资源与生态学报 ›› 2022, Vol. 13 ›› Issue (1): 113-119.DOI: 10.5814/j.issn.1674-764x.2022.01.013
许中旗1,†,*(), 张乃暄1,†(
), 王冉1, 杨鑫1, 孙守家2, 闫腾飞3
收稿日期:
2021-07-21
接受日期:
2021-10-18
出版日期:
2022-01-30
发布日期:
2022-01-08
通讯作者:
许中旗
XU Zhongqi1,†,*(), ZHANG Naixuan1,†(
), WANG Ran1, YANG Xin1, SUN Shoujia2, YAN Tengfei3
Received:
2021-07-21
Accepted:
2021-10-18
Online:
2022-01-30
Published:
2022-01-08
Contact:
XU Zhongqi
About author:
XU Zhongqi, E-mail: xzq7110@163.com; ZHANG Naixuan, E-mail: 575221370@qq.com.† means that they have the same contribution to this paper.
Supported by:
摘要:
为了了解冀西北坝上地区不同植被的生态需水量,为该地区的植被建设提供科学依据,采用实际观测数据及Irmak-Allen公式对张北坝上地区乔木林、灌丛和草地的生态需水量、生态缺水量进行了研究。研究结果表明,冀西北坝上地区3种植被生长季的实际蒸散量由高到低为乔木林、灌丛和草地,分别为401.81 mm、358.78 mm和346.02 mm。生长季乔木林、灌丛和草地的最小生态需水量分别为243.96 mm、218.35 mm和211.36 mm,适宜生态需水量分别为472.99 mm、423.34 mm和409.77 mm,适宜生态缺水量分别为198.56 mm、148.91 mm和135.34 mm。植被生态缺水量具有明显的季节性,5、6月份缺水量最大,7-10月份较低,甚至还有盈余,5、6月份进行人为补水将有助于缓解植被的干旱胁迫。冀西北坝上地区的降雨量能够满足乔木林最小生态需水量的要求,但与适宜生态需水量差距较大,不足以使乔木林维持良好的生长状态,这是导致坝上地区杨树防护林退化的主要原因。
许中旗, 张乃暄, 王冉, 杨鑫, 孙守家, 闫腾飞. 冀西北坝上地区不同植被类型的生态需水量[J]. 资源与生态学报, 2022, 13(1): 113-119.
XU Zhongqi, ZHANG Naixuan, WANG Ran, YANG Xin, SUN Shoujia, YAN Tengfei. The Ecological Water Demand of Different Vegetation Types in the Bashang Area, Northwest Hebei Province[J]. Journal of Resources and Ecology, 2022, 13(1): 113-119.
Month | Forest | Shrub | Grassland |
---|---|---|---|
April | 0.5 | 0.4 | 0.3 |
May | 0.7 | 0.6 | 0.6 |
June | 0.9 | 0.8 | 0.8 |
July | 1.1 | 0.9 | 0.9 |
August | 0.8 | 0.8 | 0.8 |
September | 0.6 | 0.6 | 0.6 |
October | 0.5 | 0.5 | 0.4 |
Table 1 Vegetation coefficients (Kc) of different vegetation types
Month | Forest | Shrub | Grassland |
---|---|---|---|
April | 0.5 | 0.4 | 0.3 |
May | 0.7 | 0.6 | 0.6 |
June | 0.9 | 0.8 | 0.8 |
July | 1.1 | 0.9 | 0.9 |
August | 0.8 | 0.8 | 0.8 |
September | 0.6 | 0.6 | 0.6 |
October | 0.5 | 0.5 | 0.4 |
Month | Monthly average soil moisture (%) | Modified soil moisture coefficient KS |
---|---|---|
April | 6.58 | 0.87 |
May | 4.81 | 0.79 |
June | 3.08 | 0.68 |
July | 7.25 | 0.89 |
August | 3.69 | 0.73 |
September | 7.10 | 0.89 |
October | 8.66 | 0.93 |
Table 2 Soil moisture correction factor for each month
Month | Monthly average soil moisture (%) | Modified soil moisture coefficient KS |
---|---|---|
April | 6.58 | 0.87 |
May | 4.81 | 0.79 |
June | 3.08 | 0.68 |
July | 7.25 | 0.89 |
August | 3.69 | 0.73 |
September | 7.10 | 0.89 |
October | 8.66 | 0.93 |
Month | Forest | Shrub | Grassland | |||
---|---|---|---|---|---|---|
Actual evapotranspiration (mm) | Proportion (%) | Actual evapotranspiration (mm) | Proportion (%) | Actual evapotranspiration (mm) | Proportion (%) | |
April | 37.71 | 9.39 | 30.17 | 8.41 | 22.63 | 6.54 |
May | 58.55 | 14.57 | 50.19 | 13.99 | 50.19 | 14.50 |
June | 65.57 | 16.32 | 58.28 | 16.24 | 58.28 | 16.84 |
July | 109.13 | 27.16 | 89.29 | 24.89 | 89.29 | 25.80 |
August | 63.39 | 15.78 | 63.39 | 17.67 | 63.39 | 18.32 |
September | 41.38 | 10.30 | 41.38 | 11.53 | 41.38 | 11.96 |
October | 26.07 | 6.49 | 26.07 | 7.27 | 20.86 | 6.03 |
Whole growing season | 401.81 | 100.00 | 358.78 | 100.00 | 346.02 | 100.00 |
Table 3 The monthly actual evapotranspiration of different vegetation types
Month | Forest | Shrub | Grassland | |||
---|---|---|---|---|---|---|
Actual evapotranspiration (mm) | Proportion (%) | Actual evapotranspiration (mm) | Proportion (%) | Actual evapotranspiration (mm) | Proportion (%) | |
April | 37.71 | 9.39 | 30.17 | 8.41 | 22.63 | 6.54 |
May | 58.55 | 14.57 | 50.19 | 13.99 | 50.19 | 14.50 |
June | 65.57 | 16.32 | 58.28 | 16.24 | 58.28 | 16.84 |
July | 109.13 | 27.16 | 89.29 | 24.89 | 89.29 | 25.80 |
August | 63.39 | 15.78 | 63.39 | 17.67 | 63.39 | 18.32 |
September | 41.38 | 10.30 | 41.38 | 11.53 | 41.38 | 11.96 |
October | 26.07 | 6.49 | 26.07 | 7.27 | 20.86 | 6.03 |
Whole growing season | 401.81 | 100.00 | 358.78 | 100.00 | 346.02 | 100.00 |
Month | Rainfall | Forest | Shrub | Grassland |
---|---|---|---|---|
April | 0 | 37.71 | 30.17 | 22.63 |
May | 5.8 | 52.75 | 44.39 | 44.39 |
June | 36.7 | 28.87 | 21.58 | 21.58 |
July | 96.85 | 12.28 | -7.56 | -7.56 |
August | 64.78 | -1.39 | -1.39 | -1.39 |
September | 37.8 | 3.58 | 3.58 | 3.58 |
October | 32.5 | -6.43 | -6.43 | -11.64 |
Whole growing season | 274.43 | 127.38 | 84.35 | 71.59 |
Table 4 Actual ecological water deficit of the different vegetation types in the growing season (Unit: mm)
Month | Rainfall | Forest | Shrub | Grassland |
---|---|---|---|---|
April | 0 | 37.71 | 30.17 | 22.63 |
May | 5.8 | 52.75 | 44.39 | 44.39 |
June | 36.7 | 28.87 | 21.58 | 21.58 |
July | 96.85 | 12.28 | -7.56 | -7.56 |
August | 64.78 | -1.39 | -1.39 | -1.39 |
September | 37.8 | 3.58 | 3.58 | 3.58 |
October | 32.5 | -6.43 | -6.43 | -11.64 |
Whole growing season | 274.43 | 127.38 | 84.35 | 71.59 |
Month | Forest | Shrub | Grassland | |||
---|---|---|---|---|---|---|
Minimum | Optimal | Minimum | Optimal | Minimum | Optimal | |
April | 21.24 | 41.18 | 16.99 | 32.94 | 12.74 | 24.71 |
May | 36.32 | 70.41 | 31.13 | 60.35 | 31.13 | 60.35 |
June | 47.25 | 91.60 | 42.00 | 81.43 | 42.00 | 81.43 |
July | 60.08 | 116.49 | 49.16 | 95.31 | 49.16 | 95.31 |
August | 42.55 | 82.50 | 42.55 | 82.50 | 42.55 | 82.50 |
September | 22.78 | 44.17 | 22.78 | 44.17 | 22.78 | 44.17 |
October | 13.74 | 26.63 | 13.74 | 26.63 | 10.99 | 21.31 |
Whole growing season | 243.96 | 472.99 | 218.35 | 423.34 | 211.36 | 409.77 |
Table 5 Minimum and optimal ecological water requirements of the different vegetation types during the growing season (Unit: mm)
Month | Forest | Shrub | Grassland | |||
---|---|---|---|---|---|---|
Minimum | Optimal | Minimum | Optimal | Minimum | Optimal | |
April | 21.24 | 41.18 | 16.99 | 32.94 | 12.74 | 24.71 |
May | 36.32 | 70.41 | 31.13 | 60.35 | 31.13 | 60.35 |
June | 47.25 | 91.60 | 42.00 | 81.43 | 42.00 | 81.43 |
July | 60.08 | 116.49 | 49.16 | 95.31 | 49.16 | 95.31 |
August | 42.55 | 82.50 | 42.55 | 82.50 | 42.55 | 82.50 |
September | 22.78 | 44.17 | 22.78 | 44.17 | 22.78 | 44.17 |
October | 13.74 | 26.63 | 13.74 | 26.63 | 10.99 | 21.31 |
Whole growing season | 243.96 | 472.99 | 218.35 | 423.34 | 211.36 | 409.77 |
Month | Forest | Shrub | Grassland | ||||
---|---|---|---|---|---|---|---|
Minimum | Optimal | Minimum | Optimal | Minimum | Optimal | ||
April | 21.24 | 41.18 | 16.99 | 32.94 | 12.74 | 24.71 | |
May | 30.52 | 64.61 | 25.33 | 54.55 | 25.33 | 54.55 | |
June | 10.55 | 54.90 | 5.30 | 44.73 | 5.30 | 44.73 | |
July | -36.77 | 19.64 | -47.69 | -1.54 | -47.69 | -1.54 | |
August | -22.23 | 17.72 | -22.23 | 17.72 | -22.23 | 17.72 | |
September | -15.02 | 6.37 | -15.02 | 6.37 | -15.02 | 6.37 | |
October | -18.76 | -5.87 | -18.76 | -5.87 | -21.51 | -11.19 | |
Whole growing season | -30.47 | 198.56 | -56.08 | 148.91 | -63.07 | 135.34 |
Table 6 Minimum and optimal ecological water deficits of the different vegetation types in the growing season (Unit: mm)
Month | Forest | Shrub | Grassland | ||||
---|---|---|---|---|---|---|---|
Minimum | Optimal | Minimum | Optimal | Minimum | Optimal | ||
April | 21.24 | 41.18 | 16.99 | 32.94 | 12.74 | 24.71 | |
May | 30.52 | 64.61 | 25.33 | 54.55 | 25.33 | 54.55 | |
June | 10.55 | 54.90 | 5.30 | 44.73 | 5.30 | 44.73 | |
July | -36.77 | 19.64 | -47.69 | -1.54 | -47.69 | -1.54 | |
August | -22.23 | 17.72 | -22.23 | 17.72 | -22.23 | 17.72 | |
September | -15.02 | 6.37 | -15.02 | 6.37 | -15.02 | 6.37 | |
October | -18.76 | -5.87 | -18.76 | -5.87 | -21.51 | -11.19 | |
Whole growing season | -30.47 | 198.56 | -56.08 | 148.91 | -63.07 | 135.34 |
[1] |
Bai X, Ji X X, Zhao C L, et al. 2021. Artificial forest conversion into grassland alleviates deep-soil desiccation in typical grass zone on China’s Loess Plateau: Regional modeling. Agriculture, Ecosystems and Environment, 320: 107608. DOI: 10.1016/J.AGEE.2021.107608.
DOI |
[2] | Chen L H, Wang L X. 2001. Classification of ecological water use and quota determination of ecological water use of forest cover in Beijing. Research of Soil and Water Conservation, 8(4): 161-164. (in Chinese) |
[3] | Chu B. 2009. Calculation and forecast of ecological water demand and consumption for floodplain forest in arid area. Diss., Beijing, China: Tsinghua University. (in Chinese) |
[4] | Dong X, Zhou J P, Hu H T, et al. 2018. Ecological water requirement estimation of typical plantation tree species in Yanqing, Beijing. Journal of West China Forestry Science, 47(1): 74-79. (in Chinese) |
[5] | Guo Y L. 2013. Causes of death of poplar protective forest in Bashang Area. Land Greening, (8): 37. (in Chinese) |
[6] | He Y T, Min Q W, Li W H, et al. 2004. Calculation of ecological water requirement of forests in Jinghe Watershed. Journal of Soil Water Conservation, 18(6): 152-155.. (in Chinese) |
[7] | Li T S, Xia J, Kuang Y, et al. 2017. The applicability of various potential evapotranspiration estimation methods in the middle and upper reaches of Hanjiang River Basin. South-to-North Water Transfers and Water Science & Technology, 15(6): 1-10.. (in Chinese) |
[8] | Li Y F, Zhang L X, Cao Y Q, et al. 2019. Spatiotemporal variations of potential evapotranspiration and its climate influencing factors in Hebei Province. South-to-North Water Transfers and Water Science & Technology, 17(3): 67-78. (in Chinese) |
[9] | Liu C F. 2007. Energy and water budget of a poplar plantation in Suburban Beijing. Diss., Beijing, China: Beijing Forestry University. (in Chinese) |
[10] | Liu J. 2014. Study on the vegetation ecological water requirement in the Heihe River Basin based on 3S technology. Diss., Yangling, China: Northwest A&F University. |
[11] |
Liu Z H, Jia G D, Yu X X, et al. 2021. Morphological trait as a determining factor for Populus simonii Carr. to survive from drought in semi-arid region. Agricultural Water Management, 253: 106943. DOI: 10.1016/J.AGWAT.2021.106943.
DOI URL |
[12] | Jensen M E. 1982. Consumptive use of water and irrigation water requirements. Xiong Y Z, Lin X C (Transtalted). Beijing, China: Agricultural Press. (in Chinese) |
[13] | Min Q W, He Y T, Li W H, et al. 2004. Estimation of forests’ ecological water requirement based on agrometeorology: Taking Jinghe Watershed as an example. Acta Ecologica Sinica, 24(10): 2130-2135. (in Chinese) |
[14] | Qin M S, Hao L, Shi T T, et al. 2016. Comparison and modification of five crop reference evapotranspiration models for Qinhuai River Basin. Chinese Journal of Agrometeorology, 37(4): 390-399. (in Chinese) |
[15] |
Sun S J, He C X, Qiu L F, et al. 2018. Stable isotope analysis reveals prolonged drought stress in poplar lantation mortality of the Three-North Shelter Forest in Northern China. Agricultural and Forest Meteorology, 252: 39-48.
DOI URL |
[16] | Wang L, Feng X X, Liu G, et al. 2017. Dynamic changes in water consumption and supply of soil in artificial Pinus tabuliformis land. Acta Agriculturae Jiangxi, 29(3): 80-84. (in Chinese) |
[17] | Wang L X. 2000. Vegetative eco environment construction and water use of eco environment-Taking northwestern area for an example. Research of Soil and Water Conservation, 7(3): 5-7. (in Chinese) |
[18] | Xiao C L, Zhang L X, Cao Y Q, et al. 2019. Differentiation and analysis on characteristics of potential evapotranspiration in Hebei Province and related dominant factors. Water Resources and Hydropower Engineering, 50(6): 1-10. (in Chinese) |
[19] | Xing H F. 2015. Analysis on death causes of poplar shelterbelt in Bashang. Hebei Forestry Science and Technology, (1): 76-77. (in Chinese) |
[20] |
Xu C Y, Singh V P. 2005. Evaluation of three complementary relationship evapotranspiration models by water balance approach to estimate actual regional evapotranspiration in different climatic regions. Journal of Hydrology, 308(1-4): 105-121.
DOI URL |
[21] | Yang W, Shen R X, Liu H X. 1999. On the sustainable management of the Poplar canker (Dothiorella gregaria Sacc.). Journal of Beijing Forestry University, 21(4): 13-17. (in Chinese) |
[22] |
Zhang Y, Yang Z F. 2002. Calculation method of ecological water requirement for forestland and its application to Huang-Huai-Hai Region. Chinese Journal of Applied Ecology, 13(12): 1566-1570. (in Chinese)
PMID |
[23] | Zheng C Y, Xu Z Q, Ma C M, et al. 2018. The factors influencing the poplar shelterbelt degradation in the Bashang Plateau of Northwest Hebei Province. Forest Resources Management, (1): 9-15, 147. (in Chinese) |
[24] | Zhou X D. 2017. Study on the spatial and temporal of vegetation ecological water requirement in Xiaojiang Basin Yunnan Province based on GIS. Diss., Beijing, China: Chinese Academy of Geological Sciences. |
[1] | 徐玲玲, 钱拴, 赵秀兰, 延昊. 2000-2020年西南石漠化区植被生态质量时空变化及对气候变化的响应[J]. 资源与生态学报, 2022, 13(1): 27-33. |
[2] | 何豫川, 熊俊楠, 阿布都马南·阿合买提哈力, 程维明, 叶冲冲, 贺文, 雍志玮, 田洁. 基于Google Earth Engine的阿勒泰地区植被时空格局及驱动力分析[J]. 资源与生态学报, 2021, 12(6): 729-742. |
[3] | 田洁, 熊俊楠, 张一驰, 程维明, 何豫川, 叶冲冲, 贺文. 定量评估气候变化和人类活动对阿勒泰地区草地净初级生产力的影响[J]. 资源与生态学报, 2021, 12(6): 743-756. |
[4] | 郭彩贇, 赵东升, 郑度, 朱瑜. 放牧对内蒙古草原植被群落特征的影响[J]. 资源与生态学报, 2021, 12(3): 319-331. |
[5] | 宋明华, 李猛, 霍佳娟, 吴良, 张宪洲. 西藏高原高寒草地的多功能性及其阈值[J]. 资源与生态学报, 2020, 11(3): 263-271. |
[6] | 周玉科. 利用物候相机绿度指数分析温带草原生态系统的植被物候及其与气象因子关系[J]. 资源与生态学报, 2019, 10(5): 481-493. |
[7] | 李海防, 刘庆华, 李士美, 李伟, 杨金明. 华南地区漓江上游3种典型森林不同层次土壤湿度比较研究[J]. 资源与生态学报, 2019, 10(3): 307-314. |
[8] | 孙雷刚, 王绍强, A.MICKLER Rober, 陈敬华, 于泉洲, 钱钊晖, 周国逸, 孟泽. 基于遥感指数的中国南亚热带常绿林光合作用季节动态变化研究[J]. 资源与生态学报, 2019, 10(2): 112-126. |
[9] | Melkamu Meseret Alemu. 埃塞俄比亚安达萨河流域地表温度和归一化植被指数时空变化分析[J]. 资源与生态学报, 2019, 10(1): 77-85. |
[10] | Masoud MASOUDI, Parviz JOKAR. 基于地理信息系统的植被退化风险评估: 以伊朗Qareh Aghaj盆地为例[J]. 资源与生态学报, 2018, 9(5): 477-483. |
[11] | 田莉, 张扬建, Claus HOLZAPFEL, 黄珂, 陈宁, 陶建, 朱军涛. 藏北高原植被的分布与环境和空间因素的关系分析[J]. 资源与生态学报, 2018, 9(5): 526-537. |
[12] | 沈振西, 孙维, 李少伟, 张豪睿, 付刚, 余成群, 张光雨. 利用MODIS潜在蒸散数据模拟青藏高原饱和水汽压亏缺[J]. 资源与生态学报, 2018, 9(5): 538-544. |
[13] | Mulubrhan Balehegn, Kidane Hintsa. 埃塞俄比亚西北部半干旱地区居民安置点附近木本植被变化规律[J]. 资源与生态学报, 2018, 9(3): 317-329. |
[14] | 郗敏,孔范龙,李悦. 胶州湾滨海盐沼芦苇地上部生长动态及EVI分析[J]. 资源与生态学报, 2017, 8(6): 641-647. |
[15] | 付刚, 孙维, 李少伟, 张晶, 余成群, 沈振西. 利用MODIS影像和气候数据模拟青藏高原草地地上生物量[J]. 资源与生态学报, 2017, 8(1): 42-49. |
阅读次数 | ||||||
全文 |
|
|||||
摘要 |
|
|||||