### What are the methods of estimating missing rainfall data?

## What are the methods of estimating missing rainfall data?

The following methods are most commonly used for estimating the missing records.

- Simple Arithmetic Method.
- Normal Ratio Method.
- Modified normal ratio method.
- Inverse distance method.
- Linear programming method.

### How is inverse distance weighted calculated?

Inverse distance weighting (IDW) is a type of deterministic method for multivariate interpolation with a known scattered set of points. The assigned values to unknown points are calculated with a weighted average of the values available at the known points.

#### Which interpolation method is best for rainfall data?

Results indicated that the multiquadric, kriging, and optimal interpolation schemes were the best three methods for interpolation of monthly rainfall within the study area. The optimal and kriging methods have the advantage of providing the error of interpolation.

**What are the causes of missing rainfall data?**

Missing data is a common problem faced by researchers in environmental studies. Environmental data, particularly, rainfall data are highly vulnerable to be missed, which is due to several reasons, such as malfunction instrument, incorrect measurements, and relocation of stations.

**How do you calculate rainfall intensity of rainfall data?**

Rainfall intensities can be accurately measured by means of a continuously recording autographic rain gauge. It is also possible to time the length of individual rainstorms and to calculate the average intensities by dividing the measured rainfall depths by the corresponding duration of the storms.

## What is inverse distance weighting used for?

Inverse Distance Weighted (IDW) is a method of interpolation that estimates cell values by averaging the values of sample data points in the neighborhood of each processing cell. The closer a point is to the center of the cell being estimated, the more influence, or weight, it has in the averaging process.

### What does the term inverse distance weighting imply?

As mentioned above, weights are proportional to the inverse of the distance (between the data point and the prediction location) raised to the power value p. As a result, as the distance increases, the weights decrease rapidly.

#### How do you interpolate rainfall data?

Four common interpolation techniques (ANUDEM, Spline, IDW, and Kriging) were compared and assessed against station rainfall data and modeled rainfall. The performance was assessed by the mean absolute error (MAE), mean relative error (MRE), root mean squared error (RMSE), and the spatial and temporal distributions.

**How do you determine the consistency of rainfall data?**

The consistency of a rainfall record is tested with double-mass analysis. This method compares the cumulative annual (or alternatively, seasonal) values of station X with those of a reference station. The reference station is usually the mean of several neighboring stations.

**How can I estimate the missing Rainfall data?**

Thus, it is often necessary to estimate the missing record using data from the neighboring station. The following methods are most commonly used for estimating the missing records. For m stations, 1, 2, 3, …,m, the annual precipitation values are P1, P2, P3, …, Pm, respectively.

## How is inverse distance weightage used in ArcGIS?

Secondary data on rainfall and temperature was collected from 10 Indian Meteorology Department (IMD) weather stations and 103 blocks (Tehsil) rain gauge.Inverse Distance Weightage (IDW) method was used in ArcGIS to estimate daily weather condition (quantitative) of all the surveyed villages by spatial extrapolation of weather data.

### How to calculate daily temperature and rainfall using inverse distance?

Estimation of Daily Temperature & Rainfall Using Inverse Distance Weightage (IDW) Method & Inter-Relationship with Water Quality & Adaptive Behaviors[Full-Text ] International Journal of Scientific & Engineering Research, Volume 4, Issue 12, December-2013 ISSN 2229-5518

#### Is the inverse distance method satisfactory for hilly regions?

As in inverse distance method the weighting is strictly based on distance, hence this method is not satisfactory for hilly regions. Example 7.2 Data for the base station and 5 surrounding stations are tabulated below. Find missing data at ‘A’ using (i) modified normal ratio method and (ii) inverse distance method.

What are the methods of estimating missing rainfall data? The following methods are most commonly used for estimating the missing records. Simple Arithmetic Method. Normal Ratio Method. Modified normal ratio method. Inverse distance method. Linear programming method. How is inverse distance weighted calculated? Inverse distance weighting (IDW) is a type of deterministic method for multivariate…