KMS XINJIANG INSTITUTE OF ECOLOGY AND GEOGRAPHY，CAS
| 中亚地区降水侵蚀力的时空变化与预测 | |
| Alternative Title | SPATIOTEMPORAL VARIATIONS AND PROJECTION OF CLIMATE CHANGE-INDUCED RAINFALL EROSIVITY OVER CENTRAL ASIA |
| Duulatov Eldiiar | |
| Subtype | 博士 |
| Thesis Advisor | 陈曦 |
| 2019-06-30 | |
| Degree Grantor | 中国科学院大学 |
| Place of Conferral | 北京 |
| Degree Discipline | 理学博士 |
| Keyword | 降雨侵蚀力 中亚 GCMs 土壤侵蚀 RUSLE 气候变化 Rainfall erosivity Central Asia GCMs Soil erosion RUSLE Climate Change |
| Abstract | 气候变化引起的降水变异是导致世界大多数国家土壤过度流失的降雨侵蚀的主要原因。研究利用全球气候模型(GCMs) 对中亚地区降雨侵蚀度的时空预测进行了表征，并对降雨侵蚀度变化的影响进行了评价。该博士论文的研究内容为整个中亚地区的降雨侵蚀力，主要包含以下几点：（1）哈萨克斯坦年降雨侵蚀力时空变化及预测研究；（2）吉尔吉斯斯坦土壤侵蚀风险评估；（3）干旱-半干旱气候区域典型代表区域。研究结果表明：(1) 在代表性浓度路径 (RCPs) 2.6 和 8.5 下，采用 delta 方法对 GCMs(BCCCSM1-1、 IPSLCM5BLR、 MIROC5 和 MPIESMLR) 在“近”和“远” 未来 (2030 年代和 2070 年代) 两个时间段进行了统计学上的缩尺。这些 GCMs 数据被用于估计中亚地区的降雨侵蚀率及其预测变化。使用 WorldClim 数据作为研究区域的当前基线降水情景。利用修正的普遍土壤流失方程(RUSLE) 的降雨侵蚀率(R) 因子来确定降雨侵蚀率。结果表明，与基线相比，未来的年降雨量侵蚀率呈上升趋势。在所有 GCMs 中，与 402 MJ mm ha-1 h-1 year-1 基线相比，2030 年代的降雨侵蚀率平均变化为 5.6% (424.49 MJ mm ha-1 h-1 year-1) ， 2070 年代为 9.6% (440.57 MJ mm ha-1 h-1 year-1) 。变化的幅度随 GCMs 而变化，最大的变化是 26.6% (508.85 MJ mm ha-1 h-1 year-1)，发生在 2070 年代的 MIROC-5RCP8.5 场景中。尽管年降雨量侵蚀率呈稳定上升趋势，但 IPSLCM5ALR (RCP和周期)平均侵蚀率呈下降趋势。降雨量的增加是导致时空降雨侵蚀度增加的主要原因。(2) 研究了 1970-2017 年哈萨克斯坦降雨侵蚀度的时空变化。结果表明，过去 48 年哈萨克斯坦年平均降雨侵蚀度为 464 MJ mm ha-1 h-1 year-1。年降雨量侵蚀率没有明显的时间变化趋势。本文提出的一些结果与进一步研究哈萨克斯坦潜在的土壤侵蚀有关。东哈萨克斯坦、北哈萨克斯坦、阿拉木图地区受降雨侵蚀的威胁比其他地区更大。由于日降雨量总是有限的，了解干旱和半干旱地区过去和未来降雨侵蚀度的差异及其后果具有重要意义。采用 Delta 方法对 GCM场景 (GISSE2H、 HadGEM2-ES 和 NorESM1M) 进行三个周期的统计缩小。本研究利用过去和未来的气候数据估计了哈萨克斯坦年降雨量侵蚀率的长期变化。根据基线气候，在本世纪 30 年代、 50 年代和 70 年代，降雨侵蚀率的平均变化百分比分别为 26.9%、 26.4%和 35.2%。与基准气候相比，所有情景下所有气候模型的年降水量和侵蚀活动总量均呈现稳定增长。(3) 通过遥感和地理信息系统手段，利用 RUSLE 对吉尔吉斯斯坦的土壤流失进行了评估。结果表明，降雨侵蚀率(R)、土壤可蚀性(K)、坡长陡度(LS)、覆盖管理因子(C)、养护实践因子(P)的均值分别为 144.2–4509 MJ mm ha-1 h-1 year-1,0.014–0.042 t h MJ-1 mm-1, 0.0–44.6, 0.001–1.218 and 0.5–1.0。结果表明，平均年土壤侵蚀为<10 to >200 t ha-1 year-1，平均年土壤侵蚀为 94.6 t ha-1 year-1，标准差为 206.3 t ha-1 year-1。吉尔吉斯斯坦的年土壤损失量为 17410 千吨。这些结果使我们能够确定易受侵蚀的区域。研究结果将将有助于出现组织情景，并为决策者提供有效管理土壤侵蚀风险的选择，以便对不同领域进行排序，进而充分执行政策。查明加剧侵蚀性增长的其他基本因素; 特别是未来土地利用和土地覆盖 (LULC) 的变化，仍有待于进一步的调查。 |
| Other Abstract | Climate change-induced precipitation variability is the leading cause of rainfallerosivity that leads to excessive soil losses in most countries of the world. In thisstudy, global climate models (GCMs) were used to characterize the spatiotemporalprediction of rainfall erosivity and assess the effect of variations of rainfall erosivityin Central Asia. The study area of this PhD thesis included entire Central Asia forproject rainfall erosivity (1); Kazakhstan for spatiotemporal variation and projectionof annual rainfall erosivity (2); and Kyrgyzstan for soil erosion risk assessment (3).(1) The GCMs (BCCCSM1-1, IPSLCM5BLR, MIROC5, and MPIESMLR) werestatistically downscaled using the delta method under Representative ConcentrationPathways (RCPs) 2.6 and 8.5 for two periods: ―Near‖ and ―Far‖ future (2030s and2070s). These GCMs data were used to estimate rainfall erosivity and its projectedchanges over Central Asia. WorldClim data was used as the present baselineprecipitation scenario for the study area. The rainfall erosivity (R) factor of theRevised Universal Soil Loss Equation (RUSLE) was used to determine rainfallerosivity. The results show an increase in the future periods of the annual rainfallerosivity compared to the baseline. For all GCMs, with an average change in rainfallerosivity of about 5.6% (424.49 MJ mm ha-1 h-1 year -1) in 2030s and 9.6% (440.57MJ mm ha-1 h-1 year -1) in 2070s as compared to the baseline of 402 MJ mm ha-1 h-1year-1. The magnitude of the change varies with the GCMs, with the largest changebeing 26.6% (508.85 MJ mm ha-1 h-1 year -1), occurring in the MIROC-5 RCP8.5scenario in the 2070s. Although annual rainfall erosivity shows a steady increase,IPSLCM5ALR (both RCPs and periods) shows a decrease in the average erosivity.Higher rainfall amounts were the prime causes of increasing spatial-temporal rainfallerosivity.(2) In this study, the spatial-temporal variation of rainfall erosivity in Kazakhstanin 1970–2017 was investigated. The results showed that the average annual rainfallerosivity in Kazakhstan over the past 48 years was 464 MJ mm ha-1 h-1 year -1. Nosignificant time trend was found in annual rainfall erosivity. Some of the resultspresented here are relevant to the further study of potential soil erosion in Kazakhstan.The East Kazakhstan, North Kazakhstan, Almaty regions were under a moresignificant threat of rainfall erosivity than other regions. It is important to understandpast and future differences in rainfall erosivity and its consequences in arid and semi-arid regions, where the amount of daily precipitation is always limited.GCM scenarios (GISSE2H, HadGEM2-ES and NorESM1M) were statisticallydownscaled using the delta method for three periods. This study estimated the longterm variations in annual rainfall erosivity in Kazakhstan using past and future climatedata. Based on the baseline climate, the average change in percent rainfall erosivity is26.9%, 26.4% and 35.2% in the 2030s, 2050s and 2070s, respectively. The aggregateaverage annual precipitation and erosion activity for all climate models for allscenarios shows steady growth compared with the baseline climate.(3) The purpose of this study is to assess soil loss in Kyrgyzstan using RUSLEwith RS and GIS. The result shows that the mean values of rainfall erosivity (R), soilerodibility (K), slope length and steepness (LS), cover management factor (C) andconservation practice (P) factors were equal to 144.2–4509 MJ mm ha-1 h-1 year-1,0.014–0.042 t h MJ-1 mm-1, 0.0–44.6, 0.001–1.218 and 0.5–1.0, respectively. Ourresults show that the average annual soil erosion is <10 to >200 t ha-1 year-1, mean soilerosion 94.6 t ha-1 year-1 with a standard deviation of 206.3 t ha-1 year-1. Annual soilloss in Kyrgyzstan is 17410 K t year−1. These results allowed us to define the areas,which are vulnerable to erosion.This will assist in emerging organization scenarios and provide choices topolicymakers for managing soil erosion risks efficiently for the ordering of differentareas for adequate policy implementation. It suggests that further investigations arerequired to identify other essential factors that intensify the growth of erosivity;particularly the future land use and land cover (LULC) changes. |
| Subject Area | 地图学与地理信息系统 |
| Language | 英语 |
| Document Type | 学位论文 |
| Identifier | http://ir.xjlas.org/handle/365004/15292 |
| Collection | 中国科学院新疆生态与地理研究所 研究系统 |
| Affiliation | 中国科学院新疆生态与地理研究所 |
| First Author Affilication | 中国科学院新疆生态与地理研究所 |
| Recommended Citation GB/T 7714 | Duulatov Eldiiar. 中亚地区降水侵蚀力的时空变化与预测[D]. 北京. 中国科学院大学,2019. |
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