DMAP
Drought Monitor And Prediction

DMAP tool (Drought Monitor And Prediction) is used in:

1. Estimation of meteorological drought indices based on AgMERRA precipitation data and station-observed precipitation data
2. Predictive value of Keetch-Byram Drought Index for cereal yields in a semi-arid environment
3. Rainfed wheat (Triticum aestivum L.) yield prediction using economical, meteorological, and drought indicators through pooled panel data and statistical downscaling
4. Prediction of meteorological drought in arid and semi-arid regions using PDSI and SDSM: a case study in Fars Province, Iran

What is DMAP (Drought Monitor And Prediction) software?

Among natural hazards, drought is known to cause extensive damage and affects a significant number of people (Wilhite 1993). To reduce the damage from drought, it is crucial to monitor this event. Drought indices are quantitative measures that characterize drought levels by assimilating data from one or several variables such as precipitation and evapotranspiration into a single numerical value (Zargar et al. 2011). A reliable index must be able to quantify drought severity, detect drought beginning and end times for early warning systems, monitor and prospective water resources planning.

Since calculating different indices are sometimes sophisticated and time consuming, so researchers need a comprehensive software. As we know, there are three main drought types, namely meteorological, agricultural, and hydrological droughts. The DMAP (Drought Monitor And Prediction) software can calculate different drought indices in three different types of drought that are listed in following:

1- Meteorological drought

A: Rain Based-drought indices (Salehnia et al., 2017):

• SPI (Standardized Precipitation Index, McKee et al. 1993, 1995
• DI (Deciles Index), Gibbs and Maher, 1967
• PN (Percent of Normal Index), Willeke et al. (1994)
• CZI (China-Z Index), Wu et al. (2001)
• MCZI (Modified CZI), Wu et al. (2001)
• EDI (Effective drought Index), Byun and Wilhite (1999)
• RAI (Rainfall Anomaly Index), van Rooy (1965)
• ZSI (Z-score Index), Palmer (1965)

B: Other meteorological drought indices:

• PDSI (Palmer Drought Severity Index), Palmer (1965) and Dehghan et al., 2020
• PHDI (Palmer Hydrological Drought Index), Palmer (1965)
• SPEI (Standardized Precipitation Evapotranspiration Index), Vicente-Serrano et al., 2010 and Salehnia et al., 2020
• RDI (Reconnaissance Drought Index), Tsakiris and Vangelis, 2005.

2- Agricultural drought indices

• ARI (Agricultural Rainfall Index), Nieuwolt, 1981
• SMDI (Soil Moisture Deficit Index), Narasimhan and Srinivasan, 2005
• ETDI (Evapotranspiration Deficit Index), Narasimhan and Srinivasan, 2005

3- Hydrological drought indices

• SWSI (Surface Water Supply Index), Garen, 1993
• SDI (Streamflow Drought Index), Nalbantis and Tsakiris, 2009

In the monitor phase in DMAP (Drought Monitor And Prediction) software, through selecting every index, the user can calculating it and then by available graphs (line, columnar, and Boxplot), the user can monitor the happened drought event in various time scale in the study area. In the prediction phase, the user by importing the downscaled outputs of GCMs models in DMAP tool, he/she can calculate every index the he wants for future period.

Watch Drought Course Videos: Drought Lesson

Type of input file in DMAP (Drought Monitor And Prediction) tool:

In DMAP the input file can be in different format files, namely csv, xls, xlsx, and also nc (NetCDF). This is a unique characteristic and due to this feature, users can easily import and browse his fie, without any concern. Another benefit of this software is the positioning of data in columns. In this software, the ordering of data in columns is not important, and the software recognizes the location of the data according to the input column header. This feature is not considered in other existing software that compute only a few indexes. So the user is having trouble, in such tools, therefore DMAP solve the problem and the user by selecting the header of each column can easily determine the order of them.

Calculation of each index in DMAP (Drought Monitor And Prediction) software:

In DMAP the equations of each index were extracted from the origin paper that it presents the intent index and all details of it. All the used equations were clarified in these papers. The main papers of each index are listed in the reference section in following.

What is severity of drought in DMAP (Drought Monitor And Prediction)

In DMAP, the user can calculate the severity of drought by using a favorite border. This border is different for any index. For example, in SPI, usually this border is less than -0.99 or you can enter zero whereas in KBDI is more than 200 or 250. DMAP (Drought Monitor And Prediction) will calculate severity for SPI index (less than border) by following these steps.

• calculate S0 = SPI - border
• consider drought events all S0 less than zero
• each drought events will start when S0 is less than zero
• each drought events continue while S0 is less than zero
• the duration of each drought is days between the start and end of each drought events
• the severity of each drought is cumulative values of |S0| between the start and end of each drought events

And DMAP (Drought Monitor And Prediction) will calculate severity in KBDI index (more than border) by following these steps.

• calculate S0 = SPI - border
• consider drought events all S0 more than zero
• each drought events will start when S0 is more than zero
• each drought events continue while S0 is more than zero
• the duration of each drought is days between the start and end of each drought events
• the severity of each drought is cumulative values of S0 between the start and end of each drought events

Tips and points

In the Drought Monitor And Prediction (DMAP) software tool V1.0, the input files can have different format of data, including xls, xlsx, txt, and csv, an in the Drought Monitor And Prediction software tool V1.1 beside the mentioned formats, the NetCDF (nc and nc4) as well supported. Also, there is a tool in the V1.1 which can extract data for a point and an area from a NetCDF file; if you select a region, you should calculate the mean value of the region.

In the DMAP (Drought Monitor And Prediction) V.1.1, there is an option which can convert the unit of data of NetCDF files, for example, consider the models of CMIP5, the precipitation values are in flux so that this tool can convert flux value to mm value.

The timescale of input data can be in daily, monthly and yearly. Be careful; if you enter yearly data to the software, then you can't compute the value of drought index on a monthly scale.

Some of the indices such as KBDI and EDI need to daily data, if you use monthly and yearly data as input to the Drought Monitor And Prediction tool V1.1, so you can't obtain the value of these indices, and the Drought Monitor And Prediction software (DMAP) tool V1.1 can't calculate the amount of them, and the calculation icon would be deactivated.

The Drought Monitor software tool V1.1 can compute 19 drought indices in different types of drought, including meteorological drought, agricultural drought, and hydrological drought. The indices have different types.

You can enter five values as input data into the Drought Monitor software tool V1.1. For calculating of each index, we should consider the original relation and equation of the index which has one or more input data of the five variables. The Drought Monitor software tool V1.1 is an intelligence tool, since when a user wants to evaluate a drought index, then the index which relevant to the input data variables would be active.

In the first tab, the variables are entered to the Drought Monitor software tool V1.1 are as a time series (daily, monthly, and yearly). But by considering the kind of drought index, some of the other inputs maybe need to enter in the second tab (additional section), for example in the PDSI drought index; we need to enter geographical latitude, which during the calculation drought index, the user should enter them as a requested input variable.

Depend on the type of drought index; you can calculate drought index at various time scale, including daily, monthly, yearly, and moving average.

The remarkable point is that if you choose a monthly scale, the "Moving Average" Combo box would be activated, and the moving average of one month is equal to the monthly scale of the selected index.

The value of evapotranspiration can be calculated through three methods, including ThornThwaite, Hamon, and enter the amount of evapotranspiration from input data, which selection of these three methods will be made through the active combo box (that it is selected after the selection of index).

For computing the SPEI, there are two icons, one of them is related to the "SPEI" which represents that the amount of SPEI is calculated by computing evapotranspiration via ThornThwaite and Hamon methods, also the other is "SPEI1 that related to the calculation of SPEI by the amount of the evapotranspiration which enters by the user.

For calculation of PDSI and if you apply the amount of computed evapotranspiration, then you need to fill three items, including Surface Soil water in mm, Available Water Capacity (AWC) in mm, and Latitude in decimal number.

For calculation SPEI and with using the amount of computed evapotranspiration, the user should write the value of Latitude in decimal number.

For calculating the KBDI, we need to write the value of Field Capacity (FC) in mm.

For calculating the RDI, the user can select the check-box of "Standardized," which this icon will present the Standardized RDI.

In the Drought Monitor And Prediction software (DMAP) tool, there is a panel for plotting graphs. There are three various kinds of graphs, namely BoxPlot, Linear, and columnar. Also, you can select every color that you want for your graph. There are two other options with names of H-Line and Grayscale that H-Line adds the horizontal line on the graph and Grayscale creates gray color for your graph.

References:

• Byun H R, Wilhite D A. 1999. Objective quantification of drought severity and duration. Journal of Climate, 12(9): 2747-2756.
• Garen DC, 1993. Revised surface-water supply index for western United States, J. Water Resour. Plann. Manage. 1993.119:437-454.
• Gibbs, W.J., and Maher, J.V. 1967. Rainfall Deciles as Drought Indicators, Bureau of Meteorology bulletin, No. 48. Commonwealth of Australia: Melbourne; 29.
• McKee T B, Doesken N J, Kleist J. 1993. The relationship of drought frequency and duration to time scales. In: Proceedings of the 8th Conference on Applied Climatology. Anaheim, CA: American Meteorological Society, 179-184.
• McKee T B, Doesken N J, Kleist J. 1995. Drought monitoring with Multiple Time scales. In: Proceeding of the 9th Conference on Applied Climatology. Dallas, TX: American Meteorological Society, 233-236.
• Nalbantis, I., and Tsakiris, G. 2009. Assessment of hydrological drought revisited. Water Resour Manage. 23:881-897
• Nieuwolt S, 1981. Agricultural droughts in Peninsular Malaysia. Malaysian Agricultural Research and Development Institute, Serdang, p: 16.
• Narasimhan, B., and Srinivasan, R. 2005. Development and Evaluation of soil Moisture Deficit index and Evaporation Deficit Index for Agriculture of Drought Monitoring, Agricultural and Forest Meteorology, 133-69-88.
• Palmer WC, 1965. Meteorological drought: US Department of Commerce, Weather Bureau Washington, DC, USA. 45, 58.
• Salehnia N, et al., 2017. Estimation of meteorological drought indices based on AgMERRA precipitation data and station-observed precipitation data. J Arid Land (2017) 9(6): 797-809. Drought AgMerra
• Tsakiris G, and Vangelis H, 2005. Establishing a Drought Index incorporating evapotranspiration. European Water. 9/10:3-11
• Van Rooy MP, 1965. A rainfall anomaly index independent of time and space. Notos 14:43-48
• Vicente-Serrano SM, Beguerra S, and Lopez-Moreno JI, 2010. A Multi-Scalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index - SPEI. Journal of Climate 23(7):1696-1718, DOI: 10.1175/2009JCLI2909.1
• Wilhite DA, 1993. The enigma of drought. Drought Assessment, Management, and Planning: Theory and Case Studies. Kluwer Academic Publishers, Boston, Ma. pp. 3-15.
• Willeke G, Hosking J R M, Wallis J R, et al., 1994. The national drought atlas. In: Institute for Water Resources Report 94-NDS-4. U.S Army Corp of Engineers, CD-ROM. Norfolk, VA.
• Wu H, Hayes M J, Weiss A, et al., 2001. An evaluation of the Standardized Precipitation Index, the China-Z Index and the statistical Z-Score. International Journal of Climatology, 21(6): 745-758.
• Zargar A, Sadiq R, Naser B, Khan FI, 2011. A review of drought indices. Environ. Rev. 19: 333-349 (2011). Doi: 10.1139/A11-013

---

The license of this tool is applicable for one year of using and you would renew it for the new year if you need.

DMAP V2.0

---