scholarly journals Spatio-Temporal Characteristics of Dry-Wet Conditions and Boundaries in Five Provinces of Northwest China from 1960 to 2020

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1499
Author(s):  
Miao Wang ◽  
Puxing Liu ◽  
Xuemei Qiao ◽  
Wenyang Si ◽  
Lu Liu
Keyword(s):  
Arid Regions ◽  
Meteorological Data ◽  
Northwest China ◽  
Practical Significance ◽  
Kriging Interpolation ◽  
Wetness Index ◽  
Function Decomposition ◽  
Humid Region ◽  
Wet Climate ◽  
Semi Arid

The study of dry-wet climate boundaries in the context of climate warming is of great practical significance for improving the environment of ecologically fragile zones and promoting economic and natural sustainable development. In this study, based on the daily meteorological data of 110 stations, using the wetness index, empirical orthogonal function decomposition, regime shift detection test, Fourier power spectrum, and Kriging interpolation, the researchers analyzed the spatiotemporal characteristics of dry-wet conditions and boundaries in five provinces of Northwest China from 1960 to 2020. The results showed that the overall wetness index increased in the past 61 years, but with significant internal differences, among which the western and central climate tended to be warm and wet, and the eastern tended to be warm and dry. The annual wetness index changed abruptly in 1986 with cycles of 3.61 a, 7.11 a and 8.83 a. The mutations occurred correspondingly in spring, summer, autumn, and winter in 1972, 1976, 1983, and 1988, with periods of 3.88 a and 4.92 a, 2.18 a and 2.81 a, 2.15 a, and 2.10 a, respectively. The dry-wet climate boundary has fluctuated markedly since 1960. The extreme arid and arid regions boundary shifted southward and shrank in size until the extreme arid region disappeared in the 2010s. The arid along with semi-arid regions and semi-arid in addition to semi-humid regions boundaries both have two boundary lines, and show the shift of the northwestern boundary to the southeast and the southeastern boundary to the northwest, with the area of the arid together with semi-arid regions shrinking significantly by 5.64%, simultaneously, the area of the semi-humid region area expanding significantly by 84.11%. The boundary of semi-humid and relatively humid regions, and the boundary of relatively humid and humid regions all shifted to the southeast, moreover, the area of the relatively humid region and humid region shrank significantly by 12.08%. The expansion of semi-humid region and the contraction of other climate regions are characteristics of the dry-wet climate variability in five provinces of Northwest China. The area of the three arid climate zones dwindled by 9.61%, and the area of the three humid zones extended by 39.01%. Obviously, the climate inclined to be warm and humid in general.

scholarly journals Estimating the Pan Evaporation in Northwest China by Coupling CatBoost with Bat Algorithm

Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 256
Author(s):  
Liming Dong ◽  
Wenzhi Zeng ◽  
Lifeng Wu ◽  
Guoqing Lei ◽  
Haorui Chen ◽  
...  
Keyword(s):  
Arid Regions ◽  
Meteorological Data ◽  
Bat Algorithm ◽  
Economic Assessment ◽  
Northwest China ◽  
Irrigation Scheduling ◽  
Gradient Boosting ◽  
Accurate Estimation ◽  
Pan Evaporation ◽  
Semi Arid

Accurate estimation of pan evaporation (Ep) is vital for the development of water resources and agricultural water management, especially in arid and semi-arid regions where it is restricted to set up the facilities and measure pan evaporation accurately and consistently. Besides, using pan evaporation estimating models and pan coefficient (kp) models is a classic method to assess the reference evapotranspiration (ET0) which is indispensable to crop growth, irrigation scheduling, and economic assessment. This study estimated the potential of a novel hybrid machine learning model Coupling Bat algorithm (Bat) and Gradient boosting with categorical features support (CatBoost) for estimating daily pan evaporation in arid and semi-arid regions of northwest China. Two other commonly used algorithms including random forest (RF) and original CatBoost (CB) were also applied for comparison. The daily meteorological data for 12 years (2006–2017) from 45 weather stations in arid and semi-arid areas of China, including minimum and maximum air temperature (Tmin, Tmax), relative humidity (RH), wind speed (U), and global solar radiation (Rs), were utilized to feed the three models for exploring the ability in predicting pan evaporation. The results revealed that the new developed Bat-CB model (RMSE = 0.859–2.227 mm·d−1; MAE = 0.540–1.328 mm·d−1; NSE = 0.625–0.894; MAPE = 0.162–0.328) was superior to RF and CB. In addition, CB (RMSE = 0.897–2.754 mm·d−1; MAE = 0.531–1.77 mm·d−1; NSE = 0.147–0.869; MAPE = 0.161–0.421) slightly outperformed RF (RMSE = 1.005–3.604 mm·d−1; MAE = 0.644–2.479 mm·d−1; NSE = −1.242–0.894; MAPE = 0.176–0.686) which had poor ability to operate the erratic changes of pan evaporation. Furthermore, the improvement of Bat-CB was presented more comprehensively and obviously in the seasonal and spatial performance compared to CB and RF. Overall, Bat-CB has high accuracy, robust stability, and huge potential for Ep estimation in arid and semi-arid regions of northwest China and the applications of findings in this study have equal significance for adjacent countries.

scholarly journals Spatial–Temporal Evolution Characteristics and Influencing Factors of Agricultural Water Use Efficiency in Northwest China—Based on a Super-DEA Model and a Spatial Panel Econometric Model

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 632
Author(s):  
Weinan Lu ◽  
Wenxin Liu ◽  
Mengyang Hou ◽  
Yuanjie Deng ◽  
Yue Deng ◽  
...  
Keyword(s):  
Water Use Efficiency ◽  
Water Use ◽  
Water Resource ◽  
Arid Regions ◽  
Econometric Model ◽  
Northwest China ◽  
Agricultural Water ◽  
Agricultural Water Use ◽  
Use Efficiency ◽  
Semi Arid

Improving agricultural water use efficiency (AWUE) is an important way to solve the shortage of water resources in arid and semi-arid regions. This study used the Super-DEA (data envelopment analysis) to measure the AWUE of 52 cities in Northwest China from 2000 to 2018. Based on spatial and temporal perspectives, it applied Exploratory Spatial Data Analysis (ESDA) to explore the dynamic evolution and regional differences of AWUE. A spatial econometric model was then used to analyze the main factors that influence the AWUE in Northwest China. The results showed firstly that the overall AWUE in Northwest China from 2000 to 2018 presented a steady upward trend. However, only a few cities achieved effective agricultural water usage by 2018, and the differences among cities were obvious. Secondly, AWUE showed an obvious spatial autocorrelation in Northwest China and showed significant high–high and low–low agglomeration characteristics. Thirdly, economic growth, urbanization development, and effective irrigation have significant, positive effects on AWUE, while per capita water resource has a significant, negative influence. Finally, when improving the AWUE in arid and semi-arid regions, plans should be formulated according to local conditions. The results of this study can provide new ideas on the study of AWUE in arid and semi-arid regions and provide references for the formulation of regional agricultural water resource utilization policies as well.

scholarly journals Spatial and temporal variation of precipitation characteristics in the semiarid region of Xi'an, northwest China

2021 ◽  
Author(s):  
Hao Han ◽  
Jingming Hou ◽  
Rengui Jiang ◽  
Jiahui Gong ◽  
Ganggang Bai ◽  
...  
Keyword(s):  
Temporal Variation ◽  
Arid Regions ◽  
Resource Planning ◽  
Northwest China ◽  
Annual Precipitation ◽  
Spatial And Temporal Variation ◽  
Semiarid Region ◽  
Monthly Precipitation ◽  
Xi’An City ◽  
Semi Arid

Abstract Precipitation variations mostly affect the water resource planning in semi-arid regions of northwest China. The objective of this study is to quantitatively explore the spatial and temporal variations of precipitation in different time scales in Xi'an city area. The Mann–Kendall test and wavelet analysis methods were applied to analyze the precipitation variability. In terms of temporal variation of precipitation, the results indicated that the annual precipitation exhibited a significant decreasing trend during 1951–2018. Except for summer precipitation representing a slightly increasing trend, the other seasonal precipitations had a similar decreasing trend to annual precipitation throughout 1951–2018. The monthly precipitation had different change trends, showing the precipitation from June to September could account for 58.4% of the total annual precipitation. In addition, it was clear that annual precipitation had a significant periodic change, with the periods of 6, 13, 19, and 27 years. For the spatial variation of precipitation during 1961–2018, the results showed that annual and seasonal precipitation exhibited obvious spatial differences, indicating an increasing spatial trend from north to south. Thus, understanding the precipitation variation in Xi'an city can provide a theoretical foundation of future water resources management for other cities in semi-arid regions of northwest China.

scholarly journals Study on the hydro-chemistry process after mixing between water and rocks

2018 ◽  
Vol 54 (2) ◽  
pp. 104-114
Author(s):  
Xiuyan Jing ◽  
Hongbin Yang ◽  
Na Wang
Keyword(s):  
River Water ◽  
Arid Regions ◽  
Yellow River ◽  
Dilution Effect ◽  
Northwest China ◽  
Experimental Simulation ◽  
The Yellow River ◽  
Mixing Ratio ◽  
Close Attention ◽  
Semi Arid

Abstract The chemical evolution of groundwater has received close attention from hydro-geologists. Northwest China largely consists of arid and semi-arid regions, where surface water and groundwater frequently exchange with each other, and where the mixing and water–rock interactions significantly affect the direction of water quality evolution. Based on experimental simulation, this paper investigates the interactions among the Yellow River water, groundwater and rocks in Yinchuan. The study found that when groundwater is mixed with the Yellow River water, the Yellow River water has a certain dilution effect on the hydro-chemical composition of groundwater; however, this effect is not simply diluted by proportion for no reaction between irons, but a portion of calcium, sulfur, and carbonate form precipitates. After mixing of the Yellow River water, groundwater and rocks, the pH increased, and the carbon dioxide system reached equilibrium again. In addition, CO32− was produced. While Na+ increase was mainly due to dissolution, SO42− decrease was because of precipitation. The precipitation or dissolution of Ca2+, Mg2+, and CO32− mainly depended on the mixing ratio between groundwater and river water, which suggested the reversible behavior of the dissolution-precipitation of carbonate minerals.

scholarly journals Can climate change influence agricultural GTFP in arid and semi-arid regions of Northwest China?

2020 ◽  
Vol 12 (5) ◽  
pp. 837-853
Author(s):  
Jian Feng ◽  
Lingdi Zhao ◽  
Yibo Zhang ◽  
Lingxiao Sun ◽  
Xiang Yu ◽  
...  
Keyword(s):  
Climate Change ◽  
Arid Regions ◽  
Northwest China ◽  
Semi Arid

scholarly journals Improving Estimation of Gross Primary Production in Dryland Ecosystems by a Model-Data Fusion Approach

2019 ◽  
Vol 11 (3) ◽  
pp. 225 ◽  
Author(s):  
Haibo Wang ◽  
Xin Li ◽  
Mingguo Ma ◽  
Liying Geng
Keyword(s):  
Carbon Cycle ◽  
Arid Region ◽  
Arid Regions ◽  
Meteorological Data ◽  
Gross Primary Production ◽  
Arid Ecosystems ◽  
Desert Ecosystems ◽  
Dryland Ecosystems ◽  
Semi Arid

Accurate and continuous monitoring of the production of arid ecosystems is of great importance for global and regional carbon cycle estimation. However, the magnitude of carbon sequestration in arid regions and its contribution to the global carbon cycle is poorly understood due to the worldwide paucity of measurements of carbon exchange in arid ecosystems. The Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary productivity (GPP) product provides worldwide high-frequency monitoring of terrestrial GPP. While there have been a large number of studies to validate the MODIS GPP product with ground-based measurements over a range of biome types. Few studies have comprehensively validated the performance of MODIS estimates in arid and semi-arid ecosystems, especially for the newly released Collection 6 GPP products, whose resolution have been improved from 1000 m to 500 m. Thus, this study examined the performance of MODIS-derived GPP by compared with eddy covariance (EC)-observed GPP at different timescales for the main ecosystems in arid and semi-arid regions of China. Meanwhile, we also improved the estimation of MODIS GPP by using in situ meteorological forcing data and optimization of biome-specific parameters with the Bayesian approach. Our results revealed that the current MOD17A2H GPP algorithm could, on the whole, capture the broad trends of GPP at eight-day time scales for the most investigated sites. However, GPP was underestimated in some ecosystems in the arid region, especially for the irrigated cropland and forest ecosystems (with R2 = 0.80, RMSE = 2.66 gC/m2/day and R2 = 0.53, RMSE = 2.12 gC/m2/day, respectively). At the eight-day time scale, the slope of the original MOD17A2H GPP relative to the EC-based GPP was only 0.49, which showed significant underestimation compared with tower-based GPP. However, after using in situ meteorological data to optimize the biome-based parameters of MODIS GPP algorithm, the model could explain 91% of the EC-observed GPP of the sites. Our study revealed that the current MODIS GPP model works well after improving the maximum light-use efficiency (εmax or LUEmax), as well as the temperature and water-constrained parameters of the main ecosystems in the arid region. Nevertheless, there are still large uncertainties surrounding GPP modelling in dryland ecosystems, especially for desert ecosystems. Further improvements in GPP simulation in dryland ecosystems are needed in future studies, for example, improvements of remote sensing products and the GPP estimation algorithm, implementation of data-driven methods, or physiology models.

scholarly journals Spatial Characteristics of Deep-Developed Boundary Layers and Numerical Simulation Applicability over Arid and Semi-Arid Regions in Northwest China

Atmosphere ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 195
Author(s):  
Ma ◽  
Tan ◽  
Ding ◽  
Chen ◽  
Yang
Keyword(s):  
Numerical Simulation ◽  
Boundary Layer ◽  
Arid Region ◽  
Arid Regions ◽  
Northwest China ◽  
Late Spring ◽  
Arid Areas ◽  
Layer Height ◽  
Boundary Layer Height ◽  
Semi Arid

The spatial distribution and long-time variation of the deep-developed boundary layer are not well understood in arid and semi-arid regions of northwest China. ERA-Interim (ECMWF Reanalysis data, ECMWF: European Centre for Medium-Range Weather Forecasts) were used to study the deep-developed boundary layer in the five representative areas in summer and then the Weather Research Forecast (WRF) model was applied to simulate and verify its applicability. The results show that the boundary layer heights in the five representative areas are higher in late spring and summer (the highest is 2485~3502 m in June) and lower in autumn, winter and early spring (the lowest is 758~907 m in December). The seasonal variations of the boundary layer height are smaller at 02:00 BJT and 08:00 BJT, while the variations are relatively larger at 14:00 BJT and 20:00 BJT. The atmospheric boundary layer, with heights over 4000 m, generally exists in late spring and summer. The boundary layer heights are higher in the arid region than in the semi-arid region and the deep-developed boundary layer lasts longer in the arid region. The boundary layer heights present reductions from the northwest to the southeast, except for Minqin in the middle north. The numerical simulation results show that there is a significant difference between different combinations of parameterization schemes to simulate the deep-developed boundary layer in these areas. The combination Goddard+SLAB+ACM2 performs better in the extreme arid area, Dunhuang, and the arid areas, Jiuquan and Minqin, whereas the simulation effect of the combination Dudhia+Noah+ACM2 is better in the semi-arid areas, Yuzhong and Lanzhou. The difference between the schemes is related to the determination of the boundary layer height.

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