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渭河流域水土流失治理效率的时空格局演化与影响因素
({{custom_author.role_cn}}), {{javascript:window.custom_author_cn_index++;}}Spatio-temporal Pattern Evolution and Influencing Factors of Governance Efficiency of Soil and Water Loss in the Weihe River Catchment
({{custom_author.role_en}}), {{javascript:window.custom_author_en_index++;}}运用Bootstrap-DEA模型计算2000~2015年渭河流域陕西段39个县区水土流失治理效率;结合探索性空间分析方法（ESDA）和地理加权回归模型(GWR)分析各县水土流失治理效率的时空演化特征及其影响因素。研究结果表明：① 2000~2015年,研究区水土流失治理效率从0.263增至0.336,整体治理效率仍处较低水平;前期生态治理效率的增加缘于纯技术效率的提高,后期规模效率对治理效率的增加起到了主导作用。② 县域的治理效率在空间上呈现集聚状态;热点分析结果进一步显示,2005年治理效率表现出2个热点集聚区,即以宝鸡市千阳县为热点区、乾县和武功县为核心辐射至永寿县和礼泉县的热点集聚区,冷点区域则以临潼为中心,辐射到西安市辖区、高陵、富平和三原县;2010~2015年治理效率的热点区域与冷点区域较2005年有所收缩且保持相对稳定。③ 渭河流域水土流失治理效率的时空变化是降水、坡度、灌草面积覆盖度、人口经济和农业生产共同作用的结果,且各影响因素在不同时期对各县的治理效率的贡献呈动态变化,这意味着政策制定者需要从全局角度权衡不同因素的影响效果。
Objectively assessing the effectiveness of ecological restoration measures and analyzing effective ways to promote the efficiency of ecological management are important scientific and policy issues in the Weihe River Basin. Using an interdisciplinary approach, the aim of this study is to measure the control efficiency of the Sloping Land Conversion Program（SLCP）and terrace fields on soil and water loss by adopting the Bootstrap-DEA model and using a comprehensive dataset (including biophysical and socioeconomic data) from 39 counties in the period 2000-2015. Then, exploratory spatial data analysis (ESDA) was used to capture the spatial correlation in overall control efficiency. Finally, geographically weighted regression (GWR) was employed to identify the spatial heterogeneity and evolutionary characteristics in the relationship between control efficiency and natural conditions and socioeconomic development in each sample county.Results show that the control efficiency of soil erosion increased from 0.263 to 0.336 during the study period. The increase of the treatment efficiency for soil and water loss in the early stage was due to the improvement of pure technical efficiency; while later the scale efficiency played a leading role in promoting the treatment efficiency. In addition, the efficiency showed a stable spatial agglomeration. The hotspots of efficiency were concentrated primarily in Baoji City, while the cold-spot center was Lintong, the radius of which extended to the municipality districts of Xi'an, Gaoling, and Fuping. The difference in control efficiency is the result of a combination of multiple factors; the factors affecting control efficiency vary across counties, indicating that regional governments should consider full-scale initiatives.
退耕还林（草） / Bootstrap-DEA / 地理空间加权模型(GWR Model) / 探索性空间分析（ESDA） / 渭河流域 / 治理效率 {{custom_keyword}} /
sloping land conversion program / Bootstrap-DEA / Geographically Weighted Regression(GWR) / exploratory spatial data analysis(ESDA) / the Weihe River catchment / control efficiency {{custom_keyword}} /
图5 2005~2015年水土流失治理效率热点分布Fig.5 Hotspot distribution of control efficiency in 2005(a), 2010(b) and 2015(c) |
表2 2005~2015年GWR模型各自变量对治理效率的影响系数Table 2 Regression coefficient of GWR in 2005-2015 |
| 变量 | 2005年 | 2010年 | 2015年 |
|---|---|---|---|
| lnintercept | -1.91~-1.52*** | -1.55~-1.05*** | -1.39~-1.24*** |
| lncover | 0.17~0.39** | 0.05~0.12 | 0.17~0.23* |
| （0.22） | （0.06） | （0.20） | |
| lnslope | -0.32~0.01 | -0.42~-0.20* | -0.32~-0.15* |
| （-0.09） | （-0.26） | （-0.25） | |
| lnprep | -0.17~0.01* | -0.01~0.36 | 0.40~0.55*** |
| （-0.12） | （0.12） | （0.49） | |
| lnpgdp | 1.83~13.12* | -2.45~2.31 | -1.18~1.51 |
| （7.14） | （-1.72） | （-0.82） | |
| (lnpgdp)2 | -13.48~-2.18** | 1.14~2.44 | 0.47~1.48 |
| （-7.51） | （1.77） | （0.65） | |
| lnpgrain | 0.16~0.33* | 0.01~0.20 | 0.05~0.68** |
| （0.25） | （0.10） | （0.43） | |
| lndensity | -0.46~-0.24** | -0.77~-0.25*** | -0.90~0.01** |
| （-0.35） | （-0.53） | （-0.60） | |
| 带宽 | 100 | 90 | 90 |
| AIC | 104.60 | 118.31 | 104.78 |
| R2 | 0.58 | 0.50 | 0.63 |
| Adjusted R2 | 0.36 | 0.28 | 0.42 |
| GWR Residuals | 15.18 | 16.43 | 11.87 |
| Global Residuals | 17.94 | 25.50 | 16.42 |
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PDF(1717 KB)
图1 研究区位置
表1 影响治理效率的指标选取说明图2 2000~2015年研究区主要观测站水沙量与降水的年际波动变化趋势图3 2005~2015年研究区水土流失治理效率空间分布图4 2005~2015年研究区水土流失治理效率分解图5 2005~2015年水土流失治理效率热点分布表2 2005~2015年GWR模型各自变量对治理效率的影响系数/
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