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 Coupling a Bat Algorithm with XGBoost to Estimate Reference Evapotranspiration in the Arid and Semiarid Regions of China

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Yixiu Han ◽  
Jianping Wu ◽  
Bingnian Zhai ◽  
Yanxin Pan ◽  
Guomin Huang ◽  
...  
Keyword(s):  
Air Temperature ◽  
Reference Evapotranspiration ◽  
Meteorological Data ◽  
Bat Algorithm ◽  
Irrigation Scheduling ◽  
Multivariate Adaptive Regression Splines ◽  
Accurate Estimation ◽  
Agricultural Irrigation ◽  
Semiarid Regions ◽  
Arid And Semiarid

Accurate estimation of reference evapotranspiration (ETo) is key to agricultural irrigation scheduling and water resources management in arid and semiarid areas. This study evaluates the capability of coupling a Bat algorithm with the XGBoost method (i.e., the BAXGB model) for estimating monthly ETo in the arid and semiarid regions of China. Meteorological data from three stations (Datong, Yinchuan, and Taiyuan) during 1991–2015 were used to build the BAXGB model, the multivariate adaptive regression splines (MARS), and the gaussian process regression (GPR) model. Six input combinations with different sets of meteorological parameters were applied for model training and testing, which included mean air temperature (Tmean), maximum air temperature (Tmax), minimum air temperature (Tmin), wind speed (U), relative humidity (RH), and solar radiation (Rs) or extraterrestrial radiation (Ra, MJ m−2·d−1). The results indicated that BAXGB models (RMSE = 0.114–0.412 mm·d−1, MAE = 0.087–0.302 mm·d−1, and R2 = 0.937–0.996) were more accurate than either MARS (RMSE = 0.146–0.512 mm·d−1, MAE = 0.112–0.37 mm·d−1, and R2 = 0.935–0.994) or GPR (RMSE = 0.289–0.714 mm·d−1, MAE = 0.197–0.564 mm·d−1, and R2 = 0.817–0.980) model for estimating ETo. Findings of this study would be helpful for agricultural irrigation scheduling in the arid and semiarid regions and may be used as reference in other regions where accurate models for improving local water management are needed.

scholarly journals Global comparison of 20 reference evapotranspiration equations in a semi-arid region of Iran

2018 ◽  
Vol 50 (1) ◽  
pp. 282-300 ◽  
Author(s):  
Hadi Farzanpour ◽  
Jalal Shiri ◽  
Ali Ashraf Sadraddini ◽  
Slavisa Trajkovic
Keyword(s):  
Arid Region ◽  
Reference Evapotranspiration ◽  
Meteorological Data ◽  
Irrigation Scheduling ◽  
Climatic Conditions ◽  
Accurate Estimation ◽  
Management Scenarios ◽  
Global Comparison ◽  
Semi Arid Region ◽  
Semi Arid

Abstract Accurate estimation of reference evapotranspiration (ETo) is a major task in hydrology, water resources management, irrigation scheduling and determining crop water requirement. There are many empirical equations suggested by numerous references in literature for calculating ETo using meteorological data. Some such equations have been developed for specific climatic conditions while some have been applied universally. The potential for usage of these equations depends on the availability of necessary meteorological parameters for calculating ETo in different climate conditions. The focus of the present study was a global cross-comparison of 20 ETo estimation equations using daily meteorological records of 10 weather stations (covering a period of 12 years) in a semi-arid region of Iran. Two data management scenarios, namely local and cross-station scenarios, were adopted for calibrating the applied equations against the standard FAO56-PM model. The obtained results revealed that the cross-station calibration might be a good alternative for local calibration of the ETo models when proper similar stations are used for feeding the calibration matrix.

scholarly journals Evaluation of Pan Coefficient Models and Trend Analysis for a Station in Coastal Andhra Pradesh

2020 ◽  
Vol 1 (2) ◽  
Author(s):  
P. Heramb ◽  
P. K. Singh
Keyword(s):  
Trend Analysis ◽  
Andhra Pradesh ◽  
Meteorological Data ◽  
Irrigation Scheduling ◽  
Trend Detection ◽  
Accurate Estimation ◽  
Positive Trend ◽  
Pan Evaporation ◽  
Crop Water ◽  
Annual Time

Irrigation scheduling needs an accurate estimation of crop water requirement and can be done using pan evaporation data which is easily available across the country at various meteorological stations. This study aims to evaluate different K models for a station in coastal Andhra Pradesh, India. A10-year meteorological data from 2006 to 2015 was used for p the study. The results indicated that the Snyder method was able to successfully estimate K and ET accurately on an p 0 annual time scale and during the months of January to September. However, Cuenca and FAO-56 K equation for dry p fetch gave a better result during the months of October to December. The trend detection for the estimates was taken up for the study period. The trend analysis showed that the K estimated by FAO 56 PM showed some declining trend p whereas the K estimated by the other models in the study showed positive trend during the study period for the region.

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 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
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