Search

This paper aims to investigate the spatial and temporal variation characteristics of the potential evapotranspiration (ET0) and its response to climate change using the collected data from the daily weather observation of 23 meteorological stations in the Beijing-Tianjin-Hebei region for 57 years from 1960-2016. The specific parameters of dataset included the daily average air temperature, the maximum and minimum air temperature, relative humidity, wind speed and sunshine hours. We chose the Penman-Monteith formula to calculate the daily ET0 at each site, and then analyzed the spatial and temporal variation characteristics of the calculated ET0. A sensitivity coefficient was used to quantitatively study the sensitivity of ET0 to various meteorological elements and its spatial and temporal distribution. The contribution rate was set to evaluate the influence of meteorological elements changes on the variation of ET0 during the calculation. The results show that: 1) The spatial distribution of ET0 shows a decreasing trend from south to north across the Beijing-Tianjin-Hebei region, except a high ET0 in the central region, such as Tanggu, Huangye and Baoding stations. There was a linear decline rate of -0.92mm /a. e in the whole distribution of ET0. The spatial distribution of ET0 MK (Penman-Monteith) decreased from the northwest to southeast. In temporal characteristics, spring has the most obvious decrease, followed by autumn, summer, and winter. 2) The sensitivity coefficient of ET0 to the average air temperature, sunshine hours, relative humidity and wind speed are 0.26, 0.28, 0.31 and -044, respectively, indicating the most sensitive to the changes of relative humidity in the Beijing-Tianjin-Hebei region, followed by the wind speed and sunshine hours. The sensitivity coefficient of ET0 to meteorological elements presents in a fluctuating trend from1960-2016, the sensitivity coefficient of ET0 to the wind speed and relative humidity in a downward trend, while the sensitivity coefficient of ET0 to average temperature and sunshine hours in an upward trend. The spatial distribution of the sensitivity coefficient from northwest to southeast: the wind speed and average temperature gradually increased, while the sunshine hours and relative humidity gradually decreased. The spatial distribution characteristics of the sensitivity coefficient of ET0 to relative humidity and average temperature were the opposite situation, where the high sensitivity zone of average temperature belongs to the low sensitive zone of relative humidity. The opposite phenomenon also occurred in the spatial distribution characteristics of the sensitivity coefficient of ET0 to sunshine hours and wind speed sensitivity, i.e., the high sensitivity zone of sunshine hours belongs to the low sensitive zone of wind speed. 3) The contribution rate of meteorological elements to ET0 depends on the sensitivity coefficient and the relative change of meteorological elements. ET0 has the most sensitivity to the changes of relative humidity, but the change rate of the relative humidity was small. ET0 has the lower sensitive to the changes of wind speed, but the change rate of the wind speed was large, resulting the most contribution to ET0 in the whole region was the wind speed. However, the stations number of the wind speed as the dominant factor decreased with the measure time, whereas the stations number of the average temperature as the dominant factor increased with the measure time, especially in the period of 2010—2014 to 2010s, 12 stations with the average temperature as the dominant factor. The stations number of the sunshine hours as the dominant factor also increased with the measured time. It infers that the average temperature and sunshine hours have much significant influences on ET0 in recent years. From 2013 to 2016, the correlation coefficients of the winter average air temperature, sunshine hours, relative humidity, wind speed and PM2.5 concentration were -0.44, -0.53, 0.42 and -0.35, respectively, while the correlation coefficients of ET0 and PM2.5 concentration were -0.37. Therefore, it is possible that the haze, especially winter haze, has a certain impact on meteorological elements, and thereby on ET0 in the Beijing-Tianjin-Hebei region. [ABSTRACT FROM AUTHOR]

Understanding the mechanisms underlying drying-wetting cycles and their consequence for vegetation dynamic is important for sustainable eco-environmental development in alpine regions. We investigated these in this paper by taking the Yarlung Zangbo River (YZR) basin in southeast Qinghai-Tibet Plateau as an example. The standardized precipitation evapotranspiration index (SPEI) in the region was calculated using the global land data assimilation system (GLDAS) from 1982 to 2015 to represent the drying-wetting cycles. The spatiotemporal variation of the dry-wet cycles and the responsive vegetation dynamic was investigated using the remotely sensed NDVI (normal difference vegetation index) from GIMMS (global inventory modeling and mapping studies). The results showed that: 1) Spatiotemporal variation of both precipitation and surface air temperature calculated from GLDAS agreed well with the ground-truth data. 2) The spatiotemporal changes in the dry-wet cycles calculated from the SPEI from 1982 to 2015 showed that the YZR basin became increasingly wet from 1982-1999 but changed course in 2000 and has been become increasingly drier since. In particular, the arid areas showed a tendency of wetting whereas the humid areas tended to become drying. 3) The overall vegetation calculated from the NDVI had been in increase from 1982 to 2000 but changed course in 2000 and has been in decline since. In terms of spatial distribution, areas with higher NDVI value represented vegetation degradation, while areas with lower NDVI represented an improvement in vegetation. 4) Approximately 71.83% of the areas saw a positive correlation between the SPEI and NDVI, mainly in the middle and low reaches of the basin which have a high vegetation coverage. Areas showing negative correlation between SPEI and NDVI were small and not statistically significant. The high consistency between spatiotemporal variation of the NDVI and SPEI indicated that the drying-wetting cycles played an important role in vegetation dynamics. 5) The driving forces of the dry-wet cycles were precipitation, surface air temperature, potential evapotranspiration and soil water content, which were consistent with that estimated from SPEI. In addition, the SPEI showed that soil water content was the dominant factor impacting the drying-wetting in 92.17% of the areas in the region. Results of this study have important implications for evaluating water cycles and the associated vegetation dynamics in alpine regions. [ABSTRACT FROM AUTHOR]

Evaluation of the healthy productivity of cultivated land in China, analysis of key problems of different regions that endangers cultivated land health is of great significance to explore sustainable cultivated land utilization path and safeguard national food security and ecological security. The evaluation of cultivated land healthy productivity should be executed base on integration of existing evaluation indicators system and evaluation method achievements and clarification of key factor states and driving processes that affecting cultivated land health from the perspective of cultivated land components. And interaction characteristics between cultivated land health and cultivated land productivity should be analyzed by coupling them with each other. In this paper, we selected 65 counties (cities) nationwide as research regions with considering the difference of climate conditions in different regions of China, and used 5 categories of indicators including topographic characteristics, soil properties, tillage conditions, environmental conditions and biological characteristics to present the cultivated land health status. And on that basis, we defined critical health threshold and critical sub-health threshold of different indicators by analyzing counties’ indicator standard deviation convergence characteristics and scoring rules. We divided all pilot counties into three statuses: Health, sub-health and unhealth, and analyzed spatial distribution features of counties with different health status. Furthermore, regional climate conditions indicator, cultivated land natural conditions indicator and tillage technique level indicator had been synthetically integrated to evaluate the productivity of cultivated land, and regional cultivated land health-productivity interaction characteristic had been analyzed. Experimental result showed that counties whose cultivated land in sub-healthy or unhealthy status expressed significant regional features, and the key factors of limiting cultivated land health were different among pilot counties. On the one hand, the sub-health status cases caused by inferior farming conditions indicator were more common (accounting for nearly 40% of pilot counties) than other indicators, which was not only manifested by serious fragmentation of cultivated land and imperfect farmland infrastructure, but also reflected the urgent requirement for promoting high-standard farmland construction. On the other hand, the form of biological characteristics was severe, indicating that under the interaction of climatic conditions, soil structure and tillage technology, the ability of cultivated land to guarantee the healthy growth of animals was facing degradation. Furthermore, through coupling analysis of cultivated land health and cultivated land productivity, we divided the cultivated land healthy productivity characteristics of pilot counties into six categories: “health-high productivity”, “health-low productivity”, “sub-health-high productivity”, “sub-health-low productivity”, “unhealth-high productivity” and “unhealth-low productivity”, and respectively analyzed the regional farmland protection directions for each category. “Sub-health/unhealth-high productivity” type was widely distributed, which was the core region for implementation of “storing grain on land and storing grain in technology” strategy in China. Therefore, it is necessary to give consideration to the health and productivity of cultivated land in this region, and strengthen the research and practice on methods to improve the health of cultivated land. This study provides scientific basis for improving cultivated land healthy productivity and provides effective support for designing protection paths of cultivated land resources in different regions. [ABSTRACT FROM AUTHOR]

Drought has become a problem that is universally faced by global terrestrial ecosystems. Northeast China is dominated by a temperate monsoon climate and located in an area sensitive to global climate changes, and one of the main impacts of climate changes in Northeast China is manifested as drought in growing seasons. The drought area has a gradual increase trend, and drought has become the main agro-meteorological disaster in this region which is also the main maize planting area in China. Drought normalization seriously restricts the stable development of maize production in Northeast China. So in this paper, we took spring maize in Liaoning Province as an example and made clear the drought variation characteristics in different growth stages by using the data of MODIS, FY-3A, relative soil moisture and growth stages and the methods of RS, GIS and statistical analysis. Then we analyzed the correlation between multi-time scale remote sensing indexes and relative soil moisture in different soil depth, and established the remote sensing monitoring index set and models of relative soil moisture for each growth stage and soil depth. The accuracy of the monitoring models was verified and the application research of monitoring the drought of spring maize in Liaoning Province was studied. The results showed that: From 1993 to 2012, drought occurred in each growth stage of spring maize in Liaoning Province and the highly frequent drought occurred in the period from 1999 to 2002. The drought grade in each year was mainly light drought, and the drought was the most serious at milk stage, followed by heading stage. There was no significant correlation between the monitoring indexes and relative soil moisture at sowing and emergence stage, but there was a significant or extremely significant correlation between them at three-leaf and maturity stage. The monitoring index LSWI (land surface water index) had a strong ability to monitor relative soil moisture, followed by WI (water index). Multi-index coordination could improve the monitoring ability of relative soil moisture by remote sensing means, and the monitoring ability at 10-day scale was generally higher than that at 5-day scale and 20-day scale. Based on the monitoring models of soil relative humidity, the drought condition of partial growth stages and soil depth from 2001 to 2004 was monitored. The overall monitoring accuracy was 73.32%, in which the monitoring accuracy of jointing and three-leaf stage was more than 85%. The dynamic monitoring of drought grades in different growth stages in 2000 was realized. The monitoring results were consistent with the agro-meteorological observation records in terms of the growth stages and space. This study would be very significant to improve the capacity of disaster prevention and mitigation by monitoring spring maize accurately and synchronously on a large range. [ABSTRACT FROM AUTHOR]

Evaluation of the healthy productivity of cultivated land in China, analysis of key problems of different regions that endangers cultivated land health is of great significance to explore sustainable cultivated land utilization path and safeguard national food security and ecological security. The evaluation of cultivated land healthy productivity should be executed base on integration of existing evaluation indicators system and evaluation method achievements and clarification of key factor states and driving processes that affecting cultivated land health from the perspective of cultivated land components. And interaction characteristics between cultivated land health and cultivated land productivity should be analyzed by coupling them with each other. In this paper, we selected 65 counties (cities) nationwide as research regions with considering the difference of climate conditions in different regions of China, and used 5 categories of indicators including topographic characteristics, soil properties, tillage conditions, environmental conditions and biological characteristics to present the cultivated land health status. And on that basis, we defined critical health threshold and critical sub-health threshold of different indicators by analyzing counties’ indicator standard deviation convergence characteristics and scoring rules. We divided all pilot counties into three statuses: Health, sub-health and unhealth, and analyzed spatial distribution features of counties with different health status. Furthermore, regional climate conditions indicator, cultivated land natural conditions indicator and tillage technique level indicator had been synthetically integrated to evaluate the productivity of cultivated land, and regional cultivated land health-productivity interaction characteristic had been analyzed. Experimental result showed that counties whose cultivated land in sub-healthy or unhealthy status expressed significant regional features, and the key factors of limiting cultivated land health were different among pilot counties. On the one hand, the sub-health status cases caused by inferior farming conditions indicator were more common (accounting for nearly 40% of pilot counties) than other indicators, which was not only manifested by serious fragmentation of cultivated land and imperfect farmland infrastructure, but also reflected the urgent requirement for promoting high-standard farmland construction. On the other hand, the form of biological characteristics was severe, indicating that under the interaction of climatic conditions, soil structure and tillage technology, the ability of cultivated land to guarantee the healthy growth of animals was facing degradation. Furthermore, through coupling analysis of cultivated land health and cultivated land productivity, we divided the cultivated land healthy productivity characteristics of pilot counties into six categories: “health-high productivity”, “health-low productivity”, “sub-health-high productivity”, “sub-health-low productivity”, “ill-health-high productivity” and “ill health-low productivity”, and respectively analyzed the regional farmland protection directions for each category. “Sub-health/ill-health-high productivity” type was widely distributed, which was the core region for implementation of “storing grain on land and storing grain in technology” strategy in China. Therefore, it is necessary to give consideration to the health and productivity of cultivated land in this region, and strengthen the research and practice on methods to improve the health of cultivated land. This study provides scientific basis for improving cultivated land healthy productivity and provides effective support for designing protection paths of cultivated land resources in different regions. [ABSTRACT FROM AUTHOR]

The greenhouse climate model has the characteristics of nonlinearity, strong disturbance and time variance. The commonly used methods to deal with the complex model are to linearize the original nonlinear models or to do some offline identification research. Without considering the complex characteristics completely, the usual modeling methods cannot predict the greenhouse climate dynamic behaviour effectively. In this paper, on account of the complex characteristics of greenhouse climate system, taking the temperature model as the example, the continuous-discrete recursive error algorithm was used to identify combined parameter and state online. Firstly, describe the greenhouse temperature model. The greenhouse temperature is affected by the heat load imposed on the greenhouse by the sun, the energy lost to the external air because of transmission through the greenhouse cover, the heat transfer between the internal air and soil, the heat loss by crop transpiration, the heat lost through natural ventilation of the roof windows and the energy supply from the heating system. In all of the model parameters, due to the fact that external solar radiation has a great effect on greenhouse temperature, radiation conversion factor changes over time and the parameters related to heating and ventilation are fundamental but difficult to obtain, this paper attempted to estimate and update 5 key parameters online. Secondly, continuous-discrete recursive prediction error algorithm to estimate combined parameters and states online was developed. This algorithm is appropriate for a continuous-discrete system, which is defined as a dynamic system with a continuous state function, and the observation function is discrete. The algorithm estimates the parameters and states by minimizing the error sum of squares between predicted values and measured values, which is usual in this technology. Compared with other traditional estimation algorithm such as the extended Kalman filter, the big difference of the algorithm is that there is no need to set the initial value of system noise precisely. It defines the system noise in real time by introducing an extra parameter as gain matrix and estimating it online. The algorithm adjusts the system noise to match the model predicted values and actual values by regulating the gain matrix. As estimating the system noise for the greenhouse temperature system beforehand is extremely difficult, the advantage of the proposed algorithm enhances the feasibility of its application in practice. At last, in order to test the developed algorithm, the model identification results were compared between the continuous-discrete recursive prediction error algorithm and the extended Kalman filter in MATLAB. The simulation was based on the measured data containing outside temperature, outside solar radiation, control inputs and temperature of an experiment greenhouse. The results showed that the proposed algorithm could lead to a higher model fit value of 93.7% compared with 89.5% of the extended Kalman filter. The gain matrix varied from zero to non-zero, and it nearly maintained stable at a non-zero constant in the end of each test day. The changing process indicated that there were errors between the model predicted value and the measured value in the initial, and the errors could be compensated by regulating the gain matrix. The different values of gain matrix in 2 days showed that system noise may vary largely in different condition and it should not be set as a constant. From the simulation results and the data analysis, it can be known that the proposed continuous-discrete recursive prediction error algorithm can estimate the temperature well and improve the model accuracy and validity. [ABSTRACT FROM AUTHOR]

Under the background of changing global environment and frequent anthropogenic activities, rainfall-runoff relationship has suffered tremendous change in many regions of China, particularly in arid and semi-arid regions. The Jinghe River basin (JRB) in the middle of the Loess Plateau, which is the major base of grain production in Shannxi Province, has experienced significant changes in hydro-climatic variables and the relationship between them during the past decades, causing many water resources problems. In this paper, we focused on analyzing the variation characteristics of rainfall-runoff relationship in JRB, and quantitatively assessing the effects of climate changes and human activities on the runoff reduction. It was of great importance for mastering the evolution of hydrological cycle, water resources planning and management, and water and soil conservation in JRB. The monthly rainfall and runoff data were used in the study and summed annually to investigate the variation characteristics in 1960-2010. To detect the change points of rainfall-runoff relationship, the sliding partial correlation coefficients method was proposed and the change points were further confirmed by the double mass curve method. On the basis of the studies, the relative changes of rainfall, runoff, and rainfall-runoff relationship were analyzed around the change points. Moreover, we also introduced the Archimedean Copula function, from the perspective of probability, to analyze the probability of synchronous-asynchronous encounter of rainfall and runoff in JRB. What caused the variation of rainfall-runoff relationship? Climate change or human activities? To figure out this, the method of slope change ratio of cumulative quantity (SCRCQ) was adopted in this paper. According to these results, we obtained the following conclusions: (i) Annual runoff and rainfall presented wavelike decrease change. Nevertheless, annual runoff declined more greatly than rainfall; especially, in some periods annual rainfall increased, however, runoff decreased. This illustrated that some non-rainfall factors caused the occurrence of phenomenon in JRB; (ii) Change points of rainfall-runoff relationship occurred in 1996 validated by the sliding partial correlation coefficients method and double mass curve method. Meanwhile, we could ascertain the conclusion by the evidence of the process of human activities in JRB, which presented the increasing industrial, agricultural and domestic water consumption and large-scale water conservancy and soil conservation projects since 1990s; (iii) To compare the magnitude of the changes of rainfall, runoff and rainfall-runoff relationship, the hydrological variables series were divided into the periods of 1960-1996 and 1997-2010. Compared to runoff and rainfall in 1960-1996, the annual mean runoff and rainfall in 1997-2010 dropped 43.47% and 6.64%, respectively. The change of monthly rainfall had no significance in different periods. On the contrary, monthly runoff decreased more greatly and the difference was smaller in each month i.e. the runoff distribution for each month was more uniform. The correlation between rainfall and runoff diminished and runoff yield decreased under the same rainfall. When precipitation was above 400 mm, the relative change rate of runoff was above 40% in 1997-2010 compared to that in 1960-1996; (iv) The joint distributions of rainfall and runoff constructed by the Archimedean Copula function were different in 1960-1996 and 1997-2010, and the distributions in the 2 periods were fitting Clayton and Gumbel-Hougaard Copula better, respectively. The probabilities of synchronous-asynchronous encounter of the same rainfall and runoff changed strikingly in different periods. For instance, when rainfall was less than 550 mm and runoff was less than 40 mm, the probability of synchronous-asynchronous encounter was 44% in 1960-1996 and 73% in 1997-2010; (v) In JRB, human activities, i.e. non-rainfall factors, have played a fundamental role in rainfall-runoff relationship change. Further compared with some research results, the irrigation, the construction of reservoirs and the water-and-soil conservation measures in the region should be responsible for the change to a large extent. Compared to the period of 1960-1996, the contribution from human activities in the period of 1997-2010 reached about 81% and climate change was merely around 19% obtained by the method of SCRCQ. The research results can provide theoretical basis for water resource management and water and soil conservation for the administrators. [ABSTRACT FROM AUTHOR]

The changes of lake water resources record the impacts of climate change and human activities on the regional hydrological processes in the changing environment. Especially for inland areas with less precipitation, timely and accurate information on changes in lake water resources are recorded. Environmental evolution has an important reference value. With China’s largest desert freshwater lake-Hongjiannao Lake as an example, based on the 3S (RS, GIS, and GPS, which are remote sensing, global position system, geographic information system) technology, lake water surface area change was analyzed, which provided important scientific guidance for the restoration, protection and utilization of ecological and economic functions of Hongjiannao Lake. However, due to the different sources of data, the uneven technology, the discontinuous time series and the generally short time series, as well as the different monitoring phases, the result analysis on the change of water area of Hongjiannao Lake is quite different and systematic study and overall analysis of long time series of the entire river basin are lacking. Fifteen periods of both basic and RS data collected for Hongjiannao Lake, such as DRG, DLG, DOM, remote sensing images, and paper maps, were selected for analysis over a recent 60-year period (from 1957 to 2015), together with field annotation data and relevant attributes. All the data and images above have passed the geometric correction of digital elevation model data from Shaanxi Surveying and Mapping Archives and Geological Information Bureau of State Bureau of Surveying and Mapping, which have good quality. Different data can meet the high-precision registration requirements of water body information extraction in the study area. Among them, NDWI (normalized difference water index) with better extraction effect was used to extract water body information, which could restrain the vegetation soil while enhance the water body information. To analyze characteristics in spatio-temporal variations and identify trends of the change in lake water area over the period, we comprehensively utilized RS and GIS techniques and adopted spatial data processes, extracted and interpreted information, constructed a massive database, and conducted integrated management and analysis. We also explored major causes that triggered spatio-temporal variations of lake water area by combining climate change and anthropogenic factors from the same period. Results indicated that in a recent 60-year period, the area covered by water significantly changed in the study area. During 1957-1976, the water area continuously increased from 37.6 to 55.53 km2, and reached the maximum value over the entire record of study with increased amplitude of 47.69%. The growth rates in northern and southeastern areas of the lake were relatively fast, followed by other regions. During 1977-1999, the overall water area was stable, approximately 50 km2. During 2000-2015, water area showed a decreasing trend year by year, from 50.27 to 31.05 km2 with decreased amplitude of 38.23%, and all regions showed this shrinking trend except waters near Qibusu River in 2005, in which the reverse occurred and the water area slightly increased. In general, over the last 60 years, the revolution process of the water area of Hongjiannao Lake could be divided into 3 phases corresponding to the annual variability of water area: expanding period (1957-1976), stabilizing period (1977-1999), and shrinking period (2000-2015), showing an overall shrinking trend. The area of lakes and waters has experienced a dynamic trend of expansion-stabilization-atrophy in the recent 60 years, and has shown a significant atrophy situation since 1999 and a strong signal of ecological and hydrological deterioration, deserving attention. Trends in both warming and drying climate may be the major factors, which affect lake water area variation in both expanding and stabilizing periods, and the superimposition of these trends with anthropogenic effects (i.e. a water conservation project construction in the upper streams, coal mining, pavement construction around the lake, and water consumption for irrigation) may be the essential factor leading to water area variations during the shrinking period. [ABSTRACT FROM AUTHOR]

In order to study the driving factors of irrigation water requirement and find the effective measures for relieving the sharp contradiction between the supply and demand of agriculture water resources, in this paper the factors decomposition model for irrigation water requirement was established based on the extended Kaya equation. The logarithmic mean Divisia index (LMDI) decomposition method was used to quantitatively analyze the driving factors for changes in irrigation water requirement. The change of irrigation water requirement was decomposed into 4 driving factors including planting scale effect, planting structure effect, climate change and water saving engineering effect. The irrigating quota of crop and irrigation water utilization coefficient reflected the climate change and water saving engineering, respectively. Two different decomposition methods of LMDI, addition decomposition and multiplication decomposition, were applied to calculate the effect value of the 4 driving factors for irrigation water requirement change. The irrigation water requirement from 1995 to 2012 in Wuwei city, Gansu Province was taken as an example. The effect values of 4 driving factors were calculated in different periods from 1995 to 2012. The results showed that during 1995-2012, the planting structure in Wuwei city was adjusted by reducing the planting area of wheat and increasing planting area of maize and cotton consuming less irrigation water than wheat. The amount of irrigation water requirement in 2012 was decreased by 5.023×108 m3 in Wuwei city than that in 1995 including an increase of 2.435×108 m3 caused by the planting scale effect, and the decrease of 3.994×108 m3, 1.286 ×108 m3, 2.178×108 m3 for the planting structure effect, the climate change effect, and the water saving engineering effect, respectively. The adjustment of planting structure was the most important factor for the decrease of the irrigation water requirement. From the effect value of different crops in the counties of Wuwei city, each crop had different effect on the change in irrigation water requirement. Wheat had the negative impact on the irrigation water requirement change and played a prominent role in decreasing the irrigation water requirement during 1995 to 2012. Among the 4 driving factors for the same crop, for most crops the planting structure effect was stronger than the others in all the regions. In addition, 4 driving factors in different periods played different role in changing irrigation water requirement in the counties of Wuwei city. However, the planting structure always had the inhibitory effect on increasing irrigation water requirement obviously in all the regions and periods except for Liangzhou in 2000-2005.. Water saving engineering had the positive effect on increasing irrigation water requirement in Wuwei city, Liangzhou county and Minqin county during 2005-2012. The main reason was a decrease in irrigation water utilization coefficient. Therefore, improving the efficiency of irrigation water utilization and controlling agricultural development scale are effective measures for saving irrigation water in Wuwei city. [ABSTRACT FROM AUTHOR]

Under the background of frequent anthropogenic activities and global environment change, it is necessary to carry out the study of future climate change, for understanding of the characteristics of temporal and spatial evolution of future climate is of great significance to agricultural production and local water resources planning and management. Located in the middle of the Loess Plateau, China, the Jinhe River basin, the second largest river in Guanzhong area, is the major base of grain production in Shaanxi Province, which has flat land and developed agriculture since ancient times. With the establishment of the Guanzhong-Tianshui economic zone, which is a national key economic development zone and will greatly promote the rapid development of the economy in the whole western region, the security of water resources in Jinhe River basin is becoming more and more important for the economic development and local peace and stability. Therefore, in this paper, we took Jinhe River basin as the research object. Then the variation characteristics of rainfall and temperature in the future were focused and analyzed by using downscaling method and CMIP5 (coupled model intercomparison project 5) global climate models, which were applied to simulate and predict climatic elements in Jinghe River basin. There were 3 steps to establish the statistical downscaling models: firstly, determinate forecast factors based on the relationship between the factors and rainfall as well as the air temperature; then normalize the forecasting factors in the NCEP (national centers for environmental prediction) reanalysis data; eventually based on the reanalysis data and historical meteorological observation data of monthly precipitation and temperature from 7 weather stations in or around the basin from 1960 to 2010, the models were set up through screening major factors by using stepwise regression. In order to evaluate the effect of the model, the fitting degree R2, the relative error of the mean Rmean and the relative error of standard deviation Rsd were selected as the evaluation index. These models were calibrated so that the results could be satisfactory. Then, on the foundation of the calibrated models, future precipitation and temperature in the Jinhe River basin were predicted by atmospheric circulation factors came from CMIP5 experiments: the RCP8.5 (highest emission of greenhouse gases) and RCP4.5 (median emission of greenhouse gases) forcing pathways under CNRM-CM5. Finally, we analyzed the characteristics of temporal and spatial of future precipitation and temperature in the basin. The results show that: (1) The statistical downscaling models function better in simulating temperature than precipitation with higher fitting degree and lower relative error in average and standard deviation; (2) Precipitation in the basin from 2011 to 2050 showed a decreasing trend from south to north direction, and would increase only in winter with different magnitudes under 2 scenarios; moreover, the annual average precipitation was 356.41 mm under the RCP8.5 scenario, which was lower than RCP4.5 forcing pathway (374.19 mm); (3) The predicted temperature in the future was much higher under RCP8.5 scenario (9.32℃) compared to RCP4.5 scenario (8.96℃) because of greenhouse gas emission with different concentration; spatial distribution of future temperature in Jinghe River basin was characterized by higher in the north and west; besides, temperature in the basin would decrease in the late winter and early spring, but significantly increase in summer, and it was inferred that there was the possibility of occurrence of extremely high temperature in summer and extremely low temperature in winter. In conclusion, there is not only a trend of decreasing in precipitation, but also a risk of extreme weather events in Jinghe River basin, which should be paid attention to in the future water resources management and planning. [ABSTRACT FROM AUTHOR]

Fluctuation of animal husbandry system (FAHS) can affect not only the sustainability of farmers' livelihood, but also the stability of regional ecosystem. Characteristics of FAHS and its driving factors in Yanchi County, Ningxia Hui Autonomous Region, which was a typical agro-pastoral zone, were studied and discussed in this paper. According to previous research results and our surveys, total number of sheep was defined as the dependent variable and 10 driving factors were defined as the independent variables, namely, average annual precipitation, average annual temperature, effective irrigated area, grain acreage, gross output of grain, afforestation area, grassland area, vegetation index, agricultural labor force and per capita net income of farmers. Then, the empirical mode decomposition (EMD), which is a powerful method for analyzing the nonlinear and non-stationary time series data, was used to analyze the variability of animal husbandry system and its driving factors. The time series data of total number of sheep and its 10 driving factors from 1954 to 2013 were decomposed into several intrinsic mode functions (IMFs) and a residual trend respectively. Meanwhile, the set pair analysis (SPA) method was used to analyze the contribution of each driving factor to FAHS. Here, 3 IMFs that were decomposed from total number of sheep and the corresponding IMFs that were decomposed from each driving factor were input in the set pair analysis model, and the relationship between FAHS and its driving factors was obtained by this method. The results showed: 1) The total number of sheep increased significantly with an annual fluctuation during the past 60 years and its coefficient of variation was moderate. The total number of sheep had 3 IMFs and its 10 driving factors had 2-5 IMFs. The most of IMFs had the fluctuant periods of 3-4, 7-15, 22-26 and 40-45 years respectively. The IMFs that had the fluctuant period of 22-26 years and the biggest variance contribution were the most important components that were decomposed from the total number of sheep. 2) The fluctuation of the total number of sheep mainly depended on grain acreage, followed by average annual precipitation, and the contribution rate of both driving factors accounted for 75%. The fluctuation of the number of sheep was also weakly affected by average annual temperature, gross output of grain and total output and afforestation area. 3) In these IMFs that were decomposed from total number of sheep, the one that had a longer fluctuation period was affected more seriously by agriculture. In contrast, the one that had a shorter fluctuation period was affected more seriously by climatic factors. Economic and social factors had limited effect on the fluctuations of the total number of sheep. 4) Climatic factors such as average annual precipitation and average annual temperature mainly drove the fluctuation of the total number of sheep. In contrast, grain total output and annual afforestation area had a reverse effect to the total number of sheep. Other 6 factors including effective irrigated area, grain acreage, grassland area, vegetation index, agricultural labor force and per capita net income of farmers had bi-directional effects on the total number of sheep. Based on above analyses, we suggest that the sustainable development for animal husbandry system in Yanchi County is constructing an effective agro-forestry-animal composite husbandry system in this typical agro-pastoral zone. In particular, developing appropriate scale and efficient farmland and feed shrub stands is very important to maintain the stability of animal husbandry system. [ABSTRACT FROM AUTHOR]

Climate change, as one of the most important environmental issues, has become an increasing global concern to scientists, policy makers, and the public. Paddy soils are a dominant source of N2O emissions. Agricultural management practices (e.g., water regime, fertilizers management, tillage) have important impacts on N2O emissions due to the changing microenvironment of paddy fields that can affect the processes of soil nitrification and denitrification. This paper summaried current literatures on the influence of these practices on N2O production and emission and their corresponding mechanisms in rice fields. At present, the generation and the pathway of N2O emission from paddy soils are clarified. Nevertheless, the current information on the action of farming management practices on N2O indirect emission is limited. The fertilizer application rate, the various types of fertilizers, and the varying timing and placement of application have a significant effect on the N2O emissions of paddy fields due to the different supplementation of nitrate and ammonium substrate in the processes of nitrification and denitrification. Generally, N2O emissions increase with increasing nitrogen (N) fertilizer rate. Previous studies showed that applying N fertilizer deeper can decrease N2O emissions compared to surface application. Water regime exerts substantial influence on N2O emission through the changes in oxidation and reduction in paddy soil layers during rice cropping. The mid-season aeration and drying-wetting alternation can stimulate N2O generation and emissions from paddy soils. Tillage and residue management practices can also affect nitrification and denitrification due to the change of soil characteristics. However, cultivation patterns do not have significant impacts on N2O emissions from paddy fields in current studies. Further research is needed to study the long-term effects of cultivations on N2O emissions. Most studies showed that N2O emissions decrease by incorporating biochar into paddy soils, but inconsistent results have also been reported. In addition, models (e.g., DNDC, CENTURY) are good options to simulate the effects of alternative agricultural practices on N2O emission from paddy fields and to identify potential strategies for climate change mitigation. In addition, the different effect of farming management practices on N2O emission may be presented based on the difference of many factors (e.g., climate conditions, soil types). An immense challenge to find ways to reduce N2O emission from paddy soils lies ahead for the scientific community and policy makers. Researchable priorities should be: 1) to implement exhaustive research on mechanisms that new agricultural management practices affect N2O generation and its emission pathways; 2) to assess effect of agricultural practices on the direct and indirect N2O emissions from paddy fields and their mechanisms; 3) to make in-depth studies on characteristics of N2O emission in technologies with integration of various farming practices; and 4) to simulate and forecast impacts of agricultural practices on N2O emissions in paddy ecosystems. Integrated farming approaches that exert a crucial role in the reduction of N2O emissions from paddy soils are necessary to be explored to mitigate the consequences of climate change on our planet. [ABSTRACT FROM AUTHOR]

The Yellow River flows through an extensive aeolian alluvial plain in Ningxia and Inner Mongolia plateau, which extends from Xiaheyan in Ningxia to Toudaoguai in Inner Mongolia. The Hedong sandy land, the Ulanbuh Desert and the Kubuqi Desert all border on the Yellow River. Frequent strong winds and erodible surfaces cause extreme wind-erosion process in the watershed of Ningxia-Inner Mongolia reach of the Yellow River. A large amount of aeolian sediment flows into the main stream and tributaries of the Yellow River by particle saltation and dune avalanche, which result in the continuous elevation of riverbed. Especially since 1986, the combined operation of Longyangxia Reservoir and Liujiaxia Reservoir has decreased the number and discharge of the flood crest, and lowered the erosiveness of the flow in the upper reach of the Yellow River. In this situation, the siltation of the Ningxia-Inner Mongolia reach of the Yellow River is severer and severer. To resolve the silting problem in this reach, it is urgent to estimate the spatial and temporal variations of wind erosion hazards and the quantities of aeolian sediment fed into the river in this watershed. In this study, the models of IWEMS (integrated wind-erosion modelling system) and RWEQ (revised wind erosion equation) were selected to estimate the wind erosion modulus in this watershed. The observed data in the field in 2011 and 2012 were used to calibrate the models, and the calibration result showed that the simulation accuracies of the 2 models were both satisfactory. Using the calibrated models, the wind erosion moduli in this watershed were obtained. The results showed that the wind erosion moduli in this watershed ranged from 0 to 27 780.6 t/(km2-a) in the period from 1986 to 1995, from 0 to 33 673.1 t/(km2-a) during 1996-2002, from 0 to 37 251.3 t/(km2-a) in the period from 2003 to 2007, and from 0 to 16 111.4 t/(km2-a) in the period from 2008 to 2013, respectively. Since 1986, the wind erosion hazards mainly occurred in the sandy lands such as the Ulanbuh Desert, the Kubuqi Desert and the Hedong sandy land. The wind erosion modulus of the Hedong sandy land gradually dropped from 1986 till now, but the wind erosion modulus of the Ulanbuh Desert was increasingly highlighting in this period, and this desert became to the region with severest wind erosion hazard in the whole watershed. The results also showed that the areas having wind erosion risk in the watershed of the Ningxia-Inner Mongolia reach of the Yellow River were diminishing gradually in these years. The average wind erosion modulus of this watershed was also decreasing, and the fitting regression function between average wind erosion modulus and time showed that the slope was high to -182.81. Based on the estimated wind erosion modulus in watershed of Ningxia-Inner Mongolia reach of the Yellow River, the quantities of aeolian sediment blown into the different reaches of the Yellow River were calculated by aeolian sediment transport equations. The results showed that the Shizuishan- Bayangol reach had the highest value, and the average quantity of aeolian sediment blown into the Yellow River was 9.31 x 106 t/a. The quantity in the Xiaheyan-Qingtongxia reach was lowest, and it was only 7.6 x 105 t/a. Excluding in Shizuishan- Bayangol Reach, in the other reaches, the quantities of aeolian sediment blown into the river did not show the trend of obviously decreasing with time. Through analyzing the relationship between wind erosion modulus and changes of climate and land use, we found the dropping wind erosion modulus in watershed of Ningxia-Inner Mongolia reach of the Yellow River was mainly affected by the climate change. The study results in this paper are not only meaningful for solving the siltation in Ningxia-Inner Mongolia reach of the Yellow River, but also important to the complete the protection systems of wind-blown hazards in this watershed. [ABSTRACT FROM AUTHOR]

Cultivated land is an important indicator of landscape changes driven by human activities. Mapping the spatio-temporal changes of cultivated lands will help us to understand its corresponding environmental and ecological changes in their downstream areas. The Manas drainage basin is the key area of agricultural region in the northern slope of the Tianshan Mountains. However, the drastic farmland reclamation in the last 50 years makes irrigation water increasing rapidly, leading to environmental degradation in the downstream of the Manas River. In this paper, remote sensing and GIS technologies are used to analyze the spatio-temporal characteristics of farmland changes in the Manas drainage basin under the condition of intense soil-water utilization. Firstly, remote sensing images in 1962, 1977, 1989, 2000 and 2010 are applied to map land use changes with the cognition classification software and manual edition. Then the temporal process and spatial pattern of land cover changes are analyzed by geo-statistics and landscape analysis. On the temporal scale, the cultivated land changes and its mutual transition relationships with other land types are analyzed with areal ratio and transition matrix methods; on the spatial scale, GIS spatial analysis tool and landscape class level index are used to describe the characteristics of farmland expansion or shrinking changes in different regions and different land patches. Finally, hydrological data and irrigation construction data are used to explain the impact of climate change and human activities on the farmland landscape. The results show that: (1) The overall land use changes of the Manas drainage basin in the last 50 years are as follows: cultivated land and built-up areas increase continuously, while the unutilized land, wetland and snow/glacier have been decreasing steadily; grassland area is increasing in the former 20 years and then decreasing gradually in the last 30 years; the intensity of land use changes keeps stable after dramatic changes. (2) The overall cultivated land transformations have shifted from outward and inward transformations to single inward transformation; in inward land types, grassland and unutilized land are the main inward land types to farmland, and woodland and wetland take larger percentages in the first 20 years, while less percentages in the later 30 years; in outward land types, built-up land and grassland are the main outward land types, and grassland and unutilized land have larger percentages in the former 20 years due to cultivated land degradation; the total area of inward land types far exceeds than that of the outward land types, and the cultivated land area is steadily increasing in the last 50 years. (3) The focus of cultivated land expansion has shifted from the margins of cities to desert regions, and the newly-increased farmland gradually from the upstream to the downstream; cultivated land expansion firstly begins at the Changji Hutubi and Manas County in the former 20 years, then shifts to Shawan County, the river's surrounding areas and northern deserts; the cultivated landscapes are characterized from discrete and messy pieces into continuous land patches, so the advantage of cultivated landscape is increasing, while the landscape diversity and heterogeneity are decreasing due to land parcel combinations. (4) The increasing precipitation and runoff in the Manas drainage basin provide more water resource for cultivated land reclamation, and reservoir and irrigation channel construction have positive effects on spatial expansion of the cultivated land; when reservoirs and channels are built up, cultivated land will expand correspondingly in a rapid rate in the next decade, and hence the spatio-temporal processes of farmland expansion have high relations with the irrigation facilities. (5) The increasing water resource induced by climate change cannot keep up with the increasing speed of the farmland, and water resource is in the state of over exploitation; measures must be taken to reduce the amount of irrigated water, so as to improve ecological environments in the downstream of the Manas River. [ABSTRACT FROM AUTHOR]

Cultivated land is an important indicator of landscape changes driven by human activities. Mapping the spatio-temporal changes of cultivated lands will help us to understand its corresponding environmental and ecological changes in their downstream areas. The Manas drainage basin is the key area of agricultural region in the northern slope of the Tianshan Mountains. However, the drastic farmland reclamation in the last 50 years makes irrigation water increasing rapidly, leading to environmental degradation in the downstream of the Manas River. In this paper, remote sensing and GIS technologies are used to analyze the spatio-temporal characteristics of farmland changes in the Manas drainage basin under the condition of intense soil-water utilization. Firstly, remote sensing images in 1962, 1977, 1989, 2000 and 2010 are applied to map land use changes with the cognition classification software and manual edition. Then the temporal process and spatial pattern of land cover changes are analyzed by geo-statistics and landscape analysis. On the temporal scale, the cultivated land changes and its mutual transition relationships with other land types are analyzed with areal ratio and transition matrix methods; on the spatial scale, GIS spatial analysis tool and landscape class level index are used to describe the characteristics of farmland expansion or shrinking changes in different regions and different land patches. Finally, hydrological data and irrigation construction data are used to explain the impact of climate change and human activities on the farmland landscape. The results show that: (1) The overall land use changes of the Manas drainage basin in the last 50 years are as follows: cultivated land and built-up areas increase continuously, while the unutilized land, wetland and snow/glacier have been decreasing steadily; grassland area is increasing in the former 20 years and then decreasing gradually in the last 30 years; the intensity of land use changes keeps stable after dramatic changes. (2) The overall cultivated land transformations have shifted from outward and inward transformations to single inward transformation; in inward land types, grassland and unutilized land are the main inward land types to farmland, and woodland and wetland take larger percentages in the first 20 years, while less percentages in the later 30 years; in outward land types, built-up land and grassland are the main outward land types, and grassland and unutilized land have larger percentages in the former 20 years due to cultivated land degradation; the total area of inward land types far exceeds than that of the outward land types, and the cultivated land area is steadily increasing in the last 50 years. (3) The focus of cultivated land expansion has shifted from the margins of cities to desert regions, and the newly-increased farmland gradually from the upstream to the downstream; cultivated land expansion firstly begins at the Changji Hutubi and Manas County in the former 20 years, then shifts to Shawan County, the river's surrounding areas and northern deserts; the cultivated landscapes are characterized from discrete and messy pieces into continuous land patches, so the advantage of cultivated landscape is increasing, while the landscape diversity and heterogeneity are decreasing due to land parcel combinations. (4) The increasing precipitation and runoff in the Manas drainage basin provide more water resource for cultivated land reclamation, and reservoir and irrigation channel construction have positive effects on spatial expansion of the cultivated land; when reservoirs and channels are built up, cultivated land will expand correspondingly in a rapid rate in the next decade, and hence the spatio-temporal processes of farmland expansion have high relations with the irrigation facilities. (5) The increasing water resource induced by climate change cannot keep up with the increasing speed of the farmland, and water resource is in the state of over exploitation; measures must be taken to reduce the amount of irrigated water, so as to improve ecological environments in the downstream of the Manas River. [ABSTRACT FROM AUTHOR]

There is an important significance for China's food security to explore the fluctuation characteristics and influence factors of grain output per sown area (hereinafter referred to as grain yield), and then to take corresponding measures to stabilize and improve the grain yield level. In this paper, the time-series yields of grain and main crops (rice, wheat and maize) from 1978 to 2012 in China were decomposed using empirical mode decomposition (EMD) method, and then multi-scale fluctuation characteristics and its main influence factors of grain yield were analyzed. The results showed: 1) the time series of grain yield could be decomposed into two intrinsic mode functions (IMF) and a residual item. The residual item denotes a slow and steady rising trend in grain yield which is dominated by the technological progress. The IMF1 and IMF2 represent a short-term fluctuation in about 4-yr cycle and a medium-term fluctuation in about 9-yr cycle, which respectively reflect the influence of meteorological and policy factors on grain yields according to the analysis of grain production system. The variance contribution rate of the residual item was greatly larger than that of the IMFs, which means the upward trend in grain yield was more pronounced than fluctuations. 2) Fluctuation of trend yield of grain was distinct before and after 1997: fast rise with an average annual growth rate of 2.28% before 1997 and slow rise with an average annual growth rate of only 0.69% after 1997. The change of trend yield was similar between rice and grain, but the former seemed to rise more slowly after 1997. For wheat and maize, the trend yield was still increased obviously although the growing rate had been significantly slowing down after 1997. 3) The IMF2 included 3 complete cycles (1979-1988, 1989-1993, and 1994-2002) and an ongoing cycle (2003 to present) which coincided with adjustment of Chinese agricultural policy. In general, the impact of policy and market factors on fluctuation of grain yield is greater than that of climate factors, but responses of different crops to different policies varied: policies on land, tax, subsidies, incentives and insurance had positive or negative effect on medium-term fluctuation of main crops synchronously, but price policies was not the case for main crops especially for maize. Medium-term fluctuation rate of grain yield was 2.94%, and that of wheat was 3.83%, significantly higher than that of maize (2.38%) and rice (2.18%). It suggested wheat's vulnerability to policies. 4) The short-term fluctuation rate of grain yield was 1.80%, and that of maize, wheat, and rice was 3.38%, 2.55%, and 1.06%, respectively. It indicated that Chinese grain production system had a strong ability to resist against meteorological disaster. The disaster prevention capabilities of different crops was not the same, and maize was more easily affected by meteorological disasters than wheat and rice. 5) Both considering the short-term and medium-term fluctuation rates, rice was the most stable crop in yield. The main problem of rice production was the slow growth of yield trend after 1998, while maize was strongly influenced by meteorological disaster, and fluctuation of wheat was significantly affected by policy cycles. At present, China's agriculture production has entered a new development stage. It is necessary to adjust the agricultural policy in order to adapt to the new situation. The results here can help with decision-making and adjustment of agricultural policies. [ABSTRACT FROM AUTHOR]