Flash droughts (FDs) develop rapidly and can strongly affect ecosystem functioning and water resources. However, their spatiotemporal variability in China and their effects on diverse ecosystems remain poorly characterized. In this study, the frequency of FD events during the growing season in China from 2001 to 2023 and their key driving interaction mechanisms were systematically analyzed. Using multisource remote-sensing indicators, including the leaf area index, potential evapotranspiration, and gross primary productivity, we quantitatively assessed response timing and impact intensity across different ecosystems. Furthermore, we projected future FD changes in China for 2000–2100 under different climate scenarios. The results reveal that FD frequency varies across different ecosystems in China, with the highest occurrence in humid regions (mean = 6.98 events) and the lowest in arid regions (6.13). Driver analysis indicates that drought risk increases notably under high temperatures and low precipitation. Furthermore, soil moisture dynamics exhibit a two-phase evolutionary pattern of “rapid depletion followed by differential recovery”, whereas ecosystem indicators demonstrate a “transient enhancement followed by persistent decline” response pattern. Compared to arid regions dominated by short vegetation, humid-forest ecosystems exhibit faster response times and greater intensity reactions to FD. The Coupled Model Intercomparison Project Phase 6 (CMIP6) multimodel ensemble projections indicate the most severe future conditions under the RCP5-8.5 scenario. These findings underscore how climate change threatens vegetation ecosystem stability and highlight the urgent need for effective mitigation policies and sustainable management strategies to protect terrestrial vegetation ecosystems.

As a critical ecological security and economic corridor in China, monitoring the ecological quality of the Yellow River Basin (YRB) is essential for China’s ecological protection and sustainable economic development. In this study, we constructed a modified Remote Sensing Ecological Index (MRSEI) to investigate the spatiotemporal dynamics of ecological quality in the YRB from 2001 to 2023. Meanwhile, we incorporated the Aridity Index (AI) and the temperature (T). Furthermore, Multiple Linear Regression and Random Forest models were employed to quantify the contributions of moisture (NDMI), urbanization (NDBI), and productivity (NPP) to ecological variance. Finally, land cover type conversion was employed to interpret ecological variations detected by the MRSEI dynamic ratio. The primary results are as follows: (1) Ecological quality in the middle reaches of the YRB significantly improved from 2001 to 2010, remaining relatively stable from 2011 to 2023. (2) No significant correlation was observed between temperature (T) and MRSEI, but significant correlations between Aridity Index (AI) and MRSEI were observed during 2001–2010 in the Windbreak and Sand Fixation Functional Zone (WSFZ, r2001−2010=0.520 ± 0.225, p < 0.01) and Soil Conservation Functional Zone (SCFZ, r2001−2010=0.467 ± 0.350, p < 0.01). (3) The dominant land cover conversion types include barred land-to-cropland conversion (3640.44 km2) and cropland/barren land-to-grassland conversion (3212.19 km2; 1507.25 km2) in regions where ecological conditions improved from 2001 to 2023. (4) Form 2001–2023, NDMI (Surface Moisture), contributes 52%-56% to ecological dynamics, while the water cycle budget exerts a governing influence on basin-wide ecological quality. This study offers critical insights for promoting ecological protection and sustainable development in the functional zones of the YRB.

Investigating surface dry-wet patterns on the Qinghai Plateau (QP) is crucial for water allocation, ecological sustainability, and climate variability adaptation strategies. Existing discrepancies in the QP dry-wet trends and distribution characteristics underscored the need for a more refined analysis. This study utilized the Thornthwaite Moisture Index (IM) to quantify changes in surface dryness and wetness under prevailing climatic conditions. Linear trend regression and ensemble empirical mode decomposition (EEMD) were applied to study the dynamic and periodic characteristics of the QP from 1980 to 2018. Our findings revealed a decrease from southeast to northwest in IM, with the semi-arid and sub-humid transition line aligning closely with the 400 mm isohyet. The dry-wet transition line exhibited a northwestward trend over the past four decades. Possibly influenced by monsoon circulation and El Nino-Southern Oscillation (ENSO), the annual IM displayed a quasi-cycle of 3 to 5 years, manifested by a dry period (1990-2004) and a wet period (2005-2012). However, spatial differences existed, challenging the universality of the "Dry gets Drier and Wet gets Wetter (DDWW)" pattern. Precipitation (PRCP) changes could predict over 90 % of IM spatiotemporal variations. Additionally, the IM response to Average Temperature (TAVG) exhibited an inverted U-shaped curve, with a boundary (-3.8 degrees C) below which cooler regions became wetter and above which they became drier. The observed warming and precipitation shifts suggested that continued warming could lead to warmer and wetter climates, potentially causing ecological and environmental problems. Therefore, examining the surface moisture budget is of critical scientific and practical significance, in order to provide a decision- making basis for mitigating and adapting to climate change.

Evapotranspiration (ET) plays an important in the exchange of water, carbon and energy on land. The ET estimates based on different models and remote sensing data have different degrees of uncertainty. Bayesian model averaging (BMA) provides a way to reduce the uncertainty. Based on water and heat flux observation data in the Three-River Headwaters Region of China, evapotranspiration simulated by ARTS and PT-JPL models, and internationally shared MOD16 and SSEBop remote sensing evapotranspiration products, we conducted a BMA integration study, resulting in a dataset of surface evapotranspiration in the Three-River Headwaters Region of Qinghai Province based on Bayesian model averaging from 2003 to 2015. By verifying the results of each input model and BMA integrated model, it is found that the correlation between ET based on BMA and flux observation data is 0.94, which can explain 89% of the seasonal variation data, outperforming the performance of a single model. The results show that BMA model integration can integrate the inherent advantages of different models and reduce the uncertainty of result estimation for more reliable estimation results. This dataset can provide more accurate data for studying hydrothermal changes and evaluating ecosystem regulation functions in the Three-River Headwaters Region.

中国陆地生态系统在全球碳循环中发挥着重要作用,植被净初级生产力(NPP)是重要碳循环分量.但对中国植被NPP未来变化趋势、稳定性及应对气候变化机制的研究尚少见报道.本文应用前期发展的生态系统过程模型CEVSA-RS,分别模拟了RCP4.5和RCP8.5气候情景下2006-2099年中国植被NPP,利用分段线性回归分析NPP年际变化转折点,采用滑动窗口法分析NPP稳定性的变化及气温和降水的影响.结果表明:①中国植被NPP在RCP4.5和RCP8.5气候情景下的总量分别为4.41 Pg Ca-1和4.40 Pg C a-1,季风区分别贡献了总量的72.8％和73.4％.②两种情景下NPP年际变化均为先增后减,转折点分别为2062年和2055年;转折年份之前NPP分别以5.3gCm-210a-1、6.5gCm-2 10a-1显著增加,后以前期的4.28倍和2.57倍速率下降.③两种气候情景下滑动窗口计算的NPP稳定性分别以-2.9％10a-1和-4.3％10a-1的速率显著下降.④RCP4.5和RCP8.5情景下,气温显著升高,干旱指数显著下降,饱和水汽压差显著升高,全国趋向暖干化.⑤降水稳定性的降低主导着温带季风区NPP稳定性的降低,而气温稳定性的降低主导着青藏高原区NPP稳定性的降低.本文结果表明,未来气候系统的稳定性降低、气候趋向暖干化将导致全国植被NPP不升反降.因此,积极开展减缓和适应气候变化行动,如双碳行动,具有重要的科学和现实意义.

The alpine grasslands of the Qinghai-Tibetan Plateau play an important role in multiple ecosystem functions, all of which are key in regulating regional climate influences and providing pristine headwaters for millions of people downstream from this basin. Alpine grasslands act as a carbon sink, storing carbon dioxide and keeping heat-trapping greenhouse gases out of the atmosphere, but it is not clear how this will change in a warming climate in the future. In this paper, the net ecosystem productivity (NEP) of alpine grasslands in Qinghai province, on the Qinghai-Tibetan Plateau, was predicted for the period from 2010 to 2099. Trends and stability were analyzed under two climate scenarios, Representative Concentration Pathway 4.5 (RCP4.5) and 8.5 (RCP8.5) representing the lower and higher emission scenarios for greenhouse gases. The results suggest that grasslands will continue to contribute as a carbon sink, with a positive NEP through this century. Almost the same magnitude (38 Tg C a-1, 1 T g = 1012 g) of contribution was projected under both scenarios. Grasslands are projected to be the major contributor to NEP in Qinghai province, with more than 89% of NEP in the future. The carbon sink function will increase over more than 69% of the grasslands and peak around 2069 (RCP4.5) or 2066 (RCP8.5). Then the carbon sink function will begin to decrease and it will decrease more quickly and become more variable under the RCP8.5 than the RCP4.5. The impacts of temperature and precipitation changes were analyzed and NEP was found to be more sensitive to temperature than precipitation change. The trend of increasing contribution to NEP is driven by a warming climate, while the stability of NEP is mainly influenced by the precipitation, which results in an upward trend before the peak and a decline due to stresses from limits in available water in a continued warming climate.

Numbers and sizes of photovoltaic solar power plants have grown unprecedentedly over the last few years in China, which aims to achieve a carbon emission peak by 2030 and carbon neutrality by 2060. Thus, timely and accurate monitoring of photovoltaic solar power plants is crucial to the design and management of renewable electricity systems in China. Random forest algorithm has been used to map photovoltaic solar power plants at multiple scales, however, it always causes several salt-and-pepper noises, limiting its application at larger spatial scales. Here we first develop a photovoltaic solar power plant mapping method through integrating time series Landsat imagery, random forest, and morphological characteristics. Then we apply this method in Gansu Province, which has abundant solar and wind energy resources and provide large amounts of potential lands for photovoltaic development, and generate the annual photovoltaic maps from 2015 to 2020. We further analyze the spatial-temporal dynamics of sizes and areas of photovoltaic solar power plants and major land cover conversion of expansive photovoltaic regions. Finally, we discuss the reliability, uncertainties, implications, and future development of our improved methods. We find our photovoltaic mapping method can remove most of salt-and-pepper noises effectively, and the resultant maps in Gansu for 2020 have very high accuracies with user's and producer's accuracies of 97.57% and 99.22%, respectively. There are 165.29 km2 photovoltaic solar power plants in Gansu for 2020, and most of which are located in the northwestern Gansu. In addition, the photovoltaic with patch size > 1 km2 and & LE; 2 km2 (53.4 km2, 32.3%) has largest patch number (39, 15.7%). The improved photovoltaic mapping methods and further analysis in this study provide critical information for accurate and automatic classification of photovoltaic solar power plants in the future, as well as the environmental and sustainable development of solar energy in China.

In order to investigate NPP and its stability at long time scales of nearly 100 years under future climate scenarios,the authors developed the dataset of Stability of Vegetation Net Primary Productivity and Climate Impacts in China in the Following Century using HadGEM2-ES data scenarios based on the Regional Climate Model RegCM4.6 and CMIP5.The dataset includes:(1)mean NPP values and their trends from 2006 to 2099 under RCP4.5 and RCP8.5 scenarios;(2)multi-year mean NPP stability values for the full(2006-2099),early(2006-2035),mid(2036-2065)and late(2066-2099)periods.The spatial resolution of the data is 0.1°.The dataset is archived in 17 data files with data size of 15.0 MB(Compressed into one file with 4.26 MB).One of the research results based on this dataset was published in Acta Geographica Sinica,Vol.78,No.3,2023.

Agricultural activities have been expanding globally with the pressure to provide food security to the earth's growing population. These agricultural activities have profoundly impacted soil organic carbon (SOC) stocks in global drylands. However, the effects of clearing natural ecosystems for cropland (CNEC) on SOC are uncertain. To improve our understanding of carbon emissions and sequestration under different land uses, it is necessary to characterize the response patterns of SOC stocks to different types of CNEC. We conducted a meta-analysis with mixed-effect model based on 873 paired observations of SOC in croplands and adjacent natural ecosystems from 159 individual studies in global drylands. Our results indicate that CNEC significantly (p < .05) affects SOC stocks, resulting from a combination of natural land clearing, cropland management practices (fertilizer application, crop species, cultivation duration) and the significant negative effects of initial SOC stocks. Increases in SOC stocks (in 1 m depth) were found in croplands which previously natural land (deserts and shrublands) had low SOC stocks, and the increases were 278.86% (95% confidence interval, 196.43%-361.29%) and 45.38% (26.53%-62.23%), respectively. In contrast, SOC stocks (in 1 m depth) decreased by 24.11% (18.38%-29.85%) and 10.70% (1.80%-19.59%) in clearing forests and grasslands for cropland, respectively. We also established the general response curves of SOC stocks change to increasing cultivation duration, which is crucial for accurately estimating regional carbon dynamics following CNEC. SOC stocks increased significantly (p < .05) with high long-term fertilizer consumption in cleared grasslands with low initial SOC stocks (about 27.2 Mg ha-1 ). The results derived from our meta-analysis could be used for refining the estimation of dryland carbon dynamics and developing SOC sequestration strategies to achieve the removal of CO2 from the atmosphere.

地表反照率是影响地表辐射收支与能量平衡的重要地表物理参数,是区域和全球气候变化研究中的一个关键要素.以三江源为案例区,基于2001-2018年生长季(6-8月)中分辨率成像光谱仪(MODIS)地表反照率(MCD43C3)产品,以及同期气候和植被指数数据,应用随机森林回归算法量化植被和气候对地表反照率时空变化的影响分析了土地利用/覆被变化导致的地表辐射特性参数(地表反照率)的改变引起的辐射温度效应.结果表明:三江源区域生长季地表反照率在空间上呈自东南向西北递增的特征,其均值为(0.163±0.027),集中分布在0.12-0.18.长江源园区、黄河源园区以及澜沧江源园区地表反照率差异较大,分别是(0.177±0.036)、(0.153±0.037)和(0.156±0.002).从年际变化来看,研究区地表反照率以每10年(0.152±0.763)％速率不显著下降(P=0.47),但其变化趋势存在明显空间分异,其中显著减少(增加)的区域占8.4％(1.9％),长江源园区、黄河源园区以及澜沧江源园区以不同速率下降,分别为每10年下降(0.078±0.900)％、(0.215±0.740)％、(0.152±0.450)％.三江源地表反照率时空变化受气候和植被因子双重影响,而植被因子是主导因子.在气候因子中,最高气温对地表反照率年际变化的影响最大,其次是降水,影响最小的是最低气温.生长季地表反照率变化的辐射温度效应总体上表现为辐射增温效应,值为(0.11±0.42)℃,空间上既有增温效应,也有降温效应.植被覆盖度、地表反照率与辐射温度效应间为正反馈,生长季草地覆盖度增加(降低),地表反照率减少(增加)引起辐射温增(降温)效应.统计分析表明高寒退化植被恢复对区域地表反照率影响引起了辐射增温效应,需对该问题予以更多关注,建议开展进一步的观测和模拟研究,以更深入地揭示高寒草地生物地球物理过程和机制.

净初级生产力(NPP)是评估全球气候变化和人类活动下生态系统状况、过程和机制的重要指标之一.研究以中国首批国家公园之一的三江源国家公园为对象,利用GLOPEM-CEVSA耦合模型,以1981-2018年空间插值的气象数据和基于遥感反演的FPAR数据为输入,分别估算仅气候驱动的潜在NPP(NPPCL)和气候遥感共同驱动的现实NPP(NPPRS),以二者之差厘定人类活动影响的NPP(NPPHA),进而探究全球气候变化下人类活动的影响.结果表明:(1)三江源地区NPPRS多年均值为309.70 g C m-2 a-1,占NPPCL的61.65％.其中,黄河源、长江源和澜沧江源园区NPPRS分别为249.88 g C m-2 a-1、140.18 g C m-2a-1和330.55 g C m-2a-1.(2)全区NPPRS以2.00 g C m-2a-1速率显著增加,高于NPPCL(1.74 g C m-2 a-1),其中黄河源、长江源和澜沧江源园区NPPRs增长速率分别占各自NPPCL增长速率的89.13％、90.23％和77.43％,澜沧江源园区整体受人类活动影响最大.(3)气候影响方面,年降水、年平均日最高气温和年平均日最低气温共同可解释全区NPPCL和NPPRS年际变化的51％和73％,可分别解释黄河源、长江源和澜沧江源园区的48％和58％、52％和69％、42％和50％,其中气温对NPP年际变化趋势影响更大.(4)人类活动在大部分区域呈负影响,存在西北向东南负面影响增强的空间分布特征,但2000年前后人类活动对生产力变化趋势呈负影响的面积从79.12％降低到56.34％,NPP变化量从-71.41 Tg C降低到-38.72 Tg C,作为主导因子的变化范围从18.73％增加至38.76％,三江源地区生态保护与恢复等措施促进了植被生产力增加,但需进一步实施生态保护与恢复措施,这是一项长期而艰巨的任务.

Widespread concern about ecological degradation has prompted development of concepts and exploration of methods to quantify ecological quality with the aim of measuring ecosystem changes to contribute to future policy-making. This paper proposes a conceptual framework for ecological quality measurement based on current ecosystem functions and biodiverse habitat, compared with pixel-scale historical baselines. The framework was applied to evaluate the changes and driving factors of ecological quality for Chinese terrestrial ecosystems through remote sensing-based and ecosystem process modeled data at 1 km spatial resolution from 2000 to 2018. The results demonstrated the ecological quality index (EQI) had a very different spatial pattern based upon vegetation distribution. An upward trend in EQI was found over most areas, and variability of 46.95% in EQI can be explained well by change in climate, with an additional 10.64% explained by changing human activities, quantified by population density. This study demonstrated a practical and objective approach for quantifying and assessing ecological quality, which has application potential in ecosystem assessments on scales from local to region and nation, yet would provide a new scientific concept and paradigm for macro ecosystems management and decision-making by governments.

Evapotranspiration (ET) is a fundamental flux in land surface hydrothermal process. Because of the differences in basic concepts, assumptions, application scales, different models have induced varying uncertainties to the estimation and simulation of evapotranspiration. With the Three-River-Source National Park as an example, we used the Bayesian model averaging (BMA) method to integrate the ET estimations from five models of PT-JPL, ARTS-GIMMS3, ARTS-MODIS, MODIS global evapotranspiration product (MOD16), and SSEBop, and tried to improve the estimating accuracy of evapotranspiration. The results showed that the five models could well capture the seasonal variations in evapotranspiration at Haibei Flux Station, with an explanation range of 64%-86% variability in the observed ET, and a root means square deviation (RMSD) ranged from 0.47 mm·(8 d)-1 to 0.76 mm·(8 d)-1. BMA-based ET greatly improved its explanation to 89% and decreased the RMSD to 0.43 mm·(8 d)-1. The Three-River-Source National Park experienced an overall insignificant increasing trend in its inter-annual ET from 2003 to 2015. At the regional scale, the effects of temperature and precipitation on evapotranspiration were not significant, but were significant in the Yangtze River Source Park. Temperature and precipitation had positive impacts on evapotranspiration. The evapotranspiration showed different trends due to the geographi-cal differences between parks. This study provided a method reference for other multi-source data integration analysis. The integrated evapotranspiration data could effectively reduce the uncertainty of the original models and provide a more accurate data basis for the study of regional water heat change, which is of great significance to better understand water cycle under climate changes.

Monitoring and evaluating ecological quality and changes are crucial for policy formulation to guide ecosystem management and socioeconomic sustainable development. However, evaluation of ecological quality is still very challenging due to difficulties in determination of its associated indicators and weights. This paper proposes supporting, providing and regulating ecosystems services-based indicators to describe ecological quality, and applies a Projection Pursuit Model to eliminate redundant indicators and objectively determine weights for an ecological quality index (EQI) on a regional scale. Taking Jiangxi Province, China, as a demonstration area, the data for indicator measures were retrieved from satellite remote sensing and ecosystem modelling with a spatial resolution of 1 km for the three years 2005, 2010 and 2015. The results suggest that Normalized Difference Vegetation Index (NDVI) and water use efficiency (WUE) should be weighed higher and leaf area index (LAI) and Bowen ratio should be weighed lowest in the calculation of an EQI for Jiangxi Province. For 2015, the regional EQI was calculated to be 55.32 on a scale from 0 as the worst to 100 as the best, with higher values ascribed to the hills and mountains and the lower values existing near urban areas. The EQI increased from 52.26 in 2005 to 55.32 in 2015 with an increased area of good-and-above grade from 25.47% to 36.8% for the whole province. The changes in EQI could be attributed to a warmer and wetter climate trend playing a positive dominant effect, while urbanization and afforestation have negative and positive effects, respectively. This study demonstrates that it is feasible to evaluate ecological quality based on a comprehensive set of indicators and PPM-based weight determination, which could be further applied in regular ecological quality monitoring and evaluation on the regional, or even the national scale.

Abstract: As a material carrier contributing to human survival and social sustainable development, the ecological environment is declining in its integrity and overall health. With the rapid development of society and economy, it is currently very necessary to carry out ecological security evaluation research to provide scientific guidance and suggestions for the construction of ecological civilization and the harmonious co-existence between man and nature. Taking Altay region as the research area, this paper collected and integrated regional geological, geographical, cultural, socio-economic, and statistical data, as well as previous research results. Combined with DPSIR and EES framework model, the evaluation index system of land resource ecological security in Altay region was constructed by using the analytic hierarchy process, entropy method and linear weighted summation function method. Using this index system, the evaluation research work was carried out to determine the current state of the security situation and the major threats which should be addressed. (1) The overall ecological security situation of Altay region was relatively safe, while the local ecological security situation was relatively fragile. Among them, the areas with safe and safer ecological environment accounted for 38.72%, while the areas with critically safe status accounted for 30.83%, and the areas with a less safe and unsafe environment accounted for 30.45%. In terms of spatial characteristics, the areas with unsafe ecological environment were mainly distributed in the west and east of the study area, while the areas with good ecological environment were distributed in the north of the study area. (2) Large-scale mining activities, frequent geological disasters, large-scale reclamation and long-term cultivation of arable land, and long-term large-scale grazing activities resulting in the destruction of grassland and vegetation were the main factors leading to the prominent ecological security problems of land resources in the Altay region. Therefore, in the process of the continuous development of the urban economy, we should pay more attention to the harmony between man and nature, and also actively and effectively advocate and implement certain policies and measures, such as returning farmland to forest, returning grazing land to grassland and integrating the mining of mineral resources.

Data and knowledge of the spatial-temporal dynamics of surface water area (SWA) and terrestrial water storage (TWS) in China are critical for sustainable management of water resources but remain very limited. Here we report annual maps of surface water bodies in China during 1989-2016 at 30m spatial resolution. We find that SWA decreases in water-poor northern China but increases in water-rich southern China during 1989-2016. Our results also reveal the spatial-temporal divergence and consistency between TWS and SWA during 2002-2016. In North China, extensive and continued losses of TWS, together with small to moderate changes of SWA, indicate long-term water stress in the region. Approximately 569 million people live in those areas with deceasing SWA or TWS trends in 2015. Our data set and the findings from this study could be used to support the government and the public to address increasing challenges of water resources and security in China. The authors of this study compile data on spatial and temporal dynamics of surface water bodies across China, covering a time span from 1989 - 2016. The study describes hot-spot areas with strongly decreasing trends in surface water area and terrestrial water storage in North China and discusses implications of water resources and security in China.

How vegetation phenology responds to climate change is a key to the understanding of the mechanisms driving historic and future changes in regional terrestrial ecosystem productivity. Based on the 250-m and 8-day moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data for 2000–2014 in the Three-River Source Region (TRSR) of Qinghai Province, China, i.e., the hinterland of the Tibetan Plateau, we extracted relevant vegetation phenological information (e.g., start, end, and length of growing season) and analyzed the changes in the TRSR vegetation in response to climate change. The results reveal that, under the increasingly warm and humid climate, the start of vegetation growing season (SOS) advanced 1.03 day yr−1 while the end of vegetation growing season (EOS) exhibited no significant changes, which led to extended growing season length. It is found that the SOS was greatly affected by the preceding winter precipitation, with progressively enhanced precipitation facilitating an earlier SOS. Moreover, as the variations of SOS and its trend depended strongly on topography, we estimated the elevation break-points for SOS. The lower the elevations were, the earlier the SOS started. In the areas below 3095-m elevation, the SOS delay changed rapidly with increasing elevation; whereas above that, the SOS changes were relatively minor. The SOS trend had three elevation break-points at 2660, 3880, and 5240 m.

In this study, the Weather Research and Forecasting model was coupled with an improved Noah land surface model (WRF-Noah) where dynamic flood and drip irrigation processes were implemented firstly. We simulated the different irrigation effects on surface water-heat processes in a typical mountain-oasis-desert system in Central Asia for both wet and drought years, respectively, using the modified WRF-Noah. The modified WRF-Noah model can dynamically generate amounts of irrigation in agreement with actual values. The statistically significant decrease in the root mean square error and increase in the Pearson correlation coefficient for the 2-m temperature (T2), relative humidity (RH), latent heat flux (LE), and precipitation suggest that the modified WRF-Noah model was improved by implementing irrigation processes. During the irrigation season, flood and drip irrigation decreased the average sensible heat flux by -80.69 and -50.50 W/m(2) and T2 by 1.09 and 0.82 degrees C over the irrigated area and increased LE by 88.47 and 66.70 W/m(2) and RH by 6.23% and 4.65%, respectively. Throughout the domain, flood irrigation had equivalent or slightly weaker effects on near-surface temperature and humidity due to the smaller irrigated area. Both flood and drip irrigation increased precipitation throughout the domain, especially in the mountainous area, thereby accelerating the hydrological cycle in the mountain-oasis-desert system. The local oasis breeze circulation that plays a role in maintaining the oasis stability is still counteracted by the dominant background circulation even with irrigation processes. Thus, more effort should be exerted to maintain the future sustainability of the oasis.