Kirsten Kienzler

Evaluation of the CropSyst model for simulating the potential yield of cotton

Cotton produced in Uzbekistan has a low water and fertilizer use efficiency and yield is below its potential. To introduce improved production methods, knowledge is required on how the agro-ecosystem would respond to these alternatives. For this assessment, dynamic simulation models such as the crop-soil simulation model CropSyst are useful tools. CropSyst had never been applied to cotton, so it first was calibrated to the cotton variety Khorezm-127 grown under researcher-managed optimal conditions in the Khorezm region of Uzbekistan in 2005. The model performance was evaluated with a data set obtained in 2004 on two farmer-managed sites. Both data sets comprised in-situ measurements of leaf area index and aboveground biomass. In addition, the 2004 data set included the normalized difference vegetation index derived from satellite imagery of the two cotton fields, which provided estimations of leaf area index with a high temporal resolution. The calibrated optimum mean daily temperature for cotton growth was 25 °C., the specific leaf area 13.0 m2 kg−1, the leaf/stem partition coefficient 3.0, the biomass/transpiration coefficient 8.1 kg m−2 kPa m−2 and the radiation use efficiency 2.0 g MJ−1. Simulations matched 2005 data, achieving a root mean square error between simulated and observed leaf area index and aboveground biomass of 0.36 m2 m−2 and 0.97 Mg ha−1, respectively. The evaluation showed that early cotton growth and leaf area index development could be simulated with sufficient accuracy using CropSyst. However, final aboveground biomass was slightly overestimated by CropSyst, because some unaccounted plant stress at the sites diminished actual aboveground biomass, leading to a root means square error of around 2 Mg ha−1. Some characteristics of cotton, such as the indeterminate growth habit, could not be incorporated in detail in the model. However, these simplifications were compensated by various other advantages of CropSyst, such as the option to simulate crop-rotation or its generic crop growth routine that allows modelling of additional, undocumented crops. The availability of normalized difference vegetation index data with a high temporal and acceptable spatial resolution opened possibilities for a precise, in-expensive and resource-efficient way of model evaluation.

Crop Diversification in Support of Sustainable Agriculture in Khorezm

Escalating soil degradation caused by soil salinity and rising saline groundwater tables, limits crop production in the irrigated lowlands of arid Uzbekistan. Crop diversification is one option for obtaining more stable farm incomes while improving natural resource use and environmental sustainability. Although the agro-climatic conditions in the country allow growing a wide variety of crops, few crops (cotton, winter wheat, rice, maize) dominate the crop portfolio, which also reflects the restrictions imposed by the state. In the Khorezm region in northwest Uzbekistan, we examined the economic and ecological suitability of alternative crops in a stepwise approach. A literature review resulted in a list of about 30 crops that would theoretically fit the agro-climatic conditions in this region. For field research, five crops with a high potential were selected based on socio-economic (potential income) and bio-physical (potential yield, crop quality, options for soil improvement, water use efficiency) criteria. The crops included sorghum (Sorghum bicolor (L.) Moench), potato (Solanum tuberosum), the cash crop indigo (Indigofera tinctoria), and the food and feed crops mung bean (Vigna radiata) and sweet maize (Zea Mays L.). Field experiments were complemented with laboratory analyses and mathematical modeling for estimating the potential economic and ecological benefits from these crops. Three potato varieties from Germany out-yielded the local variety by at least 50%. Sorghum, indigo, maize and mung bean grew well on marginal lands and obtained very high revenues. Findings from the simulation runs demonstrate that crops such as maize for grain, potato and fodder crops could play an important role in coping with risks in drought years and for securing farm income. Field experiments and modeling results based on this extensive data set from Khorezm allow upscaling to regions in Central Asia with similar agro-climatic conditions.

Groundwater Contribution to N fertilization in Irrigated Cotton and Winter Wheat in the Khorezm Region, Uzbekistan

In the irrigated areas of Uzbekistan the nitrogen (N) fertilizer efficiency in crop production is low, as N is partially leached to the groundwater. The N-fertilizer use is still based on recommendations from Soviet times when fertilizer supply was subsidized to maximize production at all costs. Also irrigation water is applied sub-optimally, and groundwater levels have been reported to be of less than 1 m during the vegetation period. As substantial upward movement of salts from the groundwater is frequently observed due to high evapotranspiration rates, it can be expected that nitrate from leached N fertilizer may also move in the soil profile thus influencing the N balance of the soil. In this study we therefore estimated the groundwater contribution to N-fertilization to improve the N management while sustaining yields and quality and reducing negative environmental effects of groundwater nitrate. Nitrate in irrigation and groundwater was measured during spring and summer. Data were complemented with field measurements of groundwater levels, irrigation and N-fertilizer amounts. With the CropSyst model, upward fluxes of groundwater and evapotranspiration rates were derived, as we could not measure these in the field. We calculated the contribution from the upward flux of nitrate-containing groundwater to the N content in the rooting zone. The difference between the simulated actual evapotranspiration and the irrigated water amount was 335 mm. The average nitrate content in the groundwater was low under summer crops (2 mg nitrate L−1) and higher under the spring crop (24 mg nitrate L−1). However, the temporal dynamics were very much linked to the irrigation and fertilization practices, and corresponded to the changes in groundwater table depth: Almost immediately after fertilization, the nitrate content increased to up to 75 mg nitrate L−1 in spring. At the end of the growing period, the nitrate amounts had reached levels similar to those prior to fertilization. A groundwater contribution of 355 mm and an average nitrate concentration of up to 75 mg nitrate L−1 would enhance the N stocks in the soil by up to 5–61 kg N ha−1. This is equivalent to one single fertilizer application event. However, in case farmers would rely on the input of N through the groundwater to satisfy crop demand and consequently reduce N fertilizer application levels, the N concentrations in the groundwater would reduce and become an unreliable source.

Optimal Irrigation and N-fertilizer Management for Sustainable Winter Wheat Production in Khorezm, Uzbekistan

The efficiency of the nitrogen (N) application rates 0, 120, 180 and 240 kg N ha−1 in combination with low or medium water levels in the cultivation of winter wheat (Triticum aestivum L.) cv. Kupava was studied for the 2005–2006 and 2006–2007 growing seasons in the Khorezm region of Uzbekistan. The results show an impact of the initial soil Nmin (NO3-N + NH4-N) levels measured at wheat seeding on the N fertilizer rates applied. When the Nmin content in the 0–50 cm soil layer was lower than 10 mg kg−1 during wheat seeding in 2005, the N rate of 180 kg ha−1 was found to be the most effective for achieving high grain yields of high quality. With a higher Nmin content of about 30 mg kg−1 as was the case in the 2006 season, 120 kg N ha−1 was determined as being the technical and economical optimum. The temporal course of N2O emissions of winter wheat cultivation for the two water-level studies shows that emissions were strongly influenced by irrigation and N-fertilization. Extremely high emissions were measured immediately after fertilizer application events that were combined with irrigation events. Given the high impact of N-fertilizer and irrigation-water management on N2O emissions, it can be concluded that present N-management practices should be modified to mitigate emissions of N2O and to achieve higher fertilizer use efficiency.

Evaluation of CropSyst for Simulating the potential yield of cotton in Uzbekistan

Cotton produced in Uzbekistan has a low water and fertilizer use efficiency and yield is below its potential. To introduce improved production methods, knowledge is required on how the agro-ecosystem would respond to these alternatives. For this assessment, dynamic simulation models such as the crop-soil simulation model CropSyst are useful tools. CropSyst had never been applied to cotton, so it first was calibrated to the cotton variety Khorezm-127 grown under researcher-managed optimal conditions in the Khorezm region of Uzbekistan in 2005. The model performance was evaluated with a data set obtained in 2004 on two farmer-managed sites. Both data sets comprised in-situ measurements of leaf area index and aboveground biomass. In addition, the 2004 data set included the normalized difference vegetation index derived from satellite imagery of the two cotton fields, which provided estimations of leaf area index with a high temporal resolution. The calibrated optimum mean daily temperature for cotton growth was 25 °C., the specific leaf area 13.0 m2 kg−1, the leaf/stem partition coefficient 3.0, the biomass/transpiration coefficient 8.1 kg m−2 kPa m−2 and the radiation use efficiency 2.0 g MJ−1. Simulations matched 2005 data, achieving a root mean square error between simulated and observed leaf area index and aboveground biomass of 0.36 m2 m−2 and 0.97 Mg ha−1, respectively. The evaluation showed that early cotton growth and leaf area index development could be simulated with sufficient accuracy using CropSyst. However, final aboveground biomass was slightly overestimated by CropSyst, because some unaccounted plant stress at the sites diminished actual aboveground biomass, leading to a root means square error of around 2 Mg ha−1. Some characteristics of cotton, such as the indeterminate growth habit, could not be incorporated in detail in the model. However, these simplifications were compensated by various other advantages of CropSyst, such as the option to simulate crop-rotation or its generic crop growth routine that allows modelling of additional, undocumented crops. The availability of normalized difference vegetation index data with a high temporal and acceptable spatial resolution opened possibilities for a precise, in-expensive and resource-efficient way of model evaluation.