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Xue, B. ; Helman, D. ; Wang, G. ; Xu, C. - Y. ; Xiao, J. ; Liu, T. ; Wang, L. ; Li, X. ; Duan, L. ; Lei, H. The low hydrologic resilience of Asian Water Tower basins to adverse climatic changes. 2021, 155, 103996. Publisher's VersionAbstract
Climate change has a significant impact on the runoff of basins in cold, dry areas. The quantification of regional ecohydrological responses to climate change such as warming and drought is essential for establishing proper water resource management schemes. We propose a simple and novel method based on the Budyko framework to evaluate the hydrologic resilience of 16 basins that conform the Asian Water Tower in the Tibetan Plateau (TP). Our method defines two metrics within the Budyko domain – tolerance (ψ) and plasticity (φ) – that characterize the hydrologic resilience of a basin. Based on an ecohydrological point of view, a basin is considered hydrologically resilient if ψ and φ are both greater than 1 or its φ is negative and ψ is greater than 1. Our results show that ψ varies between 0.27 and 0.74, with an average value of 0.45 and φ varies between 2 and 16.33, with an average value of 6.90, for 14 out of the 16 basins. Only two basins – Taohe and Datonghe – had negative φ (-11.67 and -8.11, respectively) and ψ greater than 1 (2.26 and 19.58, respectively), suggesting that these two are the only basins with a hydrologic resilience to climatic warming/drying in the TP. Within the non-resilient basins, we found vegetation to play a key role in the level of tolerance and plasticity indicating that basins with a larger vegetation cover display a lower capability to adapt to adverse climatic changes. Following these results, we call for afforestation efforts to be carefully considered in cold, dry areas. The proposed method and conclusions drawn by this study may help predict the hydrologic responses to future adverse climatic conditions.
Shiff, S. ; Helman, D. ; Lensky, I. M. Worldwide continuous gap-filled MODIS land surface temperature dataset. Scientific Data 2021, 8 74 - 74. Publisher's VersionAbstract
Satellite land surface temperature (LST) is vital for climatological and environmental studies. However, LST datasets are not continuous in time and space mainly due to cloud cover. Here we combine LST with Climate Forecast System Version 2 (CFSv2) modeled temperatures to derive a continuous gap filled global LST dataset at a spatial resolution of 1 km. Temporal Fourier analysis is used to derive the seasonality (climatology) on a pixel-by-pixel basis, for LST and CFSv2 temperatures. Gaps are filled by adding the CFSv2 temperature anomaly to climatological LST. The accuracy is evaluated in nine regions across the globe using cloud-free LST (mean values: R2 = 0.93, Root Mean Square Error (RMSE) = 2.7 °C, Mean Absolute Error (MAE) = 2.1 °C). The provided dataset contains day, night, and daily mean LST for the Eastern Mediterranean. We provide a Google Earth Engine code and a web app that generates gap filled LST in any part of the world, alongside a pixel-based evaluation of the data in terms of MAE, RMSE and Pearson’s r.
Michael, Y. ; Helman, D. ; Glickman, O. ; Gabay, D. ; Brenner, S. ; Lensky, I. M. Forecasting fire risk with machine learning and dynamic information derived from satellite vegetation index time-series. 2021, 764, 142844. Publisher's VersionAbstract
Fire risk mapping – mapping the probability of fire occurrence and spread – is essential for pre-fire management as well as for efficient firefighting efforts. Most fire risk maps are generated using static information on variables such as topography, vegetation density, and fuel instantaneous wetness. Satellites are often used to provide such information. However, long-term vegetation dynamics and the cumulative dryness status of the woody vegetation, which may affect fire occurrence and spread, are rarely considered in fire risk mapping. Here, we investigate the impact of two satellite-derived metrics that represent long-term vegetation status and dynamics on fire risk mapping – the long-term mean normalized difference vegetation index (NDVI) of the woody vegetation (NDVIW) and its trend (NDVIT). NDVIW represents the mean woody density at the grid cell, while NDVIT is the 5-year trend of the woody NDVI representing the long-term dryness status of the vegetation. To produce these metrics, we decompose time-series of satellite-derived NDVI following a method adjusted for Mediterranean woodlands and forests. We tested whether these metrics improve fire risk mapping using three machine learning (ML) algorithms (Logistic Regression, Random Forest, and XGBoost). We chose the 2007 wildfires in Greece for the analysis. Our results indicate that XGBoost, which accounts for variable interactions and non-linear effects, was the ML model that produced the best results. NDVIW improved the model performance, while NDVIT was significant only when NDVIW was high. This NDVIW–NDVIT interaction means that the long-term dryness effect is meaningful only in places of dense woody vegetation. The proposed method can produce more accurate fire risk maps than conventional methods and can supply important dynamic information that may be used in fire behavior models.
Xue, B. ; Wang, G. ; Xiao, J. ; Helman, D. ; Sun, W. ; Wang, J. ; Liu, T. Global convergence but regional disparity in the hydrological resilience of ecosystems and watersheds to drought. 2020, 591, 125589. Publisher's VersionAbstract
Drought is a major climate disturbance that can lower vegetation productivity and induce widespread vegetation die-off, which in turn can have a profound effect on the water cycle. Therefore, quantification of vegetation-specific responses to drought is essential to predict the impacts of climate change on ecosystem services. We used two previously-suggested quantitative metrics – dynamic deviation (d) and elasticity (e) based on the Budyko framework –to evaluate site- and watershed-level hydrological resilience of different plant functional types (PFTs) to drought. By using data from 41 FLUXNET sites and 2275 watersheds, we found a global convergence in hydrological resilience to drought across a variety of PFTs. Hydrological resilience of vegetation was related to drought intensity and water use efficiency. A greater hydrological resilience was found in PTFs in drier areas than in wetter areas, while this greater hydrological resilience was related to the coefficient of variation in precipitation. We also found that PFTs with a larger water use efficiency had higher hydrological resilience, particularly in drier regions, indicating adaptation strategies to changes in local climate conditions. Our findings can shed light on how ecosystems and watersheds dominated by different PFTs will respond to future climatic change and inform water resources management.
Helman, D. ; Zaitchik, B. F. ; Funk, C. Climate has contrasting direct and indirect effects on armed conflicts. Environmental Research Letters 2020, 15, 104017. Publisher's VersionAbstract
There is an active debate regarding the influence that climate has on the risk of armed conflict, which stems from challenges in assembling unbiased datasets, competing hypotheses on the mechanisms of climate influence, and the difficulty of disentangling direct and indirect climate effects. We use gridded historical non-state conflict records, satellite data, and land surface models in a structural equation modeling approach to uncover the direct and indirect effects of climate on violent conflicts in Africa and the Middle East (ME). We show that climate–conflict linkages in these regions are more complex than previously suggested, with multiple mechanisms at work. Warm temperatures and low rainfall direct effects on conflict risk were stronger than indirect effects through food and water supplies. Warming increases the risk of violence in Africa but unexpectedly decreases this risk in the ME. Furthermore, at the country level, warming decreases the risk of violence in most West African countries. Overall, we find a non-linear response of conflict to warming across countries that depends on the local temperature conditions. We further show that magnitude and sign of the effects largely depend on the scale of analysis and geographical context. These results imply that extreme caution should be exerted when attempting to explain or project local climate–conflict relationships based on a single, generalized theory.
Helman, D. ; Zaitchik, B. F. Temperature anomalies affect violent conflicts in African and Middle Eastern warm regions. 2020, 63, 102118. Publisher's VersionAbstract
Several studies have linked high temperatures to increases in violent conflicts. The findings are controversial, however, as there has been no systematic cross-sectional analysis performed to demonstrate the generality of the proposed relationship. Moreover, the timescale of temperature/violence relationships have not been fully investigated; it is unclear how short versus long-term, or seasonal and inter-annual temperature variability contribute to the likelihood or frequency of violent events. We here perform systematic regional and grid-based longitudinal analyses in Africa and the Middle East for the period 1990–2017, using geolocated information on armed conflicts and a recently released satellite-based gridded temperature data set. We find seasonal synchrony between temperature and number of armed conflicts at the regional scale (climatic region), as well as a positive relationship in temperature and conflict anomalies on inter-annual timescales at the grid cell level (for the entire African and ME region). After controlling for ‘location effects’, we do not find that long-term warming has affected armed conflicts for the last three decades. However, the effects of temperature anomalies are stronger in warmer places (~5% increase per 10 °C, P < 0.05), suggesting that populations living in warmer places are more sensitive to temperature deviations. Taken together, these findings imply that projected warming and increasing temperature variability may enhance violence in these regions, though the mechanisms of the relationships still need to be exposed.
Helman, D. ; Mussery, A. Using Landsat satellites to assess the impact of check dams built across erosive gullies on vegetation rehabilitation. 2020, 730, 138873. Publisher's VersionAbstract
Gully erosion, a process of soil removal due to water accumulation and runoff, is a worldwide problem affecting agricultural lands. Building check dams perpendicular to the flow direction is one of the suggested control practices to stabilize this process. Though there are many studies on the effect of erosive controls on land stabilization, few examine its effect on the rehabilitation of vegetation. Here we use information from the satellites Landsat-7 (1999–2018) and Landsat-8 (2013–2018) to assess the effect of soil check dams built during 2012 across three gullies with distinct structures in a dryland area on vegetative cover and water status. We use a time series analysis technique to decompose Landsat-derived soil adjusted vegetation index (SAVI) into woody (SAVIW) and herbaceous (iSAVIH) contributions. The integral over the seasonal signal of the normalized difference water index (iNDWI) was used to assess changes in water status in the gully. We used herbaceous biomass collected in the field in 2014–2017 to validate iSAVIH as a proxy of herbaceous biomass. Our results show that following the construction of the check dams, the change in woody vegetation cover is best described by a sigmoid model with an increase of ~57% (95% CI: 39%–76%; p < 0.0001), while the herbaceous vegetation increases linearly at a rate of ~71% per year (95% CI: 48%–93% y−1; p < 0.0001). The correlation between iSAVIH and herbaceous biomass (R2 = 0.56; n = 16; p < 0.001) corroborates this increase. We found higher herbaceous productivity in the deeper gully compared to the shallower gullies but not statistically different increase rates. An increase in iNDWI of ~68% (95% CI: 43%–95%; p < 0.0001) likely implies an improved water infiltration rate that favored the vegetation expansion. Our satellite-based approach can be used to assess the impact of erosive control practices on vegetation rehabilitation in heterogeneous gullies.
Mor-Mussery, A. ; Helman, D. ; Agmon, Y. ; Ben-Shabat, I. ; El-Frejat, S. ; Golan, D. G. The indigenous Bedouin farmers as land rehabilitators—Setup of an action research programme in the Negev. Land Degradation & DevelopmentLand Degradation & DevelopmentLand Degrad Dev 2020, n/a. Publisher's VersionAbstract
Abstract The Negev suffers from enhanced land degradation, mostly due to lack of awareness about its state, and hostility between the region's indigenous Bedouin farmers and the authorities. In order to examine a potential solution to this 'Lose?Lose' situation, a unique project is underway, with the collaboration of the Yeroham Municipality and the adjacent Rahma Bedouin farmers' village. The concept of this ongoing Programme is based on bidirectional knowledge transfer of farming data between the farmers and land scientists, aimed to adapt Bedouin traditional cultivation methods and transform them into methods that restore the environment and are also profitable. In order to reach this goal, a highly knowledgeable Bedouin liaison person was appointed to carry out the project together with the Coordinating Team. A comprehensive study and tour were carried out in order to analyze the different landforms and Bedouin cultivation preferences. An initial survey was carried out and data from literature collected in order to determine the ecological and archaeological characteristics of the ecosystem. The area was then prepared for agricultural utilization by removing widespread garbage and dealing with wadis that have been filled with construction waste. This project, which integrates soil enhancement, agriculture utilization, and traditional Bedouin farming, aims for rehabilitation of the northern Negev gullied areas. However, the implementation of the study concept in the field is accompanied by many challenges related to Bedouin interclan communication and the diverse types of degraded lands.
Grodek, T. ; Morin, E. ; Helman, D. ; Lensky, I. ; Dahan, O. ; Seely, M. ; Benito, G. ; Enzel, Y. Eco-hydrology and geomorphology of the largest floods along the hyperarid Kuiseb River, Namibia. Journal of Hydrology 2020, 582, 124450. Publisher's VersionAbstract
Flood-fed aquifers along the sandy lower reach of the Kuiseb River sustain a 130-km-long green belt of lush oases across the hyperarid Namib desert. This oasis is a year-round source for water creating dense-tall woodland along the narrow corridor of the ephemeral river valley, which, in turn, supports human activity and fauna including during the long dry austral winters and multi-year droughts. Occasional floods, originating at the river’s wetter headwaters, travel ∼280 km downstream, before recharging these aquifers. We analyzed the flood-aquifer-vegetation dynamics at-a-site and along the river, determining the relative impact of floods with diverse magnitude and frequency on downstream reaches. We find that flood discharge that feeds the alluvial aquifers also affects vegetation dynamics along the river. The downstream aquifers are fed only by the largest floods that allow the infrequent germination of plants; mean annual recharge volume is too low to support the aquifers level. These short-term vegetation cycles of green-up and then fast senescence in-between floods are easily detected by satellite-derived vegetation index. This index identifies historical floods and their magnitudes in arid and hyperarid regions; specifically, it determines occurrences of large floods in headwater-fed, ephemeral Namib streams as well as in other hyperarid regions. Our study reveals the importance of flood properties on the oasis life cycle, emphasizing the impact of drought and wet years on the Namib’s riparian vegetation.
Ott, R. F. ; Gallen, S. F. ; Caves Rugenstein, J. K. ; Ivy-Ochs, S. ; Helman, D. ; Fassoulas, C. ; Vockenhuber, C. ; Christl, M. ; Willett, S. D. Chemical Versus Mechanical Denudation in Meta-Clastic and Carbonate Bedrock Catchments on Crete, Greece, and Mechanisms for Steep and High Carbonate Topography. Journal of Geophysical Research: Earth Surface 2019, 124. Publisher's VersionAbstract
Abstract On Crete—as is common elsewhere in the Mediterranean—carbonate massifs form high mountain ranges whereas topography is lower in areas with meta-clastic rocks. This observation suggests that differences in denudational processes between carbonate-rich rocks and quartzofeldspathic units impart a fundamental control on landscape evolution. Here we present new cosmogenic basin-average denudation rate measurements from both 10Be and 36Cl in meta-clastic and carbonate bedrock catchments, respectively, to assess relationships between denudation rates, processes, and topographic form. We compare total denudation rates to dissolution rates calculated from 49 new and previously published water samples. Basin-average denudation rates of meta-clastic and carbonate catchments are similar, with mean values of  0.10 mm/a and  0.13 mm/a, respectively. The contribution of dissolution to total denudation rate was <10% in the one measured meta-clastic catchment, and  40% for carbonate catchments ( 0.05 mm/a), suggesting the dominance of physical over chemical weathering at the catchment scale in both rock types. Water mass-balance calculations for three carbonate catchments suggests 40–90% of surface runoff is lost to groundwater. To explore the impact of dissolution and infiltration to groundwater on relief, we develop a numerical model for carbonate denudation. We find that dissolution modifies the river profile channel steepness, and infiltration changes the fluvial response time to external forcing. Furthermore, we show that infiltration of surface runoff to groundwater in karst regions is an efficient way to steepen topography and generate the dramatic relief in carbonates observed throughout Crete and the Mediterranean.
Helman, D. ; Lensky, I. M. ; Bonfil, D. J. Early prediction of wheat grain yield production from root-zone soil water content at heading using Crop RS-Met. Field Crops Research 2019, 232, 11 - 23. Publisher's VersionAbstract
Wheat production in drylands is determined greatly by the available water at the critical growth stages. In dry years, farmers usually face the dilemma of whether to harvest at an early stage for hay or silage, with reduced profit, or leave the crop for grain production with the risk of a major economic loss. Thus, an early prediction of potential wheat grain yield production is essential for agricultural decision making, particularly in water-limited areas. Here, we test whether using a proximal-based biophysical model of actual evapotranspiration (water use) and root-zone soil water content (SWC) – Crop RS-Met – may assist in providing early grain yield predictions in dryland wheat fields. Crop RS-Met was examined in eight experimental fields comprising a variety of spring wheat (Triticum aestivum L.) cultivars exposed to different treatments and amounts of water supply (185 mm - 450 mm). Crop RS-Met was first validated against SWC measurements at the root-zone profile. Then, modeled SWC at heading (SWCHeading) was regressed against end-of-season grain yields (GYEOS), which ranged from 1.30 tons ha−1 to 7.12 tons ha−1, for a total of 56 treatment blocks in 4 seasonal years (2014–2017). Results show that Crop RS-Met accurately reproduce seasonal changes in SWC with an average R2 of 0.89 ± 0.05 and RMSE and bias of 0.014 ± 0.004 m3 m−3 and -0.002 ± 0.004 m3 m−3, respectively. Modeled SWCHeading showed high and significant positive linear relationship with GYEOS (GYEOS[tons ha-1] = 0.080×SWCHeading[mm] - 5.387; R2 = 0.90; P < 0.001; N=56). Moreover, Crop RS-Met showed to be capable of accurately predicting GYEOS even in cases where water supply and grain yield had adverse relationships. Aggregating results to the field-scale level and classifying fields per water supply conditions resulted in an even stronger linear relationship (R2 = 0.94; P < 0.001; N=9). We conclude that Crop RS-Met may be used to predict GYEOS at heading in dryland fields for possible use by farmers in decision making at critical wheat growth stages.
Helman, D. ; Bonfil, D. J. ; Lensky, I. M. Crop RS-Met: A biophysical evapotranspiration and root-zone soil water content model for crops based on proximal sensing and meteorological data. Agricultural Water Management 2019, 211, 210 - 219. Publisher's VersionAbstract
Assessing crops water use is essential for agricultural water management and planning, particularly in water-limited regions. Here, we present a biophysical model to estimate crop actual evapotranspiration and root-zone soil water content using proximal sensing and meteorological data (Crop RS-Met). The model, which is based on the dual FAO56 formulation, uses a water deficit factor calculated from rainfall and atmospheric demand information to constrain actual evapotranspiration and soil water content in crops growing under dry conditions. We tested the Crop RS-Met model in a dryland experimental field comprising a variety of wheat (Triticum aestivum L. and T. durum) cultivars with diverse phenology. Crop RS-Met was shown to accurately capture seasonal changes in wheat water use during the growing season. The average R2 of modeled vs. observed soil water content for all cultivars (N = 11) was 0.92 ± 0.02 with average relative RMSE and bias of 9.29 ± 1.30% and 0.13 ± 0.03%, respectively. We found that changing the integration time period of the water deficit factor in Crop RS-Met affects the accuracy of the model implying that this factor has a vital role in modeling crop water use under dry conditions. Currently, Crop RS-Met has a simple representation of surface runoff and does not take into consideration heterogeneity in the soil profile. Thus, efforts to combine numerical models that simulate soil water dynamics with a Crop RS-Met model driven by high-resolution remote sensing data may be needed for a spatially continuous assessment of crop water use in fields with more complex edaphic characteristics.
Miller, O. ; Helman, D. ; Svoray, T. ; Morin, E. ; Bonfil, D. J. Explicit wheat production model adjusted for semi-arid environments. Field Crops Research 2019, 231, 93 - 104. Publisher's VersionAbstract
Current literature suggests that wheat production models are limited either to wide-scale or plot-based predictions ignoring pattern of habitat conditions and surficial hydrological processes. We present here a high-spatial resolution (50 m) non-calibrated GIS-based wheat production model for predictions of aboveground wheat biomass (AGB) and grain yield (GY). The model is an integration of three sub-models, each simulating elemental processes relevant for wheat growth dynamics in water-limited environments: (1) HYDRUS-1D, a finite element model that simulates one-dimensional movement of water in the soil profile; (2) a two-dimensional GIS-based surface runoff model; and (3) a one-dimensional process-driven mechanistic wheat growth model. By integrating the three sub-models, we aimed to achieve a more accurate spatially continuous water balance simulation with a better representation of root zone soil water content (SWC) impacts on plant development. High-resolution grid-based rainfall data from a meteorological radar system were used as input to HYDRUS-1D. Twenty-two commercial wheat fields in Israel were used to validate the model in two seasons (2010/11 and 2011/12). Results show that root zone SWC was accurately simulated by HYDRUS-1D in both seasons, particularly at the top 10-cm soil layer. Observed vs simulated AGB and GY were highly correlated with R2 = 0.93 and 0.72 (RMSE = 171 g m−2 and 70 g m−2) having low biases of -41 g m−2 (8%) and 52 g m−2 (10%), respectively. Model sensitivity test showed that HYDRUS-1D was mainly driven by spatial variability in the input soil characteristics while the integrated wheat production model was mostly affected by rainfall spatial variability indicating the importance of using accurate high-resolution rainfall data as model input. Using the integrated model, we predict decreases in AGB and GY of c. 10.5% and c. 12%, respectively, for 1 °C of warming and c. 7.7% and c. 7.3% for 5% reduction in rainfall amount in our study sites. The suggested model could be used by scientists to better understand the causes of spatial and temporal variability in wheat production and the consequences of future scenarios such as climate change.