scholarly journals A watershed classification approach that looks beyond hydrology: application to a semi-arid, agricultural region in Canada

2019 ◽  
Vol 23 (9) ◽  
pp. 3945-3967 ◽  
Author(s):  
Jared D. Wolfe ◽  
Kevin R. Shook ◽  
Chris Spence ◽  
Colin J. Whitfield

Abstract. Classification and clustering approaches provide a means to group watersheds according to similar attributes, functions, or behaviours, and can aid in managing natural resources. Although they are widely used, approaches based on hydrological response parameters restrict analyses to regions where well-developed hydrological records exist, and overlook factors contributing to other management concerns, including biogeochemistry and ecology. In the Canadian Prairie, hydrometric gauging is sparse and often seasonal. Moreover, large areas are endorheic and the landscape is highly modified by human activity, complicating classification based solely on hydrological parameters. We compiled climate, geological, topographical, and land-cover data from the Prairie and conducted a classification of watersheds using a hierarchical clustering of principal components. Seven classes were identified based on the clustering of watersheds, including those distinguishing southern Manitoba, the pothole region, river valleys, and grasslands. Important defining variables were climate, elevation, surficial geology, wetland distribution, and land cover. In particular, three classes occur almost exclusively within regions that tend not to contribute to major river systems, and collectively encompass the majority of the study area. The gross difference in key characteristics across the classes suggests that future water management and climate change may carry with them heterogeneous sets of implications for water security across the Prairie. This emphasizes the importance of developing management strategies that target sub-regions expected to behave coherently as current human-induced changes to the landscape will affect how watersheds react to change. The study provides the first classification of watersheds within the Prairie based on climatic and biophysical attributes, with the framework used being applicable to other regions where hydrometric data are sparse. Our findings provide a foundation for addressing questions related to hydrological, biogeochemical, and ecological behaviours at a regional level, enhancing the capacity to address issues of water security.

2019 ◽  
Author(s):  
Jared D. Wolfe ◽  
Kevin R. Shook ◽  
Chris Spence ◽  
Colin J. Whitfield

Abstract. Classification and clustering approaches provide a means to group watersheds according to similar attributes, functions, or behaviours, and can aid in managing natural resources within these regions. While widely used, approaches based on hydrological response parameters restrict analyses to regions where well-developed hydrological records exist, and overlook factors contributing to other management concerns, including biogeochemistry and ecology. In the Canadian Prairie, hydrometric gauging is sparse and often seasonal, large areas are endorheic and the landscape is highly modified by human activity, complicating classification based solely on hydrological parameters. We compiled climate, geological, topographical, and land cover data from the Prairie and conducted a classification of watersheds using a hierarchical clustering of principal components. Seven classes were identified based on the clustering of watersheds, including those distinguishing southern Manitoba, the pothole region, river valleys, and grasslands. Important defining variables were climate, elevation, surficial geology, wetland distribution, and land cover. In particular, three classes occur almost exclusively within regions that tend not to contribute to major river systems, and collectively encompass the majority of the study area. The gross difference in key characteristics across the classes suggests that future water management and climate change may carry with them heterogeneous sets of implications for water security across the Prairies. This emphasizes the importance of developing management strategies that target sub-regions expected to behave coherently as current human-induced changes to the landscape will affect how watersheds react to change. This study provides the first classification of watersheds within the Prairie based on climatic and biophysical attributes, and our findings provide a foundation for addressing questions related to hydrological, biogeochemical, and ecological behaviours at a regional level.


2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Suci Arisa Purba ◽  
Bejo Slamet ◽  
Abdul Rauf

Land conversion activities cause changes in the area of vegetation and carbon storage in the air. These changes can lead to emissions (reduction of carbon stocks) or sequestration (addition of carbon stocks). This study aims to calculate stored carbon in the Padang watershed in 2009 and 2019 and to determine the dynamics of emissions and carbon sequestration due to land conversion in the Padang watershed, North Sumatra Province from 2009 to 2019. The method used in this research is spatial data processing using software Arc Gis. Processing, interpretation and classification of land cover are obtained from land cover data for 2009 and 2019 from the Ministry of Environment and Forestry. Furthermore, the analysis of emissions and carbon sequestration in the Padang watershed was carried out using the REDD Abacus SP software. The results showed that the total carbon stored in 2009 was 5,168,464.09 tons. Meanwhile, the total carbon stored in 2019 was 5,150,784.81 tons. This means that there is a decrease or carbon emission during the 2009-2019 period of 17,679.28 tons. The total net emissions and sequestration that occurred in the Padang watershed due to changes in land use from 2009 - 2019 were 22,851,751.43 tonnes CO2-eq / year and  3,100,199.00 tonnes CO2-eq / year, respectively. Efforts to reduce emissions include planting and developing forests and community-based forest management.


Author(s):  
Djan'na H. Koubodana ◽  
Bernd Diekkrüger ◽  
Kristian Näschen ◽  
Julien Adounkpe ◽  
Kossi Atchonouglo

The results reveal CILSS as the most accurate data set with a Kappa coefficient of 68% and an overall accuracy of 83%. CILSS data shows a decrease of savanna and forest whereas an increase of cropland over the period 1975 to 2013. The increase of cropland area of 30.97% from 1975 to 2013 can be related to the increase in population and their food demand, while the losses of forest area and the decrease of savanna are further amplified by using wood as energy sources and the lack of forest management. The three datasets were used to simulate future LULC changes using the Terrset Land Change Modeler. The validation of the model using CILSS data for 2013 showed a quality of 50.94%, it is only 40.04% for ESA and 20.13% for Globeland30. CILSS data was utilized to simulate the LULC distribution for the years 2020 and 2027 because of its satisfactory performances. The results show that a high spatial resolution is not a guarantee of high quality. The results of this study can be used for impact studies and to develop management strategies for mitigating negative effects of land use and land cover change.


2020 ◽  
Vol 4 (1) ◽  
pp. 62-76
Author(s):  
Andi Rasti Serastiwati ◽  
St. Subaedah ◽  
Netty Syam

The Pamukkulu watershed is one of the Jeneberang-Kelara Sub-watersheds, which is one of the 108 Priority Watersheds in Indonesia determined based on the 2017 Ministry of Environment and Forestry Performance Report which is prioritized as a location for Forest and Land Rehabilitation activities. The purpose of this study was to analyze changes in land cover in the Pamukkulu watershed in 2008 and 2017, the effect of land cover changes in the Pamukkulu watershed on fluctuations in major river flows and analyze the health level of the Pamukkulu watershed based on analysis of major river discharge and changes in land cover. The study was conducted in February to April 2018. Data collection was carried out by taking secondary data in the form of land cover data in 2008 and 2017, climate data and Pamukkulu River discharge data. The results showed that based on the results of the analysis of the Land Cover Index (IPL), the condition of Pamukkulu watershed land cover in 2008 was at 19.38% and 16.96% in 2017 so that it was categorized as bad. The results of the hydrological analysis (river water discharge) on the River Regime Coefficient in 2008 were 125 and in 2017 amounted to 119.6 so that the KRS is also categorized as bad. While the results of the analysis of the Variant Coefficient (CV) in 2008 amounted to 144.90% and in 2017 amounted to 87.5% then the CV was categorized as poor. Based on the analysis of the value of the Land Cover Index, River Regime Coefficient and River Regime Coefficient in the Pamukkulu Watershed in 2008 and 2017 which are in the poor category, the performance of the Pamukkulu Watershed is in the poor category.


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