A regional-scale ecological risk framework for environmental flow evaluations

被引:58
|
作者
O'Brien, Gordon C. [1 ]
Dickens, Chris [2 ]
Hines, Eleanor [3 ]
Wepener, Victor [4 ]
Stassen, Retha [1 ]
Quayle, Leo [5 ]
Fouchy, Kelly [6 ]
MacKenzie, James [1 ]
Graham, P. Mark [7 ]
Landis, Wayne G. [3 ]
机构
[1] Univ KwaZulu Natal, Coll Agr Engn & Sci, Sch Life Sci, Private Bag X01, Scottsville, South Africa
[2] Int Water Management Inst, Private Bag X813, ZA-0127 Silverton, South Africa
[3] Western Washington Univ, Inst Environm Toxicol, Bellingham, WA 98225 USA
[4] North West Univ, Water Res Grp Ecol, Unit Environm Sci & Management, Private Bag x6001, ZA-2520 Potchefstroom, South Africa
[5] Inst Nat Resources NPC, POB 100 396, ZA-3209 Scottsville, South Africa
[6] IHE Delft Inst Water Educ, POB 3015, NL-2601 DA Delft, Netherlands
[7] Univ KwaZulu Natal, Coll Agr Engn & Sci, Sch Hydrol, Ctr Water Resources Res, Private Bag X01, Scottsville, South Africa
关键词
MARA RIVER-BASIN; BAYESIAN BELIEF NETWORKS; WATER-RESOURCES; LAND-USE; CLIMATE-CHANGE; CHERRY-POINT; MANAGEMENT; KENYA; HYDROLOGY; MODELS;
D O I
10.5194/hess-22-957-2018
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Environmental flow (E-flow) frameworks advocate holistic, regional-scale, probabilistic E-flow assessments that consider flow and non-flow drivers of change in a socio-ecological context as best practice. Regional-scale ecological risk assessments of multiple stressors to social and ecological endpoints, which address ecosystem dynamism, have been undertaken internationally at different spatial scales using the relative-risk model since the mid-1990s. With the recent incorporation of Bayesian belief networks into the relative-risk model, a robust regional-scale ecological risk assessment approach is available that can contribute to achieving the best practice recommendations of E-flow frameworks. PROBFLO is a holistic E-flow assessment method that incorporates the relative-risk model and Bayesian belief networks (BN-RRM) into a transparent probabilistic modelling tool that addresses uncertainty explicitly. PROBFLO has been developed to evaluate the socio-ecological consequences of historical, current and future water resource use scenarios and generate E-flow requirements on regional spatial scales. The approach has been implemented in two regional-scale case studies in Africa where its flexibility and functionality has been demonstrated. In both case studies the evidence-based decision making, with trade-off considerations in the context of social and ecological aspirations. This paper presents the PROBFLO approach as applied to the Senqu River catchment in Lesotho and further developments and application in the Mara River catchment in Kenya and Tanzania. The 10 BN-RRM procedural steps incorporated in PROBFLO are demonstrated with examples from both case studies. PROBFLO can contribute to the adaptive management of water resources and contribute to the allocation of resources for sustainable use of resources and address protection requirements.
引用
收藏
页码:957 / 975
页数:19
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