Estimation of agricultural water consumption from meteorological and yield data: a case study of Hebei, North China.

Over-exploitation of groundwater resources for irrigated grain production in Hebei province threatens national grain food security. The objective of this study was to quantify agricultural water consumption (AWC) and irrigation water consumption in this region. A methodology to estimate AWC was developed based on Penman-Monteith method using meteorological station data (1984-2008) and existing actual ET (2002-2008) data which estimated from MODIS satellite data through a remote sensing ET model. The validation of the model using the experimental plots (50 m(2)) data observed from the Luancheng Agro-ecosystem Experimental Station, Chinese Academy of Sciences, showed the average deviation of the model was -3.7% for non-rainfed plots. The total AWC and irrigation water (mainly groundwater) consumption for Hebei province from 1984-2008 were then estimated as 864 km(3) and 139 km(3), respectively. In addition, we found the AWC has significantly increased during the past 25 years except for a few counties located in mountainous regions. Estimations of net groundwater consumption for grain food production within the plain area of Hebei province in the past 25 years accounted for 113 km(3) which could cause average groundwater decrease of 7.4 m over the plain. The integration of meteorological and satellite data allows us to extend estimation of actual ET beyond the record available from satellite data, and the approach could be applicable in other regions globally where similar data are available

Distribution of annual mean <i>ET</i>₀ (a), actual ET (b), and changes in averaged ET for the period of 1984–1993 to 1999–2008 (c).

<p>The contour lines in (a) indicate the distribution of annual mean temperature (Ta); contour lines in (c) indicate the change of annual air temperature (Tachg) for the same time slices.</p

Geographical position of Hebei province.

<p>The contour lines and the points indicate average precipitation (1984–2008) and locations of weather stations used in this study, respectively.</p

Inter-annual variations of precipitation (<i>Q_p</i>), net groundwater consumption (<i>Irr_nc</i>), and grain yield (<i>GY</i>) in Hebei Province (1984–2008).

<p>Inter-annual variations of precipitation (<i>Q_p</i>), net groundwater consumption (<i>Irr_nc</i>), and grain yield (<i>GY</i>) in Hebei Province (1984–2008).</p

Relationship between remote sensing derived annual ET (<i>ET_rs</i>) and grain yield (GY) from 2002 to 2008 of 121 major grain production counties.

<p>Relationship between remote sensing derived annual ET (<i>ET_rs</i>) and grain yield (GY) from 2002 to 2008 of 121 major grain production counties.</p

Annual mean net groundwater irrigation in 1984–2008 (a), and its change (b) from the periods of 1984–1993 to 1999–2008.

<p>Annual mean net groundwater irrigation in 1984–2008 (a), and its change (b) from the periods of 1984–1993 to 1999–2008.</p

Accumulated net groundwater consumption (a<i>Irr_nc</i>), grain yield gain (a<i>GYG</i>), and observed groundwater table depth change for Luancheng county (1984–2008).

<p>Accumulated net groundwater consumption (a<i>Irr_nc</i>), grain yield gain (a<i>GYG</i>), and observed groundwater table depth change for Luancheng county (1984–2008).</p

Validation of the model by using field experimental data from Luancheng Agro-ecosystem Experimental Station, Chinese Academy of Sciences.

<p>The numbers associated with the 5 points, representing rain-fed treatments, at the lower part refer to annual precipitation. The data for 3 filled blocks (409 mm, 366 mm, and 364 mm) are not included in the regression line because of the large deviations to the observed ET, indicating the model will underestimate actual ET for the non-irrigated lands when annual P less than around 400 mm.</p

Optimum combination of soil amendments under drip irrigation with different water sources in coastal areas of East China

The effects of drip irrigation (DI) with fresh water (FW) and brackish water (BW) on saline-alkali soil improvement were compared under treatments of five amendment combinations. The experiment was designed using the orthogonal test method and performed using an indoor DI system. Soil electrical conductivity (EC), pH, sodium adsorption ratio and soil nutrients were analyzed after DI both before evaporation and after one month of evaporation. The results showed that after one month of evaporation, soil EC increased by an average of 97.26% and 27.76% for the FW and BW treatments, respectively. Furthermore, it was shown that soil nutrients increased greatly under the BW treatment and that cow dung proved to be a leading agent influencing soil nutrients except available soil potassium (p<0.05). Consequently, the optimum combination of soil amendments was determined as 0.03 m3/m2 of straw, 3 kg/m2 of phosphogypsum, 0.04 m3/m2 of cow dung, 0.6 kg/m2 of humic acid and 0.18 kg/m2 of microbial fertilizer under the BW treatment

Optimum combination of soil amendments under drip irrigation with different water sources in coastal areas of East China

The effects of drip irrigation (DI) with fresh water (FW) and brackish water (BW) on saline-alkali soil improvement were compared under treatments of five amendment combinations. The experiment was designed using the orthogonal test method and performed using an indoor DI system. Soil electrical conductivity (EC), pH, sodium adsorption ratio and soil nutrients were analyzed after DI both before evaporation and after one month of evaporation. The results showed that after one month of evaporation, soil EC increased by an average of 97.26% and 27.76% for the FW and BW treatments, respectively. Furthermore, it was shown that soil nutrients increased greatly under the BW treatment and that cow dung proved to be a leading agent influencing soil nutrients except available soil potassium (p<0.05). Consequently, the optimum combination of soil amendments was determined as 0.03 m3/m2 of straw, 3 kg/m2 of phosphogypsum, 0.04 m3/m2 of cow dung, 0.6 kg/m2 of humic acid and 0.18 kg/m2 of microbial fertilizer under the BW treatment