Impact of climate and land-use changes on hydrological processes and sediment yield—a case study of the Be River catchment,Vietnam

Abstract

The impact of climate and land-use changes on hydrological processes and sediment yield is investigated in the Be River catchment, Vietnam, using the Soil and Water Assessment Tool (SWAT) hydrological model. The sensitivity analysis, model calibration and validation indicated that the SWAT model could reasonably simulate the hydrology and sediment yield in the catchment. From this, the responses of the hydrology and sediment to climate change and land-use changes were considered. The results indicate that deforestation had increased the annual flow (by 1.2%) and sediment load (by 11.3%), and that climate change had also significantly increased the annual streamflow (by 26.3%) and sediment load (by 31.7%). Under the impact of coupled climate and land-use changes, the annual streamflow and sediment load increased by 28.0% and 46.4%, respectively. In general, during the 1978–2000 period, climate change influenced the hydrological processes in the Be River catchment more strongly than the land-use change.

Editor Z.W. Kundzewicz; Associate editor Q. Zhang

Citation Khoi, D.N. and Suetsugi, T., 2014. Impact of climate and land-use changes on hydrological processes and sediment yield—a case study of the Be River catchment, Vietnam. Hydrological Sciences Journal, 59 (5), 1095–1108.     

Multitemporal Landsat-MODIS fusion for cropland drought monitoring in El Salvador

Abstract

This study aims to develop an approach to characterize cropland drought conditions in El Salvador, Central America. The data were processed for 2016–2017 through three main steps: (1) reconstructing MODIS land-surface temperature (LST), (2) Landsat-MODIS data fusion and (3) drought delineation using the temperature vegetation dryness index (TVDI). The results of LST reconstruction using the random forests (RF) indicated the median RMSE value of 0.5?°C. The fusion results achieved from the STARFM compared with the reference Landsat data revealed close agreement with the correlation coefficient (r) values higher than 0.84. The TVDI results verified with that from the reference Landsat data indicated r values of 0.85 and 0.75 for 2016 and 2017, respectively. The larger very dry area was observed for the 2016 primera season due to prolonged droughts. Approximately 11.5% and 10.7% of croplands were, respectively, associated with very dry moisture condition in the 2016 and 2017 primera seasons.     

Soil salinity and sodicity in a shrimp farming coastal area of the Mekong Delta,Vietnam

Soil salinity and sodicity are environmental problems in the shrimp farming areas of the Cai Nuoc district, Ca Mau province, Vietnam. In 2000, farmers in the district switched en masse from rice cropping to shrimp culture. Due to recent failure in shrimp farming, many farmers wish to revert to a rotational system with rice in the wet season and shrimps in the dry season. So far, all their attempts to grow rice have failed. To assess soil salinity and sodicity, 25 boreholes in shrimp ponds were analysed in four consecutive seasons from 2002 to 2004. The results showed that soil salinity was quite serious (mean EC_e 29.25 dS m⁻¹), particularly in the dry season (mean EC_e 33.44 dS m⁻¹). In the wet season, significant amounts of salts still remained in the soil (mean EC_e 24.65 dS m⁻¹) and the highest soil salinity levels were found near the sea. Soil sodicity is also a problem in the district (exchangeable sodium percentage range 9.63–72.07%). Sodicity is mainly a phenomenon of topsoils and of soils near the sea. Both soil salinity and sodicity are regulated by seasonal rainfall patterns. They could together result in disastrous soil degradation in the Cai Nuoc district.     

Settlement Prediction of Surcharge Preloaded Low Embankment on Soft Ground Subjected to Cyclic Loading

This article studies the effect of dynamic cyclic loading and surcharge preloading method on the post-construction settlement of low embankments. Soil samples obtained from the soft ground under an embankment were consolidated by surcharge preloading followed by static and dynamic cyclic loading in the odometer. The results show that the consolidation deformation of the soil samples is independent of the frequency of the dynamic cyclic loading, which was simulated to follow the half-sine wave, and this is consistent with the energy concept. The post-construction settlement increases with increasing amplitude of cyclic load and the effectiveness of surcharge preloading depends on the difference between magnitude of surcharge and amplitude of the cyclic load. Based on the consolidation theory combined with the test results, a formula has been proposed to compute the post-construction settlement of a low embankment under cyclic loading.     

Spatial prediction of rainfall-induced shallow landslides using hybrid integration approach of Least-Squares Support Vector Machines and differential evolution optimization: a case study in Central Vietnam

This study represents a hybrid intelligence approach based on the differential evolution optimization and Least-Squares Support Vector Machines for shallow landslide prediction, named as DE–LSSVM_SLP. The LSSVM is used to establish a landslide prediction model whereas the DE is adopted to search the optimal tuning parameters of the LSSVM model. In this research, a GIS database with 129 historical landslide records in the Quy Hop area (Central Vietnam) has been collected to establish the hybrid model. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to assess the performance of the newly constructed model. Experimental results show that the proposed model has high performances with approximately 82% of AUCs on both training and validating datasets. The model’s results were compared with those obtained from other methods, Support Vector Machines, Multilayer Perceptron Neural Networks, and J48 Decision Trees. The result comparison demonstrates that the DE–LSSVM_SLP deems best suited for the dataset at hand; therefore, the proposed model can be a promising tool for spatial prediction of rainfall-induced shallow landslides for the study area.     

Urban flood vulnerability assessment in a densely urbanized city using multi-factor analysis and machine learning algorithms

Theoretical and Applied Climatology - Flood is considered as the most devastating natural hazards that cause the death of many lives worldwide. The present study aimed to predict flood...     

Determination of groundwater solute transport parameters in finite element modelling using tracer injection and withdrawal testing data

The groundwater tracer injection and withdrawal tests are often carried out for the determination of aquifer solute transport parameters. However, the parameter analyses encounter a great difficulty due to the radial flow nature and the variability of the temporal boundary conditions. An adaptive methodology for the determination of groundwater solute transport parameters using tracer injection and withdrawal test data had been developed and illustrated through an actual case. The methodology includes the treatment of the tracer boundary condition at the tracer injection well, the normalization of tracer concentration, the groundwater solute transport finite element modelling and the method of least squares to optimize the parameters. An application of this methodology was carried out in a field test in the South of Hanoi city. The tested aquifer is Pleistocene aquifer, which is a main aquifer and has been providing domestic water supply to the city since the French time. Effective porosity of 0.31, longitudinal dispersivity of 2.2 m, and hydrodynamic dispersion coefficients from D = 220 m²/d right outside the pumping well screen to D =15.8 m²/d right outside the tracer injection well screen have been obtained for the aquifer at the test site. The minimal sum of squares of the differences between the observed and model normalized tracer concentration is 0.00119, which is corresponding to the average absolute difference between observed and model normalized concentrations of 0.035 5 (while 1 is the worst and 0 is the best fit).     

Local stress analysis in granular materials at a mesoscale

The purpose of this paper is to contribute to the change of scale techniques developed for granular materials. The proposed approach consists in considering an intermediate scale between the macroscales and microscales, called the mesoscale, using the classical homogenization scheme. In this approach, the mesoscale for 2D granular materials was defined at the level of local volumes, called mesodomains, which are local closed structures composed of particles in contact. In this paper, we focused on defining a local stress field at this scale. Two different methods are proposed, both based on the equivalent continuum mean stress but using different approximations of the mean stress tensor for each mesodomain. The two proposed methods were then compared to each other. Analyses performed on the stress field at the mesoscale show that this local field is heterogeneous and, in particular, that its heterogeneity is significantly structured at this scale. The distribution of the local mean stress (first invariant of the local stress tensor) is uniform in any mesodomain, whereas the distribution of the stress deviator (second invariant of the deviatoric part of the local stress tensor) is significantly dependent on the elongation direction and on the elongation degree of the mesodomains. The local stress ratio (ratio of the stress deviator to the mean stress) is higher within the mesodomains that are elongated in the global compression direction than that within the ones elongated in the global extension direction. Copyright © 2011 John Wiley & Sons, Ltd.