Assessment of nutrient leaching in flooded paddy rice field experiment using Hydrus-1D

Solute runoff and leaching are two direct pathways of nutrient pollution from paddy fields into water systems. Due to the dynamic nature of paddy fields, solute transport and transformation processes are complex and difficult to understand. Therefore, in this study, nitrogen (N) transport in flooded paddy rice fields with conventional irrigation (flooding irrigation) in the Tanjung Karang Rice Irrigation Scheme (TAKRIS), Sawah Sempadan, were observed and modelled using the Hydrus-1D numerical model during two consecutive rice growing seasons. Based on solute transport analysis results, it was observed that 50.3% to 48% of percolated N was accumulated in the top 40-cm soil layer, while 49.7% to 52% of leachate N was lost below the 40-cm soil layer (40–100 cm) during the off and main seasons, respectively. About 85% of N leaching loss was in the form of NO3−. NO3− was absorbed by rice roots within 0–40 cm and the denitrified root zone; however, there was still a large quantity of NO3− which remained below the root zone, which was quickly transported downward along with the leachate water. The NH4+ concentration in subsurface water was lower than the NO3− concentration due to various processes that removed NH4+ from the topsoil layer (0–40 cm), such as ammonium volatilisation, nitrification, and plant uptake. The total leaching loss of N was 34.9 and 27.9 kg/ha during the off and main seasons, respectively. The simulated and observed water flow and nutrient leaching were in a good agreement (R2 = 0.98, RMSE = 0.24). The results showed that Hydrus-1D successfully simulated the solute movement under different soil depths during the study period

Modeling solute transport for improved fertiliser use in rice production system

Quantification of water and nutrients and their interactions of a paddy field environment are crucial for the improved utilization of fertilizers for the sustainable rice production. Solutes runoff and leaching are two direct pathways of nutrient pollution from paddy fields to water resources systems. Due to the dynamic nature of paddy fields, solute transport and transformation process are complex and difficult to understand. The past investigation on the water balance components using multifarious parameters did not reflect the true condition of paddy field environments. Quantification of agrochemical losses from paddy fields are generally related to the amount of inflow and outflow water in the paddy field environment which yet to be measured accurately. In order to overcome the challenges, the modern monitoring devices together with sensors and data logging system were installed for intensive field observations in a paddy and developed empirical models to quantify the solute losses through the surface and sub-surface water leaving from a paddy field system for the better utilization of fertilizers (N, P, K). The intensive field investigation was carried out in a paddy plot at Sawah Sempadan compartment of the Tanjung Karang Rice Irrigation Scheme (TAKRIS) for two rice growing seasons (January-April and July-October) in 2017. Firstly, the water balance components in a paddy plot was analysed from the intensive field observations with 1-10 minutes interval of a paddy field. Water balance analysis results revealed that irrigation water accounted 59.6 % of the total water input (irrigation and rainfall) during the January to April (Off Season). However, about 76.2% of total water input during the July to October (Main season). The amount of rainfall contributed to 23.8% and 40.4% of total water input in the main season and off-season, respectively. Drainage flow accounted 37.3% and 43.7% of the total water input during off season and main season, respectively. The daily evapotranspiration accounted 41.7% and 61% of total water input during offseason and main season, respectively. Observed seepage and percolation of 17.1% to 19.2% of total water input accounted during both seasons respectively. The yield of the experimental plot was obtained 2.5 t/ha and 2.7 t/ha for the off season and main season, respectively. Finally, the water productivity index was analyzed 0.72 kg m-3 during off-season and 0.78 kg m-3 during main season, respectively. Based on solute transport analysis, the accumulated total nitrogen (T-N) of 50.3% to 49.7% estimated in the top 40 cm soil layer while 49.7 % to 53 % T-N as leachate obtained below 40 cm soil layer (40-100 cm) during off season and main season, respectively. About 85% of N leaching losses were in the form of NO3-, however there was still a large quantity of NO3- remained below root zone that contributes the groundwater. The total leaching loss of T-N was 34.9 and 27.9 kg/ha during off and main seasons respectively. The estimated loss of total phosphorous during the two rice growing seasons were 3 and 1.7 kg/ha, respectively. The total amount of T-N, TP and K loss through drainage were 27.7 and 18.5, 2.2 and 1.1, 5.9 and 3.5 kg/ha during off-season and main season, respectively. The Hydrus-1D was applied to simulate water and solute movement under different soil depths of 20, 40, 60, 80 and 100 cm in real paddy environment experiments. The simulated and observed water flow and nutrient leaching were in good agreement (R2= 0.98, RMSE = 0.24). Hydrus-1D simulation showed the similar patterns of the water and solute movement under different soil depths during the study period. The observed and simulated N, P and K concentration in paddy was high due to fertilization and other climatic factors. Therefore, reduction of excessive fertilizer rate especially during early rice growing period and adaptation of water saving techniques can reduce the pollutant risks from paddy soil. Regression analyses were performed for the development of the improved fertilizer use models. Multiple linear regression analysis was performed to know the relationships between EC versus solutes (N, P and K) during the both seasons. The polynomial regression analysis was fitted to evaluate whether EC changes has an impact on N, P and K concentrations in paddy field. Finally, empirical models were established to estimate the concentrations of N, P and K using two rice growing season data. MS Excel solver program were used to develop the empirical models. The results obtained a strong agreement between observed and predicted N, P, and K with the determination coefficients (R2) of 0.91 and 0.95 during the both seasons. Therefore, the models could be useful in predicting the solute concentration changes within root zone and below root zone during entire rice growing season for better utilization of fertilizers

Utilization of global circulation models for climate change impacts assessments on agricultural water and crop production: a review

Agricultural sectors are among the vulnerable areas which could be affected by the projected climatic change and associated global warming. Without adaption, climate change is commonly precarious for agriculture production, economies and communities dependent on agriculture. However, with appropriate adaption,vulnerabilities can be reduced and there are numerous opportunities to be realized. Therefore, it is critical to early find and prepare for adaptation strategies for various agro-systems in order to prevent adverse effects on water, crop production and economic conditions. In this review paper, we have summarized and compiled the effect of climatic change on irrigation water demands (IWR), crop evapotranspiration (ET) and crop yield production. The role of utilizing various Global Circulation Models for climate change impact studies was also included and tabulated.Climate changes may cause crop damages, low yield, and increased production cost resulting to income losses for farmers, grow their lower income level, and enhance their annual unemployment. Currently, the techniques to evaluate climate change consist of the statistical method computed from the historical data as well as the GCM simulation model. Nevertheless, various GCMs result in completely different results. Undoubtedly, there is uncertainty in any climate change analysis, thus, it's commended that several models need to be used where possible to prevent improper planning or adaptation responses especially in the near future

Prioritization of zoonoses for multisectoral, One Health collaboration in Somalia, 2023

Background The population of Somalia is vulnerable to zoonoses due to a high reliance on animal husbandry. This disease risk is exacerbated by relatively low income (poverty) and weak state capacity for health service delivery in the country as well as climate extremes and geopolitical instability in the region. To address this threat to public health efficiently and effectively, it is essential that all sectors have a common understanding of the priority zoonotic diseases of greatest concern to the country. Methods Representatives from human, animal (domestic and wildlife), agriculture, and environmental health sectors undertook a multi-sectoral prioritization exercise using the One Health Zoonotic Disease Prioritization tool developed by the US CDC. The process involved: reviewing available literature and creating a longlist of zoonotic diseases for potential inclusion; developing and weighting criteria for establishing the importance of each zoonoses; formulating categorical questions (indicators) for each criteria; scoring each disease according to the criteria; and finally ranking the diseases based on the final score. Participants then brainstormed and suggested strategic action plans to prevent, and control prioritized zoonotic diseases. Results Thirty-three zoonoses were initially considered for prioritization. Final criteria for ranking included: 1) socioeconomic impact (including sensitivity) in Somalia; 2) burden of disease in humans in Somalia); 3) availability of intervention in Somalia; 4) environmental factors/determinants; and 5) burden of disease in animals in Somalia. Following scoring of each zoonotic disease against these criteria, and further discussion of the OHZDP tool outputs, seven priority zoonoses were identified for Somalia: Rift Valley fever, Middle East respiratory syndrome, anthrax, trypanosomiasis, brucellosis, zoonotic enteric parasites (including Giardia and Cryptosporidium), and zoonotic influenza viruses. Conclusions The final list of seven priority zoonotic diseases will serve as a foundation for strengthening One Health approaches for disease prevention and control in Somalia. It will be used to: shape improved multisectoral linkages for integrated surveillance systems and laboratory networks for improved human, animal, and environmental health; establish a multisectoral public health emergency preparedness and response plans using One Health approaches; and enhance workforce capacity to prevent, control and respond to priority zoonotic diseases