Publications

AVM Ines’ Citations: Google Scholar


JOURNAL AND PEER-REVIEWED PAPERS:

Ines, A.V.M., Jha, P.K., Han, E. and R. Cruz. 2019. Estimating Robust and Resilient Genetic Coefficients of Improved Rice Cultivars in the Philippines Using GENCALC, GLUE, NMCGA and an Ensembling Approach. Field Crops Research (submitted).

Manzano, V.J.P. Jr. and A.V.M. Ines. 2019. Downscaling Seasonal Climate Forecasts for Agricultural Risks Management in the Philippines. Agricultural and Forest Meteorology (in revision).

Han, E., Ines, A.V.M. and J. Koo. 2019. Development of a 10-km Resolution Global Soil Profile Dataset for Crop Modeling Applications. Environmental Modelling and Software. 119: 70-83.

Han, E., Baethgen, W.E., Ines, A.V.M., Mer, F., Souza, J.S., Adaime, M.B., Atunez, G. and C. Barreira. 2019. SIMAGRI: An Agro-climate Decision Support Tool. Computers and Electronics in Agriculture. 161: 241-251.

Shin, Y., Mohanty, B.P. and A.V.M. Ines. 2018. Development of Non-Parametric Evolutionary Algorithm for Predicting Soil Moisture Dynamics. Journal of Hydrology. 564: 208-221.

Jha, P.K., Kumar, S.N. and A.V.M. Ines. 2018. Responses of Soybean to Water Stress and Supplemental Irrigation in Upper Indo-Gangetic Plain: Field Experiment and Modeling Approach. Field Crops Research. 219: 76-86.

Han, E. and A.V.M. Ines. 2017. Downscaling Probabilistic Seasonal Climate Forecasts for Decision Support in Agriculture: A Comparison of  Parametric and Non-parametric Approach.  Climate Risk Management. 18: 51-65.

Han, E., Ines, A.V.M. and W. Baethgen. 2017. Climate-Agriculture-Modeling and Decision Tool (CAMDT): A Software Framework for Climate Risk Management in Agriculture. Environmental Modelling and Software. 95: 102-114.

Konstantinos, A.M., Das, N.N., Stampoulis, D., Ines, A.V.M., Fisher, J.B., Granger, S., Kawata, K., Han, E. and A. Behrangi. 2017. The Regional Hydrologic Extremes Assessment System: A Software Framework for Hydrologic Modeling and Data Assimilation. PLoS ONE. 12(5): e0176506.

Chinnachodteeranun, R., Hung, N. D., Honda, K., Ines, A.V.M., and E. Han. 2016. Designing and implementing weather generators as web services. Future Internet. 8(4), 55; doi: 10.3390/fi8040055.

Capa, M.I., Ines, A.V.M., Baethgen, W.E., Rodríguez-Fonseca, B., Han, E. and M. Ruiz-Ramos. 2016. Crop yield outlooks in the Iberian Peninsula: Connecting seasonal climate forecasts with crop simulation models. Agricultural Systems. 149:75-87.

Stampoulis, D. , Andreadis, K.M., Granger, S.L., Fisher, J.B., Turk, F.J., Behrangi, A., Ines, A.V.M., and N.N. Das. 2016. Assessing hydro-ecological vulnerability using microwave radiometric measurements from WindSat. Remote Sensing of Environment. 184: 58–72.

Manzano, V.J.P. Jr. and A.V.M. Ines. 2015. Predictability of May to August (MJJA) Seasonal Rainfall in Northern Philippines. Journal of Nature Studies. 14 (2): 32-39.

Mishra, A., Ines, A.V.M., Das, N.N., Khedun, C.P., Singh, V.P., Sivakumar, B. and J.W. Hansen. 2015. Anatomy of a local-scale drought: Application of assimilated remote sensing products, crop model, and statistical methods to an agricultural drought study. Journal of Hydrology. 526: 15-29. DOI: 10.1016/j.jhydrol.2014.10.038.

Greene, A.M., Goddard, L. Gonzalez, P.L. Ines, A.V.M. and J. Chryssanthacopoulos. 2015. A climate generator for agricultural planning in southeastern South America. Agricultural and Forest Meteorology. 203: 217–228. doi: 10.1016/j.agrformet.2015.01.008

Honda, K., A.V.M. Ines, A. Yui, A. Witayangkurn, R. Chinnachodteeranun and K. Teeravech. 2014. Agriculture information service built on geospatial data infrastructure and crop modeling. International Workshop on Web Intelligence and Smart Sensing, IWWISS ’14, Sep 01-02 2014, Saint Etienne, France. ACM 978-1-4503-2747-3/14/09. (peer-reviewed).

Honda Kiyoshi, Akihiro Yui, Amor V.M. Ines, Rassarin Chinnachodteeranun, Apichon Witayangkurn, Yuka Matsubara, Hirotomo Nagai and Jun Miyamoto. 2014. FieldTouch: An Innovative Agriculture Decision Support Service Based on Multi-scale Sensor Platform. 2014 Annual SRII Global Conference. SRII pp. 228-229, doi:10.1109/SRII.2014.39 (peer-reviewed)

Garcia, K., Lasco, R.D., Ines, A.V.M., Lyon, B. and F. Pulhin. 2013. Predicting geographic distribution and habitat suitability due to climate change of selected threatened forest tree species in the Philippines. Applied Geography. 44: 12-22 doi: 10.1016/j.apgeog.2013.07.005. 

Ines, A.V.M., Das, N.N., Hansen, J.W. and E.G. Njoku. 2013. Assimilation of remotely sensed soil moisture and vegetation with a crop simulation model for maize yield prediction. Remote Sensing of Environment. 138: 149–164. doi: 10.1016/j.rse.2013.07.018. (Top 4 Most Downloaded Article)

Shin, Y., Mohanty, B.P. and A.V.M. Ines. 2013. Estimating effective soil hydraulic properties using spatially distributed soil moisture and evapotranspiration products at multiple scales. Vadose Zone Journal. 12: 1-16. doi: 10.2136/vzj2012.0094.

Ines, A.V.M., Mohanty, B.P. and Y. Shin. 2013. An unmixing algorithm for remotely sensed soil moisture. Water Resources Research. 49: 408-425, doi:10.1029/2012WR012379.

Koide, N., Robertson, A.W., Ines, A.V.M., Qian, J., DeWitt, D. and A. Lucero. 2013. Predictability of rice production in the Philippines with seasonal climate forecasts. Journal of Applied Meteorology and Climatology. 52: 552-569. doi:10.1175/JAMC-D-11-0254.1

Mishra, A.K., Ines, A.V.M., Singh, V.P. and J.W. Hansen. 2013. Extraction of information contents from downscaled precipitation variables for crop simulations. Stochastic Environmental Research and Risk Assessment. 27: 449-457. doi: 10.1007/s00477-012-0667-9.

Shin, Y., Mohanty, B.P. and A.V.M. Ines. 2012. Soil hydraulic properties in layered soil profile using layer-specific soil moisture assimilation scheme. Water Resources Research. 48, W06529, doi:10.1029/2010WR009581.

Charoenhirunyingyos, S., Honda, K., Kamthonkiat, D. and A.V.M. Ines. 2011. Soil hydraulic parameters estimated by satellite information through data assimilation. International Journal of Remote Sensing. 32 (23): 8033-8051.

Ines, A.V.M., Hansen, J.W. and A.W. Robertson. 2011. Enhancing the utility of daily GCM rainfall for crop yield prediction. International Journal of Climatology. 31 (14): 2168-2182.

Joshi, C., Mohanty, B. P., Jacobs, J. and A.V.M. Ines. 2011. Spatio-temporal analysis of soil moisture at different hydro-climatic regions. Water Resources Research. 47, W01508, doi:10.1029/2009WR009002.

Charoenhirunyingyos, S., Honda, K., Kamthonkiat, D. and A.V.M. Ines. 2011. Soil moisture estimation from inverse modeling using multiple criteria functions. Computers and Electronics in Agriculture. 75(2): 278-287.

Sahoo, D., Smith, P. H. and A.V.M. Ines. 2010. Autocalibration of HSPF for simulation of streamflow using genetic algorithm. Transactions of the American Society of Agricultural and Biological Engineers 53: 75-86.

Ines, A.V.M. and B.P. Mohanty. 2009. Near-surface soil moisture assimilation for quantifying effective soil hydraulic properties using genetic algorithm. II. with air-borne remote sensing during SGP97 and SMEX02. Water Resources Research. doi:10.1029/2008WR007022.

Ines, A.V.M. and B.P. Mohanty. 2008. Near-surface soil moisture assimilation to quantify effective soil hydraulic properties under different hydro-climatic conditions. Vadose Zone Journal. 7:39-52. doi:10.2136/vzj2007.0048.

Ines, A.V.M. and B. P. Mohanty. 2008. Parameter conditioning with a noisy Monte Carlo genetic algorithm to estimate effective soil hydraulic properties from space. Water Resources Research. Vol. 44, W08441, doi:10.1029/2007WR006125.

Ines, A.V.M. and B.P. Mohanty. 2008. Near-surface soil moisture assimilation to quantify effective soil hydraulic properties using genetic algorithm. I. Conceptual modeling. Water Resources Research. Vol. 44, W06422, doi:10.1029/2007WR005990.

Robertson, A.W., Ines, A.V.M. and J.W. Hansen. 2007. Downscaling of seasonal precipitation for crop simulation. Journal of Applied Meteorology and Climatology. 46: 677-693.

Ines, A.V.M., Honda, K., Gupta, A.D., Droogers, P. and R.S. Clemente. 2006. Combining remote sensing-simulation modeling and genetic algorithm optimization to explore water management options in irrigated agriculture. Agricultural Water Management. 83: 221-232.

Ines, A.V.M. and J.W. Hansen. 2006. Bias correction of daily GCM rainfall for crop simulation studies. Agricultural and Forest Meteorology. 138: 44-53. (Highly Cited Paper)

Hansen, J.W., Challinor, A., Ines, A.V.M., Wheeler, T. and V. Moron. 2006. Translating climate forecasts into agricultural terms: Advances and challenges. Climate Research. 33(1): 27-41.

Ines, A.V.M. and K. Honda. 2005. On quantifying agricultural and water management practices from low spatial resolution RS data using genetic algorithms: a numerical study for mixed pixel environment. Advances in Water Resources. 28: 856-870.

Hansen, J.W. and A.V.M. Ines. 2005. Stochastic disaggregation of monthly rainfall data for crop simulation studies. Agricultural and Forest Meteorology. 131: 233-246.

Chemin, Y., Honda, K. and A.V.M. Ines. 2005. Genetic algorithm for assimilating remotely sensed evapotranspiration data using a soil-water-atmosphere-plant model – implementation issues. Technical letter. International Journal of Geoinformatics. 1(1):87-90.

Ines, A.V.M. and P. Droogers. 2002. Inverse modelling in estimating soil hydraulic functions: a genetic algorithm approach. Hydrology and Earth System Sciences. 6 (1): 49-65.

Ines, A.V.M. and P. Droogers. 2002. Inverse modeling to quantify irrigation system characteristics and operational management. Irrigation and Drainage Systems. 16 (3): 233-252.

Ines, A.V.M., Gupta, A. D. and R. Loof. 2002. Application of GIS and crop growth models in estimating water productivity. Agricultural Water Management. 54 (3): 205-225.


BOOKS AND TECHNICAL REPORTS:

Rola, A,C., de los Santos, E.B., Ines, A.V.M. and D.D. Elazegui. 2017. Adapting to Climate Change: Lessons from Bicol, Philippines. In Rola et al., (2017). Building Resilience in Farming Communities: Science, Technology and Governance Innovations in Bicol, Philippines. UPLBFI, College, Laguna; DA RFO-5, Pili, Camarines Sur; and DOST-PAGASA, Diliman Quezon City, Phil. 1: 1-13.

Han, E., Ines, A.V.M., Kim, K-H. and R. Cousin. 2017. Decision Support Tools for Climate Risk Management in Agriculture. In Rola et al., (2017). Building Resilience in Farming Communities: Science, Technology and Governance Innovations in Bicol, Philippines. UPLBFI, College, Laguna; DA RFO-5, Pili, Camarines Sur; and DOST-PAGASA, Diliman Quezon City, Phil. 3: 33-45.

Mohanty, B.P.M., Ines, A.V.M., Shin, Y., Gaur, N., Das, N. and R. Jana. 2017. A framework for assessing soil moisture deficit and crop water stress at multiple space and time scales under climate change scenarios using model platform, satellite remote sensing and decision support. Chapter 9: pp 173-196. V. Lakshmi (ed.), Remote Sensing of Hydrological Extremes, Springer Remote Sensing/Photogrammetry, DOI 10.1007/978-3-319-43744-6_9

Han, E., Ines, A.V.M. and J. Koo. 2015. Global High-Resolution Soil Profile Database for Crop Modeling Applications. Working Paper. HarvestChoice/International Food Policy Research Institute (IFPRI). Washington, D.C., USA.

Wilco Terink, Peter Droogers, Jos van Dam, Gijs Simons, Maurits Voogt and Amor V.M. Ines. 2013. Satellite based data mining to support Egypt’s agriculture. Working Paper. FutureWater, The Netherlands.

Hoefsloot, P., Ines, A.V.M., van Dam, J., Duveiller, G., Kayitakire, F. and J. Hansen. 2012. Combining crop models and remote sensing for yield prediction: Concepts, applications and challenges for heterogeneous, smallholder environments. JRC Scientific and Policy Reports. doi:10.2788/72447.

Ines, A.V.M. 2010. Remote Sensing – Simulation Modeling for Agriculture and Water Management. Lulu Press Inc., Raleigh, NC. 225p.

Hansen, J.W., Tippett, M.K., Bell, M.A. and A.V.M. Ines. 2010. Linking seasonal forecasts into RiskView to enhance food security contingency planning. IRI Technical Report #10-13. IRI, Columbia University, NY.

Ines, A.V.M., Droogers, P., Makin, I.W. and A. D. Gupta. 2001. Crop growth and soil water balance modeling to explore water management options. IWMI Working Paper 22. Colombo, Sri Lanka: International Water Management Institute. 26 p.