scholarly journals A multi-approach and multi-scale study on water quantity and quality changes in the Tapajós River basin, Amazon

Author(s):  
Rodolfo Luiz Bezerra Nóbrega ◽  
Gabriele Lamparter ◽  
Harold Hughes ◽  
Alphonce Chenjerayi Guzha ◽  
Ricardo Santos Silva Amorim ◽  
...  

Abstract. We analyzed changes in water quantity and quality at different spatial scales within the Tapajós River basin (Amazon) based on experimental fieldwork, hydrological modelling, and statistical time-trend analysis. At a small scale, we compared the river discharge (Q) and suspended-sediment concentrations (SSC) of two adjacent micro-catchments (< 1 km2) with similar characteristics but contrasting land uses (forest vs. pasture) using empirical data from field measurements. At an intermediary scale, we simulated the hydrological responses of a sub-basin of the Tapajós (Jamanxim River basin, 37 400 km2), using a hydrological model (SWAT) and land-use change scenario in order to quantify the changes in the water balance components due to deforestation. At the Tapajós' River basin scale, we investigated trends in Q, sediments, hydrochemistry, and geochemistry in the river using available data from the HYBAM Observation Service. The results in the micro-catchments showed a higher runoff coefficient in the pasture (0.67) than in the forest catchment (0.28). At this scale, the SSC were also significantly greater during stormflows in the pasture than in the forest catchment. At the Jamanxim watershed scale, the hydrological modelling results showed a 2 % increase in Q and a 5 % reduction of baseflow contribution to total Q after a conversion of 22 % of forest to pasture. In the Tapajós River, however, trend analysis did not show any significant trend in discharge and sediment concentration. However, we found upward trends in dissolved organic carbon and NO3- over the last 20 years. Although the magnitude of anthropogenic impact has shown be scale-dependent, we were able to find changes in the Tapajós River basin in streamflow, sediment concentration, and water quality across all studied scales.

Author(s):  
Davide Bonaldo ◽  
Alvise Benetazzo ◽  
Andrea Bergamasco ◽  
Francesco Falcieri ◽  
Sandro Carniel ◽  
...  

AbstractThe shallow, gently sloping, sandy-silty seabed of the Venetian coast (Italy) is studded by a number of outcropping rocky systems of different size encouraging the development of peculiar zoobenthic biocenoses with considerably higher biodiversity indexes compared to neighbouring areas. In order to protect and enhance the growth of settling communities, artificial monolithic reefs were deployed close to the most important formations, providing further nesting sites and mechanical hindrance to illegal trawl fishing.In this framework, a multi-step and multi-scale numerical modelling activity was carried out to predict the perturbations induced by the presence of artificial structures on sediment transport over the outcroppings and their implications on turbidity and water quality. After having characterized wave and current circulation climate at the sub-basin scale over a reference year, a set of small scale simulations was carried out to describe the effects of a single monolith under different geometries and hydrodynamic forcings, encompassing the conditions likely occurring at the study sites. A dedicated tool was then developed to compose the information contained in the small-scale database into realistic deployment configurations, and applied in four protected outcroppings identified as test sites. With reference to these cases, under current meteomarine climate the application highlighted a small and localised increase in suspended sediment concentration, suggesting that the implemented deployment strategy is not likely to produce harmful effects on turbidity close to the outcroppings.In a broader context, the activity is oriented at the tuning of a flexible instrument for supporting the decision-making process in benthic environments of outstanding environmental relevance, especially in the Integrated Coastal Zone Management or Maritime Spatial Planning applications. The dissemination of sub-basin scale modelling results via the THREDDS Data Server, together with an user-friendly software for composing single-monolith runs and a graphical interface for exploring the available data, significantly improves the quantitative information collection and sharing among scientists, stakeholders and policy-makers.


2021 ◽  
Author(s):  
Santiago Duarte ◽  
Gerald Corzo ◽  
Germán Santos

&lt;p&gt;Bogot&amp;#225;&amp;#8217;s River Basin, it&amp;#8217;s an important basin in Cundinamarca, Colombia&amp;#8217;s central region. Due to the complexity of the dynamical climatic system in tropical regions, can be difficult to predict and use the information of GCMs at the basin scale. This region is especially influenced by ENSO and non-linear climatic oscillation phenomena. Furthermore, considering that climatic processes are essentially non-linear and possibly chaotic, it may reduce the effectiveness of downscaling techniques in this region.&amp;#160;&lt;/p&gt;&lt;p&gt;In this study, we try to apply chaotic downscaling to see if we could identify synchronicity that will allow us to better predict. It was possible to identify clearly the best time aggregation that can capture at the best the maximum relations between the variables at different spatial scales. Aside this research proposes a new combination of multiple attractors. Few analyses have been made to evaluate the existence of synchronicity between two or more attractors. And less analysis has considered the chaotic behaviour in attractors derived from climatic time series at different spatial scales.&amp;#160;&lt;/p&gt;&lt;p&gt;Thus, we evaluate general synchronization between multiple attractors of various climate time series. The Mutual False Nearest Neighbours parameter (MFNN) is used to test the &amp;#8220;Synchronicity Level&amp;#8221; (existence of any type of synchronization) between two different attractors. Two climatic variables were selected for the analysis: Precipitation and Temperature. Likewise, two information sources are used: At the basin scale, local climatic-gauge stations with daily data and at global scale, the output of the MPI-ESM-MR model with a spatial resolution of 1.875&amp;#176;x1.875&amp;#176; for both climatic variables (1850-2005). In the downscaling process, two RCP (Representative Concentration Pathways)&amp;#160; scenarios are used, RCP 4.5 and RCP 8.5.&lt;/p&gt;&lt;p&gt;For the attractor&amp;#8217;s reconstruction, the time-delay is obtained through the&amp;#160; Autocorrelation and the Mutual Information functions. The False Nearest Neighbors method (FNN) allowed finding the embedding dimension to unfold the attractor. This information was used to identify deterministic chaos at different times (e.g. 1, 2, 3 and 5 days) and spatial scales using the Lyapunov exponents. These results were used to test the synchronicity between the various chaotic attractor&amp;#8217;s sets using the MFNN method and time-delay relations. An optimization function was used to find the attractor&amp;#8217;s distance relation that increases the synchronicity between the attractors.&amp;#160; These results provided the potential of synchronicity in chaotic attractors to improve rainfall and temperature downscaling results at aggregated daily-time steps. Knowledge of loss information related to multiple reconstructed attractors can provide a better construction of downscaling models. This is new information for the downscaling process. Furthermore, synchronicity can improve the selection of neighbours for nearest-neighbours methods looking at the behaviour of synchronized attractors. This analysis can also allow the classification of unique patterns and relationships between climatic variables at different temporal and spatial scales.&lt;/p&gt;


2020 ◽  
Vol 20 (7) ◽  
pp. 2471-2483
Author(s):  
Chun Kang Ng ◽  
Jing Lin Ng ◽  
Yuk Feng Huang ◽  
Yi Xun Tan ◽  
Majid Mirzaei

Abstract Climate change is most likely to cause changes to the temporal and spatial variability of rainfall. A trend analysis to investigate the rainfall pattern can detect changes over temporal and spatial scales for a rainfall series. In this study, trend analysis using the Mann–Kendall test and Sen's slope estimator was conducted in the Kelantan River Basin, Malaysia. The Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test was applied to evaluate the stationarity of the rainfall series. This basin annually faces onslaughts of varying year-end flooding conditions. The trend analysis was applied for monthly, seasonal and yearly rainfall series between 1989 and 2018. The temporal analysis results showed that both increasing and decreasing trends were detected for all rainfall series. The spatial analysis results indicated that the northern region of the Kelantan River Basin showed an increasing trend, whilst the southwest region showed a decreasing trend. It was found that almost all the rainfall series were stationary except at two rainfall stations during the Inter Monsoon 1, Inter Monsoon 2 and yearly rainfall series. Results obtained from this study can be used as reference for water resources planning and climate change assessment.


2020 ◽  
Author(s):  
David Wichmann ◽  
Christian Kehl ◽  
Henk A. Dijkstra ◽  
Erik van Sebille

Abstract. The detection of finite-time coherent particle sets in Lagrangian trajectory data using data clustering techniques is an active research field at the moment. Yet, the clustering methods mostly employed so far have been based on graph partitioning, which assigns each trajectory to a cluster, i.e. there is no concept of noisy, incoherent trajectories. This is problematic for applications to the ocean, where many small coherent eddies are present in a large fluid domain. In addition, to our knowledge none of the existing methods to detect finite-time coherent sets has an intrinsic notion of coherence hierarchy, i.e. the detection of finite-time coherent sets at different spatial scales. Such coherence hierarchies are present in the ocean, where basin scale coherence coexists with smaller coherent structures such as jets and mesoscale eddies. Here, for the first time in this context, we use the density-based clustering algorithm OPTICS (Ankerst et al., 1999) to detect finite-time coherent particle sets in Lagrangian trajectory data. Different from partition based clustering methods, OPTICS does not require to fix the number of clusters beforehand. Derived clustering results contain a concept of noise, such that not every trajectory needs to be part of a cluster. OPTICS also has a major advantage compared to the previously used DBSCAN method, as it can detect clusters of varying density. Further, clusters can also be detected based on density changes instead of absolute density. Finally, OPTICS based clusters have an intrinsically hierarchical structure, which allows to detect coherent trajectory sets at different spatial scales at once. We apply OPTICS directly to Lagrangian trajectory data in the Bickley jet model flow and successfully detect the expected vortices and the jet. The resulting clustering separates the vortices and the jet from background noise, with an imprint of the hierarchical clustering structure of coherent, small scale vortices in a coherent, large-scale, background flow. We then apply our method to a set of virtual trajectories released in the eastern South Atlantic Ocean in an eddying ocean model and successfully detect Agulhas rings. At larger scale, our method also separates the eastward and westward moving parts of the subtropical gyre. We illustrate the difference between our approach and partition based k-Means clustering using a 2-dimensional embedding of the trajectories derived from classical multidimensional scaling. We also show how OPTICS can be applied to the spectral embedding of a trajectory based network to overcome the problems of k-Means spectral clustering in detecting Agulhas rings.


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