| Title: | Crop location specific agricultural drought quantification: Part I. Method development |
| Authors: | McDaniel, R.L., C. Munster and J. T. Cothren |
| Year: | 2017 |
| Journal: | Transactions of the ASABE |
| Volume (Issue): | 60(3) |
| Pages: | 721-728 |
| Article ID: | |
| DOI: | 10.13031/trans.11649 |
| URL (non-DOI journals): | |
| Model: | SWAT |
| Broad Application Category: | conceptual approach |
| Primary Application Category: | drought assessment |
| Secondary Application Category: | groundwater and/or soil water impacts |
| Watershed Description: | none |
| Calibration Summary: | |
| Validation Summary: | |
| General Comments: | |
| Abstract: | The prevailing definition of drought is low moisture conditions over a period of time; however, no single definition
exists for drought. The numerous drought definitions and classifications have led to many indices that attempt to
quantify drought. Most of these indices rely on a single variable, such as precipitation or soil moisture, and do not consider
crop-specific information such as threshold values, which cause crop stress when exceeded. An example of a crop threshold
is the soil moisture value below which the crop experiences stress. The goal of this study was to provide a new methodology
to quantify drought for a specific crop at a specific location, allowing water management decisions on a crop-specific basis.
This was achieved by scaling and combining five factors: precipitation, temperature, biomass production, soil moisture,
and transpiration. The scaled temperature and soil moisture are calculated using crop-specific stress thresholds, whereas
the scaled precipitation is calculated by using location-specific normal values. Transpiration stress is a crop and location
specific value that is calculated by comparing the actual transpiration to the daily maximum transpiration. The biomass
production is also a crop and location specific value that uses the normal values for linear scaling. The variables are
combined with multiple linear regression models that estimate crop yields. A single model is created for each week of the
growing season using the variable or variables that are significant for that week. The predicted yield deciles indicate the
yield trend based on crop water stress and are therefore used as the crop-specific drought index. |
| Language: | English |
| Keywords: | Crop modeling, Drought, Drought index, Hydrologic modeling, SWAT, Water conservation, Water management, Water stress. |