Water Productivity Evaluation under Multi-GCM Projections of Climate Change in Oases of the Heihe River Basin, Northwest China

Abstract

As the second largest inland river basin situated in the middle of the Hexi Corridor, Northwest China, the Heihe River basin (HRB) has been facing a severe water shortage problem, which seriously restricts its green and sustainable development. The evaluation of climate change impact on water productivity inferred by crop yield and actual evapotranspiration is of significant importance for water-saving in agricultural regions. In this study, the multi-model projections of climate change under the three Representative Concentration Pathways emission scenarios (RCP2.6, RCP4.5, RCP8.5) were used to drive an agro-hydrological model to evaluate the crop water productivity in the middle irrigated oases of the HRB from 2021–2050. Compared with the water productivity simulation based on field experiments during 2012–2015, the projected water productivity in the two typical agricultural areas (Gaotai and Ganzhou) both exhibited an increasing trend in the future 30 years, which was mainly attributed to the significant decrease of the crop water consumption. The water productivity in the Gaotai area under the three RCP scenarios during 2021–2050 increased by 9.2%, 14.3%, and 11.8%, while the water productivity increased by 15.4%, 21.6%, and 19.9% in the Ganzhou area, respectively. The findings can provide useful information on the Hexi Corridor and the Belt and Road to policy-makers and stakeholders for sustainable development of the water-ecosystem-economy system.

Modeling Soil Water–Heat Dynamic Changes in Seed-Maize Fields under Film Mulching and Deficit Irrigation Conditions

“…It indicated that the future climate change had a more significant impact on yield reduction under the M1WF treatment, compared with the M0WF treatment. The ET decreased by 16.1%, 14.3%, 22.3% for the M1WF treatment and 15.4%, 12.6%, 21.0% for the M0WF treatment under the RCP2.6, RCP4.5, RCP8.5, respectively [30,66,69]. The interannual variation trend of seed-maize yield under the RCP2.6 and RCP8.5 scenarios for the future 30 years were shown in Figure 8.…”

“…Future climate change has brought both opportunities and challenges to food production. Representative Concentration Paths (RCPs) scenarios are the most widely used method to study climate change and its impact on crop productivity [66,67]. Liu et al [66] obtained the daily precipitation, maximum air temperature and minimum air temperature under three RCPs (RCP2.6, RCP4.5, RCP8.…”

The Spatiotemporal Patterns of Climate Asymmetric Warming and Vegetation Activities in an Arid and Semiarid Region

“…The least-square linear regression method was applied to analyze the trend of DNW at the regional and pixel scales [36,37], and the significance of regression coefficients was determined by the t-test (p-values). * indicated significant (p = 0.05).…”

Projections of future precipitation and air temperature over the Tibetan Plateau based on Coupled Model Intercomparison Project Phase 6 multimodel ensembles

“…(2019) also demonstrated that the 33 CMIP5 models evaluated in their study could capture the seasonal temperature patterns; however, most of them tended to underestimate temperatures by approximately 2.0°C. Therefore, downscaling methods and multimodel ensembles (MMEs) are of great significance for correcting biases and reducing uncertainty, as well as for retaining the valuable climate change signals of GCMs (Wang et al ., 2016; Ngai et al ., 2020; Zhang et al ., 2019; Wang et al ., 2019a; Chen et al ., 2016a; 2016b; Liu et al ., 2019). For example, Yang et al .…”