Evaluation of Land Use Changes on Stream Discharge by SWAT Model and Remote Sensing in Agro-Forestry Basin in Nghinh Tuong Subwatershed, Northern Vietnam

Abstract. Standard practice of setting up Soil and Water Assessment Tool (SWAT) involves use of a single land use (LU) layer under the assumption that no change takes place in LU condition irrespective of the length of simulation period. This assumption leads to erroneous conclusions about efficacy of management practices in those watersheds where land use changes (LUCs) (e.g. agriculture to urban, forest to agriculture etc.) occur during the simulation period. To overcome this limitation, we have developed a user-friendly, web-based tool named LUU Checker that helps create a composite LU layer by integrating multiple years of LU layers available in watersheds of interest. The results show that the use of composite LU layer for hydrologic response unit (HRU) delineation in 2474-km2 L’Anguile River Watershed in Arkansas was able to capture changed LU at subbasin level by using LU data available in the year 1999 and 2006, respectively. The web-based tool is applicable for large size watersheds and is accessible to multiple users from anywhere in the world. Keywords: Land use, Web-based tool, SWAT, LUU Checker.

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Evaluating and Predicting the Effects of Land Use Changes on Hydrology in Wami River Basin, Tanzania

Hydrology ◽

10.3390/hydrology7010017 ◽

2020 ◽

Vol 7 (1) ◽

pp. 17 ◽

Cited By ~ 2

Author(s):

Sekela Twisa ◽

Shija Kazumba ◽

Mathew Kurian ◽

Manfred F. Buchroithner

Keyword(s):

Land Use ◽

Water Resources ◽

Assessment Tool ◽

Swat Model ◽

Land Use Changes ◽

Management Strategies ◽

River System ◽

Least Squares Regression ◽

Natural Forests ◽

The Impact

Understanding the variation in the hydrological response of a basin associated with land use changes is essential for developing management strategies for water resources. The impact of hydrological changes caused by expected land use changes may be severe for the Wami river system, given its role as a crucial area for water, providing food and livelihoods. The objective of this study is to examine the influence of land use changes on various elements of the hydrological processes of the basin. Hybrid classification, which includes unsupervised and supervised classification techniques, is used to process the images (2000 and 2016), while CA–Markov chain analysis is used to forecast and simulate the 2032 land use state. In the current study, a combined approach—including a Soil and Water Assessment Tool (SWAT) model and Partial Least Squares Regression (PLSR)—is used to explore the influences of individual land use classes on fluctuations in the hydrological components. From the study, it is evident that land use has changed across the basin since 2000 (which is expected to continue in 2032), as well as that the hydrological effects caused by land use changes were observed. It has been found that the major land use changes that affected hydrology components in the basin were expansion of cultivation land, built-up area and grassland, and decline in natural forests and woodland during the study period. These findings provide baseline information for decision-makers and stakeholders concerning land and water resources for better planning and management decisions in the basin resources’ use.

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Research on Land Use Changes in Panjin City Basing on Remote Sensing Data

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/153/6/062050 ◽

2018 ◽

Vol 153 ◽

pp. 062050

Author(s):

Hua Ding ◽

Ru Ren Li ◽

Li Shuang Sun ◽

Xin Wang ◽

Yu Mei Liu

Keyword(s):

Remote Sensing ◽

Land Use ◽

Land Use Changes ◽

Remote Sensing Data ◽

Sensing Data

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Land use/land cover change detection and validation of SWAT model on VISHOW sub-basin using remote sensing and GIS techniques

International Journal of Hydrology Science and Technology ◽

10.1504/ijhst.2021.10037340 ◽

2021 ◽

Vol 1 (1) ◽

pp. 1

Author(s):

Mohammad Asif Naikoo ◽

Manzoor Ahmad Ahanger

Keyword(s):

Remote Sensing ◽

Land Use ◽

Land Cover ◽

Change Detection ◽

Land Cover Change ◽

Swat Model ◽

Remote Sensing And Gis ◽

Land Use Land Cover ◽

Gis Techniques ◽

Land Cover Change Detection

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The Ecology and Management of Wood in World Rivers

The Ecology and Management of Wood in World Rivers ◽

10.47886/9781888569568.ch11 ◽

2003 ◽

Keyword(s):

Land Use ◽

Land Use Changes ◽

Livestock Grazing ◽

Wood Structures ◽

Groundwater Levels ◽

Stream Discharge ◽

Small Streams ◽

World Rivers ◽

Beaver Dams ◽

Stream Systems

<em>Abstract.</em>—Beaver dams alter the hydrology and geomorphology of stream systems and affect habitat for fishes. Beaver dams measurably affect the rates of groundwater recharge and stream discharge, retain enough sediment to cause measurable changes in valley floor morphology, and generally enhance stream habitat quality for many fishes. Historically, beaver dams were numerous in small streams throughout most of the Northern Hemisphere. The cumulative loss of millions of beaver dams has dramatically affected the hydrology and sediment dynamics of stream systems. Assessing the cumulative hydrologic and geomorphic effects of depleting these millions of wood structures from small and medium-sized streams is urgently needed. This is particularly important in semiarid climates, where the widespread removal of beaver dams may have exacerbated effects of other land use changes, such as livestock grazing, to accelerate incision and the subsequent lowering of groundwater levels and drying of streams.

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Parallel Cellular Automata Markov Model for Land Use Change Prediction over MapReduce Framework

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi8100454 ◽

2019 ◽

Vol 8 (10) ◽

pp. 454 ◽

Cited By ~ 3

Author(s):

Junfeng Kang ◽

Lei Fang ◽

Shuang Li ◽

Xiangrong Wang

Keyword(s):

Remote Sensing ◽

Land Use ◽

Cellular Automata ◽

Markov Model ◽

Agricultural Land ◽

Land Use Changes ◽

Remote Sensing Images ◽

Mapreduce Framework ◽

Construction Land ◽

Model Based

The Cellular Automata Markov model combines the cellular automata (CA) model’s ability to simulate the spatial variation of complex systems and the long-term prediction of the Markov model. In this research, we designed a parallel CA-Markov model based on the MapReduce framework. The model was divided into two main parts: A parallel Markov model based on MapReduce (Cloud-Markov), and comprehensive evaluation method of land-use changes based on cellular automata and MapReduce (Cloud-CELUC). Choosing Hangzhou as the study area and using Landsat remote-sensing images from 2006 and 2013 as the experiment data, we conducted three experiments to evaluate the parallel CA-Markov model on the Hadoop environment. Efficiency evaluations were conducted to compare Cloud-Markov and Cloud-CELUC with different numbers of data. The results showed that the accelerated ratios of Cloud-Markov and Cloud-CELUC were 3.43 and 1.86, respectively, compared with their serial algorithms. The validity test of the prediction algorithm was performed using the parallel CA-Markov model to simulate land-use changes in Hangzhou in 2013 and to analyze the relationship between the simulation results and the interpretation results of the remote-sensing images. The Kappa coefficients of construction land, natural-reserve land, and agricultural land were 0.86, 0.68, and 0.66, respectively, which demonstrates the validity of the parallel model. Hangzhou land-use changes in 2020 were predicted and analyzed. The results show that the central area of construction land is rapidly increasing due to a developed transportation system and is mainly transferred from agricultural land.

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