Spatiotemporal crop NDVI responses to climatic factors in mainland China

Climate change has caused a great impact on vegetation growth, production and distribution through variations of precipitation, temperature and sunshine. In this study, a categorization of zones for vegetation responses to climatic variability was conducted. Seasonal and annual crop responses to climate change in each region were analysed with multiple linear regression. The results show that the annual impact of climatic factors on crop growth was most significant in lower North China (R² = 0.48) and most insignificant in Northeast China (R² = 0.22). Temperature is the limiting climatic factor for crop growth annually in North China and Northeast China (zones 1–3), (p ≤ 0.05), while sunshine duration plays an important role for crop growth in zones which are more southern (zones 3 ~ 5). Precipitation significantly affects the annual crop growth in Inner Mongolia-Hebei-Shandong zone (zone 2) and Southeast zone (zone 5). Therefore, more attention should be paid to these zones. The spring temperature is the limiting climatic factor for crop growth in all the zones (p ≤ 0.05). Spring warming is helpful for crop growth in mainland China. Different agricultural and administrative measures should be taken in each zone to adapt to future climate change.     

Evaluation of MODIS Gross Primary Productivity (GPP) in tropical monsoon regions

Near real-time vegetation indices derived from MODIS (MODerate resolution Imaging Spectroradiometer) observations (http://modis.gsfc.nasa.gov) provide a first opportunity to monitor ecohydrological systems globally at a spatial resolution consistent with biophysical processes at the field scale. Here, we present work toward the quantitative estimation of the uncertainty associated with MODIS Gross Primary Productivity (GPP), an end-product that depends on several MODIS derived vegetation indices. GPP products, available at 8-day and 1-km resolutions, were evaluated in two representative tropical ecosystems: a mixed forest site in the humid tropics (the Marsyandi river basin in the Nepalese Himalayas), and an open shrubland site in a semi-arid region (the Sonora river basin in northern Mexico). The MODIS-GPP products were compared against simulations made with a process-based biochemical-hydrology model driven by flux tower meteorological observations. Whereas the temporal march of vegetation indices and GPP products is consistent between the model and the algorithm, our study indicates that that there is a positive bias in the case of the mixed forest biome in the Marsyandi basin, and a negative bias in the case of open shrublands in the Sonora basin. We examined the error contribution from the DAO meteorological data used in the standard MODIS GPP products. The bias between the GPP estimates using DAO and tower meteorology is − 2.77 gC/m²/day (i.e., − 77% of the mean of the tower-based GPP) in the Marsyandi, and 0.33 gC/m²/day (i.e., 18% of the mean of the tower-based GPP) in Sonora. Analysis of the temporal evolution of the discrepancies between the model and the MODIS algorithm points to the need for examining the light use efficiency parameterization, especially with regard to the representation of nonlinear functional dependencies on vapor pressure deficit (VPD), photosynthetically available radiation (PAR), and seasonal evolution of the productive capacity of vegetation as influenced by water stress.     

Integration of MONERIS and GREAT-ER in the decision support system for the German Elbe river basin

The Elbe-DSS is a computer based system for integrated river basin management of the German part of River Elbe basin. Simulation models are used to assess the efficiency of measures such as reforestation, changes of agricultural practices or the efficiency of wastewater treatment plants for achieving management targets. MONERIS and GREAT-ER are integrated into the Elbe-DSS to assess nutrient and pollutant loads. MONERIS calculates nutrient inputs from diffuse and point sources on a sub-catchment scale of about 1000 km². GREAT-ER is a tool for exposure assessment of point source emissions and considers fate in sewage treatment plants as well as degradation and transport in rivers. Both models make long-term predictions, but their spatial scales of operations differ. GREAT-ER divides the whole river network into small segments that are linked through a routing algorithm. The segments are coupled to MONERIS using accumulated flow length distribution. Linking the two models allows to distribute diffuse nutrient emissions calculated from MONERIS and point source emissions from GREAT-ER to the river network, where further elimination and transport processes are calculated. We exemplify the DSS in a study assessing the effects of different reforestation and erosion control measures on phosphate loads and concentrations in the river network.     

Characteristics and Sustainability Evaluation of Vegetation Change in Heihe River Basin during 2001 to 2017

Characteristics of vegetation variation play an important role in ecological monitoring and provide the basis for integrated river basin management decisions. In this study, the spatial-temporal trends in vegetation cover change and its sustainability in Heihe river basin during 2001~2017 were characterized, using MODIS-EVI time series data at a spatial resolution of 250 meters in Google Earth Engine(GEE) platform. Combined with temperature, precipitation and river runoff data, the factors affecting vegetation growth in Heihe River Basin were identified. The results show that: Over the last 17 years, the average annual increment of EVI in Heihe river basin was 0.003 9, and the annual expansion of vegetation area was 480.3 km². Vegetation in the upper, middle and lower reaches of Heihe river has changed in varying degrees affected by temperature, precipitation, reclamation of cultivated land, water resources management and related groundwater. Whether the annual maximum EVI value or vegetation area, the increase trend of vegetation in the middle reaches was the most significant, and the oasis area was more obvious than the non-oasis area. This trend is sustainable in the short term, but there is a greater risk for a long time scale. The study provides a demonstration for high-speed monitoring of vegetation changes, reflecting the equal importance of growth and type changes for monitoring vegetation in arid regions. The regional synergy of vegetation changes in river basin puts forward higher requirements for integrated river basin management, such as reasonable water separation and strengthening surface-groundwater collaborative management.     

黑河流域2001~2017年植被变化特征及其可延续性评价

植被的变化特征是流域生态监测的重要内容和流域综合管理决策的基础信息。基于谷歌地球引擎(Google Earth Engine,GEE),利用空间分辨率为250 m的MODIS-EVI(Enhanced Vegetation Index)产品,研究2001~2017年黑河流域植被的时空变化趋势及延续性特征。结合气温、降水与河流径流量观测数据,分析黑河流域上游、中下游绿洲与非绿洲区植被变化的影响因素。结果表明:近17年来黑河流域植被年最大EVI值年均增幅为0.0039,年均新增植被面积为480.3 km^2。受气温、降水、耕地开垦、水资源管理措施及与其密切相关的地下水等因素的不同影响,上中下游表现出不同的变化特征。无论是年最大EVI值还是植被面积,中游的增加趋势最为显著,绿洲区较非绿洲区增加趋势更为明显。这种变化趋势短期内可能延续,但长时间内存在较大风险。研究为快速监测植被变化提供了示范,揭示了干旱区植被监测中长势变化与类型变化的同等重要性,流域植被变化的区域协同性对合理分水、加强地表-地下水协同管理等流域综合管理提出了更高要求。     

Coupling agent-based models of subsistence farming with individual-based forest models and dynamic models of water distribution

Subsistence farming communities are dependent on the landscape to provide the resource base upon which their societies can be built. A key component of this is the role of climate and the feedback between rainfall, crop growth, land clearance and their coupling to the hydrological cycle. Temporal fluctuations in rainfall alter the spatial distribution of water availability, which in turn is mediated by soil-type, slope and landcover. This pattern ultimately determines the locations within the landscape that can support agriculture and controls sustainability of farming practices. The representation of such a system requires us to couple together the dynamics of human and ecological systems and landscape change, each of which constitutes a significant modelling challenge on its own. Here we present a proto-type coupled modelling system to simulate land-use change by bringing together three simple process models: (a) an agent-based model of subsistence farming; (b) an individual-based model of forest dynamics; and (c) a spatially explicit hydrological model which predicts distributed soil moisture and basin scale water fluxes. Using this modelling system we investigate how demographic changes influence deforestation and assess its impact on forest ecology, stream hydrology and changes in water availability.     

Vegetation dynamics and their response to groundwater and climate variables in Qaidam Basin,China

This article discusses an evaluation of Moderate Resolution Imaging Spectroradiometer (MODIS) time-series data for monitoring vegetation variation in Qaidam Basin, Northwest China. In this study, 16 day composite 250 m normalized difference vegetation index (NDVI) products (MOD13Q1) acquired from 2000 to 2011 were processed to determine vegetation cover fraction (VCF) for detecting the annual dynamics of different types of vegetation cover in the basin and the products were validated by comparing field measurement in spatial distribution. The results show that the annual NDVI value increased from 0.126 to 0.172 on average between 2000 and 2011. The basin interior is dominated by desert and 74% of the area is covered by low-density shrubs and bare soil. Both areas of bare soil and low-density vegetation present a decreased rate, whereas medium-, medium-high-, and high-density vegetation show increase trends in the vegetation cover. Generally, the vegetation fluctuation depends on various attributes such as climate change, elevation, water table depth, and total dissolved solids (TDS) in arid areas. We found strong statistical correlation between NDVI time series and climatic factors such as air temperature and precipitation. There is also an agreement between the spatial distribution of NDVI value and elevation, because elevation has important impacts on the distribution of vegetation pattern, which are different in coverage. The vegetation dependent on water table depth is more complicated: shrubs of Phragmites australis, Artemisia desertorum, and Tamarix ramossissima Ledeb. are sensitive to water table depth and the maximum NDVI occurred at a water table depth shallower than 2 m. However, high-height shrub such as Nitraria Schoberi L. reflects less dependence on water table depth. Normally, vegetation can develop well at TDS between 0 and 3 g l^?1 whereas Tamarix ramossissima Ledeb. can still survive when the TDS is larger than 8 g l^?1.     

动态全球植被模型的研究进展

植被与气候之间的相互作用是一个复杂的过程,为了研究植被与气候之间相互作用的机理和评价气候变化对植被影响,植被模型得以迅速发展,并从静态的植被模型发展到了动态全球植被模型（Dynamic Global Vegetation Model,DGVM）。DGVM主要模拟植被的生理过程、植被动态、植被物候和营养物质循环,包括动态的生物地球化学模型和动态的生物地球物理模型两类。国际上应用最广泛的DGVM有LPJ、IBIS、VECODE和TRIFFID等。目前DGVM研究的焦点主要有4个：①模型本身的完善;②不同模型比较研究;③与气候模型的耦合研究;④碳数据同化系统研究。     

Detecting the effects of climate change on canopy phenology in coniferous forests in semi-arid mountain regions of China

An increased understanding of the responses of forest phenology to climate on regional scales is critical to the evaluation of biochemical cycles (i.e. carbon, water, heat, and nutrient) under environmental changes. In this study, we aimed to identify climatic constraints on phenological events in an evergreen coniferous forest in semi-arid mountain regions of northern China. We quantified the start of season (SOS), end of season (EOS), and growing season length (GSL) based on satellite-derived data sets (normalized difference vegetation index (NDVI)) and investigated the relationships between these phenological events and climate factors. The results revealed discontinuous trends in phenological events throughout the study period, with neither an obvious extension nor decrement in GSL. We demonstrated that minimum temperatures controlled the dynamics of SOS and EOS, thus providing strong evidence for the need to include minimum temperature as a control on phenology in simulation models. Additionally, precipitation was coupled to the shift in maximum NDVI, as rainfall is a major climatic limitation to vegetation growth in semi-arid regions. It appears that selecting appropriate timescales to analyse the relationships between phenology and climate is critical. We illustrated that NDVI was an effective tool in an effort to gain greater understanding of the effects of environmental change on ecosystem functioning in this forest. Our results may be used as reference to track local changes in the evergreen coniferous forest dynamics under different climate change scenarios for semi-arid mountain regions.     

Changes in agricultural cropland areas between a water-surplus year and a water-deficit year impacting food security,determined using MODIS 250 m time-series data and spectral matching techniques,in the Krishna River basin (India)

The objective of this study was to investigate the changes in cropland areas as a result of water availability using Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m time-series data and spectral matching techniques (SMTs). The study was conducted in the Krishna River basin in India, a very large river basin with an area of 265 752 km² (26 575 200 ha), comparing a water-surplus year (2000–2001) and a water-deficit year (2002–2003). The MODIS 250 m time-series data and SMTs were found ideal for agricultural cropland change detection over large areas and provided fuzzy classification accuracies of 61–100% for various land‐use classes and 61–81% for the rain-fed and irrigated classes. The most mixing change occurred between rain-fed cropland areas and informally irrigated (e.g. groundwater and small reservoir) areas. Hence separation of these two classes was the most difficult. The MODIS 250 m-derived irrigated cropland areas for the districts were highly correlated with the Indian Bureau of Statistics data, with R ²-values between 0.82 and 0.86.

The change in the net area irrigated was modest, with an irrigated area of 8 669 881 ha during the water-surplus year, as compared with 7 718 900 ha during the water-deficit year. However, this is quite misleading as most of the major changes occurred in cropping intensity, such as changing from higher intensity to lower intensity (e.g. from double crop to single crop). The changes in cropping intensity of the agricultural cropland areas that took place in the water-deficit year (2002–2003) when compared with the water-surplus year (2000–2001) in the Krishna basin were: (a) 1 078 564 ha changed from double crop to single crop, (b) 1 461 177 ha changed from continuous crop to single crop, (c) 704 172 ha changed from irrigated single crop to fallow and (d) 1 314 522 ha changed from minor irrigation (e.g. tanks, small reservoirs) to rain-fed. These are highly significant changes that will have strong impact on food security. Such changes may be expected all over the world in a changing climate.     

An interdisciplinary modelling framework for selecting adaptation measures at the river basin scale in a global change scenario

Shaping global change adaptation strategy in water resource systems requires an interdisciplinary approach to deal with the multiple dimensions of the problem. The modelling framework presented integrates climate, economic, agronomic and hydrological scenarios to design a programme of adaptation measures at the river basin scale. Future demand scenarios, combined with a down-scaled climate scenario, provide the basis to estimate the demand and water resources in 2030. A least-cost river basin optimisation model is then applied to select adaptation measures ensuring that environmental and supply management goals are achieved. In the Orb river basin (France), the least-cost portfolio selected suggests mixing demand and supply side measures to adapt to global change. Trade-offs among the cost of the programme of measures, the deficit in agricultural water supply and the level of environmental flows are investigated. The challenges to implement such interdisciplinary approaches in the definition of adaptation strategies are finally discussed.     

Mapping the potential annual total nitrogen load in the river basins of Japan with remotely sensed imagery

The increase of nutrient loads such as nitrogen and phosphorus to a river due to land cover changes in surrounding areas has been one of the major sources of water pollution or eutrophication. Monitoring the influent nutrient load from river basins to rivers is now crucial in the management of river basin environments. The monitoring is not easy, however, because it requires spatial and temporal measurement tools for land cover changes in the river basin and water qualities, and also it requires models relating them.In this study, we first analyzed the relation between the land cover types estimated from monthly maximum Normalized Difference Vegetation Index (NDVI) imagery calculated from NOAA Advanced Very High Resolution Radiometer (AVHRR) imagery and the annual total nitrogen load discharged from river basins. We found that the runoff load factor from urban areas is higher than those of forested areas. We also found that the impacts of land cover such as plantation and field weed communities on the total nitrogen load of each river are higher than the impacts of other land cover types such as Beech and Camellia japonica community type.Finally, we produced two advanced maps of the potential annual total nitrogen load (PTNL) index and the potential annual total nitrogen load for each river basin area (PTNL/area) index by considering the relationship between the land cover types and the annual total nitrogen load discharged from river basins in Japan. The PTNL map will be useful for the risk assessment of total nitrogen load impact on lakes and the sea through rivers from each basin. The PTNL/area index, which considers the effects of river basin areas, will allow evaluation of the state of river basins.     

Nutrient monitoring,simulation and management within a major lowland UK river system: the Kennet

This paper describes an assessment of the nitrogen and phosphorus dynamics of the River Kennet in the south east of England. The Kennet catchment (1200 km²) is a predominantly groundwater fed river impacted by agricultural and sewage sources of nutrient (nitrogen and phosphorus) pollution. The results from a suite of simulation models are integrated to assess the key spatial and temporal variations in the nitrogen (N) and phosphorus (P) chemistry, and the influence of changes in phosphorous inputs from a Sewage Treatment Works on the macrophyte and epiphyte growth patterns. The models used are the Export Co-efficient model, the Integrated Nitrogen in Catchments model, and a new model of in-stream phosphorus and macrophyte dynamics: the ‘Kennet’ model. The paper concludes with a discussion on the present state of knowledge regarding the water quality functioning, future research needs regarding environmental modelling and the use of models as management tools for large, nutrient impacted riverine systems.     

遥感水分收支对区域水资源估算潜能

为获得遥感水分收支对区域水资源估算潜力，利用遥感降水与蒸散发数据，通过研究中国十大水资源一级区及省区尺度上遥感水分收支平衡(降水与实际蒸散发差值)与水利统计水资源量间的关系，发现遥感降水蒸散差折合水资源量与基于统计数据的水资源量间具有较强正相关性，但总体偏低且存在区域差异，其中海河区低估最为显著，其次为淮河区、西南诸河区，西北诸河区则存在较大高估。对于地下水需求较大的区域，如海河区，地下水开采量没有被考虑作为遥感水资源量来源是造成遥感水资源量低估的主要原因。遥感降水低估、蒸散发高估也导致遥感水分收支平衡折合水资源量低于基于统计数据的水资源量。水资源时间变化趋势显示，中国水资源量总体呈增加趋势，但作为粮食主产区及人口密集区的华北地区，水资源形势严峻，呈显著减少趋势，将对经济发展及人们生活产生重大影响。     

Cellular automata approach for modelling climate change impact on water resources

ABSTRACT

In this work, we consider the cellular automata (CA) approach for modelling the climate change impact on water resources. This consists in: constructing a CA model that describes the water cycle dynamics taking into account physical terrain attributes and climatic constraints; coupling the CA model with climate projection scenarios for a considered region as input data; determining and analysing in output the variations of the underground, surface and evaporated water. We present these variations per time interval and per zone of influence. As an application, we consider simulation for a basin in northern Morocco using a simulation software we have designed in Java Object Oriented Programming.

We consider cellular automata (CA) approach for modelling climate change impact on water resources. This consists in, first constructing a CA model that describes the water cycle dynamics taking into account physical terrain attributes and climatic constraints, then coupling the CA model with climate projection scenarios for a considered region as input data, and we determine and analyze in output the variations of the water resources (groundwater and surface water). We present these variations per time interval and per zone of influence. The approach application is for a basin in northern Morocco for which we use simulation software that we have designed in Java Object Oriented Programming. Digital terrain model, geological map and satellites image are used for input data.     

Regional integrated modelling of climate change impacts on natural resources and resource usage in semi-arid Northeast Brazil

Semi-arid regions are characterised by a high vulnerability of natural resources to climate change, pronounced climatic variability and often by water scarcity and related social stress. The analysis of the dynamics of natural conditions and the assessment of possible strategies to cope with drought-related problems require an integration of diverse knowledge including climatology, hydrology, and socio-economics. The integrated model introduced here dynamically describes the relationships between climate forcing, water availability, agriculture and selected societal processes. The model has been designed to simulate the complex human-environment system in semi-arid Northeast Brazil quantitatively and is applied to study the sensitivity of regional natural resources and socio-economy to climate change. The validity of the model is considered.Climate change is concluded to have an enormous potential impact on the region. River flow, water storage and irrigated production are specifically affected, assuming a continuous regional development and unfavourable but plausible changes in climate. Under plausible favourable changes in climate, these variables remain stressed. The impact of the integrated model and its applications on present policy making and possible future roles are briefly discussed.     

Downscaling real-time vegetation dynamics by fusing multi-temporal MODIS and Landsat NDVI in topographically complex terrain

Canopy phenology is an important factor driving seasonal patterns of water and carbon exchange between land surface and atmosphere. Recent developments of real-time global satellite products (e.g., MODIS) provide the potential to assimilate dynamic canopy measurements with spatially distributed process-based ecohydrological models. However, global satellite products usually are provided with relatively coarse spatial resolutions, averaging out important spatial heterogeneity of both terrain and vegetation. Therefore, bias can result from lumped representation of ecological and hydrological processes especially in topographically complex terrain. Successful downscaling of canopy phenology to high spatial resolution would be indispensable for catchment-scale distributed ecohydrological modeling, aiming at understanding complex patterns of water, carbon and nutrient cycling in mountainous watersheds. Two downscaling approaches are developed in this study to overcome this issue by fusing multi-temporal MODIS and Landsat TM data in conjunction with topographic information to estimate high spatio-temporal resolution biophysical parameters over complex terrain. MODIS FPAR (fraction of absorbed photosynthetically active radiation) is used to provide medium spatial resolution phenology, while the variability of vegetation within a MODIS pixel is characterized by Landsat NDVI. The algorithms depend on the scale-invariant linear relationship between FPAR and NDVI, which is verified in this study. Downscaled vegetation dynamics are successfully validated both temporally and spatially with ground-based continuous FPAR and leaf area index measurements. Topographic correction during the downscaling process has a limited effect on downscaled FPAR products except for the period around the winter solstice in the study area.     

东北植被生长峰值特征的变化及对气候和物候的响应

全球气候变化导致植被生长的季节性节律事件(如返青期、衰落期和生长峰值期等)发生显著变化.植被返青期、衰落期和生长季长度的变化已经得到广泛报道,植被生长峰值代表植被光合作用能力和对气候变化的响应,目前关于植被生长峰值特征(时间点和最大生长幅度)的时空变化和控制机理的研究相对较少,仍需在不同区域深入探讨.以植被覆盖度较好的...     

Scenario analysis and management options for sustainable river basin management: Application of the Elbe DSS

We developed a decision support system (DSS) for sustainable river basin management in the German Elbe catchment (～100,000 km²), called Elbe-DSS. The system integrates georeferenced simulation models and related data sets with a user friendly interface and includes a library function. Design and content of the DSS have been developed in close cooperation with end users and stakeholders. The user can evaluate effectiveness of management actions like reforestation, improvement of treatment plant technology or the application of buffer strips under the influence of external constraints on climate, demographic and agro-economic changes to meet water management objectives such as water quality standards and discharge control. The paper (i) describes the conceptual design of the Elbe-DSS, (ii) demonstrates the applicability of the integrated catchment model by running three different management options for phosphate discharge reduction (reforestation, erosion control and ecological-farming) under the assumption of regional climate change based on IPCC scenarios, (iii) evaluates the effectiveness of the management options, and (iv) provides some lessons for the DSS-development in similar settings. The georeferenced approach allows the identification of local inputs in sub-catchments and their impact on the overall water quality, which helps the user to prioritize his management actions in terms of spatial distribution and effectiveness.