**3.4. Soil moisture comparison**

**3.2. Instruments**

62 Soil Moisture

provided by the company.

A monitoring station was installed in the north of the Calakmul Biosphere Reserve in the town Modesto Angel (MA) and at the South close to Ley de Fomento town was an Automatic Weather Station [36]. Soil moisture was measured using the direct gravimetric method and also continuously using indirect methods based on reflectometry: time domain (TDR) and frequency domain (FDR). Additionally, other measured variables at this station were physical

TDR sensors used in this study are CS616 (CS) from Campbell placed at 2.5, 5, 10, 20 and 30 cm with a latency of every 20 min. The calibration of the CS616 sensors was done according to the manufacturer (ref). In particular, these sensors use linear or quadratic equations to estimate the volumetric water content, depending on the expected range of water content and accuracy requirements. The accuracy reported for these probes is ±2.5 volumetric water content. Measurements of CS sensors are stored in a Campbell CR800 datalogger, which records the data and can then be accessed via peripheral communications using a software interface

FDR sensors tested were Decagon EC-5 and Diviner 2000. Decagon EC-5 (DEC) sensors measure the dielectric constant operates at 70 MHz minimising salinity and texture effects. An advantage is that they provide an accurate sensor reading in almost any soil. Factory calibrations are provided for mineral soils, potting soil and others. The design and measurement frequency allows measurement of volumetric water content (VWC) [37]. The EC-5 sensors were connected by a 3.5-mm stereo jack plug to the Generation I THHINK datalogger collecting data every 20 min [38]. Diviner 2000 [39] is a multi-sensor capacitance probe used to determine soil water content by measuring the frequency change induced by the changing permittivity of the soil permeated by the fringing fields of the capacitor sensor. The probe consists of multiple sensors located at various depths installed in specific access tubes. A high-frequency electric field is created around each sensor (sphere of influence). The sphere of influence is every 10 cm, thus readings are taken in 10 cm depth intervals in the access tube; this allows the sphere of influence for each reading to sample a separate soil horizon. Volumetric soils water measurements are done in real time and the readings are converted to soil moisture using a calibration equation. This universal calibration equation is independent of soil temperature but could be affected by salinity. One advantage is that the access tube is installed with minimum disruption to the soil profile. The accuracy level is better than 99% of the volumetric soil water content (θv) that is taken instantaneously with excellent repeatability. An access tube was allocated at each of the nine test sites into the soil to different depths until 150 cm, and in some cases just above the water table. Readings were registered every 3 days the first weeks and then every 15 days. Results were used applying the calibration equation in order to have volumetric water

content and to compare with the gravimetric, TDR, and FDR (Decagon) methods.

Field campaigns were performed in September 2012, February and August 2013, May and September-October 2014 and June 2015. Dates correspond to the rainy and dry periods, to

**3.3. Soil moisture measurement procedure**

characteristics of the soil, rainfall, air temperature, and relative humidity.

In order to estimate the accuracy between the three soil moisture methods, a comparison analysis was performed. Statistical indicators such as the coefficient of determination (R<sup>2</sup> ), the root mean square error (RMSE), relative error, mean bias error (MBE) and normalised root mean square error (NRMSE) were applied [40].

$$\begin{aligned} \text{Then} \\ \text{RMSE} &= \sqrt{\frac{1}{n} \sum\_{i=1}^{n} (D\_i - \text{Obs}\_i)^2} \\\\ \text{RMSE} &= \sqrt{\frac{1}{n} \sum\_{i=1}^{n} (D\_i - \text{Obs}\_i)^2} \end{aligned} \tag{4}$$

where subscripts *Di* is the output of the devices (FDR and TDR readings) and *Obsi* is the observed gravimetric soil moisture. *RMSE* minimum value is zero under the hypothetical situation that the model is capable of perfect (long-term) readings of the system, and there are no data errors being small values desirable. Mean bias error (MBE) measures the average magnitude of the errors in a set of readings. It is the average over the test sample of the absolute differences between prediction and actual observations having the differences an equal weight. According to [41] an acceptable value for volumetric soil moisture is 0.04 m<sup>3</sup> m−<sup>3</sup> .

is severe and drought is taking place. According to [30], the rainy season occurs during the middle of summer until autumn, although it was observed in **Figure 2** that occurs from July to February. During the winter, the tropical storms have influence on the generation of precipi-

Correlation between TDR and FDR Soil Moisture Measurements at Different Scales to Establish…

**Figure 2** shows the rainfall distribution in the study area. Although the north area seems more affected by the winter rainfall, there is more rain in the south part of the CBR. Besides, in the dry season from April to July, there was some rainfall at the north area. This variability favoured the presence of humidity maintaining the diversity of vegetation species in both

The characterisation of the soil is based on the measurement of its texture on the surface and some physical parameters such as electric conductivity, pH, soil moisture, % of saturation, field capacity (CC) and permanent wilt point (PWP) (see **Table 1**). CC is the largest amount of water that this type of soil will retain under conditions of complete humidity *CC* = (%clay) ∗ *a* + (%sil) ∗ *b* + (%sand) ∗ *c*, and the PWP is the minimum water content where the plants usually die;

region and type of floor, and in this case, the coefficients used are *a* = 0.555, *b* = 0.187 and

Modesto Ángel where the three techniques were implemented has a more constant type of soil: the first 5 cm is a sandy soil, from 10 to 80 cm is Frank and more than 90 cm is loamy clay.

> **% Humidity**

Refugio 12.00 58.56 29.44 Clayish 37.04 104.0 78.0 41.0 6.42 0.251

Ley Fomento 26.20 42.16 31.64 Clay 38.34 107.0 80.3 42.1 6.57 0.551 La Ceiba 31.84 27.80 40.36 Frank 39.13 120.0 90.0 47.3 7.93 1.101

31.84 31.80 36.36 Frank 30.77 102.2 76.7 40.2 7.23 0.361

**% Saturation**

1.84, the coefficients a, b and c are determined for each

37.04 60.0 45.0 23.6 7.38 0.291

35.71 65.8 49.4 25.9 6.80 0.797

37.93 125.0 93.8 49.2 6.84 0.564

32.38 120.2 90.2 47.3 5.43 0.024

**CC PWP pH Electric** 

http://dx.doi.org/10.5772/intechopen.81477

65

**conductivity**

tations and also they cause a decrease of the temperature until reaching 10°C [30].

areas. The archaeological zone is considered at the south.

In all the other sites, soil type varies as the depth increases.

**soil**

loam

loam

sandy

sandy

**4.2. Soil characteristics**

*c* = 0.027 [42].

Modesto Ángel

for each of the sampling soils *PWP* <sup>=</sup> \_\_\_\_ *CC*

**Site Sand Clay Silt Type of** 

Flores Magón 53.28 15.08 31.64 Sandy

Ramonal 74.40 7.24 18.36 Sandy

Bonfil 30.76 31.24 38.00 loamy

Helipuerto 32.20 25.80 42.00 loamy

**Table 1.** Soil characteristics measured at 10 cm depth in the sites.
