Catchment In China Research Articles

Characterizing spatiotemporal variations of chromophoric dissolved organic matter in headwater catchment of a key drinking water source in China.

Natural surface drinking water sources with the increasing chromophoric dissolved organic matter (CDOM) have profound influences on the aquatic environment and drinking water safety. Here, this study investigated the spatiotemporal variations of CDOM in Fengshuba Reservoir and its catchments in China. Twenty-four surface water samples, 45 water samples (including surface water, middle water, and bottom water), and 15 pore water samples were collected from rivers, reservoir, and sediment of the reservoir, respectively. Then, three fluorescent components, namely two humic-like components (C1 and C2) and a tryptophan-like component (C3), were identified from the excitation-emission matrix coupled with parallel factor analysis (EEM-PARAFAC) for all samples. For spatial distributions, the levels of CDOM and two humic-like components in the reservoir were significantly lower than those in the upstream rivers (p<0.01), indicating that the reservoir may act as a reactor to partly reduce the levels of exogenous input including CDOM and humic-like matters from the surrounding catchment. For temporal variations, the mean levels of CDOM and three fluorescent components did not significantly change in rivers, suggesting that perennial anthropic activity maybe an important factor impacting the concentration and composition of river CDOM but not the precipitation and runoff. However, these mean values of CDOM for the bulk waters of the reservoir changed markedly along with seasonal variations, indicating that the hydrological processes in the reservoir could control the quality and quantity of CDOM. The different correlations between the fluorescent components and primary water parameters in the river, reservoir, and pore water samples further suggest that the reservoir is an important factor regulating the migration and transformation of FDOM along with the variations of different environmental gradients.

The regional variation of denitrification phenotypes under anoxic incubation with soils from eight forested catchments in different climate zones of China

Denitrification characteristics of forest soils from eight headwater catchments in China were investigated in this study, along a climatic gradient from the tropics in the South to the temperate zones. Within each catchment, different landscape positions along hydrological flow paths were also considered, including well-drained soils on hill slopes and poorly drained soils in groundwater discharge zones. The results showed that instantaneous denitrification rates were much greater in soils from the northern sites than those from the southern sites (with the average of 110.0 and 25.4nmolNg−1drysoilh.−1, respectively). Large potentials for nitrous oxide (N2O) loss (evaluated as maximum N2O accumulation before it was reduced to dinitrogen (N2)) were observed in the six tropical and subtropical catchments, particularly in soils with high carbon (C) and nitrogen (N). Meanwhile high N2O/(N2O+N2) stoichiometries were displayed in soils from these southern sites. Within catchments, soils from the groundwater discharge zones showed greater potential denitrification rates but smaller N2O/(N2O+N2) ratios in comparison with those on the hill slopes, implying large N removal potentials of soils from the groundwater discharge zones. Furthermore, our findings suggest soil pH is the key controller for the potential denitrification rates and the N2O/(N2O+N2) stoichiometries. Soil pH, C and N availability affect the potential for N2O loss synergistically. Our findings not only pinpoint the denitrification phenotypes of soils along the climatic gradient, but also confirm the small-scale variations within catchments which reflect the in situ habitat of the denitrifiers. These indicate the importance of discrimination related to different landscape positions when modeling N2O emissions and N removals from regional N loading.

Impacts of 1.5 and 2\xa0\xb0C global warming on water availability and extreme hydrological events in Yiluo and Beijiang River catchments in China

In the discussion of climate impacts, 1.5 and 2 °C have become iconic values. This study examines the impacts of 1.5 and 2 °C global warming on water availability, runoff seasonality, and extreme monthly and daily runoff in two catchments, using the semi-distributed hydrological model Hydrologiska Byråns Vattenbalansavdelning-D, based on a combination of five global climate models (GCMs) and four representative concentration pathways (RCPs). Subsequently, quantitative assessments were made for projection uncertainties from GCMs and RCPs. The two catchments are the Yiluo River catchment (YLC) in northern China and the Beijiang River catchment (BJC) in southern China. The results indicate wetter flood seasons for YLC and warmer mean annual temperatures, drier springs, and more severe floods over long return periods (25 and 50 years) for both catchments. The change magnitude of most indicators is expected to be larger in YLC than in BJC. Mean annual temperatures in both catchments are expected to have smaller changes under the 1.5 °C scenario than under the 2.0 °C scenario. However, the change magnitude of the other hydrological variables is projected to be approximately equivalent for both catchments under both scenarios. Uncertainties of projected impacts from GCMs are generally larger than those from RCP scenarios, for both catchments and warming scenarios, with the exception of mean annual temperature of BJC. These findings indicate that effective measures are required to address increasing annual temperatures, more severe flood events (25- and 50-year return periods), and drier spring seasons in both catchments and wetter flood seasons in YLC.

Efficacy of in situ and meteoric 10Be mixing in fluvial sediment collected from small catchments in China

Using measurements of in situ and meteoric 10Be in fluvial sand to measure erosion rates, quantify soil loss, and trace sediment sources and sinks relies on the assumption that such sediment is well-mixed and representative of the upstream area. We test this assumption at 13 river junctions in three tributary watersheds (200–2500km2) to the Mekong River, Yunnan, China, where human alteration of the landscape is significant and widespread.We find that two of the three watersheds mix well for in situ10Be and none mix well for meteoric 10Be when considering the concentration of 10Be at the outlet compared to the area-weighted mean of headwater samples. We also assessed mixing at 13 river junctions by comparing the erosion rate-weighted isotopic concentration of sediment taken from tributaries upstream of a junction to the concentration in a sample taken downstream of the junction. With this metric, mixing is generally poor for both in situ and meteoric 10Be but is better for in situ10Be than for meteoric 10Be (p<0.05). This is likely because in situ10Be is measured in quartz, which is resilient to physical and chemical breakdown in river systems whereas meteoric 10Be is measured in grain coatings which can abrade and dissolve.Basins eroding faster (>100mm/kyr) tend to mix better than slowly eroding basins. We find no evidence that agricultural land use in sampled basins affects sediment mixing downstream. Mixing improves with increased basin area (particularly >200km2), increased sampling distance downstream from an upstream junction (>500m), and increased difference in size between tributaries (one tributary >3 times larger than the other). The most important factor affecting mixing efficacy for both in situ and meteoric 10Be is the fraction of the basin area contributing to the downstream sample that does not contribute to the upstream samples. Junctions with >2% of the basin area unsampled by upstream samples tend not to mix as well. Our data suggest specific sampling location strategies (such as amalgamation) likely to improve the outcome of fluvial network analysis using cosmogenic nuclides.

Evaluating the impact of climate and underlying surface change on runoff within the Budyko framework: A study across 224 catchments in China

Climate change and underlying surface change are two main factors affecting the hydrological cycle. In respect of climate change, precipitation alters not only in magnitude, but also in intensity, which can be represented by precipitation depth. To further understand the spatial variation of the impact of precipitation, potential evapotranspiration, precipitation depth and the water storage capacity during 1960–2010, 224 catchments located from arid areas to humid areas across China were analyzed in this paper based on the Choudhury-Porporato equation within the Budyko hypothesis. The results show that underlying surface change is the major driving force of runoff change in the Songhua Basin, the Liaohe Basin and the Haihe Basin, while climate change dominates runoff change in other basins. Climate change causes runoff increase in most catchments, except for some catchments in the Yellow River Basin and the Yangtze River Basin. Specifically, changes in precipitation depth induce runoff increase in almost each catchment and show a considerable contribution rate (14.8% on average, larger than 20% in 32% catchments). The contribution of precipitation depth change has little correlation with the aridity index, while positively correlates to the significance of trend in precipitation depth. This study suggests that precipitation depth is an important aspect that should be taken into consideration in attribution of runoff change. The findings in this study provide a sight for future researches in attribution analysis within the Budyko framework.

Characteristics and Bioaccumulation of Progestogens, Androgens, Estrogens, and Phenols in Erhai Lake Catchment, Yunnan, China

Occurrence and behavior of steroid estrogens and phenols in natural waters have been widely reported, but information about progestogens and androgens is rarely published. In this study, occurrence, spatiotemporal distribution, bioaccumulation, and ecotoxicological risk of steroidal and phenolic endocrine disrupting chemicals (EDCs) (progestogens, androgens, estrogens, and phenols) were documented in the catchment of China's Erhai Lake. Phenols were detected in concentration ranging from 47 to 215 ng/L in water and 16 to 76 ng/g in sediment. The pollution of phenols was mainly caused by the emission of agriculture, industry, and daily activities. Natural and synthetic steroids were also found in Erhai Lake catchment with the total concentrations ranging from 19 to 161 ng/L in water and from 2.76 to 29.1 ng/g in sediment. Bisphenol A, estrone, and dihydrotestosterone were the alkyl phenol, estrogen, and androgen found in the highest concentrations. Bioaccumulation of these EDCs in fish tissues was most pronounced in livers, followed by gills and then muscle tissue. Computed risk quotients suggest that the ecotoxicological risk of steroids and phenols in Erhai Lake was lower than that in the rivers feeding the lake. 17α-ethinylestradiol and bisphenol A pose the greatest risk and should be controlled preferentially in this catchment.

Investigation of the complexity of streamflow fluctuations in a large heterogeneous lake catchment in China

The occurrence of flood and drought frequency is highly correlated with the temporal fluctuations of streamflow series; understanding of these fluctuations is essential for the improved modeling and statistical prediction of extreme changes in river basins. In this study, the complexity of daily streamflow fluctuations was investigated by using multifractal detrended fluctuation analysis (MF-DFA) in a large heterogeneous lake basin, the Poyang Lake basin in China, and the potential impacts of human activities were also explored. Major results indicate that the multifractality of streamflow fluctuations shows significant regional characteristics. In the study catchment, all the daily streamflow series present a strong long-range correlation with Hurst exponents bigger than 0.8. The q-order Hurst exponent h(q) of all the hydrostations can be characterized well by only two parameters: a (0.354 ≤ a ≤ 0.384) and b (0.627 ≤ b ≤ 0.677), with no pronounced differences. Singularity spectrum analysis pointed out that small fluctuations play a dominant role in all daily streamflow series. Our research also revealed that both the correlation properties and the broad probability density function (PDF) of hydrological series can be responsible for the multifractality of streamflow series that depends on watershed areas. In addition, we emphasized the relationship between watershed area and the estimated multifractal parameters, such as the Hurst exponent and fitted parameters a and b from the q-order Hurst exponent h(q). However, the relationship between the width of the singularity spectrum (Δα) and watershed area is not clear. Further investigation revealed that increasing forest coverage and reservoir storage can effectively enhance the persistence of daily streamflow, decrease the hydrological complexity of large fluctuations, and increase the small fluctuations.

The Dataset of Groundwater in the Baiyangdian Lake Catchment of China

The Dataset of Groundwater in the Baiyangdian Lake Catchment of China

Investigation of factors affecting intra-annual variability of evapotranspiration and streamflow under different climate conditions

Investigating the factors that affect intra-annual evapotranspiration (ET) and streamflow variability is important to regional hydrological cycles and energy balance research. In this study, ET and streamflow variability (defined as their standard deviations) are attributed to precipitation, potential evapotranspiration (ET0) and total water storage change (TWSC) based on a Budyko-based approach at 282 catchments in China. The results show that the Budyko-based approach satisfactorily simulates the intra-annual ET and streamflow variability (R2 of 0.63–0.84). The dominant contributor to ET variability is ET0 under energy-limited condition (aridity index⩽0.76), whereas the dominant contributor is precipitation under equitant (0.76<aridity index⩽1.35) and water-limited conditions (aridity index⩾1.35). The contribution of ET0 to ET variability decreases with the aridity index, whereas the contribution of precipitation to ET variability increases with the aridity index. However, the dominant contributor to streamflow variability is precipitation under all the three climate conditions, which is unaffected by the aridity index. TWSC enhances ET variability under energy-limited condition and inhibits ET variability under water-limited and equitant conditions. However, TWSC inhibits streamflow variability under all the three climate conditions. In addition, geography and vegetation also influence the contributors to ET and streamflow variability. The effects of geography on the contributors to streamflow variability are larger than that to ET variability. In contrast, the impacts of vegetation on the contributors to ET variability are larger than that to streamflow variability. This study demonstrates that the mechanism of ET variability under different climate conditions is much more complex than that of streamflow variability, suggesting that more attention should be given to ET for water-energy modeling, hydrological predictions and local water management.

Dominant climatic factors driving annual runoff changes at the catchment scale across China

Abstract. With global climate changes intensifying, the hydrological response to climate changes has attracted more attention. It is beneficial not only for hydrology and ecology but also for water resource planning and management to understand the impact of climate change on runoff. In addition, there are large spatial variations in climate type and geographic characteristics across China. To gain a better understanding of the spatial variation of the response of runoff to changes in climatic factors and to detect the dominant climatic factors driving changes in annual runoff, we chose the climate elasticity method proposed by Yang and Yang (2011). It is shown that, in most catchments of China, increasing air temperature and relative humidity have negative impacts on runoff, while declining net radiation and wind speed have positive impacts on runoff, which slow the overall decline in runoff. The dominant climatic factors driving annual runoff are precipitation in most parts of China, net radiation mainly in some catchments of southern China, air temperature and wind speed mainly in some catchments in northern China.

Annual actual evapotranspiration in inland river catchments of China based on the Budyko framework

By investigating long time series of climate and discharge data set were collected from 68 inland river catchments in China, we analyzed the spatial and temporal variations of the annual actual evapotranspiration (AE, mm/year) using the Budyko hypothesis. A simple parameterization estimated parameter $$\bar{w}$$ model (SMR Model, $$\bar{w}$$ parameter for the Fu’s equation, one form of the Budyko hypothesis), was proposed using a dataset of 68 catchment independently and combined based on the landscape characteristics [Relative soil water storage $$\left( {\frac{{S_{max} }}{{\overline{ET}_{0} }}} \right)$$ , catchment areas (A) and average slope (tanβ)], this model explains 58.3 % of observed variance (the optimized $$\bar{w}$$ ) with the root-mean-square error of 0.24. The Budyko hypothesis with estimated parameter $$\bar{w}$$ reproduced observed mean annual AE well for the combined 68 catchments. The estimated mean annual AE for 68 catchments showed remarkable agreement with that derived from the long-term water balance with the determining coefficient of R 2 = 0.918. This implies that Budyko hypothesis can be used for estimating AE accurately in inland river catchments, and it is especially useful for estimates in ungauged catchments.

Quantifying the effect of vegetation change on the regional water balance within the Budyko framework

AbstractThe Budyko framework is widely used to investigate the impacts of climate and landscape changes on regional hydrology, but quantifying the effect of vegetation change is still a challenge due to the lack of an explicit expression of vegetation in Budyko equations. This study establishes a relationship between the change in the landscape parameter in a Budyko equation and vegetation change (represented by fPAR, the fraction of Photosynthetically Active Radiation absorbed by vegetation) for catchments in China, where, due to large‐scale soil and water conservation projects implemented by the Chinese government, vegetation and regional hydrology have changed substantially over the past 30 years. The ratio of landscape parameter change to the change in fPAR has a strong relationship with the aridity index, and thus, vegetation change can be converted into a change in the landscape parameter. Then, the fPAR elasticity of runoff is introduced and formulated under the Budyko framework. It provides a useful tool for the quantitative evaluation of the regional hydrological response to vegetation change, but the proposed relationship still needs to be evaluated in other catchments around the globe where large‐scale afforestation or vegetation recovery has occurred.

Modeling middle and final flush effects of urban runoff pollution in an urbanizing catchment

Summary In current literature, the first flush effect of urban runoff pollution has been studied and reported extensively. However, the effects of middle and final flushes on pollutant flushing were not given much attention. In addition, few previous studies have discussed the suitability of the widely used exponential wash-off model for describing the middle or final flush processes. In this paper, the Shiyan River catchment, a typical rapidly urbanizing catchment in China, is chosen as a study area to analyze the effects of first, middle and final flushes based on monitoring hydrographs and pollutographs. In order to simulate the middle and final flush processes observed in storm events, a new, realistically simple, parsimonious model (named as logistic wash-off model) is developed with the assumption that surface pollutant loads available for wash-off increase with cumulative runoff volume following a logistic curve. The popular exponential wash-off model and the newly developed model are used and compared in simulating the flush processes in storm events. The results indicate that all the three types of pollutant flushing are observed in the experiment; however, the first flush effect is weak, while the middle and final flush effects are substantial. The exponential model has performed well in simulating the first flush process but failed to simulate well the middle and final flush processes. However, the logistic wash-off model has effectively simulated all the three types of pollutant flush, and particularly, it has performed better in simulating the middle and final flush processes than the exponential model.

Runoff sensitivity to climate change for hydro-climatically different catchments in China

Communities are facing severe water stress due to the rapid development of agriculture and industry, climate change, as well as population growth. Climate variability has a big impact on runoff variation and it is important to understand these hydrological responses. Using a water balance model, monthly discharges of 21 climatically different catchments in China were simulated. Sensitivities of runoff to climate change were investigated by adopting hypothetical climate scenarios. Results indicate that the water balance model performs well for monthly discharge simulations of climatically different catchments with Nash–Sutcliffe coefficients >65 % and relative errors falling in the range of ±5 %. In general, runoff in arid north China are more sensitive to climate change than those in humid south China. A 1 °C rise in temperature would probably lead to 1.2–4.4 % decreases in runoff. A decrease in precipitation of 10 % would result in 9.4–17.4 % of decreases in runoff. It is essential to consider the implications of climate change in future water resources management.

Effects of cultivation and reforestation on suspended sediment concentrations: a case study in a mountainous catchment in China

Abstract. Understanding how sediment concentrations vary with land use/cover is critical for evaluating the current and future impacts of human activities on river systems. This paper presents suspended sediment concentration (SSC) dynamics and the relationship between SSC and discharge (Q) in the 8973 km2 Du catchment and its sub-catchment (4635 km2). In the Du catchment and its sub-catchment, 4235 and 3980 paired SSC–Q samples, respectively, were collected over 30 years. Under the influence of the Household Contract Responsibility System and Grain-for-Green projects in China, three periods were designated, the original period (1980s), cultivation period (1990s) and reforestation period (2000s). The results of a Mann–Kendall test showed that rainfall slightly increased during the study years; however, the annual discharge and sediment load significantly decreased. The annual suspended sediment yield of the Du catchment varied between 1.3 × 108 and 1.0 × 1010 kg, and that of the sub-catchment varied between 6.3 × 107 and 4.3 × 109 kg. The SSCs in the catchment and sub-catchment fluctuated between 1 and 22400 g m−3 and between 1 and 31800 g m−3, respectively. The mean SSC of the Du catchment was relatively stable during the three periods (±83 g m−3). ANOVA (analysis of variance) indicated that the SSC did not significantly change under cultivation for low and moderate flows, but was significantly different under high flow during reforestation of the Du catchment. The SSC in the sub-catchment was more variable, and the mean SSC in the sub-catchment varied from 1058 ± 2217 g m−3 in the 1980s to 1256 ± 2496 g m−3 in the 1990s and 891 ± 1558 g m−3 in the 2000s. Reforestation significantly decreased the SSCs during low and moderate flows, whereas cultivation increased the SSCs during high flow. The sediment rating curves showed a stable relationship between the SSC and Q in the Du catchment during the three periods. However, the SSC–Q of the sub-catchment exhibited scattered relationships during the original and cultivation periods and a more linear relationship during the reforestation period.

Similarity, difference and correlation of meteorological and hydrological drought indices in a humid climate region – the Poyang Lake catchment in China

Based on the estimation of standardized precipitation–evapotranspiration index (SPEI) and standardized runoff index (SRI), this study investigated the variability and correlation of hydrological drought and meteorological drought in a humid climate region – the Poyang Lake catchment in China. Results indicate that the occurrences of hydrological droughts in the catchment are different from those of meteorological drought on both a seasonal and annual basis. However, annual variability of both indices showed the same periodic variation characteristics during the study period. With comparison of the performance of SPEI and SRI time series at different timescales, our observation reveals that the two drought indices show a higher degree of similarity and correlation as timescales increased. In addition, SRI is found to be less variable than SPEI at shorter timescales and it shows an obvious hydrologic delay of about 1–2 months in response to SPEI at timescales &amp;gt;12 months. Due to hydrologic detention of subsurface soil moisture, shallow groundwater and perhaps reservoir storage, a 2-month timescale of SPEI is found to be more appropriate for river discharge monitoring, especially for those rivers with similar drainage area, climate and geographical conditions as in this study region.

Ecological Catchments in China – Health, Restoration, Division and Management

Ecological Catchments in China – Health, Restoration, Division and Management

Risk of endocrine disruption to fish in the Yellow River catchment in China assessed using a spatially explicit model.

The global water availability assessment (GWAVA) model, incorporating regional water abstractions and reservoir information, was used to model the human-sourced steroid estrogens estrone (E1) and estradiol (E2) in the Yellow River catchment (China). The river flows in the main stem were calibrated using gauged flows. Following a review of Chinese data on estrogen discharge from a range of sewage treatment plants, low, median, and high discharge rates were identified and used as best, expected, and worst-case scenarios, respectively. For any given location, the temporal variation of modeled estrogen levels was summarized using the mean and upper 90th percentile, which is where the model predicts 90% of values would be below this concentration. The predicted means and 90th percentiles for E1 were comparable to previous E1 measurements reported in the river. For the whole catchment, only 19% (mean value) of the river system by length was predicted to exceed 1 ng/L E2 equivalents (EEQs) using expected estrogen sewage discharge. Only 3% of the network by length was predicted to exceed the dangerously high 10 ng/L EEQ when considering 90th percentile concentrations. The highest exposures were in the Fen and Wei tributaries. Endocrine disruption risk from estrogens was predicted to be minimal in the main stem. Only in the worst-case discharge scenario and 90th percentile predicted concentrations were the most downstream river reaches of the main stem predicted to be at risk. Reservoirs appeared to be helpful in reducing estrogen concentrations thanks to longer water residence facilitating biodegradation.

Application of HEC-HMS for flood forecasting in Misai and Wan'an catchments in China

The hydrologic model HEC-HMS (Hydrologic Engineering Center, Hydrologic Modeling System), used in combination with the Geospatial Hydrologic Modeling Extension, HEC-GeoHMS, is not a site-specific hydrologic model. Although China has seen the applications of many hydrologic and hydraulic models, HEC-HMS is seldom applied in China, and where it is applied, it is not applied holistically. This paper presents a holistic application of HEC-HMS. Its applicability, capability and suitability for flood forecasting in catchments were examined. The DEMs (digital elevation models) of the study areas were processed using HEC-GeoHMS, an ArcView GIS extension for catchment delineation, terrain pre-processing, and basin processing. The model was calibrated and verified using historical observed data. The determination coefficients and coefficients of agreement for all the flood events were above 0.9, and the relative errors in peak discharges were all within the acceptable range.

Assessing the Uncertainty of the Xinanjiang Rainfall-Runoff Model: Effect of the Likelihood Function Choice on the GLUE Method

In this paper, the generalized likelihood uncertainty estimation (GLUE) methodology, which is widely applied in the field of hydrology, is used for testing and predictive uncertainty estimation in the application of the Xinanjiang rainfall-runoff (XAJ-RR) model for estimating monthly stream flow (Nangao reservoir) catchment in China. However, one of the drawbacks of using the GLUE method is the definition of the likelihood function, which reflects the behavior of the hydrological model. Although there are different formulations of likelihood functions in the literature, most previous research focused on the application of the GLUE method with the likelihood function of Nash-Sutcliffe (NS) efficiency. In this respect, to illustrate the impact of the selection of likelihood functions on the results of the GLUE method, the authors adopted four likelihood functions: NS, normalized absolute error (NAE), index of agreement (IoA), and Chiew and McMahon (CM). The main findings of the study are that (1) the parameter uncertainty is more sensitive to the choice of the likelihood functions than the uncertainty in the model prediction by the GLUE method; (2) the parameters of the XAJ-RR model with NS had less uncertainty compared to those of NAE, IoA, and CM; (3) the uncertainty bounds showed slight differences from various likelihood functions; and (4) the computational efficiency of the GLUE method based on likelihood function IoA was much better because the IoA likelihood function corresponded to narrower uncertainty bounds, higher bracketing of observations, and the best maximum value of likelihood functions. Thus, this study confirms the importance of the likelihood function selection in the application of GLUE to the uncertainty assessment of the XAJ-RR model.