A Species-Specific and spatially-Explicit Model for Estimating Vegetation Water Requirements in Desert Riparian Forest Zones

Yuan, Guohui; Zhu, Xiaoyan; Tang, Xianming; Du, Tao; Yi, Xiaoyun

doi:10.1007/s11269-016-1398-3

Cited by 8 publications

(8 citation statements)

References 34 publications

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“…The narrow riparian forest in the lower reaches of the Tarim River distributes within a range of about 3 km from the river channel. Vegetation coverage is less than 0.2 in most of the riparian forest and it generally decreases with increasing distance from the river channel [14]. The vegetation types in this area mainly consist of Tamarix (Tamarix ramosissima) thicket and Populus (Populus euphratica) woodland.…”

Section: Site Description and Measurementsmentioning

confidence: 94%

“…Accurate estimates of regional scale ET are needed for sustainable water resource management, particularly for arid ecosystems due to competing demands for water resources among agricultural irrigation, public and domestic needs, industrial production, and ecological environments [4,5]. In recent decades, some empirical remotely sensed ET models have been developed [6][7][8][9][10][11][12][13][14] and their potential for regional scale ET estimation in arid ecosystems has been demonstrated [15][16][17][18][19][20][21][22][23][24][25][26]. These models extrapolate ET observed or estimated at the site scale to regional scale based on the empirical relationship constructed at the local site scale, which relates daily ET from the eddy covariance or Bowen ratio flux towers to vegetation indices (VIs) and meteorological data [27][28][29].…”

Section: Introductionmentioning

confidence: 99%

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Effects of Distinguishing Vegetation Types on the Estimates of Remotely Sensed Evapotranspiration in Arid Regions

Wang

Yuan

et al. 2019

Remote Sensing

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Accurate estimates of evapotranspiration (ET) in arid ecosystems are important for sustainable water resource management due to competing water demands between human and ecological environments. Several empirical remotely sensed ET models have been constructed and their potential for regional scale ET estimation in arid ecosystems has been demonstrated. Generally, these models were built using combined measured ET and corresponding remotely sensed and meteorological data from diverse sites. However, there are usually different vegetation types or mixed vegetation types in these sites, and little information is available on the estimation uncertainty of these models induced by combining different vegetation types from diverse sites. In this study, we employed the most popular one of these models and recalibrated it using datasets from two typical vegetation types (shrub Tamarix ramosissima and arbor Populus euphratica) in arid ecosystems of northwestern China. The recalibration was performed in the following two ways: using combined datasets from the two vegetation types, and using a single dataset from specific vegetation type. By comparing the performance of the two methods in ET estimation for Tamarix ramosissima and Populus euphratica, we investigated and compared the accuracy of ET estimation at the site scale and the difference in annual ET estimation at the regional scale. The results showed that the estimation accuracy of daily, monthly, and yearly ET was improved by distinguishing the vegetation types. The method based on the combined vegetation types had a great influence on the estimation accuracy of annual ET, which overestimated annual ET about 9.19% for Tamarix ramosissima and underestimated annual ET about 11.50% for Populus euphratica. Furthermore, substantial difference in annual ET estimation at regional scale was found between the two methods. The higher the vegetation coverage, the greater the difference in annual ET. Our results provide valuable information on evaluating the estimation accuracy of regional scale ET using empirical remotely sensed ET models for arid ecosystems.

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Section: Site Description and Measurementsmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Effects of Distinguishing Vegetation Types on the Estimates of Remotely Sensed Evapotranspiration in Arid Regions

Wang

Yuan

et al. 2019

Remote Sensing

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“…The most obvious one is soil erosion, and soil erosion is also the cause of water pollution. Relevant indicators involve forest coverage [29], green percentage, the proportion of salinization area and the proportion of soil erosion area [30].…”

Section: Ecological Subsystemmentioning

confidence: 99%

Evaluation of Sustainable Use of Water Resources in the Beijing-Tianjin-Hebei Region Based on S-Type Functions and Set Pair Analysis

Men

Liu

2018

Water

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Beijing-Tianjin-Hebei is an area with insufficient per capita water resources. This study evaluates the current status and development trend of sustainable use of water resources in the region, and identifies specific factors influencing sustainable development so as to provide a theoretical basis and data support for the management of water resources in the Beijing-Tianjin-Hebei region. Applying the compound system of social, economic and ecological environment, this study established an evaluation index system. The evaluation index data is obtained through the relevant calculations based on the National Economic and Social Development Announcement, the Water Resources Bulletin and the National Bureau of Statistics data. The index weights are calculated using a combination of rough set and fuzzy theory. The obtained weights were added to the set pair analysis method to acquire evaluation results. Based on the traditional set pair analysis method, this study proposes a new set pair analysis method (Method 4) using S-type functions (Formula (11)) instead of the addition weighted synthesis method (Formula (10)) in the calculation of weighted connections. In order to verify the feasibility of this method, the Spearman correlation coefficient method was used to calculate the correlation coefficient between evaluation results of Method 4 and evaluation results of other traditional methods. In addition, the set pair exponential potential is adopted to determine the impact indicators of the sustainable utilization of water resources in Beijing-Tianjin-Hebei in this study. The results show that in the Beijing-Tianjin-Hebei region, the overall level of sustainable use of water resources has been gradually raised in the past 12 years. The results of the set pair analysis method that cites S-type functions have obtained higher Spearman correlation coefficients than traditional methods. The values of the correlation coefficients are 0.9954, 0.9910, and 0.9928 respectively in Beijing, Tianjin and Hebei. Moreover, according to the results of set pair exponential potential, the indicators in the region are quasi-inverse potential or strong inverse potential, including per capita water resources and the ecological environment water use rate. Thus, a dense population with scarce water resources, and a lack of ecological water are the common problems that Beijing, Tianjin and Hebei have to face.

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“…(10) NSE ranges from -∞ to 1. NSE = 1 indicates that the simulated and measured SOCD are the same; NSE = 0 indicates that the estimate is as accurate as the mean measured SOCD; and an NSE < 0 indicates that the simulated SOCD is not as accurate as the mean measured SOCD (Nash and Sutcliffe 1970;Yuan et al 2016).…”

Section: Statistics and Evaluationmentioning

confidence: 99%

Distribution, stock, and influencing factors of soil organic carbon in an alpine meadow in the hinterland of the Qinghai–Tibetan Plateau

Zhu

Shao

2018

J Earth Syst Sci

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Understanding the spatial distribution, stocks, and influencing factors of soil organic carbon (SOC) is important for understanding the current situation of SOC in alpine meadow ecosystems on the Qinghai-Tibetan Plateau (QTP). We sampled 23 soil profiles to a depth of 50 cm in a 33.5 hm 2 plot in a typical meadow on the central QTP. The distribution, stock and influencing factors of SOC was then analyzed. The mean density of soil carbon content (SOCD) was 2.28 kg m −2 with a range of 5.99 kg m −2. SOCD in the 0-10 cm layer was 3.94 kg m −2 and decreased quadratically with depth. The total stock of SOC to a depth of 50 cm was ca. 2950 t, the 0-10 and 0-30 cm layers accounting for 38 and 80%, respectively. SOCD varied moderately spatially and was distributed more homogeneously in the 0-10 and 40-50 cm layers but was more variable in the middle three layers. SOCD was significantly correlated positively with soil-water content, total porosity, and silt content and negatively with soil pH, bulk density, stone content and sand content. This study provides an important contribution to understanding the role of alpine meadows in the global carbon cycle. It also provides field data for model simulation and the management of alpine meadow ecosystems.

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A Species-Specific and spatially-Explicit Model for Estimating Vegetation Water Requirements in Desert Riparian Forest Zones

Cited by 8 publications

References 34 publications

Effects of Distinguishing Vegetation Types on the Estimates of Remotely Sensed Evapotranspiration in Arid Regions

Effects of Distinguishing Vegetation Types on the Estimates of Remotely Sensed Evapotranspiration in Arid Regions

Evaluation of Sustainable Use of Water Resources in the Beijing-Tianjin-Hebei Region Based on S-Type Functions and Set Pair Analysis

Distribution, stock, and influencing factors of soil organic carbon in an alpine meadow in the hinterland of the Qinghai–Tibetan Plateau

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