Spatiotemporal variations of potential evapotranspiration and aridity index in relation to influencing factors over Southwest China during 1960–2013

Traditional villages are the historical and cultural heritage of people around the world. With the increases in urbanization and industrialization, the continuation of traditional villages and the inheritance of historical and cultural heritage are facing risk. Therefore, to grasp the spatial characteristics of them and the human–nature interaction mechanism in Southwest China, we analyzed the distribution pattern of traditional villages using the ArcGIS software. Then, we further analyzed the spatial clustering characteristics, influencing factors and landscape pattern, and put forward relevant protection countermeasures and suggestions. The results revealed that traditional villages in Southwest China were clustered, being mainly distributed in areas with relatively low elevation, gentle slopes, low relative positions, nearby water sources, and convenient transportation. They can be divided into four categories due to obvious differences in influencing factors such as elevation, slope, relative position, distance to the nearest river, population density, etc. The landscape pattern of traditional villages differed among the different clusters, being mainly composed of forests, shrubs, and cultivated land. With the increase in the buffer radius, the landscape pattern of them changed significantly. The results of this study reflect that traditional villages and the natural environment are interdependent, so the protection of traditional villages should carry out measures according to local conditions.

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The role of climatic and terrain attributes in estimating baseflow recession in tropical catchments

Hydrology and Earth System Sciences ◽

10.5194/hess-14-2193-2010 ◽

2010 ◽

Vol 14 (11) ◽

pp. 2193-2205 ◽

Cited By ~ 34

Author(s):

J. L. Peña-Arancibia ◽

A. I. J. M. van Dijk ◽

M. Mulligan ◽

L. A. Bruijnzeel

Keyword(s):

Potential Evapotranspiration ◽

Aridity Index ◽

Global Scale ◽

Tree Cover ◽

Annual Rainfall ◽

Ungauged Catchments ◽

Ongoing Research ◽

Daily Streamflow ◽

Terrain Attributes ◽

Streamflow Data

Abstract. The understanding of low flows in rivers is paramount more than ever as demand for water increases on a global scale. At the same time, limited streamflow data to investigate this phenomenon, particularly in the tropics, makes the provision of accurate estimations in ungauged areas an ongoing research need. This paper analysed the potential of climatic and terrain attributes of 167 tropical and sub-tropical unregulated catchments to predict baseflow recession rates. Daily streamflow data (m3 s–1) from the Global River Discharge Center (GRDC) and a linear reservoir model were used to obtain baseflow recession coefficients (kbf) for these catchments. Climatic attributes included annual and seasonal indicators of rainfall and potential evapotranspiration. Terrain attributes included indicators of catchment shape, morphology, land cover, soils and geology. Stepwise regression was used to identify the best predictors for baseflow recession coefficients. Mean annual rainfall (MAR) and aridity index (AI) were found to explain 49% of the spatial variation of kbf. The rest of climatic indices and the terrain indices average catchment slope (SLO) and tree cover were also good predictors, but co-correlated with MAR. Catchment elongation (CE), a measure of catchment shape, was also found to be statistically significant, although weakly correlated. An analysis of clusters of catchments of smaller size, showed that in these areas, presumably with some similarity of soils and geology due to proximity, residuals of the regression could be explained by SLO and CE. The approach used provides a potential alternative for kbf parameterisation in ungauged catchments.

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Spatiotemporal variations and influencing factors of CO2 and CH4 emissions from urban small landscape waters

Acta Ecologica Sinica ◽

10.5846/stxb202005141226 ◽

2021 ◽

Vol 41 (15) ◽

Author(s):

黄婷，王晓锋，刘婷婷，庞吉丽，陈彦蓉，吴文洁，赵舒宁，吴胜男，王继龙 HUANG Ting

Keyword(s):

Influencing Factors ◽

Spatiotemporal Variations ◽

Ch4 Emissions

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Multiple causes of nonstationarity in the Weihe annual low-flow series

Hydrology and Earth System Sciences ◽

10.5194/hess-22-1525-2018 ◽

2018 ◽

Vol 22 (2) ◽

pp. 1525-1542 ◽

Cited By ~ 8

Author(s):

Bin Xiong ◽

Lihua Xiong ◽

Jie Chen ◽

Chong-Yu Xu ◽

Lingqi Li

Keyword(s):

Frequency Analysis ◽

Driving Forces ◽

Potential Evapotranspiration ◽

Aridity Index ◽

Base Flow ◽

Low Flow ◽

Distribution Model ◽

Flow Index ◽

Explanatory Variables ◽

Distribution Parameters

Abstract. Under the background of global climate change and local anthropogenic activities, multiple driving forces have introduced various nonstationary components into low-flow series. This has led to a high demand on low-flow frequency analysis that considers nonstationary conditions for modeling. In this study, through a nonstationary frequency analysis framework with the generalized linear model (GLM) to consider time-varying distribution parameters, the multiple explanatory variables were incorporated to explain the variation in low-flow distribution parameters. These variables are comprised of the three indices of human activities (HAs; i.e., population, POP; irrigation area, IAR; and gross domestic product, GDP) and the eight measuring indices of the climate and catchment conditions (i.e., total precipitation P, mean frequency of precipitation events λ, temperature T, potential evapotranspiration (EP), climate aridity index AIEP, base-flow index (BFI), recession constant K and the recession-related aridity index AIK). This framework was applied to model the annual minimum flow series of both Huaxian and Xianyang gauging stations in the Weihe River, China (also known as the Wei He River). The results from stepwise regression for the optimal explanatory variables show that the variables related to irrigation, recession, temperature and precipitation play an important role in modeling. Specifically, analysis of annual minimum 30-day flow in Huaxian shows that the nonstationary distribution model with any one of all explanatory variables is better than the one without explanatory variables, the nonstationary gamma distribution model with four optimal variables is the best model and AIK is of the highest relative importance among these four variables, followed by IAR, BFI and AIEP. We conclude that the incorporation of multiple indices related to low-flow generation permits tracing various driving forces. The established link in nonstationary analysis will be beneficial to analyze future occurrences of low-flow extremes in similar areas.

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Characterizing the spatiotemporal variations of evapotranspiration and aridity index in mid-western China from 2001 to 2016

Journal of Arid Land ◽

10.1007/s40333-021-0087-0 ◽

2021 ◽

Author(s):

Le Mu ◽

Yixiao Lu ◽

Minguo Liu ◽

Huimin Yang ◽

Qisheng Feng

Keyword(s):

Aridity Index ◽

Western China ◽

Spatiotemporal Variations

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Analysis on the Influencing Factors of Building Energy Consumption—A Southwest China Case Study

Proceedings of the 21st International Symposium on Advancement of Construction Management and Real Estate ◽

10.1007/978-981-10-6190-5_24 ◽

2017 ◽

pp. 259-272

Author(s):

Z. N. Zhao ◽

H. M. Zhang ◽

Y. F. Ding ◽

L. Y. Shen

Keyword(s):

Energy Consumption ◽

Influencing Factors ◽

Southwest China ◽

Building Energy ◽

Building Energy Consumption

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Monitoring Agricultural Drought in the Near East

Monitoring and Predicting Agricultural Drought ◽

10.1093/oso/9780195162349.003.0025 ◽

2005 ◽

Author(s):

Eddy De Pauw

Keyword(s):

Near East ◽

Potential Evapotranspiration ◽

Groundwater Resources ◽

Winter Season ◽

Aridity Index ◽

Agricultural Drought ◽

Moisture Regime ◽

Temperature Regimes ◽

Moisture Regimes ◽

Dry Climates

The countries of North Africa and West Asia, hereafter referred to as the “Near East,” cover a large part of the world (more than 7,200,000 km2). This region is characterized by diverse but generally dry climates, in which evaporation exceeds precipitation. The level of aridity is indicated by the aridity index, the ratio of annual precipitation to annual potential evapotranspiration, calculated by the Penman method (UNESCO, 1979). The degree of aridity is shown spatially in figure 16.1 and summarized per country in table 16.1. These data show that the region is characterized by humid, subhumid, semiarid, and arid to hyperarid moisture regimes. In addition, temperature regimes vary considerably, particularly due to the differences in altitudes and, to a lesser extent, due to the oceanic/continental influences. For most of the region, the precipitation generally occurs during the October–April period and thus is concentrated over the winter season. Table 16.1 shows that, with more than 90% of the land area in hyperarid, arid, or semiarid moisture regimes, aridity is very significant in the Near East. Turkey is better endowed with surface and groundwater resources due to the orographic capture of Atlantic cyclonal precipitation, but much of the interior is semiarid. If one excludes the hyperarid zones, which cover the driest deserts and have no potential for agricultural use, nearly 34% of the region, or about 2,460,000 km2, is dryland (i.e., the area with arid or semiarid moisture regime). These are the areas with some potential for either dryland farming (in semiarid zones) or for extensive rangeland (in arid zones). In the Near East countries, agriculture contributes about 10–20% to the gross domestic product and is therefore a major pillar of their economies. However, the indirect importance of agriculture is larger because it provides the primary goods that constitute the majority of merchandise exports and because of the relatively high number of people employed in agriculture. Because of the high degree of aridity in large parts of the region, agriculture in the Near East is particularly vulnerable to drought. Most of the agricultural systems depend on rainfall.

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Mid-Holocene drylands: A multi-model analysis using Paleoclimate Modelling Intercomparison Project Phase III (PMIP3) simulations

The Holocene ◽

10.1177/0959683619854512 ◽

2019 ◽

Vol 29 (9) ◽

pp. 1425-1438

Author(s):

Shanshan Liu ◽

Dabang Jiang ◽

Xianmei Lang

Keyword(s):

Relative Humidity ◽

Potential Evapotranspiration ◽

Aridity Index ◽

Phase Iii ◽

Collective Effects ◽

Model Data ◽

Intercomparison Project ◽

The Difference ◽

Paleoclimate Modelling Intercomparison Project ◽

Paleoclimate Modelling

This study examines changes in aridity levels during the mid-Holocene (approximately 6000 cal. yr ago) using multi-model simulations from the Paleoclimate Modelling Intercomparison Project Phase III. Overall, there is little difference in the total area of drylands from the preindustrial period; global drylands are 8% wetter than during the preindustrial period as measured by an aridity index; and 16% of preindustrial drylands convert to a wetter climate subtype, double the sum of zones that are replaced by a drier category. Considerable variations are present among regions with major contractions of each dryland subtype from northern Africa to South Asia and the main expansions of arid, semiarid, and dry subhumid climates in southern hemisphere continents. The difference in precipitation is the leading factor of the aforementioned changes. The second factor is the altered potential evapotranspiration as mainly induced by relative humidity, which contributes to additional aridity changes in a same direction as precipitation does. The collective effects of precipitation and relative humidity account for more than 80% of the dryland variations. In comparison, the simulated aridity change is in reasonable agreement with reconstructions, while there are model–data discrepancies for Australia and uncertainties across proxies for southern Africa.

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Delimitation of Agricultural Areas with Natural Constraints in Greece: Assessment of the Dryness Climatic Criterion Using Geostatistics

Agronomy ◽

10.3390/agronomy8090161 ◽

2018 ◽

Vol 8 (9) ◽

pp. 161 ◽

Cited By ~ 6

Author(s):

Konstantinos Soulis ◽

Dionissios Kalivas ◽

Costas Apostolopoulos

Keyword(s):

Climate Variability ◽

Spatial Variability ◽

Potential Evapotranspiration ◽

Aridity Index ◽

Data Series ◽

Eu Member States ◽

Daily Data ◽

Agricultural Areas ◽

Soil Climate ◽

The Eu

The Less Favored Areas (LFAs) scheme has existed in various forms since 1975 and it is a broad mechanism supporting rural development in agricultural areas with natural constraints (ANC). Within the programme period 2014–2020, the European Commission developed a common set of biophysical criteria (soil, climate, and terrain) to meet the requirement for a robust and harmonized approach of delimiting ANC throughout the EU Member States. Soil and terrain criteria can be derived directly from soil maps using geospatial analysis techniques based on the provided guidelines. However, the assessment of climatic criteria can be challenging especially in regions characterized by increased spatial variability and data scarcity. In this paper, the assessment of the dryness climatic criterion in a data-scarce region (Greece) as well as the challenges, limitations, and solutions are presented. Daily data-series from 140 meteorological stations for a 30-year reference period were analyzed and the spatial distribution of the precipitation and the potential evapotranspiration for each year were estimated in order to make the final assessment of the dryness criterion. Climate variability and the presence of trends were investigated as well. The obtained results indicated that most of the utilized agricultural area is affected by dryness due to a combination of low precipitation and high evapotranspiration rates. The extreme spatial variability especially in precipitation was also highlighted. An important temporal variability was observed as well, including indications of decreasing trends in precipitation and aridity index. Climate variability and possible trends should be investigated in more detail using longer time series in order to evaluate their impact in agricultural production.

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Spatiotemporal Variations in Gastric Cancer Mortality and Their Relations to Influencing Factors in S County, China

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16050784 ◽

2019 ◽

Vol 16 (5) ◽

pp. 784 ◽

Cited By ~ 2

Author(s):

Cheng Cui ◽

Baohua Wang ◽

Hongyan Ren ◽

Zhen Wang

Keyword(s):

Public Health ◽

Gastric Cancer ◽

Population Density ◽

Influencing Factors ◽

Cancer Mortality ◽

Socioeconomic Development ◽

Environmental Changes ◽

Central China ◽

Environment And Public Health ◽

Spatiotemporal Variations

Increasingly stricter and wider official efforts have been made by multilevel Chinese governments for seeking the improvements of the environment and public health status. However, the contributions of these efforts to environmental changes and spatiotemporal variations in some environmental diseases have been seldom explored and evaluated. Gastric cancer mortality (GCM) data in two periods (I: 2004–2006 and II: 2012–2015) was collected for the analysis of its spatiotemporal variations on the grid scale across S County in Central China. Some environmental and socioeconomic factors, including river, farmlands, topographic condition, population density, and gross domestic products (GDP) were obtained for the exploration of their changes and their relationships with GCM’s spatiotemporal variations through a powerful tool (GeoDetector, GD). During 2004–2015, S County achieved environmental improvement and socioeconomic development, as well as a clear decline of the age-standardized mortality rate of gastric cancer from 35.66/105 to 23.44/105. Moreover, the GCM spatial patterns changed on the grid scale, which was spatially associated with the selected influencing factors. Due to the improvement of rivers’ water quality, the distance from rivers posed relatively larger but reversed impacts on the gridded GCM. In addition, higher population density and higher economic level (GDP) acted as important protective factors, whereas the percentage of farmlands tended to have adverse effects on the gridded GCM in period II. It can be concluded that the decline of GCM in S County was spatiotemporally associated with increasingly strengthened environmental managements and socioeconomic developments over the past decade. Additionally, we suggest that more attentions should be paid to the potential pollution caused by excessive pesticides and fertilizers on the farmlands in S County. This study provided a useful clue for local authorities adopting more targeted measures to improve environment and public health in the regions similar to S County.

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