Open AccessRisk Assessment of Cold Damage to Maize Based on GIS and a Statistical Model
Author(s) -
Zhewen Zhao,
Jingfeng Huang,
Zhuokun Pan,
Yuanyuan Chen
Publication year - 2015
Publication title -
the open biotechnology journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.308
H-Index - 11
ISSN - 1874-0707
DOI - 10.2174/1874070701509010236
Subject(s) - risk assessment , agriculture , geography , yield (engineering) , sowing , environmental science , china , index (typography) , climate change , physical geography , geographic information system , environmental protection , ecology , agronomy , cartography , biology , materials science , computer security , archaeology , world wide web , computer science , metallurgy
Cold damage to maize is the primary meteorological disaster in northwest China. In order to establish acomprehensive risk assessment model for cold damage to maize, in this study, risk models and indices were developedfrom average daily temperature and maize yield and acreage data in 1991-2012. Three northwest provinces were used tocalculate the temperature sum during the growth period, temperature departure over the years and relative meteorologicalyield in order to obtain the climate risk index, risk sensitivity index and damage assessment index. Using the geographicinformation system (GIS) and cold damage risk indices obtained from the statistical assessment model, the studied areawas divided into four risk regions: low, medium, medium-high and high. Northeast and southwest Gansu were grouped tothe high-risk region; west Shaanxi and north NHAR were grouped into to the low-risk region; all other areas fell intomedium and medium-high risk regions. Our results can help growers avoid cold damage to maize using local climate dataand optimize the structure and layout of maize planting. It is of significance in guiding the agricultural production in thethree northwest provinces in China and also can serve as a reference in modeling risk assessment in other regions.