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- Upstream-downstream linkages of hydrological processes in the Himalayan region
- Upstream-downstream linkages of hydrological processes in the Himalayan region
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- Global hydro-environmental sub-basin and river reach characteristics at high spatial resolution
Not a MyNAP member yet? Register for a free account to start saving and receiving special member only perks. Given the great variety of sizes and types of watersheds and the economic and political landscapes, what is the best organizational structure for implementing successful watershed management? Organizational structure can be either a barrier or an avenue to success.
Upstream-downstream linkages of hydrological processes in the Himalayan region
Version 1. HydroATLAS derives the hydro-environmental characteristics by aggregating and reformatting original data from well-established global digital maps, and by accumulating them along the drainage network from headwaters to ocean outlets. The standardized format of HydroATLAS ensures easy applicability while the inherent topological information supports basic network functionality such as identifying up- and downstream connections.
Freshwater systems are under multiple threats 1 which can be detrimental to their biodiversity and the ecosystem services they provide 2 , 3 , 4 , 5. Researchers, governments, water managers, policy makers, and conservation organizations around the world face the challenge of developing innovative strategies to alleviate the pressures on freshwater resources 6 , and many applied approaches and solutions require large amounts of data 7. Furthermore, integrated freshwater resource assessments are often carried out at large scales, from regional to global, and thus suffer from incompatible or differing data conventions among the involved spatial units, such as multiple countries or river basins.
In these cases, global data can provide consistent and homogeneous coverage required for seamless analyses. Global data can also provide baseline information in remote areas where little monitoring is available yet stakeholders need to address urgent issues in a timely manner.
Despite these advancements, users interested in additional watershed or river characteristics, such as topographic, climatic or land cover information, are required to derive or summarize these data independently from alternative sources.
This typically involves repetitive geospatial procedures that assign the attribute values of auxiliary datasets to the desired sub-basin or river units, often necessitating the development of new algorithms or software customizations within Geographic Information Systems GIS. Besides the time-consuming processing, the individual, non-standardized solutions create results that are difficult to compare.
To offer consistent baseline data without the need of repetition, efforts have been made in the past to create predefined compilations of hydro-environmental watershed and river characteristics. At even larger scales, Domisch et al.
They derived more than individual attributes of climatic, stream-topographic, land cover, geological, and soil characteristics and applied upstream accumulation techniques to assess the watershed contributions to each river pixel.
Although their river network is based on the HydroSHEDS database 9 , they applied local modifications which render the results unique to their own flow directional grid. Also, they do not provide a sub-basin perspective, and the spatial extent is limited to below 60 degrees northern latitude. HydroATLAS provides a single, comprehensive, consistently organized and fully-global data compendium that gathers and presents a wide range of hydro-environmentally relevant characteristics at both sub-basin and river reach scales at high spatial resolution.
The first database, BasinATLAS, derives sub-basin characteristics for hierarchically nested watersheds at twelve spatial scales. The second database, RiverATLAS, provides similar attributes yet derived for river and stream reaches rather than sub-basins. The geospatial units for both databases, i. HydroATLAS is envisioned to be expanded and updated in the future with new attribute data as more global information becomes available, or by customizing it for individual regional applications.
Other key applications in ecological sciences include species distribution modelling and conservation planning 21 , 22 , 23 , We also imagine advances in macro-ecology, such as exploring life history traits or environmental drivers, as other global databases containing functional ecological parameters become available that can be combined with HydroATLAS.
The corresponding spatial relationships, once established, are expected to further amplify the utility and versatility of the HydroATLAS database. HydroSHEDS provides hydrographic baseline information in a consistent and comprehensive format to support regional and global watershed analyses, hydrological modeling, and freshwater conservation planning. It is currently considered the leading global product in terms of quality and resolution 11 , HydroSHEDS offers a suite of geo-referenced datasets at multiple scales as seamless global coverages, including both raster and vector formats.
The core data layers are a hydrologically conditioned digital elevation model and a corresponding drainage direction map from which auxiliary layers can be derived, including flow accumulations, flow distances, river orders, watershed boundaries, and stream networks. Based on the HydroSHEDS drainage direction map at 15 arc-second resolution, watershed boundaries were delineated and subdivided following the topological concept of the Pfafstetter coding system 30 which provides a methodology for the breakdown of sub-basins into increasingly smaller sizes in a hierarchical and systematic manner Fig.
Following this coding scheme, twelve nested levels of sub-basins were generated globally, each depicting consistently sized sub-basin polygons at scales ranging from millions level 1 to tens of square kilometers level At the first level top panel , the original watershed is divided into nine sub-basins i.
At the next level bottom panel , each sub-basin is again divided into nine sub-basins. This process is iterated for each subsequent level of subdivisions. Connectivity between sub-basins is defined based on the underpinning drainage direction map of HydroSHEDS which identifies the ID of the next downstream neighbor of every sub-basin except for those sub-basins ending at the ocean or at inland sinks. The HydroBASINS dataset does not contain any hydro-environmental attribute information other than what can be derived directly from the polygon geometry and topology, including the polygon area and the total upstream contributing watershed area.
For this network, rivers have been defined to start at all pixels where the accumulated upstream watershed area exceeds 10 km 2 , or where the long-term average natural discharge exceeds 0. Streams smaller than these thresholds were not extracted as they are increasingly unreliable in their spatial representation due to the uncertainties in the underpinning global geometric and hydrologic data.
All identified river pixels at 15 arc-second resolution were then converted into vector format to produce a line network consisting of individual river reaches Fig.
Connectivity between reaches is defined based on the underpinning drainage direction map of HydroSHEDS which identifies the ID of the next downstream neighbor to every reach except for those reaches ending at the ocean or at inland sinks. The HydroRIVERS dataset does not contain any hydro-environmental attribute information other than what can be derived directly from the line geometry and topology, including the length of the river reach; the distance from the upstream headwater source and from the final downstream pour point; and the upstream contributing watershed area.
Raster or vector input data for all hydro-environmental characteristics were acquired either from free and publicly available sources, or from collaborators who provided their data for this project. All data sources were assessed regarding their suitability for this project using the following selection criteria:. It should be noted, however, that the selection of an attribute dataset does not imply any kind of endorsement or warranty of its quality or superiority over other data.
Before extracting their attribute information into HydroATLAS format, the original attribute datasets were preprocessed into a standardized grid format with the same geometric specifications as the HydroSHEDS 15 arc-second resolution grids. The goal of this step was to ensure full spatial congruency between preprocessed attribute data and HydroSHEDS to avoid misalignments in the subsequent conversion processes. If an original dataset was in grid format with a cell size other than 15 arc-seconds, it was either aggregated or disaggregated, depending on its native resolution.
For disaggregation, original attribute values were preserved, i. For certain high resolution categorical datasets, a new attribute was calculated representing the percent coverage of a class within each 15 arc-second pixel e.
If original datasets were in vector format, i. If the original vector maps offered sufficient precision, the data were first converted to a grid of higher resolution, e. This conversion method was applied, for example, to the high-precision data of lakes, reservoirs, and glaciers. Due to different interpretations of the global coastline, the land extents of the input attribute grids typically exhibited slight mismatches in comparison to the spatial extent of the HydroSHEDS land mask, both over- and undershooting it i.
To prevent the creation of void attributes for coastal sub-basins, all resulting input grids were expanded or clipped to the HydroSHEDS land mask, which represents all global landmasses except Antarctica. Some exceptions were made for particular attributes such as for elevation and population for which all pixels with missing values along the coast were substituted with zero instead of extending the value of the nearest neighbor. In contrast, if pixels in the original data were located within ocean areas of HydroSHEDS, they were removed from the final grid, i.
A particular exception was made for population data as large numbers of people inhabit coastal areas and waterfront cities, thus the removal of pixels beyond the HydroSHEDS coastline would lead to a significant underestimation of population totals in the output grids. To avoid this loss, the population counts in pixels outside of the HydroSHEDS land mask were added to the nearest coastal pixel on land. Besides mismatches along the coastlines, some original attribute datasets contained voids within the land mask of HydroSHEDS, or data were absent for small remote islands.
Different aggregation methods and statistics were applied as described below additional specifications for individual attributes are provided in the Technical Documentation. The zonal statistics tool produces spatial summary statistics, including mean, majority, sum, maximum, and minimum, by performing calculations on cells from a value grid i. These zones are defined by cells with the same value i. For the zonal statistics calculations, the sub-basin polygons and river reach line segments were applied in the native grid format of HydroSHEDS rather than in their converted vector representation to ensure proper alignment with the resolution and extent of the preprocessed attribute grids.
After zonal statistics were derived, the resulting statistics were appended to the vectorized sub-basin polygons and river reach line segments via their unique identifier codes IDs. Various zoning options were applied to derive specific attribute statistics in different or multiple ways, depending on the nature of the attribute variable. For sub-basins, two alternative zones exist: i all cells that describe the entire sub-basin Fig.
Panel a shows the flow directions of every pixel from which the river network red lines and sub-basins are derived. Other panels show the spatial zones of: b sub-basins; c sub-basin pour points; d reach catchments; e river reaches; and f reach pour points.
Individual zones are identified by different solid colors, while light background shades are for orientation only. For example, some attributes are well suited to be calculated as the average or sum within the entire sub-basin or reach catchment Fig. Yet for other attributes using the entire sub-basin or reach catchment as the zone does not deliver a meaningful metric.
For instance, a sub-basin typically contains pixels that span a wide range of possible discharge values, ranging from very small headwater streams originating at the edge of the sub-basin, to mainstem rivers traversing through the sub-basin with discharges that are orders of magnitude larger.
Given this extreme heterogeneity, it is more meaningful to use a single, clearly defined pixel within the sub-basin as a representative location i. Hence, in BasinATLAS the representative discharge of a sub-basin is defined as the discharge that leaves the sub-basin at the pour point location Fig. The additional zone of the river reach itself Fig.
For instance, the percent forest cover within a sub-basin may represent a key hydrologic characteristic for the local conditions of that sub-basin, yet for a river reach, which is influenced by the larger drainage network upstream, the percent forest cover in the entire upstream watershed may be a better descriptor of its hydrologic condition.
Due to the hydrologic connectivity of the river network and associated sub-basins, however, many characteristics are better suited to an upstream perspective where the entire contributing watershed is taken into account.
For example, if an application wanted to model the water temperature of a river reach, this would depend both on the conditions at the reach itself e. The latter conditions can be described with upstream statistics, such as the average air temperature or the total glacier, snow, or forest extent in the entire upstream watershed that contributes to the river reach.
In fact, it is the very nature of fluvial systems that they depend both on local conditions, defined by the immediate neighborhood that the river runs through, and by the conditions of the entire contributing upstream watershed which can include parts that are far away. To allow for the duality of both local and upstream perspectives, HydroATLAS offers pre-calculated upstream statistics for many of its characteristics. All upstream watershed statistics in HydroATLAS are extracted at the pour point location of sub-basins and river reaches.
The upstream perspective is particularly useful and fitting for river systems, as presented by the line segments of RiverATLAS. All parts within a river reach are affected by the larger upstream watershed as it drains towards and through it. But second, there are also pixels that represent very different locations within the sub-basin, including small tributaries or land next to the main river.
These different locations are not affected by the larger upstream watershed of the sub-basin but only by their own individual contributing watersheds. This spatial complexity mandates a careful interpretation of the suitability of upstream attributes before using them in intended applications.
In order to produce upstream averages, a correction was performed to account for the latitudinal distortion in pixel sizes due to the applied geographic projection: each pixel value was first multiplied by its individual pixel area and the accumulated sum of multiplied values was then divided by the accumulated sum of pixel areas to derive an area weighted average for the watershed.
In a similar way, the upstream extent of an attribute in percent coverage , such as percent forest cover, was calculated by dividing the total area of the attribute in the upstream watershed by the total watershed area, using latitude-corrected pixel areas.
Future versions of HydroATLAS are anticipated to include attributes with an upstream perspective where either distance weighting or runoff weighting will be applied. In distance weighting, every pixel is multiplied by a weight depending on their upstream distance, allowing for placing more emphasis on near versus far influences. In runoff weighting, every pixel is multiplied by a weight representing the local runoff amount, allowing for reducing or eliminating the influence of upstream areas that do not contribute much or any water to the downstream flows.
All hydro-environmental attributes available in version 1. Most attributes with a time component i. In particular, the Technical Documentation includes a browsable catalog and overview maps for all available variables.
Upstream-downstream linkages of hydrological processes in the Himalayan region
This section reviews, assesses, and summarizes the potential strategies investigated in past scientific and technical research for positively affecting the watersheds and tributaries draining to Puget Sound. The review and assessment covers strategies for both protecting resources that remain and recovering or improving resources that have been impaired. Concentration is on presenting the level of effectiveness of the candidate strategies, as established by the research, and the relative certainty associated with the reported effectiveness. Of particular interest is identifying strategies that reduce multiple threats to the Puget Sound ecosystem. This section covers the scientific and technical aspects of potential restoration and protection strategies for application in watersheds, whether they drain to tributary fresh waters or to the estuarine and marine waters of Puget Sound.
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Understanding the upstream-downstream linkages in hydrological processes is essential for water resources planning in river basins. Although there are many studies of individual aspects of these processes in the Himalayan region, studies along the length of the basins are limited. This study summarizes the present state of knowledge about linkages in hydrological processes between upstream and downstream areas of river basins in the Himalayan region based on a literature review. The paper studies the linkages between the changes in the physical environment of upstream areas land use, snow storage, and soil erosion and of climate change on the downstream water availability, flood and dry season flow, and erosion and sedimentation. It is argued that these linkages are complex due to the extreme altitudinal range associated with the young and fragile geology, extreme seasonal and spatial variation in rainfall, and diversity of anthropogenic processes. Based on the findings, the paper concludes that integrated systems analysis is required to understand the holistic complexity of upstream-downstream linkages of hydrological processes in the river basin context.
on incorrect understanding of the hydrological cycle in forest ecosystems. The good reasons for reforesting watersheds (e.g. reducing soil loss, keeping sediments ways they support human well-being through ecosystem services, and consequently total amount of water in streams flowing from the catchment area.
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Land use and land cover LULC change is one of the key driving elements responsible for altering the hydrology of a watershed. In this study, we investigated the spatio-temporal LULC changes between and and their impacts on the water balance of the Jhelum River Basin. The model was calibrated and validated with discharge data between and and then simulated with different land use. The increase was observed in forest, settlement and water areas during the study period. At the catchment scale, we found that afforestation has reduced the WY and surface runoff, while enhanced the ET.
The global burden of diarrhea is a leading cause of morbidity and mortality worldwide. In montane areas of South-East Asia such as northern Laos, recent changes in land use have induced increased runoff, soil erosion and in-stream suspended sediment loads, and potential pathogen dissemination. To our knowledge, few studies have related diarrhea incidences to catchment scale hydrological factors such as river discharge, and loads of suspended sediment and of Fecal Indicator Bacteria FIB such as Escherichia coli , together with sociological factors such as hygiene practices. We hypothesized that climate factors combined with human behavior control diarrhea incidence, either because higher rainfall, leading to higher stream discharges, suspended sediment loads and FIB counts, are associated with higher numbers of reported diarrhea cases during the rainy season, or because water shortage leads to the use of less safe water sources during the dry season. Using E.
Global hydro-environmental sub-basin and river reach characteristics at high spatial resolution
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Mapping the sources and sinks of precipitation and soils while adding to catchment water budgets and downstream and forest managers have always needed to consider hydrology management, land protection, reforestation sustainably manage their forest and water resources in ways that benefit both themselves.
1. Section Scope
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