Responses of seasonal indicators to extreme droughts in southwest China

Significant impact of extreme droughts on human society and ecosystem has occurred in many places of the world, for example, Southwest China (SWC). Considerable research concentrated on analyzing causes and effects of droughts in SWC, but few studies have examined seasonal indicators, such as variations of surface water and vegetation phenology. With the ongoing satellite missions, more and more earth observation data become available to environmental studies. Exploring the responses of seasonal indicators from satellite data to drought is helpful for the future drought forecast and management. This study analyzed the seasonal responses of surface water and vegetation phenology to drought in SWC using the multi-source data including Seasonal Water Area (SWA), Permanent Water Area (PWA), Start of Season (SOS), End of Season (EOS), Length of Season (LOS), precipitation, temperature, solar radiation, evapotranspiration, the Palmer Drought Severity Index (PDSI), the Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), Gross Primary Productivity (GPP) and data from water conservancy construction. The results showed that SWA and LOS effectively revealed the development and recovery of droughts. There were two obvious drought periods from 2000 to 2017. In the first period (from August 2003 to June 2007), SWA decreased by 11.81% and LOS shortened by 5 days. They reduced by 21.04% and 9 days respectively in the second period (from September 2009 to June 2014), which indicated that there are more severe droughts in the second period. The SOS during two drought periods delayed by 3~6 days in spring, while the EOS advanced 1~3 days in autumn. All of PDSI, SWA and LOS could reflect the period of droughts in SWC, but the LOS and PDSI were very sensitive to the meteorological events, such as precipitation and temperature, while the SWA performed a more stable reaction to drought and could be a good indicator for the drought periodicity. This made it possible for using SWA in drought forecast because of the strong correlation between SWA and drought. Our results improved the understanding of seasonal responses to extreme droughts in SWC, which will be helpful to the drought monitoring and mitigation for different seasons in this ecologically fragile region

Earth Observations and Integrative Models in Support of Food and Water Security

Global food production depends upon many factors that Earth observing satellites routinely measure about water, energy, weather, and ecosystems. Increasingly sophisticated, publicly-available satellite data products can improve efficiencies in resource management and provide earlier indication of environmental disruption. Satellite remote sensing provides a consistent, long-term record that can be used effectively to detect large-scale features over time, such as a developing drought. Accuracy and capabilities have increased along with the range of Earth observations and derived products that can support food security decisions with actionable information. This paper highlights major capabilities facilitated by satellite observations and physical models that have been developed and validated using remotely-sensed observations. Although we primarily focus on variables relevant to agriculture, we also include a brief description of the growing use of Earth observations in support of aquaculture and fisheries

A New Satellite-Based Methodology for Continental-Scale Disturbance Detection

The timing, location, and magnitude of major disturbance events are currently major uncertainties in the global carbon cycle. Accurate information on the location, spatial extent, and duration of disturbance at the continental scale is needed to evaluate the ecosystem impacts of land cover changes due to wildfire, insect epidemics, flooding, climate change, and human-triggered land use. This paper describes an algorithm developed to serve as an automated, economical, systematic disturbance detection index for global application using Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua Land Surface Temperature (LST) and Terra/MODIS Enhanced Vegetation Index (EVI) data from 2003 to 2004. The algorithm is based on the consistent radiometric relationship between LST and EVI computed on a pixel-by-pixel basis. We used annual maximum composite LST data to detect fundamental changes in land–surface energy partitioning, while avoiding the high natural variability associated with tracking LST at daily, weekly, or seasonal time frames. Verification of potential disturbance events from our algorithm was carried out by demonstration of close association with independently confirmed, well-documented historical wildfire events throughout the study domain. We also examined the response of the disturbance index to irrigation by comparing a heavily irrigated poplar tree farm to the adjacent semiarid vegetation. Anomalous disturbance results were further examined by association with precipitation variability across areas of the study domain known for large interannual vegetation variability. The results illustrate that our algorithm is capable of detecting the location and spatial extent of wildfire with precision, is sensitive to the incremental process of recovery of disturbed landscapes, and shows strong sensitivity to irrigation. Disturbance detection in areas with high interannual variability of precipitation will benefit from a multiyear data set to better separate natural variability from true disturbance

Monitoring Landscape Changes Using Remote Sensing Technology in Southern Africa

Rangelands are a major global resource, and there is an urgency to improve the assessment of landscape performance to capture carbon, produce biomass, and improve water use. Effective monitoring necessitates the collection of high quality rangeland condition data using repeatable techniques. Despite much effort, there are few comprehensive data sets that allow confident detection of landscape change. Data are lacking for several reasons, including high cost of data collection, conflicting methodologies, and loss of archival data. Satellite imagery provides the basis for trend and pattern analysis of rangeland in different conditions classes and this paper presents some examples of the analysis and interpretation of selected imagery from southern African rangelands. One approach to understanding rangeland change is to identify models that use functional concepts to describe landscape performance. Rangeland water use has being equated to that of more thirsty crops, resulting in further pressure to convert rangeland to dryland cultivation. Water use efficiency (WUE) is of considerable value in defining functionality. Here, WUE defines the ability of an ecosystem to produce above-ground biomass (kg DM) per unit of actual evapotranspiration (mm). It been calculated for several condition classes at sites in arid and semi-arid rangelands. In the past, estimates of WUE have been hampered by the scarcity of reliable net primary production (NPP) and evapotranspiration data. With the availability of spatially explicit estimates of actual evapotranspiration (ETa) from the MODIS programme, it is now possible to validate annual ETa surfaces at a spatial resolution of 1 km. We have validated these ETa surfaces for southern Africa using a range of instruments and approaches. In addition, a global annual net primary production (MOD17) surface is available from MODIS. By combining these products, we have prepared an estimate of WUE (WUE = NPP/ ETa) for natural rangelands in southern Africa for 2009. WUE varies spatially, with values ranging from 0.1 kg DM mm/ha/y in the arid western regions to \u3e 8 kg DM/mm/ha/y in the forests and grasslands of the eastern region. Using data from several ground-based measurements of WUE, this surface has been validated, and demonstrates that this is a useful product for comparing landscape management strategies and condition classes. I show how this product, and other remote sensing products, can be used to evaluate different land management strategies

Monitoring land-cover changes in Mediterranean coastal dunes, northwest Tunisia, using remote sensing data

Coastal dune landscapes are subject to morphological and ecological changes. In many parts of the world, coastal dunes are under severe pressure. The present study illustrates an integrated remote sensing and Geographical Information System (GIS) approach, i.e., geospatial techniques for assessing land-cover dynamics in Zouaraa coastal dunes, located in northwest Tunisia. As a main result, the analysis of the situation in the past six decades indicates that the dune area showed a decreasing trend with up to 31% (i.e., 6198 ha) in favour of forest area, which has increased by up to 6485 ha. The geo-spatial analysis revealed that restoration works have positively contributed to stabilize coastal dune systems with a substantial increase in vegetation cover. An increase in drought frequency and intensity was detected during the 1952-2017 period using the SPEI index, which enhanced the vegetation activity and growth in the study area. The SPEI significantly correlated with vegetation greenness on the 12- and 24-months’ time scales. The croplands, water and buildings in the study area have increased respectively by 6% (i.e., 1256 ha), 13% (i.e., 3073 ha) and 3% (i.e., 719 ha). In contrast, land cover like shrub and bare soil has decreased respectively by 13% (i.e., 3073 ha) and 2% (i.e., 1831 ha) during the same period. Furthermore, this study highlights the importance of the revegetation techniques undertaken for conserving coastal dune systems. The findings of this study allow land-use planning decision makers to manage and improve situations in similar coastal regions.This work was supported by the National Research Institute for Rural Engineering, Waters, and Forestry-INRGREF. Laboratory of Management and Valorization of Forest Resources, Tunisia. This research is part of the project: HYDROMED (PID-2019-111332RB-C21)

Predicted impacts of land use change on groundwater recharge of the upper Berg catchment, South Africa

Land use change is a major factor influencing catchment hydrology and groundwater resources. In South Africa, the management of scarce water resources is a big concern. The study area, the upper Berg catchment, Western Cape, South Africa, contains strategic water resources. The catchment has undergone many changes in recent years, not least of all the construction of a dam on the upper reach. To reduce water loss due to evapotranspiration, non-native hill slope vegetation upstream of the Berg River Dam was cut down. It was hypothesised that recharge has been increased due to this change in vegetation. The objectives of this study were to determine land use changes in upper Berg catchment using multi-temporal Landsat images from 1984, 1992, 2002, and 2008, and to predict the impact of these land use changes on groundwater recharge. For the simulation of groundwater recharge the distributed hydrological model WetSpa was used. Forest plantations lost 72% (18.8 km2) of their areal extent between 1984 and 2008, due to deforestation as part of a plan to implement the ecological Reserve as required by national water policy; the area of barren land increased by 15.7 km2 in the same period. The high increase in precipitation, especially in the period of 2005–2009, combined with the change in land use in the study area resulted in a highly increased (278%) predicted mean groundwater recharge. Simulated groundwater recharge shows strong spatial differences for each evaluated year. The effect of the rapid clearing of non-native hill slope vegetation upstream of the Berg River Dam for the land use scenario of 2008 was tested to check if clearing is an important factor in the increase of groundwater recharge. Hence, we simulated the whole time-series from 1984–2004 (21 years) with the land use map from 2008 instead of the land use maps for 1984, 1992 and 2002. A systematic increase of about 8% per year for the 21-year period, due to the change in land use from the different years to that of 2008, is predicted , which confirms that the clearing of the non-native hill slope vegetation is of considerable importance for the increase in groundwater recharge.Keywords: Berg catchment, ecological Reserve, WetSpa, remote sensin

The future for global water assessment

The global water cycle is a fundamental component of our climate and Earth system. Many, if not the majority, of the impacts of climate change are water related. We have an imperfect description and understanding of components of the water cycle. This arises from an incomplete observation of some of the stores and fluxes in the water cycle (in particular: precipitation, evaporation, soil moisture and groundwater), problems with the simulation of precipitation by global climate models and the wide diversity of global hydrological models currently in use. This paper discusses these sources of errors and, in particular, explores the errors and advantages of bias correcting climate model outputs for hydrological models using a single large catchment as an example (the Rhine). One conclusion from this analysis is that bias correction is necessary and has an impact on the mean flows and their seasonal cycle. However choice of hydrological model has an equal, if not larger effect on the quality of the simulation. The paper highlights the importance of improving hydrological models, which run at a continental and global scale, and the importance of quantifying uncertainties in impact studies