We use the 2013 cotton precision farming survey data to study the adoption of irrigation technologies by cotton farmers in 14 states of the United States. We find that farmers with a higher irrigated yield, and who are from the Southern Plains (Texas and Oklahoma), adopt water-efficient irrigation technologies, such as sub-surface drip and trickle irrigation technologies. There are 10 irrigation technologies that farmers can adopt for cotton production in these 14 cotton-growing states. The intensity of the irrigation technologies, as measured by the number of irrigation technologies adopted in cotton production, is affected by the irrigated cotton yield realized, land holding (total land owned), education, computer use, and the origin of the cotton farmer being from the Southern Plains. We use a multivariate fractional regression model to identify land allocation by the different irrigation technologies used. Our results indicate that significant variables affecting land allocation with different irrigation technologies are the age of the operator, the cover crop, the information sources used, the per acre irrigated yield, the education, and the cotton farmer being from the Southern Plains.

The glaciers in the Nepalese Himalayas are retreating due to rising temperatures. Lack of data and information on Nepal’s cryosphere has impeded scientific studies and field investigations in the Nepalese Himalayas. Therefore, IRD France and Ev-K2 CNR Italy have conducted the PAPRIKA (CryosPheric responses to Anthropogenic PRessures in the HIndu Kush-Himalaya regions: impacts on water resources and society adaptation in Nepal) project in Nepal with the financial support of the French and Italian scientific agencies. This project aims to address the current and future evolution of the cryosphere in response to overall environmental changes in South Asia, and its consequences for water resources in Nepal. Thus, two hydrological models, the GR4J lumped precipitation–runoff model and the snowmelt runoff model (SRM), were used in the Dudh Koshi basin. The GR4J model has been successfully applied in different parts of Europe. To obtain better results in such a harsh and rugged topography, modifications needed to be made, particularly in the snow module. The runoff pattern is analysed herein both for past years and, in a sensitivity analysis, for possible future climatic conditions (i.e. precipitation and temperature) using the SRM and GR4J modelling approaches. The results reveal a significant contribution of snow- and glacier-melt to runoff, and the SRM model shows better performance in Nepalese catchments than the GR4J model.

We conducted biophysical simulations using MapShed to determine the effects of adopting best management practices (BMPs) to reduce nutrients and sediment pollution in a watershed dominated by poultry production in the Saline Bayou Watershed, Louisiana, USA. The reduction of three water pollutants, nitrogen, phosphorus, and sediment from adopting different BMPs were assessed using a linear programming model with the cost minimization objective. We considered three weather scenarios (dry, normal, and wet) and BMP parameter efficiencies obtained from linear regression models. Optimization results showed that nutrient management and agricultural land retirement reduced most of the phosphorus runoff in the watershed at the lowest cost. Results were robust to alternative weather (dry, normal, and wet) scenarios.