Optimizing Reservoir Operation Policy Using Chance Constraint Nonlinear Programming for Koga Irrigation Dam, Ethiopia

Birhanu, Kassahun; Alamirew, Tena; Dinka, Megersa Olumana; Ayalew, Semu Moges; Aklog, Dagnachew

doi:10.1007/s11269-014-0770-4

Cited by 43 publications

(19 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It was commissioned in 2009 to irrigate 7000 ha of wheat, corn and teff crops. The rainy season (June to August) generates about 70% of the run-off feeding the Koga River [21]. The length of the reservoir shoreline at full capacity is 120 km.…”

Section: Methodsmentioning

confidence: 99%

Environmental and meteorological factors linked to malaria transmission around large dams at three ecological settings in Ethiopia

Kibret

Wilson

Ryder

et al. 2019

Malar J

View full text Add to dashboard Cite

Background A growing body of evidence suggests that dams intensify malaria transmission in sub-Saharan Africa. However, the environmental characteristics underpinning patterns in malaria transmission around dams are poorly understood. This study investigated local-scale environmental and meteorological variables linked to malaria transmission around three large dams in Ethiopia. Methods Monthly malaria incidence data (2010–2014) were collected from health centres around three dams located at lowland, midland and highland elevations in Ethiopia. Environmental (elevation, distance from the reservoir shoreline, Normalized Difference Vegetation Index (NDVI), monthly reservoir water level, monthly changes in water level) and meteorological (precipitation, and minimum and maximum air temperature) data were analysed to determine their relationship with monthly malaria transmission at each dam using correlation and stepwise multiple regression analysis. Results Village distance to reservoir shoreline (lagged by 1 and 2 months) and monthly change in water level (lagged by 1 month) were significantly correlated with malaria incidence at all three dams, while NDVI (lagged by 1 and 2 months) and monthly reservoir water level (lagged by 2 months) were found to have a significant influence at only the lowland and midland dams. Precipitation (lagged by 1 and 2 months) was also significantly associated with malaria incidence, but only at the lowland dam, while minimum and maximum air temperatures (lagged by 1 and 2 months) were important factors at only the highland dam. Conclusion This study confirmed that reservoir-associated factors (distance from reservoir shoreline, monthly average reservoir water level, monthly water level change) were important predictors of increased malaria incidence in villages around Ethiopian dams in all elevation settings. Reservoir water level management should be considered as an additional malaria vector control tool to help manage malaria transmission around dams. Electronic supplementary material The online version of this article (10.1186/s12936-019-2689-y) contains supplementary material, which is available to authorized users.

show abstract

Section: Methodsmentioning

confidence: 99%

Environmental and meteorological factors linked to malaria transmission around large dams at three ecological settings in Ethiopia

Kibret

Wilson

Ryder

et al. 2019

Malar J

View full text Add to dashboard Cite

show abstract

“…Water resources reservoirs are important tools for integrated water resources development and management [1,2], but nowadays their operation and management is challenging due to various factors [3,4]. The reservoir operates to supply water for municipal consumption, hydropower production, irrigation and industrial needs, flood control, recreation, navigation or ecological requirements.…”

Section: Introductionmentioning

confidence: 99%

“…Most research conducted in the reservoir operations have specific objectives like hydropower [12,14,15], flood control [13], irrigation [3] and environmental [16].…”

Section: Introductionmentioning

confidence: 99%

“…In the Nile River basin, the rapidly growing hydropower based energy need, population growth, food insecurity and finite water resources will lead to competitions for water in the riparian countries and this will be aggravated by the climate change. Several studies have been conducted on the variability of precipitation and streamflow in the Nile River basin [37][38][39][40][41] that affects reservoir planning and management [3].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal Operation of Hydropower Reservoirs under Climate Change: The Case of Tekeze Reservoir, Eastern Nile

Abera

Asfaw

Engida

et al. 2018

Water

View full text Add to dashboard Cite

Abstract:Optimal operation of reservoirs is very essential for water resource planning and management, but it is very challenging and complicated when dealing with climate change impacts. The objective of this paper was to assess existing and future hydropower operation at the Tekeze reservoir in the face of climate change. In this study, a calibrated and validated Soil and Water Assessment Tool (SWAT) was used to model runoff inflow into the Tekeze hydropower reservoir under present and future climate scenarios. Inflow to the reservoir was simulated using hydro-climatic data from an ensemble of downscaled climate data based on the Coordinated Regional climate Downscaling Experiment over African domain (CORDEX-Africa) with Coupled Intercomparison Project Phase 5 (CMIP5) simulations under Representative Concentration Pathway (RCP)4.5 and RCP8.5 climate scenarios. Observed and projected inflows to Tekeze hydropower reservoir were used as input to the US Army Corps of Engineer's Reservoir Evaluation System Perspective Reservoir Model (HEC-ResPRM), a reservoir operation model, to optimize hydropower reservoir release, storage and pool level. Results indicated that climate change has a clear impact on reservoir inflow and showed increase in annual and monthly inflow into the reservoir except in dry months from May to June under RCP4.5 and RCP8.5 climate scenarios. HEC-ResPRM optimal operation results showed an increase in Tekeze reservoir power storage potential up to 25% and 30% under RCP4.5 and RCP8.5 climate scenarios, respectively. This implies that Tekeze hydropower production will be affected by climate change. This analysis can be used by water resources planners and mangers to develop reservoir operation techniques considering climate change impact to increase power production.

show abstract

“…In recent years, the increasing conflicts of water demand and supply have promoted a greater need for reasonable water resource development and management [1][2][3][4]. Currently, the operation target for a reservoir has shifted from single objective to multi-objective, including agricultural irrigation, industry, urban supply, and even river ecology.…”

Section: Introductionmentioning

confidence: 99%

Application of a Classifier Based on Data Mining Techniques in Water Supply Operation

Lei

Cai

Wang

2016

Water

View full text Add to dashboard Cite

Data mining technology is applied to extract the water supply operation rules in this study. Five characteristic attributes-reservoir storage water, operation period number, water demand, runoff, and hydrological year-are chosen as the dataset, and these characteristic attributes are applied to build a mapping relation with the optimal operation mode calculated by dynamic programming (DP). A Levenberg-Marquardt (LM) neural network and a classification and regression tree (CART) are chosen as data mining algorithms to build the LM neural network classifier and CART decision tree classifier, respectively. In order to verify the classification effect of the LM and CART, the two classifiers are applied to the operation mode recognition for the Heiquan reservoir, which is located in the Qinghai Province of China. The accuracies of the two classifiers are 73.6% and 86.9% for the training sample, and their accuracies are 65.8% and 83.3%, respectively, for the test sample, which indicates that the classification result of the CART classifier is better than that of the LM neural network classifier. Thus, the CART classifier is chosen to guide the long-series water supply operation. Compared to the operation result with the other operation scheme, the result shows that the water deficit index of the CART is mostly closest to the DP scheme, which indicates that the CART classifier can guide reservoir water supply operation effectively.

show abstract

Optimizing Reservoir Operation Policy Using Chance Constraint Nonlinear Programming for Koga Irrigation Dam, Ethiopia

Cited by 43 publications

References 15 publications

Environmental and meteorological factors linked to malaria transmission around large dams at three ecological settings in Ethiopia

Environmental and meteorological factors linked to malaria transmission around large dams at three ecological settings in Ethiopia

Optimal Operation of Hydropower Reservoirs under Climate Change: The Case of Tekeze Reservoir, Eastern Nile

Application of a Classifier Based on Data Mining Techniques in Water Supply Operation

Contact Info

Product

Resources

About