Naga Manohar Velpuri

Influence of resolution in irrigated area mapping and area estimation

The overarching goal of this paper was to determine how irrigated areas change with resolution (or scale) of imagery. Specific objectives investigated were to (a) map irrigated areas using four distinct spatial resolutions (or scales), (b) determine how irrigated areas change with resolutions, and (c) establish the causes of differences in resolution-based irrigated areas. The study was conducted in the very large Krishna River basin (India), which has a high degree of formal contiguous, and informal fragmented irrigated areas. The irrigated areas were mapped using satellite sensor data at four distinct resolutions: (a) NOAA AVHRR Pathfinder 10,000 m, (b) Terra MODIS 500 m, (c) Terra MODIS 250 m, and (d) Landsat ETM 30 m. The proportion of irrigated areas relative to Landsat 30 m derived irrigated areas (9.36 million hectares for the Krishna basin) were (a) 95 percent using MODIS 250 m, (b) 93 percent using MODIS 500 m, and (c) 86 percent using AVHRR 10,000 m. In this study, it was found that the precise location of the irrigated areas were better established using finer spatial resolution data. A strong relationship (R 2 0.74 to 0.95) was observed between irrigated areas determined using various resolutions. This study proved the hypotheses that “the finer the spatial resolution of the sensor used, greater was the irrigated area derived,” since at finer spatial resolutions, fragmented areas are detected better. Accuracies and errors were established consistently for three classes (surface water irrigated, ground water/conjunctive use irrigated, and nonirrigated) across the four resolutions mentioned above. The results showed that the Landsat data provided significantly higher overall accuracies (84 percent) when compared to MODIS 500 m (77 percent), MODIS 250 m (79 percent), and AVHRR 10,000 m (63 percent).

Actual evapotranspiration (water use) assessment of the Colorado River Basin at the Landsat resolution using the operational simplified surface energy balance model

Accurately estimating consumptive water use in the Colorado River Basin (CRB) is important for assessing and managing limited water resources in the basin. Increasing water demand from various sectors may threaten long-term sustainability of the water supply in the arid southwestern United States. We have developed a first-ever basin-wide actual evapotranspiration (ETa) map of the CRB at the Landsat scale for water use assessment at the field level. We used the operational Simplified Surface Energy Balance (SSEBop) model for estimating ETa using 328 cloud-free Landsat images acquired during 2010. Our results show that cropland had the highest ETa among all land cover classes except for water. Validation using eddy covariance measured ETa showed that the SSEBop model nicely captured the variability in annual ETa with an overall R2 of 0.78 and a mean bias error of about 10%. Comparison with water balance-based ETa showed good agreement (R2 = 0.85) at the sub-basin level. Though there was good correlation (R2 = 0.79) between Moderate Resolution Imaging Spectroradiometer (MODIS)-based ETa (1 km spatial resolution) and Landsat-based ETa (30 m spatial resolution), the spatial distribution of MODIS-based ETa was not suitable for water use assessment at the field level. In contrast, Landsat-based ETa has good potential to be used at the field level for water management. With further validation using multiple years and sites, our methodology can be applied for regular production of ETa maps of larger areas such as the conterminous United States.

Analysis of long-term trends (1950-2009) in precipitation, runoff and runoff coefficient in major urban watersheds in the United States

This study investigates the long-term trends in precipitation, runoff and runoff coefficient in major urban watersheds in the United States. The seasonal Mann‐Kendall trend test was performed on monthly precipitation, runoff and runoff coefficient data from 1950 to 2009 obtained from 62 urban watersheds covering 21 major urban centers in the United States. The results indicate that only five out of 21 urban centers in the United States showed an uptrend in precipitation. Twelve urban centers showed an uptrend in runoff coefficient. However, six urban centers did not show any trend in runoff coefficient, and three urban centers showed a significant downtrend. The highest rate of change in precipitation, runoff and runoff coefficient was observed in the Houston urban watershed. Based on the results obtained, we also attributed plausible causes for the trends. Our analysis indicated that while a human only influence is observed in most of the urban watersheds, a combined climate and human influence is observed in the central United States.

Drought Monitoring and Assessment: Remote Sensing and Modeling Approaches for the Famine Early Warning Systems Network

Abstract Drought monitoring is an essential component of drought risk management. It is usually carried out using drought indices/indicators that are continuous functions of rainfall and other hydrometeorological variables. This chapter presents a few examples of how remote sensing and hydrologic modeling techniques are being used to generate a suite of drought monitoring indicators at dekadal (10-day), monthly, seasonal, and annual time scales for several selected regions around the world. Satellite-based rainfall estimates are being used to produce drought indicators such as standardized precipitation index, dryness indicators, and start of season analysis. The Normalized Difference Vegetation Index is being used to monitor vegetation condition. Several satellite data products are combined using agrohydrologic models to produce multiple short- and long-term indicators of droughts. All the data sets are being produced and updated in near-real time to provide information about the onset, progression, extent, and intensity of drought conditions. The data and products produced are available for download from the Famine Early Warning Systems Network (FEWS NET) data portal at http://earlywarning.usgs.gov . The availability of timely information and products support the decision-making processes in drought-related hazard assessment, monitoring, and management with the FEWS NET. The drought-hazard monitoring approach perfected by the U.S. Geological Survey for FEWS NET through the integration of satellite data and hydrologic modeling can form the basis for similar decision support systems. Such systems can operationally produce reliable and useful regional information that is relevant for local, district-level decision making.

Understanding the hydrologic sources and sinks in the Nile Basin using multisource climate and remote sensing data sets

In this study, we integrated satellite-drived precipitation and modeled evapotranspiration data (2000–2012) to describe spatial variability of hydrologic sources and sinks in the Nile Basin. Over 2000–2012 period, 4 out of 11 countries (Ethiopia, Tanzania, Kenya, and Uganda) in the Nile Basin showed a positive water balance while three downstream countries (South Sudan, Sudan, and Egypt) showed a negative balance. Gravity Recovery and Climate Experiment (GRACE) mass deviation in storage data analysis showed that at annual timescales, the Nile Basin storage change is substantial while over longer time periods, it is minimal (<1% of basin precipitation). We also used long-term gridded runoff and river discharge data (1869–1984) to understand the discrepancy in the observed and expected flow along the Nile River. The top three countries that contribute most to the flow are Ethiopia, Tanzania, and Kenya. The study revealed that ∼85% of the runoff generated in the equatorial region is lost in an interstation basin that includes the Sudd wetlands in South Sudan; this proportion is higher than the literature reported loss of 50% at the Sudd wetlands alone. The loss in runoff and flow volume at different sections of the river tend to be more than what can be explained by evaporation losses, suggesting a potential recharge to deeper aquifers that are not connected to the Nile channel systems. On the other hand, we also found that the expected average annual Nile flow at Aswan is greater (97 km3) than the reported amount (84 km3). Due to the large variations of the reported Nile flow at different locations and time periods, the study results indicate the need for increased hydrometeorological instrumentation of the basin. The study also helped improve our understanding of the spatial dynamics of water sources and sinks in the Nile Basin and identified emerging hydrologic questions that require further attention.

Evaluating New SMAP Soil Moisture for Drought Monitoring in the Rangelands of the US High Plains

On the Ground Level 3 soil moisture datasets from the recently launched Soil Moisture Active Passive (SMAP) satellite are evaluated for drought monitoring in rangelands. Validation of SMAP soil moisture (SSM) with in situ and modeled estimates showed high level of agreement. SSM showed the highest correlation with surface soil moisture (0–5 cm) and a strong correlation to depths up to 20 cm. SSM showed a reliable and expected response of capturing seasonal dynamics in relation to precipitation, land surface temperature, and evapotranspiration. Further evaluation using multi-year SMAP datasets is necessary to quantify the full benefits and limitations for drought monitoring in rangelands.

Assessing the potential hydrological impact of the Gibe III Dam on Lake Turkana water level using multi-source satellite data

Lake Turkana, the largest desert lake in the world, is fed by ungauged or poorly gauged river systems. To meet the demand of electricity in the East African region, Ethiopia is currently building the Gibe III hydroelectric dam on the Omo River, which supplies more than 80 % of the inflows to Lake Turkana. On completion, the Gibe III dam will be the tallest dam in Africa with a height of 241 m. However, the nature of interactions and potential impacts of regulated inflows to Lake Turkana are not well understood due to its remote location and unavailability of reliable in situ datasets. In this study, we used 12 yr (1998–2009) of existing multisource satellite and model-assimilated global weather data. We used a calibrated multi-source satellite data-driven water balance model for Lake Turkana that takes into account model routed runoff, lake/reservoir evapotranspiration, direct rain on lakes/reservoirs and releases from the dam to compute lake water levels. The model evaluates the impact of the Gibe III dam using three different approaches – a historical approach, a rainfall based approach, and a statistical approach to generate rainfall-runoff scenarios. All the approaches provided comparable and consistent results. Model results indicated that the hydrological impact of the Gibe III dam on Lake Turkana would vary with the magnitude and distribution of rainfall post-dam commencement. On average, the reservoir would take up to 8–10 months, after commencement, to reach a minimum operation level of 201 m depth of water. During the dam filling period, the lake level would drop up to 1–2 m (95 % confidence) compared to the lake level modeled without the dam. The lake level variability caused by regulated inflows after the dam commissioning were found to be within the natural variability of the lake of 4.8 m. Moreover, modeling results indicated that the hydrological impact of the Gibe III dam would depend on the initial lake level at the time of dam commencement. Areas along the Lake Turkana shoreline that are vulnerable to fluctuations in lake levels due to the Gibe III dam were also identified. This study demonstrates the effectiveness of using existing multi-source satellite data in a basic modeling framework to assess the potential hydrological impact of an upstream dam on a terminal downstream lake. The results obtained from this study could also be used to evaluate alternative damfilling scenarios and assess the potential impact of the dam on Lake Turkana under different operational strategies.

On the Downscaling of Actual Evapotranspiration Maps Based on Combination of MODIS and Landsat-Based Actual Evapotranspiration Estimates

Downscaling is one of the important ways of utilizing the combined benefits of the high temporal resolution of Moderate Resolution Imaging Spectroradiometer (MODIS) images and fine spatial resolution of Landsat images. We have evaluated the output regression with intercept method and developed the Linear with Zero Intercept (LinZI) method for downscaling MODIS-based monthly actual evapotranspiration (AET) maps to the Landsat-scale monthly AET maps for the Colorado River Basin for 2010. We used the 8-day MODIS land surface temperature product (MOD11A2) and 328 cloud-free Landsat images for computing AET maps and downscaling. The regression with intercept method does have limitations in downscaling if the slope and intercept are computed over a large area. A good agreement was obtained between downscaled monthly AET using the LinZI method and the eddy covariance measurements from seven flux sites within the Colorado River Basin. The mean bias ranged from −16 mm (underestimation) to 22 mm (overestimation) per month, and the coefficient of determination varied from 0.52 to 0.88. Some discrepancies between measured and downscaled monthly AET at two flux sites were found to be due to the prevailing flux footprint. A reasonable comparison was also obtained between downscaled monthly AET using LinZI method and the gridded FLUXNET dataset. The downscaled monthly AET nicely captured the temporal variation in sampled land cover classes. The proposed LinZI method can be used at finer temporal resolution (such as 8 days) with further evaluation. The proposed downscaling method will be very useful in advancing the application of remotely sensed images in water resources planning and management.

Establishing an operational waterhole monitoring system using satellite data and hydrologic modelling: Application in the pastoral regions of East Africa

Timely information on the availability of water and forage is important for the sustainable development of pastoral regions. The lack of such information increases the dependence of pastoral communities on perennial sources, which often leads to competition and conflicts. The provision of timely information is a challenging task, especially due to the scarcity or non-existence of conventional station-based hydrometeorological networks in the remote pastoral regions. A multi-source water balance modelling approach driven by satellite data was used to operationally monitor daily water level fluctuations across the pastoral regions of northern Kenya and southern Ethiopia. Advanced Spaceborne Thermal Emission and Reflection Radiometer data were used for mapping and estimating the surface area of the waterholes. Satellite-based rainfall, modelled run-off and evapotranspiration data were used to model daily water level fluctuations. Mapping of waterholes was achieved with 97% accuracy. Validation of modelled water levels with field-installed gauge data demonstrated the ability of the model to capture the seasonal patterns and variations. Validation results indicate that the model explained 60% of the observed variability in water levels, with an average root-mean-squared error of 22%. Up-to-date information on rainfall, evaporation, scaled water depth and condition of the waterholes is made available daily in near-real time via the Internet (http://watermon.tamu.edu). Such information can be used by non-governmental organizations, governmental organizations and other stakeholders for early warning and decision making. This study demonstrated an integrated approach for establishing an operational waterhole monitoring system using multi-source satellite data and hydrologic modelling.

Africa-Wide Monitoring of Small Surface Water Bodies Using Multisource Satellite Data: A Monitoring System for FEWS NET

Continental Africa has the highest volume of water stored in wetlands, large lakes, reservoirs, and rivers, yet it suffers from problems such as water availability and access. With climate change intensifying the hydrologic cycle and altering the distribution and frequency of rainfall, the problem of water availability and access will increase further. Famine Early Warning Systems Network (FEWS NET) funded by the United States Agency for International Development (USAID) has initiated a large-scale project to monitor small to medium surface water points in Africa. Under this project, multisource satellite data and hydrologic modeling techniques are integrated to monitor several hundreds of small to medium surface water points in Africa. This approach has been already tested to operationally monitor 41 water points in East Africa. The validation of modeled scaled depths with field-installed gauge data demonstrated the ability of the model to capture both the spatial patterns and seasonal variations. Modeled scaled estimates captured up to 60 % of the observed gauge variability with a mean root-mean-square error (RMSE) of 22 %. The data on relative water level, precipitation, and evapotranspiration (ETo) for water points in East and West Africa were modeled since 1998 and current information is being made available in near-real time. This chapter presents the approach, results from the East African study, and the first phase of expansion activities in the West Africa region. The water point monitoring network will be further expanded to cover much of sub-Saharan Africa. The goal of this study is to provide timely information on the water availability that would support already established FEWS NET activities in Africa. This chapter also presents the potential improvements in modeling approach to be implemented during future expansion in Africa.