Eunjin Han | Columbia University (original) (raw)

Papers by Eunjin Han

Research paper thumbnail of SMAP soil moisture data assimilation impacts on water quality and crop yield predictions in watershed modeling

Research paper thumbnail of Planting Rice at Monsoon Onset Could Mitigate the Impact of Temperature Stress on Rice–Wheat Systems of Bihar, India

Atmosphere

The rice–wheat rotation is the dominant cropping system in Bihar, where food security of the rura... more The rice–wheat rotation is the dominant cropping system in Bihar, where food security of the rural population depends heavily on the production of rice and wheat. In Bihar, farmers plant rice after the first significant rains, and climatic shocks induced by low temperatures and terminal heat stress at the end of the corresponding season can significantly affect rice and wheat yields. The present work evaluates the benefit of using an earlier date for planting rice, following the monsoon onset, in reducing thermal stress on rice–wheat systems. High-resolution gridded crop simulations using the APSIM model were performed to simulate potential yields using the monsoon onset and the farmers’ practice as planting dates. The monsoon onset was calculated using an agronomic definition, and farmers’ practice dates were estimated using satellite data. The results were analyzed in terms of planting dates, yields, and the incidence of temperature stress on rice and wheat by means of the APSIM y...

Research paper thumbnail of Evaluating Agronomic Onset Definitions in Senegal through Crop Simulation Modeling

Atmosphere

Rainfed agriculture in Senegal is heavily affected by weather-related risks, particularly timing ... more Rainfed agriculture in Senegal is heavily affected by weather-related risks, particularly timing of start/end of the rainy season. For climate services in agriculture, the National Meteorological Agency (ANACIM) of Senegal has defined an onset of rainy season based on the rainfall. In the field, however, farmers do not necessarily follow the ANACIM’s onset definition. To close the gap between the parallel efforts by a climate information producer (i.e., ANACIM) and its actual users in agriculture (e.g., farmers), it is desirable to understand how the currently available onset definitions are linked to the yield of specific crops. In this study, we evaluated multiple onset definitions, including rainfall-based and soil-moisture-based ones, in terms of their utility in sorghum production using the DSSAT–Sorghum model. The results show that rainfall-based definitions are highly variable year to year, and their delayed onset estimation could cause missed opportunities for higher yields ...

Research paper thumbnail of Planting Aman Rice at Monsoon Onset Could Mitigate the Impact of Temperature Stress on Rice-Wheat Systems of Bihar, India

The rice-wheat rotation is the dominant cropping system in Bihar, where food security of the rura... more The rice-wheat rotation is the dominant cropping system in Bihar, where food security of the rural population depends heavily on the production of rice and wheat. In Bihar, climatic shocks induced by low temperatures and terminal heat stress can significantly affect rice and wheat yields. The present work evaluates the benefit of using the monsoon onset as the date for planting rice in reducing thermal stress on rice-wheat systems. High-resolution gridded crop simulations using the APSIM model were performed to simulate potential yields of rice and wheat using the monsoon onset and the farmers’ practice as planting dates. The monsoon onset was calculated using an agronomic definition and farmers’ practice dates were estimated using satellite data. Model outputs were analyzed in terms of planting dates, yields, and the incidence of low temperature stress on rice and high temperature stress on wheat by means of the APSIM yields limiting factors. The results show that the rice planting...

Research paper thumbnail of Re-prioritizing climate services for agriculture: Insights from Bangladesh

Research paper thumbnail of Global High-Resolution Soil Profile Database for Crop Modeling Applications

One of the obstacles in applying advanced crop simulation models such as DSSAT at a grid-based pl... more One of the obstacles in applying advanced crop simulation models such as DSSAT at a grid-based platform is the lack of gridded soil input data at various resolutions. Recently, there has been many efforts in scientific communities to develop spatially continuous soil database across the globe. The most representative example is the SoilGrids 1km released by ISRIC in 2014. In addition recent AfSIS project put a lot of efforts to develop more accurate soil database in Africa at high spatial resolution. Taking advantage of those two available high resolution soil databases (SoilGrids 1km and ISRIC-AfSIS at 1km resolution), this project aims to develop a set of DSSAT compatible soil profiles on 5 arc-minute grid (which is HarvestChoice’s standard grid). Six soil properties (bulk density, organic carbon, percentage of clay and silt, soil pH and cation exchange capacity) available from the original SoilGrids 1km or ISRIC-AfSIS were directly used as DSSAT inputs. We applied a pedo-transfer function to derive some soil hydraulic properties (saturated hydraulic conductivity, soil water content at field capacity, wilting point and saturation) which are critical to simulate crop growth. For other required variables, HarvestChoice’s HC27 database are used as a reference. Final outputs are provided in *.SOL file format (DSSAT soil database) for each country at 5-min resolution. In addition, uncertainty maps for organic carbon and soil water content at wilting points at the top 15 cm soil layers were generated to provide brief idea about accuracy of the final products. The generated soil properties were evaluated by visualizing their global maps and by comparing them with IIASA-IFPRI cropland map and AfSIS-GYGA’s available water content maps.Non-PRIFPRI1; HarvestChoice; CRP2EPTD; PIMCGIAR Research Program on Policies, Institutions, and Markets (PIM

Research paper thumbnail of Parameter Estimation of Improved Rice Varieties in the Philippines Using GENCALC, GLUE and NMCGA

Research paper thumbnail of Assessing methods for developing crop forecasting in the Iberian Peninsula

Seasonal climate prediction may allow predicting crop yield to reduce the vulnerability of agricu... more Seasonal climate prediction may allow predicting crop yield to reduce the vulnerability of agricultural production to climate variability and its extremes. It has been already demonstrated that seasonal climate predictions at European (or Iberian) scale from ensembles of global coupled climate models have some skill (Palmer et al., 2004).

Research paper thumbnail of Toward Better Understanding of the Impacts of Climate Variability on Agricultural Decision-Making and Longer-Term Adaptation II Posters

Research paper thumbnail of On the utility of agronomic monsoon onset definitions for rainfed Aman rice in Bangladesh

The monsoon-season ‘aman' rice crop contributes approximately 40% of total rice production in... more The monsoon-season ‘aman' rice crop contributes approximately 40% of total rice production in Bangladesh, where per-capita rice consumption rates are among the highest in the world. Aman rice is primarily rainfed and relies largely on monsoon rainfall, more specifically monsoon onset and withdrawal. Aman rice farmers’ perception on the monsoon onset for the preparation of seedling does not necessarily coincide with typical meteorological onset definitions and varies with different locations. Therefore, agronomic definitions of monsoon onset, rather than meteorological definitions are needed in order to produce climate forecast information that can better support smallholder farmers’ decision making, and the definitions should be tailored for different regions. In this study, we analyzed historical daily rainfall from three regional weather stations across a north-south gradient in Bangladesh where rainfed transplanted rice is the dominant summer crop. We defined threshold number...

Research paper thumbnail of Interoperable field sensor network andmulti-layered web services for agricultural applications

Research paper thumbnail of Utility of Seasonal Climate Forecasts for Agricultural Decision Supports in Ethiopia

Research paper thumbnail of Downscaling Probabilistic Seasonal Rainfall and Temperature Forecasts for Climate Risk Management in Agriculture

Research paper thumbnail of MJO teleconnections to agro-climate extremes and crop yields

Research paper thumbnail of Linking seasonal climate forecasts with crop models in Iberian Peninsula

Translating seasonal climate forecasts into agricultural production forecasts could help to estab... more Translating seasonal climate forecasts into agricultural production forecasts could help to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse conditions. In this study, we use seasonal rainfall forecasts and crop models to improve predictability of wheat yield in the Iberian Peninsula (IP). Additionally, we estimate economic margins and production risks associated with extreme scenarios of seasonal rainfall forecast.

Research paper thumbnail of Point-scale Estimation of Soil Moisture Profile through Data Assimilation with Root Zone Water Quality Model

ABSTRACT Recent developments in remote-sensing technologies have accelerated research in data ass... more ABSTRACT Recent developments in remote-sensing technologies have accelerated research in data assimilation techniques that use near-surface soil moisture observations or brightness temperature to estimate soil moisture profile. However, much of this research has been conducted at large scales to improve climate forecasts based on synthetic experiments. In this study, field measured surface soil moisture was assimilated into the one-dimensional point-scale Root Zone Water Quality Model by using two data assimilation techniques: Ensemble Kalman Filter (EnKF), and direct insertion method. Measured soil moisture data at four different depths (5cm, 20cm, 40cm and 60cm) from two subwatersheds in northeastern Indiana were used for assimilation and validation purposes. First, surface measured data from the top 5cm layer was assimilated on daily basis to estimate soil moisture in 20cm, 40cm and 60cm layers. Second, the soil moisture in the top soil layer (~5cm) was updated bi-daily (every two days) to investigate the improvement in soil moisture in the top layer through data assimilation. Daily data assimilation shows that EnKF provides better estimates of soil moisture in 20 cm layer compared to direct insertion method and model results without assimilation. Soil moisture estimates for deeper layers (40cm and 60cm) did not show significant improvement from assimilating surface soil moisture. Bi-daily assimilation shows that EnKF produced better results for 5cm and 20cm layers compared to direct insertion method. Overall, the results of this study indicate that daily (or bi-daily) assimilation of surface soil moisture improves soil moisture estimation in the upper more dynamic layers (5 and 20cm) but has little affect on deeper layers (40 and 60cm).

Research paper thumbnail of The Regional Hydrologic Extremes Assessment System: A software framework for hydrologic modeling and data assimilation

PloS one, 2017

The Regional Hydrologic Extremes Assessment System (RHEAS) is a prototype software framework for ... more The Regional Hydrologic Extremes Assessment System (RHEAS) is a prototype software framework for hydrologic modeling and data assimilation that automates the deployment of water resources nowcasting and forecasting applications. A spatially-enabled database is a key component of the software that can ingest a suite of satellite and model datasets while facilitating the interfacing with Geographic Information System (GIS) applications. The datasets ingested are obtained from numerous space-borne sensors and represent multiple components of the water cycle. The object-oriented design of the software allows for modularity and extensibility, showcased here with the coupling of the core hydrologic model with a crop growth model. RHEAS can exploit multi-threading to scale with increasing number of processors, while the database allows delivery of data products and associated uncertainty through a variety of GIS platforms. A set of three example implementations of RHEAS in the United State...

Research paper thumbnail of Soil moisture data assimilation at multiple scales and estimation of representative field scale soil moisture characteristics

Research paper thumbnail of The Madden-Julian Oscillation affects crop yields around the world

Understanding what causes weather-related stresses that lead to crop failures is a critical step ... more Understanding what causes weather-related stresses that lead to crop failures is a critical step towards stabilizing global food production. While there are many sources of weather-related stresses...

Research paper thumbnail of Development of a 10-km resolution global soil profile dataset for crop modeling applications

Environmental Modelling & Software

One major challenge in applying crop simulation models at the regional or global scale is the lac... more One major challenge in applying crop simulation models at the regional or global scale is the lack of available global gridded soil profile data. We developed a 10-km resolution global soil profile dataset, at 2 m depth, compatible with DSSAT using SoilGrids1km. Several soil physical and chemical properties required by DSSAT were directly extracted from SoilGrids1km. Pedo-transfer functions were used to derive soil hydraulic properties. Other soil parameters not available from SoilGrids1km were estimated from HarvestChoice HC27 generic soil profiles. The newly developed soil profile dataset was evaluated in different regions of the globe using independent soil databases from other sources. In general, we found that the derived soil properties matched well with data from other soil data sources. An ex-ante assessment for maize intensification in Tanzania is provided to show the potential regional to global uses of the new gridded soil profile dataset.

Research paper thumbnail of SMAP soil moisture data assimilation impacts on water quality and crop yield predictions in watershed modeling

Research paper thumbnail of Planting Rice at Monsoon Onset Could Mitigate the Impact of Temperature Stress on Rice–Wheat Systems of Bihar, India

Atmosphere

The rice–wheat rotation is the dominant cropping system in Bihar, where food security of the rura... more The rice–wheat rotation is the dominant cropping system in Bihar, where food security of the rural population depends heavily on the production of rice and wheat. In Bihar, farmers plant rice after the first significant rains, and climatic shocks induced by low temperatures and terminal heat stress at the end of the corresponding season can significantly affect rice and wheat yields. The present work evaluates the benefit of using an earlier date for planting rice, following the monsoon onset, in reducing thermal stress on rice–wheat systems. High-resolution gridded crop simulations using the APSIM model were performed to simulate potential yields using the monsoon onset and the farmers’ practice as planting dates. The monsoon onset was calculated using an agronomic definition, and farmers’ practice dates were estimated using satellite data. The results were analyzed in terms of planting dates, yields, and the incidence of temperature stress on rice and wheat by means of the APSIM y...

Research paper thumbnail of Evaluating Agronomic Onset Definitions in Senegal through Crop Simulation Modeling

Atmosphere

Rainfed agriculture in Senegal is heavily affected by weather-related risks, particularly timing ... more Rainfed agriculture in Senegal is heavily affected by weather-related risks, particularly timing of start/end of the rainy season. For climate services in agriculture, the National Meteorological Agency (ANACIM) of Senegal has defined an onset of rainy season based on the rainfall. In the field, however, farmers do not necessarily follow the ANACIM’s onset definition. To close the gap between the parallel efforts by a climate information producer (i.e., ANACIM) and its actual users in agriculture (e.g., farmers), it is desirable to understand how the currently available onset definitions are linked to the yield of specific crops. In this study, we evaluated multiple onset definitions, including rainfall-based and soil-moisture-based ones, in terms of their utility in sorghum production using the DSSAT–Sorghum model. The results show that rainfall-based definitions are highly variable year to year, and their delayed onset estimation could cause missed opportunities for higher yields ...

Research paper thumbnail of Planting Aman Rice at Monsoon Onset Could Mitigate the Impact of Temperature Stress on Rice-Wheat Systems of Bihar, India

The rice-wheat rotation is the dominant cropping system in Bihar, where food security of the rura... more The rice-wheat rotation is the dominant cropping system in Bihar, where food security of the rural population depends heavily on the production of rice and wheat. In Bihar, climatic shocks induced by low temperatures and terminal heat stress can significantly affect rice and wheat yields. The present work evaluates the benefit of using the monsoon onset as the date for planting rice in reducing thermal stress on rice-wheat systems. High-resolution gridded crop simulations using the APSIM model were performed to simulate potential yields of rice and wheat using the monsoon onset and the farmers’ practice as planting dates. The monsoon onset was calculated using an agronomic definition and farmers’ practice dates were estimated using satellite data. Model outputs were analyzed in terms of planting dates, yields, and the incidence of low temperature stress on rice and high temperature stress on wheat by means of the APSIM yields limiting factors. The results show that the rice planting...

Research paper thumbnail of Re-prioritizing climate services for agriculture: Insights from Bangladesh

Research paper thumbnail of Global High-Resolution Soil Profile Database for Crop Modeling Applications

One of the obstacles in applying advanced crop simulation models such as DSSAT at a grid-based pl... more One of the obstacles in applying advanced crop simulation models such as DSSAT at a grid-based platform is the lack of gridded soil input data at various resolutions. Recently, there has been many efforts in scientific communities to develop spatially continuous soil database across the globe. The most representative example is the SoilGrids 1km released by ISRIC in 2014. In addition recent AfSIS project put a lot of efforts to develop more accurate soil database in Africa at high spatial resolution. Taking advantage of those two available high resolution soil databases (SoilGrids 1km and ISRIC-AfSIS at 1km resolution), this project aims to develop a set of DSSAT compatible soil profiles on 5 arc-minute grid (which is HarvestChoice’s standard grid). Six soil properties (bulk density, organic carbon, percentage of clay and silt, soil pH and cation exchange capacity) available from the original SoilGrids 1km or ISRIC-AfSIS were directly used as DSSAT inputs. We applied a pedo-transfer function to derive some soil hydraulic properties (saturated hydraulic conductivity, soil water content at field capacity, wilting point and saturation) which are critical to simulate crop growth. For other required variables, HarvestChoice’s HC27 database are used as a reference. Final outputs are provided in *.SOL file format (DSSAT soil database) for each country at 5-min resolution. In addition, uncertainty maps for organic carbon and soil water content at wilting points at the top 15 cm soil layers were generated to provide brief idea about accuracy of the final products. The generated soil properties were evaluated by visualizing their global maps and by comparing them with IIASA-IFPRI cropland map and AfSIS-GYGA’s available water content maps.Non-PRIFPRI1; HarvestChoice; CRP2EPTD; PIMCGIAR Research Program on Policies, Institutions, and Markets (PIM

Research paper thumbnail of Parameter Estimation of Improved Rice Varieties in the Philippines Using GENCALC, GLUE and NMCGA

Research paper thumbnail of Assessing methods for developing crop forecasting in the Iberian Peninsula

Seasonal climate prediction may allow predicting crop yield to reduce the vulnerability of agricu... more Seasonal climate prediction may allow predicting crop yield to reduce the vulnerability of agricultural production to climate variability and its extremes. It has been already demonstrated that seasonal climate predictions at European (or Iberian) scale from ensembles of global coupled climate models have some skill (Palmer et al., 2004).

Research paper thumbnail of Toward Better Understanding of the Impacts of Climate Variability on Agricultural Decision-Making and Longer-Term Adaptation II Posters

Research paper thumbnail of On the utility of agronomic monsoon onset definitions for rainfed Aman rice in Bangladesh

The monsoon-season ‘aman' rice crop contributes approximately 40% of total rice production in... more The monsoon-season ‘aman' rice crop contributes approximately 40% of total rice production in Bangladesh, where per-capita rice consumption rates are among the highest in the world. Aman rice is primarily rainfed and relies largely on monsoon rainfall, more specifically monsoon onset and withdrawal. Aman rice farmers’ perception on the monsoon onset for the preparation of seedling does not necessarily coincide with typical meteorological onset definitions and varies with different locations. Therefore, agronomic definitions of monsoon onset, rather than meteorological definitions are needed in order to produce climate forecast information that can better support smallholder farmers’ decision making, and the definitions should be tailored for different regions. In this study, we analyzed historical daily rainfall from three regional weather stations across a north-south gradient in Bangladesh where rainfed transplanted rice is the dominant summer crop. We defined threshold number...

Research paper thumbnail of Interoperable field sensor network andmulti-layered web services for agricultural applications

Research paper thumbnail of Utility of Seasonal Climate Forecasts for Agricultural Decision Supports in Ethiopia

Research paper thumbnail of Downscaling Probabilistic Seasonal Rainfall and Temperature Forecasts for Climate Risk Management in Agriculture

Research paper thumbnail of MJO teleconnections to agro-climate extremes and crop yields

Research paper thumbnail of Linking seasonal climate forecasts with crop models in Iberian Peninsula

Translating seasonal climate forecasts into agricultural production forecasts could help to estab... more Translating seasonal climate forecasts into agricultural production forecasts could help to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse conditions. In this study, we use seasonal rainfall forecasts and crop models to improve predictability of wheat yield in the Iberian Peninsula (IP). Additionally, we estimate economic margins and production risks associated with extreme scenarios of seasonal rainfall forecast.

Research paper thumbnail of Point-scale Estimation of Soil Moisture Profile through Data Assimilation with Root Zone Water Quality Model

ABSTRACT Recent developments in remote-sensing technologies have accelerated research in data ass... more ABSTRACT Recent developments in remote-sensing technologies have accelerated research in data assimilation techniques that use near-surface soil moisture observations or brightness temperature to estimate soil moisture profile. However, much of this research has been conducted at large scales to improve climate forecasts based on synthetic experiments. In this study, field measured surface soil moisture was assimilated into the one-dimensional point-scale Root Zone Water Quality Model by using two data assimilation techniques: Ensemble Kalman Filter (EnKF), and direct insertion method. Measured soil moisture data at four different depths (5cm, 20cm, 40cm and 60cm) from two subwatersheds in northeastern Indiana were used for assimilation and validation purposes. First, surface measured data from the top 5cm layer was assimilated on daily basis to estimate soil moisture in 20cm, 40cm and 60cm layers. Second, the soil moisture in the top soil layer (~5cm) was updated bi-daily (every two days) to investigate the improvement in soil moisture in the top layer through data assimilation. Daily data assimilation shows that EnKF provides better estimates of soil moisture in 20 cm layer compared to direct insertion method and model results without assimilation. Soil moisture estimates for deeper layers (40cm and 60cm) did not show significant improvement from assimilating surface soil moisture. Bi-daily assimilation shows that EnKF produced better results for 5cm and 20cm layers compared to direct insertion method. Overall, the results of this study indicate that daily (or bi-daily) assimilation of surface soil moisture improves soil moisture estimation in the upper more dynamic layers (5 and 20cm) but has little affect on deeper layers (40 and 60cm).

Research paper thumbnail of The Regional Hydrologic Extremes Assessment System: A software framework for hydrologic modeling and data assimilation

PloS one, 2017

The Regional Hydrologic Extremes Assessment System (RHEAS) is a prototype software framework for ... more The Regional Hydrologic Extremes Assessment System (RHEAS) is a prototype software framework for hydrologic modeling and data assimilation that automates the deployment of water resources nowcasting and forecasting applications. A spatially-enabled database is a key component of the software that can ingest a suite of satellite and model datasets while facilitating the interfacing with Geographic Information System (GIS) applications. The datasets ingested are obtained from numerous space-borne sensors and represent multiple components of the water cycle. The object-oriented design of the software allows for modularity and extensibility, showcased here with the coupling of the core hydrologic model with a crop growth model. RHEAS can exploit multi-threading to scale with increasing number of processors, while the database allows delivery of data products and associated uncertainty through a variety of GIS platforms. A set of three example implementations of RHEAS in the United State...

Research paper thumbnail of Soil moisture data assimilation at multiple scales and estimation of representative field scale soil moisture characteristics

Research paper thumbnail of The Madden-Julian Oscillation affects crop yields around the world

Understanding what causes weather-related stresses that lead to crop failures is a critical step ... more Understanding what causes weather-related stresses that lead to crop failures is a critical step towards stabilizing global food production. While there are many sources of weather-related stresses...

Research paper thumbnail of Development of a 10-km resolution global soil profile dataset for crop modeling applications

Environmental Modelling & Software

One major challenge in applying crop simulation models at the regional or global scale is the lac... more One major challenge in applying crop simulation models at the regional or global scale is the lack of available global gridded soil profile data. We developed a 10-km resolution global soil profile dataset, at 2 m depth, compatible with DSSAT using SoilGrids1km. Several soil physical and chemical properties required by DSSAT were directly extracted from SoilGrids1km. Pedo-transfer functions were used to derive soil hydraulic properties. Other soil parameters not available from SoilGrids1km were estimated from HarvestChoice HC27 generic soil profiles. The newly developed soil profile dataset was evaluated in different regions of the globe using independent soil databases from other sources. In general, we found that the derived soil properties matched well with data from other soil data sources. An ex-ante assessment for maize intensification in Tanzania is provided to show the potential regional to global uses of the new gridded soil profile dataset.