Journal of Natural Disaster Science, Volume 27, Number 1, 2005, pp1-7

The Relationship between Vegetation Changes and Cut-offs
in the Lower Yellow River Based on Satellite and Ground Data
Xiufeng WANG1, Nobuhiro MATSUOKA2, Guirui YU3 and Zhongxue ZHANG3
1
Graduate School of Agriculture, Hokkaido University
2
Faculty of Horticulture, Chiba University
3
Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences(Received for 11 Aug., 2003 and in revised from 29 Aug., 2005)

ABSTRACT
Absences of water flow (cut-offs) have occurred frequently since 1972 in the Yellow River, China. Satellite
and ground data were used to determine the causes and to understand the river’s present state. Actual conditionsof river flow/cut-offs were analyzed by means of ground data. Fluctuation trends of the average NDVI for 20
years were obtained from satellite data over the study area. Relationships between the flow/cut-offs of the Yellow
River obtained from ground data and NDVI change in the lower reaches of the river obtained from satellite data
were analyzed as was the relationship between changing NDVI and precipitation (or temperature). Multiple
regression analyses of cut-offs that used predictor variables of the average NDVI, precipitation, and temperature
also were performed. The absence of water flow (cut-off) was assumed to be caused by marked water intake fromthe Yellow River as a result of the increased area for the cultivation of wheat.

1. INTRODUCTION

2. MATERIALS AND METHODSIn China s Yellow River, the absence of flow due to the drying up of river water (referred to as cut-offs in China) has occurred
frequently since 1972, and in almost every year of the 1990s. The
main causes of these cut-offs are presumed to be the long-term
decrease in precipitation and rise in temperature in the Yellow
River basin as a result of climate change, together with excess
intake of irrigation water due to the increase in farmland in thebasin and in agricultural methods change (Chen and Mu, 2000; Yu
and Zhang, 2002; and Li 1998 (unpublished document)).
Shortages of water for Chinese food production will be felt
throughout the world particularly in Japan. It is believed that the
global supply of and demand for crops will tighten in the near
future because China will become a large-scale crop importingstate in order to continue its lifestyle improvement. Consequently,
worldwide food problem is anticipated, resulting in rising global
food prices. In particularly, the food issue in China will exacerbate
global and Japanese food problems. The authors have conducted
this study with the objective that solving one Chinese water issue
may provide a partial solution to global and Japanese food problems; more generally, it may provide a solution to global environment problems.
This study, that uses satellite data and ground data, wasintended to clarify the cause of the Yellow River cut-offs by investigating flow fluctuation, cut-off conditions, and precipitation, temperature change, and farm land area change in the river s area in
the Yellow River.

2.1 Study Area
The satellite data area encompasses the lower Yellow Riverbasin, from 34°40 to 38°00 N, and 115°40 to 119°00 E(about 300 km×330 km). The area studied is shown in Fig. 1.
2.2 Data Used
(1) Ground Data
Daily precipitation data in the Yellow River basin from 1961

Fig. 1 Study area.
(○Temp.Ob., ◎Temp.+Preci.Ob, ●Flow Ob., ▲Boundary of basin )KEY WORDS: vegetation change, cut-off, NDVI, satellite data, the lower Yellow River2

X. WANG, N. MATSUOKA, G.YU AND Z. ZHANG

through 2000 were obtained from meteorological stations at
Lanzhou (upper), Mengjin (middle), and Jinan (lower). Monthly
flow data from 1980 through 1997 were provided by gauging stations at Toudaoguai (upper), Huayuankou (middle), and Lijin(lower). River cut-off data from 1972 through 1999 were suppliedby the Yellow River Lijin gauging station. In additions, daily temperature data from 1961 through 2000 were provided by meteorological stations in Xinghai, Lanzhou, Zhongning, and Linhe in theupper reaches, from Hequ, Suide and Mengjinin in the middle
reaches, and from Jinan in the lower reaches.
(2) Satellite Data
The twenty-year Global 4-minute AVHRR NDVI data set at
Chiba University (hereafter referred to as NDVI data) was used.
These data, composed of 10-day NDVIs, (Normalized Differential
Vegetation Index) for 20 years from 1981 to 2000, were compiledby the Center for Environmental Remote Sensing, Chiba
University, Japan.
2.3 Analysis ProcedureThree categories of analysis were carried out: (1) actual condition analysis based on ground data, (2) fluctuation trend analysis
over the study area based on satellite data, and (3) correlation
analyses of ground and satellite data.
(1) Actual Condition Analysis based on Ground Data
Analyzed items include (1) monthly average flow in the middle reaches; (2) cut-off conditions; (3) yearly flow in the upper,
middle, and lower reaches; (4) yearly precipitation in the upper,
middle, and lower reaches; and (5) yearly average temperature in
the upper, middle, and lower reaches.
(2) Fluctuation Trend Analysis over the Study Area based onSatellite Data
Precipitation and temperature change may affect vegetation
within the area. Therefore, the fluctuation trend of vegetation overthe entire study area based on the NDVIs of satellite data (Cong etal. 1999) was analyzed. Four items were analyzed: (1) the fluctuation trend for 20 years based on the yearly average NDVI, (2) seasonal change based on the monthly average NDVI, (3) monthly
variation in the fluctuation trend for 20 years, and (4) local characteristics in the yearly average NDVI.
(3) Correlation Analyses of Ground and Satellite Data

Fig. 2Monthly average flow in the middle reaches of the Yellow River.

The average NDVI correlation was analyzed from satellitedata, and the cut-offs, flows, precipitation, and temperature in the
Yellow River basin, from ground data. Multiple regression analysis of a cut-off based on the average NDVI, precipitation, and temperature also was performed.
3. RESULTS AND DISCUSSION
3.1 Actual Condition Analysis based on Ground Data
The monthly average flow in the middle reaches of the
Yellow River is shown in Fig. 2. This figure indicates that adrought season from December to June and a high-water seasonfrom July to November are usual in the Yellow River basin.
Furthermore, the monthly average flow from 1971 through 1980 isless than that from 1934 through 1970, indicative that the average
flow decreases from May in the drought season to November in thehigh-water season. Particularly, from 1971 through 1980 in June,it was below the minimum flow for the period 1934 - 1970, evidence that cut-offs are likely to occur in June. In fact, data showthat cut-offs began normally in late May and ceased at the end ofJune during the period 1972 - 1991. In 1992 - 1999, however, cutoffs typically began in late February and ended in mid-October.
Fig. 3 shows the cut-off period (days) and cut-off distances in
the Yellow River from 1972 through 1999. The longest cut-off
distance is 700 km in 1997, the average 248 km. Cut-offs
increased markedly in the 1990s. Although previously cut-offs
were observed only near the river mouth, the yearly longest cut-off
distance recently often has exceeded 500 km.
Cut-offs were observed in the 22 years of the 28-year period1972 to 1999. They also occurred in six years of the 1970s, totally
86 days; in seven years of the 1980s, 105 days; and in nine years of
the 1990s, 901 days. No cut-off has been recorded since 2000
because the Chinese government has restricted water intake, but
the future is unpredictable because of the anticipated increase inwater consumption and climate change.
Fig. 4 shows the three-year moving average of the monthly
average flow in the upper, middle, and lower reaches of the Yellow
River for 1980 through 1997. It indicates that the flow is highest
in the middle reaches and is decreasing year after year throughout
the basin. Although flow in the lower reaches temporarily wasFig. 3 State of dried up water in the Yellow River and annual
precipitation in the lower basin.

THE RELATIONSHIP BETWEEN VEGETATION CHANGES AND CUT-OFFS IN THE LOWER YELLOW RIVER BASED ON SATELLITE AND GROUND DATA

close to that in the middle reaches, it is equal to or less than that in
the upper reaches in recent years. We have analyzed the causes forthis in a later section.
Fig. 5 shows the three-year moving average of annual precipitation in the upper, middle, and lower reaches of the Yellow Riverfor 1961 to 2000. Regression lines are shown to illustrate thedownward trend except in the upper reaches. Comparison of theslopes of the regression lines in the upper, middle, and lower
reaches indicates that the trend is the greatest in the middle.
Consideration of the effect of precipitation on cut-offs and the flowof the Yellow River suggests that precipitation in the upper andmiddle river is more influential than that in the lower reaches. The
decrease in precipitation in the middle reaches therefore may berelated to the decrease in the flow of the Yellow River.
The change and three-year moving average of the annual
mean temperature for 1961 to 2000 at three points in the upper,
middle, and lower reaches of the Yellow River are shown in Fig. 6.
Regression lines are included to show fluctuation trends. There isan upward trend on the whole. In particular, the upsurge of temperature at Lanzhou is large about 2℃. Data at other points in theupper reaches also show a larger upward trend than in the middle
and lower reaches; i.e. the temperature upsurge in the upper reach-3

es tends to be higher. This may reflect the progress of global
warming and desertification in the inland area.
3.2 Fluctuation Trend Analysis over the Study Area based onSatellite Data
The 20-year fluctuation trend of the average NDVI over theentire study area was investigated. The average NDVI for 1981 to
1999 shows a yearly upward trend (Fig. 7). Moreover, the average
NDVI peaks in 1984, 1990, and 1995, whereas it has valleys in
1982, 1986, 1992, and 1996, indicative of periodicity. Calculationof the period by the autocorrelation method based on data transformed to a moving average suggests a 4 to 5 year periodicity.
Furthermore, the monthly fluctuation trend for 20 years is evidence
that there is a certain upward yearly trend January through June,
but that this trend is small from July through December. Fig. 8
gives typical examples of the NDVI in May and August. The
regression coefficients show that the upward trend in May isgreater than in August.
Seasonal variation in the average NDVI is shown in Fig. 9.
There are peaks in May and August, which months are peak of leaf
coverage respectively for fall-sown wheat and common crops(especially corn). Moreover, this finding agrees with the research

Fig. 4Three-year moving averages of the Yellow River flow.

Fig. 6

Yearly transition of the annual mean temperature in the
Yellow River basin.

Fig. 5

Moving average of annual precipitation in the Yellow
River basin.

Fig. 7

Yearly change and moving average of the average NDVI
over the study area.

4

X. WANG, N. MATSUOKA, G.YU AND Z. ZHANG

Fig. 8Moving average of the yearly change of the monthly
average NDVI in May and August.

Fig. 9Seasonal variation in the average NDVI.

Fig. 10 Difference for each pixel of the NDVI in May on the basis of the NDVI in May 1982.
(The area is equal to the square in Fig.1)

THE RELATIONSHIP BETWEEN VEGETATION CHANGES AND CUT-OFFS IN THE LOWER YELLOW RIVER BASED ON SATELLITE AND GROUND DATA

results of Jingfeng et al. (2002) who mapped crop seasons in the
North China plain using satellite data. Images in Fig. 10 express
the difference in each pixel on the basis of the NDVI in May 1982
in order to investigate the upward trend in the local cultivation areaof wheat. The darker portions of Fig. 10 denote higher NDVIs.
Fig. 10 (a) represents the 1980s, showing the difference
between May 1983 and May 1982, and Fig. 10 (b) represents the
1990s, showing the difference between May 1997 and May 1982.
No great change occurred in the 1980s, whereas the NDVI
increased in the 1990s. The upper left part of the area studied is
cultivated land north of the Yellow River, and the lower right partis occupied by a mountain range, showing that the increase in the
NDVI in and after the 1990s is remarkable in the cultivated land
areas. This is considered to be the result of the increase in the cultivation area of wheat. Fig. 10 (c) shows the NDVI difference
between May 2000 and May 1982, May 2000 indicating a partwith little change in the upper left part of the study area, which had
increased until 1999. The cultivated area may have decreased dueto the reported cut in water intake in 2000. No cut-off occurred inFig. 11

Correlation between the monthly average NDVI andwater cut-off.

Fig. 12

Correlation between the monthly average NDVI andwater flow.

52000 owing to that cut in water intake.
3.3 Correlation Analyses of Ground and Satellite Data
Correlations were calculated to determine the relevance
between ground and satellite data. Fig. 11 shows the correlation
between the monthly average NDVI in each year of the area studied and the yearly cut-off distance or cut-off period. The cut-off
has a high positive correlation with the NDVI in early, middle, andlate May; the NDVI in May is high in years with a heavy cut-off.
Correlation between the monthly average NDVI for each year andyearly flow is shown in Fig. 12. Flow has a high negative correlation with the NDVI from mid-April to late May. These two results
suggest that the increased cultivated area of fall-sown wheat raised
the average NDVI; hence, water intake from the Yellow River
increased, reducing the river s flow and causing a cut-off. Any
cut-off beginning in February or March of a year with a heavy cutoff possibly may affect wheat cultivation.
Fig. 13 shows the correlation between the monthly average
NDVI in the area studied by year and yearly precipitation in thelower reaches. Precipitation has a high correlation with the NDVI
in late June to early August, being especially high in mid-July.
The main crops currently grown during this period are assumed tobe affected by precipitation. The correlations between cut-off andprecipitation in the upper, middle, and lower reaches also were
investigated. Precipitation in May in the upper and middle reaches
shows a negative correlation, indicative that precipitation also is afactor in the occurrence of a cut-off. Moreover, the correlation of
cut-off with monthly and yearly average temperatures in the upper,
middle, and lower reaches was studied. There was a high correlation between yearly average temperature and cut-offs over theentire basin. That is, temperature also is considered to act as acause of cut-offs.
Multiple regression analyses of cut-offs based on the predictor
variables of the yearly average NDVI of the study area, yearly precipitation, and yearly mean temperature in the upper, middle, andlower reaches were made. In the middle and lower reaches, thestandard regression coefficient of the yearly mean temperature waslarger than that of the average NDVI and yearly precipitation (Fig.

Fig. 13

Correlation between the monthly average NDVI and
precipitation.

6

X. WANG, N. MATSUOKA, G.YU AND Z. ZHANG

Fig. 14

Standard regression coefficients of multiple regression
equations for the upper, middle, and lower reaches of
the Yellow River based on yearly data (Correlation
coefficient between the same number’s items is significant at the 5 or 1% level).

14). It is presumed that cut-offs are caused by the intake of irrigation water due to high temperature.
Multiple regression analyses for May, when the NDVI peaked
and the upper NDVI trend was remarkable, were calculated bymeans of the predictor variables of the monthly average NDVI of
the area studied, and the monthly precipitation and monthly mean
temperature in the upper, middle, and lower reaches. The standard
regression coefficient of the average NDVI was larger than that of
precipitation and temperature in May (Fig. 15). The average
NDVI is the main cause of the cut-offs in May.
4. CONCLUSIONS
Analysis of ground data showed the following: (1) The
monthly average flow in the middle reaches of the Yellow River
from 1971 through 1980 was less than that from 1934 through1970; therefore, the average flow decreased from May in the
drought season to November in the high-water season. (2) The
longest cut-off distance was 700 km in 1997, 248 km on the average. The longest cut-off distance often has been more than 500 km
in recent years. (3) Cut-offs took place in six years of the 1970s(totally 86 days), in seven years of the 1980s, (105 days), and innine years of the 1990s (901 days). (4) Of the upper, middle, andlower reaches, flow is greatest in the middle reaches, but flow has

Fig. 15

Standard regression coefficients of multiple regression
euations for the upper, middle, and lower reaches basedon monthly data for May (Correlation coefficient
between the same number’s items is significant at the 5or 1% level).

decreased year after year throughout the basin. (5) A certain
downward precipitation trend is seen in the middle and lower
reaches, and a comparison of decrements in the upper, middle, andlower reaches suggests that it is greatest in the middle. (6) On thewhole, an upward trend is seen in the yearly average temperature
at eight sites in the upper, middle, and lower reaches, in particular
the trend in the upper reaches was larger than in the middle andlower ones.
Satellite data analysis indicated (1) The average NDVI
throughout the study area had an upward trend with a periodicity
of four to five years, but it showed no cause for this periodicity.
(2) The average NDVI peaks in May and August. These are therespective peak of leaf coverage for fall-sown wheat and common
crops (especially corn) in this area. (3) The upward trend of theaverage NDVI is large in January through June as a result of theincreased area for the cultivation of wheat. (4) The NDVI shows aremarkable increase in cultivated land in the upper left part of thearea studied north of the Yellow River. The increase in NDVI inthe cultivated land is considered to be due to the increased area forwheat cultivation.
Analysis of ground and satellite data suggested that (1) There
are significant correlations in May between the average NDVI andthe yearly cut-off period, cut-off distance, and flow. (2) A highcorrelation between the average NDVI and yearly precipitation

THE RELATIONSHIP BETWEEN VEGETATION CHANGES AND CUT-OFFS IN THE LOWER YELLOW RIVER BASED ON SATELLITE AND GROUND DATA

occurred in early June through August. (3) Cut-offs therefore areconsidered to be affected by the increased area for the cultivationof wheat in the lower reach. (4) For that reason, flow in the lower
reaches is the smallest.
Initially, in this study, our analysis was based on the assumption that cut-offs would impede crop growth in the lower reachesof the Yellow River, thereby decreasing the NDVI. However, weconcluded that the NDVI is high in years of Yellow River cut-offs
due to the increased area for wheat cultivation in the lower reaches. Future analyses that use high-resolution data, such as original
NOAA data (resolution of 1.1 km), and ASTER data (resolution of
15 m), are needed to obtain greater detail. We will then obtain thedetails of regional increases and detailed characteristics of theyearly increase in the wheat cultivation area using this high-resolution data.
ACKNOWLEDGMENTS
This study was supported by a Grand-in-Aid for Scientific
Research (B)(1),13574015 (PI: Asoc. Prof. Nobuhiro Matsuoka,
Chiba University)

7

REFERENCES
Chen J. and Mu X., 2000. Tendency, causes and control measures on
Yellow River dry-up. J. Natural Resource.15-1, 31-35.
Cong M., Saito G., Murakami T. and Ishitsuka N., 1999. A study of land
cover in China using multi-temporal NOAA/AVHRR data, Proc. ofthe 27th Conf. of Remote Sens. So. Japan, 129-132.
Xin J. , Yu Z., Louise L. and Driessen P. M., 2002. Mapping crop key phenological stages in the North China Plain using NOAA time series
images. Int. J. of Appl. Earth Observ. and Geo-inf., 4, 109-117.
Yu G. and Zhang Z., 2002. Studies on the management of eco-systematicwater resources for the Yellow River Basin. Report for 100
researchers group , Subjects of study on basic and managerial ecosystem, Chinese Academy of Sciences, Beijing.