河北坝上与坝下不同土地利用类型土壤入渗特征及其影响因素

为查明河北省坝上与坝下不同土地利用类型土壤入渗能力,选择张北县（坝上风蚀区）和阳原县（坝下水蚀区）作为典型研究区,采用微型圆盘入渗仪测量土壤入渗特性,并分析其主要影响因素。研究结果表明：（1）阳原县不同土地利用类型土壤渗透性能表现为：高盖度草地>低盖度草地>耕地>林地,张北县表现为：草地>耕地>灌木林地>防护林地;（2）不同入渗模型拟合度之间存在显著差异,其中Philip模型拟合效果最佳;（3）土壤初始入渗速率、稳定入渗速率、稳定入渗时间与容重呈极显著负相关关系,而与总孔隙度均呈极显著正相关关系。结果表明,该区草地土壤入渗能力最强,后期开展生态工程建设时应更加重视草地涵养水源的作用。     

基于土地利用与植被恢复情景的土壤侵蚀演变特征

基于土地利用与植被恢复情景,使用USLE和土壤风蚀方程对坝上地区水蚀和风蚀强度进行估算。结果表明：（1）2015年坝上地区风蚀、水蚀和总侵蚀强度均值分别为8.83±5.15 t·ha^-1·a^-1、4.37±6.62 t·ha^-1·a^-1和13.22±8.18 t·ha^-1·a^-1;风蚀占总侵蚀67%,水蚀占33%。（2）土地利用调整情景下,风蚀、水蚀和总侵蚀强度分别减少4.9%~9.9%、2.9%~8.3%和4.3%~9.3%;土地利用+植被恢复情景下,风蚀、水蚀和总侵蚀强度则分别减少6.3%~13.8%、5.2%~16.2%和5.9%~14.3%。（3）土地调整面积与风蚀强度减少率呈对数关系,与水蚀强度减少率呈指数关系,与总侵蚀强度减少率呈线性关系（P<0.01）。本文结果可以为土壤侵蚀方程计算及区域土壤侵蚀防治提供数据参考。     

基于土地利用视角的乡村居业协同多尺度分析——以徐州市为例

“乡村振兴”战略是解决城乡发展不协调、乡村发展不充分问题的重要抓手。居业协同作为乡村人居融合发展的高级形态,其程度能够反映乡村振兴的质量与成效。采用土地利用数据从结构和利用两个维度探索淮海经济区中心城市徐州三个尺度下的居业协同格局,结果表明：（1）徐州市土地在供给方面表现出居业失衡,宅基地供给相对于经营性建设用地优势明显;但由于使用中宅基地的空废,二者利用状态表现得更协同。（2）不同空间尺度下,居业协同状态有所差异,其中乡镇尺度居业空间关系较为稳定,基本维持相对平衡,本文认为乡镇是土地资源配置、实施乡村振兴战略的最佳尺度。（3）后续研究中,居业用地适宜的比例及农用地对居业协同的影响都需要进一步探索。     

三江源植被碳利用率动态变化及其对气候响应

本文基于MODIS GPP/NPP数据估算了三江源植被碳利用率（CUE）,结合气象数据和高程数据采用一元线性回归和相关分析法,探讨了2001~2017年三江源植被CUE的时空变化特征及植被CUE对气温、降水量和蒸散量变化的响应.结果表明：（1）三江源植被CUE年内3~10月表现为先增加后降低的变化趋势,其中6月植被CUE最高.（2）三江源年植被碳利用率位于0.73~1,平均水平为0.85;植被CUE空间上呈现北高南低,西高东低的分布特征.（3）整体上,三江源4~10月植被碳利用率与同期气温、降水量和蒸散量分别呈现正相关、负相关和负相关关系,降水量是影响三江源植被CUE变化的主要影响因素,气温为次要因素,蒸散量影响程度最小.     

土地利用方式下土壤有机碳特征及影响因素——以后寨河喀斯特小流域为例

为研究喀斯特小流域土壤有机碳空间分布与土地利用之间的关系,基于网格法在后寨河流域挖掘了2 755个土壤剖面,并采集了22 057个土壤样品。分析了后寨河流域不同土地利用方式下土壤有机碳密度特征。结果表明：后寨河流域土壤有机碳密度主要受人为干扰、土壤厚度与岩石裸露率的制约。不同利用方式土壤有机碳密度（0~100 cm）总体上呈现以下规律：水田>旱地>经果林地>园地>草地>弃耕地>坡耕地>乔灌木林地>乔木林地>荒地>灌木林地>灌草地。后寨河流域100 cm土壤有机碳平均碳密度为8.70 kg/m²,低于中国土壤有机碳平均密度10.83 kg/m²,总有机碳储量为5.39×10⁸ kg。科学合理地进行土地利用方式调整与管理,可以增大喀斯特小流域土壤有机碳储量。     

典型铅锌矿化区不同土地利用类型土壤重金属污染特征与评价

选取云南者海典型铅锌矿区周边冶炼区（A）、粮食主产区（B）、保护区（C）三个区域土壤为研究对象,分析三个区域内林地（LD）和耕地（GD）土壤pH、总碳（TC）、总氮（TN）、总磷（TP）和5种重金属（Hg、Cd、Pb、Zn、Cu）含量,利用典范对应分析（CCA）研究不同土地利用类型下它们之间的关系,基于系统熵值与重金属生物毒性改进灰色聚类评价法对研究区重金属污染程度进行评价。结果表明,A、B、C三区土壤的5种重金属均超过云南省土壤背景值,且含量A区 > B区 > C区,所有土壤样品Hg、Cd、Pb、Zn、Cu平均含量分别为7.24、1.53、1 794、2 892、210 mg/kg;LD土壤重金属含量普遍高于GD。研究区土壤pH总体呈弱酸性,但A区土壤受矿业活动影响呈弱碱性。TC、TN含量和C/N值均表现出LD大于GD,但TP含量表现为GD显著大于LD （P<0.05）。CCA分析表明LD和GD土壤pH与Cd和Cu呈负相关,与Zn和Pb呈正相关,且pH对重金属含量的影响最大;TC、TP与重金属Cd和Cu在LD土壤中呈正相关,在GD土壤中呈负相关。改进灰色聚类评价结果表明重金属污染程度均表现为LD大于GD;A区污染最严重且均呈重度污染,B区次之,C区污染程度最轻。经比较本文改进的灰色聚类评价法在准确性和灵敏度方面优于传统方法。     

Linking Land Cover and Water Quality in New York City’S Water Supply Watersheds

The Catskill/Delaware reservoirs supply 90% of New York City’s drinking water. The City has implemented a series of watershed protection measures, including land acquisition, aimed at preserving water quality in the Catskill/Delaware watersheds. The objective of this study was to examine how relationships between landscape and surface water measurements change between years. Thirty-two drainage areas delineated from surface water sample points (total nitrogen, total phosphorus, and fecal coliform bacteria concentrations) were used in step-wise regression analyses to test landscape and surface-water quality relationships. Two measurements of land use, percent agriculture and percent urban development, were positively related to water quality and consistently present in all regression models. Together these two land uses explained 25 to 75% of the regression model variation. However, the contribution of agriculture to water quality condition showed a decreasing trend with time as overall agricultural land cover decreased. Results from this study demonstrate that relationships between land cover and surface water concentrations of total nitrogen, total phosphorus, and fecal coliform bacteria counts over a large area can be evaluated using a relatively simple geographic information system method. Land managers may find this method useful for targeting resources in relation to a particular water quality concern, focusing best management efforts, and maximizing benefits to water quality with minimal costs.The United States Environmental Protection Agency through its Office of Research and Development funded and managed the research described here. It has been subjected to Agency’s administrative review and approved for publication as an EPA document.     

Modeling the spatial pattern of farmland using GIS and multiple logistic regression: a case study of Maotiao River Basin, Guizhou Province, China

Land use change is an important topic in the field of global environmental change and sustainable development. Land use change modeling has attracted substantial attention because it helps researchers understand the mechanisms of land use change and assists regulatory bodies in formulating relevant policies. Maotiao River Basin is located in the province of Guizhou, China, which has a developed agricultural industry in the karst mountain areas. This paper selected biophysical and social–economic factors as independent variables, and constructed a multiple logistic regression of farmland spatial distribution probability by random sampling. Then, by using GIS technology and integrating the 2000 data, this study predicted the farmland spatial pattern. When the predicted map was compared with the actual farmland map for 2000, we noted that 71% of the simulation is in accordance with the 2000 farmland pattern. The result satisfactorily proves the reasonability and applicability of our model.     

Assessing land use impacts on flood processes in complex terrain by using GIS and modeling approach

A distributed hydrologic modeling and GIS approach is applied for the assessment of land use impact in the Steinsel sub-basin, Alzette, Grand-Duchy of Luxembourg. The assessment focuses on the runoff contributions from different land use classes and the potential impact of land use changes on runoff generation. The results show that the direct runoff from urban areas is dominant for a flood event compared with runoff from other land use areas in this catchment, and tends to increase for small floods and for the dry season floods, whereas the interflow from forested, pasture and agricultural field areas contributes to the recession flow. Significant variations in flood volume, peak discharge, time to the peak, etc., are found from the model simulation based on the three hypothetical land use change scenarios.     

Using environmental stressor information to predict the ecological status of Maryland non-tidal streams as measured by biological indicators

In Maryland, U.S., an interim framework has recentlybeen developed for using biologically based thresholds, or `biocriteria', to assess the health of nontidal streams statewide at watershed scales. The evaluation of impairment is based on indices of biological integrity from the Maryland Biological Stream Survey (MBSS). We applied logistic regression to quantify how the biotic integrity of streams at a local scale is affected by cumulative effects resulting from catchment land uses, point sources, and nearby transmission line rights-of-way. Indicators for land use were developed from the remote sensing National Land Cover Data and applied at different scales. We determined that the risk of local impairment in nontidal streams rapidly increases with increased urban land use in the catchment area. The average likelihood of failing biocriteria doubled with every 10% points increment in urban land, thus an increase in urban land use from 0 to 20% quadruples the risk of impairment. For the basins evaluated in this study, catchments with more than 40–50% urban land use had greater than 80% probability of failing biocriteria, on average. Inclusion of rights-of-way and point sources in the model did not significantly improve the fit for this data set, most likely because of their low numbers. The overall results indicate that our predictive modeling approach can help pinpoint stream ecosystems experiencing or vulnerable to degradation.