Runoff Variability Research Articles

Long-Term Impacts of Runoff and Coastal Reclamation on Tidal Bore Variations in the Qiantang River Estuary, China

Tidal bore dynamics in estuarine environments are influenced by both natural hydrological changes and human activities, such as coastal reclamation. This study focuses on the Qiantang River estuary, assessing the impacts of runoff variations and reclamation on tidal bores over the past five decades. By employing statistical and time-frequency methods, including the Mann–Kendall test, ordered clustering, and wavelet analysis, the relationships between tidal bore height, river discharge, and reclamation activities are examined. The results indicate that increased freshwater discharge reduces bore intensity over short timescales of 0.3 to 1.2 years, while decreased runoff amplifies it. Over longer periods of 4.1 to 8.3 years, a positive correlation emerges, with changes in runoff preceding variations in tidal bore height. Coastal reclamation, particularly the narrowing of channels, has significantly reduced the bore height at Yanguan, especially in the years following the 2000s. Additionally, the long-term interactions of other factors influencing tidal bores are explored. These findings reveal a delayed estuarine response to human modifications, highlighting the necessity of long-term monitoring and adaptive management strategies to mitigate these impacts. The study provides valuable insights into the complex interplay of natural and human factors, offering guidance for future estuarine management and conservation efforts.

Runoff variation alters estuarine sediment microbiome and nitrogen removal processes by affecting salinity

Runoff variations shape the dynamics of the estuarine environmental factors, profoundly influencing the nitrogen cycle in estuarine sediments. However, our understanding of how these changes regulate microbially-mediated nitrogen removal processes remains limited. In this study, the impacts of changes in environmental factors caused by normal and low runoffs on denitrification and anammox in sediments of the Liao River Estuary in China, were investigated, using continuous-flow experiments combined with 15N tracing techniques and molecular methods. Results indicated that denitrification was the main nitrogen removal process in estuarine sediments under both runoff conditions. Elevated salinity under low runoff condition increased the abundance of nitrifying bacteria (Nitrospina, Nitrosomonas and Nitrosomonadaceae), thereby promoting the coupled nitrification-denitrification nitrogen removal process. Furthermore, seawater intrusion under low runoff contributed to dilute nitrite concentrations, resulting in decreased denitrification rates in sediments. Overall, this study highlighted the impacts of runoff variations on biological nitrogen removal process through affecting environmental factors, gene abundance and microbial community in the estuary.

Projected evolution of the Qiyi Glacier in the Qilian Mountains using the PyGEM with the calibration of glaciological mass balance

Owing to glacial retreat and associated future runoff variations, major concerns have been raised over the sustainability of water resources in the Qilian Mountains. Based on the Python Glacier Evolution Model, we present projections of the Qiyi glacier for shared socioeconomic pathways (SSPs) calibrated with the glaciological mass balance. The results indicate the air temperature as the dominant factor in the continuous mass loss of the Qiyi Glacier in the future. Glacier area and volume are projected to decline to 0.16 ± 0.11 km2 (6.4% ± 4.4%, relative to 2015) and 0.0023 ± 0.0006 km³ (2.1% ± 1.5%, relative to 2015), respectively, by 2100, for SSP1-2.6. For SSP5-8.5, the glacier will disappear by 2088. The mass loss of the Qiyi Glacier will accelerate before 2050 for all SSPs but will decelerate after 2050 for SSP1-2.6 and SSP2-4.5. The peak water of glacier runoff will occur between 2034 and 2045, with the duration of high water from 7 to 18 years. Thereafter, the runoff will rapidly decline till 2070–2080 and remain low afterward. Compared with the existing projections, the present projections indicate that the Qiyi Glacier will experience more drastic shrinkage and ice loss in the coming decades. Finally, the glacier runoff is expected to reach its peak water earlier with a shorter duration of high water.

Landscape metrics as predictors of water-related ecosystem services: Insights from hydrological modeling and data-based approaches applied on the Arno River Basin, Italy

The study addresses the challenge of integrating complex landscape-hydrological interactions into predictive models for improved water resource management. The aim is to investigate the effectiveness of landscape metrics—quantitative indices measuring landscape composition and configuration—as predictors of WES in the Arno River Basin, Italy. Utilizing two hydrological models alongside a random forest algorithm, we assessed spatial and temporal variations in water yield, runoff, and groundwater recharge. The findings indicate that landscape metrics derived from high-resolution land use data significantly impact WES outcomes. Specifically, the models demonstrated average landscape metric importances of 16.8 % for spatial and 17.8 % for temporal predictions concerning runoff. For water yield, these averages were 32.9 % spatially and 43.5 % temporally, while groundwater modeling showed importances of 14.09 % spatially and 33.8 % temporally. Key landscape metrics identified include the core area index for broad-leaved forests and the perimeter-to-area ratio for non-irrigated agricultural areas as critical spatial and temporal predictors of water yield and groundwater recharge. Thresholds were observed, indicating landscape configurations that minimize hydrological variability. For instance, runoff variation is minimal when the landscape exhibits high forest fragmentation (over 1000 coniferous patches), low aggregation (aggregation index <75), and reduced connectivity (cohesion index under 80). Similarly, groundwater variation is minimized with decreased boundary length of vegetation patches (perimeter-to-area ratio <0.8), agricultural lands (perimeter-to-area ratio under 1), and the presence of low core agricultural areas (core area index above 8). The identified thresholds could inform land-use policies, such as targeted afforestation or crop diversification strategies, to optimize WES provision.

Fund allocation modeling of compensation subjects for various protection levels of the ecological flow in rivers under runoff variations

Ecological compensation for protecting of river ecological flow (e-flow) is crucial to maintaining the health of river ecosystems; however, determining the fund sharing for ecological compensation can be challenging. To fill this scientific gap, we herein developed a specific framework to determine the fund-sharing of ecological compensation subjects. Such a framework mainly consists of three parts:1) Identifying the subjects who benefit from the consumption and eco-products provided by e-flow protection, and determining the sharing coefficient of the compensation subjects based on the ratio of their economic benefit to the total economic benefit; 2) Evaluating the ecological compensation resulting from the e-flow protection with the help of the production function method; 3) Combining the ecological compensation and compensation sharing coefficient to determine the fund sharing of compensation subjects. We have successfully applied this approach to the Baoji Section of the Weihe River and the Baojixia Yuanshang Irrigation District (BYID). The obtained results revealed that the compensation subjects were Baoji and Xianyang City, and their corresponding fund-sharing coefficients in 2010 in order were 0.71 and 0.29. It was predicted that ecological compensation for e-flow protection would be 209 million yuan in 2010 year, and the corresponding values of capital sharing are 148 million and 61 million yuan. Over the last 23 years (in the time interval of 2000–2022), the share of compensation funds has gradually decreased, indicating an increasing trend with the improvement of the security level. Join us in our mission to protect river ecosystems and maintain a healthy balance by using this approach for ecological compensation.

Uncovering the impact of climate and vegetation changes on runoff in karstic regions of southwest China

The vegetation-runoff relationship remains unclear in karstic regions. The karst landform in southwest China is a focal area where significant changes in vegetation have occurred in the past few decades, which may substantially impact water resources. To date, the effects of these changes on runoff remain uncertain. This study employed statistical analysis, numerical simulation, and scenario analysis to investigate the temporal and spatial patterns of runoff, climate, and vegetation in 20 typical catchments. The study also evaluated the response of runoff to vegetation and climate changes and the underlying factors. The findings revealed precipitation changes dominated changes in runoff in these catchments (mean contribution of 53.03%), whereas the contributions of vegetation and potential evapotranspiration changes were 23.16% and 23.82%, respectively. The study also revealed that the impacts of vegetation changes on runoff were significantly dependent on vegetation and climate factors (R2 = 0.60, P < 0.01). Furthermore, under the same climate change conditions, a higher distribution of natural vegetation (such as forest) in the catchment resulted in a larger decreasing trend in runoff. The results provide guidelines for the prediction of runoff variation in southwest China, and benefits to decision-making on ecological restoration and water resources development.

Ecological flow research in response to hydrological variation: A case study of the Jinsha River Basin, China

Climate change and human activities have altered the natural state of rivers to a certain extent, leading to runoff variation and impacting the stability of riverine ecosystems. The ecological flow has emerged to balance the water relationship between humanity and riverine ecosystems and to safeguard the health and biodiversity of rivers. Presently, the scientific quantification of riverine ecological flow has become a focal point in water resource research. Addressing the quantification of ecological flow under hydrological variation conditions, the cumulative deviation method (CDM) and Pettitt methods were firstly employed to detect breakpoints in the runoff sequences. Then, the natural monthly runoff post-variation was restored using the Soil and Water Assessment Tool (SWAT) model, i.e., natural runoff restoration, and three testing methods were employed to determine the optimal hydrological distribution functions for natural monthly runoff. Subsequently, an improved frequency calculation method was used to calculate the ecological flow. The Jinsha River Basin was selected as the study area, and four crucial sections in the mainstream of the Jinsha River were studied, including Zhimenda (ZMD), Shigu (SG), Xiaodeshi (XDS), and Pingshan (PS). The results indicated: (1) the runoff sequences (1960–2017) at the four crucial sections exhibit different breakpoint times, with breakpoint years being 2004, 1986, 2005, and 1996, respectively; (2) the SWAT model, in simulating runoff at the four crucial sections, exhibited NSE values all exceeding 0.85, and r values all surpassing 0.9, demonstrating its effective ability to restore natural runoff in the Jinsha River basin; (3) the optimal hydrological distribution functions for natural monthly runoff at the four sections varied, and most natural monthly runoff conforms to the Generalized Extreme Value (GEV) distribution; (4) the average annual ecological flows for the ZMD, SG, XDS, and PS sections were 296 m3/s, 992 m3/s, 1238 m3/s, and 2755 m3/s, and the ecological flows derived using the improved frequency calculation method under the optimal hydrological distribution functions were more rational. This study can provide a scientific basis for the optimal allocation of water resources and the protection of riverine ecosystems in the Jinsha River basin.

Quantifying the Influence of Climatic and Anthropogenic Factors on Multi-Scalar Streamflow Variation of Jialing River, China

Clarifying the impact of driving forces on multi-temporal-scale (annual, quarterly and monthly) runoff changes is of great significance for watershed water resource planning. Based on monthly runoff data and meteorological data of the Jialing River (JLR) during 1982–2020, the Mann–Kendall tendency testing approach was first applied to analyze variation tendencies of multi-timescale runoff. Then, abrupt variation years of runoff were determined using Pettitt and cumulative anomaly mutation testing approaches. The ABCD model was employed for simulating hydrological change processes in the base period and variation period. Finally, influences of climatic and anthropic factors on multi-scalar runoff were computed using the multi-scalar Budyko formula. The following conclusions were drawn in this study: (1) The mutation year of discharge was 1993; (2) the monthly runoff in the JLR presented a “single peak” distribution, and the concentration degree and concentration period in the JLR both showed an insignificant reduction trend; (3) anthropic factors were the dominant factor for spring runoff variations; climatic factors were the dominant factor on annual, summer, fall and winter runoff variations; (4) except for November, climatic factors were the dominant factor causing runoff changes in the other 11 months. This study has important reference value for water resource allocation and flood control decisions in the JLR.

An Attribution Analysis of Runoff Alterations in the Danjiang River Watershed for Sustainable Water Resource Management by Different Methods

Determining the relative roles of climatic versus anthropogenic factors in runoff alterations is important for sustainable water resource utilization and basin management. The Danjiang River watershed is a crucial water resource area of the middle route of the South-to-North Water Transfer Project. In this study, four widely used quantitative methods, including the simple linear regression, the double mass curve, the paired year with similar climate conditions, and an elasticity method based on the Budyko framework were applied to detect the relative contribution of climatic and anthropogenic factors to runoff variation in the Danjiang River watershed. The calculation processes of each method were systematically explained, and their characteristics and applications were summarized. The results showed that runoff decreased significantly (p &lt; 0.05) with an average change rate of −3.88 mm year−1 during the period of 1960–2017, and a significant change year was detected in 1989 (p &lt; 0.05). Generally, consistent estimates could be derived from different methods that human activity was the dominant driving force of significant runoff reduction. Although the impacts of human activity estimated by the paired year with similar climate conditions method varied among paired years, the other three methods demonstrated that human activity accounted for 80.22–92.88% (mean 86.33%) of the total reduction in the annual runoff, whereas climate change only contributed 7.12–19.78% (mean 13.67%). The results of this study provide a good reference for estimating the effects of climate change and human activities on runoff variation via different methods.

Evolution characteristics and attribution analysis of runoff in the coal mining area in northwest China: A case study of the Kuye River Basin

ABSTRACT The Kuye River Basin is the main coal-producing area in northwest China, and it is also a typical arid and semi-arid area. Under the combined influence of climate change and human activities, the runoff of the basin decreases noticeably. The Mann–Kendall trend test, the Hurst index, cumulative anomaly, and wavelet analysis were used to analyze the runoff evolution characteristics of the Kuye River, and the contributions of climate change and human activities to the runoff reduction were quantitatively separated by the slope-changing ratio of the cumulative quantity. The results showed that the runoff decreased significantly from 1970 to 2020, and there was an obvious abrupt change in 1996, while the change trends in precipitation and evaporation were not significant. The contributions of climate change and human activities to runoff reduction were 22.71 and 77.29%, respectively, and human activities have become the dominant factor in runoff variations. Coal mining and the implementation of soil and water conservation measures are considered to be the main human activities contributing to the reduction in runoff. In particular, mining activities reduce groundwater recharge to rivers, which provides a profound understanding of the effect of human activities in mining areas on runoff variation.

Saltwater intrusion of the Nandu River under the changing environment in China

Saltwater problems in the Nandu River have gradually intensified in recent years. The effect of runoff variability (RV) on saltwater intrusion has not yet been fully revealed. Long-term trends in runoff and sea level (SL) were analyzed using the Mann-Kendall test and Theil-Sen estimation, and salinity exceedance rates (Ps) were calculated based on MIKE 11 and daily runoff distributions. As RV increased, Ps decreased the most at 16.0 km (6.7 %) and increased the most at 23.2 km (5.3 %). SL increased by 0.4 m and Ps increased the most at 20.5 km (11.7 %). Constant Ps is projected to move downstream by the 2060s and 210 s, with maximum increases in Ps of 6.2 % and 10.1 %, respectively. The ratio of changes in Ps due to changes in RV and SL is about 0.85. Constant Ps sections can be used to assess the risk of saline intrusion in some of the world's estuaries.

Response to hydrometeorological changes and evaluation of habitat quality in the Dongting Lake basin, China

ABSTRACT With the advancement of hydraulic engineering processes, surface water resources are encountering unprecedented crises that threaten social and ecological sustainability. This study analyzed the response changes and potential correlations between river conditions and climate change in the Dongting Lake (DTL) basin using gray correlation analysis and the LSTM model. Additionally, the InVEST model was employed to further assess the distribution of habitat quality within the basin. The results of the study showed that (1) the range of variation of environmental flows in each tributary became significantly narrower and the frequency of extreme hydrological conditions was reduced in the period after the abrupt hydrological change. (2) The hydrological status had a higher degree of correlation with the rainfall index, and the performance is more prominent on the Xiang River, and the influence of temperature is less. (3) Except in the Xiang River Basin, human activities are the dominant factor of runoff variation, and the annual contribution is generally higher than 50%. (4) Habitat quality in the ‘high’ distribution was the most guarded and always accounted for more than 60% of the basin, while habitat quality in the east-central part of the DTL basin and around the DTL was generally low.

Stronger influences of grassland growth than grassland area on hydrological processes in the source region of the Yellow River

Concerns about regional hydrological responses to land use cover changes have arisen worldwide. However, the separation and quantification of the effects of changes in vegetation area and growth status on hydrological processes remains unclear. Here, we applied a distributed hydrology soil vegetation model (DHSVM) to analyze how the grassland growth state and surface area influence hydrological processes in the source region of the Yellow River (SRYR). The results showed that although the grassland surface area decreased slightly from 1981 to 2020, grassland growth (represented by the leaf area index) tended to increase from 2000. Grassland changes (including area and growth status) increased soil moisture storage and evapotranspiration to an overall extent of 2.03 % and 5.66 %, respectively; and most of the increase occurred after 2000 by 2.90 % and 9.40 %, respectively. These processes under grassland change led to an overall decrease in runoff of 2.41 %, with a much stronger decrease after 2000 of 4.3 %. Changes in grassland growth accounted for ∼95 % of the runoff variations caused by grassland changes in the SRYR during the 40-year study period, compared to changes in grassland surface area. Simulations assuming different extents of grassland degradation suggest that such degradation can reduce evapotranspiration and soil moisture storage, thereby increasing runoff, whereas grassland restoration has the opposite effect. Our results highlighted the sensitivity of hydrological processes in the SRYR to grassland growth and the need for appropriate interventions to maintain and restore grasslands.

Hydrological simulation and evaluation of drought conditions in the ungauged watershed Parishan lake Iran, using the SWAT model

ABSTRACT ke Parishan has experienced significant water scarcity, leading to its complete disappearance. This study utilized the SWAT model to assess the impact of changes in vegetation, precipitation, temperature, and evaporation on runoff and the lake's surface. Two strategies were employed: analyzing runoff variations based on land use and land cover (LULC) changes and evaluating the effects of precipitation, temperature, and humidity on runoff during the simulation period. A key challenge was the lack of runoff statistics, which was addressed by using data from donor watershed stations and Copernicus satellite information to improving simulation processes and calibration. The findings reveal that environmental changes, particularly land use, have increased evaporation and temperature fluctuations which results in reducing runoff. While Copernicus satellite data proved useful, runoff statistics from the neighboring Chamchit station provided more accurate simulations. The study finding suggests that the LULC strategy is an effective management approach, as in this case Parishan Lake's historical conditions with less urbanization and agriculture correlated with higher runoff and lake levels. Finally, meteorological and hydrometric drought and its impact on lake area changes were measured to reach a more comprehensive conclusion.

Driving factors and trend prediction for annual runoff in the upper and middle reaches of the yellow river from 1990 to 2020

The Yellow River Basin (YRB) plays a pivotal role in the water resources management of its region, significantly influenced by the interplay between climate change and human activities, particularly in its upper and middle reaches (UMRYR). This study aims to elucidate the evolving patterns and determinants of runoff within the UMRYR, a matter of considerable importance for the basin’s water resource management, strategy, and distribution. Utilizing the Google Earth Engine (GEE) platform, this research accessed comprehensive datasets including precipitation, drought index, and terrace area, among others, to examine their effects on runoff variations at five gauge stations across the YRB. Terrace data was extracted from Landsat imagery via the Random Forest Model, while annual runoff figures from 1990 to 2020 were sourced from the Sediment Bulletin of China River. Employing the Mann-Kendall test, we assessed the temporal changes in runoff over three decades. In addition, runoff drivers were analyzed by stepwise regression and redundancy analysis, leading to the construction of a multiple linear regression model. The accuracy of predicting annual runoff using the multiple linear model was verified through cross-validation and comparison with the ARIMA time series model. Our findings reveal the efficacy of the random forest algorithm in classifying terraces, achieving an accuracy rate exceeding 0.8. The period from 1990 to 2020 saw a general increase in annual runoff across the five gauging stations in the UMRYR, albeit with variations in the pattern, particularly at the Tangnaihai gauge station which presented the most complex changes. Crucially, three main drivers—summer precipitation (SP), terrace area (TR), and drought index (DI)—were identified as significant predictors in the regression models. The multiple linear regression model outperformed the ARIMA model in forecasting accuracy, underlining the significance of integrating these drivers into runoff prediction models for the UMRYR.

A diagnostic approach to modeling watersheds with human interference

Most watersheds have human impacts that modify hydrological responses differently over a range of timescales. However, these impacts are not accounted for in most hydrological models. Human impacts in watersheds are diverse and case specific, unlike natural hydrologic processes. Incorporating all plausible human impacts comes at a high data acquisition and modeling cost. This raises the question, which human impacts do we need to incorporate to represent observed streamflow patterns at different timescales? To answer this question, we develop a diagnostic approach to modeling watersheds with human interference. This mixed methods approach is informed by the case history and builds on the top-down hydrological modeling approach where process complexity is incrementally added with changing timescales to identify and respond to changing dominant hydrological processes in a given watershed. Here we implement this modeling approach in the East Fork watershed in California, USA for which data on changes in water imports, withdrawals, irrigation and agriculture land cover is available from the early 1940′s, making it an ideal demonstration case. In the East Fork watershed, we find that incorporation of water imports and rights are sufficient to replicate annual patterns of runoff variability, and that adding crop water demand and irrigation enables replication of monthly and daily patterns, while incorporation of groundwater pumping results in negligible improvements. To demonstrate the capabilities of the diagnostic approach in and beyond this case we conducted two computational experiments: checking for needed model structural change and exploring a counterfactual scenario of intensified agriculture.

Spatiotemporal geographically weighted regression analysis for runoff variations in the Weihe River Basin

In order to investigate the effects of vegetation changes on runoff and to obtain recommendations for improving runoff in the Weihe River Basin (. In this study, a spatiotemporal geographic autocorrelation weighted regression analysis (SGAWRA) approach was newly developed based on previous studies. This approach investigates spatial non-stationarity of the dynamic response from vegetation variations to climatic change and human activity. Implications of spatial non-stationarity related to runoff variability were also discussed, which in turn yield the effect that vegetation changes have on runoff. The method systematically analysed the spatial non-stationarity of vegetation variations and its associated effects on runoff. Therefore, more closely related results with less error were produced at each step, and results with more accuracy were obtained. These results indicated that the average trend rates of NDVI in the annual average, each season, and the growing season (Growing season refers to April to September) exceeded 0. Areas where NDVI show a growing trend cover more than 50%, which is greater than the area with a decreasing trend. The GWR regression parameters of precipitation, average temperature, and NDVI are all greater than 0. The GWR regression parameters of human activities and NDVI also have more than 50% of the area greater than 0. Based on the visual analysis of the calculation results, it can be seen that there are obvious spatial trends in the data, and the spatial data are significantly different between different regions. Therefore, WRB can be regarded as spatio-temporally non-stationary. In the WRB, the underlying surface change with vegetation change as the prominent feature is the leading cause (about 60%) of the runoff attenuation. The results showed that WRB has spatial and temporal non-stationarity. The spatial non-stationarity of vegetation has a greater effect on runoff changes. The results of this study support recommendations for improving runoff in the WRB.

Spatiotemporal variations of groundwater and gully impact in two peatland watersheds in the Upper Yellow River, Qinghai‐Tibet Plateau

AbstractThe spatiotemporal variability of groundwater level is an important property of peatland hydrology that directly alternates water storage. Nonetheless, the current understanding of the variations of groundwater level over long periods of time remains limited. In this study, we investigated two peatland watersheds (0.151 km2 for Watershed 1 and 0.844 km2 for Watershed 2) in the Zoige Basin in the upper watershed of the Yellow River to monitor temporal variability of groundwater level using self‐recorded water loggers over 4 years (2017–2021). The main results demonstrate that (1) groundwater level variations were controlled by gully drainage in sites adjacent to the gully but were more affected by rainfall in sites distant from the gully. The groundwater level near the gully downcut was lower than that near the gully without complete downcutting through the pear layer, with a maximum difference of 58.3 cm, indicating the longitudinal effect of groundwater level in the watershed. (2) Because the rainfall had a lag effect on the groundwater level, the length of lag gradually decreased with increased rainfall intensity (i.e., the lag time for sites distant from the gully was about 18 min shorter than that of sites close to the gully in Watershed 1). (3) The peak values of the groundwater level occurred simultaneously with the maximum and minimum rainfall in Watershed 2, and the peak occurrence time was related to the ratio of precipitation to evaporation. In the downstream sites, the groundwater level fluctuated more than the upstream ones in Watershed 2. Moreover, the average groundwater level in the upstream sites was 14.3 cm higher than that of the middle ones, indicating a decreasing trend of water storage along the gully. (4) The differences in groundwater level between wet and dry seasons were clear, but the difference was smaller in the upstream sites due to limited gully incision and higher water storage within the peat layer. Additionally, groundwater level changes were more extreme on rainy days during both the wet and dry seasons, but the different intensities of rainfall resulted in stable groundwater in the dry season and an oscillating groundwater level in the wet season in Watershed 2. This study uncovers the groundwater dynamics in the two peatland watersheds, which is of great significance for understanding runoff variation, ecohydrological processes, and wetland shrinkage.

Elevation-dependent effects of snowfall and snow cover changes on runoff variations at the source regions of the Yellow River basin

ABSTRACT Accurate simulation of the snowmelt runoff process is of great significance in understanding the evolution of water resources in high-altitude cold regions and achieving efficient utilization of water resources. This study focuses on the source regions of the Yellow River basin (SYRB) and aims to improve the snow identification and snowmelt simulation methods in the WEP-L hydrological model. The results show a significant decrease in the snowfall ratio from 2002 to 2018. The fraction of snow cover decreased at lower altitudes but increased at higher altitudes, displaying an exponential relationship with negative accumulated temperature. Snowmelt was found to be negatively correlated with snowfall and snow cover, with a stronger negative correlation at higher altitudes. The decrease in the snowfall ratio intensified with increasing elevation, while snow cover increased with elevation. However, the overall trend of snowmelt runoff was not significant. These findings highlight the dynamic relationship between snowfall, snow cover, and temperature in the SYRB. By incorporating the established response function, the accuracy of snow identification and snowmelt simulation in the WEP-L model has been enhanced. This study contributes to a better understanding of water resource evolution and the efficient utilization of water resources in high-altitude cold regions.

Protozoan communities serve as a strong indicator of water quality in the Nile River

The relationship between the protozoan communities and environmental variables was studied in the Nile River to evaluate their potential as water quality indicators. Protozoans were sampled monthly at six sampling sites in the Nile's Damietta Branch across a spatial gradient of environmental conditions during a 1-year cycle (February 2016–January 2017). The Protozoa community was comprised of 54 species belonging to six main heterotrophic Protozoa phyla. The abundance (average, 1089 ± 576.18 individuals L−1) and biomass (average, 86.60 ± 106.13 μg L−1) were comparable between sites. Ciliates comprised the majority of protozoan species richness (30 species), abundance (79.72%), and biomass (82.90%). Cluster analysis resulted in the distribution of protozoan species into three groups, with the most dominant species being the omnivorous ciliate Paradileptus elephantinus. Aluminium, fluoride, and turbidity negatively affected abundance and biomass, while dissolved oxygen and potassium positively impacted biomass. Of the dominant species recorded over the study area, the amoebozoa Centropyxis aculeata was associated with runoff variables, while the bacterivorous ciliates Colpidium colpoda, Glaucoma scintillans, and Vorticella convallaria were related to the abundance of heterotrophic bacteria, phytoplankton biomass, and total organic carbon. Total dissolved salts, PO4, NH3, NO2, dissolved oxygen, and total organic carbon were the strongest causative factors for protozoa distribution. The α-Mesosaprobic environment at site VI confirmed a high load of agricultural runoffs compared to other sites. This study demonstrates that protozoans can be a potential bioindicator of water quality status in this subtropical freshwater river system.