Search

Soil moisture and salinity are two key factors for crop production in arid irrigation districts. It is critical to modify soil water-salt dynamics and crop growth on a regional scale for the sustainable agriculture. In this paper, a distributed agro-hydrological model that well considers the spatial variability of soil and hydrological factors was developed to simulate soil water movement, solute transport and crop growth process on the regional scale. Jiefangzha Irrigation System (JIS) of the Hetao Irrigation District was selected as the study area. The JIS was divided into 201 homogeneous simulation units based on the combinations of weather-soil-crop-irrigation. In this way, the one-dimensional agro-hydrological model--HYDRUS-EPIC (HYDRUS-1D coupled with EPIC crop growth module), was used and expanded to the regional scale. Field experiments were conducted in 2012 and 2013. The dataset of soil moisture, soil solute concentration, leaf area index (LAI) and crop yield were collected at 40 monitoring points, and used for model calibration and validation. Simulated soil moisture and salinity concentration in the root zone showed good agreement with the measured values. During the calibration process, root mean square error (RMSE), mean relative error (MRE) and coefficient of determination (R²) for soil moisture were 0.03 cm³/cm³, 0.3% and 0.67, respectively. For salinity concentration, RMSE, MRE and R² were 2.72 g/L, -13.5% and 0.53. LAI and crop yields were fitted well with the observations. MRE values for the estimated and measured LAI and crop yields were 1.0% and 1.1%, and R² were both larger than 0.90 for these two items. During the validation process, RMSE, MRE, and R² were 0.04 cm³/cm³, 2.6%, 0.57 for soil moisture, and 2.62 g/L, -4.5%, 0.51 for salinity concentration, respectively. And MRE and R² were 9.1%, 0.88 for LAI, and -1.9%, 0.92 for crop yields. These results showed that the distributed agro-hydrological model was able to simulate the soil water flow, salt transport, and crop growth process in JIS with accuracy. The calibrated and validated model was then applied to predict spatial distribution of soil moisture, salinity concentration, crop evaporation and crop yields of the study area in present irrigation water management practices. Effective saturation and salinity concentration in the root zone were chosen to represent soil water and salinity stress on crop growth. Results showed that effective saturation ranged from 0.44 to 0.90 with an average of 0.7 for the JIS. In most areas, soil water could meet crop water consumption needs. In the areas where groundwater depth (GWD) was less than 1.3 m, root water uptake was limited due to waterlogging. The average salinity concentration in the root zone varied from 3.1 g/L in the northwest to 13.5 g/L in the northeast with an average of 6.4 g/L for the whole district. High soil salinity concentration limited crop production seriously. Corresponding to the spatial distribution of salinity concentration in the root zone, crop relative yield (ratio of actual yield and average yield of JIS) ranged from 0.33 to 1.33. The results suggested that for the northeastern part, where GWDs were larger than 2.0 m, more irrigation was needed for leaching salt. It was also better to plant more salt tolerant crops in these areas. In northwestern and southwestern parts, shallow groundwater levels intensified waterlogging or salinity accumulation problems. The study indicated that it is better to keep the groundwater depth not shallower than 1.3 m for maintaining the crop yields. [ABSTRACT FROM AUTHOR]

Evapotranspiration is the main way of soil water depletion in field, and soil evaporation is an important part of evapotranspiration, and it may account for 32%-50% of the total evapotranspiration during the whole crop growth period. Soil evaporation does little effect on the formation of crop biomass and yield, so reducing soil evaporation is important for improving water use efficiency and agricultural water saving management. In recent years, straw mulching has been used widely due to its capability of improving soil structure, increasing soil organic matter, reducing soil evaporation and maintaining soil water content. Mulching affects exchange of energy and heat between soil surface and free air, so the mechanism for soil evaporation under mulching condition may be different from that without mulching. Considering the fast development of straw mulching, therefore modeling soil evaporation under straw mulching is of important for making agricultural water management. In this paper, the factors (soil water content and mulching amount) that affect soil evaporation had been analyzed, the values of mulching resistance were calculated, the equations for calculating resistance of mulching and the resistances of soil evaporation and soil evaporation under straw mulching had been established, the parameters for the equation had been determined. The experiment was carried out from late July to middle August in 2010 and from middle July to middle August in 2011, respectively. The undisturbed soil with winter wheat plants was prepared and put into plastic buckets when winter wheat was maturity, two main treatments (stubble and stubble+mulch treatments) were set up, there were five sub-treatments for each of the two main treatments. The stubble heights for stubble treatments were 0, 5, 15, 25, 35cm. Stubble heights were 0, 5, 15, 25, 35 cm with mulching amounts of 0.47, 0.43, 0.348, 0.267, 0.187 kg/m2 in stubble+mulch treatment, respectively. The total biomass (stubble biomass) for each stubble treatment was 0, 0.04, 0.122, 0.203, 0.283 kg/m2, respectively; the total biomass (stubble biomass and mulching amount) in each stubble+mulch treatment was 0.47 kg/m2. During the prepared period, water was applied to the soil until all the soil in the plastic bucket was saturated, and then the excessive water was discharged out off plastic bucket through small hole at the bottom of plastic bucket to make sure soil water content was about field capacity at the beginning of the experiment. The soil evaporation and soil temperature were measured daily and soil water content in 0-2 cm depth was measured every 2 ~ 5 days according to the soil evaporation. Meteorological data, including relative humidity, hourly mean air temperature, and wind speed were measured with an automatic weather station. Results showed that the relative soil evaporation (the ratio of soil evaporation to water evaporation from 20 cm diameter pan) kept relatively stable when soil water content was higher than 0.23 cm3/cm3 (60% field capacity), the ratio declined linear with the decreasing of soil water content when soil water content was higher than 0.05 cm3/cm3 (wilting point) and less than 0.23 cm3/cm3. Mulching affected soil evaporation, reducing stubble height and increasing mulching amount could reduce soil evaporation when the total biomass was the same. The total amount of soil evaporation during experiment period reduced by 8%-51% under stubble+mulch treatment with mulching amount of 0.348-0.47 kg/m2 compared with stubble treatment when stubble height was 0-15 cm. Mulching resistance was 158-600 s/m in this study and it was exponentially increasing with the mulching amount, and the resistance of soil layer decreased linearly with the soil water content increasing when soil water was less than 0.23 cm3/cm3 and higher than 0. 05 cm3/cm3. The validation processes showed that the developed method and related parameters (mulching resistance and the resistance of soil layer) performed well for modeling soil evaporation under mulching condition. [ABSTRACT FROM AUTHOR]

Reduction of water diversion from the Yellow River will intensify water shortage problems in the Yinbei Irrigation District (YID). Reasonable use of groundwater for irrigation is helpful to maintain the agricultural production. Groundwater exploitation may cause groundwater level declines in local areas. This helps to reduce the salinity accumulation in the root zone but decreases the capillary rise. Thus, it is important to figure out the responses of soil water-salt dynamics and crop yields to groundwater table fluctuations for salinity control and stable yields. In this study, HYDRUS-1D model was modified by coupling with the EPIC (erosion-productivity impact calculator) crop growth module for simulating agro-hydrological processes. The new crop module could simulate crop height, leaf area index (LAI), above-ground biomass and crop yield. The information between HYDRUS-1D and EPIC was exchanged by daily step. Root water uptake under water and salt stress was calculated with HYDRUS-1D and imported to EPIC to limit crop growth. EPIC module estimated crop height, LAI and root depth for HYDRUS-1D to calculate soil water-solute dynamics. HYDRUS-1D assumed that soil evaporation remained at the potential rate unless pressure head of the soil surface decreased to a prescribed value. After then this prescribed value was set as a constant head to renew the top boundary condition. However, it cannot reasonably reflect the decrease stage of soil evaporation when using the constant head boundary. This may overestimate soil evaporation. Therefore, a new soil evaporation module, estimating soil evaporation reduction coefficient using soil water content of the top layer (0-10 cm), was added for better describing the soil evaporation under shallow water tables. With the experimental data collected from the maize field in 2008, the model was calibrated by the data of groundwater irrigation treatment and validated by the data of canal irrigation treatment. Simulated soil water content and solute concentration in the root zone (0-90 cm) showed good agreement with the measured values. Root mean square error (RMSE), mean relative error (MRE) and coefficient of determination for soil moisture were 0.03 cm3/cm3, 3.4% and 0.78, respectively. For solute concentration, RMSE, MRE, coefficient of determination were 1.6 g/L, 1.3% and 0.29, respectively. LAI and above-ground biomass values were fitted well with the observations. MRE values for estimated and measured LAI and above-ground biomass were 5.9% and 10.6%, and R2 were both larger than 0.95 for these two items. The model was then used to assess the impacts of groundwater table and irrigation changes on soil water-salt dynamics and maize yields. Nine groundwater depth (GWD) scenarios (100, 110, 125, 140, 155, 170, 185, 200 and 250 cm) and 6 irrigation treatments (0.6, 0.8, 1.0, 1.2, 1.4 and 1.6 times of the present irrigation) were considered. The results showed that soil water content and salt storage in the root zone declined with the reduction of groundwater level and irrigation amount. Due to the decrease of groundwater contribution and soil moisture, lowering groundwater depth resulted in a gradual increase of the average solute concentration in the root zone. Maize yields increased first and then decreased as the groundwater table declined. Generally, the maximum yields were achieved when GWD was between 140 and 155 cm. The maize yields may decrease with reducing the irrigation amount, therefore water-saving strategies were not recommended for local farmers with low incomes. Finally, the optimum groundwater depth of 140-155 cm was suggested, and three irrigations with an amount of 900 m3/hm2 for each will be applied during maize growing period. [ABSTRACT FROM AUTHOR]