WLE Journal Articles

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Tritrophic defenses as a central pivot of low-emission, pest-suppressive farming systems
(Journal Article, 2022-10) Wyckhuys, Kris A.G.; Wei Zhang; Colmenarez, Yelitza C.; Simelton, Elisabeth; Sander, Björn Ole; Yanhui Lu
The ongoing COVID-19 pandemic has spotlighted the intricate connections between human and planetary health. Given that pesticide-centered crop protection degrades ecological resilience and (in-)directly harms human health, the adoption of ecologically sound, biodiversity-driven alternatives is imperative. In this Synthesis paper, we illuminate how ecological forces can be manipulated to bolster ‘tritrophic defenses’ against crop pests, pathogens, and weeds. Three distinct, yet mutually compatible approaches (habitat-mediated, breeding-dependent, and epigenetic tactics) can be deployed at different organizational levels, that is, from an individual seed to entire farming landscapes. Biodiversity can be harnessed for crop protection through ecological infrastructures, diversification tactics, and reconstituted soil health. Crop diversification is ideally guided by interorganismal interplay and plant–soil feedbacks, entailing resistant cultivars, rotation schemes, or multicrop arrangements. Rewarding opportunities also exist to prime plants for enhanced immunity or indirect defenses. As tritrophic defenses spawn multiple societal cobenefits, they could become core features of healthy, climate-resilient, and low-carbon food systems.
High-resolution mapping of forest carbon stock using Object-Based Image Analysis (OBIA) technique
(Journal Article, 2020-06) Pandey, S. K.; Chand, N.; Nandy, S.; Muminov, A.; Sharma, A.; Ghosh, Surajit; Srinet, R.
This study assessed and mapped the aboveground tree carbon stock using very high-resolution satellite imagery (VHRS)—WorldView-2 in Barkot forest of Uttarakhand, India. The image was pan-sharpened to get the spectrally and spatially good-quality image. High-pass filter technique of pan-sharpening was found to be the best in this study. Object-based image analysis (OBIA) was carried out for image segmentation and classification. Multi-resolution image segmentation yielded 74% accuracy. The segmented image was classified into sal (Shorea robusta), teak (Tectona grandis) and shadow. The classification accuracy was found to be 83%. The relationship between crown projection area (CPA) and carbon was established in the field for both sal and teak trees. Using the relationship between CPA and carbon, the classified CPA map was converted to carbon stock of individual trees. Mean value of carbon stock per tree for sal was found to be 621 kg, whereas for teak it was 703 kg per tree. The study highlighted the utility of OBIA and VHRS imagery for mapping high-resolution carbon stock of forest.
Water level status of Indian reservoirs: a synoptic view from altimeter observations
(Journal Article, 2021-07) Thakur, P. K.; Garg, V.; Kalura, P.; Agrawal, B.; Sharma, V.; Mohapatra, M.; Kalia, M.; Aggarwal, S.P.; Calmant, S.; Ghosh, Surajit; Dhote, P. R.; Sharma, R.; Chauhan, P.
Most of the part of India is already under water-stressed condition. In this regard, the continuous monitoring of the water levels (WL) and storage capacity of reservoirs, lakes, and rivers is very important for the estimation and utilization of water resources effectively. The long term ground observed WL of many of the water bodies is not easily available, which may be very critical for proper water resources management. Satellite radar altimetry is the remote sensing technique, which is being used to study sea surface height for the last three decades. The advancement in radar technology with time has provided the opportunity to exploit the technique to retrieve the WL of inland water bodies. In the current study, an attempt has been made to generate long term time series on WL of around 29 geometrically complicated inland water bodies in India. These water bodies are mainly large reservoirs namely Ban Sagar, Balimela, Bargi, Bhakra, Gandhi Sagar, Hasdeo, Indravati, Jalaput, Kadana, Kolab, Mahi Bajaj, Maithon, Massanjore, Pong, Ramganga, Ranapratap Sagar, Rihand, Sardar Sarovar, Shivaji Sagar, Tilaiya, Ujjani, and Ukai. The WL of these water bodies was retrieved for around two decades using the European Remote-Sensing Satellite – 2 (ERS-2), ENVISAT Radar Altimeter – 2 (ENVISAT RA-2), and Saral-AltiKa altimeters data through Ice-1 retracking algorithm. Further, an attempt has also been made to estimate the WL of gauged/ungauged lakes namely Mansarovar, Pangong, Chilika, Bhopal, and Rann of Kutch over which Saral-AltiKa pass was there. As after July 2016, the SARAL-AltiKa is operating in the drifting orbit, systematic repeated observation of WL data of all reservoirs was not possible. The data of drifted tracks of Saral-AltiKa were tested for WL estimation of Ban Sagar reservoir. As the ERS-2, ENVISAT RA-2 and Saral-AltiKa all were having almost the same passing tracks, a long term WL series of these lakes could be generated from 1997 to 2016. However, at present only Sentinel – 3 is in orbit, the continuous altimeter based WL monitoring of some of these reservoirs (Gandhi Sagar, Nathsagar, Ranapratap, Ujjani, and Ukai) was attempted through Sentinel-3A satellite data from 2016 to 2018. The accuracy of the retrieved WL was than validated against the observed WL. In most of the reservoirs, a systematic bias was found due to the different characteristics and geoid height of each reservoir. The coefficient of determination, R2 , value for a majority of reser voirs was as good as 0.9. In the case of ERS-2, the values of R2 varied for 0.44–0.97 with root mean square error (RMSE) in the range of 0.63–2.72 m. These statistics improved with the ENVISAT RA-2 data analysis, the R2 value reached more than 0.90 for around 11 reservoirs. The highest, 0.99, for Hasdeo and Shivaji Sagar Reservoirs with RMSE of 0.44 and 0.56, respectively. Further, the accuracy improved with the analysis of Saral-AltiKa data. The R2 was always more than 0.9 for each reservoir and the lowest RMSE reduced to 0.03. Therefore, it can be said that the accuracy and consistency of WL retrieval through satellite altimetry has improved with time. Furthermore, the altimeter based retrieved WL may be used in hydrological studies and can contribute to better water resources management.
Retrieving vegetation biophysical parameters and GPP [Gross Primary Production] using satellite-driven LUE [Light Use Efficiency] model in a national park
(Journal Article, 2022-07) Marandi, M.; Parida, B. R.; Ghosh, Surajit
The terrestrial biosphere plays an active role in governing the climate system by regulating carbon exchange between the land and the atmosphere. Analysis of vegetation biophysical parameters and gross primary production (GPP) makes it convenient to monitor vegetation's health. A light use efficiency (LUE) model was employed to estimate daily GPP from satellite-driven data and environmental factors. The LUE model is driven by four major variables, namely normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and moisture for which both satellite-based and ERA5-Land data were applied. In this study, the vegetation health of Dibru Saikhowa National Park (DSNP) in Assam has been analyzed through vegetation biophysical and biochemical parameters (i.e., NDVI, EVI, LAI, and chlorophyll content) using Sentinel-2 data. Leaf area index (LAI) varied between 1 and 5.2, with healthy forests depicted LAI more than 2.5. Daily GPP was estimated for January (winter) and August (monsoon) 2019 for tropical evergreen and deciduous forest types. A comparative analysis of GPP for two seasons has been performed. In January, GPP was found to be 3.6 gC m-2 day-1, while in August, GPP was 5 gC m-2 day-1. The outcome of this study may be constructive to forest planners to manage the National Park so that net carbon sink may be attained in DSNP.
Karnataka’s ‘Surya Raitha’ experiment: lessons for PM–KUSUM
(Journal Article, 2021-11-27) Durga, N.; Shah, Tushaar; Verma, Shilp; Manjunatha, A.V
Solar-powered irrigation has expanded in India at an unprecedented pace—the number of solar irrigation pumps—from less than 4,000 in 2012 to more than 2,50,000 by 2019. It has been argued that besides giving farmers an additional and reliable source of income, grid-connected SIPs also incentivise efficient energy and water use—critical for sustaining groundwater irrigation. The Surya Raitha scheme was the country’s first, state-driven initiative for solarisation of agriculture feeders by replacing subsidy-guzzling, inefficient electric pumps with energy-efficient, net-metered SIPs. An early appraisal of Surya Raitha lauded the scheme as a smart initiative and argued that it could set an example for promoting solar power as a remunerative crop. However, the scheme was eventually executed as a single feeder pilot with some design changes in Nalahalli panchayat from 2015–18. The authors visited the pilot in 2017–18 and 2018–19 to assess if it had delivered the promises of Surya Raitha scheme. The results are a mixed bag and offer important lessons for implementation and scaling out of component C of the Government of India’s Pradhan Mantri Kisan Urja Suraksha evam Utthaan Mahabhiyan policy.
Revisiting the levels of aerosol optical depth in South-Southeast Asia, Europe and USA amid the COVID-19 pandemic using satellite observations
(Journal Article, 2021-02) Acharya, P.; Barik, G.; Gayen, B. K.; Bar, S.; Maiti, A.; Sarkar, A.; Ghosh, Surajit; De, S.K.; Sreekesh, S.
The countries around the world are dealing with air quality issues for decades due to their mode of production and energy usages. The outbreak of COVID-19 as a pandemic and consequent global economic shutdown, for the first time, provided a base for the real-time experiment of the effect of reduced emissions across the globe in abetting the air pollution issue. The present study dealt with the changes in Aerosol Optical Depth (AOD), a marker of air pollution, because of global economic shutdown due to the coronavirus pandemic. The study considered the countries in south and south-east Asia (SSEA), Europe and the USA for their extended period of lockdown due to coronavirus pandemic. Daily Aerosol Optical Depth (AOD) from Moderate-resolution imaging spectroradiometer (MODIS) and tropospheric column density of NO2 and SO2 from Ozone monitoring instrument (OMI) sensors, including meteorological data such as wind speed (WS) and relative humidity (RH) were analyzed during the pre-lockdown (2017–2019) and lockdown periods (2020). The average AOD, NO2 and SO2 during the lockdown period were statistically compared with their pre-lockdown average using Wilcoxon-signed-paired-rank test. The accuracy of the MODIS-derived AOD, including the changing pattern of AOD due to lockdown was estimated using AERONET data. The weekly anomaly of AOD, NO2 and SO2 was used for analyzing the space-time variation of aerosol load as restrictions were imposed by the concerned countries at the different points of time. Additionally, a random forest-based regression (RF) model was used to examine the effects of meteorological and emission parameters on the spatial variation of AOD. A significant reduction of AOD (- 20%) was obtained for majority of the areas in SSEA, Europe and USA during the lockdown period. Yet, the clusters of increased AOD (30–60%) was obtained in the south-east part of SSEA, the western part of Europe and US regions. NO2 reductions were measured up to 20–40%, while SO2 emission increased up to 30% for a majority of areas in these regions. A notable space-time variation was observed in weekly anomaly. We found the evidence of the formation of new particles for causing high AOD under high RH and low WS, aided by the downward vertical wind flow. The RF model showed a distinguishable relative importance of emission and meteorological factors among these regions to account for the spatial variability of AOD. Our findings suggest that the continued lockdown might provide a temporary solution to air pollution; however, to combat persistent air quality issues, it needs switching over to the cleaner mode of production and energy. The findings of this study, thus, advocated for alternative energy policy at the global scale.
The contribution of tipping fees to the operation, maintenance, and management of fecal sludge treatment plants: the case of Ghana
(Journal Article, 2022-02) Tanoh, Rebecca; Nikiema, Josiane; Asiedu, Zipporah; Jayathilake, Nilanthi; Cofie, Olufunke O.
Globally, collection of tipping fees is being promoted as a solution to sustain the operation of fecal sludge treatment plants (FSTPs). Currently, there are six large-scale FSTPs in Ghana, of which five were in operation in June 2017. In Kumasi, Sekondi-Takoradi and Tamale, fecal sludge (FS) is co-treated with landfill leachate using waste stabilization ponds (WSPs). In Tema and Accra, FS is treated using WSPs and a mechanical dewatering system coupled with an upflow anaerobic sludge blanket (UASB). The focus of this study is FSTPs and to assess how, and if, the tipping fees set by the municipalities could enable cost recovery to sustain their long-term operation. Using a questionnaire survey to interview plant managers from the public and private sectors, and directors of waste management departments, we found that the overall average operation, maintenance and management (OM&M) costs per 1000 m3 of treated waste (FS or FS + leachate) in 2017 were USD89 in Kumasi, USD150 in Tamale, USD179 in Tema, USD244 in Sekondi-Takoradi and USD1,743 in Accra. There were important disparities between FSTPs due to their scale, age, and level of treatment and monitoring. Currently, most FSTPs charge tipping fees that range between USD310 and USD530/1000 m3 of FS, averaging USD421 ± 98/1000 m3 of FS discharged at FSTPs. Our study also showed that the OM&M costs of large-scale intensive FSTPs cannot be sustained by relying solely on tipping fees. However, there could be potential to cover the routine expenditures associated with operating smaller FSTPs that relying on WSP technologies.
Assessment of sal (Shorea robusta) forest phenology and its response to climatic variables in India
(Journal Article, 2021-09) Nandy, S.; Ghosh, Surajit; Singh, S.
Remote sensing-based observation provides an opportunity to study the spatiotemporal variations of plant phenology across the landscapes. This study aims to examine the phenological variations of different types of sal (Shorea robusta) forests in India and also to explore the relationship between phenology metrics and climatic parameters. Sal, one of the main timber-producing species of India, can be categorized into dry, moist, and very moist sal. The phenological metrics of different types of sal forests were extracted from Moderate Resolution Imaging Spectroradiometer (MODIS)-derived Enhanced Vegetation Index (EVI) time series data (2002–2015). During the study period, the average start of season (SOS) was found to be 16 May, 17 July, and 29 June for very moist, moist, and dry sal forests, respectively. The spatial distribution of mean SOS was mapped as well as the impact of climatic variables (temperature and rainfall) on SOS was investigated during the study period. In relation to the rainfall, values of the coefficient of determination (R2) for very moist, moist, and dry sal forests were 0.69, 0.68, and 0.76, respectively. However, with temperature, R2 values were found higher (R2 = 0.97, 0.81, and 0.97 for very moist, moist, and dry sal, respectively). The present study concluded that MODIS EVI is well capable of capturing the phenological metrics of different types of sal forests across different biogeographic provinces of India. SOS and length of season (LOS) were found to be the key phenology metrics to distinguish the different types of sal forests in India and temperature has a greater influence on SOS than rainfall in sal forests of India.
Effect of irrigation water withdrawal on the hydrology of the Lake Tana sub-basin
(Journal Article, 2021-12) Taye, Meron Teferi; Haile, Alemseged Tamiru; Fekadu, A. G.; Nakawuka, P.
Study region: The Lake Tana sub-basin, upper Blue Nile, Ethiopia. Study focus: The Lake Tana sub-basin is one of the agricultural growth corridors for Ethiopia’s ambitious plan to expand irrigation. Despite the booming irrigation activities in the sub-basin, limited information exists on the rate of irrigation expansion and its impact on the water balance of the sub-basin. This study collected and organized smallholder irrigation data in the subbasin to identify the actual irrigated area, the abstracted irrigation water, and its implications on seasonal water availability. The area under small-scale irrigation was estimated through data obtained from ’woredas’ (districts) databases. Crop patterns were obtained through field surveys. Irrigation water abstracted at daily timescale was measured. New hydrological insights for the Region: In the sub-basin, 38,694 ha was under small-scale irrigation in 2020/21. Surface water is the dominant water source, and it supplies about 80% of irrigation withdrawal. Water abstraction for small-scale irrigation is about 430 MCM per dry season (~50% of dry season flow). The eastern side of the sub-basin faces water shortages as the dry season flow is not sufficient for irrigation. With the prospects of more irrigation expansion, small-scale irrigation water withdrawals pose concerns of water scarcity at local level and to the water balance of the sub-basin. Hence, there is urgent need for adaptive management of the small-scale irrigation effect on the sub-basin’s hydrology.
Establishing the foundation for the global observing system for marine life
(Journal Article, 2021-10-25) Satterthwaite, E. V.; Bax, N. J.; Miloslavich, P.; Ratnarajah, L.; Canonico, G.; Dunn, D.; Simmons, S. E.; Carini, R. J.; Evans, K.; Allain, V.; Appeltans, W.; Batten, S.; Benedetti-Cecchi, L.; Bernard, A. T. F.; Bristol, S.; Benson, A.; Buttigieg, Pier Luigi; Gerhardinger, L. C.; Chiba, S.; Davies, T. E.; Duffy, J. E.; Giron-Nava, A.; Hsu, A. J.; Kraberg, A. C.; Kudela, R. M.; Lear, D.; Montes, E.; Muller-Karger, F. E.; O’Brien, T. D.; Obura, D.; Provoost, P.; Pruckner, S.; Rebelo, Lisa-Maria; Selig, E. R.; Kjesbu, O. S.; Starger, C.; Stuart-Smith, R. D.; Vierros, M.; Waller, J.; Weatherdon, L. V.; Wellman, T. P.; Zivian, A.
Maintaining healthy, productive ecosystems in the face of pervasive and accelerating human impacts including climate change requires globally coordinated and sustained observations of marine biodiversity. Global coordination is predicated on an understanding of the scope and capacity of existing monitoring programs, and the extent to which they use standardized, interoperable practices for data management. Global coordination also requires identification of gaps in spatial and ecosystem coverage, and how these gaps correspond to management priorities and information needs. We undertook such an assessment by conducting an audit and gap analysis from global databases and structured surveys of experts. Of 371 survey respondents, 203 active, long-term (>5 years) observing programs systematically sampled marine life. These programs spanned about 7% of the ocean surface area, mostly concentrated in coastal regions of the United States, Canada, Europe, and Australia. Seagrasses, mangroves, hard corals, and macroalgae were sampled in 6% of the entire global coastal zone. Two-thirds of all observing programs offered accessible data, but methods and conditions for access were highly variable. Our assessment indicates that the global observing system is largely uncoordinated which results in a failure to deliver critical information required for informed decision-making such as, status and trends, for the conservation and sustainability of marine ecosystems and provision of ecosystem services. Based on our study, we suggest four key steps that can increase the sustainability, connectivity and spatial coverage of biological Essential Ocean Variables in the global ocean: (1) sustaining existing observing programs and encouraging coordination among these; (2) continuing to strive for data strategies that follow FAIR principles (findable, accessible, interoperable, and reusable); (3) utilizing existing ocean observing platforms and enhancing support to expand observing along coasts of developing countries, in deep ocean basins, and near the poles; and (4) targeting capacity building efforts. Following these suggestions could help create a coordinated marine biodiversity observing system enabling ecological forecasting and better planning for a sustainable use of ocean resources.
Mapping plant functional types in Northwest Himalayan foothills of India using random forest algorithm in Google Earth Engine
(Journal Article, 2020-09-16) Srinet, R.; Nandy, S.; Padalia, H.; Ghosh, Surajit; Watham, T.; Patel, N. R.; Chauhan, P.
Plant functional types (PFTs) have been widely used to represent the vegetation characteristics and their interlinkage with the surrounding environment in various earth system models. The present study aims to generate a PFT map for the Northwest Himalayan (NWH) foothills of India using seasonality parameters, topographic conditions, and climatic information from various satellite data and products using Random Forest (RF) algorithm in Google Earth Engine (GEE) platform. The seasonality information was extracted by carrying out a harmonic analysis of Normalized Difference Vegetation Index (NDVI) time-series (2008 to 2018) from Moderate Resolution Imaging Spectroradiometer (MODIS) Terra surface reflectance 8 day 500 m data (MOD09A1). For topographic information, Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) derived aspect and Multi-Scale Topographic Position Index (MTPI) were used, whereas, for climatic variables, WorldClim V2 Bioclimatic (Bioclim) variables were used. RF, a machine learning classifier, was used to generate a PFT map using these datasets. The overall accuracy of the resulting PFT map was found to be 83.33% with a Kappa coefficient of 0.71. The present study provides an effective approach for PFT classification using different well-established, freely available satellite data and products in the GEE platform. This approach can also be implemented in different ecological settings by using various meaningful variables at varying resolutions.
Berken plow and intercropping with pigeon pea ameliorate degraded soils with a hardpan in the Ethiopian highlands
(Journal Article, 2022-02) Fenta, H.M.; Hussein, M.A.; Tilahun, Seifu A.; Nakawuka, Prossie; Steenhuis, Tammo S.; Barron, Jennie; Adie, Aberra; Blümmel, Michael; Schmitter, Petra S.
Closing the yield gap and enhancing efficiency in rainfed maize production systems in Ethiopia requires urgent action in increasing the productivity of degraded agricultural land. The degradation of land through continuous compaction and decline in the organic matter has resulted in a wide-spread formation of a hardpan that restricts deep percolation, prevents plant root development, and, ultimately can lead to increased erosion. Studies exploring practical low-cost solutions to break the hardpan are limited in Ethiopia. The main objective was to evaluate soil mechanical (i.e. modified plow or Berken plow) or biological intervention (i.e. intercropping with pigeon pea) effectiveness to enhance soil water management and crop yield of rainfed maize systems whilst reducing soil erosion and runoff. Five farm fields, each including four plots with different tillage treatments, were monitored during two rainy seasons in 2016 and 2017. The treatments were: (i) farmers practice under conventional (CT) tillage; plots tilled three times using an oxen driven local plow Maresha, (ii) no-till (NT), (iii) Berken tillage (BT), plots tilled three times using an oxen pulled Berken plow, and (iv) biological (CT + Bio), taprooted pigeon pea intercropped with maize on plots conventionally tilled. Results showed that mean tillage depth was significantly deeper in the BT (28 cm) treatment compared to CT and CT + Bio (18 cm) treatments. Measured soil penetration resistance significantly decreased up to 40 cm depth under BT and maize roots reached 1.5 times deeper compared to roots measured in the CT treatment. Under BT, the estimated water storage in the root zone was estimated at 556 mm, 1.86 times higher compared to CT, 3.11 times higher compared to NT and 0.89 times higher compared to CT + Bio. The positive effects on increased water storage and root development resulted in an average increase in maize grain (i.e. 15%, 0.95 t ha- 1 ) and residual above ground biomass (0.3%, 6.4 t ha- 1 ) leading to a positive net benefit of 138 USD ha- 1 for the BT treatment compared to the CT treatment. The negative net benefit obtained under CT and CT+Bio was mainly related to the high labor cost related to plowing, weeding, planting, and fertilizer application whilst in the NT this was related to the significantly lower maize yields. The positive effects in the BT treatment, and to some extent the CT+Bio treatment show great potential for smallholder rainfed maize systems where degraded soils with hardpans and high variability in rainfall prevail.
Examining migration governance: evidence of rising insecurities due to COVID-19 in China, Ethiopia, Kyrgyzstan, Moldova, Morocco, Nepal and Thailand
(Journal Article, 2021-12) Murzakulova, A.; Dessalegn, Mengistu; Phalkey, N.
The COVID-19 pandemic has significantly changed the context of global migration. From a migration perspective, the pandemic is a source of insecurities that challenge migrants, their livelihoods and migration governance. Meanwhile, curtailment in movement has led to economic decline affecting labour markets. For migrant origin and hosting countries, this poses multidimensional development challenges. Analysis from March to August 2020 of China, Ethiopia, Kyrgyzstan, Moldova, Morocco, Nepal and Thailand highlights the varying ways in which they are all severely affected by the disruptions in migration, suggesting a potentially emerging complex situation in migration patterns and pathways. The disruptions in migration and remittances have had a profound impact on migrants and migrant-sending households. The uncertainty of migration returning to pre-pandemic levels and the potential of lasting consequences on migrants and migration patterns and pathways, suggests a future of greater risk and exploitation, and a wider gap between formal and informal migration. This paper calls for greater mobility cooperation between countries and suggests strengthening mobility migration frameworks and policies for safer migration and for the rights of migrants.
Quantifying cooperation benefits for new dams in transboundary water systems without formal operating rules
(Journal Article, 2021-05-07) Gonzalez, J. M.; Matrosov, E. S.; Obuobie, E.; Mul, M.; Pettinotti, L.; Gebrechorkos, S. H.; Sheffield, J.; Bottacin-Busolin, A.; Dalton, J.; Smith, D. Mark; Harou, Julien J.
New dams impact downstream ecosystems and water infrastructure; without cooperative and adaptive management, negative impacts can manifest. In large complex transboundary river basins without well codified operating rules and extensive historical data, it can be difficult to assess the benefits of cooperating, in particular in relation to new dams. This constitutes a barrier to harmonious development of river basins and could contribute to water conflict. This study proposes a generalised framework to assess the benefits of cooperation on the management of new dams in water resource systems that do not have formal sharing arrangements. Benefits are estimated via multi-criteria comparison of historical reservoir operations (usually relatively uncooperative) vs. adopting new cooperative rules which would achieve the best results for riparian countries as evaluated by a water resources simulator and its performance metrics. The approach is applied to the Pwalugu Multipurpose Dam (PMD), which is being built in Ghana in the Volta river basin. The PMD could impact downstream ecosystems and infrastructure in Ghana and could itself be impacted by how the existing upstream Bagre Dam is managed in Burkina Faso. Results show that with cooperation Ghana and Burkina Faso could both increase energy production although some ecosystem services loss would need to be mitigated. The study confirms that cooperative rules achieve higher overall benefits compared to seeking benefits only for individual dams or countries.
Streamflow variability and its linkage to ENSO events in the Ethiopian Rift Valley Lakes Basin
(Journal Article, 2021-06) Worako, A. W.; Haile, Alemseged Tamiru; Taye, Meron Teferi
Study Region: The Ethiopian Rift Valley Lakes basin is found in the main Ethiopian Rift Valley system. Study Focus: Understanding the hydrological impact of El Niño-Southern Oscillation (ENSO) is of a paramount importance for society since it substantially affects the environmental and socio-economic conditions. The relation between ENSO indicators (SOI, MEI and Niño3.4) and streamflow magnitude was statistically evaluated with partial correlation, cross correlation, extreme streamflow indices and streamflow deficits to provide empirical evidence on how ENSO phases (La Niña and El Niño) affect streamflow variability. Trends of streamflow and ENSO indicators were tested using the non-parametric Mann-Kendall test. New Hydrological Insights for the Region: Our findings indicate that the partial correlation between the catchment area and ENSO effect on streamflow were not statistically significant at p < 0.05 after removing the south-north gradient. The direction of the ENSO effect is spatially inconsistent since El Niño (La Niña) causes positive deviation in some catchments and negative deviation for other catchments. Though statistically insignificant, reduced flow is detected for many catchments during El Niño years. For most catchment, the extreme high flow has a larger magnitude during La Niña than El Niño whereas the extreme low flow has a larger magnitude during El Niño than La Niña years. Overall, the relationship between ENSO and streamflow of the study area is found spatially inconsistent and statistically insignificant for most catchments.
Impact of water resource development plan on water abstraction and water balance of Lake Ziway, Ethiopia
(Journal Article, 2021-06) Goshime, D. W.; Haile, Alemseged Tamiru; Absi, R.; Ledesert, B.
Lake Ziway is providing water for a wide variety of sectors in the central rift valley of Ethiopia. However, there is a lack of systematic study that informs the effect of water abstraction on the lake water balance. In the present study, we conducted a Water Abstraction Survey (WAS) to estimate actual water withdrawal from the lake and developed a water balance model of the lake to evaluate the associated impact on the lake water storage and outflow for three development plans. The mean error and root mean square error of the simulated lake water level as compared with observed counterparts were estimated as 0.1 and 0.2 m, respectively, which is smaller than the range of the observed fluctuation of the lake water level under natural condition. Our findings indicate that the actual storage and outflow of Lake Ziway are significantly impacted by the existing water withdrawal. When the future development plans are fully implemented, the annual amount of irrigation and domestic water withdrawal from the lake will reach 95 Mm3 . This will cause the lake water level to drop by 0.94 m, which translates to 38 km2 reductions in the lake surface area. Consequently, the lake will lose 26.5% of its actual storage volume when the future development plan (2029–2038) is implemented as compared to the observed storage between 1986 and 2000. Hence, the current impact of water resources development around the lake is substantially large and will exacerbate in the future. This indicates the need for urgent actions to monitor and manage water abstraction from the lake.
Vulnerability of community to climate stress: an indicator-based investigation of Upper Gana Watershed in Omo Gibe Basin in Ethiopia
(Journal Article, 2021-09) Tessema, K. B.; Haile, Alemseged Tamiru; Nakawuka, P.
Seasonal effect on the accuracy of land use/land cover classification in the Bilate Sub-basin, Abaya-Chamo Basin, Rift Valley Lakes Basin of Ethiopia
(Journal Article, 2021-07-22) Yimer, A. K.; Haile, Alemseged Tamiru; Hatiye, S. D.; Azeref, A. G.
A correct and timely land use/land cover (LULC) classification provides indispensable information for the effective management of environmental and natural resources. However, earlier studies mapped the LULC map of Bilate Sub-basin using remote sensing images that were acquired for a single season. Hence, these studies did not consider the seasonal effects on the accuracy of LULC classification. Therefore, the objective of this study was to evaluate changes in classification accuracy for images acquired during wet and dry seasons in the Bilate Sub-basin. LULC of the study area was classified using the Landsat 8 satellite imageries. Based on field observations, we classified the LULC of the study area into 9 dominant classes. The classification for the two seasons resulted in a noticeable difference between the LULC composition of the study area because of seasonal differences in the classification accuracy. The overall accuracy of the LULC maps was 80%for the wet season and 90% for the dry season with Kappa coefficient values of 0.8 and 0.9 respectively. Therefore, the two seasons showed a significant difference in the overall accuracy of the classification. However, we discovered that when the classification accuracy was tested locally, that is for individual pixels, the results were not the same. In Bilate Sub-basin, several pixels (14.71%) were assigned to different LULC classes on the two seasons maps while 85.29% of the LULC classes remained unaltered in the two maps. According to the classification results, the season had a noticeable effect on the accuracy of LULC classification. This suggests that for LULC classification, multitemporal images should be used rather than a single remote sensing image.
Impact of sustainable land management on vegetation cover using remote sensing in Magera micro Watershed, Omo Gibe Basin, Ethiopia
(Journal Article, 2021-12) Assefa, A.; Haile, Alemseged Tamiru; Dhanya, C. T.; Walker, D. W.; Gowing, J.; Parkin, G.
The hydrological impact of many expensive investments on watershed interventions remains unquantified due to lack of time series data. In this study, remote sensing imagery is utilized to quantify and detect vegetation cover change in Magera micro-watershed, Ethiopia, where sustainable land management interventions have been implemented. Normalized difference vegetation index (NDVI) values were retrieved for the period 2010 to 2019, which encompasses before, during and after the interventions. Mann-Kendal trend test was used to detect temporal trends in the monthly NDVI values. In addition, multiple change-point analyses were carried out using Pettitt’s, Buishand’s and Standard Normal Homogeneity (SNH) tests to detect any abrupt changes due to the watershed interventions. The possible influence of rainfall on changes in vegetation cover was investigated. A significant increasing trend (from 1.5% to 33%) was detected for dense vegetation at the expense of a significant reduction in bare land from 40.9% to 0.6% over the analysis period. An abrupt change in vegetation cover was detected in 2015 in response to the interventions. A weak and decreasing correlation was obtained between monthly rainfall magnitude and NDVI values, which indicates that the increase in vegetation cover is not from rainfall influences. The study shows that the sustainable land management has an overall positive impact on the study area. The findings of this research support the applicability of remote sensing approaches to provide useful information on the impacts of watershed intervention investments.
Social change innovations, citizen science, miniSASS and the SDGs
(Journal Article, 2022-05-01) Taylor, J.; Graham, M.; Louw, A.; Lepheana, A.; Madikizela, B.; Dickens, Chris; Chapman, D. V.; Warner, S.
The United Nations Sustainable Development Goals (SDGs) describe a course of action to address poverty, protect the planet and ensure prosperity for all (https://sdgs.un.org/goals). More specifically, SDG 6 clarifies how water quality, quantity and access are crucial to human well-being, and yet human activities are compromising water resources through over-exploitation, pollution, as well as contributing to the spread of disease. Globally aquatic ecosystems are highly threatened and concerted efforts by governments and civil society to ‘turn the situation around’ are simply not working. Human-created problems require human-centred solutions and these require different ways of thinking and acting to those behaviour patterns that are contributing to the challenges. In this paper, we first consider causal approaches to attitude change and behaviour modification that are simply not working as intended. We then explore enabling responses such as citizen science and co-engaged action learning as more tenable alternatives. SDG 6 has a focus on clean water and sanitation for all. The SDGs further clarify how the extent to which this goal can be realized depends, to a large extent, on stakeholder engagements and education. Through stakeholder engagements and educational processes, people can contribute towards SDG 6 and the specific indicator and target in SDG 6.b – Stakeholder participation. Following a three-year research process, that investigated a wide range of participatory tools, this paper explores how the Stream Assessment Scoring System (miniSASS; www.minisass.org) can enable members of the public to engage in water quality monitoring at a local level. The paper continues to demonstrate how miniSASS can contribute to the monitoring of progress towards Sustainable Development Goal Target 6.3, by providing a mechanism for data collection indicator 6.3.2. miniSASS is proving popular in southern Africa as a methodology for engaging stakeholder participation in water quality monitoring and management. The technique costs very little to implement and can be applied by children and scientists alike. As a biomonitoring approach, it is based on families of macroinvertebrates that are present in most perennial rivers of the world. The paper concludes by describing how useful the miniSASS technique can be for addressing data gaps for SDG 6.3.2 reporting, and that it can be applied in most regions of the world.

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