In the present study, the streamflow simulation capacities between the Soil and Water Assessment Tool (SWAT) and the Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS) were compared for the Huai Bang Sai (HBS) watershed in northeastern Thailand. During calibration (2007–2010) and validation (2011–2014), the SWAT model demonstrated a Coefficient of Determination (R²) and a Nash Sutcliffe Efficiency (NSE) of 0.83 and 0.82, and 0.78 and 0.77, respectively. During the same periods, the HEC-HMS model demonstrated values of 0.80 and 0.79, and 0.84 and 0.82. The exceedance probabilities at 10%, 40%, and 90% were 144.5, 14.5, and 0.9 mm in the flow duration curves (FDCs) obtained for observed flow. From the HEC-HMS and SWAT models, these indices yielded 109.0, 15.0, and 0.02 mm, and 123.5, 16.95, and 0.02 mm. These results inferred those high flows were captured well by the SWAT model, while medium flows were captured well by the HEC-HMS model. It is noteworthy that the low flows were accurately simulated by both models. Furthermore, dry and wet seasonal flows were simulated reasonably well by the SWAT model with slight under-predictions of 2.12% and 13.52% compared to the observed values. The HEC-HMS model under-predicted the dry and wet seasonal flows by 10.76% and 18.54% compared to observed flows. The results of the present study will provide valuable recommendations for the stakeholders of the HBS watershed to improve water usage policies. In addition, the present study will be helpful to select the most appropriate hydrologic model for humid tropical watersheds in Thailand and elsewhere in the world.

The frequency and severity of floods have been found to increase in recent decades, which have adverse effects on the environment, economics, and human lives. The catastrophe of such floods can be confronted with the advance prediction of floods and reliable analyses methods. This study developed a combined flood modeling system for the prediction of floods, and analysis of associated vulnerabilities on urban infrastructures. The application of the method was tested on the Blue River urban watershed in Missouri, USA, a watershed of historical significance for flood impacts and abundance of data availability for such analyses. The combined modeling system included two models: hydrodynamic model HEC-RAS (Hydrologic Engineering Center—River Analysis System) and hydrologic model SWAT (Soil and Water Assessment Tool). The SWAT model was developed for the watershed to predict time-series hydrograph data at desired locations, followed by the setup of HEC-RAS model for the analysis and prediction of flood extent. Both models were calibrated and validated independently using the observed data. The well-calibrated modeling setup was used to assess the extent of impacts of the hazard by identifying the flood risk zones and threatened critical infrastructures in flood zones through inundation mapping. Results demonstrate the usefulness of such combined modeling systems to predict the extent of flood inundation and thus support analyses of management strategies to deal with the risks associated with critical infrastructures in an urban setting. This approach will ultimately help with the integration of flood risk assessment information in the urban planning process.

A field-scale experimental study was conducted in Sub-Saharan Africa (Ethiopia and Ghana) to examine the effects of conservation agriculture (CA) with drip irrigation system on water productivity in vegetable home gardens. CA here refers to minimum soil disturbance (no-till), year-round organic mulch cover, and diverse cropping in the rotation. A total of 28 farmers (13 farmers in Ethiopia and 15 farmers in Ghana) participated in this experiment. The experimental setup was a paired ‘t’ design on a 100 m² plot; where half of the plot was assigned to CA and the other half to conventional tillage (CT), both under drip irrigation system. Irrigation water use and crop yield were monitored for three seasons in Ethiopia and one season in Ghana for vegetable production including garlic, onion, cabbage, tomato, and sweet potato. Irrigation water use was substantially lower under CA, 18% to 45.6%, with a substantial increase in crop yields, 9% to about two-fold, when compared with CT practice for the various vegetables. Crop yields and irrigation water uses were combined into one metric, water productivity, for the statistical analysis on the effect of CA with drip irrigation system. One-tailed paired ‘t’ test statistical analysis was used to examine if the mean water productivity in CA is higher than that of CT. Water productivity was found to be significantly improved (α = 0.05) under the CA practice; 100%, 120%, 222%, 33%, and 49% for garlic, onion, tomato, cabbage, and sweet potato respectively. This could be due to the improvement of soil quality and structure due to CA practice, adding nutrients to the soil and sticking soil particles together (increase soil aggregates). Irrigation water productivity for tomato under CA (5.17 kg m⁻³ in CA as compared to 1.61 kg m⁻³ in CT) is found to be highest when compared to water productivity for the other vegetables. The mulch cover provided protection for the tomatoes from direct contact with the soil and minimized the chances of soil-borne diseases. Adapting to CA practices with drip irrigation in vegetable home gardens is, therefore, a feasible strategy to improve water use efficiency, and to intensify crop yield, which directly contributes towards the sustainability of livelihoods of smallholder farmers in the region.

It is widely known that land use/land cover (LULC) changes significantly alter watershed hydrology and sediment yields. The impact, especially on erosion and sedimentation, is likely to be exacerbated in regions dominated by high rainfall patterns such as monsoons. This study analyzed the hydrological responses of LULC changes in terms of streamflow (SF) and sediment yield (SY) in a monsoon-dominated tropical watershed, the Periyar River Watershed (PRW) in Kerala, India. This watershed drains an area of 4793 km² characterized by an average monsoon rainfall of 2900 mm from June to November. The watershed hydrology and sediment dynamics were simulated using the Soil and Water Assessment Tool (SWAT) model for the impact assessment at the watershed outlet and the sub-watershed level. Historical LULC data were analyzed for 1988, 1992, 2002, and 2016 using the maximum likelihood method, and future LULC changes were projected for 2030, 2050, 2075, and 2100 using the Markov chain–cellular automata technique. Between 1988 and 2016, the urban area increased by 4.13 percent, while plantation and forest coverage decreased by 1.5 percent. At this rate, by 2100, the urban area is expected to grow by 16.45% while plantations and forest area will shrink by 13.7% compared to 1988. The effects of these changes on SF and SY were found to be minimal at the watershed outlet; however, at the spatial scale of sub-watersheds, the changes varied up to 70% for surface runoff and 200% for SY. These findings highlight the potential impacts of LULC changes in a monsoon-dominated watershed and may contribute to the development of successful LULC-based watershed management strategies for prevention of flooding and sediment loss.