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Water Loss Due to Increasing Planted Vegetation over the Badain Jaran Desert, China

Zhang, Xunhe, Wang, Nai'ang, Xie, Zunyi, Ma, Xuanlong, and Huete, Alfredo, 2018. Water Loss Due to Increasing Planted Vegetation over the Badain Jaran Desert, China. Remote Sensing, 10(1):134, doi:10.3390/rs10010134.

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@ARTICLE{2018RemS...10..134Z,
       author = {{Zhang}, Xunhe and {Wang}, Nai'ang and {Xie}, Zunyi and {Ma}, Xuanlong and {Huete}, Alfredo},
        title = "{Water Loss Due to Increasing Planted Vegetation over the Badain Jaran Desert, China}",
      journal = {Remote Sensing},
     keywords = {arid lands, ecohydrology, precipitation, human influences, planted vegetation},
         year = 2018,
        month = jan,
       volume = {10},
       number = {1},
          eid = {134},
        pages = {134},
     abstract = "{Water resources play a vital role in ecosystem stability, human
        survival, and social development in drylands. Human activities,
        such as afforestation and irrigation, have had a large impact on
        the water cycle and vegetation in drylands over recent years.
        The Badain Jaran Desert (BJD) is one of the driest regions in
        China with increasing human activities, yet the connection
        between human management and the ecohydrology of this area
        remains largely unclear. In this study, we firstly investigated
        the ecohydrological dynamics and their relationship across
        different spatial scales over the BJD, using multi-source
        observational data from 2001 to 2014, including: total water
        storage anomaly (TWSA) from Gravity Recovery and Climate
        Experiment (GRACE), normalized difference vegetation index
        (NDVI) from Moderate Resolution Imaging Spectroradiometer
        (MODIS), lake extent from Landsat, and precipitation from in
        situ meteorological stations. We further studied the response of
        the local hydrological conditions to large scale vegetation and
        climatic dynamics, also conducting a change analysis of water
        levels over four selected lakes within the BJD region from 2011.
        To normalize the effect of inter-annual variations of
        precipitation on vegetation, we also employed a relationship
        between annual average NDVI and annual precipitation, or
        modified rain-use efficiency, termed the RUE$_{mo}$. A focus of
        this study is to understand the impact of the increasing planted
        vegetation on local ecohydrological systems over the BJD region.
        Results showed that vegetation increases were largely found to
        be confined to the areas intensely influenced by human
        activities, such as croplands and urban areas. With
        precipitation patterns remaining stable during the study period,
        there was a significant increasing trend in vegetation greenness
        per unit of rainfall, or RUE$_{mo}$ over the BJD, while at the
        same time, total water storage as measured by satellites has
        been continually decreasing since 2003. This suggested that the
        increased trend in vegetation and apparent increase in
        RUE$_{mo}$ can be attributed to the extraction of ground water
        for human-planted irrigated vegetation. In the hinterland of the
        BJD, we identified human-planted vegetation around the lakes
        using MODIS observations and field investigations. Four lake
        basins were chosen to validate the relationship between lake
        levels and planted vegetation. Our results indicated that
        increasing human-planted vegetation significantly increased the
        water loss over the BJD region. This study highlights the value
        of combining observational data from space-borne sensors and
        ground instruments to monitor the ecohydrological dynamics and
        the impact of human activities on water resources and ecosystems
        over the drylands.}",
          doi = {10.3390/rs10010134},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2018RemS...10..134Z},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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