Measurement of soil properties and surface hydrology parameters to assess the variation induced by different plantations

Author(s):  
Chitra Shukla ◽  
K. N. Tiwari ◽  
Gurjeet Singh
2017 ◽  
Vol 21 (9) ◽  
pp. 4591-4613 ◽  
Author(s):  
Laetitia Gal ◽  
Manuela Grippa ◽  
Pierre Hiernaux ◽  
Léa Pons ◽  
Laurent Kergoat

Abstract. In recent decades, the Sahel has witnessed a paradoxical increase in surface water despite a general precipitation decline. This phenomenon, commonly referred to as the Sahelian paradox, is not completely understood yet. The role of cropland expansion due to the increasing food demand by a growing population has been often put forward to explain this situation for the cultivated Sahel. However, this hypothesis does not hold in pastoral areas where the same phenomenon is observed. Several other processes, such as the degradation of natural vegetation following the major droughts of the 1970s and the 1980s, the development of crusted topsoils, the intensification of the rainfall regime and the development of the drainage network, have been suggested to account for this situation. In this paper, a modeling approach is proposed to explore, quantify and rank different processes that could be at play in pastoral Sahel. The kinematic runoff and erosion model (KINEROS-2) is applied to the Agoufou watershed (245 km2), in the Gourma region in Mali, which underwent a significant increase of surface runoff during the last 60 years. Two periods are simulated, the past case (1960–1975) preceding the Sahelian drought and the present case (2000–2015). Surface hydrology and land cover characteristics for these two periods are derived by the analysis of aerial photographs, available in 1956, and high-resolution remote sensing images in 2011. The major changes identified are (1) a partial crusting of isolated dunes, (2) an increase of drainage network density, (3) a marked decrease in vegetation with the nonrecovery of tiger bush and vegetation growing on shallow sandy soils, and (4) important changes in soil properties with the apparition of impervious soils instead of shallow sandy soil. The KINEROS-2 model was parameterized to simulate these changes in combination or independently. The results obtained by this model display a significant increase in annual discharge between the past and the present case (p value < 0.001), which is consistent with observations, despite a slight overestimation of the past discharge. Mean annual discharges are estimated at 0.51  ×  106 m3 (2.1 mm yr−1) and 3.29  ×  106 m3 (13.4 mm yr−1) for past and present, respectively. Changes in soil properties and vegetation cover (tiger bush thickets and grassland on shallow sandy soil) are found to be the main factors causing this increase of simulated runoff, with the drainage network development contributing to a lesser extent but with a positive feedback. These results shed a new light on the Sahelian paradox phenomenon in the absence of land use change and call for further tests in other areas and/or with other models. The synergetic processes highlighted here could play a role in other Sahelian watersheds where runoff increase has been also observed.


2014 ◽  
Vol 11 (1) ◽  
pp. 15
Author(s):  
Set Foong Ng ◽  
Pei Eng Ch’ng ◽  
Yee Ming Chew ◽  
Kok Shien Ng

Soil properties are very crucial for civil engineers to differentiate one type of soil from another and to predict its mechanical behavior. However, it is not practical to measure soil properties at all the locations at a site. In this paper, an estimator is derived to estimate the unknown values for soil properties from locations where soil samples were not collected. The estimator is obtained by combining the concept of the ‘Inverse Distance Method’ into the technique of ‘Kriging’. The method of Lagrange Multipliers is applied in this paper. It is shown that the estimator derived in this paper is an unbiased estimator. The partiality of the estimator with respect to the true value is zero. Hence, the estimated value will be equal to the true value of the soil property. It is also shown that the variance between the estimator and the soil property is minimised. Hence, the distribution of this unbiased estimator with minimum variance spreads the least from the true value. With this characteristic of minimum variance unbiased estimator, a high accuracy estimation of soil property could be obtained.


2020 ◽  
Vol 16 (2) ◽  
pp. 41-63
Author(s):  
V.L. Zakharov ◽  
◽  
G.N. Pugachev ◽  

2018 ◽  
Vol 32 (5) ◽  
pp. 37
Author(s):  
Rajaram Majhi ◽  
Gouri Sankar Bhunia ◽  
Tapan Kumar Das ◽  
Pravat Kumar Shit ◽  
Rabindranath Chattopadhyay

2020 ◽  
Vol 5 (2) ◽  
pp. 37-42
Author(s):  
Inobat Ruzieva ◽  
◽  
Inobat Ruzieva ◽  
Islom Xaitov ◽  
Ulug`berdi Xursanov

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