Integrated universal soil loss equation (USLE) and Geographical Information System (GIS) for soil erosion estimation in A Sap basin:Central Vietnam

Central Vietnam is very susceptible to soil erosion due to its complicated terrain and heavy rainfall. The objective of this study was to quantify soil erosion in the A Sap river basin, A Luoi district, Thua Thien Hue Province, Vietnam, using the Universal Soil Loss Equation (USLE) and Geographical Informa-tion System (GIS). The results showed that 34% of land area lost accumulated to 10 t ha-1 year-1 while 47% of the total area lost less than 1 t ha-1 year-1. Natural forest land lost the most with an average of about 19 t ha-1 year-1, followed by plantation forest with approximately 7 t ha-1 year-1 and other agricultural lands at 3.70 and 1.45 t ha-1 year-1 for yearly crops and paddy rice, respectively. Soil erosion was most sensitive to the topographic factor (LS), followed by the practice support factor (P), soil erodibility factor (K), cropping management (C), and the rainfall erosivity factor (R). Implications are that changes to the cultivated calendar and implementing intercropping are effective ways to prevent soil erosion in cultivated lands. Furthermore, introducing broad leaves trees for mountainous areas in A Sap basin was the most effective practice in reducing soil erosion. The study also pointed out that the combination of available data sources used with the USLE and GIS technology is a viable option to cal-culate soil erosion in Central Vietnam, which would allow targeted attention toward a solution is to reduce future soil erosion.

Assessment of soil quality indicators under different agricultural land uses and topographic aspects in Central Vietnam

Soil quality assessment is valuable for agricultural production. In this research, 155 soil samples at two soil depths were collected from four land use types in an agricultural area of the A Luoi district in the Central Vietnam. Differences of soil organic carbon, total nitrogen in soil and soil pH under different land use types and topographic aspects were compared. Soil organic carbon contents in arable land and plantation forest are higher than those in natural forest and grassland (p < 0.05). Conversely, the total nitrogen in natural forest was significantly lesser in comparison to other land use types. Meanwhile there were no significant differences of the total nitrogen content (p < 0.05) among arable land, plantation forest, and grassland. The soil of grassland, natural and plantation forests land use types were more significantly acidic than those of the soils of the arable land use type. Soil organic carbon and total nitrogen showed a decreasing trend while soil depth increased in all land use types. The soil pH in plantation forest and arable land use types showed no significant change in relation to soil depth. Significant differences were not found in topographic aspects and soil organic carbon content;however, the different changing trends of soil organic carbon content between land use types and aspects were found. The impact of slope, elevation, farming system or soil texture accounted for the differences in these soil indicators under different land use types in the A Luoi district.

An integrated methodology for soil moisture analysis using multispectral data in Mongolia

Soil moisture(SM)content is one of the most important environmental variables in relation to land surface climatology,hydrology,and ecology.Long-term SM data-sets on a regional scale provide reasonable information about climate change and global warming specific regions.The aim of this research work is to develop an integrated methodology for SM of kastanozems soils using multispectral satellite data.The study area is Tuv(48°40′30″N and 106°15′55″E)province in the forest steppe zones in Mongolia.In addition to this,land surface temperature(LST)and normalized difference vegetation index(NDVI)from Landsat satellite images were integrated for the assessment.Furthermore,we used a digital elevation model(DEM)from ASTER satellite image with 30-m resolution.Aspect and slope maps were derived from this DEM.The soil moisture index(SMI)was obtained using spectral information from Landsat satellite data.We used regression analysis to develop the model.The model shows how SMI from satellite depends on LST,NDVI,DEM,Slope,and Aspect in the agricultural area.The results of the model were correlated with the ground SM data in Tuv province.The results indicate that there is a good agreement between output SM and SM of ground truth for agricultural area.Further research is focused on moisture mapping for different natural zones in Mongolia.The innovative part of this research is to estimate SM using drivers which are vegetation,land surface temperature,elevation,aspect,and slope in the forested steppe area.This integrative methodology can be applied for different regions with forest and desert steppe zones.

Variability and change of climate extremes from indigenous herder knowledge and at meteorological stations across central Mongolia

In semi-arid regions,air temperatures have increased in the last decades more than in many other parts of the world.Mongolia has an arid/semi-arid climate and much of the population are herders whose livelihoods depend upon limited water resources that fluctuate with a variable climate.Herders were surveyed to identify their observations of changes in climate extremes for two soums of central Mongolia,Ikh-Tamir in the forest steppe north of the Khangai Mountains and Jinst in the desert steppe south of the mountains.The herders’indigenous knowledge of changes in climate extremes mostly aligned with the station-based analyses of change.Temperatures were warming with more warm days and nights at all stations.There were fewer cool days and nights observed at the mountain stations both in the summer and winter,yet more cool days and nights were observed in the winter at the desert steppe station.The number of summer days is increasing while the number of frost days is decreasing at all stations.The results of this study support further use of local knowledge and meteorological observations to provide more holistic analysis of climate change in different regions of the world.