Spatial and temporal variability of drought during 1960–2012 in Inner Mongolia, north China

Huang, Jin; Xue, Yan; Sun, Shurong; Zhang, Jinchi

doi:10.1016/j.quaint.2014.10.036

Cited by 82 publications

(57 citation statements)

References 24 publications

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“…Figure 10 illustrates the spatial patterns of the rotated loadings of the PDSI_SWAT. A threshold value of 0.5-0.6 on the loadings is reasonable for spatially delimiting the sub-regions which experience similar drought variability in the study period [53]. Figure 11.…”

Section: Pca On Pdsi_swat Time Seriesmentioning

confidence: 73%

Drought Characteristic Analysis Based on an Improved PDSI in the Wei River Basin of China

Zou

Xia

She

2017

Water

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Abstract:In this study, to improve the efficiency of the original Palmer Drought Severity Index (PDSI_original), we coupled the Soil and Water Assessment tool (SWAT) and PDSI_original to construct a drought index called PDSI_SWAT. The constructed PDSI_SWAT is applied in the Wei River Basin (WRB) of China during 1960-2012. The comparison of the PDSI_SWAT with four other commonly used drought indices reveals the effectiveness of the PDSI_SWAT in describing the drought propagation processes in WRB. The whole WRB exhibits a dry trend, with more significant trends in the northern, southeastern and western WRB than the remaining regions. Furthermore, the drought frequencies show that drought seems to occur more likely in the northern part than the southern part of WRB. The principle component analysis method based on the PDSI_SWAT reveals that the whole basin can be further divided into three distinct sub-regions with different drought variability, i.e., the northern, southeastern and western part. Additionally, these three sub-regions are also consistent with the spatial pattern of drought shown by the drought frequency. The wavelet transform analysis method indicates that the El Niño-Southern Oscillation (ENSO) events have strong impacts on inducing droughts in the WRB. The results of this study could be beneficial for a scientific water resources management and drought assessment in the current study area and also provide a valuable reference for other areas with similar climatic characteristics.

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Section: Pca On Pdsi_swat Time Seriesmentioning

confidence: 73%

Drought Characteristic Analysis Based on an Improved PDSI in the Wei River Basin of China

Zou

Xia

She

2017

Water

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“…Ecosystem models can provide a mechanistic understanding of ecosystem function and processes and conduct ''experiments'' to test the relative effects of different drivers on plant productivity (Xiao et al 2009, Tian et al 2011. Ecosystem models can explicitly the effects of climate change (Zhang et al 2014b, Huang et al 2015, Thorn et al 2015 and disturbance (Wang et al 2014. Despite their complexity and mechanistic nature, ecosystem models can lead to substantial uncertainty in plant productivity (Schaefer et al 2012, Raczka et al 2013.…”

Section: Challenges and Limitationsmentioning

confidence: 99%

Contributions of natural and human factors to increases in vegetation productivity in China

2015

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Increasing trends in vegetation productivity have been identified for the last three decades for many regions in the northern hemisphere including China. Multiple natural and human factors are possibly responsible for the increases in vegetation productivity, while their relative contributions remain unclear. Here we analyzed the long‐term trends in vegetation productivity in China using the satellite‐derived normalized difference vegetation index (NDVI) and assessed the relationships of NDVI with a suite of natural (air temperature, precipitation, photosynthetically active radiation (PAR), atmospheric carbon dioxide (CO2) concentrations, and nitrogen (N) deposition) and human (afforestation and improved agricultural management practices) factors. Overall, China exhibited an increasing trend in vegetation productivity with an increase of 2.7%. At the provincial scale, eleven provinces exhibited significant increases in vegetation productivity, and the majority of these provinces are located within the northern half of the country. At the national scale, annual air temperature was most closely related to NDVI and explained 36.8% of the variance in NDVI, followed by afforestation (25.5%) and crop yield (15.8%). Altogether, temperature, total forest plantation area, and crop yield explained 78.1% of the variance in vegetation productivity at the national scale, while precipitation, PAR, atmospheric CO2 concentrations, and N deposition made no significant contribution to the increases in vegetation productivity. At the provincial scale, each factor explained a part of the variance in NDVI for some provinces, and the increases in NDVI for many provinces could be attributed to the combined effects of multiple factors. Crop yield and PAR were correlated with NDVI for more provinces than were other factors, indicating that both elevated crop yield resulting from improved agricultural management practices and increasing diffuse radiation were more important than other factors in increasing vegetation productivity at the provincial scale. The relative effects of the natural and human factors on vegetation productivity varied with spatial scale. The true contributions of multiple factors can be obscured by the correlation among these variables, and it is essential to examine the contribution of each factor while controlling for other factors. Future changes in climate and human activities will likely have larger influences on vegetation productivity in China.

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“…To define and identify extreme drought years, this study adopted the Standardized Precipitation Index (SPI), a drought index that has been widely used worldwide and was relevant to evaluate ecosystem services (Zhang et al, 2009;Zhao et al, 2011;Huang et al, 2014aHuang et al, , 2014b. This approach was designed to monitor droughts based on the long-term monthly precipitation data over a given period (McKee et al, 1993).…”

Section: Defining Top-5 Droughtsmentioning

confidence: 99%

“…This approach was designed to monitor droughts based on the long-term monthly precipitation data over a given period (McKee et al, 1993). After fitting a Gamma distribution and transforming precipitation to a normal distribution by an equal probability transformation, the SPI was estimated as precipitation anomaly divided by the standard deviation of the transformed data (Huang et al, 2014a(Huang et al, , 2014b. The SPI tracks droughts at different time-scales, i.e., 1-, 3-, 6-, 12-, and 24-month, and is flexible with respect to the period chosen (Raziei et al, 2009).…”

Section: Defining Top-5 Droughtsmentioning

confidence: 99%

Drought impacts on ecosystem functions of the U.S. National Forests and Grasslands: Part II assessment results and management implications

Sun

Caldwell

et al. 2015

Forest Ecology and Management

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a b s t r a c tThe 781,000 km 2 (193 million acre) United States National Forests and Grasslands system (NF) provides important ecosystem services such as clean water supply, timber production, wildlife habitat, and recreation opportunities to the American public. Quantifying the historical impacts of climate change and drought on ecosystem functions at the national scale is essential to develop sound forest management and watershed restoration plans under a changing climate. This study applied the previously validated Water Supply and Stress Index model (WaSSI) to 170 NFs in the conterminous U.S. (CONUS) to examine how historical extreme droughts have affected forest water yield (Q) and gross primary productivity (GPP). For each NF, we focused on the five years with the lowest annual SPI3 (Standardized Precipitation Index on a 3-month time scale) during 1962-2012. The extent of extreme droughts as measured by the number of NFs and total area affected by droughts has increased during the last decade. Across all lands in CONUS, the most extreme drought during the past decade occurred in 2002, resulting in a mean reduction of Q by 32% and GPP by 20%. For the 170 individual NFs, on average, the top-five droughts represented a reduction in precipitation by 145 mm yr À1 (or 22%), causing reductions in evapotranspiration by 29 mm yr À1 (or 8%), Q by 110 mm yr À1 (or 37%) and GPP by 65 gC m À2 yr À1 (or 9%). The responses of the forest hydrology and productivity to the top-five droughts varied spatially due to different land-surface characteristics (e.g., climatology and vegetation) and drought severity at each NF. This study provides a comprehensive benchmark assessment of likely drought impacts on the hydrology and productivity in NFs using consistent methods and datasets across the conterminous U.S. The study results are useful to the forestry decision makers for developing appropriate strategies to restore and protect ecosystem services in anticipating potential future droughts and climate change.Published by Elsevier B.V.

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Spatial and temporal variability of drought during 1960–2012 in Inner Mongolia, north China

Cited by 82 publications

References 24 publications

Drought Characteristic Analysis Based on an Improved PDSI in the Wei River Basin of China

Drought Characteristic Analysis Based on an Improved PDSI in the Wei River Basin of China

Contributions of natural and human factors to increases in vegetation productivity in China

Drought impacts on ecosystem functions of the U.S. National Forests and Grasslands: Part II assessment results and management implications

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