• Energy Research

Lower Mekong Basin (LMB) experiences a recurrent drought phenomenon. However, few studies have focused on drought monitoring in this region due to lack of ground observations. The newly released Climate Hazards Group Infrared Precipitation with Station data (CHIRPS) with a long-term record and high resolution has a great potential for drought monitoring. Based on the assessment of CHIRPS for capturing precipitation and monitoring drought, this study aims to evaluate the drought condition in LMB by using satellite-based CHIRPS from January 1981 to July 2016. The Standardized Precipitation Index (SPI) at various time scales (1–12-month) is computed to identify and describe drought events. Results suggest that CHIRPS can properly capture the drought characteristics at various time scales with the best performance at three-month time scale. Based on high-resolution long-term CHIRPS, it is found that LMB experienced four severe droughts during the last three decades with the longest one in 1991–1994 for 38 months and the driest one in 2015–2016 with drought affected area up to 75.6%. Droughts tend to occur over the north and south part of LMB with higher frequency, and Mekong Delta seems to experience more long-term and extreme drought events. Severe droughts have significant impacts on vegetation condition.

The Xinjiang Uyghur Autonomous Region of China has experienced significant land cover and climate change since the beginning of the 21st century. However, a reasonable simulation of evapotranspiration (ET) and its response to environmental factors are still unclear. For this study, to simulate ET and its response to climate and land cover change in Xinjiang, China from 2001 to 2012, we used the Common Land Model (CoLM) by adding irrigation effects for cropland and modifying root distributions and the root water uptake process for shrubland. Our results indicate that mean annual ET from 2001 to 2012 was 131.22 (±21.78) mm/year and demonstrated no significant trend (p = 0.12). The model simulation also indicates that climate change was capable of explaining 99% of inter-annual ET variability; land cover change only explained 1%. Land cover change caused by the expansion of croplands increased annual ET by 1.11 mm while climate change, mainly resulting from both decreased temperature and precipitation, reduced ET by 21.90 mm. Our results imply that climate change plays a dominant role in determining changes in ET, and also highlight the need for appropriate land-use strategies for managing water sources in dryland ecosystems within Xinjiang.

Even with significant breakthroughs in the production and delivery of meteorological information, most farmers are not able to utilize such information properly and pertinently. Up to the present time, a standardized scale has not been developed to examine farmers’ sustainability barriers to meteorological information use (BMIU). Furthermore, there is no doubt that identifying indicators and dimensions of sustainability barriers to meteorological information and weather forecasts’ usage by farmers can play a major role in their adaptation and resilience to the risks of climate change. Therefore, the present study aimed to generate and validate a scale for BMIU by farmers through an eight-step approach. Accordingly, the statistical population included 9006 Iranian farmers, 368 of whom were selected as study samples. The principal component factor analysis (PCFA) and second-order confirmatory factor analysis (CFA) were further practiced to develop the scale for meteorological information and weather forecasts’ use. Factor analysis also led to the emergence of five latent factors including “educational–communicative barriers (ECBs)”, “normative barriers (NBs)”, “informational barriers (IBs)”, “infrastructural–political barriers (IPBs)”, and “professional–economic barriers (PEBs)”. The second-order CFA correspondingly confirmed these five factors and their 25 related indicators. Given the challenges facing academic scholars, decision makers, and authorities in the application and facilitation of meteorological information, the developed multidimensional scale in this study along with its implementation steps can be effective in examining the limitations of utilizing such information and measuring its impacts in different agricultural communities.

The aim of the present research was to analyze the farmers’ intention towards participation in the management and conservation of wetlands through the lens of the extended theory of planned behavior (TPB). To do this, a cross-sectional survey of Iranian farmers was carried out. To select the samples, a multi-stage random sampling process with a proportional assignment was employed. The research instrument was a researcher-made questionnaire whose validity and reliability were verified using various quantitative and qualitative indicators. The results of the extended TPB using structural equation modeling showed that four variables, namely moral norms of participation in management and conservation (MNPMC), attitude towards participation in management and conservation (APMC), subjective norms towards participation in management and conservation (SNPMC), and self-concept about participation in management and conservation (SCPMC) had positive and significant impacts on intention towards participation in management and conservation (IPMC). The results also revealed that that entering MNPMC and SCPMC into TPB could increase its explanatory power. Also, the fit indicators supported the extended TPB. From a practical point of view, the present study provides justifications and insights for the use of MNPMC, APMC, SNPMC, and SCPMC in policies and programs intended to encourage farmers and local communities to participate in wetlands management and conservation.

Because of the use of outdated terrestrial datasets, regional climate models (RCMs) have a limited ability to accurately simulate weather and climate conditions over heterogeneous oasis-desert systems, especially near large mountains. Using actual terrestrial datasets from satellite products for RCMs is the only possible solution to the limitation; however, it is impractical for long-period simulations due to the limited satellite products available before 2000 and the extremely time- and labor-consuming processes involved. In this study, we used the Weather Research and Forecasting (WRF) model with observed estimates of land use (LU), albedo, Leaf Area Index (LAI), and green Vegetation Fraction (VF) datasets from satellite products to examine which terrestrial datasets have a great impact on simulating water and heat conditions over heterogeneous oasis-desert systems in the northern Tianshan Mountains. Five simulations were conducted for 1–31 July in both 2010 and 2012. The decrease in the root mean squared error and increase in the coefficient of determination for the 2 m temperature (T2), humidity (RH), latent heat flux (LE), and wind speed (WS) suggest that these datasets improve the performance of WRF in both years; in particular, oasis effects are more realistically simulated. Using actual satellite-derived fractional vegetation coverage data has a much greater effect on the simulation of T2, RH, and LE than the other parameters, resulting in mean error correction values of 62%, 87%, and 92%, respectively. LU data is the primary parameter because it strongly influences other secondary land surface parameters, such as LAI and albedo. We conclude that actual LU and VF data should be used in the WRF for both weather and climate simulations.

The effects of global climate change threaten the availability of water resources worldwide and modify their tempo-spatial pattern. Properly quantifying the possible effects of climate change on water resources under different hydrological models is a great challenge in ungauged alpine regions. By using remote sensing data to support established models, this study aimed to reveal the effects of climate change using two models of hydrological processes including total water resources, peak flows, evapotranspiration, snowmelt and snow accumulation in the ungauged Hotan River Basin under future representative concentration pathway (RCP) scenarios. The results revealed that stream flow was much more sensitive to temperature variation than precipitation change and increased by 0.9–10.0% according to MIKE SHE or 6.5–10.5% according to SWAT. Increased evapotranspiration was similar for both models with a range of 7.6–31.3%. The snow-covered area shrank from 32.5% to 11.9% between the elevations of 4200–6400 m, respectively, and snow accumulation increased when the elevation exceeded 6400 m above sea level (asl). The results also suggested that the fully distributed and semi-distributed structures of these two models strongly influenced the responses to climate change. The study proposes a practical approach to assess the climate change effect in ungauged regions.

The growing resource constraints around land, water, and energy while tackling climate change in Central Asia threaten the agricultural sustainability that underpins food security and people livelihoods. However, there is a lack of comprehensive long-term evaluations of the intricate water-food-energy‑carbon nexus on a wider scale, hindering sustainable agriculture across this region. This study developed an integrated top-down and bottom-up approach to quantify the water consumption, energy use, and carbon emissions from crop production in Central Asia and established the coupling coordination model to evaluate the nexus (1995–2020). The results show that the total water consumption in Central Asia increased from 161.55 × 109 to 170.93 × 109 m3 at a rate of 1.39 × 109 m3/a in which blue water accounted for 59%. However, the energy use and carbon emissions decreased at a rate of − 1.57 PJ/a and − 0.06 MtCO2eq/a, respectively, in which the indirect energy and indirect carbon emissions varied greatly. Furthermore, the coupling coordination level of water-food-energy‑carbon nexus oscillated between uncoordinated and transitional development stages before 2000 and then entered coordinated development in 2003 after a short transitional development. The findings revealed that this oscillation may have been abnormal owing to issues such as yield loss and soil degradation. These results highlight the complex interplay between water, food, energy, and carbon of crop production across Central Asia and emphasise the need for a more integrated policymaking with increased regional cooperation, improvement in resource utilization efficiency, agricultural structure optimization, and protection of farmers rights towards agricultural sustainability.