Quantifying Spatiotemporal Dynamics of Solar Radiation over the Northeast China Based on ACO-BPNN Model and Intensity Analysis

Reliable information on the spatiotemporal dynamics of solar radiation plays a crucial role in studies relating to global climate change. In this study, a new backpropagation neural network (BPNN) model optimized with an Ant Colony Optimization (ACO) algorithm was developed to generate the ACO-BPNN model, which had demonstrated superior performance for simulating solar radiation compared to traditional BPNN modelling, for Northeast China. On this basis, we applied an intensity analysis to investigate the spatiotemporal variation of solar radiation from 1982 to 2010 over the study region at three levels: interval, category, and conversion. Research findings revealed that (1) the solar radiation resource in the study region increased from the 1980s to the 2000s and the average annual rate of variation from the 1980s to the 1990s was lower than that from the 1990s to the 2000s and (2) the gains and losses of solar radiation at each level were in different conditions. The poor, normal, and comparatively abundant levels were transferred to higher levels, whereas the abundant level was transferred to lower levels. We believe our findings contribute to implementing ad hoc energy management strategies to optimize the use of solar radiation resources and provide scientific suggestions for policy planning

Fuzzy Comprehensive Evaluation-Based Disaster Risk Assessment of Desertification in Horqin Sand Land, China

Desertification is a typical disaster risk event in which human settlements and living environments are destroyed. Desertification Disaster Risk Assessment can control and prevent the occurrence and development of desertification disasters and reduce their adverse influence on human society. This study presents the methodology and procedure for risk assessment and zoning of desertification disasters in Horqin Sand Land. Based on natural disaster risk theory and the desertification disaster formation mechanism, the Desertification Disaster Risk Index (DDRI) combined hazard, exposure, vulnerability and restorability factors and was developed mainly by using multi-source data and the fuzzy comprehensive evaluation method. The results showed that high risk and middle risk areas account for 28% and 23% of the study area, respectively. They are distributed with an “S” type in the study area. Low risk and very low risk areas account for 21% and 10% of the study area, respectively. They are distributed in the west-central and southwestern parts. Very high risk areas account for 18% of the study area and are distributed in the northeastern parts. The results can be used to know the desertification disaster risk level. It has important theoretical and practical significance to prevention and control of desertification in Horqin Sand Land and even in Northern China

Assessment of Land Desertification and Its Drivers on the Mongolian Plateau Using Intensity Analysis and the Geographical Detector Technique

Desertification is one of the most harmful ecological disasters on the Mongolian Plateau, placing the grassland ecological environment under great pressure. Remote-sensing monitoring of desertification and exploration of the drivers behind it are important for effectively combating this issue. In this study, four banners/counties on the border of China and Mongolia on the Mongolian Plateau were selected as the target areas. We explored desertification dynamics and their drivers by using remote sensing imagery and a product dataset for the East Ujimqin Banner and three counties in Mongolia during the period 2000–2015. First, remote sensing information on desertification in the fourth phase of the study area was extracted using the visual interpretation method. Second, the dynamic change characteristics of desertification were analyzed using the intensity analysis method. Finally, the drivers of desertification and their explanatory powers were identified using the geographical detector method. The results show that the desertification of the East Ujimqin Banner has undergone a process of reversion, development, and mild development, with the main transition occurring between slight (SL) and non-desertified land (N), very serious desertified land (VS), and water areas. The dynamics of desertification in this region are influenced by a combination of natural and anthropogenic factors. Desertification in the three counties of Mongolia has undergone processes of development, mild development and mild development with SL and vs. as the main types. Desertification in Mongolia is mainly concentrated in Matad County, which is greatly affected by natural conditions and has little impact from anthropogenic activities. In addition, the change intensity of desertification dynamics in the study area showed a decreasing trend, and the interaction between natural and anthropogenic drivers could enhance the explanatory power of desertification dynamics. The research results provide a scientific basis for desertification control, ecological protection, and ecological restoration on the Mongolian Plateau

Characteristic Analysis of Droughts and Waterlogging Events for Maize Based on a New Comprehensive Index through Coupling of Multisource Data in Midwestern Jilin Province, China

Frequent droughts and waterlogging events are a threat to food security. An understanding of the spatial and temporal variations that occur during such events is essential when conducting a regional and/or global drought and waterlogging assessment. The goal of this study is to define a comprehensive index that considers the continuum system of atmosphere, crops, and soil moisture impacts on droughts and waterlogging events, and to analyze the temporal and spatial distribution of such events in the development of maize. The results show that the proposed comprehensive drought and waterlogging index (CDWI) can bring together the advantages of a single drought and waterlogging index and reasonably describe its range. During the study period, the annual trends of the CDWI decreased at different growth stages from 1982 to 2015, whereas the CDWI did not show significant spatial heterogeneity during any particular stage. Increasing trends of CDWI over 0.019/year were found in the northern part of Midwestern Jilin Province from the emergence to tasseling stages. In addition, decreasing trends were observed in the study area from the tasseling to maturation stages. Slight drought and waterlogging events occurred more frequently than moderate and serious drought and waterlogging events

Spatial pattern of GPP variations in terrestrial ecosystems and its drivers : Climatic factors, CO2 concentration and land-cover change, 1982-2015

Quantitative estimation of spatial pattern of gross primary production (GPP) trends and its drivers plays a crucial role in global change research. This study applied C-Fix model to estimate the net effect of each factor on GPP trends of 1982-2015, used an unsupervised classifier to group similar GPP trend behaviors, and analyzed the responses of GPP to changes in climatic, atmospheric and environmental drivers. According to the features of monthly GPP trends and the patterns of growing season, we presented nine categories as aids in interpreting large-scale behavior. Land-cover change (LCC), rising CO2, temperature and water conditions changes have the positive overall effect on GPP over the entire world, contrary to radiation change effects. The global average contributions of LCC, CO2, temperature, radiation and water on GPP trend are 4.57%, 65.73%, 13.07%, -7.24 and 11.74%, respectively. LCC and climatic factors changes have had a greater impact on GPP in terms of a specific location or regional rather than globally, and the interactions between factors are positive on GPP. The effects of climatic factors trends on GPP in different locations can be opposite, in general: regionally, GPP changes at middle and high latitudes are likely dominated by rises in radiation and temperature; at lower latitudes, GPP changes are likely to be driven by shifts in water conditions; at high altitudes, GPP changes are probably caused by changes in temperature and water conditions. These results will increase the understanding of the variations of carbon flux under future CO2, LCC and climate conditions

Quantitative Agricultural Flood Risk Assessment Using Vulnerability Surface and Copula Functions

Agricultural flood disaster risk assessment plays a vital role in agricultural flood disaster risk management. Extreme precipitation events are the main causes of flood disasters in the Midwest Jilin province (MJP). Therefore, it is important to analyse the characteristics of extreme precipitation events and assess the flood risk. In this study, the Multifractal Detrended Fluctuation Analysis (MF-DFA) method was used to determine the threshold of extreme precipitation events. The total duration of extreme precipitation and the total extreme precipitation were selected as flood indicators. The copula functions were then used to determine the joint distribution to calculate the bivariate joint return period, which is the flood hazard. Historical data and flood indicators were used to build an agricultural flood disaster vulnerability surface model. Finally, the risk curve for agricultural flood disasters was established to assess the flood risk in the MJP. The results show that the proposed approaches precisely describe the joint distribution of the flood indicators. The results of the vulnerability surface model are in accordance with the spatiotemporal distribution pattern of the agricultural flood disaster loss in this area. The agricultural flood risk of the MJP gradually decreases from east to west. The results provide a firm scientific basis for flood control and drainage plans in the area

Assessment of Land Desertification and Its Drivers on the Mongolian Plateau Using Intensity Analysis and the Geographical Detector Technique

Desertification is one of the most harmful ecological disasters on the Mongolian Plateau, placing the grassland ecological environment under great pressure. Remote-sensing monitoring of desertification and exploration of the drivers behind it are important for effectively combating this issue. In this study, four banners/counties on the border of China and Mongolia on the Mongolian Plateau were selected as the target areas. We explored desertification dynamics and their drivers by using remote sensing imagery and a product dataset for the East Ujimqin Banner and three counties in Mongolia during the period 2000–2015. First, remote sensing information on desertification in the fourth phase of the study area was extracted using the visual interpretation method. Second, the dynamic change characteristics of desertification were analyzed using the intensity analysis method. Finally, the drivers of desertification and their explanatory powers were identified using the geographical detector method. The results show that the desertification of the East Ujimqin Banner has undergone a process of reversion, development, and mild development, with the main transition occurring between slight (SL) and non-desertified land (N), very serious desertified land (VS), and water areas. The dynamics of desertification in this region are influenced by a combination of natural and anthropogenic factors. Desertification in the three counties of Mongolia has undergone processes of development, mild development and mild development with SL and vs. as the main types. Desertification in Mongolia is mainly concentrated in Matad County, which is greatly affected by natural conditions and has little impact from anthropogenic activities. In addition, the change intensity of desertification dynamics in the study area showed a decreasing trend, and the interaction between natural and anthropogenic drivers could enhance the explanatory power of desertification dynamics. The research results provide a scientific basis for desertification control, ecological protection, and ecological restoration on the Mongolian Plateau

Estimation of Variability Characteristics of Regional Drought during 1964–2013 in Horqin Sandy Land, China

Drought has an important influence on the hydrological cycle, ecological system, industrial and agricultural production, and social life. Based on the different time scales of characteristics of drought variability, the standardized precipitation evapotranspiration index (SPEI), a multi-timescale index with consideration of evaporation, was used in this study to estimate the spatial and temporal variability characteristics of drought. Climatic data from 15 meteorological stations across Horqin Sandy Land during 1964–2013 were used to calculate the SPEI of 1, 3, 6, and 12 months. In order to examine the relationship between droughts and other variables, 10 extreme climate indices were calculated based on the daily precipitation and maximum/mean/minimum temperature data of 15 meteorological stations, and linkages between SPEI-12 and atmosphere indices were established using by the cross wavelet transform method. The results indicated that the climate of Horqin Sandy Land had a tendency towards drought conditions, which is particularly apparent from the year 2000 onwards. During the study period, drought events were frequent in the region. Mild drought occurred in a quarter of the month, with that of moderate, severe, and extreme drought accounting for 0.11, 0.05, and 0.02 of the total months. The spatial trend of multi-timescale drought revealed that there was an increase in the severity of drought throughout Horqin Sandy Land, among which the magnitude in southern parts was larger than that of northern parts. The results also showed that the short time scale drought negatively correlated with precipitation extremes and positively correlated with temperature extremes. Furthermore, the long time scale drought (SPEI-12) was associated with atmosphere indices. Significant resonance periods were found between El Nino southern oscillation (ENSO), the East Asian summer monsoon index (EASMI), and SPEI-12

Spatiotemporal Variation in Compound Dry and Hot Events and Its Effects on NDVI in Inner Mongolia, China

In recent decades, frequent compound dry and hot events have posed a great threat to humans and the ecological environment, especially in Inner Mongolia, which has arid and semi-arid characteristics. In this study, monthly temperature and precipitation data from 115 meteorological stations in Inner Mongolia from 1982 to 2020 were used to establish a standardized dry and hot index (SDHI). Theil–Sen median trend analysis, Mann–Kendall test, partial correlation analysis, and stepwise multiple regression models were used to characterize the changes in compound dry and hot events and the normalized difference vegetation index (NDVI) from 1982 to 2020, and the relationship between the SDHI and NDVI was quantitatively evaluated. The results showed that the overall SDHI values in Inner Mongolia showed a significant decrease at a rate of 0.03/year from 1982 to 2020, indicating an increase in the severity of compound dry and hot events. NDVI values showed a significant increasing trend and NDVI showed mutated 2001. Among the grassland vegetation types, SDHI and NDVI trends were more significant in forests, and meadow steppe, desert steppe, and desert were more susceptible to compound dry and hot events, and forests had the greatest severity of compound dry and hot events. The results of the partial correlation analysis showed that the average value of the partial correlation coefficient between the SDHI and NDVI was 0.68, and the area of positive correlation was 84.13%. Spatially, it showed strong response characteristics in the middle and gradual weakening towards the east and west sides. The correlation between NDVI and climatic conditions varied greatly in different vegetation areas. The forest area is most sensitive to the influence of temperature, and the desert steppe area is most affected by compound dry and hot events. The overall vegetation growth in Inner Mongolia was most affected by temperature conditions, followed by compound dry and hot conditions, and the influence of drought conditions was the least significant. The results of the relative importance analysis confirmed this. The research results provide a more detailed understanding of compound dry and hot events in arid and semi-arid regions and useful insights and support for ecological protection

Changes of Reference Evapotranspiration and Its Relationship to Dry/Wet Conditions Based on the Aridity Index in the Songnen Grassland, Northeast China

Reference evapotranspiration (ET0) plays an important role in regional dry/wet conditions. Based on the Food and Agriculture Organization of the United (FAO) Penman-Monteith method and daily climate variables, ET0 was calculated for 21 stations in and around the Songnen Grassland, northeast China, during 1960–2014. The temporal and spatial variations of ET0 and precipitation (P) were analyzed in the annual, seasonal, and growing season (from April to October) time series using the Mann-Kendall test, Sen’s slope estimator, and linear regression coupled with a break trend analysis. A sensitivity analysis was used to detect the key climate parameter contributing to ET0 change. By linear regression analysis on the relationship between ET0, P, and the aridity index (AI), the role of ET0 in determining regional wet/dry conditions was analyzed. Results show a higher ET0 in the southwest and a lower ET0 in the northeast, but P was opposite to that of ET0. Evident decreasing trends of ET0 in the annual, seasonal, and growing season time series were detected in almost the entire region by the trend analysis methods. For the entire region, the decreasing trend of ET0 can be linked to the relative humidity and maximum air temperature. The positive contribution of increasing temperature to ET0 was offset by the effect of the significantly decreasing relative humidity, wind speed, and sunshine duration at the 0.05 level during 1960–2014. In addition, the value of ET0 was higher in drought years and lower in wet years