scholarly journals Spatially Explicit Reconstruction of Cropland Using the Random Forest: A Case Study of the Tuojiang River Basin, China from 1911 to 2010

Land ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1338
Author(s):  
Qi Wang ◽  
Min Xiong ◽  
Qiquan Li ◽  
Hao Li ◽  
Ting Lan ◽  
...  
Keyword(s):  
Random Forest ◽  
River Basin ◽  
Climatic Conditions ◽  
Spatially Explicit ◽  
Flexible Framework ◽  
Ecological Simulation ◽  
Cropland Change ◽  
Archive Data

A long-term, high-resolution cropland dataset plays an essential part in accurately and systematically understanding the mechanisms that drive cropland change and its effect on biogeochemical processes. However, current widely used spatially explicit cropland databases are developed according to a simple downscaling model and are associated with low resolution. By combining historical county-level cropland archive data with natural and anthropogenic variables, we developed a random forest model to spatialize the cropland distribution in the Tuojiang River Basin (TRB) during 1911–2010, using a resolution of 30 m. The reconstruction results showed that the cropland in the TRB increased from 1.13 × 104 km2 in 1911 to 1.81 × 104 km2. In comparison with satellite-based data for 1980, the reconstructed dataset approximated the remotely sensed cropland distribution. Our cropland map could capture cropland distribution details better than three widely used public cropland datasets, due to its high spatial heterogeneity and improved spatial resolution. The most critical factors driving the distribution of TRB cropland include nearby-cropland, elevation, and climatic conditions. This newly reconstructed cropland dataset can be used for long-term, accurate regional ecological simulation, and future policymaking. This novel reconstruction approach has the potential to be applied to other land use and cover types via its flexible framework and modifiable parameters.

scholarly journals EVALUATION OF POSSIBLE CHANGES IN THE RIVER LINE OF THE OKA BASIN FOR THE COMING PERIOD OF THE FIRST HALF OF THE XXI CENTURY

2020 ◽  
Vol 1 (5) ◽  
pp. 71-75
Author(s):  
G. Kh. Ismaiylov ◽  
◽  
N.V. Muraschenkova ◽  
Keyword(s):  
River Basin ◽  
21St Century ◽  
River Runoff ◽  
River Flow ◽  
Climatic Conditions ◽  
Global Changes ◽  
The Future ◽  
Seasonal Runoff ◽  
The City

A retrospective analysis and assessment of long-term changes in the annual and seasonal runoff of the Oka River basin over a long 131-year observation period (1881 / 1882–2011/2012) was performed. The changes in the annual distribution of the Oka river runoff over the seasons of the year (spring flood, summer-autumn and winter low water) from its annual value for the selected time periods (before and after 1976/1977) are considered. It has been noted that over the past decades, river runoff has been formed in new climatic conditions associated with global changes and, as a result, regional climate. The assessment of possible changes in the annual and seasonal runoff of the Oka River basin (to the final alignment – the city of Kaluga, with a basin area of 54,900 km2 ) in the first half of the 21st century is carried out. In assessing changes in the river flow of the Oka basin for the future period, the method of trends (trends) is used, based on the identification of cycles in fluctuations in hydrological characteristics and unidirectional trends (trends) inherent in individual phases (ups and downs) of these cycles, as well as to the establishment of functional (correlation) relationships between environmental factors (climatic, anthropogenic) and the nature of the response (river flow). In this case, the trend model serves as an alternative to the homogeneity hypothesis of long-term fluctuations in river flow. The change in the future values of the river flow of the Oka basin was estimated using averaged data of 30-year periods of time characterized by relative stationarity of climatic and hydrological conditions. The dynamics of the average 30-year values of the annual runoff in the upper reaches of the Oka River (the closure target is the city of Kaluga for the period 1881/1882–2011/2012) is considered. Possible forecasted mean annual values of the annual flow of the Oka River for the first half of the 21st century are obtained

scholarly journals Spatially Explicit Mapping of Historical Population Density with Random Forest Regression: A Case Study of Gansu Province, China, in 1820 and 2000

2020 ◽  
Vol 12 (3) ◽  
pp. 1231 ◽  
Author(s):  
Fahao Wang ◽  
Weidong Lu ◽  
Jingyun Zheng ◽  
Shicheng Li ◽  
Xuezhen Zhang
Keyword(s):  
Spatial Distribution ◽  
Random Forest ◽  
Population Density ◽  
Census Data ◽  
Gansu Province ◽  
Spatially Explicit ◽  
Random Forest Regression ◽  
Independent Variables ◽  
Population Weighting

This study established a random forest regression model (RFRM) using terrain factors, climatic and river factors, distances to the capitals of provinces, prefectures (Fu, in Chinese Pinyin), and counties as independent variables to predict the population density. Then, using the RFRM, we explicitly reconstructed the spatial distribution of the population density of Gansu Province, China, in 1820 and 2000, at a resolution of 10 by 10 km. By comparing the explicit reconstruction with census data at the township level from 2000, we found that the RFRM-based approach mostly reproduced the spatial variability in the population density, with a determination coefficient (R2) of 0.82, a positive reduction of error (RE, 0.72) and a coefficient of efficiency (CE) of 0.65. The RFRM-based reconstructions show that the population of Gansu Province in 1820 was mostly distributed in the Lanzhou, Gongchang, Pingliang, Qinzhou, Qingyang, and Ningxia prefecture. The macro-spatial pattern of the population density in 2000 kept approximately similar with that in 1820. However, fine differences could be found. The 79.92% of the population growth of Gansu Province from 1820 to 2000 occurred in areas lower than 2500 m. As a result, the population weighting in the areas above 2500 m was ~9% in 1820 while it was greater than 14% in 2000. Moreover, in comparison to 1820, the population density intensified in Lanzhou, Xining, Yinchuan, Baiyin, Linxia, and Tianshui, while it weakened in Gongchang, Qingyang, Ganzhou, and Suzhou.

scholarly journals Green roof evapotranspiration rates and stormwater control under subtropical climate: a case study in Brazil

RBRH ◽  
2021 ◽  
Vol 26 ◽  
Author(s):  
Nathana Karina Swarowski Arboit ◽  
Rutineia Tassi ◽  
Tiago Liberalesso ◽  
Denise Ester Ceconi ◽  
Daniel Gustavo Allasia Piccili
Keyword(s):  
Green Roof ◽  
Crop Coefficient ◽  
Climatic Conditions ◽  
Subtropical Climate ◽  
Water Abundance ◽  
Whole Process ◽  
Stormwater Control

ABSTRACT In this study a long-term field experiment evaluating evapotranspiration rates from irrigated and non-irrigated green roof modules, as well their impacts on stormwater control was accomplished. Six green roof modules (3 irrigated and 3 non-irrigated) vegetated with S. rupestre were monitored throughout 8 months in southern Brazil. Four non-vegetated modules (2 irrigated and 2 non-irrigated) were simultaneously assessed to understand the role of the vegetation in the whole process. The average evapotranspiration under water-stress (ETr) was 2.6 mm.day-1, while mean evapotranspiration under water-abundance (ETp) was 2.8 mm.day-1. Higher evapotranspiration rates were observed during summer, increasing the substrate storage capacity, although ETr amount along the seasons was very similar, mainly affected by climatic conditions. The long-term analysis showed that 47% of the total rainfall was converted into runoff, 21% was retained in the green roof modules and 32% was released through evapotranspiration, reinforcing the importance of vegetation as a mechanism for improving stormwater control benefits. The results of this research also allowed the establishment of a crop coefficient (Kc) time series, with a monthly average of 0.9 which permits the S. rupestre evapotranspiration to be preliminarily estimated by using equations developed for reference culture without the need of monitoring.

Hybrid PSO–SVM-based method for long-term forecasting of turbidity in the Nalón river basin: A case study in Northern Spain

2014 ◽  
Vol 73 ◽  
pp. 192-200 ◽  
Author(s):  
P.J. García Nieto ◽  
E. García-Gonzalo ◽  
J.R. Alonso Fernández ◽  
C. Díaz Muñiz
Keyword(s):  
River Basin ◽  
Northern Spain ◽  
Long Term Forecasting

Monitoring meteorological drought in a semiarid region using two long-term satellite-estimated rainfall datasets: A case study of the Piranhas River basin, northeastern Brazil

2021 ◽  
Vol 250 ◽  
pp. 105380
Author(s):  
Célia Soares de Brito ◽  
Richarde Marques da Silva ◽  
Celso Augusto Guimarães Santos ◽  
Reginaldo Moura Brasil Neto ◽  
Victor Hugo Rabelo Coelho
Keyword(s):  
River Basin ◽  
Meteorological Drought ◽  
Northeastern Brazil ◽  
Semiarid Region

scholarly journals Palaeoclimatological perspective on river basin hydrometeorology: case of the Mekong Basin

2013 ◽  
Vol 17 (5) ◽  
pp. 2069-2081 ◽  
Author(s):  
T. A. Räsänen ◽  
C. Lehr ◽  
I. Mellin ◽  
P. J. Ward ◽  
M. Kummu
Keyword(s):  
Interannual Variability ◽  
River Basin ◽  
Southern Oscillation ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Case Study Area ◽  
Weather Events ◽  
Basin Scale

Abstract. Globally, there have been many extreme weather events in recent decades. A challenge has been to determine whether these extreme weather events have increased in number and intensity compared to the past. This challenge is made more difficult due to the lack of long-term instrumental data, particularly in terms of river discharge, in many regions including Southeast Asia. Thus our main aim in this paper is to develop a river basin scale approach for assessing interannual hydrometeorological and discharge variability on long, palaeological, time scales. For the development of the basin-wide approach, we used the Mekong River basin as a case study area, although the approach is also intended to be applicable to other basins. Firstly, we derived a basin-wide Palmer Drought Severity Index (PDSI) from the Monsoon Asia Drought Atlas (MADA). Secondly, we compared the basin-wide PDSI with measured discharge to validate our approach. Thirdly, we used basin-wide PDSI to analyse the hydrometeorology and discharge of the case study area over the study period of 1300–2005. For the discharge-MADA comparison and hydrometeorological analyses, we used methods such as linear correlations, smoothing, moving window variances, Levene type tests for variances, and wavelet analyses. We found that the developed basin-wide approach based on MADA can be used for assessing long-term average conditions and interannual variability for river basin hydrometeorology and discharge. It provides a tool for studying interannual discharge variability on a palaeological time scale, and therefore the approach contributes to a better understanding of discharge variability during the most recent decades. Our case study revealed that the Mekong has experienced exceptional levels of interannual variability during the post-1950 period, which could not be observed in any other part of the study period. The increased variability was found to be at least partly associated with increased El Niño Southern Oscillation (ENSO) activity.

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