluated. Additionally, innovative polygon trend analysis (IPTA), innovative visualization for innovative trend analysis (IV-ITA), and Bayesian changepoint detection and time series decomposition (BEAST) algorithms were used to assess the trends’ magnitudes and transitions. The seasonal MK analysis identified significant decreasing trends, primarily during summer. The results of IPTA and IV-ITA revealed consistent decreasing trends throughout most months, with a notable increase in September, especially at high flow values. The rivers’ behavior differed between the first and second halves of the month. BEAST analysis detected abrupt changes, including earlier shifts (1951–1968) in the Bednja and more recent ones (2013–2015) in both the Bednja and, to a lesser extent, the Gornja Dobra rivers. This comprehensive approach enhances our understanding of long-term streamflow trends and short-term fluctuations induced by climate change.

Developing Non-Stationary Frequency Relationships for Greater Pamba River basin, Kerala India incorporating dominant climatic precursors

Abstract. Global climate changes significantly contribute to increased frequency of hydrologic extremes. This significantly underestimates the hydrologic design parameters, bringing of hydro systems to increased failure risk. In order to address this concern, the current practice of development of hydrologic frequency tools need to be updated accounting for non-stationarity. This study first considered a diverse set of statistical tests to examine the trend, change points, non-stationarity and randomness of streamflow, rainfall and temperature time series of scales ranging from daily to annual. The annual maxima time series indicated non stationarity against the stationary behaviour of daily series of hydro-meteorological datasets of the basin. Subsequently, this study developed the Temperature Duration Frequency (TDF), Rainfall Intensity Duration Frequency (IDF) and Flood Frequency (FF) curves of Greater Pamba river basin in Kerala India, the part of which was most severely affected by the near century return period flood event of 2018. The analysis was performed for a multitude of combinations of variations in distribution parameters with time and climatic drivers as physical covariates in the extreme value formulations. The study proposed a novel wavelet coherence (WC) based driver selection of most dominant combination of climatic precursors in developing FF and IDF relations of three locations of Kalloopara, Malakkara and Thumpamon and TDF curve of Kuttanad region in the basin, considering data of 1985–2015 period. The proposed WC framework considers bi-multi-and partial effects of climatic oscillations (COs) like El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO) in identifying potential drivers. The different WC formulations captured in-phase relationships of streamflows and rainfall with COs at intra-annual, annual and inter annual scales up to 4 years. The methods showed that addition of climatic precursors improved the NS estimates of flood and rainfall quantiles by more accurately capturing the magnitudes of extreme streamflows and rainfalls of 2018, 2021 than the time covariate formulations. However, the role of COs on extreme temperature is not found to be influential in developing TDF relationships, which needs further investigation.

Modeling streamflow responses to land use and land cover change using MIKE SHE model in the upper Omo Gibe catchment of Ethiopia

AbstractThe land use and land cover (LULC) changes in the upper Gibe catchment were studied intricately using the MIKE SHE model and analyzed through statistical tests. The Mann–Kendall test was used to identify potential trends, while the Pettit test was used to detect abrupt changes in rainfall, temperature, and streamflow. A set of three maps of LULC change (1990, 2003, and 2018) was developed to observe how they affect the hydrological pattern of the catchment. Statistical analyses were conducted at mean annual time scales to establish relationships among the anomalies. It has been noted that certain temperature gauges showed statistically significant increases in temperature. Change points in the 1980s and 1990s were identified during the study period. The annual streamflow trends displayed an increasing trend that was not that significant. LULC changes contributed to increased surface runoff, attributed to agricultural, settlement, and water body expansion, as well as reductions in bare land, forest, shrubland, and grassland. The MIKE SHE model performed well during both the calibration and validation periods on the monthly time scale. The alterations in LULC had a noticeable impact on stream flows during both wet and dry seasons, resulting in increased mean monthly stream flows during the wet season and decreased flows during the dry season. The MIKE SHE study and related statistical analysis is quite a different method to perceive the results.

Evaluating the impact of climatic changes on streamflow in headwater mountain catchments with varying human pressure. An example from the Tatra Mountains (Western Carpathians)

Study regionTatra Mountains, Western Carpathians Study focusOur study aims to assess the impact of climatic changes on streamflow in headwater mountain catchments with varying human pressure. The research bases on hydrological and climatological data from a period 1971–2020 and includes trend analysis, wavelet analysis and paired catchment observations, comparing semi-natural and human-altered catchments. New hydrological insights for the regionAir temperature has increased (+0.4°C decade−1) in the region. Precipitation totals remained unchanged, however annual snowfall totals decreased (−69 mm decade−1, ∼6.3%) at the expense of rainfalls, especially in winter. Air temperature and precipitation exhibited altitude-dependent changes. Snow depths remained stable; however, snow cover duration has shortened (−2 to −4 days decade−1). The observed climatic changes have led to an increase in annual low flows (+7–11.5% decade−1), as well as winter low, average, and high flows, affecting the timing of snowmelt runoff. Streamflow changes were more pronounced in semi-natural catchments. Climatic-driven trends in streamflow were more evident in winter, whereas trends associated with human activities and land use were detected throughout the year. Discharge was more coherent with precipitation in human-altered catchments, and weaker in semi-natural catchments. The intensification of annual cycle in precipitation and semiannual cycle in snow cover at high altitudes, along with the intensification of semiannual cycle in streamflow, provide evidence of ongoing climatic changes.

Hydroclimatic Trends and Streamflow Response to Recent Climate Change: An Application of Discrete Wavelet Transform and Hydrological Modeling in the Passaic River Basin, New Jersey, USA

The exigency of the current climate crisis demands a more comprehensive approach to addressing location-specific climate impacts. In the Passaic River Basin (PRB), two bodies of research—hydroclimatic trend detection and hydrological modeling—have been conducted with the aim of revealing the basin’s hydroclimate patterns as well as the hydrologic response to recent climate change. In a rather novel application of the wavelet transform tool, we sidelined the frequently used Mann–Kendal (MK) trend test, to identify the hidden monotonic trends in the inherently noisy hydroclimatic data. By this approach, the use of MK trend test directly on the raw data, whose results are almost always ambiguous and statistically insignificant in respect of precipitation data, for instance, no longer poses a challenge to the reliability of trend results. Our results showed that, whereas trends in temperature and precipitation are increasing in the PRB, streamflow trends are decreasing. Based on results from the hydrological modeling, streamflow is more sensitive to actual evapotranspiration (ET) than it is to precipitation. In periods spanning decades with sufficient water availability, energy governs actual evapotranspiration rates, rendering streamflow more sensitive to increases in precipitation. Conversely, during meteorologically stressed decades, water availability dictates actual evapotranspiration, consequently amplifying streamflow sensitivity to fluctuations in actual evapotranspiration. We found that the choice of baseline condition constitutes an important source of uncertainty in the sensitivities of streamflow to precipitation and evapotranspiration changes and should routinely be considered in any climate impact assessment.

Enhanced Role of Streamflow Processes in the Evolutionary Trends of Dissolved Organic Carbon.

Investigating dissolved organic carbon (DOC) dynamics and drivers in rivers enhances the understanding of carbon-environment linkages and support sustainability. Previous studies did not fully consider the dynamic nature of key drivers that influence the long-term changing trends in DOC concentration over time (the controlling factors and their roles in DOC trend can undergo alterations over time). We analyzed 42 years (1979-2018) of hydrometeorology, sulfate SO4, and DOC data from a 5.42 km2 watershed in central-southern Ontario, Canada. Our findings reveal a significant (p ≤ 0.01) overall increase in DOC concentrations, mainly due to the coevolution of SO4 and streamflow trends, especially the extreme flows. Over the 42-year period, the changing trend of streamflow (especially the extreme high or low flows) have significantly (p < 0.05) intensified their influence on DOC trends, increasing by an average of 30%. Conversely, the impact of SO4 has weakened, experiencing an average decrease of 32.6%. The upward trend in the annual average DOC concentration is attributed to the increasing number of maximum flow days within a year, while the decreasing trend in the number of minimum flow days has a contrasting effect. In other words, changes in maximum and minimum flow days have a counteracting effect on the DOC concentration trends. These results underscore the importance of considering the effects of altered streamflow processes on carbon cycle changes under evolving environmental conditions.

Impact and Trends of Climate Change Analysis of Streamflow at Various Gauging Stations in the Jhelum River, Jammu &amp; Kashmir

Abstract: The planet Earth's water resources are involved in the biggest matter movement in the Earth's system, the hydrological cycle, which is infinitely repeated. Given that water is the fundamental component of the planet's life support system, it is critical to comprehend how current and anticipated climate change is affecting water availability and supplies. Stream flow trend analysis is crucial for flood forecasting and hydrologic drought assessment-related research, in addition to the study of water resource management. This study examined the long-term variations in stream flow at several gauging stations in the Jhelum River of Jammu and Kashmir . The Modified Mann-Kendall Test was used to analyze trends (MMKT). Sen's Slope Estimator (SSE) was employed in order to quantify trend. Trend analysis was performed using long-term time series data of the monthly and annual maximum stream flows at 10 gauging stations. The streamflow annual timeseries was not visible. any discernible upward or downward trends at any gauging point. Nonetheless, it was discovered that every noteworthy trend discovered at several gauging sites over the course of several seasons was declining in character. Throughout July, six gauging sites showed tendencies of declining streamflow. However, in addition to helping with regional hydrologic studies, this kind of river water flow research would also be helpful for studying the occurrence of floods and hydrologic droughts.

Wavelet analysis of rainfall and application of hydrological model in a semi‐arid river basin of Rajasthan, India

AbstractRainfall–runoff modeling requires a selection of a suitable hydrologic model for the determination of an accurate quantity. A better understanding of rainfall–runoff processes is important for stream flow generation within a river basin. This study investigate the long‐term spatial–temporal trend of rainfall and streamflow using the hydrologic engineering center‐hydrologic modeling system (HEC‐HMS) model to understand the rainfall–runoff dynamics in the Banas River basin. Rainfall variability was analyzed for two periods: 1971–1995 and 1996–2020. Continuous wavelet transform was used to analyze the periodicity and the inter‐seasonal relationship in rainfall. HEC‐GeoHMS was used to generate the various inputs for the hydrologic modeling inputs for the HEC‐HMS model. Initial constant loss and ModClark transform method were used to set up the HEC‐HMS model for the study area. Calibration and validation of the model were performed using 3 years of observed data 2010–2012 and 2013–2015, respectively. Statistical model efficiency was checked using the coefficient of determination (R2), Nash–Sutcliffe efficiency, and root mean squared error to evaluate the performance of the HEC‐HMS model. The finding indicated that the R2 values are 0.80 for calibration and 0.82 for validation periods, respectively, which are in good arrangement with the measured values. This study analyzes the relationship between rainfall and runoff, which will aid in proper and efficient water resource management.

Attribution of current trends in streamflow to climate change for 12 Central Asian catchments

This study investigates the attribution of climate change to trends in river discharge during six decades from 1955 until 2014 in 12 selected river catchments across six Central Asian countries located upstream of the main rivers. For this purpose, the semi-distributed eco-hydrological model SWIM (Soil and Water Integrated Model) was firstly calibrated and validated for all study catchments. Attributing climate change to streamflow simulation trends was forced by factual (reanalysis) and counterfactual climate data (assuming the absence of anthropogenic influence) proposed in the framework of the ISIMIP (Inter-Sectoral Impact Model Intercomparison Project) or ESM without anthropogenic forcing that were firstly tested and then compared. The trend analysis was performed for three variables: mean annual discharge and high flow (Q5) and low flow (Q95) indices. The results show that trends in the annual and seasonal discharge could be attributed to climate change for some of the studied catchments. In the three northern catchments (Derkul, Shagan, and Tobol), there are positive trends, and in two catchments (Sarysu and Kafirnigan), there are negative streamflow trends under the factual climate, which could be attributed to climate change. Also, our analysis shows that the average level of discharge in Murghab has increased during the historical study period due to climate change, despite the overall decreasing trend during this period. In addition, the study reveals a clear signal of shifting spring streamflow peaks in all catchments across the study area.