Influence Of Catchment Characteristics Research Articles

Unlocking the potential of stochastic simulation through Bluecat: Enhancing runoff predictions in arid and high‐altitude regions

AbstractRunoff prediction is crucial for effective water resource management and risk mitigation. However, predicting these catchment responses is challenging due to their unique characteristics and the randomness of hydrological processes. This manuscript explores two different types of modelling frameworks (deterministic and stochastic) and aims to answer questions regarding the reliance on stochastic simulation based on deterministic simulations, the suitability of simple deterministic models, and the influence of catchment characteristics on the results. A simple deterministic rainfall‐runoff model (with only one model parameter) was used to feed the Brisk Local Uncertainty Estimator for Hydrological Simulations and Predictions (Bluecat) framework, exploring the whole range of values of the model parameter. Our findings showed that Bluecat enhanced the Kling‐Gupta Efficiency (KGE) outcomes in arid and semi‐arid regions as well as high‐altitude catchments. Additionally, using the mean of the confidence band of the stochastic simulation as the simulated discharge, rather than the median, resulted in improved KGE values for all catchments. Hysteresis between S‐KGE (stochastic KGE) and D‐KGE (deterministic KGE) was observed, indicating a non‐monotonic relationship between the two variables, and therefore, S‐KGE optimisation can be achieved even when D‐KGE is not optimal. Bluecat showed exceptional performance extended to arid and semi‐arid regions, as well as high‐altitude areas, making it a promising alternative for rainfall‐runoff simulations in these challenging locations.

Catchment Scale Evaluation of Multiple Global Hydrological Models from ISIMIP2a over North America

A satisfactory performance of hydrological models under historical climate conditions is considered a prerequisite step in any hydrological climate change impact study. Despite the significant interest in global hydrological modeling, few systematic evaluations of global hydrological models (gHMs) at the catchment scale have been carried out. This study investigates the performance of 4 gHMs driven by 4 global observation-based meteorological inputs at simulating weekly discharges over 198 large-sized North American catchments for the 1971–2010 period. The 16 discharge simulations serve as the basis for evaluating gHM accuracy at the catchment scale within the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a). The simulated discharges by the four gHMs are compared against observed and simulated weekly discharge values by two regional hydrological models (rHMs) driven by a global meteorological dataset for the same period. We discuss the implications of both modeling approaches as well as the influence of catchment characteristics and global meteorological forcing in terms of model performance through statistical criteria and visual hydrograph comparison for catchment-scale hydrological studies. Overall, the gHM discharge statistics exhibit poor agreement with observations at the catchment scale and manifest considerable bias and errors in seasonal flow simulations. We confirm that the gHM approach, as experimentally implemented through the ISIMIP2a, must be used with caution for regional studies. We find the rHM approach to be more trustworthy and recommend using it for hydrological studies, especially if findings are intended to support operational decision-making.

Effects of land cover, topography, and soil on stream water quality at multiple spatial and seasonal scales in a German lowland catchment

The influence of catchment characteristics on water quality varies with space and time. Understanding the key factors influencing water quality is needed for effective land use and riparian management to protect river health. To this end, we quantified effects on stream water quality in summer and winter between 1992 and 2019 at multiple spatial scales in the upper Stör catchment, Germany. We applied multivariate statistical analyses on three scales: the catchment, riparian, and reach scale. Our results indicated that poorer water quality mostly occurred in winter and in steeper arable and pasture areas and in wetlands. Water quality was strongly affected by soil properties, land use composition (the areal shares of arable or pasture land respectively with slopes >2%, forest, and urban) and configuration. The spatial variation of the overall water quality was better explained at the larger scales (riparian and catchment) and in summer (73–78%). The most important variables differed among scales and for the different water quality variables. Forest and complex landscape patterns showed more negative correlations with degraded water quality at the reach scale when compared to larger scales. At larger scales, besides permeable and organic soils, steeper arable lands were most significant for nitrate-nitrogen (NO3-N) and steeper pasture areas for phosphate-phosphorus (PO4-P) pollution. The results of this study provide valuable insights for guiding sustainable and spatially specific land-water management of river catchments at different scales to improve stream water quality.

Bacterial production, abundance and cell properties in boreal estuaries: relation to dissolved organic matter quantity and quality

Estuarine bacteria are key modifiers of allochthonous matter entering the sea, and thereby control major biogeochemical processes such as nutrient cycling and organic matter transformation. In a highly dynamic estuarine environment, bacterial growth and activity are regulated by multiple factors including the availability of organic carbon, inorganic nutrient concentrations, salinity and temperature. The variability of estuarine bacterial communities in relation to environmental factors and dissolved organic matter (DOM) quantity and quality was studied in three Baltic Sea estuaries with different catchment characteristics, flow and mixing regimes. The work was conducted during six consecutive seasons over 2 years. Bacterial activity, biomass and cytometric cell population characteristics were studied against an suite of environmental parameters and DOM quality and quantity (Salinity, DOC, DON and DIN concentration, SUVA254, UV Slope275–295, Fluoresecence peaks A and T, and Apparent mean molecular weight). Environmental variables and DOM quality varied significantly between rivers, indicating influence of catchment characteristics. Bacterial biomass varied significantly between the sampling seasons, and bacterial production also varied between the rivers, indicating an influence of DOM quality on bacterial activity. Based on cytometric grouping into low- and high- nucleic acid bacterial populations (LNA and HNA, respectively) salinity-dependent and salinity-independent clusters of bacterial variables were identified. The results suggest that the LNA clusters were not directly dependent on salinity, but possibly linked to humic substance degradation, whereas the HNA clusters were linked to salinity-correlated environmental variables reflecting DOM quality. Mixed-effects regression modeling of bacterial biomass turnover time suggests DOM fluorescence properties to be useful proxies of bioavailability. Our study shows that growth and community dynamics of estuarine bacteria may be partially regulated by quality of riverine DOM, and cytometric sub-populations of estuarine bacteria have differing regulative factors.

Classification of dissolved organic carbon (DOC) in river systems: Influence of catchment characteristics and autochthonous processes

Dissolved organic carbon (DOC) in surface waters is influenced by natural and anthropogenic allochthonous sources in the catchment and by autochthonous production and degradation processes. An objective differentiation procedure, a principal component analysis, has been used to answer the question: Is it possible to classify different water types using only DOC-patterns, and how do seasonal variations influence such a classification? Organic compounds from various sources and river systems were analyzed by means of automated size-exclusion chromatography. Four different DOC fractions (humic substances, polysaccharides, low molecular weight acids and low weight substances) were separated on the basis of their molecular weight characteristics and quantified on the basis of their UV absorbance. Significant differences in the quality and quantity of organic compounds were found. These were related to the character of the catchment area and to autochthonous processes. It was possible to classify peat-influenced ditch waters, peat-influenced surface waters, mineral soil-influenced and anthropogenically-influenced surface waters, and waters from small and large lake–river systems. The characterization of DOC patterns combined with principal component analysis is a powerful tool for analyzing allochthonous and autochthonous DOC sources in surface waters, especially if seasonal variations are taken into account.

The influence of catchment characteristics on the seasonality of carbon and nitrogen species concentrations in upland rivers of Northern Scotland

Data from 13 catchments with no arable land in Northern Scotland were used to develop empirical linear regression models of average monthly NO3 − concentrations and average summer and winter concentrations for NH4 +, dissolved organic N (DON) and dissolved organic carbon (DOC) as a function of catchment characteristics. All catchments displayed a pronounced seasonal NO3 − cycle. Variation in monthly mean NO3 − concentration within and between catchments could be predicted from mean monthly air temperature using separate regression equations for temperatures < and ≥ 5 °C. Soil type, climate and land use influenced NH4 + concentrations. In summer, concentrations of NH4 + were largest in catchments with extensive areas of brown forest soils, which are less acidic and more base-rich than other upland soils. However, concentrations declined with increasing conifer cover and summer rainfall. In winter, however, % conifer cover had a positive effect, while higher temperature and higher humus iron podzol cover had negative influences. DON concentration decreased with increasing catchment elevation in both summer and winter. Surprisingly, concentrations of DON only displayed a positive relationship with percentage peat cover in the summer. The most important factor controlling DOC concentration was soil type, with a positive relationship being observed between DOC and peat and humus iron podzol coverage. Elevation was also important, but only in the winter when concentrations were negatively correlated with maximum catchment elevation. Overall, multivariate regression equations explained the spatial and seasonal variability in N species concentrations over a range of catchments within Northern Scotland.

The influence of catchment characteristics on suspended sediment properties

The influence of catchment characteristics on suspended sediment properties

Influence of catchment characteristics and hydrology on dissolved organic carbon in rivers in north-eastern Poland

Influence of catchment characteristics and hydrology on dissolved organic carbon in rivers in north-eastern Poland

Understanding runoff processes using a watershed model—a case study in the Western Ghats in South India

The wet tropical Western Ghat Mountain ranges in South India present an interesting combination of meteorological and physical characteristics. The results of a watershed model analysis carried out to understand the catchment response and the relative importance of different runoff processes in the region are reported in this paper. A lumped parameter model simulating saturated source area runoff, lateral flow through pipes and the saturated zone groundwater flow, has been developed assuming that source area runoff is the only quickflow component. The model has been calibrated on seven catchments using sufficiently long records of daily data. A wide range of tests has been used to show that the model performs reliably. The influence of catchment characteristics on the relative importance of the flow components and the catchment response has been studied. The model simulations have been interpreted to infer that the pipeflow contributions augment the contributions of source area runoff to stream quickflow. Suggestions for further research in the area are given, based on the inferences drawn.

The influence of catchment characteristics, agricultural activities and atmospheric deposition on the chemistry of small streams in the English Lake District

Six synoptic surveys of 55 streams draining the central English Lake District, Cumbria, were carried out during the period May 1996–March 1997 to measure streamwater chemistry under a variety of flow conditions and relate this to geology and land use. Annual mean flow-weighted Gran alkalinity of the streams in the study ranges from 2 to 452 μeq l−1. Using 200 μeq l−1 alkalinity as a sensitivity threshold, 41 of the streams (75%) can be considered sensitive to acidification via acid deposition. Of the sensitive streams, 12 have annual mean flow-weighted Gran alkalinities less than 50 μeq l−1, suggesting a critical level of sensitivity to acidification. By grouping the streams into categories based on the dominant geology, it is clear that geology plays a major role in determining streamwater chemistry. However, the chemical signature of the streams is significantly modified through the effects of land use. One example is stream nitrate (NO3−) concentration which ranges from 0 to 238 μeq l−1 (flow-weighted mean). All of the seven streams with flow-weighted NO3− values above 50 μeq l−1 drain predominantly agricultural catchments, with cover varying between 63 and 100%. The flow-weighted chemistry data were related to catchment characteristics (geology, land use, deposition and soil type) using multiple regression analysis. The influence of agriculture generally dominated the models. In particular, strong relationships were found between percentage agricultural land and Gran alkalinity (R2=0.53), percentage agricultural land and calcium (R2=0.50) and percentage agricultural land and nitrate concentrations (R2=0.40). This survey confirms that the resistant bedrock of the Lake District generally results in low base cation resupply to the streams. Due to this very low buffering capacity it is likely that many of the streams have been impacted by acid deposition, especially those draining the slow-weathering Skiddaw Slates, Borrowdale Volcanics and granitic bedrock. The easier-weathering Silurian Slates provide higher buffering capacity to drainage waters. Agriculture, which is mostly found on the Silurian Slates, increases the buffering capacity of the drainage water but also results in enhanced nitrate leaching.

Influence of catchment characteristics, forestry activities and deposition on nitrogen export from small forested catchments

Effect of geographical factors, forestry activities and deposition on nitrogen load from small forested catchments