Assessing the Reliability of Satellite and Reanalysis Estimates of Rainfall in Equatorial Africa

This article examines the reliability of satellite and reanalysis estimates of rainfall in the Congo Basin and over Lake Victoria and its catchment. Nine satellite products and five reanalysis products are considered. They are assessed by way of inter-comparison and by comparison with observational data sets. The three locations considered include a region with little observational gauge data (the Congo), a region with extensive gauge data (Lake Victoria catchment), and an inland water body. Several important results emerge: for one, the diversity of estimates is generally very large, except for the Lake Victoria catchment. Reanalysis products show little relationship with observed rainfall or with the satellite estimates, and thus should not be used to assess rainfall in these regions. Most of the products either overestimate or underestimate rainfall over the lake. The diversity of estimates makes it difficult to assess the factors governing the interannual variability of rainfall in these regions. This is shown by way of correlation with sea-surface temperatures, particularly with the Niño 3.4 temperatures and with the Dipole Mode Index over the Indian Ocean. Some guidance is given as to the best products to utilize. Overall, any user must establish that the is product reliable in the region studied.

Lake Chad hydrological cycle under current climate change

<p>In a near future, the Sahara and Sahelian regions could experience more rainfall than today as a result of climate change. Wetter conditions in the hottest and driest place of the planet today raise the question of whether the near future might hold in store environmental transformations, particularly in view of the growing human-induced climate, land-use and land-cover changes. Reflecting an enhancement of the global hydrological cycle under warmer conditions, some experiments provide support for the notion of a strengthening of the monsoon in the future and more rainfall in central Sahel and Sahara. However, some remote forcing could counterbalance the decadal trend. Modeling experiments suggest that the freshwater discharge coming from Greenland melting could significantly impact the sea surface temperature of North Atlantic and induce a decrease in Sahel rainfall for the next decades, remaining left open the question how Sahara will be in a warmer climate?</p><p>By chance, Lake Chad, located at the southern edge of the Sahara, is recognized for being the best site in Africa for deciphering hydrological and climate change. After being ranked at the world’s sixth largest inland water body with an open water area of 25,000 km<sup>2</sup> in the 1960s, it shrunk dramatically at the beginning of the 1970s and reached less than 2000 km<sup>2</sup> during the 1980s, decreasing by more 90% in area. Because it provides food and water to 50 millions of people, it becomes crucial to observe precisely its hydrological cycle during the last 20 years.</p><p>Here by using a new multi-satellite approach combined with ground-based observations, we show that Lake Chad extent has remained stable during the last two decades, slightly increasing at 14,000 km<sup>2</sup>. We extend further this reconstruction by adding new data from the hydrological year 2019-2020, which is considered at an extreme in precipitation recorded over the Sahel. Moreover, since the 2000s, groundwater which contributes to 70% of Lake Chad’s annual water storage, is increasing due to water supply provide by its two main tributaries draining a catchment area 610,000 km<sup>2</sup> wide. Because the current climate change seems to be characterize by a higher interannual variability affecting from year to year the amount of precipitation during the rainy season and increasing the vulnerability of the economy of the region mainly based of agropastoral activities, we investigate the yearly cycle and see how it is impacted the hydrological cycle of Lake Chad and changed over time.</p>

Feasibility of Using Sentinel-3 in Estimating Lake Nasser Water Depths

<p><strong>Abstract</strong>  After the construction of the Grand Ethiopian Renaissance Dam (GERD), Nasser Lake (NL)became one of the most challenging hot spots at both local and global level. It is one of the biggest manmade reservoirs in the world and the most important in Egypt. It is created  in the southern part of the Nile River in Upper Egypt after the construction of Aswan High Dam (AHD). The water level in NL might fluctuate between 160 to 182 m above the mean sea level. Monitoring NL  water depth is an expensive and time-consuming activity. This work investigates the possibility to use information from the Sentinel missions to estimate the depth of NL as an inland water body, in the frame of estimating storage variations from satellite measurements. In this preliminary study, we investigated the relationship between the radiance /reflectance of optical imagery from two instruments SLSTR and OLCI instruments hosted by the Sentinel-3A platform and in situ water depth data using the Lyzenga equation. The results  indictaed  that there was a reasonable correlation between Sentinel-3 optical data and in situ water depth data. Also, Heron's formula was used to estimate water storage variations of NL with limited in situ data. In addition, equations governing the relationship between water level and both surface area and water volume were worked out. This study is in the framework of a bilateral project between ASRT of Egypt and CNR of Italy which is still running.</p><p> </p><p><strong>Keywords</strong>: Sentinel, SLSTR, OLCI, Inland water body, Nasser Lake, Egypt, Water Depth, GERD, AHD, Egypt</p>

Climate Variability on Fishing Activities in Inland Waters: Case of Owena River in Ondo and Osun States, Nigeria

This chapter examined the effects of climate variability on fishing activities in inland waters: the case of Owena River in Ondo and Osun States, Nigeria. The particular inland water body (Owena) was selected purposively because the Owena River crosses across the two States (Ondo and Osun States). A total of 100 respondents/fisher folks were selected randomly. Primary data was used to get information from the respondents with the aid of the structured questionnaire. Secondary data was used to get information on the climate variability existing in the locations in order to achieve the set objectives. Specifically, the effects of climatic variables such as temperature, rainfall, and wind were determined on fisher folk, fishing duration, fish catch, fishing techniques, and fishing equipment/gears. Descriptive survey design was used to examine the demographic characteristics of respondents. The result revealed that most of the respondents (96%) were male. This chapter established that climate variability particularly strong wind, rainfall, and temperature has adverse effects on fishing activities such as reduction in fish catch, long duration of fishing, loss of fishing gear, change in fishing techniques, and effect on health; hence, the livelihoods of the residence are adversely affected on the long run. In addition to the adverse effect of poverty and loss of life for the fisher folks. Although, the fisher folks livelihoods depend mainly on fisheries resources and optimum fishing depends on favorable climate/weather conditions. Therefore, proper preventive coping strategies against the adverse effect of climate variables should be paramount in both States (Ondo and Ekiti) to improve livelihoods and food security.

Multispectral Remote Sensing Utilization for Monitoring Chlorophyll-a Levels in Inland Water Bodies in Jordan

This study focuses on the utilization of multispectral satellite images for remote water-quality evaluation of inland water body in Jordan. The geophysical parameters based on water’s optical properties, due to the presence of optically active constituents, are used to determine contaminant level in water. It has a great potential to be employed for continuous and cost-effective water-quality monitoring and leads to a reliable regularly updated tool for better water sector management. Three sets of water samples were collected from three different dams in Jordan. Chl-a concentration of the water samples was measured and used with corresponding Sentinel 2 surface reflectance (SR) data to develop a predictive model. Chl-a concentrations and corresponding SR data were used to calibrate and validate different models. The predictive capability of each of the investigated models was determined in terms of determination coefficient (R2) and lowest root mean square error (RMSE) values. For the investigated sites, the B3/B2 (green/blue bands) model and the Ln (B3/B2) model showed the best overall predictive capability of all models with the highest R2 and the lowest RMSE values of (0.859, 0.824) and (30.756 mg/m3, 29.787 mg/m3), respectively. The outcome of this study on selected sites can be expanded for future work to cover more sites in the future and ultimately cover all sites in Jordan.

Potential of Large-Scale Inland Water Body Mapping from Sentinel-1/2 Data on the Example of Bavaria’s Lakes and Rivers

The mapping of water bodies is an important application area of satellite-based remote sensing. In this contribution, a simple framework based on supervised learning and automatic training data annotation is shown, which allows to map inland water bodies from Sentinel satellite data on large scale, i.e. on state level. Using the German state of Bavaria as an example and different combinations of Sentinel-1 SAR and Sentinel-2 multi-spectral imagery as inputs, potentials and limits for the automatic detection of water surfaces for rivers, lakes, and reservoirs are investigated. Both quantitative and qualitative results confirm that fully automatic large-scale inland water body mapping is generally possible from Sentinel data; whereas, the best result is achieved when all available surface-related bands of both Sentinel-1 and Sentinel-2 are fused on a pixel level. The main limitation arises from missed smaller water bodies, which are not observed in bands with a resolution of about 20 m. Given the simplicity of the proposed approach and the open availability of the Sentinel data, the study confirms the potential for a fully automatic large-scale mapping of inland water with cloud-based remote sensing techniques.

Velocity fields in Northern Caspian near Jayik (Ural) river delta

<p>The Caspian Sea is the largest inland water body on the Earth and a unique object for analysis. It is of great importance for the socioeconomic development of bordering countries. Unique fish resources and oil and gas fields are projected to provide a significant source of food and economic prosperity to the Caspian region, as well as energy to many parts of the world. National and transnational oil and gas corporations are involved in the utilization of the commercially attractive Caspian natural resources. The Caspian Sea has been influenced by climate change and anthropogenic disturbance during recent decades, yet the scientific understanding of this water body remains poor. Climatic variability of water circulation in the Caspian Sea remains unclear. Traditionally, currents in the Caspian Sea have been investigated by numerical methods. Instrumental observations of the currents in the Caspian Sea are mostly carried out in the shelf zone. Available data cover very short periods and reflect variability only in synoptic and higher frequency of the sea dynamics. In this work, water velocity data based on SeaHorse equipment is under consideration. Three stations were in northern Caspian, area adjacent to Jayik (Ural) River delta. In both cases, the instruments were deployed in 2016 and 2017 at the point 46.782N, 51.384E, depth about 3 m. In this work, we will present the preliminary results of our study of the field observations we gathered in these points. We also present the analysis of the potential drivers for the spatial and temporal patterns of the measured currents velocity.</p>