Hydrological process knowledge in catchment modelling – lessons and perspectives from 60 years development

AbstractThe upper Benue River watershed is undergoing remarkable modifications due to man-made and natural phenomena. Hence, an evaluation is required to understand the hydrological process of the watershed for planning and management strategies. This study aimed to assess the morphometric characteristics and prioritize the upper Benue River watershed. The boundary of the watershed and sub-watersheds, as well as stream networks, was extracted from the digital elevation model (DEM) coupled with hydrological and topographic maps. Twenty-eight morphometric parameters under three categories, i.e. linear, areal, and relief aspects were computed and mapped. Findings from the study revealed that the watershed is a seventh stream order system characterized by a dendritic drainage pattern. The result also showed that 4821 streams were extracted with a cumulative length of 30,232.84 km. The hypsometric integral of the watershed was estimated to be 0.22, indicating that it is in the old stage. In the prioritization of the watershed, the morphometric variables were utilized to calculate and classify the compound factor. The result showed that sub-watersheds 12, 16, 18, 24, 26, and 27 were ranked as very high priority for which conservation measures are required to mitigate the risk of flood and erosion. The outcome of this study can be used by decision-makers for sustainable watershed management and planning.

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Hybrid Models Based on Machine Learning and an Increasing Degree of Process Knowledge: Application to Capture Chromatographic Step

Industrial & Engineering Chemistry Research ◽

10.1021/acs.iecr.1c01317 ◽

2021 ◽

Author(s):

Harini Narayanan ◽

Martin Luna ◽

Michael Sokolov ◽

Paolo Arosio ◽

Alessandro Butté ◽

...

Keyword(s):

Machine Learning ◽

Hybrid Models ◽

Process Knowledge ◽

Knowledge Application

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Assimilation of D-InSAR snow depth data by an ensemble Kalman filter

Arabian Journal of Geosciences ◽

10.1007/s12517-021-06699-y ◽

2021 ◽

Vol 14 (6) ◽

Author(s):

Jinming Yang ◽

Chengzhi Li

Keyword(s):

Remote Sensing ◽

Kalman Filter ◽

Water Resource ◽

Ensemble Kalman Filter ◽

Snow Depth ◽

Resource Assessment ◽

Measured Data ◽

Hydrological Process ◽

Depth Data ◽

Water Resource Assessment

AbstractSnow depth mirrors regional climate change and is a vital parameter for medium- and long-term numerical climate prediction, numerical simulation of land-surface hydrological process, and water resource assessment. However, the quality of the available snow depth products retrieved from remote sensing is inevitably affected by cloud and mountain shadow, and the spatiotemporal resolution of the snow depth data cannot meet the need of hydrological research and decision-making assistance. Therefore, a method to enhance the accuracy of snow depth data is urgently required. In the present study, three kinds of snow depth data which included the D-InSAR data retrieved from the remote sensing images of Sentinel-1 synthetic aperture radar, the automatically measured data using ultrasonic snow depth detectors, and the manually measured data were assimilated based on ensemble Kalman filter. The assimilated snow depth data were spatiotemporally consecutive and integrated. Under the constraint of the measured data, the accuracy of the assimilated snow depth data was higher and met the need of subsequent research. The development of ultrasonic snow depth detector and the application of D-InSAR technology in snow depth inversion had greatly alleviated the insufficiency of snow depth data in types and quantity. At the same time, the assimilation of multi-source snow depth data by ensemble Kalman filter also provides high-precision data to support remote sensing hydrological research, water resource assessment, and snow disaster prevention and control program.

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Impact of Land Use Change on Water Conservation: A Case Study of Zhangjiakou in Yongding River

Sustainability ◽

10.3390/su13010022 ◽

2020 ◽

Vol 13 (1) ◽

pp. 22

Author(s):

Tianshi Pan ◽

Lijun Zuo ◽

Zengxiang Zhang ◽

Xiaoli Zhao ◽

Feifei Sun ◽

...

Keyword(s):

Land Use ◽

Sustainable Development ◽

Water Conservation ◽

Land Use Changes ◽

Water Yield ◽

Special Focus ◽

Hydrological Process ◽

Significant Difference ◽

The Impact ◽

Yongding River

The implementation of ecological projects can largely change regional land use patterns, in turn altering the local hydrological process. Articulating these changes and their effects on ecosystem services, such as water conservation, is critical to understanding the impacts of land use activities and in directing future land planning toward regional sustainable development. Taking Zhangjiakou City of the Yongding River as the study area—a region with implementation of various ecological projects—the impact of land use changes on various hydrological components and water conservation capacity from 2000 to 2015 was simulated based on a soil and water assessment tool model (SWAT). An empirical regression model based on partial least squares was established to explore the contribution of different land use changes on water conservation. With special focus on the forest having the most complex effects on the hydrological process, the impacts of forest type and age on the water conservation capacity are discussed on different scales. Results show that between 2000 and 2015, the area of forest, grassland and cultivated land decreased by 0.05%, 0.98% and 1.64%, respectively, which reduces the regional evapotranspiration (0.48%) and soil water content (0.72%). The increase in settlement area (42.23%) is the main reason for the increase in water yield (14.52%). Most land use covered by vegetation has strong water conservation capacity, and the water conservation capacity of the forest is particularly outstanding. Farmland and settlements tend to have a negative effect on water conservation. The water conservation capacity of forest at all scales decreased significantly with the growth of forest (p < 0.05), while the water conservation capacity of different tree species had no significant difference. For the study area, increasing the forest area will be an effective way to improve the water conservation function, planting evergreen conifers can rapidly improve the regional water conservation capacity, while planting deciduous conifers is of great benefit to long-term sustainable development.

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