9 research outputs found

    Getting a grip on hydrological and sediment connectivity

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    Land degradation is a large problem worldwide, especially in agricultural areas. Between 1-6 billion ha of land worldwide is affected by land degradation. With an increasing world population, more food production is needed and, therefore, more land is converted into agricultural areas. This conversion of land to agricultural areas, in turn, leads to more land degradation. Some common forms of land degradation are desertification, salinization and soil erosion by water. The negative effects of soil erosion have been recognized for a long time. Since the early 20th century, researchers have tried to quantify soil displaced due to water, and to measure and model the efficiency of management strategies. The implications of problems with upscaling, wrong process representation and equifinality include the difficulty to properly predict sediment sources, pathways and sinks within catchments. These problems then can translate into the implementation of sub-optimal management strategies. To deal with these non-linear processes and the lack of proper representation of water and sediment sources, pathways and sinks, the concept of connectivity was developed. Currently, many definitions of connectivity have been proposed, although the definition most used is that of hydrological connectivity by Pringle (2003): ‘Hydrologic connectivity is the water-mediated transport of matter, energy and organisms within or between elements of the hydrologic cycle’. A unified theory on what constitutes connectivity and how connectivity should be measured or inferred remains one of the biggest challenges within catchment science. In addition, it is unclear whether connectivity should be an output or an input of a model and if an input, whether this should be added explicitly or implicitly. The main objective of this thesis was, therefore, to assess and quantify hydrological and sediment connectivity in a meaningful way, which can further our understanding of hydrological and sediment transport processes and catchment system dynamics. The study was carried out in three catchments in Navarre, northern Spain. Two catchments, ‘Latxaga’ and ‘La Tejeria’, are agricultural catchments with sizes of 2.07 km2 and 1.69 km2, respectively. The ‘Oskotz Forestal’ catchment is a (semi-)natural catchment, with a size of 5.05 km2. Land cover in the agricultural catchments is mainly winter wheat and barley, while in the Oskotz catchment it is grassland and forest. Latxaga and La Tejeria are mainly underlain by marls and within La Tejeria some sandstone is also present. The geology in Oskotz is characterised by an alternation of marls and sandy limestone. In chapter 2, I used networks (graph theory) to characterise and quantify overland flow connectivity dynamics on hillslopes in a humid sub-Mediterranean environment by using a combination of high-resolution digital-terrain models, overland flow sensors and a network approach. Results showed that there are significant differences between overland flow connectivity on agricultural areas and semi-natural shrubs areas. Significant positive correlations between connectivity and precipitation characteristics were found. Significant negative correlations between connectivity and soil moisture were found, most likely due to soil water repellency and/or soil surface crusting. The combination of structural networks and dynamic networks for determining potential connectivity and actual connectivity proved a powerful tool for analysing overland flow connectivity. In chapter 3, I determined the functioning of hillslope-channel connectivity and the continuation of transport of these sediments in the channel. To determine this functioning, I obtained data on sediment transport from the hillslopes to the channels while simultaneously looking at factors that influence sediment export out of the catchment. For measuring hillslope-channel sediment connectivity, Rare-Earth Oxide (REO) tracers were applied to a hillslope in the Latxaga catchment preceding the winter of 2014-2015. The results showed that during the winter there have been no sediments transported from the hillslope into the channel. Analysis of precipitation data showed that although total precipitation quantities did not differ much from the mean, the precipitation intensities were low. Using a Random Forest (RF) machine learning method, I showed that hillslope-channel connectivity in Latxaga is dominated by sediment mobilisation during large (high intensity) precipitation events. Sediments are for a large part exported during those events. Large events also leave behind large amounts of sediments in and near the channel, which is gradually removed by small events. In chapter 4 I demonstrated that existing data can be used to assess governing factors of connectivity, and how these factors change over time. Data from three catchments in Navarre, Northern Spain, were used to assess factors that influence hydrologic and sediment connectivity. These factors were used as components in a spatially-lumped linear model for discharge and suspended-sediment yield. Three components of connectivity were distinguished: topographical, biological and soil. Changes in the topographical component for the studied periods were considered relatively small, and, therefore, kept constant. Changes in the biological component were determined using the Normalised Difference Vegetation Index. Changes in the soil component were assessed using an Antecedent Precipitation Index. Nash-Sutcliffe model efficiency coefficients were between 0.49 through 0.62 for the discharge models and between 0.23 through 0.3 for the sediment-yield models. I recommended applying the model at smaller spatial scales than catchment scale to minimize the lumping of spatial variability in the components. In chapter 5, the objective was to better understand the implications of model calibration at different spatial scales on the simulation of hydrology and sediment dynamics of an agricultural catchment. I applied the LAPSUS-D model to the Latxaga catchment. The model was calibrated and validated (4 years: 2011-2015) using three datasets at varying spatial scales: hillslope, catchment and the combined dataset (combined-calibrated model). The hillslope-calibrated model showed mainly infiltration-excess overland flow, the catchment-calibrated mainly saturation-excess overland flow at the footslopes and the combined-calibrated model showed saturation-excess overland flow from the midslopes to the footslopes. For hydrology, the combined-calibrated model simulated the large discharge peaks best, while at the hillslope scale, the hillslope-calibrated model performed best. The hillslope-calibrated model produced the highest model efficiencies for sediments, for calibration (0.618) and validation (0.269). The hillslope-calibrated model was the only model that showed observed gully erosion on a high-resolution DEM and displayed channel sediment dynamics. However, absolute quantities of erosion and deposition within the catchment were too high. The results show that modellers need to be aware of problems associated with automatic calibration, over-calibration and not incorporating measured data at multiple spatial scales. We advocate incorporating runoff and sediment tracing data at multiple scales whenever this is possible and to, furthermore, carry out specific measuring campaigns towards this end, ultimately to get a more comprehensive view on hydrological and sediment connectivity within a catchment. The combination of chapters in this thesis showed that the connectivity concept is useful for a wide range of studies, from hillslope scale to catchment scale. Using the concept, I was able to determine sediment dynamics for a humid-Mediterranean catchment and show that this behaviour is different than previously thought. Depending of the aim of the study, various concepts of connectivity are useful. Different geologic and climatic settings cause large differences in catchment (sediment) dynamics. It might, therefore, not be necessary, or even possible, to strive for a single, unifying conceptual framework for connectivity. Instead, a collection of frameworks for different settings should be developed. These frameworks should, however, always aim at helping to understand which measurements need to be taken and which type of models and indices should be used for that particular setting. It is my honest opinion that connectivity is definitely a useful concept to advance our knowledge on water and sediment transport processes further. However, careful consideration is also required as this particular concept will not necessary provide the ultimate explanation and insights in dynamic behaviour within watersheds around the world. The gap between the different spatial and temporal scales is too complex to be bridged with a single concept like connectivity. However, the many studies about connectivity that will be published in the near future will be able to advance knowledge on water and sediment transport processes.</p

    The effectiveness of soil conservation measures at a landscape scale in the West Usambara highlands, Tanzania

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    The adoption of soil and water conservation (SWC) technologies among small holder farmers in the East African highlands is an area which poses many challenges. When adoption occurs across a vast landscape, the locations and effectiveness of the adopted measures are often not adequately known. For this reason, the majority of SWC studies in the highlands of East Africa employed field surveys and experiments to locate and estimate effectiveness of the installed technologies. This approach however has certain limitations when applied at a landscape scale. Potentially, remote sensing techniques could be used for the purpose of locating soil conservation structures, while modeling can help in estimating the effectiveness of the implemented measures. This study therefore employed remote sensing and GIS techniques to 1) to locate SWC structures in two 100km2 areas in the West Usambara highlands of Tanzania, and 2) to determine the effectiveness of the implemented measures in reducing soil erosion at a landscape scale. The study was conducted in the west Usambara highlands of north-eastern Tanzania as a paired plot design in which two blocks of 100km2 each were studied using pixel (Maximum Likelihood Classification) and object-based image analysis (OBIA) remote sensing techniques to detect land use patterns and adoption of soil conservation technologies. Soil losses were modeled using the Universal Soil Loss Equation (USLE)-model while effectiveness of the measures was estimated from calculations. Results indicate that there are large differences in the adoption of soil conservation technologies between the two blocks. The study also finds the Maximum Likelihood Classifier to be reliable in generating land use thematic layer maps from which soil conservation measures can be studied with ease in mountainous areas. The OBIA-technique was found to be effective in identifying, classifying and mapping of the adopted SWC technologies. Effectiveness of the installed technologies remained comparable across the blocks but with higher indices for Sunga area. The study concludes that adoption of the SWC technologies in the two blocks is largely influenced by biophysical conditions within and between the two blocks and is not related to the quality of the technologies being implemented in either block.</p

    The way forward : Can connectivity be useful to design better measuring and modelling schemes for water and sediment dynamics?

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    For many years, scientists have tried to understand, describe and quantify water and sediment fluxes, with associated substances like pollutants, at multiple scales. In the past two decades, a new concept called connectivity has been used by Earth Scientists as a means to describe and quantify the influences on the fluxes of water and sediment on different scales: aggregate, pedon, location on the slope, slope, watershed, and basin. A better understanding of connectivity can enhance our comprehension of landscape processes and provide a basis for the development of better measurement and modelling approaches, further leading to a better potential for implementing this concept as a management tool. This paper provides a short review of the State-of-the-Art of the connectivity concept, from which we conclude that scientists have been struggling to find a way to quantify connectivity so far. We adapt the knowledge of connectivity to better understand and quantify water and sediment transfers in catchment systems. First, we introduce a new approach to the concept of connectivity to study water and sediment transfers and the associated substances. In this approach water and sediment dynamics are divided in two parts: the system consists of phases and fluxes, each being separately measurable. This approach enables us to: i) better conceptualize our understanding of system dynamics at different timescales, including long timescales; ii) identify the main parameters driving system dynamics, and devise monitoring strategies which capture them; and, iii) build models with a holistic approach to simulate system dynamics without excessive complexity. Secondly, we discuss the role of system boundaries in designing measurement schemes and models. Natural systems have boundaries within which sediment connectivity varies between phases; in (semi-)arid regions these boundaries can be far apart in time due to extreme events. External disturbances (eg. climate change, changed land management) can change these boundaries. It is therefore important to consider the system state as a whole, including its boundaries and internal dynamics, when designing and implementing comprehensive monitoring and modelling approaches. Connectivity is a useful tool concept for scientists that must be expanded to stakeholder and policymakers.</p

    Coupling hysteresis analysis with sediment and hydrological connectivity in three agricultural catchments in Navarre, Spain

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    Purpose: Rain storm events mobilise large proportions of fine sediments in catchment systems. Sediments from agricultural catchments are often adsorbed by nutrients, heavy metals and other (in)organic pollutants that may impact downstream environments. To mitigate erosion, sediment transport and associated pollutant transport, it is crucial to know the origin of the sediment that is found in the drainage system, and therefore, it is important to understand catchment sediment dynamics throughout the continuity of runoff events. Materials and methods: To assess the impact of the state of a catchment on the transport of fine suspended sediment to catchment outlets, an algorithm has been developed which classifies rain storm events into simple (clockwise, counter-clockwise) and compound (figure-of-eight; complex) events. This algorithm is the first tool that uses all available discharge and suspended sediment data and analyses these data automatically. A total of 797 runoff events from three experimental watersheds in Navarre (Spain) were analysed with the help of long-term, high-resolution discharge and sediment data that was collected between 2000 and 2014. Results and discussion: Morphological complexity and in-stream vegetation structures acted as disconnecting landscape features which caused storage of sediment along the transport cascade. The occurrence of sediment storage along transport paths was therefore responsible for clockwise hysteresis due to the availability of in-stream sediment which could cause the “first flush” affect. Conversely, the catchment with steeper channel gradients and a lower stream density showed much more counter-clockwise hysteresis due to better downstream and lateral surface hydrological connectivity. In this research, hydrological connectivity is defined as the actual and potential transfer paths in a catchment. The classification of event SSC-Q hysteresis provided a seasonal benchmark value to which catchment managers can compare runoff events in order to understand the origin and locations of suspended sediment in the catchment. Conclusions: A new algorithm uses all available discharge and suspended sediment data to assess catchment sediment dynamics. From these analyses, the catchment connectivity can be assessed which is useful to develop catchment land management.</p

    Modelling Discharge and Sediment Yield at Catchment Scale Using Connectivity Components

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    <p>Knowledge about connectivity and what affects it, through space and time, is needed for taking appropriate action at the right place and/or time by stakeholders. Various conceptual frameworks for hydrological and sediment connectivity have been developed in recent years. For most of these frameworks, the objective was to conceptualise connectivity, not necessarily to infer it from measurements. Studies focussing on measurements of connectivity have so far not been done often. Because of lack of data on connectivity, few real-world data have been used in recent connectivity modelling studies. The aim of this study was to demonstrate that existing data can be used to assess governing factors of connectivity, and how these change over time. Data from three catchments in Navarre, Northern Spain, were used to assess factors that influence hydrologic and sediment connectivity. These factors were used as components in a linear model for discharge and suspended-sediment yield. Three components of connectivity were distinguished: topographical, biological and soil. Changes in the topographical component for the studied periods were considered relatively small, and, therefore, kept constant. Changes in the biological component were determined using the Normalised Difference Vegetation Index. Changes in the soil component were assessed using an Antecedent Precipitation Index. Nash-Sutcliffe model efficiency coefficients were between 0·49 through 0·62 for the discharge models and between 0·23 through 0·3 for the sediment-yield models. We recommend applying the model at smaller spatial scales than catchment scale to minimise the lumping of spatial variability in the components.</p

    What do models tell us about water and sediment connectivity?

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    Connectivity has been embraced by the geosciences community as a useful concept to understand and describe hydrological functioning and sediment movement through catchments. Mathematical modelling has been used for decades to quantify and predict erosion and transport of sediments, e.g. in scenarios of land use change or conservation measures. Being intrigued by both models and the connectivity concept, as a group of modellers we aimed at investigating what different models could tell us about connectivity. Therefore, we evaluated the response of contrasted spatially-distributed models to landscape connectivity features and explained the differences based on different model structures. A total of 53 scenarios were built with varying field sizes and orientations, as well as the implementation of soil conservation measures. These scenarios were simulated, for two rainfall intensities, with five event- and process-based water and soil erosion models – EROSION3D, FullSWOF_2D, LandSoil, OpenLISEM and Watersed. Results showed that rainfall amount plays the most important role in determining relative export and connected area of runoff and sediment in all models, indicating that functional aspects of connectivity were more important than structural connectivity. As for the role of structural landscape elements, there was no overall agreement between models regarding the effects of field sizes, crop allocation pattern, and conservation practices; agreement was also low on the spatial patterns of connectivity. This overall disagreement between models was unexpected. The results of this exercise suggest that the correct parameterization of runoff and sediment production and of routing patterns may be an important issue. Thus, incorporating connectivity functions based on routing would help modelling forward. Our results also suggest that structural connectivity indices may not suffice to represent connectivity in this type of catchment (relatively simple and monotonous land cover), and functional connectivity indices should be applied

    What do models tell us about water and sediment connectivity ?

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    Recently, connectivity has emerged as a promising concept to understand the transfer of water and sediment in a catchment. Both structural connectivity – i.e. representing the connectivity of system properties such as the (micro)topography, and functional connectivity – i.e. representing connections that may change and evolve over time such as soil moisture, are important to consider.[br/] As discussed by Nunes et al. (in press), good models should be effectively connected models, i.e. represent properly the fluxes of water and sediment both within and between its fundamental spatial units. However, there is no clear framework to guide how this should be assessed. In this study we analysed changes in landscape connectivity using six well-known erosion models: Erosion3D, Fullswof, Landsoil, LISEM, MAHLERAN and Watersed. Our objective was to determine if, and how simulated connectivity is linked with model structure. The models all simulated the same, semi-virtual 124 ha watershed, loosely based on the Giser experimental agricultural watershed in Belgium. A total of 53 connectivity scenarios with differences in spatial complexity and presence of connectivity features were simulated using two rainfall events (10- and 50-year return periods).[br/] The spatial complexity was varied in terms of field size (5, 10 or 20 ha) and five different land-use patterns with tillage orientation following the axis of the fields. Finally, for mid-sized fields (10 ha) and for each of the five land-use patterns, the following connectivity features were tested: conservation tillage (i.e. orientation of fields along the contour), and presence of grass strips and a grassed waterway.[br/] We will discuss the impacts of these scenarios on overland flow and sediment connectivity for each model, in relation with its structure. In the future, these results will be used to investigate the possibility to derive more generic results using model ensembles
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