Response of evapotranspiration to changes in land use and land cover and climate in China during 2001-2013

Decoupling the response of vegetation dynamics to asymmetric warming over the Qinghai-Tibet plateau from 2001 to 2020

Global land surface air temperature data show that in the past 50 years, the rate of nighttime warming has been much faster than that of daytime, with the minimum daily temperature (Tmin) increasing about 40% faster than the maximum daily temperature (Tmax), resulting in a decreased diurnal temperature difference. The Qinghai-Tibet Plateau (QTP) is known as the "roof of the world", where temperatures have risen twice as fast as the global average warming rate in the last few decades. The factors affecting vegetation growth on the QTP are complex and still not fully understood to some extent. Previous studies paid less attention to the explanations of the complicated interactions and pathways between elements that influence vegetation growth, such as climate (especially asymmetric warming) and topography. In this study, we characterized the spatial and temporal trends of vegetation coverage and investigated the response of vegetation dynamics to asymmetric warming and topography in the QTP during 2001-2020 using trend analysis, partial correlation analysis, and partial least squares structural equation model (PLS-SEM) analysis. We found that from 2001 to 2020, the entire QTP demonstrated a greening trend in the growing season (April to October) at a rate of 0.0006/a (p < 0.05). The spatial distribution pattern of partial correlation between NDVI and Tmax differed from that of NDVI and Tmin. PLS-SEM results indicated that asymmetric warming (both Tmax and Tmin) had a consistent effect on vegetation development by directly promoting greening in the QTP, with NDVI values being more sensitive to Tmin, while topographic factors, especially elevation, mainly played an indirect role in influencing vegetation growth by affecting climate change. This study offers new insights into how vegetation responds to asymmetric warming and references for local ecological preservation.

Novel spatial models for analysis the long-term impact of LULC changes on hydrological components at sub-basin level

The main objective of this research is to assess the impacts land use and land cover changes (LULC) on hydrological components using novel spatial models at sub-basin scales. The Soil and Water Assessment Tool (SWAT) was employed to analyze the long-term effect of LULC on hydrological components. The results of the calibrated and validated SWAT model demonstrated that run-off and actual evapotranspiration (ET) are expected to experience the largest increase, more than 130% and 90% in autumn, whereas the largest decrease is anticipated to occur in the summer and winter for potential evapotranspiration (PET) (-59%) and ET (-80%) by the projected time. The impacts of hydrological components, elevation, LULC, and an indicator of urbanization and land-use intensity (La) on water yield (WYLD) at sub-basin levels were then considered by four novel spatial models due to the problem of multicollinearity which is prevalent in traditional models. In particular, the Moran eigenvector spatially varying coefficients (MESVC) showed that the soil class out of LULC categories and lateral flow among hydrological properties are expected to have a statistically significant effect on spatial fluctuation of WYLD at the sub-basin scale. The results of spatially filtered unconditional quantile regression (SF-UQR) confirm the findings of the MESVC model and further implied that the lateral flow remains as a statistically significant contributor to WYLD only in lower quantiles (e.g., for quantiles lower than 0.25). The impacts of LULCs on WYLD were statistically lower than the effects caused by the hydrological components.

Estimation of evapotranspiration in constructed wetlands under diverse climatic conditions

Constructed wetlands as a form of phytoremediation have proven to be an effective wastewater treatment method. It is a simple, economical, and environmentally friendly method compared to conventional wastewater treatments. In addition to wastewater treatment, constructed wetlands have been used to study hydrometeorological parameters such as evaporation in the vicinity, evapotranspiration (ET), and wastewater loss at a constructed wetland pilot plant at the Uttarakhand Jal Nigam sewage treatment plant at Haridwar. The relation between standard pan evaporation (PE) and ET occurring at the surface of a wetland bed was established at the constructed wetland site. To make the process of measuring ET easier, the relation between PE and ET has been established by the equation [Formula: see text]. The percent loss of water through ET vis-à-vis PE during the summer, post-monsoon, and winter seasons has been estimated to be 21.6%, 6.47%, and 1.16%, respectively. The quantity of wastewater lost in the summer, post-monsoon, and winter seasons was 53.06 m³, 13.87 m³, and 2.79 m³, respectively. The total annual wastewater loss through the pilot-scale constructed wetlands was 69.72 m³. The loss of wastewater per square meter of the planned area of constructed wetland in the temperate zone was estimated as 3.46 m³ per m² of constructed wetland. ET through wetlands enhanced the circulation of water in the hydrological cycle; therefore, this treatment has been proven to be an environmentally friendly method of wastewater treatment.

Actual evapotranspiration by machine learning and remote sensing without the thermal spectrum

The objectives of this study were to use machine learning algorithms to establish a model for estimating the evapotranspiration fraction (ETf) using two data input scenarios from the spectral information of the Sentinel-2 constellation, and to analyze the temporal and spatial applicability of the models to estimate the actual evapotranspiration (ETr) in agricultural crops irrigated by center pivots. The spectral bands of Sentinel 2A and 2B satellite and vegetation indices formed the first scenario. The second scenario was formed by performing the normalized ratio procedure between bands (NRPB) and joining the variables applied in the first scenario. The models were generated to predict the ETf using six regression algorithms and then compared with ETf calculated by the Simple Algorithm For Evapotranspiration Retrieving (SAFER) algorithm, was considered as the standard. The results possible to select the best model, which in both scenarios was Cubist. Subsequently, ETf was estimated only for the center pivots present in the study area and the classification of land use and cover was accessed through the MapBiomas product. Land use was necessary to enable the calculation of ETr in each scenario, in the center pivots with sugarcane and soybean crops. ETr was estimated using two ETo approaches (EToBrazil and Hargreaves-Samani). It was found that the Hargreaves-Samani equation overestimated ETr with higher errors mainly for center pivots with sugarcane, where systematic error (MBE) ranged from 0.89 to 2.02 mm d-1. The EToBrazil product, on the other hand, presented statistical errors with MBE values ranging from 0.00 to 1.26 mm d-1 for both agricultural crops. Based on the results obtained, it is observed that the ETr can be monitored spatially and temporally without the use of the thermal band, which causes the estimation of this parameter to be performed with greater temporal frequency.

Integrating the Budyko framework with the emerging hot spot analysis in local land use planning for regulating surface evapotranspiration ratio

Land use planning regulates surface hydrological processes by adjusting land properties with varied evapotranspiration ratios. However, a dearth of empirical spatial information hampers the regulation of place-specific hydrological processes. Therefore, this study proposed a Local Land Use Planning framework for EvapoTranspiration Ratio regulations (ETR-LLUP), which was tested for the developments of spatially-varied land use strategies in the Dongjiang River Basin (DRB) in Southern China. With the first attempt at integrating the Emerging Hot Spots Analysis (EHSA) with the Budyko framework, the spatiotemporal trends of evapotranspiration ratios based on evaporative index and dryness index, from 1992 to 2018, were illustrated. Then, representative land-cover types in each sub-basin were defined using Geographically Weighted Principal Component Analysis, in two wet years (1998 and 2016) and three dry years (2004, 2009, and 2018), which in turn were identified using the Standard Precipitation Index. Finally, Geographically Weighted Regressions (GWRs) were used to detect spatially-varied relationships between land-cover proportions and evaporative index in both dry and wet climates. Results showed that the DRB was consistently a water-limited region from 1992 to 2018, and the situation was getting worse. We also identified the upper DRB as hotspots for hydrological management. Forests and croplands experienced increasingly water stress compared to other vegetation types. More importantly, the spatial results of GWR models enabled us to adjust basin land use by 1) expanding and contracting a combination of 'mosaic natural vegetation' and 'broadleaved deciduous trees' in the western and eastern parts of the basin, respectively; and 2) increasing 'broadleaved evergreen trees' in the upstream parts of the basin. These spatially-varied land use strategies based on the ETR-LLUP framework allow for place-specific hydrological management during both dry and wet climates.

A coupled modeling approach to assess the effect of forest policies in water provision: A biophysical evaluation of a drought-prone rural catchment in south-central Chile

The effect of different forest conservation policies on water provision has been poorly investigated due to a lack of an integrative methodological framework that enables its quantification. We developed a method for assessing the effects of forest conservation policies on water provision for rural inhabitants, based on a land-use model coupled with an eco-hydrological model. We used as a case study the Lumaco catchment, Chile, a territory dominated by native forests (NF) and non-native tree farms, with an extended dry period where nearly 12,600 people of rural communities get drinking water through water trucks. We analyzed three land-use policy scenarios: i) a baseline scenario based on historical land-cover maps; ii) a NF Recovery and Protection (NFRP) scenario, based on an earlier implementation of the first NF Recovery and Forestry Development bill; and iii) a Pristine (PR) scenario, based on potential vegetation belts; the latter two based on Dyna CLUE, and simulated between 1990 and 2015. Impacts on water provision from each scenario were computed with SWAT. The NFRP scenario resulted in an increase of 6974 ha of NF regarding the baseline situation, and the PR scenario showed an increase of 26,939 ha of NF. Despite large differences in NF areas, slight increases in inflows (Q) were found between the NFRP and the PR scenarios, with relative differences with respect to the baseline of 0.3% and 2.5% for NFRP and PR, respectively. Notwithstanding, these small differences in the NFRP scenario, they become larger if we analyze the cumulative values during the dry season only (December, January, and February), where they reach 1.1% in a normal year and 3.1% in a dry year. Flows increases were transformed into water truck costs resulting in up to 441,876 USD (monthly) of fiscal spending that could be avoided during a dry period.

Different Vegetation Information Inputs Significantly Affect the Evapotranspiration Simulations of the PT-JPL Model

Evapotranspiration (ET) is an essential part of the global water cycle, and accurate quantification of ET is of great significance for hydrological research and practice. The Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model is a commonly used remotely sensed (RS) ET model. The original PT-JPL model includes multiple vegetation variables but only requires the Normalized Difference Vegetation Index (NDVI) as the vegetation input. Other vegetation inputs (e.g., Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)) are estimated by the NDVI-based empirical methods. Here we investigate whether introducing more RS vegetation variables beyond NDVI can improve the PT-JPL model’s performance. We combine the vegetation variables derived from RS and empirical methods into four vegetation input schemes for the PT-JPL model. The model performance under four schemes is evaluated at the site scale with the eddy covariance (EC)-based ET measurements and at the basin scale with the water balance-based ET estimates. The results show that the vegetation variables derived by RS and empirical methods are quite different. The ecophysiological constraints of the PT-JPL model constructed by the former are more reasonable in spatial distribution than those constructed by the latter. However, as vegetation input of the PT-JPL model, the scheme derived from empirical methods performs best among the four schemes. In other words, introducing more remotely sensed vegetation variables beyond NDVI into the PT-JPL model degrades the model performance to varying degrees. One possible reason for this is the unrealistic ET partitioning. It is necessary to re-parameterize the biophysical constraints of the PT-JPL model to ensure that the model obtains reasonable internal process simulations, that is, “getting the right results for right reasons.”

Impact of Climate Change and Rubber (Hevea brasiliensis) Plantation Expansion on Reference Evapotranspiration in Xishuangbanna, Southwest China

The expansion of rubber (Hevea brasiliensis) cultivation plantation over the past few decades has been significantly explosive in Xishuangbanna, southwest China. More and more evidences concerning the expansion of rubber plantations lead to the negative influence to local regional hydrology. It is vital to explore the impact of climate change and rubber (Hevea brasiliensis) plantation expansion on reference evapotranspiration (ET₀) for the sustainable and efficient use of regional water resources. In this study, the spatiotemporal variation of ET0 as well as its relationship in rubber plantations area in Xishuangbanna from 1970-2017 were analyzed by using trend, correlation and contribution analysis. The results showed that the rubber plantation was 12,768 ha yr^-1 from 1990 to 2017 in Xishuangbanna, and nearly 40.8% of new rubber plantations expanded above 900 m in altitude from 2000 to 2017. Sunshine duration and average relative humidity were the key meteorological factors that affect ET₀ in Xishuangbanna, with the sensitivity coefficient of 0.51 and 0.35, respectively. The multiyear relative change of ET₀ in Xishuangbanna was 9.18%, and the total contribution of major climate factors was 7.87% during 1970 and 2017. The average relative humidity in the plantation area decreases, which directly leads to the increase of ET₀. The amount of ET₀ change from 2000 to 2017 affected by climate change increased at 3.13 mm/10a, whereas it was 2.17 mm/10a affected by the expansion of rubber plantations by quantitative separation. ET₀ was significantly affected by climate change but intensified by the expansion of rubber plantation.

Intra-Annual Variability of Evapotranspiration in Response to Climate and Vegetation Change across the Poyang Lake Basin, China

Improving understanding of changes in intra-annual variability (IAV) of evapotranspiration (ET) and the underlying drivers is an essential step for modeling hydrological processes in response to global change. Previous studies paid special attention to climatic regulations of IAV of ET. However, ignoring the role of landscape characteristics (e.g., vegetation coverage) can introduce great uncertainty in the explanation of ET variance. In this work, the Poyang Lake Basin, which is a typical humid basin in China, was taken as the study area. It has experienced an obvious climate change and revegetation since the 1980s. Here, trends of IAV of ET and their responses to four climatic variables (i.e., air temperature, precipitation, downward shortwave radiation and wind speed) and vegetation coverage were explored from 1983 to 2014. The results show that IAV of ET exhibited contrary trends during the past decades. It significantly (p < 0.05) declined with a significant linear slope of −0.52 mm/year before 2000, and then slightly increased (slope = 0.06 mm/year, p > 0.05) over the basin, which was generally consistent with the IAV of temperature and radiation. The proposed variables could well capture the change in IAV of ET, while their dominators were different during the two contrasting phases mentioned above. The IAV of radiation and temperature dominated the change of the IAV of ET over 77.82% and 35.14% of the basin, respectively, before and after the turning point. Meanwhile, the rapid increase in vegetation coverage, which was associated with afforestation, significantly (p < 0.05) reduced IAV of ET over about 35% of the study area. The achievements of this study should be beneficial for a sophisticated awareness of responses of intra-annual variability of ET to climate and land cover changes at the basin scale.

Attributing the Evapotranspiration Trend in the Upper and Middle Reaches of Yellow River Basin Using Global Evapotranspiration Products

Climate variation and underlying surface dynamics have caused a significant change in the trend of evapotranspiration (ET) in the Yellow River Basin (YRB) over the last two decades. Combined with the measured rainfall, runoff and gravity recovery and climate experiment (GRACE) product, five global ET products were firstly merged using a linear weighting method. Linear slope, “two-step” multiple regression, partial differential, and residual methods were then employed to explore the quantitative impacts of precipitation (PCPN), temperature (Temp), sunshine duration (SD), vapor pressure deficit (VPD), wind speed (WS), leaf area index (LAI), and the residual factors (e.g., microtopography changes, irrigation, etc.) on the ET trend in the YRB. The results show that: (1) The ET estimates were improved by merging five global ET products using the linear weighting method. The sensitivities of climatic factors and LAI on the ET trend can be separately calculated using proposed “two-step” statistical regression method; (2) the overall ET trend in the entire study area during 2000–2018 was 3.82 mm/yr, and the highest ET trend was observed in the Toudaoguai-Longmen subregion. ET trend was dominantly driven by vegetation greening, with an impact of 2.47 mm/yr and a relative impact rate of 51.16%. The results indicated that the relative impact rate of the residual factors (e.g., microtopography, irrigation, etc.) on the ET trend is up to 28.17%. The PCPN and VPD had increasing roles on the ET trend, with impacts of 0.45 mm/yr and 0.05 mm/yr, respectively, whereas the Temp, SD, and WS had decreasing impacts of –0.19 mm/yr, –0.15 mm/yr, and –0.17 mm/yr, respectively. (3) The spatial pattern of impact of specific influencing factor on the ET trend was determined by the spatial pattern of change trend slope of this factor and sensitivity of ET to this factor. ET trends of the source area and the Qingtongxia–Toudaoguai were dominated by the climatic factors, while the residual factors dominated the ET trend in the Tangnaihai–Qingtongxia area. The vegetation restoration was the dominant factor causing the increase in the ET in the middle reaches of the YRB, and the impact rates of the LAI were ranked as follows: Yanhe Rive > Wudinghe River > Fenhe River > Jinghe River > Beiluohe River > Qinhe River > Kuyehe River > Yiluohe River.

Twenty years of change: Land and water resources in the Chindwin catchment, Myanmar between 1999 and 2019

Since 2011, Myanmar has undergone a more rapid socio-economic development, which may substantially have affected land use and land cover (LULC) and water resources. This study investigates the changes in land and water resources of the Chindwin River catchment (114,686.9 km²) in Myanmar over a twenty-year timespan from 1999 to 2019. The main aim of this study is to assess LULC change and evaluate its effects on the water balance and the people in the region. To this end, interviews were conducted, LULC classifications based on multi-temporal multi-spectral satellite data and in-situ ground truth data were created, and a hydrologic model was built. The hydrologic model shows a reasonable performance for daily discharge simulation at the catchment outlet (percent bias between -2 and 13.2, Kling-Gupta Efficiency between 0.75 and 0.76, Nash-Sutcliffe Efficiency between 0.57 and 0.61, RMSE-observations standard deviation between 0.63 and 0.66). The LULC changes detected include a decrease in forest area of about 2%, an increase in shrubland area indicating increased degradation of the forest, an increase in mining areas of 0.38%, an overall decrease in agricultural area (2.1%), but also the presence of new agricultural land pointing toward relocation of agricultural areas and an indication of an increase in settlement areas (1.5%). With the help of the hydrologic model, the most significant hydrologic impacts detected were a decrease in evapotranspiration and an increase in water yield which is correlated with the decrease of forest at the sub-catchment scale (R² = 0.72 and 0.46, respectively). Moreover, an increase of mining areas contributed to the increase in water yield (R² = 0.62). Interviews confirm that the identified LULC changes deforestation and increased mining activities contribute to major issues, e.g., water pollution, sedimentation, and changes in the river course.

Climatic and landscape changes as drivers of environmental feedback that influence rainfall frequency in the United States

Previous studies have identified regions where the occurrence of rainfall significantly increases or decreases the probability for subsequent rainfall over periods that range from a few days to several weeks. These observable phenomena are termed "rainfall feedback" (RF). To better understand the land-atmosphere interactions involved in RF, the behavior of RF patterns was analyzed using data from 1849 to 2016 at ~3000 sites in the contiguous United States. We also considered changes in major land-use types and applied a geographically weighted regression model technique for analyzing the predictors of RF. This approach identified non-linear and spatially non-stationary relationships between RF, climate, land use, and land type. RF patterns in certain regions of the United States are predictable by modeling variables associated with climate, season, and land use. The model outputs also demonstrate the extent to which the effect of precipitation, temperature, and land use on RF depend on season and location. Specifically, major changes were observed for land use associated with agriculture in the western United States, which had negative and positive influences on RF in summer and winter, respectively. In contrast, developed land in the eastern United States correlated with positive RF values in summer but with negative ones in winter. We discuss how changes in climate and land use would be expected to affect land-atmosphere interactions, as well as the possible role that physical mechanisms and rain-enhanced bioaerosol emissions may play in the spatiotemporal changes observed for historical patterns of rainfall frequency in the United States.

Determining the Contributions of Vegetation and Climate Change to Ecosystem WUE Variation over the Last Two Decades on the Loess Plateau, China

Exploring the variations in the water use efficiency (WUE) is helpful in gaining an in-depth understanding of the regional carbon and water cycles on the Chinese Loess Plateau (CLP). Here, we employed the spatial variations in the WUE and the quantitative contributions of the influencing factors, including the precipitation (P), temperature (Temp), vapor pressure deficit (VPD), sunshine duration (SD), and leaf area index (LAI), with the drought index varying over the last two decades. Results showed that the multiyear average WUE decreased significantly as the drought index increased for all of the vegetation types. Per-pixel interannual variability of WUE trend was 0.024 gC·m−2·mm−1·year−1. As the drought index increased, the WUE initially increased and then decreased for the forests, grassland, and shrubland, and their peaks occurred at drought index values of 2.60–3.10. Among the influencing factors, the WUE was predominantly controlled by the LAI, with an impact and relative contribution of 0.014 gC·m−2·mm−1·year−1 and 58.3%, respectively. The P and SD contributed the least to the trend in WUE, and impact and relative contribution of both were 0.001 gC·m−2·mm−1·year−1 and 4.17%. Our study also demonstrated that the LAI was the dominant factor affecting the WUE trends for grassland and the Yan River due to the structural parameters and geographical location. In addition, the impact and relative contribution of the residual factors on the WUE trend were 0.004 gC·m−2·mm−1·year−1 and 16.7%. Our findings suggested that comprehensive effects such as micro-geomorphic changes and nitrogen deposition could not be ignored except for vegetation and climate change. This study will clarify the spatial and temporal evolution of WUE and its influence mechanism.

Identification of the Dominant Factors in Groundwater Recharge Process, Using Multivariate Statistical Approaches in a Semi-Arid Region

Identifying contributing factors of potential recharge zones is essential for sustainable groundwater resources management in arid regions. In this study, a data matrix with 66 observations of climatic, hydrogeological, morphological, and land use variables was analyzed. The dominant factors in groundwater recharge process and potential recharge zones were evaluated using K-means clustering, principal component analysis (PCA), and geostatistical analysis. The study highlights the importance of multivariate methods coupled with geospatial analysis to identify the main factors contributing to recharge processes and delineate potential groundwater recharge areas. Potential recharge zones were defined into cluster 1 and cluster 3; these were classified as low potential for recharge. Cluster 2 was classified with high potential for groundwater recharge. Cluster 1 is located on a flat land surface with nearby faults and it is mostly composed of ignimbrites and volcanic rocks of low hydraulic conductivity (K). Cluster 2 is located on a flat lowland agricultural area, and it is mainly composed of alluvium that contributes to a higher hydraulic conductivity. Cluster 3 is located on steep slopes with nearby faults and is formed of rhyolite and ignimbrite with interbedded layers of volcanic rocks of low hydraulic conductivity. PCA disclosed that groundwater recharge processes are controlled by geology, K, temperature, precipitation, potential evapotranspiration (PET), humidity, and land use. Infiltration processes are restricted by low hydraulic conductivity, as well as ignimbrites and volcanic rocks of low porosity. This study demonstrates that given the climatic and geological conditions found in the Sierra de San Miguelito Volcanic Complex (SSMVC), this region is not working optimally as a water recharge zone towards the deep aquifer of the San Luis Potosí Valley (SLPV). This methodology will be useful for water resource managers to develop strategies to identify and define priority recharge areas with greater certainty.

Projections of desertification trends in Central Asia under global warming scenarios

Central Asia (CA) is a core area of global desertification, but the effect of the intensifying "global greening" policy on the desertification process under global warming scenarios in CA remains unclear. Based on multi-source remote sensing data and Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) 2b climate data, this study investigated desertification in CA using actual evapotranspiration (ETa), temperature and precipitation as driving factors. Coupling with the CA-Markov model, the inversion method of desertification was improved, and the evolution normal form of desertification in CA was proposed. Finally, spatio-temporal variations of desertification in CA were quantified. The results indicate that temperature, precipitation, and normalized difference vegetation index (NDVI) in CA increased during the historical period (1980-2015), with sudden changes in 1994. In contrast, although ETa exhibited fluctuating increases (7.41 mm/10 yr) during this period, no sudden changes were observed in 1994. In the future (2006-2099), the climate of CA will become warmer and wetter. With reference to 1980-2005, precipitation under global warming of 2.0 °C (GW2.0) will be higher than that under global warming of 1.5 °C (GW1.5) by 10.3 mm, and ETa will increase by 20.88 mm and 27.54 mm under GW1.5 and GW2.0, respectively. Although the area of desert lands has decreased (5.94 × 10⁴ km²/10 yr), the area of potential desert lands has increased (0.17 × 10⁴ km²/10 yr). With global warming, this situation will continue to intensify, mainly in Xinjiang of China, and Kazakhstan. The Aral Sea plays an important role in the desertification of CA. The potential increase in desert land under GW2.0 is equivalent to the current water area of the Aral Sea. The findings could provide policy support for combating desertification in CA and promoting the achievement of the Sustainable Development Goals.

Quantifying the Responses of Evapotranspiration and Its Components to Vegetation Restoration and Climate Change on the Loess Plateau of China

Quantitatively identifying the influences of vegetation restoration (VR) on water resources is crucial to ecological planning. Although vegetation coverage has improved on the Loess Plateau (LP) of China since the implementation of VR policy, the way vegetation dynamics influences regional evapotranspiration (ET) remains controversial. In this study, we first investigate long-term spatiotemporal trends of total ET (TET) components, including ground evaporation (GE) and canopy ET (CET, sum of canopy interception and canopy transpiration) based on the GLEAM-ET dataset. The ET changes are attributed to VR on the LP from 2000 to 2015 and these results are quantitatively evaluated here using the Community Land Model (CLM). Finally, the relative contributions of VR and climate change to ET are identified by combining climate scenarios and VR scenarios. The results show that the positive effect of VR on CET is offset by the negative effect of VR on GE, which results in a weak variation in TET at an annual scale and an increased TET is only shown in summer. Regardless of the representative concentration pathway (RCP4.5 or RCP8.5), differences resulted from the responses of TET to different vegetation conditions ranging from −3.7 to −1.2 mm, while climate change from RCP4.5 to RCP8.5 caused an increase in TET ranging from 0.1 to 65.3 mm. These findings imply that climate change might play a dominant role in ET variability on the LP, and this work emphasizes the importance of comprehensively considering the interactions among climate factors to assess the relative contributions of VR and climate change to ET.

Estimating the spatial distribution of evapotranspiration within the Pra River Basin of Ghana

It is important in water resource planning to accurately estimate the spatial distribution of evapotranspiration (ET) as an input parameter for hydrological studies. Although, conventional pan evaporation, lysimetric and eddy covariance techniques have been used, they only estimate point values. Hence, this study aimed at estimating the spatial distribution of ET within the Pra River Basin (a forest ecological zone) of Ghana, using cloud-free Landsat 8 (OLI/TIRS) satellite images employing the SEBAL methodology. The study further estimates the spatial distribution ET in relation to major climatic variables, Land Use Land Cover (LULC) types and energy balance components. The overall spatial distribution of ET had a mean value of 5.63 mm/day. Spatial distribution of ET (mm/day) for water body (5.51–7.81) and uncultivated forest (5.10–7.71) were high, while moderately average values were observed for logged forest (4.80–7.51). Settlement and bare landscapes observed low rates ((2.05–5.10) mm/day). Spatially, ET was higher in the upper western, central and the eastern parts of the basin, but lower in the northern part and pockets of areas at the southern part of the basin where settlement/bare landscape and logged forest dominate. Areas with high temperature and high solar radiation experiences high ET, while low wind speed, low to average temperature and solar radiation areas experience low ET. Also, areas with both high net radiation and ground heat flux but low to average sensible heat flux experiences high ET and vice versa. Linear regression analysis showed good fit with slope of 0.76 and R² of 0.93 indicating that 93 % of the variations in observed field measurement of ET fitted perfectly well with ET distributions generated by the SEBAL model.

An Improved Index for Urban Population Distribution Mapping Based on Nighttime Lights (DMSP-OLS) Data: An Experiment in Riyadh Province, Saudi Arabia

Knowledge of the spatial pattern of the population is important. Census population data provide insufficient spatial information because they are released only for large geographic areas. Nighttime light (NTL) data have been utilized widely as an effective proxy for population mapping. However, the well-reported challenges of pixel overglow and saturation influence the applicability of the Defense Meteorological Program Operational Line-Scan System (DMSP-OLS) for accurate population mapping. This paper integrates three remotely sensed information sources, DMSP-OLS, vegetation, and bare land areas, to develop a novel index called the Vegetation-Bare Adjusted NTL Index (VBANTLI) to overcome the uncertainties in the DMSP-OLS data. The VBANTLI was applied to Riyadh province to downscale governorate-level census population for 2004 and 2010 to a gridded surface of 1 km resolution. The experimental results confirmed that the VBANTLI significantly reduced the overglow and saturation effects compared to widely applied indices such as the Human Settlement Index (HSI), Vegetation Adjusted Normalized Urban Index (VANUI), and radiance-calibrated NTL (RCNTL). The correlation coefficient between the census population and the RCNTL (R = 0.99) and VBANTLI (R = 0.98) was larger than for the HSI (R = 0.14) and VANUI (R = 0.81) products. In addition, Model 5 (VBANTLI) was the most accurate model with R2 and mean relative error (MRE) values of 0.95% and 37%, respectively.

An analytical reductionist framework to separate the effects of climate change and human activities on variation in water use efficiency

Ecosystem water use efficiency (WUE) is a key indicator that depicts the carbon-water coupling relationship in terrestrial ecosystems. Separating the effects of climate change and human activities to the variation in WUE are essential for water resources and ecosystem management, especially for fragile ecosystems such as the Tibetan Plateau (TP). In this study, we introduced an analytical framework that combined the attribution approach with the elastic coefficient separation method to assess the impact of climate change and human activities on WUE variation in the TP from 1982 to 2015. The results are the following: (1) the multiyear mean annual WUE over the TP was 0.65 g C·kg^-1 H₂O and had a slightly increasing trend with a slope of 0.004 g C·kg^-1 H₂O yr^-1 with about 87% of the vegetated area showed increasing trend. (2) WUE was positively correlated with temperature, precipitation and air pressure. The northwest TP tends to be a water-limited condition, while the thermal stress is spatially universal in the TP, climate warming and wetting promoted the gross primary productivity (GPP) and WUE enhancement in the TP. (3) WUE was more sensitive to GPP, and variation in WUE was mainly contributed by GPP. Climate change and human activities tend to cause more variations in GPP rather than evapotranspiration (ET), but great differences exist for different regions and vegetation types. (4) There was a good consistency between the WUE variation calculated by the framework and the actual WUE variation (R² = 0.95). Climate change dominated the increase of WUE in the TP with a contribution rate of 79.8%, while human activities tend to reduce WUE (-20.2%). Ecological projects played a positive role in the ecological restoration of the TP, but there may be other human activities, which caused ecological degradation, that may need more attention in future ecological protections.

Assessment and simulation of land use and land cover change impacts on the land surface temperature of Chaoyang District in Beijing, China

Rapid urbanization is changing the existing patterns of land use land cover (LULC) globally, which is consequently increasing the land surface temperature (LST) in many regions. The present study is focused on estimating current and simulating future LULC and LST trends in the urban environment of Chaoyang District, Beijing. Past patterns of LULC and LST were identified through the maximum likelihood classification (MLC) method and multispectral Landsat satellite images during the 1990–2018 data period. The cellular automata (CA) and stochastic transition matrix of the Markov model were applied to simulate future (2025) LULC and LST changes, respectively, using their past patterns. The CA model was validated for the simulated and estimated LULC for 1990–2018, with an overall Kappa (K) value of 0.83, using validation modules in IDRISI software. Our results indicated that the cumulative changes in built-up to vegetation area were 74.61 km2 (16.08%) and 113.13 km2 (24.38%) from 1990 to 2018. The correlation coefficient of land use and land cover change (LULCC), including vegetation, water bodies and built-up area, had values of r =  − 0.155 (p > 0.005), −0.809 (p = 0.000), and 0.519 (p > 0.005), respectively. The results of future analysis revealed that there will be an estimated 164.92 km2 (−12%) decrease in vegetation area, while an expansion of approximately 283.04 km2 (6% change) will occur in built-up areas from 1990 to 2025. This decrease in vegetation cover and expansion of settlements would likely cause a rise of approximately ∼10.74 °C and ∼12.66 °C in future temperature, which would cause a rise in temperature (2025). The analyses could open an avenue regarding how to manage urban land cover patterns to enhance the resilience of cities to climate warming. This study provides scientific insights for environmental development and sustainability through efficient and effective urban planning and management in Beijing and will also help strengthen other research related to the UHI phenomenon in other parts of the world.

Reference Evapotranspiration Modeling Using New Heuristic Methods

The study investigates the potential of two new machine learning methods, least-square support vector regression with a gravitational search algorithm (LSSVR-GSA) and the dynamic evolving neural-fuzzy inference system (DENFIS), for modeling reference evapotranspiration (ETo) using limited data. The results of the new methods are compared with the M5 model tree (M5RT) approach. Previous values of temperature data and extraterrestrial radiation information obtained from three stations, in China, are used as inputs to the models. The estimation exactness of the models is measured by three statistics: root mean square error, mean absolute error, and determination coefficient. According to the results, the temperature or extraterrestrial radiation-based LSSVR-GSA models perform superiorly to the DENFIS and M5RT models in terms of estimating monthly ETo. However, in some cases, a slight difference was found between the LSSVR-GSA and DENFIS methods. The results indicate that better prediction accuracy may be obtained using only extraterrestrial radiation information for all three methods. The prediction accuracy of the models is not generally improved by including periodicity information in the inputs. Using optimum air temperature and extraterrestrial radiation inputs together generally does not increase the accuracy of the applied methods in the estimation of monthly ETo.

The impact of increasing land productivity on groundwater dynamics: a case study of an oasis located at the edge of the Gobi Desert

BACKGROUND

Intensification of agricultural systems may result in overexploitation of water resources in arid regions because enhanced productivity of crops is often associated with increased actual evapotranspiration (AET). The aim of this study was to quantify the effect of increased regional AET on the groundwater level in a case study of the oasis located within the Shiyang River Basin near the edge of the Gobi Desert.

RESULT

The results of the study show that regional AET increased during the period from 1981 to 2010 due to increasing oasis area and air temperature. The water losses due to AET exceeded the water supply from the mountainous discharges of the basin by the end of this period, leading to groundwater overexploitation in the oasis area.

CONCLUSIONS

This case study shows the importance of considering the effect of climate change on water losses associated with increasing agricultural production for the sustainable agricultural development of arid regions.

Assessment of an Automated Calibration of the SEBAL Algorithm to Estimate Dry-Season Surface-Energy Partitioning in a Forest–Savanna Transition in Brazil

Evapotranspiration ( E T ) provides a strong connection between surface energy and hydrological cycles. Advancements in remote sensing techniques have increased our understanding of energy and terrestrial water balances as well as the interaction between surface and atmosphere over large areas. In this study, we computed surface energy fluxes using the Surface Energy Balance Algorithm for Land (SEBAL) algorithm and a simplified adaptation of the CIMEC (Calibration using Inverse Modeling at Extreme Conditions) process for automated endmember selection. Our main purpose was to assess and compare the accuracy of the automated calibration of the SEBAL algorithm using two different sources of meteorological input data (ground measurements from an eddy covariance flux tower and reanalysis data from Modern-Era Reanalysis for Research and Applications version 2 (MERRA-2)) to estimate the dry season partitioning of surface energy and water fluxes in a transitional area between tropical rainforest and savanna. The area is located in Brazil and is subject to deforestation and cropland expansion. The SEBAL estimates were validated using eddy covariance measurements (2004 to 2006) from the Large-Scale Biosphere-Atmosphere Experiment in the Amazon (LBA) at the Bananal Javaés (JAV) site. Results indicated a high accuracy for daily ET, using both ground measurements and MERRA-2 reanalysis, suggesting a low sensitivity to meteorological inputs. For daily ET estimates, we found a root mean square error (RMSE) of 0.35 mm day−1 for both observed and reanalysis meteorology using accurate quantiles for endmembers selection, yielding an error lower than 9% (RMSE compared to the average daily ET). Overall, the ET rates in forest areas were 4.2 mm day−1, while in grassland/pasture and agricultural areas we found average rates between 2.0 and 3.2 mm day−1, with significant changes in energy partitioning according to land cover. Thus, results are promising for the use of reanalysis data to estimate regional scale patterns of sensible heat (H) and latent heat (LE) fluxes, especially in areas subject to deforestation.

Monitoring land surface thermal environments under the background of landscape patterns in arid regions: A case study in Aksu river basin

Land surface temperature (LST) is defined as an important indicator in the formation and evolution of climate. In some cases, changes in landscape patterns affect LST, even more than the contribution of greenhouse gases. Although much work has been done with respect to the correlations between urban development and thermal environment dynamics, the related questions regarding relationships between LST and landscape patterns in arid regions are not thoroughly considered. Understanding these questions is important in climate change and land planning. The objective of this study was to explore the spatiotemporal variations of LST by distribution index (DI) and Mann-Kendall mutation analysis method and to quantify the relationships between landscape patterns, climatic factors, topographic factors, and the land surface thermal environment (LSTE) by the ordinary linear regressions (OLS) model. The landscape patterns dataset, which was validated by a field trip, was extracted from the Land satellite (Landsat) TM/OLI images by the Random Forest methodology in ArcGIS software. The MODIS/LST product was validated by the "Monthly dataset of China's surface climate" and a field trip. Annual LST increased by 0.54 °C (23.15 °C in 2000 and 23.79 °C in 2015). In different landscape patterns, the percentage of areas with a high level of LST showed a significant difference. In barren land, the highest area proportion for the high LST level was larger than in other landscape patterns. Meanwhile, the area of low LST was mainly concentrated in water bodies. Considerable changes have occurred in landscape patterns, in which the most noteworthy was cultivated land encroaching on grass land (3708.44 km²). The composition of landscape patterns was more important than distribution in determining the region's LST. These findings provide valuable information for land planners dealing with climate change and ecosystem conservation in arid regions.

Separating the effects of climate change and human activity on water use efficiency over the Beijing-Tianjin Sand Source Region of China

Water use efficiency (WUE) is a central parameter for linking carbon and water exchange processes in terrestrial ecosystems. The Beijing-Tianjin Sand Source Region (BTSSR) in China has undergone tremendous vegetation restoration and climate change. Understanding the WUE responses to climate change and human activity and their relative contributions to the trends and inter-annual variations (IAVs) in WUE is necessary to improve water use efficiency and strengthen water resource management. The evapotranspiration (ET) dataset based on the model tree ensemble (MTE) algorithm which was a machine learning approach using flux-tower ET measurements and the GLASS GPP dataset, as well as the variance decomposition method, were used to analyze the spatiotemporal changes in water use efficiency and inherent water use efficiency (IWUE) and the impacts of climate change and human activities. The results showed that the annual WUE and IWUE exhibited significantly increase in most regions of the BTSSR. The trend of human activity played the most important role in the increases of WUE and IWUE, with relative contributions of 88.2% and 85.9%, respectively, followed by the IAV of human activity for WUE (6.1%) and the trend of climate change (8.7%) for IWUE. The contribution of IAV to climate change was relatively small. Moreover, WUE and IWUE were all positively correlated with precipitation and temperature in most regions. Our results indicated that ecological restoration projects had significantly improved water use efficiency in BTSSR and may decrease the water burden in the BTSSR.

Modeling the Effects of Anthropogenic Land Cover Changes to the Main Hydrometeorological Factors in a Regional Watershed, Central Greece

In this study, the physically-based hydrological model MIKE SHE was employed to investigate the effects of anthropogenic land cover changes to the hydrological cycle components of a regional watershed in Central Greece. Three case studies based on the land cover of the years 1960, 1990, and 2018 were examined. Copernicus Climate Change Service E-OBS gridded meteorological data for 45 hydrological years were used as forcing for the model. Evaluation against observational data yielded sufficient quality for daily air temperature and precipitation. Simulation results demonstrated that the climatic variabilities primarily in precipitation and secondarily in air temperature affected basin-averaged annual actual evapotranspiration and average annual river discharge. Nevertheless, land cover effects can locally outflank the impact of climatic variability as indicated by the low interannual variabilities of differences in annual actual evapotranspiration among case studies. The transition from forest to pastures or agricultural land reduced annual actual evapotranspiration and increased average annual river discharge while intensifying the vulnerability to hydrometeorological-related hazards such as droughts or floods. Hence, the quantitative assessment of land cover effects presented in this study can contribute to the design and implementation of successful land cover and climate change mitigation and adaptation policies.

Hydrological responses to land use/land cover change and climate variability in contrasting agro-ecological environments of the Upper Blue Nile basin, Ethiopia

Land use/land cover (LULC) change and climate variability are two major factors controlling hydrological responses. The present study analyzed the separate and combined effects of these two factors on annual surface runoff and evapotranspiration (ET) after validating the selected models in three drought-prone watersheds of the Upper Blue Nile basin: Kasiry (highland), Kecha (midland), and Sahi (lowland). LULC maps were produced from aerial photographs and very-high-resolution satellite images from 1982, 2005/06 and 2016/17. During 1982-2016/17 the area covered by natural vegetation showed dramatic decreases, ranging from 60.2% in Kasiry to 51.8% in Sahi. In contrast, increases in cultivated land ranged from 36.7% in Kasiry to 279.6% in Sahi; the smaller increase in Kasiry resulted from the conversion of a portion of the cultivated land to an Acacia decurrens plantation after 2006. The observed LULC changes over the study period resulted in runoff increases ranging from 4% in Kecha to 28.7% in Kasiry. Climate variability in terms of annual rainfall had no significant effect on estimated runoff; whereas both LULC change and climate variability had significant effect on estimated ET. Though climate variability increased ET from 33.6% in Kecha to 42.1% in Kasiry, the LULC change related to the reduction in natural vegetation had an offsetting effect, which led to overall decreases in ET ranging from 15.8% in Kasiry to 32.8% in Kecha watershed. As changes in LULC and climate are expected to intensify in the future, it is important to study further hydrological responses considering these changes to devise future sustainable land and water management strategies.

Variation in actual evapotranspiration following changes in climate and vegetation cover during an ecological restoration period (2000-2015) in the Loess Plateau, China

The spatial distribution of water resources largely influences Earth ecosystems and human civilization. Being a major component of the global water cycle, evapotranspiration (ET) serves as an indicator of the availability of water resources. Understanding the actual ET (ET_a) variation mechanism at different spatial and temporal scales can improve management of water use within the sustainable development limits. In this study, remote sensing derived ET_a data were used to study water resource fluctuations in the Loess Plateau, China. This region covers diverse climate types from humid to arid and experienced large changes in vegetation cover during a revegetation project between 2000 and 2015. The relations between spatiotemporal variation of ET_a, climate factors and vegetation change were explored using statistical methods. The results show that cropland, forestland and grassland take the largest percentage of total ET_a. Total ET_a exhibited a marginally increasing trend (p < 0.1) during 2000-2010 and no trend during 2011-2015. Windspeed and vegetation cover index highly influenced ET_a, followed by atmospheric pressure, air humidity, precipitation, bright sunshine duration and temperature. Temperature has little effect on ET_a throughout the Loess Plateau. The monitoring of water resources based upon water balance between precipitation, ET_a and river flow changes shows that water consumption deficit is consistent with vegetation changes: it was large during 2000-2010 when vegetation increased rapidly and decreased after 2010. These results could help to develop different water saving strategies across the Loess Plateau and build a better monitoring system of water resources.

Impact of land use and land cover transitions and climate on evapotranspiration in the Lake Naivasha Basin, Kenya

The Lake Naivasha Basin in Kenya has experienced significant land use cover changes (LUCC) that has been hypothesized to have altered the hydrological regime in recent decades. While it is generally recognized that LUCC will impact evapotranspiration (ET), the precise nature of such impact is not very well understood. This paper describes how land use conversions among grassland and croplands have influenced ET in the Lake Naivasha Basin for the period 2003 to 2012. MODIS data products were used in combination with the European Centre for Medium-Range Weather Forecasts (ECMWF) data sets to model ET using the Surface Energy Balance System (SEBS). The results indicate that conversions from grassland to cropland accounted for increases in ET of up to 12% while conversion from cropland back to grasslands (abandonment) reduced ET by ~4%. This suggests that recently cultivated agricultural lands could increase local water demands, while abandonment of the farms could decrease the water loss and eventually increase the water availability. Also, recovery of ET following re-conversion from cropland to grassland might be impeded due to delayed recovery of soil properties since parts of the catchment are continuously being transformed with no ample time given for soil recovery. The annual ET over the 10 years shows an estimated decline from 724 mm to 650 mm (~10%). This decline is largely explained by a reduction in net radiation, an increase in actual vapour pressure whose net effect also led to decrease in the surface-air temperature difference. These findings suggest that in order to better understand LUCC effects on water resources of Lake Naivasha, it is important to take into account the effect of LUCC and climate because large scale changes of vegetation type from grassland to cropland substantially will increase evapotranspiration with implications on the water balance.

The Spatiotemporal Variability of Evapotranspiration and Its Response to Climate Change and Land Use/Land Cover Change in the Three Gorges Reservoir

Evapotranspiration (ET) has undergone profound changes as a result of global climate change and anthropogenic activities. The construction of the Three Gorges Reservoir (TGR) has led to changes in its land use/land cover (LUCC) and local climate, which in turn has changed ET processes in the TGR region. In this paper, the CLM4.5 land surface model is used to simulate and analyze the spatiotemporal variability of ET between 1993 and 2013. Four experiments were conducted to quantify the contribution rate of climate change and LUCC to changes in ET processes. The results show that the climate showed a warming and drying trend from 1993 to 2013, and the LUCC indicates decreasing cropland with increasing forest, grassland, water bodies and urban areas. These changes increased the mean annual ET by 13.76 mm after impoundment. Spatially, the vegetation transpiration accounts for the largest proportion in ET. The decreasing relative humidity and increasing wind speeds led to an increase in vegetation transpiration and ground evaporation, respectively, in the center of the TGR region, while the LUCC drove changes in ET in water bodies, urban areas and high-altitude regions in the TGR region.

Assessing long-term urban surface water changes using multi-year satellite images: A tale of two cities, Dhaka and Hong Kong

Water is a fundamental component of an urban environment. Management of water resources is important to facilitate a liveable environment and urban sustainability. Several factors affect water resources, including urbanization, climate change and seasons. Moreover, the nature of urban expansion and unsustainable water management practices have been associated with water scarcity, loss of biodiversity and increase of flood risk. Knowledge of the changes in urban surface water in relation to changes in seasons, land covers, anthropogenic activities, and topographical characteristics are important for managing watersheds and urban planning, and developing adaptation strategies to address environmental challenges posed by urbanization. However, existing studies rarely consider all the above factors when monitoring surface water changes in the urban environment. To address this problem, this study uses satellite images from multiple seasons and years, and assess the changes in surface water in relation to changes of several important factors, e.g., seasons, urbanization, land cover and topography. Moreover, this study applies advanced geostatistical tools to assess the local relationship between changes in surface water and the driving factors, and compares the findings in two cities Dhaka (Bangladesh) and Hong Kong with a large contrast in many aspects. First, seasonal influence in the distribution of water area is evaluated. Second, land cover classifications are assigned, and then the contingency matrix and decadal maps are formulated to investigate and evaluate the influence of urbanization on the occurrence and transitions in surface water. Third, an advanced geostatistical regression model is used to investigate the spatially varying relationships for change in surface water in relation to change in other land covers and topography. The investigations confirm that the temporal and seasonal variation, and urbanization induced land cover changes largely affect surface water. In addition, topography influences the nature of the city's expansion, which in turn entails the changes in surface water. The flat terrain of Dhaka facilitates the easy invasion of water bodies and horizontal expansion, in contrast, the steep terrain of Hong Kong prohibits horizontal expansion thus it's surface water is more stable than Dhaka.

Dynamic simulation of land use change based on logistic-CA-Markov and WLC-CA-Markov models: a case study in three gorges reservoir area of Chongqing, China

The construction of The Three Gorges Reservoir has changed land use structure and reconstituted landscape pattern as imparts significant influence upon the land use structure and ecological environment of Three Gorges Reservoir Regions. The ecological safety of reservoir area is extremely dependent on unique location and special geological conditions of Zhongxian County, the center of Three Gorges Reservoir Regions in Chongqing, and therefore, ecological environment of reservoir area will be changed with the transition of land use in Zhongxian County. Based on land use data in 2000, 2005, 2010, this paper chooses influencing factors from aspects of natural topographic and geomorphological conditions, accessibility to economic development and land use expansion, and then establishes Logistic-CA-Markov (Logistic-Cellular Automata-Markov) and WLC-CA-Markov (Weighted Linear Combination- Cellular Automata- Markov) models so as to simulate spatial pattern of land use of Zhongxian County. The results demonstrate that WLC-CA-Markov model established here has better controllability and higher simulation precision (the kappa coefficient is 0.9295). In the future development of Zhongxian County, the area of grassland and plow land will be reduced continuously, the area of construction land will be expanded obviously mostly because of the added area both near the water and in the north of Zhongxian county, the area of woodland will be increased to a little extent, the area of water area and unused land has gentle change. In the sustainable scenario, the area of grassland will be reduced slightly, the area of water area keeps steady, the area of plow land is reduced but higher than red line of plow land, the area of construction land is increased with significantly smaller increase amplitude than that in the natural development scenario, and the woodland is increased. This scenario coordinates ecological environment with economic development of regional society and turns out to be the best development scenario of land use.

Application of the Simple Biosphere Model 2 (SiB2) with Irrigation Module to a Typical Low-Hilly Red Soil Farmland and the Sensitivity Analysis of Modeled Energy Fluxes in Southern China

Land surface processes are an important part of the Earth’s mass and energy cycles. The application of a land surface process model for farmland in the low-hilly red soil region of southern China continues to draw research attention. Conventional model does not perform well in the simulation of irrigated farmland, because the influence of land surface water is not considered. In this study, an off-line version of the Simple Biosphere model 2 (SiB2) was locally parameterized in a typical farmland of the low-hilly red soil region using field observations and remote sensing data. The performance of SiB2 was then evaluated through comparison to Bowen-ratio direct measurements in a second growing period of rice in 2015 (late rice from 23 July to 31 October). The results show that SiB2 underestimated latent heat flux (LE) by 16.0% and overestimated sensible heat flux (H) by 16.7%, but net radiation flux (Rn) and soil heat flux were reasonably simulated. The single factor sensitivity analysis of Rn, H, and LE modeled in SiB2 indicated that downward shortwave radiation (DSR) and downward longwave radiation (DLR) had a significant effect on Rn simulation. In driving data, DSR, DLR and wind speed (u) were the main factors that could cause a distinct change in sensible heat flux. An irrigation module was added to the original SiB2 model to simulate the influence of irrigated paddy fields according to the sensitivity analysis results of the parameters (C1, bulk boundary-layer resistance coefficient; C2, ground to canopy air-space resistance coefficient; and Ws, volumetric water content at soil surface layer). The results indicate that application of the parameterized SiB2 with irrigation module could be better in southern Chinese farmland.

A Statistical–Distributed Model of Average Annual Runoff for Water Resources Assessment in DPR Korea

Water resource management is critical for the economic development of the Democratic People’s Republic of Korea (DPRK), where runoff plays a central role. However, long and continuous runoff data at required spatial and temporal scales are generally not available in many regions in DPRK, the same as in many countries around the world. A common practice to fill the gaps is to use some kind of interpolation or data-infilling methods. In this study, the gaps in annual runoff data were filled using a distributed runoff map. A novel statistical–distributed model of average annual runoff was derived from 50 years’ observation on 200 meteorological observation stations in DPRK, considering the influence of climatic factors. Using principal component analysis, correlation analysis and residual error analysis, average annual precipitation, average annual precipitation intensity, average annual air temperature, and hot seasonal air temperature were selected as major factors affecting average annual runoff formation. Based on the water balance equation and assumptions, the empirical relationship for runoff depth and impact factors was established and calibrated. The proposed empirical model was successfully verified by 93 gauged stations. The cartography of the average annual runoff map was automatically implemented in ArcGIS. A case study on the Tumen River Basin illustrated the applicability of the proposed model. This model has been widely used for the development and management of water resources by water-related institutes and design agencies in DPRK. The limitation of the proposed model and future works are also discussed, especially the impacts of climate changes and topology changes and the combination with the physical process of runoff formation.

Response of Wetland Evapotranspiration to Land Use/Cover Change and Climate Change in Liaohe River Delta, China

This study aims to investigate the effects of land use/cover change (LUCC) and climate change on wetland evapotranspiration (ET), and to identify the importance of the main effect factors in the spatiotemporal dynamics of ET. In the wetland of Liaohe River Delta, China, the ET of eight growing seasons during 1985–2017 was estimated using the surface energy balance algorithm for land (SEBAL) model with Landsat and meteorological data. Results show that the average relative error of regional ET estimated by the SEBAL model is 9.01%, and the correlation coefficient between measured and estimated values is 0.61, which indicates that the estimated values are reliable. This study observed significant spatial and temporal variations in ET across the region of interest. The distribution of the average and relative change rate of daily ET in the study area showed bimodal characteristics, that is, the lowest trough occurred in 2005, whereas crests occurred in 1989 and 2014. Simultaneously, the daily ET varied with the land use/cover area. Regional daily ET displays highly heterogeneous spatial distribution, that is, the ET of different land uses/cover types in descending order is as follows: water body, wetland vegetation, non-wetland vegetation, and non-vegetation (except water area). Therefore, the spatial pattern of ET is relevant to the land use/cover types to some extent. In addition, the temporal variation of wetland ET is closely related to landscape transformation and meteorological factor change. A strong correlation was found between ET and the weighted values of meteorological factors, with a correlation coefficient of 0.69. Meanwhile, the annual fluctuations of daily ET and the weighted values were relatively similar. Therefore, the findings highlight the importance of using cheap and readily available remote sensing data for estimating and mapping the variations in ET in coastal wetland.

Contributions of climate change and vegetation greening to evapotranspiration trend in a typical hilly-gully basin on the Loess Plateau, China

Significant increases in vegetation cover on the Loess Plateau since the early 2000s have been well documented. However, the relevant hydrological effects are still unclear. Here, we investigated the changes in actual evapotranspiration (ET_a) from 2000 to 2016 and related them to climate change and vegetation greening in Yanhe River basin (YRB), a typical hilly-gully basin on the Loess Plateau, by using the remote-sensing based VIP model. Results showed that the annual ET_a in the YRB increased significantly with a trend of 3.45mmyr^-1 (p<0.01) and changes of ET_a in summer months dominated the annual trend. Partial correlation analysis suggested that vegetation greening was the dominant driving factor of ET_a inter-annual variations in 56% area of YRB. Model simulation experiments illustrated that relative contributions of NDVI, precipitation, and potential evapotranspiration (ET_p) to the ET_a trend were 93.0%, 18.1%, and -7.4%, respectively. Vegetation greening, which is closely related to the Grain for Green (GFG) afforestation, was the main driver to the long-term tendency of water consumption in the YRB. This study highlights potential water demanding conflicts between the socio-economic system and the natural ecosystem on the Loess Plateau due to the rapid vegetation expansion in this water-limited area.

Projections of actual evapotranspiration under the 1.5 °C and 2.0 °C global warming scenarios in sandy areas in northern China

Actual evapotranspiration (ETa) is an essential component of Earth's global energy balance and water cycle. The Paris Agreement aspires to limit global mean surface warming to <2 °C and no >1.5 °C relative to preindustrial levels. However, it is uncertain how this global level will impact the shifts in the extents of sandy areas caused by global desertification. Using Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) datasets and advection-aridity models, we investigated the spatiotemporal features of ETa in sandy areas in northern China under global warming scenarios of 1.5 °C and 2.0 °C. The four climate models indicated significant increases in ETa in arid areas across northwestern China. Over time, the ETa value under only the representative concentration pathway 2.6 (RCP2.6) emission scenario increased towards a plateau and significantly increased in the other three emission scenarios (P < 0.01) under global warming of 1.5 °C and 2.0 °C. In terms of the spatial variations, ETa showed an increasing trend in all seasons except winter. The maximum ETa was 84.61 mm, and high values were mainly located in the southeast of the study area. Precipitation and the normalized difference vegetation index (NDVI) showed good correlations with ETa in the sandy areas in northern China. The sandy areas in northern China showed decreasing trends (0.45 km²/a) from 1980 to 2015. Under global warming of 2.0 °C (2040-2059) relative to that of 1.5 °C (2020-2039), the area of sandy land will increase at a rate of 27.04 km² per decade (P < 0.01); after this period, the sandy land area in northern China may gradually stabilize, with a trend of 0.02 km²/a (2047-2100). Early efforts to achieve the 1.5 °C temperature goal could therefore markedly reduce the likelihood that large regions will face substantial global desertification and the related impacts.

The science of food security

We need to feed an estimated population in excess of 9 billion by 2050 with diminishing natural resources, whilst ensuring the health of people and the planet. Herein we connect the future global food demand to the role of agricultural and food science in producing and stabilising foods to meet the global food demand. We highlight the challenges to food and agriculture systems in the face of climate change and global megatrends that are shaping the future world. We discuss the opportunities to reduce food loss and waste, and recover produce that is currently wasted to make this the new raw ingredient supply for the food industry. Our systems-based perspective links food security to agricultural productivity, food safety, health and nutrition, processing and supply chain efficiency in the face of global and industry megatrends. We call for a collaborative, transdisciplinary approach to the science of food security, with a focus on enabling technologies within a context of social, market and global trends to achieve food and nutritional security.

Integrated Change Detection and Classification in Urban Areas Based on Airborne Laser Scanning Point Clouds

This paper suggests a new approach for change detection (CD) in 3D point clouds. It combines classification and CD in one step using machine learning. The point cloud data of both epochs are merged for computing features of four types: features describing the point distribution, a feature relating to relative terrain elevation, features specific for the multi-target capability of laser scanning, and features combining the point clouds of both epochs to identify the change. All these features are merged in the points and then training samples are acquired to create the model for supervised classification, which is then applied to the whole study area. The final results reach an overall accuracy of over 90% for both epochs of eight classes: lost tree, new tree, lost building, new building, changed ground, unchanged building, unchanged tree, and unchanged ground.

Changes in reference evapotranspiration and its driving factors in the middle reaches of Yellow River Basin, China

Reference evapotranspiration (ET₀) is important for agricultural, environmental and other studies, and understanding the attribution of its change is helpful to provide information for irrigation scheduling and water resources management. The present study investigates the attribution of the change of ET₀ at 49 meteorological stations in the middle reaches of Yellow River basin (MRYRB) of China from 1960 to 2012. Results show that annual ET₀ increases from the northwest to the southeast of MRYRB in space. We find that annual ET₀ clearly presents a zigzag change pattern rather than a monotonically change during the whole period. The detected three breakpoints at 1972, 1988 and 1997 divide the whole period into four subperiods. The sensitivity analysis indicates that the ET₀ is the most sensitive to surface solar radiation (Rs), followed by relative humidity (RH) and mean air temperature (T), and the least sensitive to wind speed (u) in our study area. Furthermore, we find that ET₀ is becoming less sensitive to RH and more sensitive to T during 1960-2012. The attributions of the change in ET₀ vary largely at different regions and subperiods. The declined wind speed is the dominant factor, followed by Rs to the ET₀ reduction during 1960-2012. Further analysis shows that Rs and u are the two major contributing factors that control the change of ET₀ at most stations and during most subperiods. Our study confirms that the change of ET₀ is influenced by the complex interactions of climatic factors, and the dominant factor to the change of ET₀ is different in various regions and time periods. The results presented here can provide a reference for agricultural production and water resources management in MRYRB as well as other semi-arid and semi-humid regions.