Hydrology & Meteorology

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https://hdl.handle.net/20.500.14540/130

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Browsing Hydrology & Meteorology by Subject "DSSAT 4.7 crop model"

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    Multi-Year Prediction of Rice Yield As Affected by Changing Agro-Climatic Indices in Nawalparasi Using Dssat Crop Model
    (Department of Hydrology and Meteorology, 2020) Adhikari, Shailesh
    Nawalparasi district is one of the major production domain of rice however, its yield over last 30 years have been majorly affected by anomalies of agro-climatic indices like fluctuating maximum and minimum temperatures, solar radiation and rainfall. Even though, Department of Hydrology and Meteorology is the prime institute to record the historical weather data in Nepal, some major indicators like solar radiation are missing from their data repository. Therefore, NASA Power data of 33 years records (1985-2018) were purposively selected and validated for the study of the multi-year prediction of agroclimatic scenarios on yield of rice in Nawalparasi district. The trend analysis on grain yields of rice was correlated over the historical records of maximum and minimum temperatures along with rainfall. A positive correlation was found with rainfall with wellformed regression equations as well as strong coefficient of determination (R² value of 0.71). However, the yield was found to be negatively correlated with the maximum temperature (R² value of -0.56) and minimum temperature (R² value of -0.11). Cropping Systems model CERES-Rice embedded in Decision Support System for Agro-technology Transform (DSSAT) ver 4.7 model was used to study the multi-year prediction of rice yield over the recorded and simulated climatic scenarios. The data set to run the CSMCERES-Rice model taken from the well predicted and validated crop model Sukkha-5 cultivar of rice and was well used in Terai condition of clay loam soil, resembling the production domain of the project sites. The simulation results using DSSAT model over the 33 years of weather data were found to be very closely agreeing with the observed data of the rice yield recorded from the Ministry of Agriculture and Livestock Development in Nepal. The multi-year prediction of the weather years was also done after following IPCC (2007) scenario using environmental modification section of the DSSAT ver 4.7 models and result showed that the rice yields for few years can only be sustained by using the present crop varieties and urged for the development of climate change ready crop varieties to feed the increasingly growing population. Simulation of the model showed that the rice yield will be decreased by about 62% at the end of 2080s comparing to the standard condition. Agro-climatic indices mainly rainfall was found to be more sensitive for rice production in Central Terai including Nawalparasi district, Nepal. Keywords: Agro-climatic indices, DSSAT 4.7 crop model, Multi-year prediction, Rice yield
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    Multi-Year Prediction of Wheat Yield as Influenced by Changing Agro-Climatic Indices in Kapilvastu Using Dssat Crop Model
    (Department of Hydrology and Meteorology, 2020) Dhakal, Devid
    Central Terai in Nepal is the major production domain of wheat; however, wheat yields have been majorly affected by anomalies of agro-climatic indices like fluctuating maximum and minimum temperatures, solar radiation and rainfall. NASA Power data over 33 years records (1985-2018) were purposively download and compared with the ground station measured data for the study of study by using four years of weather data (1986, 1996, 2006 and 2016) randomly selected years for the multi-year prediction of agroclimatic scenarios on yields of wheat in Kapilvastu district, of Central Terai, Nepal. The relationship between the DHM recorded weather data and the NASA power data was found fairly valid and safe to see the long-term climate change impacts. At Kapilvastu the annual average and maximum temperatures were found to be decreasing by 0.017˚C and 0.046˚C per year, respectively, whereas the minimum temperature was increasing by 0.011˚C. Similarly, the total precipitation was increased by 28.63mm per year and solar radiation was decreasing by 0.035 MJm -2 per year. The trend analysis on grain yields of wheat were correlated over the historical records of maximum temperature, minimum temperature, rainfall and solar radiations. A positive correlation was found with minimum temperature and rainfall. However, the yield was found to be negatively correlated with the maximum temperature and solar radiations. Cropping Systems model CERES-Wheat embedded in Decision Support System for Agro-technology Transform (DSSAT) ver 4.7 model was used to study the multi-year prediction of wheat yield over the changing agro-climatic scenarios after following IPCC (2007) scenario using environmental modification section of the DSSAT ver 4.7 models. The data sets to run the CSM-CERES- Wheat models have been taken from the well predicted and validated crop model with WK-1204 cultivar of wheat which is popularly grown in Terai and hills condition of sandy-clay loam soil, resembling the production domain of the project sites. The simulation results using DSSAT model over the 33 years of weather data were found to be very closely agreeing with the observed data of the wheat yield recorded from the Ministry of Agriculture and Livestock Development in Nepal. The trend analysis, regression and correlation studies and from sensitivity analysis using DSSAT, all have resulted the uniform relationship between agroclimatic indices and wheat yields. The different climate change scenarios as advocated by IPCC (2007) for 2020, 2050, and 2080 were studied to simulate the yield performance of WK-1204 cultivar of wheat. Increased in temperature by 1˚C will increase the wheat yield and furthermore increased in temperature decreased the yield under the present levels of agronomic management options. The result showed that the wheat yields for few years can only be sustained by using the present crop varieties and urged for the development of climate change ready crop varieties to feed the increasingly growing population. Keywords: Agro-climatic indices, DSSAT 4.7 crop model, Multi-year prediction, Wheat yield v