Physical and Environmental Geography Commons^™

Reanalysis Data Underestimate Significant Changes In Growing Season Weather In Kazakhstan, C. K. Wright, K. M. De Beurs, Z. K. Akhmadiyeva, P. Y. Groisman, G. M. Henebry

Geoffrey Henebry

We present time series analyses of recently compiled climate station data which allowed us to assess contemporary trends in growing season weather across Kazakhstan as drivers of a significant decline in growing season normalized difference vegetation index (NDVI) recently observed by satellite remote sensing across much of Central Asia. We used a robust nonparametric time series analysis method, the seasonal Kendall trend test to analyze georeferenced time series of accumulated growing season precipitation (APPT) and accumulated growing degree-days (AGDD). Over the period 2000–2006 we found geographically extensive, statistically significant (p < 0.05) decreasing trends in APPT and increasing trends in AGDD. The temperature trends were especially apparent during the warm season and coincided with precipitation decreases in northwest Kazakhstan, indicating that pervasive drought conditions and higher temperature excursions were the likely drivers of NDVI declines observed in Kazakhstan over the same period. We also compared the APPT and AGDD trends at individual stations with results from trend analysis of gridded monthly precipitation data from the Global Precipitation Climatology Centre (GPCC) Full Data Reanalysis v4 and gridded daily near surface air temperature from the National Centers for Climate Prediction Reanalysis v2 (NCEP R2). We found substantial deviation between the station and the reanalysis trends, suggesting that GPCC and NCEP data substantially underestimate the geographic extent of recent drought in Kazakhstan. Although gridded climate products offer many advantages in ease of use and complete coverage, our findings for Kazakhstan should serve as a caveat against uncritical use of GPCC and NCEP reanalysis data and demonstrate the importance of compiling and standardizing daily climate data from data-sparse regions like Central Asia.

Land Surface Phenologies And Seasonalities Using Cool Earthlight In Mid-Latitude Croplands, W. G. Alemu, G. M. Henebry

Geoffrey Henebry

Phenology deals with timing of biotic phenomena and seasonality concerns temporal patterns of abiotic variables. Studies of land surface phenology (LSP) and land surface seasonality (LSS) have long been limited to visible to near infrared (VNIR) wavelengths, despite degradation by atmospheric effects and solar illumination constraints. Enhanced land surface parameters derived from passive microwave data enable improved temporal monitoring of agricultural land surface dynamics compared to the vegetation index data available from VNIR data. LSPs and LSSs in grain growing regions of the Volga River Basin of Russia and the spring wheat belts of the USA and Canada were characterized …

Spatial And Seasonal Responses Of Precipitation In The Ganges And Brahmaputra River Basins To Enso And Indian Ocean Dipole Modes: Implications For Flooding And Drought, M. S. Pervez, G. M. Henebry

Geoffrey Henebry

We evaluated the spatial and seasonal responses of precipitation in the Ganges and Brahmaputra basins as modulated by the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) modes using Global Precipitation Climatology Centre (GPCC) full data reanalysis of monthly global land-surface precipitation data from 1901 to 2010 with a spatial resolution of 0.5° × 0.5°. The GPCC monthly total precipitation climatology targeting the period 1951–2000 was used to compute gridded monthly anomalies for the entire time period. The gridded monthly anomalies were averaged for the years influenced by combinations of climate modes. Occurrences of El Niño alone significantly …

Remote Sensing-Based Time Series Models For Malaria Early Warning In The Highlands Of Ethiopia, A. Midekisa, G. Senay, G. M. Henebry, P. Semuniguse, M. C. Wimberly

Geoffrey Henebry

Background

Malaria is one of the leading public health problems in most of sub-Saharan Africa, particularly in Ethiopia. Almost all demographic groups are at risk of malaria because of seasonal and unstable transmission of the disease. Therefore, there is a need to develop malaria early-warning systems to enhance public health decision making for control and prevention of malaria epidemics. Data from orbiting earth-observing sensors can monitor environmental risk factors that trigger malaria epidemics. Remotely sensed environmental indicators were used to examine the influences of climatic and environmental variability on temporal patterns of malaria cases in the Amhara region of Ethiopia. …

Change And Persistence In Land Surface Phenologies Of The Don And Dnieper River Basins, V. Kovalskyy, G. M. Henebry

Geoffrey Henebry

The formal collapse of the Soviet Union at the end of 1991 produced major socio-economic and institutional dislocations across the agricultural sector. The picture of broad scale patterns produced by these transformations continues to be discovered. We examine here the patterns of land surface phenology (LSP) within two key river basins—Don and Dnieper—using AVHRR (Advanced Very High Resolution Radiometer) data from 1982 to 2000 and MODIS (Moderate Resolution Imaging Spectroradiometer) data from 2001 to 2007. We report on the temporal persistence and change of LSPs as summarized by seasonal integration of NDVI (normalized difference vegetation index) time series using accumulated …

Dual Scale Trend Analysis Distinguishes Climatic From Anthropogenic Effects On The Vegetated Land Surface, K. M. De Beurs, C. K. Wright, G. M. Henebry

Geoffrey Henebry

We present a dual scale trend analysis for characterizing and comparing two contrasting areas of change in Russia and Kazakhstan that lie less than 800 km apart. We selected a global NASA MODIS (moderate resolution imaging spectroradiometer) product (MCD43C4 and MCD43A4) at a 0.05◦ (∼5.6 km) and 500 m spatial resolution and a 16-day temporal resolution from 2000 to 2008. We applied a refinement of the seasonal Kendall trend method to the normalized difference vegetation index (NDVI) image series at both scales. We only incorporated composites during the vegetative growing season which was delineated by start of season and end …

Evaluation Of A Coupled Event-Driven Phenology And Evapotranspiration Model For Croplands In The United States Northern Great Plains, V. Kovalskyy, G. M. Henebry, D. P. Roy, B. Adusei, M. Hansen, G. Senay, D. M. Mocko

Geoffrey Henebry

A new model coupling scheme with remote sensing data assimilation was developed for estimation of daily actual evapotranspiration (ET). The scheme consists of the VegET, a model to estimate ET from meteorological and water balance data, and an Event Driven Phenology Model (EDPM), an empirical crop specific model trained on multiple years of flux tower data transformed into six types of environmental forcings that are called “events” to emphasize their temporally discrete character, which has advantages for modeling multiple contingent influences. The EDPM in prognostic mode supplies seasonal trajectories of normalized difference vegetation index (NDVI); whereas in diagnostic mode, it …

Evapotranspiration In The Nile Basin: Identifying Dynamics, Trends, And Drivers 2002-2011, H. Alemu, A. T. Kaptué, G. B. Senay, M. C. Wimberly, Geoffrey Henebry

Geoffrey Henebry

Analysis of the relationship between evapotranspiration (ET) and its natural and anthropogenic drivers is critical in water-limited basins such as the Nile. The spatiotemporal relationships of ET with rainfall and vegetation dynamics in the Nile Basin during 2002–2011 were analyzed using satellite-derived data. Non-parametric statistics were used to quantify ET-rainfall interactions and trends across land cover types and subbasins. We found that 65% of the study area (2.5 million km2) showed significant (p < 0.05) positive correlations between monthly ET and rainfall, whereas 7% showed significant negative correlations. As expected, positive ET-rainfall correlations were observed over natural vegetation, mixed croplands/natural vegetation, and croplands, with a few subbasin-specific exceptions. In particular, irrigated croplands, wetlands and some forests exhibited negative correlations. Trend tests revealed spatial clusters of statistically significant trends in ET (6% of study area was negative; 12% positive), vegetation greenness (24% negative; 12% positive) and rainfall (11% negative; 1% positive) during 2002–2011. The Nile Delta, Ethiopian highlands and central Uganda regions showed decline in ET while central parts of Sudan, South Sudan, southwestern Ethiopia and northeastern Uganda showed increases. Except for a decline in ET in central Uganda, the detected changes in ET (both positive and negative) were not associated with corresponding changes in rainfall. Detected declines in ET in the Nile delta and Ethiopian highlands were found to be attributable to anthropogenic land degradation, while the ET decline in central Uganda is likely caused by rainfall reduction.

Assessing The Impacts Of Climate And Land Use And Land Cover Change On The Freshwater Availability In The Brahmaputra River Basin, M. S. Pervez, G. M. Henebry

Geoffrey Henebry

Study Region: Brahmaputra River basin in South Asia.

Study Focus: The Soil and Water Assessment Tool was used to evaluate sensitivities and patterns in freshwater availability due to projected climate and land use changes in the Brahmaputra basin. The daily observed discharge at Bahadurabad station in Bangladesh was used to calibrate and validate the model and analyze uncertainties with a sequential uncertainty fitting algorithm. The sensitivities and impacts of projected climate and land use changes on basin hydrological components were simulated for the A1B and A2 scenarios and analyzed relative to a baseline scenario of 1988–2004.

New hydrological insights for …

Alternative Methods To Predict Actual Evapotranspiration Illustrate The Importance Of Accounting For Phenology: The Event Driven Phenology Model Part Ii, V. Kovalskyy, G. M. Henebry

Geoffrey Henebry

Evapotranspiration (ET) flux constitutes a major component of both the water and energy balances at the land surface. Among the many factors that control evapotranspiration, phenology poses a major source of uncertainty in attempts to predict ET. Contemporary approaches to ET modeling and monitoring frequently summarize the complexity of the seasonal development of vegetation cover into static phenological trajectories (or climatologies) that lack sensitivity to changing environmental conditions. The Event Driven Phenology Model (EDPM) offers an alternative, interactive approach to representing phenology. This study presents the results of an experiment designed to illustrate the differences in ET arising from various …

A New Concept For Simulation Of Vegetated Land Surface Dynamics: The Event Driven Phenology Model Part I, V. Kovalskyy, G. M. Henebry

Geoffrey Henebry

Phenologies of the vegetated land surface are being used increasingly for diagnosis and prognosis of climate change consequences. Current prospective and retrospective phenological models stand far apart in their approaches to the subject. We report on an exploratory attempt to implement a phenological model based on a new event driven concept which has both diagnostic and prognostic capabilities in the same modeling framework. This Event Driven Phenological Model (EDPM) is shown to simulate land surface phenologies and phenophase transition dates in agricultural landscapes based on assimilation of weather data and land surface observations from spaceborne sensors. The model enables growing …

A New Approach For The Analysis Of Hyperspectral Data: Theory And Sensitivity Analysis Of The Moment Distance Method, E.A. L. Salas, G. M. Henebry

Geoffrey Henebry

We present the Moment Distance (MD) method to advance spectral analysis in vegetation studies. It was developed to take advantage of the information latent in the shape of the reflectance curve that is not available from other spectral indices. Being mathematically simple but powerful, the approach does not require any curve transformation, such as smoothing or derivatives. Here, we show the formulation of the MD index (MDI) and demonstrate its potential for vegetation studies. We simulated leaf and canopy reflectance samples derived from the combination of the PROSPECT and SAIL models to understand the sensitivity of the new method to …

Proceedings Of The Workshop On Spatio-Temporal Data Models Of Biogeophysical Fields For Ecological Forecasting, Geoffrey Henebry, Jan Chomicki, Tony Fountain

Geoffrey Henebry