**Biodiversity Restoration and Renewable Energy from Hydropower: Conflict or Synergy?** Biodiversity Restoration and Renewable Energy from Hydropower: Conflict or Synergy?

DOI: 10.5772/intechopen.69134

Wondmagegn Tafesse Tirkaso, Ing‐Marie Gren, Leonard Sandin, Joel Segersten, David Spjut and Erik Degerman Wondmagegn Tafesse Tirkaso, Ing-Marie Gren, Leonard Sandin, Joel Segersten, David

Additional information is available at the end of the chapter Spjut and Erik Degerman

http://dx.doi.org/10.5772/intechopen.69134 Additional information is available at the end of the chapter

#### Abstract

[40] Pielou EC. The measurement of diversity in different types of biological collections.

[41] Clarke KR, Warwick RM. Change in Marine Communities: An Approach to Statistical Analysis and Interpretation. 2nd ed. Plymouth: Marine Laboratory; 2001. p. 176

[43] Khemaissia H, Raja Jelassi R, Touihri M, Souty-Grosset C, Nasri-Ammar K. Diversity of terrestrial isopods in the northern Tunisian wetlands. African Journal of Ecology. 2016.

[44] Louis M. Etude d'un peuplement mixte d'*Orchestia montagui* Audouin et d'*Orchestia deshayesii* Audouin dans la baie de Bou Ismail. Bulletin d'Ecologie. 1980;**11**:97-111 [45] ElKaïm B, Irlinger JP, Pichard S. Dynamique de la population d'*Orchestia mediterranea* L. (Crustacé, Amphipode) dans l'estuaire de Bou Regreg (Maroc). Canadian Journal of

[46] Jelassi R. Eco-éthologie des peuplements d'Amphipodes au niveau des zones humides de la Tunisie [Thèse de doctorat en Biologie]. Faculté des Sciences de Tunis, Université

[47] Bouslama MF, El Gtari M, Charfi-Cheikhrouha F. Impact of environmental factors on zonation, abundance, and other biological parameters of two Tunisian populations of

[48] Fallaci M, Colombini I, Lagar M, Scapini F, Chelazzi L. Distribution patterns of different age classes and sexes in a Tyrrhenian population of *Talitrus saltator* (Montagu). Marine

[49] Colombini I, Aloia A, Bouslama MF, El Gtari M, Fallaci M, Ronconi L, Scapini F, Chelazzi L. Small-scale spatial and seasonal differences in the distribution of beach arthropods on the northern Tunisian coasts. Are species evenly distributed along the shore? Marine

[50] Williams JA. Burrow-zone distribution of the supralittoral Amphipod *Talitrus saltator* on Derbyhaven beach, Isle of Man-a possible mechanism for regulating desiccation stress?

*Talitrus saltator* (Amphipoda, Talitridae). Crustaceana. 2009;**82**(2):141-157

[42] Henin S. Les éléments traces dans les sols. Science du sol. 1983;**2**:67-71

Journal of Theoretical Biology. 1966;**13**:131-144

DOI: 10.1111/aje.12337

118 Selected Studies in Biodiversity

Zoology. 1985;**63**:2800-2809

de Tunis El Manar; 2014. p. 328

Biology. 2003;**142**:101-110

Biology, Berlin. 2002;**140**:1001-1012

Journal of Crustacean Biology. 1995;**15**:466-475

Hydropower plants have a negative impact on biodiversity by transforming stream habitat and hydrology and thereby affecting aquatic organisms negatively. The negative effects can be mitigated by releasing water into the old river bed. This study investigates if the measure of releasing water creates costs and if ecological conditions at the old river bed contribute to such an impact. To this end, we used the cost-minimization framework in economics for deriving hypotheses. Tests were made with data from a survey to 76 hydropower plants in Sweden with questions on existence of a cost, size of the plant, type of water release from reservoirs, characteristics of the dried downstream old river bed, and official statistics on ecological status of the downstream dried segments. The results showed that 42% of the plants reported no cost, measured as impact on electricity production, from release of water into downstream old river bed. We applied logit and probit models to explain the probability of a cost. Significant results were obtained were the electricity produced and program for minimum water discharges increase the probability of loss in electricity production, but favorable ecological conditions in the old river bed decrease the probability of a cost.

Keywords: hydropower, biodiversity, streams and rivers, restoration, old river bed, cost, survey data, econometrics, Sweden

#### 1. Introduction

Similar to many other countries, Sweden needs to comply with national and international targets on renewable energy and biodiversity provision. Hydropower is important for the

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited.

provision of renewable electricity production and accounts for approximately 47% of the total electricity production in the country [1]. Nuclear power is the second largest source of electricity and accounts for 34% of total energy production. Not only is hydropower a large source of electricity, but also acts a powerful regulatory device for the large fluctuations in demand and supply of electricity. Further, it is among the least expensive sources of energy as measured in SEK/kWh [2].

use inputs, such as labor and capital, at given prices to minimize costs for producing certain outputs. By applying the so-called duality theory a cost function can be derived which shows the relation between the output and production cost (e.g., [9]). The cost is then expressed as a function of given input prices, and output level. In our case, biodiversity improvement consti-

success of restoration, which can be measured as number of fish species or as a quality index, depends on ecological conditions at the site, Eil where <sup>l</sup> <sup>¼</sup> 1,.., <sup>m</sup> conditions such as length of the channel and natural water flow, and on restoration measures at the plant, Mig where <sup>g</sup> <sup>¼</sup> 1,.., h different restoration measures such as water discharges from the dam. The biodiversity

A crucial assumption in our analysis is that the plant manager minimizes total cost for

with a cost, Cig(Mig), and a maximum capacity of implementation, Mig. For example, there is a

large plant can have more expertise for implementing restoration measures than a small plant. On the other hand, a larger plant may give rise to more damages in the downstream waters, the mitigation of which requires costly restoration measures. The decision problem for the

,..,Mih; Ei<sup>1</sup>

<sup>¼</sup> <sup>Q</sup><sup>i</sup> (Mi<sup>1</sup>

maximum limit of water discharges into the channel. Plant size, Ki

g

<sup>ð</sup>Mi<sup>1</sup>

CigðMig; Ki

, ::, Mih; Ei<sup>1</sup>

Þ

By applying the so-called duality theory to Eq. (1) we can express the cost of restoration at the

Our main interest is to investigate the impact on costs of a marginal increase in the restoration

measures need to be implemented. In this case, there is a conflict between biodiversity restoration and electricity provision since resources that could be used for electricity production are used for biodiversity restoration. On the other hand, a non-positive effect would imply the opposite interpretation. As shown in Eqs. (1) and (2), a test of this hypothesis requires data, not

.

Unfortunately, the necessary data presented in Section 2 is not available for a sufficient number of plants. Therefore, a survey was distributed to hydropower plants with dried channels. It

, …, Eim, Mi<sup>1</sup>

where i ¼ 1,.., n sites of the hydropower plants. The level of the output, or

Biodiversity Restoration and Renewable Energy from Hydropower: Conflict or Synergy?

, …, Eim<sup>Þ</sup> <sup>≥</sup> <sup>Q</sup>�<sup>i</sup> and Mig <sup>≤</sup> Mig

, ::, Mih, Ki

. Each restoration measure is then associated

http://dx.doi.org/10.5772/intechopen.69134

, ecological conditions at the site, Eig, and

, increases since more of the restoration

Þ ð2Þ

, may also affect costs; a

ð1Þ

121

,.., Eim).

tutes the output Q<sup>i</sup>

at the site is then written as Q<sup>i</sup>

plant manager is then written as:

ambition, Q\*<sup>i</sup>

only on Ci

and Q\*<sup>i</sup>

3. Description of data

achieving a minimum level of biodiversity, Q\*<sup>i</sup>

MinC<sup>i</sup> <sup>¼</sup> <sup>X</sup>

Subject to Q<sup>i</sup>

plant as a function of the chosen restoration target Q\*<sup>i</sup>

, but also on Eil

the restoration measures, Mig, which is written as follows:

<sup>C</sup><sup>i</sup> <sup>¼</sup> Ci

. The hypothesis is that the cost, Ci

<sup>ð</sup>Q�<sup>i</sup> , E<sup>i</sup><sup>1</sup>

, Mig, and Ki

Mig

Establishments of hydropower plants change the hydrological conditions in the riverine landscape which affects habitats for animals and plants. Streams can be totally or partially dried and thereby destroying the habitats for several species and migration pathways for fish species. Although there is no national evidence on the extinction of species because of the hydropower production, the effects imply a degradation of habitats for red listed species [3], which goes against the national target of preserving biodiversity.

In order to mitigate these effects water power plants may be run with a release of water from the reservoir(s) into the downstream dry channel (the old natural river channel). However, this may only be achieved at a cost in terms of less electricity production and hence fulfillment of the target on renewable energy. This study investigates whether such a cost exists, and which factors contribute to the probability of its occurrence. To this end, we use the costminimization framework to derive testable hypotheses. Test are made with data from a survey on 76 hydropower plants in Sweden with questions on the existence of a cost in terms of negative impact on electricity production, the type of water release from reservoirs, and characteristics of the dried downstream channel and the plant. This data set was completed with official statistics on ecological status in the downstream segments. We use econometric methods to examine the impact of water discharges from the reservoir and other explanatory variables on electricity production. The dependent variable is a binary variable which equals 1 when electricity production is affected and 0 otherwise. We, therefore, use a probit model for the regression analysis, where we estimate how the explanatory variables affect the probability of losing electricity production.

There is a large body of literature on ecological effects of biodiversity restoration in freshwaters, such as wetland restoration (see reviews in Refs. [4, 5]). Despite this, the literature on the determination of costs of measures mitigating biodiversity degradation from hydropower plants is scant (e.g., [6–8]). The cost of restoration objects depends on the investment and management of the restoration measure as such, and on the ecological conditions at the site affecting the need and quality of restoration [5]. In our view, the main contribution of this study is the estimation of the explanatory power of ecological conditions and water release from reservoirs on the probability of a restoration cost in terms of reduction in electricity production.
